2023/06/04 16:16:58 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.9.0 (default, Nov 15 2020, 14:28:56) [GCC 7.3.0] CUDA available: True numpy_random_seed: 777789580 GPU 0,1,2,3,4,5,6,7: NVIDIA GeForce RTX 3090 CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 11.3, V11.3.109 GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0 PyTorch: 1.12.1+cu113 PyTorch compiling details: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.6.0 (Git Hash 52b5f107dd9cf10910aaa19cb47f3abf9b349815) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.3 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 - CuDNN 8.2 - Built with CuDNN 8.3.2 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.3.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.12.1, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, TorchVision: 0.13.1+cu102 OpenCV: 4.7.0 MMEngine: 0.7.3 Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None diff_rank_seed: False deterministic: False Distributed launcher: pytorch Distributed training: True GPU number: 32 ------------------------------------------------------------ 2023/06/04 16:16:59 - mmengine - INFO - Config: model = dict( type='Recognizer3D', backbone=dict( type='ResNet3dSlowOnly', depth=50, pretrained='https://download.pytorch.org/models/resnet50-11ad3fa6.pth', lateral=False, conv1_kernel=(1, 7, 7), conv1_stride_t=1, pool1_stride_t=1, inflate=(0, 0, 1, 1), norm_eval=False), cls_head=dict( type='I3DHead', in_channels=2048, num_classes=710, spatial_type='avg', dropout_ratio=0.5, average_clips='prob'), data_preprocessor=dict( type='ActionDataPreprocessor', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], format_shape='NCTHW')) default_scope = 'mmaction' default_hooks = dict( runtime_info=dict(type='RuntimeInfoHook'), timer=dict(type='IterTimerHook'), logger=dict(type='LoggerHook', interval=20, ignore_last=False), param_scheduler=dict(type='ParamSchedulerHook'), checkpoint=dict( type='CheckpointHook', interval=4, save_best='auto', max_keep_ckpts=3), sampler_seed=dict(type='DistSamplerSeedHook'), sync_buffers=dict(type='SyncBuffersHook')) env_cfg = dict( cudnn_benchmark=False, mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), dist_cfg=dict(backend='nccl')) log_processor = dict(type='LogProcessor', window_size=20, by_epoch=True) vis_backends = [dict(type='LocalVisBackend')] visualizer = dict( type='ActionVisualizer', vis_backends=[dict(type='LocalVisBackend')]) log_level = 'INFO' load_from = None resume = False dataset_type = 'VideoDataset' data_root = 'data/kinetics700/videos_train' data_root_val = 'data/kinetics700/videos_val' ann_file_train = 'data/kinetics700/kinetics700_train_list_videos.txt' ann_file_val = 'data/kinetics700/kinetics700_val_list_videos.txt' file_client_args = dict(io_backend='disk') train_pipeline = [ dict(type='DecordInit', io_backend='disk'), dict(type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ] val_pipeline = [ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ] test_pipeline = [ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ] train_dataloader = dict( batch_size=8, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='ConcatDataset', datasets=[ dict( type='VideoDataset', ann_file='data/kinetics710/k400_train_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_train'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ]), dict( type='VideoDataset', ann_file='data/kinetics710/k600_train_list_videos.txt', data_prefix=dict(video='data/kinetics600/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ]), dict( type='VideoDataset', ann_file='data/kinetics710/k700_train_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ]) ])) val_dataloader = dict( batch_size=8, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='ConcatDataset', datasets=[ dict( type='VideoDataset', ann_file='data/kinetics710/k400_val_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_val'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True), dict( type='VideoDataset', ann_file='data/kinetics710/k600_val_list_videos.txt', data_prefix=dict(video='data/kinetics600/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True), dict( type='VideoDataset', ann_file='data/kinetics710/k700_val_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True) ])) test_dataloader = dict( batch_size=8, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='ConcatDataset', datasets=[ dict( type='VideoDataset', ann_file='data/kinetics710/k400_val_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_val'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True), dict( type='VideoDataset', ann_file='data/kinetics710/k600_val_list_videos.txt', data_prefix=dict(video='data/kinetics600/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True), dict( type='VideoDataset', ann_file='data/kinetics710/k700_val_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True) ])) val_evaluator = dict(type='AccMetric') test_evaluator = dict(type='AccMetric') train_cfg = dict( type='EpochBasedTrainLoop', max_epochs=150, val_begin=1, val_interval=5) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [ dict(type='LinearLR', start_factor=0.1, by_epoch=True, begin=0, end=10), dict( type='MultiStepLR', begin=10, end=150, by_epoch=True, milestones=[90, 130], gamma=0.1) ] optim_wrapper = dict( optimizer=dict(type='SGD', lr=0.04, momentum=0.9, weight_decay=0.0001), clip_grad=dict(max_norm=40, norm_type=2)) auto_scale_lr = dict(enable=False, base_batch_size=256) k400_data_root = 'data/kinetics400/videos_train' k600_data_root = 'data/kinetics600/videos' k700_data_root = 'data/kinetics700/videos' k400_data_root_val = 'data/kinetics400/videos_val' k600_data_root_val = 'data/kinetics600/videos' k700_data_root_val = 'data/kinetics700/videos' k400_ann_file_train = 'data/kinetics710/k400_train_list_videos.txt' k600_ann_file_train = 'data/kinetics710/k600_train_list_videos.txt' k700_ann_file_train = 'data/kinetics710/k700_train_list_videos.txt' k400_ann_file_val = 'data/kinetics710/k400_val_list_videos.txt' k600_ann_file_val = 'data/kinetics710/k600_val_list_videos.txt' k700_ann_file_val = 'data/kinetics710/k700_val_list_videos.txt' k400_trainset = dict( type='VideoDataset', ann_file='data/kinetics710/k400_train_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_train'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict(type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ]) k600_trainset = dict( type='VideoDataset', ann_file='data/kinetics710/k600_train_list_videos.txt', data_prefix=dict(video='data/kinetics600/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict(type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ]) k700_trainset = dict( type='VideoDataset', ann_file='data/kinetics710/k700_train_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict(type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ]) k400_valset = dict( type='VideoDataset', ann_file='data/kinetics710/k400_val_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_val'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True) k600_valset = dict( type='VideoDataset', ann_file='data/kinetics710/k600_val_list_videos.txt', data_prefix=dict(video='data/kinetics600/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True) k700_valset = dict( type='VideoDataset', ann_file='data/kinetics710/k700_val_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True) k400_testset = dict( type='VideoDataset', ann_file='data/kinetics710/k400_val_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_val'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True) k600_testset = dict( type='VideoDataset', ann_file='data/kinetics710/k600_val_list_videos.txt', data_prefix=dict(video='data/kinetics600/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True) k700_testset = dict( type='VideoDataset', ann_file='data/kinetics710/k700_val_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True) k710_trainset = dict( type='ConcatDataset', datasets=[ dict( type='VideoDataset', ann_file='data/kinetics710/k400_train_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_train'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ]), dict( type='VideoDataset', ann_file='data/kinetics710/k600_train_list_videos.txt', data_prefix=dict(video='data/kinetics600/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ]), dict( type='VideoDataset', ann_file='data/kinetics710/k700_train_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='RandomResizedCrop'), dict(type='Resize', scale=(224, 224), keep_ratio=False), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ]) ], _delete_=True) k710_valset = dict( type='ConcatDataset', datasets=[ dict( type='VideoDataset', ann_file='data/kinetics710/k400_val_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_val'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True), dict( type='VideoDataset', ann_file='data/kinetics710/k600_val_list_videos.txt', data_prefix=dict(video='data/kinetics600/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True), dict( type='VideoDataset', ann_file='data/kinetics710/k700_val_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=1, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='CenterCrop', crop_size=224), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True) ], _delete_=True) k710_testset = dict( type='ConcatDataset', datasets=[ dict( type='VideoDataset', ann_file='data/kinetics710/k400_val_list_videos.txt', data_prefix=dict(video='data/kinetics400/videos_val'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True), dict( type='VideoDataset', ann_file='data/kinetics710/k600_val_list_videos.txt', data_prefix=dict(video='data/kinetics600/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True), dict( type='VideoDataset', ann_file='data/kinetics710/k700_val_list_videos.txt', data_prefix=dict(video='data/kinetics700/videos'), pipeline=[ dict(type='DecordInit', io_backend='disk'), dict( type='SampleFrames', clip_len=8, frame_interval=8, num_clips=10, test_mode=True), dict(type='DecordDecode'), dict(type='Resize', scale=(-1, 256)), dict(type='ThreeCrop', crop_size=256), dict(type='FormatShape', input_format='NCTHW'), dict(type='PackActionInputs') ], test_mode=True) ], _delete_=True) launcher = 'pytorch' work_dir = './work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb' randomness = dict(seed=None, diff_rank_seed=False, deterministic=False) 2023/06/04 16:17:01 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (BELOW_NORMAL) LoggerHook -------------------- before_train: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (VERY_LOW ) CheckpointHook -------------------- before_train_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (NORMAL ) DistSamplerSeedHook -------------------- before_train_iter: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook -------------------- after_train_iter: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- after_train_epoch: (NORMAL ) IterTimerHook (NORMAL ) SyncBuffersHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook (NORMAL ) SyncBuffersHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- after_train: (VERY_LOW ) CheckpointHook -------------------- before_test_epoch: (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- 2023/06/04 16:17:05 - mmengine - INFO - load model from: https://download.pytorch.org/models/resnet50-11ad3fa6.pth 2023/06/04 16:17:06 - mmengine - INFO - These parameters in the 2d checkpoint are not loaded: {'fc.bias', 'fc.weight'} Name of parameter - Initialization information backbone.conv1.conv.weight - torch.Size([64, 3, 1, 7, 7]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.conv1.bn.weight - torch.Size([64]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.conv1.bn.bias - torch.Size([64]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.0.conv1.conv.weight - torch.Size([64, 64, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.0.conv1.bn.weight - torch.Size([64]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.0.conv1.bn.bias - torch.Size([64]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.0.conv2.conv.weight - torch.Size([64, 64, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.0.conv2.bn.weight - torch.Size([64]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.0.conv2.bn.bias - torch.Size([64]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.0.conv3.conv.weight - torch.Size([256, 64, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.0.conv3.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.0.conv3.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.0.downsample.conv.weight - torch.Size([256, 64, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.0.downsample.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.0.downsample.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.1.conv1.conv.weight - torch.Size([64, 256, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.1.conv1.bn.weight - torch.Size([64]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.1.conv1.bn.bias - torch.Size([64]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.1.conv2.conv.weight - torch.Size([64, 64, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.1.conv2.bn.weight - torch.Size([64]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.1.conv2.bn.bias - torch.Size([64]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.1.conv3.conv.weight - torch.Size([256, 64, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.1.conv3.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.1.conv3.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.2.conv1.conv.weight - torch.Size([64, 256, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.2.conv1.bn.weight - torch.Size([64]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.2.conv1.bn.bias - torch.Size([64]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.2.conv2.conv.weight - torch.Size([64, 64, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.2.conv2.bn.weight - torch.Size([64]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.2.conv2.bn.bias - torch.Size([64]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.2.conv3.conv.weight - torch.Size([256, 64, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.2.conv3.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer1.2.conv3.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.0.conv1.conv.weight - torch.Size([128, 256, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.0.conv1.bn.weight - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.0.conv1.bn.bias - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.0.conv2.conv.weight - torch.Size([128, 128, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.0.conv2.bn.weight - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.0.conv2.bn.bias - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.0.conv3.conv.weight - torch.Size([512, 128, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.0.conv3.bn.weight - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.0.conv3.bn.bias - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.0.downsample.conv.weight - torch.Size([512, 256, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.0.downsample.bn.weight - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.0.downsample.bn.bias - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.1.conv1.conv.weight - torch.Size([128, 512, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.1.conv1.bn.weight - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.1.conv1.bn.bias - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.1.conv2.conv.weight - torch.Size([128, 128, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.1.conv2.bn.weight - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.1.conv2.bn.bias - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.1.conv3.conv.weight - torch.Size([512, 128, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.1.conv3.bn.weight - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.1.conv3.bn.bias - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.2.conv1.conv.weight - torch.Size([128, 512, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.2.conv1.bn.weight - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.2.conv1.bn.bias - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.2.conv2.conv.weight - torch.Size([128, 128, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.2.conv2.bn.weight - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.2.conv2.bn.bias - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.2.conv3.conv.weight - torch.Size([512, 128, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.2.conv3.bn.weight - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.2.conv3.bn.bias - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.3.conv1.conv.weight - torch.Size([128, 512, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.3.conv1.bn.weight - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.3.conv1.bn.bias - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.3.conv2.conv.weight - torch.Size([128, 128, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.3.conv2.bn.weight - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.3.conv2.bn.bias - torch.Size([128]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.3.conv3.conv.weight - torch.Size([512, 128, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.3.conv3.bn.weight - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer2.3.conv3.bn.bias - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.0.conv1.conv.weight - torch.Size([256, 512, 3, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.0.conv1.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.0.conv1.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.0.conv2.conv.weight - torch.Size([256, 256, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.0.conv2.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.0.conv2.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.0.conv3.conv.weight - torch.Size([1024, 256, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.0.conv3.bn.weight - torch.Size([1024]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.0.conv3.bn.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.0.downsample.conv.weight - torch.Size([1024, 512, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.0.downsample.bn.weight - torch.Size([1024]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.0.downsample.bn.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.1.conv1.conv.weight - torch.Size([256, 1024, 3, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.1.conv1.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.1.conv1.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.1.conv2.conv.weight - torch.Size([256, 256, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.1.conv2.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.1.conv2.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.1.conv3.conv.weight - torch.Size([1024, 256, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.1.conv3.bn.weight - torch.Size([1024]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.1.conv3.bn.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.2.conv1.conv.weight - torch.Size([256, 1024, 3, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.2.conv1.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.2.conv1.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.2.conv2.conv.weight - torch.Size([256, 256, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.2.conv2.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.2.conv2.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.2.conv3.conv.weight - torch.Size([1024, 256, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.2.conv3.bn.weight - torch.Size([1024]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.2.conv3.bn.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.3.conv1.conv.weight - torch.Size([256, 1024, 3, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.3.conv1.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.3.conv1.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.3.conv2.conv.weight - torch.Size([256, 256, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.3.conv2.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.3.conv2.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.3.conv3.conv.weight - torch.Size([1024, 256, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.3.conv3.bn.weight - torch.Size([1024]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.3.conv3.bn.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.4.conv1.conv.weight - torch.Size([256, 1024, 3, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.4.conv1.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.4.conv1.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.4.conv2.conv.weight - torch.Size([256, 256, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.4.conv2.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.4.conv2.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.4.conv3.conv.weight - torch.Size([1024, 256, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.4.conv3.bn.weight - torch.Size([1024]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.4.conv3.bn.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.5.conv1.conv.weight - torch.Size([256, 1024, 3, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.5.conv1.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.5.conv1.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.5.conv2.conv.weight - torch.Size([256, 256, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.5.conv2.bn.weight - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.5.conv2.bn.bias - torch.Size([256]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.5.conv3.conv.weight - torch.Size([1024, 256, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.5.conv3.bn.weight - torch.Size([1024]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer3.5.conv3.bn.bias - torch.Size([1024]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.0.conv1.conv.weight - torch.Size([512, 1024, 3, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.0.conv1.bn.weight - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.0.conv1.bn.bias - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.0.conv2.conv.weight - torch.Size([512, 512, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.0.conv2.bn.weight - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.0.conv2.bn.bias - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.0.conv3.conv.weight - torch.Size([2048, 512, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.0.conv3.bn.weight - torch.Size([2048]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.0.conv3.bn.bias - torch.Size([2048]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.0.downsample.conv.weight - torch.Size([2048, 1024, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.0.downsample.bn.weight - torch.Size([2048]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.0.downsample.bn.bias - torch.Size([2048]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.1.conv1.conv.weight - torch.Size([512, 2048, 3, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.1.conv1.bn.weight - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.1.conv1.bn.bias - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.1.conv2.conv.weight - torch.Size([512, 512, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.1.conv2.bn.weight - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.1.conv2.bn.bias - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.1.conv3.conv.weight - torch.Size([2048, 512, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.1.conv3.bn.weight - torch.Size([2048]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.1.conv3.bn.bias - torch.Size([2048]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.2.conv1.conv.weight - torch.Size([512, 2048, 3, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.2.conv1.bn.weight - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.2.conv1.bn.bias - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.2.conv2.conv.weight - torch.Size([512, 512, 1, 3, 3]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.2.conv2.bn.weight - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.2.conv2.bn.bias - torch.Size([512]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.2.conv3.conv.weight - torch.Size([2048, 512, 1, 1, 1]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.2.conv3.bn.weight - torch.Size([2048]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly backbone.layer4.2.conv3.bn.bias - torch.Size([2048]): Initialized by user-defined `init_weights` in ResNet3dSlowOnly cls_head.fc_cls.weight - torch.Size([710, 2048]): Initialized by user-defined `init_weights` in I3DHead cls_head.fc_cls.bias - torch.Size([710]): Initialized by user-defined `init_weights` in I3DHead 2023/06/04 16:17:06 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 2023/06/04 16:17:06 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 2023/06/04 16:17:06 - mmengine - INFO - Checkpoints will be saved to /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb. 2023/06/04 16:17:18 - mmengine - INFO - Epoch(train) [1][ 20/2569] lr: 4.0000e-03 eta: 2 days, 18:55:59 time: 0.6253 data_time: 0.1347 memory: 5828 grad_norm: 0.9461 loss: 6.5661 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5661 2023/06/04 16:17:23 - mmengine - INFO - Epoch(train) [1][ 40/2569] lr: 4.0000e-03 eta: 1 day, 23:16:58 time: 0.2582 data_time: 0.0075 memory: 5828 grad_norm: 0.8623 loss: 6.5541 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5541 2023/06/04 16:17:28 - mmengine - INFO - Epoch(train) [1][ 60/2569] lr: 4.0000e-03 eta: 1 day, 16:53:36 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 0.8548 loss: 6.5621 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 6.5621 2023/06/04 16:17:34 - mmengine - INFO - Epoch(train) [1][ 80/2569] lr: 4.0000e-03 eta: 1 day, 13:38:13 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 0.8666 loss: 6.5552 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5552 2023/06/04 16:17:39 - mmengine - INFO - Epoch(train) [1][ 100/2569] lr: 4.0000e-03 eta: 1 day, 11:49:43 time: 0.2673 data_time: 0.0075 memory: 5828 grad_norm: 0.9106 loss: 6.5242 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5242 2023/06/04 16:17:44 - mmengine - INFO - Epoch(train) [1][ 120/2569] lr: 4.0000e-03 eta: 1 day, 10:26:13 time: 0.2569 data_time: 0.0073 memory: 5828 grad_norm: 0.9946 loss: 6.5324 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5324 2023/06/04 16:17:50 - mmengine - INFO - Epoch(train) [1][ 140/2569] lr: 4.0000e-03 eta: 1 day, 9:35:08 time: 0.2662 data_time: 0.0072 memory: 5828 grad_norm: 1.1033 loss: 6.5118 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.5118 2023/06/04 16:17:55 - mmengine - INFO - Epoch(train) [1][ 160/2569] lr: 4.0000e-03 eta: 1 day, 8:59:14 time: 0.2693 data_time: 0.0069 memory: 5828 grad_norm: 1.1899 loss: 6.4876 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 6.4876 2023/06/04 16:18:00 - mmengine - INFO - Epoch(train) [1][ 180/2569] lr: 4.0000e-03 eta: 1 day, 8:23:22 time: 0.2582 data_time: 0.0077 memory: 5828 grad_norm: 1.2691 loss: 6.4779 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.4779 2023/06/04 16:18:05 - mmengine - INFO - Epoch(train) [1][ 200/2569] lr: 4.0000e-03 eta: 1 day, 8:02:03 time: 0.2697 data_time: 0.0069 memory: 5828 grad_norm: 1.3332 loss: 6.4450 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.4450 2023/06/04 16:18:11 - mmengine - INFO - Epoch(train) [1][ 220/2569] lr: 4.0000e-03 eta: 1 day, 7:44:23 time: 0.2693 data_time: 0.0077 memory: 5828 grad_norm: 1.4025 loss: 6.4344 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 6.4344 2023/06/04 16:18:16 - mmengine - INFO - Epoch(train) [1][ 240/2569] lr: 4.0000e-03 eta: 1 day, 7:27:13 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 1.4892 loss: 6.3992 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.3992 2023/06/04 16:18:22 - mmengine - INFO - Epoch(train) [1][ 260/2569] lr: 4.0000e-03 eta: 1 day, 7:14:34 time: 0.2686 data_time: 0.0074 memory: 5828 grad_norm: 1.5842 loss: 6.3507 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.3507 2023/06/04 16:18:27 - mmengine - INFO - Epoch(train) [1][ 280/2569] lr: 4.0000e-03 eta: 1 day, 7:01:57 time: 0.2648 data_time: 0.0076 memory: 5828 grad_norm: 1.6651 loss: 6.2313 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.2313 2023/06/04 16:18:32 - mmengine - INFO - Epoch(train) [1][ 300/2569] lr: 4.0000e-03 eta: 1 day, 6:48:56 time: 0.2599 data_time: 0.0072 memory: 5828 grad_norm: 1.7596 loss: 6.2768 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.2768 2023/06/04 16:18:37 - mmengine - INFO - Epoch(train) [1][ 320/2569] lr: 4.0000e-03 eta: 1 day, 6:42:16 time: 0.2717 data_time: 0.0070 memory: 5828 grad_norm: 1.8397 loss: 6.1691 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 6.1691 2023/06/04 16:18:43 - mmengine - INFO - Epoch(train) [1][ 340/2569] lr: 4.0000e-03 eta: 1 day, 6:34:55 time: 0.2678 data_time: 0.0072 memory: 5828 grad_norm: 1.9190 loss: 6.1080 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 6.1080 2023/06/04 16:18:48 - mmengine - INFO - Epoch(train) [1][ 360/2569] lr: 4.0000e-03 eta: 1 day, 6:27:06 time: 0.2643 data_time: 0.0085 memory: 5828 grad_norm: 2.0141 loss: 5.9950 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 5.9950 2023/06/04 16:18:54 - mmengine - INFO - Epoch(train) [1][ 380/2569] lr: 4.0000e-03 eta: 1 day, 6:22:26 time: 0.2712 data_time: 0.0070 memory: 5828 grad_norm: 2.0885 loss: 5.9513 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.9513 2023/06/04 16:18:59 - mmengine - INFO - Epoch(train) [1][ 400/2569] lr: 4.0000e-03 eta: 1 day, 6:16:27 time: 0.2657 data_time: 0.0079 memory: 5828 grad_norm: 2.1598 loss: 6.0212 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 6.0212 2023/06/04 16:19:04 - mmengine - INFO - Epoch(train) [1][ 420/2569] lr: 4.0000e-03 eta: 1 day, 6:09:13 time: 0.2598 data_time: 0.0078 memory: 5828 grad_norm: 2.2445 loss: 5.7693 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 5.7693 2023/06/04 16:19:09 - mmengine - INFO - Epoch(train) [1][ 440/2569] lr: 4.0000e-03 eta: 1 day, 6:05:57 time: 0.2711 data_time: 0.0072 memory: 5828 grad_norm: 2.2902 loss: 5.8570 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.8570 2023/06/04 16:19:15 - mmengine - INFO - Epoch(train) [1][ 460/2569] lr: 4.0000e-03 eta: 1 day, 6:01:23 time: 0.2655 data_time: 0.0074 memory: 5828 grad_norm: 2.3767 loss: 5.8162 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 5.8162 2023/06/04 16:19:20 - mmengine - INFO - Epoch(train) [1][ 480/2569] lr: 4.0000e-03 eta: 1 day, 5:57:01 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 2.4633 loss: 5.5637 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 5.5637 2023/06/04 16:19:25 - mmengine - INFO - Epoch(train) [1][ 500/2569] lr: 4.0000e-03 eta: 1 day, 5:51:27 time: 0.2588 data_time: 0.0075 memory: 5828 grad_norm: 2.4986 loss: 5.6213 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.6213 2023/06/04 16:19:31 - mmengine - INFO - Epoch(train) [1][ 520/2569] lr: 4.0000e-03 eta: 1 day, 5:49:14 time: 0.2707 data_time: 0.0077 memory: 5828 grad_norm: 2.5767 loss: 5.7584 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.7584 2023/06/04 16:19:36 - mmengine - INFO - Epoch(train) [1][ 540/2569] lr: 4.0000e-03 eta: 1 day, 5:46:44 time: 0.2688 data_time: 0.0076 memory: 5828 grad_norm: 2.6162 loss: 5.4669 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 5.4669 2023/06/04 16:19:42 - mmengine - INFO - Epoch(train) [1][ 560/2569] lr: 4.0000e-03 eta: 1 day, 5:46:11 time: 0.2766 data_time: 0.0073 memory: 5828 grad_norm: 2.6654 loss: 5.5233 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.5233 2023/06/04 16:19:47 - mmengine - INFO - Epoch(train) [1][ 580/2569] lr: 4.0000e-03 eta: 1 day, 5:43:28 time: 0.2667 data_time: 0.0088 memory: 5828 grad_norm: 2.7301 loss: 5.3205 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 5.3205 2023/06/04 16:19:52 - mmengine - INFO - Epoch(train) [1][ 600/2569] lr: 4.0000e-03 eta: 1 day, 5:41:02 time: 0.2672 data_time: 0.0078 memory: 5828 grad_norm: 2.8023 loss: 5.3357 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 5.3357 2023/06/04 16:19:58 - mmengine - INFO - Epoch(train) [1][ 620/2569] lr: 4.0000e-03 eta: 1 day, 5:38:40 time: 0.2668 data_time: 0.0085 memory: 5828 grad_norm: 2.8361 loss: 5.1883 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 5.1883 2023/06/04 16:20:03 - mmengine - INFO - Epoch(train) [1][ 640/2569] lr: 4.0000e-03 eta: 1 day, 5:36:20 time: 0.2662 data_time: 0.0072 memory: 5828 grad_norm: 2.8822 loss: 5.3032 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 5.3032 2023/06/04 16:20:08 - mmengine - INFO - Epoch(train) [1][ 660/2569] lr: 4.0000e-03 eta: 1 day, 5:34:46 time: 0.2695 data_time: 0.0076 memory: 5828 grad_norm: 2.9286 loss: 5.1364 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 5.1364 2023/06/04 16:20:14 - mmengine - INFO - Epoch(train) [1][ 680/2569] lr: 4.0000e-03 eta: 1 day, 5:32:38 time: 0.2660 data_time: 0.0069 memory: 5828 grad_norm: 2.9599 loss: 5.1072 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 5.1072 2023/06/04 16:20:19 - mmengine - INFO - Epoch(train) [1][ 700/2569] lr: 4.0000e-03 eta: 1 day, 5:30:39 time: 0.2661 data_time: 0.0075 memory: 5828 grad_norm: 2.9996 loss: 5.1594 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 5.1594 2023/06/04 16:20:24 - mmengine - INFO - Epoch(train) [1][ 720/2569] lr: 4.0000e-03 eta: 1 day, 5:28:06 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 3.0031 loss: 5.0631 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 5.0631 2023/06/04 16:20:29 - mmengine - INFO - Epoch(train) [1][ 740/2569] lr: 4.0000e-03 eta: 1 day, 5:25:32 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 3.0469 loss: 5.0875 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 5.0875 2023/06/04 16:20:35 - mmengine - INFO - Epoch(train) [1][ 760/2569] lr: 4.0000e-03 eta: 1 day, 5:24:16 time: 0.2685 data_time: 0.0077 memory: 5828 grad_norm: 3.1111 loss: 5.1437 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 5.1437 2023/06/04 16:20:40 - mmengine - INFO - Epoch(train) [1][ 780/2569] lr: 4.0000e-03 eta: 1 day, 5:21:33 time: 0.2592 data_time: 0.0076 memory: 5828 grad_norm: 3.1412 loss: 4.9238 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 4.9238 2023/06/04 16:20:45 - mmengine - INFO - Epoch(train) [1][ 800/2569] lr: 4.0000e-03 eta: 1 day, 5:20:36 time: 0.2695 data_time: 0.0074 memory: 5828 grad_norm: 3.1597 loss: 4.8696 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.8696 2023/06/04 16:20:51 - mmengine - INFO - Epoch(train) [1][ 820/2569] lr: 4.0000e-03 eta: 1 day, 5:18:00 time: 0.2587 data_time: 0.0074 memory: 5828 grad_norm: 3.1661 loss: 4.8445 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.8445 2023/06/04 16:20:56 - mmengine - INFO - Epoch(train) [1][ 840/2569] lr: 4.0000e-03 eta: 1 day, 5:16:26 time: 0.2647 data_time: 0.0076 memory: 5828 grad_norm: 3.1851 loss: 4.8922 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.8922 2023/06/04 16:21:01 - mmengine - INFO - Epoch(train) [1][ 860/2569] lr: 4.0000e-03 eta: 1 day, 5:15:08 time: 0.2659 data_time: 0.0070 memory: 5828 grad_norm: 3.2229 loss: 4.7845 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 4.7845 2023/06/04 16:21:07 - mmengine - INFO - Epoch(train) [1][ 880/2569] lr: 4.0000e-03 eta: 1 day, 5:14:40 time: 0.2713 data_time: 0.0075 memory: 5828 grad_norm: 3.2627 loss: 4.7134 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 4.7134 2023/06/04 16:21:12 - mmengine - INFO - Epoch(train) [1][ 900/2569] lr: 4.0000e-03 eta: 1 day, 5:13:47 time: 0.2683 data_time: 0.0078 memory: 5828 grad_norm: 3.2742 loss: 4.8194 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 4.8194 2023/06/04 16:21:17 - mmengine - INFO - Epoch(train) [1][ 920/2569] lr: 4.0000e-03 eta: 1 day, 5:12:19 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.3008 loss: 4.7443 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.7443 2023/06/04 16:21:23 - mmengine - INFO - Epoch(train) [1][ 940/2569] lr: 4.0000e-03 eta: 1 day, 5:13:02 time: 0.2794 data_time: 0.0074 memory: 5828 grad_norm: 3.3019 loss: 4.8477 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 4.8477 2023/06/04 16:21:28 - mmengine - INFO - Epoch(train) [1][ 960/2569] lr: 4.0000e-03 eta: 1 day, 5:11:11 time: 0.2604 data_time: 0.0074 memory: 5828 grad_norm: 3.3129 loss: 4.7278 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 4.7278 2023/06/04 16:21:33 - mmengine - INFO - Epoch(train) [1][ 980/2569] lr: 4.0000e-03 eta: 1 day, 5:11:22 time: 0.2754 data_time: 0.0072 memory: 5828 grad_norm: 3.3453 loss: 4.5084 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.5084 2023/06/04 16:21:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 16:21:39 - mmengine - INFO - Epoch(train) [1][1000/2569] lr: 4.0000e-03 eta: 1 day, 5:10:53 time: 0.2704 data_time: 0.0072 memory: 5828 grad_norm: 3.3496 loss: 4.5927 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.5927 2023/06/04 16:21:44 - mmengine - INFO - Epoch(train) [1][1020/2569] lr: 4.0000e-03 eta: 1 day, 5:10:37 time: 0.2719 data_time: 0.0078 memory: 5828 grad_norm: 3.3611 loss: 4.6299 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.6299 2023/06/04 16:21:50 - mmengine - INFO - Epoch(train) [1][1040/2569] lr: 4.0000e-03 eta: 1 day, 5:09:21 time: 0.2637 data_time: 0.0074 memory: 5828 grad_norm: 3.4150 loss: 4.6554 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.6554 2023/06/04 16:21:55 - mmengine - INFO - Epoch(train) [1][1060/2569] lr: 4.0000e-03 eta: 1 day, 5:09:19 time: 0.2735 data_time: 0.0080 memory: 5828 grad_norm: 3.4275 loss: 4.3951 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.3951 2023/06/04 16:22:00 - mmengine - INFO - Epoch(train) [1][1080/2569] lr: 4.0000e-03 eta: 1 day, 5:07:34 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 3.4425 loss: 4.7030 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 4.7030 2023/06/04 16:22:06 - mmengine - INFO - Epoch(train) [1][1100/2569] lr: 4.0000e-03 eta: 1 day, 5:06:43 time: 0.2663 data_time: 0.0073 memory: 5828 grad_norm: 3.4413 loss: 4.6707 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 4.6707 2023/06/04 16:22:11 - mmengine - INFO - Epoch(train) [1][1120/2569] lr: 4.0000e-03 eta: 1 day, 5:05:05 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 3.4407 loss: 4.2081 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 4.2081 2023/06/04 16:22:16 - mmengine - INFO - Epoch(train) [1][1140/2569] lr: 4.0000e-03 eta: 1 day, 5:04:46 time: 0.2706 data_time: 0.0076 memory: 5828 grad_norm: 3.4762 loss: 4.5749 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 4.5749 2023/06/04 16:22:21 - mmengine - INFO - Epoch(train) [1][1160/2569] lr: 4.0000e-03 eta: 1 day, 5:03:30 time: 0.2618 data_time: 0.0079 memory: 5828 grad_norm: 3.4808 loss: 4.4238 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 4.4238 2023/06/04 16:22:27 - mmengine - INFO - Epoch(train) [1][1180/2569] lr: 4.0000e-03 eta: 1 day, 5:04:03 time: 0.2782 data_time: 0.0076 memory: 5828 grad_norm: 3.5291 loss: 4.4083 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 4.4083 2023/06/04 16:22:32 - mmengine - INFO - Epoch(train) [1][1200/2569] lr: 4.0000e-03 eta: 1 day, 5:03:42 time: 0.2700 data_time: 0.0074 memory: 5828 grad_norm: 3.5118 loss: 4.6981 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.6981 2023/06/04 16:22:38 - mmengine - INFO - Epoch(train) [1][1220/2569] lr: 4.0000e-03 eta: 1 day, 5:02:11 time: 0.2587 data_time: 0.0078 memory: 5828 grad_norm: 3.5060 loss: 4.3420 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.3420 2023/06/04 16:22:43 - mmengine - INFO - Epoch(train) [1][1240/2569] lr: 4.0000e-03 eta: 1 day, 5:01:28 time: 0.2661 data_time: 0.0074 memory: 5828 grad_norm: 3.5300 loss: 4.2252 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.2252 2023/06/04 16:22:48 - mmengine - INFO - Epoch(train) [1][1260/2569] lr: 4.0000e-03 eta: 1 day, 5:00:29 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 3.5353 loss: 4.4173 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.4173 2023/06/04 16:22:53 - mmengine - INFO - Epoch(train) [1][1280/2569] lr: 4.0000e-03 eta: 1 day, 4:59:05 time: 0.2588 data_time: 0.0075 memory: 5828 grad_norm: 3.5429 loss: 4.3340 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.3340 2023/06/04 16:22:59 - mmengine - INFO - Epoch(train) [1][1300/2569] lr: 4.0000e-03 eta: 1 day, 4:58:50 time: 0.2700 data_time: 0.0076 memory: 5828 grad_norm: 3.5343 loss: 4.6423 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.6423 2023/06/04 16:23:04 - mmengine - INFO - Epoch(train) [1][1320/2569] lr: 4.0000e-03 eta: 1 day, 4:58:25 time: 0.2683 data_time: 0.0076 memory: 5828 grad_norm: 3.5148 loss: 4.1885 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 4.1885 2023/06/04 16:23:09 - mmengine - INFO - Epoch(train) [1][1340/2569] lr: 4.0000e-03 eta: 1 day, 4:58:06 time: 0.2693 data_time: 0.0080 memory: 5828 grad_norm: 3.5674 loss: 4.0748 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 4.0748 2023/06/04 16:23:15 - mmengine - INFO - Epoch(train) [1][1360/2569] lr: 4.0000e-03 eta: 1 day, 4:58:02 time: 0.2719 data_time: 0.0074 memory: 5828 grad_norm: 3.6232 loss: 4.1329 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.1329 2023/06/04 16:23:20 - mmengine - INFO - Epoch(train) [1][1380/2569] lr: 4.0000e-03 eta: 1 day, 4:57:07 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 3.6341 loss: 4.3064 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.3064 2023/06/04 16:23:25 - mmengine - INFO - Epoch(train) [1][1400/2569] lr: 4.0000e-03 eta: 1 day, 4:56:30 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 3.6221 loss: 4.2588 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 4.2588 2023/06/04 16:23:31 - mmengine - INFO - Epoch(train) [1][1420/2569] lr: 4.0000e-03 eta: 1 day, 4:55:16 time: 0.2587 data_time: 0.0079 memory: 5828 grad_norm: 3.6358 loss: 4.5457 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 4.5457 2023/06/04 16:23:36 - mmengine - INFO - Epoch(train) [1][1440/2569] lr: 4.0000e-03 eta: 1 day, 4:54:32 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 3.6434 loss: 4.6133 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 4.6133 2023/06/04 16:23:41 - mmengine - INFO - Epoch(train) [1][1460/2569] lr: 4.0000e-03 eta: 1 day, 4:53:55 time: 0.2650 data_time: 0.0074 memory: 5828 grad_norm: 3.6443 loss: 4.1782 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.1782 2023/06/04 16:23:46 - mmengine - INFO - Epoch(train) [1][1480/2569] lr: 4.0000e-03 eta: 1 day, 4:53:02 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 3.6644 loss: 4.3676 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 4.3676 2023/06/04 16:23:52 - mmengine - INFO - Epoch(train) [1][1500/2569] lr: 4.0000e-03 eta: 1 day, 4:52:06 time: 0.2609 data_time: 0.0073 memory: 5828 grad_norm: 3.6605 loss: 4.2215 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.2215 2023/06/04 16:23:57 - mmengine - INFO - Epoch(train) [1][1520/2569] lr: 4.0000e-03 eta: 1 day, 4:51:26 time: 0.2640 data_time: 0.0075 memory: 5828 grad_norm: 3.6693 loss: 4.5361 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.5361 2023/06/04 16:24:02 - mmengine - INFO - Epoch(train) [1][1540/2569] lr: 4.0000e-03 eta: 1 day, 4:51:16 time: 0.2698 data_time: 0.0071 memory: 5828 grad_norm: 3.6962 loss: 4.2038 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.2038 2023/06/04 16:24:08 - mmengine - INFO - Epoch(train) [1][1560/2569] lr: 4.0000e-03 eta: 1 day, 4:51:15 time: 0.2716 data_time: 0.0077 memory: 5828 grad_norm: 3.6582 loss: 4.1825 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 4.1825 2023/06/04 16:24:13 - mmengine - INFO - Epoch(train) [1][1580/2569] lr: 4.0000e-03 eta: 1 day, 4:50:41 time: 0.2647 data_time: 0.0076 memory: 5828 grad_norm: 3.6670 loss: 4.2609 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 4.2609 2023/06/04 16:24:19 - mmengine - INFO - Epoch(train) [1][1600/2569] lr: 4.0000e-03 eta: 1 day, 4:51:43 time: 0.2847 data_time: 0.0085 memory: 5828 grad_norm: 3.6646 loss: 3.9737 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.9737 2023/06/04 16:24:24 - mmengine - INFO - Epoch(train) [1][1620/2569] lr: 4.0000e-03 eta: 1 day, 4:50:44 time: 0.2594 data_time: 0.0078 memory: 5828 grad_norm: 3.7204 loss: 4.1888 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 4.1888 2023/06/04 16:24:29 - mmengine - INFO - Epoch(train) [1][1640/2569] lr: 4.0000e-03 eta: 1 day, 4:50:43 time: 0.2716 data_time: 0.0080 memory: 5828 grad_norm: 3.7661 loss: 4.1142 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.1142 2023/06/04 16:24:35 - mmengine - INFO - Epoch(train) [1][1660/2569] lr: 4.0000e-03 eta: 1 day, 4:50:12 time: 0.2650 data_time: 0.0078 memory: 5828 grad_norm: 3.7262 loss: 4.3015 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 4.3015 2023/06/04 16:24:40 - mmengine - INFO - Epoch(train) [1][1680/2569] lr: 4.0000e-03 eta: 1 day, 4:50:08 time: 0.2708 data_time: 0.0072 memory: 5828 grad_norm: 3.7315 loss: 4.2842 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.2842 2023/06/04 16:24:46 - mmengine - INFO - Epoch(train) [1][1700/2569] lr: 4.0000e-03 eta: 1 day, 4:50:07 time: 0.2716 data_time: 0.0077 memory: 5828 grad_norm: 3.7139 loss: 3.8743 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.8743 2023/06/04 16:24:51 - mmengine - INFO - Epoch(train) [1][1720/2569] lr: 4.0000e-03 eta: 1 day, 4:50:31 time: 0.2772 data_time: 0.0073 memory: 5828 grad_norm: 3.7470 loss: 3.9007 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.9007 2023/06/04 16:24:56 - mmengine - INFO - Epoch(train) [1][1740/2569] lr: 4.0000e-03 eta: 1 day, 4:49:47 time: 0.2618 data_time: 0.0076 memory: 5828 grad_norm: 3.7414 loss: 4.0099 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.0099 2023/06/04 16:25:02 - mmengine - INFO - Epoch(train) [1][1760/2569] lr: 4.0000e-03 eta: 1 day, 4:50:15 time: 0.2782 data_time: 0.0071 memory: 5828 grad_norm: 3.7279 loss: 4.2568 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 4.2568 2023/06/04 16:25:07 - mmengine - INFO - Epoch(train) [1][1780/2569] lr: 4.0000e-03 eta: 1 day, 4:49:41 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.7585 loss: 3.9911 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 3.9911 2023/06/04 16:25:13 - mmengine - INFO - Epoch(train) [1][1800/2569] lr: 4.0000e-03 eta: 1 day, 4:50:12 time: 0.2789 data_time: 0.0078 memory: 5828 grad_norm: 3.7301 loss: 4.1565 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.1565 2023/06/04 16:25:18 - mmengine - INFO - Epoch(train) [1][1820/2569] lr: 4.0000e-03 eta: 1 day, 4:49:59 time: 0.2689 data_time: 0.0072 memory: 5828 grad_norm: 3.7281 loss: 4.1593 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 4.1593 2023/06/04 16:25:24 - mmengine - INFO - Epoch(train) [1][1840/2569] lr: 4.0000e-03 eta: 1 day, 4:49:43 time: 0.2681 data_time: 0.0080 memory: 5828 grad_norm: 3.7564 loss: 4.1028 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 4.1028 2023/06/04 16:25:29 - mmengine - INFO - Epoch(train) [1][1860/2569] lr: 4.0000e-03 eta: 1 day, 4:49:44 time: 0.2721 data_time: 0.0073 memory: 5828 grad_norm: 3.7512 loss: 3.7212 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.7212 2023/06/04 16:25:34 - mmengine - INFO - Epoch(train) [1][1880/2569] lr: 4.0000e-03 eta: 1 day, 4:49:12 time: 0.2642 data_time: 0.0079 memory: 5828 grad_norm: 3.7394 loss: 4.1018 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.1018 2023/06/04 16:25:39 - mmengine - INFO - Epoch(train) [1][1900/2569] lr: 4.0000e-03 eta: 1 day, 4:48:20 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 3.7645 loss: 4.0846 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.0846 2023/06/04 16:25:45 - mmengine - INFO - Epoch(train) [1][1920/2569] lr: 4.0000e-03 eta: 1 day, 4:47:34 time: 0.2603 data_time: 0.0075 memory: 5828 grad_norm: 3.7886 loss: 4.0567 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 4.0567 2023/06/04 16:25:50 - mmengine - INFO - Epoch(train) [1][1940/2569] lr: 4.0000e-03 eta: 1 day, 4:47:23 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 3.7945 loss: 3.8891 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.8891 2023/06/04 16:25:55 - mmengine - INFO - Epoch(train) [1][1960/2569] lr: 4.0000e-03 eta: 1 day, 4:46:55 time: 0.2645 data_time: 0.0078 memory: 5828 grad_norm: 3.7896 loss: 4.2268 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.2268 2023/06/04 16:26:00 - mmengine - INFO - Epoch(train) [1][1980/2569] lr: 4.0000e-03 eta: 1 day, 4:46:06 time: 0.2590 data_time: 0.0078 memory: 5828 grad_norm: 3.8054 loss: 4.0704 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 4.0704 2023/06/04 16:26:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 16:26:06 - mmengine - INFO - Epoch(train) [1][2000/2569] lr: 4.0000e-03 eta: 1 day, 4:45:43 time: 0.2656 data_time: 0.0082 memory: 5828 grad_norm: 3.7756 loss: 4.0747 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 4.0747 2023/06/04 16:26:11 - mmengine - INFO - Epoch(train) [1][2020/2569] lr: 4.0000e-03 eta: 1 day, 4:45:03 time: 0.2612 data_time: 0.0077 memory: 5828 grad_norm: 3.8073 loss: 3.6051 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 3.6051 2023/06/04 16:26:16 - mmengine - INFO - Epoch(train) [1][2040/2569] lr: 4.0000e-03 eta: 1 day, 4:44:24 time: 0.2611 data_time: 0.0080 memory: 5828 grad_norm: 3.8007 loss: 4.2482 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 4.2482 2023/06/04 16:26:21 - mmengine - INFO - Epoch(train) [1][2060/2569] lr: 4.0000e-03 eta: 1 day, 4:43:39 time: 0.2592 data_time: 0.0072 memory: 5828 grad_norm: 3.8319 loss: 4.0239 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 4.0239 2023/06/04 16:26:27 - mmengine - INFO - Epoch(train) [1][2080/2569] lr: 4.0000e-03 eta: 1 day, 4:43:08 time: 0.2627 data_time: 0.0083 memory: 5828 grad_norm: 3.8250 loss: 4.0612 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 4.0612 2023/06/04 16:26:32 - mmengine - INFO - Epoch(train) [1][2100/2569] lr: 4.0000e-03 eta: 1 day, 4:42:26 time: 0.2597 data_time: 0.0073 memory: 5828 grad_norm: 3.8386 loss: 3.5861 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.5861 2023/06/04 16:26:37 - mmengine - INFO - Epoch(train) [1][2120/2569] lr: 4.0000e-03 eta: 1 day, 4:42:04 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 3.8853 loss: 3.8500 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.8500 2023/06/04 16:26:42 - mmengine - INFO - Epoch(train) [1][2140/2569] lr: 4.0000e-03 eta: 1 day, 4:41:18 time: 0.2585 data_time: 0.0071 memory: 5828 grad_norm: 3.8703 loss: 3.8944 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.8944 2023/06/04 16:26:48 - mmengine - INFO - Epoch(train) [1][2160/2569] lr: 4.0000e-03 eta: 1 day, 4:40:52 time: 0.2637 data_time: 0.0075 memory: 5828 grad_norm: 3.8909 loss: 3.9427 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.9427 2023/06/04 16:26:53 - mmengine - INFO - Epoch(train) [1][2180/2569] lr: 4.0000e-03 eta: 1 day, 4:40:17 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 3.8678 loss: 3.9284 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.9284 2023/06/04 16:26:58 - mmengine - INFO - Epoch(train) [1][2200/2569] lr: 4.0000e-03 eta: 1 day, 4:39:55 time: 0.2646 data_time: 0.0074 memory: 5828 grad_norm: 3.8327 loss: 4.0072 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 4.0072 2023/06/04 16:27:03 - mmengine - INFO - Epoch(train) [1][2220/2569] lr: 4.0000e-03 eta: 1 day, 4:39:38 time: 0.2661 data_time: 0.0079 memory: 5828 grad_norm: 3.8549 loss: 4.1955 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 4.1955 2023/06/04 16:27:09 - mmengine - INFO - Epoch(train) [1][2240/2569] lr: 4.0000e-03 eta: 1 day, 4:39:19 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 3.9172 loss: 3.8758 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.8758 2023/06/04 16:27:14 - mmengine - INFO - Epoch(train) [1][2260/2569] lr: 4.0000e-03 eta: 1 day, 4:38:44 time: 0.2606 data_time: 0.0083 memory: 5828 grad_norm: 3.8621 loss: 3.8723 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.8723 2023/06/04 16:27:19 - mmengine - INFO - Epoch(train) [1][2280/2569] lr: 4.0000e-03 eta: 1 day, 4:38:52 time: 0.2732 data_time: 0.0071 memory: 5828 grad_norm: 3.8731 loss: 3.7018 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.7018 2023/06/04 16:27:25 - mmengine - INFO - Epoch(train) [1][2300/2569] lr: 4.0000e-03 eta: 1 day, 4:38:28 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.8616 loss: 3.6339 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.6339 2023/06/04 16:27:30 - mmengine - INFO - Epoch(train) [1][2320/2569] lr: 4.0000e-03 eta: 1 day, 4:37:52 time: 0.2599 data_time: 0.0074 memory: 5828 grad_norm: 3.8558 loss: 4.1384 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 4.1384 2023/06/04 16:27:35 - mmengine - INFO - Epoch(train) [1][2340/2569] lr: 4.0000e-03 eta: 1 day, 4:38:09 time: 0.2759 data_time: 0.0083 memory: 5828 grad_norm: 3.8754 loss: 3.7840 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.7840 2023/06/04 16:27:41 - mmengine - INFO - Epoch(train) [1][2360/2569] lr: 4.0000e-03 eta: 1 day, 4:37:35 time: 0.2603 data_time: 0.0077 memory: 5828 grad_norm: 3.9342 loss: 3.8636 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.8636 2023/06/04 16:27:46 - mmengine - INFO - Epoch(train) [1][2380/2569] lr: 4.0000e-03 eta: 1 day, 4:37:14 time: 0.2642 data_time: 0.0077 memory: 5828 grad_norm: 3.9046 loss: 3.7290 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.7290 2023/06/04 16:27:51 - mmengine - INFO - Epoch(train) [1][2400/2569] lr: 4.0000e-03 eta: 1 day, 4:36:50 time: 0.2633 data_time: 0.0079 memory: 5828 grad_norm: 3.9300 loss: 3.8402 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.8402 2023/06/04 16:27:57 - mmengine - INFO - Epoch(train) [1][2420/2569] lr: 4.0000e-03 eta: 1 day, 4:36:38 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 3.9585 loss: 3.8517 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.8517 2023/06/04 16:28:02 - mmengine - INFO - Epoch(train) [1][2440/2569] lr: 4.0000e-03 eta: 1 day, 4:36:19 time: 0.2646 data_time: 0.0076 memory: 5828 grad_norm: 3.9198 loss: 4.0131 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 4.0131 2023/06/04 16:28:07 - mmengine - INFO - Epoch(train) [1][2460/2569] lr: 4.0000e-03 eta: 1 day, 4:35:47 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 3.8903 loss: 3.8289 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.8289 2023/06/04 16:28:12 - mmengine - INFO - Epoch(train) [1][2480/2569] lr: 4.0000e-03 eta: 1 day, 4:35:44 time: 0.2696 data_time: 0.0075 memory: 5828 grad_norm: 3.9237 loss: 3.9545 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.9545 2023/06/04 16:28:18 - mmengine - INFO - Epoch(train) [1][2500/2569] lr: 4.0000e-03 eta: 1 day, 4:35:42 time: 0.2702 data_time: 0.0072 memory: 5828 grad_norm: 3.9051 loss: 3.8136 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.8136 2023/06/04 16:28:23 - mmengine - INFO - Epoch(train) [1][2520/2569] lr: 4.0000e-03 eta: 1 day, 4:35:23 time: 0.2642 data_time: 0.0078 memory: 5828 grad_norm: 3.9086 loss: 3.9134 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.9134 2023/06/04 16:28:29 - mmengine - INFO - Epoch(train) [1][2540/2569] lr: 4.0000e-03 eta: 1 day, 4:35:21 time: 0.2702 data_time: 0.0077 memory: 5828 grad_norm: 3.9111 loss: 3.8144 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.8144 2023/06/04 16:28:34 - mmengine - INFO - Epoch(train) [1][2560/2569] lr: 4.0000e-03 eta: 1 day, 4:34:35 time: 0.2550 data_time: 0.0073 memory: 5828 grad_norm: 3.9689 loss: 3.6701 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.6701 2023/06/04 16:28:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 16:28:36 - mmengine - INFO - Epoch(train) [1][2569/2569] lr: 4.0000e-03 eta: 1 day, 4:33:58 time: 0.2474 data_time: 0.0062 memory: 5828 grad_norm: 3.9837 loss: 3.4724 top1_acc: 0.0000 top5_acc: 0.6667 loss_cls: 3.4724 2023/06/04 16:28:43 - mmengine - INFO - Epoch(train) [2][ 20/2569] lr: 8.0000e-03 eta: 1 day, 4:37:22 time: 0.3395 data_time: 0.0518 memory: 5828 grad_norm: 3.9651 loss: 3.8967 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 3.8967 2023/06/04 16:28:48 - mmengine - INFO - Epoch(train) [2][ 40/2569] lr: 8.0000e-03 eta: 1 day, 4:37:34 time: 0.2753 data_time: 0.0075 memory: 5828 grad_norm: 3.9635 loss: 3.7779 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.7779 2023/06/04 16:28:53 - mmengine - INFO - Epoch(train) [2][ 60/2569] lr: 8.0000e-03 eta: 1 day, 4:37:00 time: 0.2594 data_time: 0.0074 memory: 5828 grad_norm: 3.9850 loss: 3.8848 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.8848 2023/06/04 16:28:59 - mmengine - INFO - Epoch(train) [2][ 80/2569] lr: 8.0000e-03 eta: 1 day, 4:37:12 time: 0.2749 data_time: 0.0074 memory: 5828 grad_norm: 3.9619 loss: 3.8768 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.8768 2023/06/04 16:29:04 - mmengine - INFO - Epoch(train) [2][ 100/2569] lr: 8.0000e-03 eta: 1 day, 4:36:41 time: 0.2604 data_time: 0.0080 memory: 5828 grad_norm: 3.9207 loss: 3.5517 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.5517 2023/06/04 16:29:09 - mmengine - INFO - Epoch(train) [2][ 120/2569] lr: 8.0000e-03 eta: 1 day, 4:36:07 time: 0.2593 data_time: 0.0070 memory: 5828 grad_norm: 3.9262 loss: 3.9474 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.9474 2023/06/04 16:29:15 - mmengine - INFO - Epoch(train) [2][ 140/2569] lr: 8.0000e-03 eta: 1 day, 4:35:59 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 3.9555 loss: 3.7446 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.7446 2023/06/04 16:29:20 - mmengine - INFO - Epoch(train) [2][ 160/2569] lr: 8.0000e-03 eta: 1 day, 4:35:32 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 3.9411 loss: 3.8690 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.8690 2023/06/04 16:29:25 - mmengine - INFO - Epoch(train) [2][ 180/2569] lr: 8.0000e-03 eta: 1 day, 4:35:10 time: 0.2630 data_time: 0.0078 memory: 5828 grad_norm: 3.9572 loss: 3.6443 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.6443 2023/06/04 16:29:30 - mmengine - INFO - Epoch(train) [2][ 200/2569] lr: 8.0000e-03 eta: 1 day, 4:34:47 time: 0.2624 data_time: 0.0077 memory: 5828 grad_norm: 3.9864 loss: 3.8454 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 3.8454 2023/06/04 16:29:36 - mmengine - INFO - Epoch(train) [2][ 220/2569] lr: 8.0000e-03 eta: 1 day, 4:34:46 time: 0.2708 data_time: 0.0076 memory: 5828 grad_norm: 3.9003 loss: 3.7083 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.7083 2023/06/04 16:29:41 - mmengine - INFO - Epoch(train) [2][ 240/2569] lr: 8.0000e-03 eta: 1 day, 4:34:42 time: 0.2694 data_time: 0.0069 memory: 5828 grad_norm: 3.9701 loss: 3.7084 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.7084 2023/06/04 16:29:46 - mmengine - INFO - Epoch(train) [2][ 260/2569] lr: 8.0000e-03 eta: 1 day, 4:34:26 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 3.9483 loss: 3.6323 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.6323 2023/06/04 16:29:52 - mmengine - INFO - Epoch(train) [2][ 280/2569] lr: 8.0000e-03 eta: 1 day, 4:34:08 time: 0.2640 data_time: 0.0078 memory: 5828 grad_norm: 3.9285 loss: 4.0080 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 4.0080 2023/06/04 16:29:57 - mmengine - INFO - Epoch(train) [2][ 300/2569] lr: 8.0000e-03 eta: 1 day, 4:33:55 time: 0.2661 data_time: 0.0074 memory: 5828 grad_norm: 3.8759 loss: 3.5748 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.5748 2023/06/04 16:30:02 - mmengine - INFO - Epoch(train) [2][ 320/2569] lr: 8.0000e-03 eta: 1 day, 4:33:54 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 3.9268 loss: 3.8272 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.8272 2023/06/04 16:30:08 - mmengine - INFO - Epoch(train) [2][ 340/2569] lr: 8.0000e-03 eta: 1 day, 4:33:27 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 3.9258 loss: 4.0544 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 4.0544 2023/06/04 16:30:13 - mmengine - INFO - Epoch(train) [2][ 360/2569] lr: 8.0000e-03 eta: 1 day, 4:33:08 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 3.9180 loss: 3.7293 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.7293 2023/06/04 16:30:18 - mmengine - INFO - Epoch(train) [2][ 380/2569] lr: 8.0000e-03 eta: 1 day, 4:33:12 time: 0.2722 data_time: 0.0085 memory: 5828 grad_norm: 3.9491 loss: 3.8454 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.8454 2023/06/04 16:30:24 - mmengine - INFO - Epoch(train) [2][ 400/2569] lr: 8.0000e-03 eta: 1 day, 4:33:02 time: 0.2669 data_time: 0.0081 memory: 5828 grad_norm: 4.0069 loss: 3.7235 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.7235 2023/06/04 16:30:29 - mmengine - INFO - Epoch(train) [2][ 420/2569] lr: 8.0000e-03 eta: 1 day, 4:32:45 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.9500 loss: 3.5117 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.5117 2023/06/04 16:30:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 16:30:34 - mmengine - INFO - Epoch(train) [2][ 440/2569] lr: 8.0000e-03 eta: 1 day, 4:32:18 time: 0.2601 data_time: 0.0075 memory: 5828 grad_norm: 3.9686 loss: 3.5752 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.5752 2023/06/04 16:30:40 - mmengine - INFO - Epoch(train) [2][ 460/2569] lr: 8.0000e-03 eta: 1 day, 4:32:31 time: 0.2759 data_time: 0.0081 memory: 5828 grad_norm: 3.9746 loss: 3.4384 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.4384 2023/06/04 16:30:45 - mmengine - INFO - Epoch(train) [2][ 480/2569] lr: 8.0000e-03 eta: 1 day, 4:32:14 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 3.9491 loss: 3.5130 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.5130 2023/06/04 16:30:50 - mmengine - INFO - Epoch(train) [2][ 500/2569] lr: 8.0000e-03 eta: 1 day, 4:31:59 time: 0.2648 data_time: 0.0075 memory: 5828 grad_norm: 4.0135 loss: 3.5958 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.5958 2023/06/04 16:30:56 - mmengine - INFO - Epoch(train) [2][ 520/2569] lr: 8.0000e-03 eta: 1 day, 4:31:45 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 3.9849 loss: 3.6601 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.6601 2023/06/04 16:31:01 - mmengine - INFO - Epoch(train) [2][ 540/2569] lr: 8.0000e-03 eta: 1 day, 4:31:40 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 4.0376 loss: 3.6861 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.6861 2023/06/04 16:31:06 - mmengine - INFO - Epoch(train) [2][ 560/2569] lr: 8.0000e-03 eta: 1 day, 4:31:24 time: 0.2647 data_time: 0.0081 memory: 5828 grad_norm: 3.9749 loss: 3.6298 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.6298 2023/06/04 16:31:12 - mmengine - INFO - Epoch(train) [2][ 580/2569] lr: 8.0000e-03 eta: 1 day, 4:31:37 time: 0.2759 data_time: 0.0078 memory: 5828 grad_norm: 4.0136 loss: 3.6277 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 3.6277 2023/06/04 16:31:17 - mmengine - INFO - Epoch(train) [2][ 600/2569] lr: 8.0000e-03 eta: 1 day, 4:31:15 time: 0.2619 data_time: 0.0080 memory: 5828 grad_norm: 4.0170 loss: 3.6930 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.6930 2023/06/04 16:31:23 - mmengine - INFO - Epoch(train) [2][ 620/2569] lr: 8.0000e-03 eta: 1 day, 4:31:25 time: 0.2754 data_time: 0.0073 memory: 5828 grad_norm: 3.9662 loss: 3.8411 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.8411 2023/06/04 16:31:28 - mmengine - INFO - Epoch(train) [2][ 640/2569] lr: 8.0000e-03 eta: 1 day, 4:31:18 time: 0.2680 data_time: 0.0075 memory: 5828 grad_norm: 3.9176 loss: 3.6754 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.6754 2023/06/04 16:31:33 - mmengine - INFO - Epoch(train) [2][ 660/2569] lr: 8.0000e-03 eta: 1 day, 4:31:18 time: 0.2709 data_time: 0.0076 memory: 5828 grad_norm: 3.9760 loss: 3.6898 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.6898 2023/06/04 16:31:39 - mmengine - INFO - Epoch(train) [2][ 680/2569] lr: 8.0000e-03 eta: 1 day, 4:31:21 time: 0.2721 data_time: 0.0079 memory: 5828 grad_norm: 3.9685 loss: 3.7931 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 3.7931 2023/06/04 16:31:44 - mmengine - INFO - Epoch(train) [2][ 700/2569] lr: 8.0000e-03 eta: 1 day, 4:31:23 time: 0.2719 data_time: 0.0074 memory: 5828 grad_norm: 3.9395 loss: 3.6203 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.6203 2023/06/04 16:31:50 - mmengine - INFO - Epoch(train) [2][ 720/2569] lr: 8.0000e-03 eta: 1 day, 4:31:22 time: 0.2707 data_time: 0.0073 memory: 5828 grad_norm: 3.9751 loss: 3.7452 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 3.7452 2023/06/04 16:31:55 - mmengine - INFO - Epoch(train) [2][ 740/2569] lr: 8.0000e-03 eta: 1 day, 4:31:19 time: 0.2697 data_time: 0.0074 memory: 5828 grad_norm: 3.9849 loss: 3.5096 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.5096 2023/06/04 16:32:00 - mmengine - INFO - Epoch(train) [2][ 760/2569] lr: 8.0000e-03 eta: 1 day, 4:31:17 time: 0.2701 data_time: 0.0075 memory: 5828 grad_norm: 3.9689 loss: 3.6703 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.6703 2023/06/04 16:32:06 - mmengine - INFO - Epoch(train) [2][ 780/2569] lr: 8.0000e-03 eta: 1 day, 4:30:59 time: 0.2635 data_time: 0.0072 memory: 5828 grad_norm: 4.0051 loss: 3.4825 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.4825 2023/06/04 16:32:11 - mmengine - INFO - Epoch(train) [2][ 800/2569] lr: 8.0000e-03 eta: 1 day, 4:30:56 time: 0.2696 data_time: 0.0076 memory: 5828 grad_norm: 4.0740 loss: 3.5169 top1_acc: 0.0000 top5_acc: 0.7500 loss_cls: 3.5169 2023/06/04 16:32:16 - mmengine - INFO - Epoch(train) [2][ 820/2569] lr: 8.0000e-03 eta: 1 day, 4:30:29 time: 0.2593 data_time: 0.0083 memory: 5828 grad_norm: 4.0840 loss: 3.7752 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.7752 2023/06/04 16:32:22 - mmengine - INFO - Epoch(train) [2][ 840/2569] lr: 8.0000e-03 eta: 1 day, 4:30:14 time: 0.2646 data_time: 0.0076 memory: 5828 grad_norm: 3.9701 loss: 3.4176 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.4176 2023/06/04 16:32:27 - mmengine - INFO - Epoch(train) [2][ 860/2569] lr: 8.0000e-03 eta: 1 day, 4:29:49 time: 0.2597 data_time: 0.0076 memory: 5828 grad_norm: 3.9961 loss: 3.2296 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.2296 2023/06/04 16:32:32 - mmengine - INFO - Epoch(train) [2][ 880/2569] lr: 8.0000e-03 eta: 1 day, 4:30:05 time: 0.2781 data_time: 0.0073 memory: 5828 grad_norm: 4.0003 loss: 3.4744 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.4744 2023/06/04 16:32:38 - mmengine - INFO - Epoch(train) [2][ 900/2569] lr: 8.0000e-03 eta: 1 day, 4:29:50 time: 0.2642 data_time: 0.0077 memory: 5828 grad_norm: 4.0732 loss: 3.6333 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.6333 2023/06/04 16:32:43 - mmengine - INFO - Epoch(train) [2][ 920/2569] lr: 8.0000e-03 eta: 1 day, 4:29:40 time: 0.2669 data_time: 0.0079 memory: 5828 grad_norm: 4.0139 loss: 3.5543 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.5543 2023/06/04 16:32:48 - mmengine - INFO - Epoch(train) [2][ 940/2569] lr: 8.0000e-03 eta: 1 day, 4:29:39 time: 0.2705 data_time: 0.0075 memory: 5828 grad_norm: 3.9964 loss: 3.5716 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.5716 2023/06/04 16:32:54 - mmengine - INFO - Epoch(train) [2][ 960/2569] lr: 8.0000e-03 eta: 1 day, 4:29:26 time: 0.2651 data_time: 0.0076 memory: 5828 grad_norm: 3.9760 loss: 3.5798 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.5798 2023/06/04 16:32:59 - mmengine - INFO - Epoch(train) [2][ 980/2569] lr: 8.0000e-03 eta: 1 day, 4:29:06 time: 0.2617 data_time: 0.0076 memory: 5828 grad_norm: 4.0310 loss: 3.4640 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.4640 2023/06/04 16:33:04 - mmengine - INFO - Epoch(train) [2][1000/2569] lr: 8.0000e-03 eta: 1 day, 4:28:49 time: 0.2634 data_time: 0.0076 memory: 5828 grad_norm: 3.9786 loss: 3.2409 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.2409 2023/06/04 16:33:09 - mmengine - INFO - Epoch(train) [2][1020/2569] lr: 8.0000e-03 eta: 1 day, 4:28:26 time: 0.2600 data_time: 0.0073 memory: 5828 grad_norm: 3.9715 loss: 3.3180 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 3.3180 2023/06/04 16:33:15 - mmengine - INFO - Epoch(train) [2][1040/2569] lr: 8.0000e-03 eta: 1 day, 4:28:22 time: 0.2694 data_time: 0.0078 memory: 5828 grad_norm: 4.0161 loss: 3.6414 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 3.6414 2023/06/04 16:33:20 - mmengine - INFO - Epoch(train) [2][1060/2569] lr: 8.0000e-03 eta: 1 day, 4:28:21 time: 0.2703 data_time: 0.0076 memory: 5828 grad_norm: 4.0083 loss: 3.4427 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.4427 2023/06/04 16:33:25 - mmengine - INFO - Epoch(train) [2][1080/2569] lr: 8.0000e-03 eta: 1 day, 4:28:06 time: 0.2643 data_time: 0.0077 memory: 5828 grad_norm: 4.0283 loss: 3.0437 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0437 2023/06/04 16:33:31 - mmengine - INFO - Epoch(train) [2][1100/2569] lr: 8.0000e-03 eta: 1 day, 4:28:06 time: 0.2708 data_time: 0.0072 memory: 5828 grad_norm: 3.9891 loss: 3.5883 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.5883 2023/06/04 16:33:36 - mmengine - INFO - Epoch(train) [2][1120/2569] lr: 8.0000e-03 eta: 1 day, 4:27:55 time: 0.2657 data_time: 0.0073 memory: 5828 grad_norm: 4.0308 loss: 3.6409 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.6409 2023/06/04 16:33:42 - mmengine - INFO - Epoch(train) [2][1140/2569] lr: 8.0000e-03 eta: 1 day, 4:28:00 time: 0.2739 data_time: 0.0075 memory: 5828 grad_norm: 4.0161 loss: 3.2588 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.2588 2023/06/04 16:33:47 - mmengine - INFO - Epoch(train) [2][1160/2569] lr: 8.0000e-03 eta: 1 day, 4:27:43 time: 0.2629 data_time: 0.0070 memory: 5828 grad_norm: 3.9993 loss: 3.2800 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.2800 2023/06/04 16:33:52 - mmengine - INFO - Epoch(train) [2][1180/2569] lr: 8.0000e-03 eta: 1 day, 4:27:50 time: 0.2746 data_time: 0.0073 memory: 5828 grad_norm: 4.0046 loss: 3.5585 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.5585 2023/06/04 16:33:58 - mmengine - INFO - Epoch(train) [2][1200/2569] lr: 8.0000e-03 eta: 1 day, 4:27:48 time: 0.2698 data_time: 0.0074 memory: 5828 grad_norm: 4.0157 loss: 3.6174 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.6174 2023/06/04 16:34:03 - mmengine - INFO - Epoch(train) [2][1220/2569] lr: 8.0000e-03 eta: 1 day, 4:27:33 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 4.1057 loss: 3.7302 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.7302 2023/06/04 16:34:08 - mmengine - INFO - Epoch(train) [2][1240/2569] lr: 8.0000e-03 eta: 1 day, 4:27:24 time: 0.2670 data_time: 0.0076 memory: 5828 grad_norm: 4.0285 loss: 3.3166 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.3166 2023/06/04 16:34:14 - mmengine - INFO - Epoch(train) [2][1260/2569] lr: 8.0000e-03 eta: 1 day, 4:27:09 time: 0.2636 data_time: 0.0078 memory: 5828 grad_norm: 4.0115 loss: 3.4187 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.4187 2023/06/04 16:34:19 - mmengine - INFO - Epoch(train) [2][1280/2569] lr: 8.0000e-03 eta: 1 day, 4:27:02 time: 0.2676 data_time: 0.0076 memory: 5828 grad_norm: 4.0192 loss: 3.2583 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.2583 2023/06/04 16:34:24 - mmengine - INFO - Epoch(train) [2][1300/2569] lr: 8.0000e-03 eta: 1 day, 4:26:57 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 4.0471 loss: 3.3519 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.3519 2023/06/04 16:34:30 - mmengine - INFO - Epoch(train) [2][1320/2569] lr: 8.0000e-03 eta: 1 day, 4:26:47 time: 0.2657 data_time: 0.0084 memory: 5828 grad_norm: 4.0463 loss: 3.5562 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.5562 2023/06/04 16:34:35 - mmengine - INFO - Epoch(train) [2][1340/2569] lr: 8.0000e-03 eta: 1 day, 4:26:44 time: 0.2697 data_time: 0.0085 memory: 5828 grad_norm: 4.0281 loss: 3.3482 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.3482 2023/06/04 16:34:40 - mmengine - INFO - Epoch(train) [2][1360/2569] lr: 8.0000e-03 eta: 1 day, 4:26:36 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 3.9997 loss: 3.2218 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.2218 2023/06/04 16:34:46 - mmengine - INFO - Epoch(train) [2][1380/2569] lr: 8.0000e-03 eta: 1 day, 4:26:16 time: 0.2607 data_time: 0.0074 memory: 5828 grad_norm: 4.0733 loss: 3.4581 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.4581 2023/06/04 16:34:51 - mmengine - INFO - Epoch(train) [2][1400/2569] lr: 8.0000e-03 eta: 1 day, 4:26:16 time: 0.2713 data_time: 0.0076 memory: 5828 grad_norm: 4.0559 loss: 3.5190 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.5190 2023/06/04 16:34:56 - mmengine - INFO - Epoch(train) [2][1420/2569] lr: 8.0000e-03 eta: 1 day, 4:25:55 time: 0.2600 data_time: 0.0079 memory: 5828 grad_norm: 4.0056 loss: 3.3931 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.3931 2023/06/04 16:34:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 16:35:02 - mmengine - INFO - Epoch(train) [2][1440/2569] lr: 8.0000e-03 eta: 1 day, 4:26:02 time: 0.2751 data_time: 0.0073 memory: 5828 grad_norm: 4.0819 loss: 3.2809 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2809 2023/06/04 16:35:07 - mmengine - INFO - Epoch(train) [2][1460/2569] lr: 8.0000e-03 eta: 1 day, 4:25:42 time: 0.2607 data_time: 0.0075 memory: 5828 grad_norm: 4.0504 loss: 3.3530 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.3530 2023/06/04 16:35:12 - mmengine - INFO - Epoch(train) [2][1480/2569] lr: 8.0000e-03 eta: 1 day, 4:25:49 time: 0.2747 data_time: 0.0077 memory: 5828 grad_norm: 3.9794 loss: 3.1477 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1477 2023/06/04 16:35:18 - mmengine - INFO - Epoch(train) [2][1500/2569] lr: 8.0000e-03 eta: 1 day, 4:25:29 time: 0.2608 data_time: 0.0079 memory: 5828 grad_norm: 4.0648 loss: 3.3514 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.3514 2023/06/04 16:35:23 - mmengine - INFO - Epoch(train) [2][1520/2569] lr: 8.0000e-03 eta: 1 day, 4:25:27 time: 0.2703 data_time: 0.0078 memory: 5828 grad_norm: 4.1033 loss: 3.4247 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.4247 2023/06/04 16:35:28 - mmengine - INFO - Epoch(train) [2][1540/2569] lr: 8.0000e-03 eta: 1 day, 4:25:15 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 4.0537 loss: 3.2121 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2121 2023/06/04 16:35:34 - mmengine - INFO - Epoch(train) [2][1560/2569] lr: 8.0000e-03 eta: 1 day, 4:24:52 time: 0.2588 data_time: 0.0078 memory: 5828 grad_norm: 4.0576 loss: 3.3509 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.3509 2023/06/04 16:35:39 - mmengine - INFO - Epoch(train) [2][1580/2569] lr: 8.0000e-03 eta: 1 day, 4:24:52 time: 0.2713 data_time: 0.0078 memory: 5828 grad_norm: 4.0818 loss: 3.6117 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.6117 2023/06/04 16:35:44 - mmengine - INFO - Epoch(train) [2][1600/2569] lr: 8.0000e-03 eta: 1 day, 4:24:49 time: 0.2695 data_time: 0.0076 memory: 5828 grad_norm: 4.0709 loss: 3.5998 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.5998 2023/06/04 16:35:50 - mmengine - INFO - Epoch(train) [2][1620/2569] lr: 8.0000e-03 eta: 1 day, 4:24:41 time: 0.2668 data_time: 0.0075 memory: 5828 grad_norm: 4.0577 loss: 3.3737 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.3737 2023/06/04 16:35:55 - mmengine - INFO - Epoch(train) [2][1640/2569] lr: 8.0000e-03 eta: 1 day, 4:24:36 time: 0.2685 data_time: 0.0078 memory: 5828 grad_norm: 4.0155 loss: 3.3594 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.3594 2023/06/04 16:36:00 - mmengine - INFO - Epoch(train) [2][1660/2569] lr: 8.0000e-03 eta: 1 day, 4:24:19 time: 0.2618 data_time: 0.0082 memory: 5828 grad_norm: 4.0662 loss: 3.7278 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.7278 2023/06/04 16:36:06 - mmengine - INFO - Epoch(train) [2][1680/2569] lr: 8.0000e-03 eta: 1 day, 4:23:58 time: 0.2599 data_time: 0.0076 memory: 5828 grad_norm: 3.9991 loss: 3.1258 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1258 2023/06/04 16:36:11 - mmengine - INFO - Epoch(train) [2][1700/2569] lr: 8.0000e-03 eta: 1 day, 4:23:40 time: 0.2612 data_time: 0.0081 memory: 5828 grad_norm: 4.0591 loss: 3.2158 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.2158 2023/06/04 16:36:16 - mmengine - INFO - Epoch(train) [2][1720/2569] lr: 8.0000e-03 eta: 1 day, 4:23:23 time: 0.2614 data_time: 0.0077 memory: 5828 grad_norm: 4.0612 loss: 3.0696 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0696 2023/06/04 16:36:21 - mmengine - INFO - Epoch(train) [2][1740/2569] lr: 8.0000e-03 eta: 1 day, 4:23:04 time: 0.2608 data_time: 0.0077 memory: 5828 grad_norm: 4.0942 loss: 3.0298 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0298 2023/06/04 16:36:27 - mmengine - INFO - Epoch(train) [2][1760/2569] lr: 8.0000e-03 eta: 1 day, 4:22:54 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 4.1099 loss: 3.3207 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.3207 2023/06/04 16:36:32 - mmengine - INFO - Epoch(train) [2][1780/2569] lr: 8.0000e-03 eta: 1 day, 4:22:45 time: 0.2662 data_time: 0.0070 memory: 5828 grad_norm: 4.0262 loss: 3.2367 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 3.2367 2023/06/04 16:36:37 - mmengine - INFO - Epoch(train) [2][1800/2569] lr: 8.0000e-03 eta: 1 day, 4:22:40 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 4.0453 loss: 3.4354 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.4354 2023/06/04 16:36:42 - mmengine - INFO - Epoch(train) [2][1820/2569] lr: 8.0000e-03 eta: 1 day, 4:22:28 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 4.0628 loss: 3.1823 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1823 2023/06/04 16:36:48 - mmengine - INFO - Epoch(train) [2][1840/2569] lr: 8.0000e-03 eta: 1 day, 4:22:44 time: 0.2809 data_time: 0.0072 memory: 5828 grad_norm: 4.1141 loss: 3.2468 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.2468 2023/06/04 16:36:53 - mmengine - INFO - Epoch(train) [2][1860/2569] lr: 8.0000e-03 eta: 1 day, 4:22:31 time: 0.2634 data_time: 0.0078 memory: 5828 grad_norm: 4.0981 loss: 3.5596 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.5596 2023/06/04 16:36:59 - mmengine - INFO - Epoch(train) [2][1880/2569] lr: 8.0000e-03 eta: 1 day, 4:22:19 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 4.0743 loss: 3.6044 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 3.6044 2023/06/04 16:37:04 - mmengine - INFO - Epoch(train) [2][1900/2569] lr: 8.0000e-03 eta: 1 day, 4:22:00 time: 0.2597 data_time: 0.0080 memory: 5828 grad_norm: 4.0949 loss: 3.4560 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.4560 2023/06/04 16:37:09 - mmengine - INFO - Epoch(train) [2][1920/2569] lr: 8.0000e-03 eta: 1 day, 4:21:56 time: 0.2693 data_time: 0.0071 memory: 5828 grad_norm: 4.0404 loss: 3.1403 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1403 2023/06/04 16:37:14 - mmengine - INFO - Epoch(train) [2][1940/2569] lr: 8.0000e-03 eta: 1 day, 4:21:38 time: 0.2606 data_time: 0.0074 memory: 5828 grad_norm: 4.0338 loss: 3.0954 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0954 2023/06/04 16:37:20 - mmengine - INFO - Epoch(train) [2][1960/2569] lr: 8.0000e-03 eta: 1 day, 4:21:51 time: 0.2788 data_time: 0.0073 memory: 5828 grad_norm: 3.9826 loss: 3.0491 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.0491 2023/06/04 16:37:25 - mmengine - INFO - Epoch(train) [2][1980/2569] lr: 8.0000e-03 eta: 1 day, 4:21:36 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 4.0541 loss: 3.6123 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.6123 2023/06/04 16:37:31 - mmengine - INFO - Epoch(train) [2][2000/2569] lr: 8.0000e-03 eta: 1 day, 4:21:20 time: 0.2613 data_time: 0.0079 memory: 5828 grad_norm: 4.0781 loss: 3.2416 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.2416 2023/06/04 16:37:36 - mmengine - INFO - Epoch(train) [2][2020/2569] lr: 8.0000e-03 eta: 1 day, 4:21:20 time: 0.2714 data_time: 0.0080 memory: 5828 grad_norm: 4.0771 loss: 3.0607 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0607 2023/06/04 16:37:41 - mmengine - INFO - Epoch(train) [2][2040/2569] lr: 8.0000e-03 eta: 1 day, 4:21:12 time: 0.2665 data_time: 0.0076 memory: 5828 grad_norm: 4.0476 loss: 3.0842 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0842 2023/06/04 16:37:47 - mmengine - INFO - Epoch(train) [2][2060/2569] lr: 8.0000e-03 eta: 1 day, 4:21:12 time: 0.2713 data_time: 0.0075 memory: 5828 grad_norm: 4.0832 loss: 3.2984 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.2984 2023/06/04 16:37:52 - mmengine - INFO - Epoch(train) [2][2080/2569] lr: 8.0000e-03 eta: 1 day, 4:21:02 time: 0.2655 data_time: 0.0074 memory: 5828 grad_norm: 4.0633 loss: 3.2774 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2774 2023/06/04 16:37:57 - mmengine - INFO - Epoch(train) [2][2100/2569] lr: 8.0000e-03 eta: 1 day, 4:21:05 time: 0.2732 data_time: 0.0073 memory: 5828 grad_norm: 4.0529 loss: 3.3824 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.3824 2023/06/04 16:38:03 - mmengine - INFO - Epoch(train) [2][2120/2569] lr: 8.0000e-03 eta: 1 day, 4:20:48 time: 0.2611 data_time: 0.0079 memory: 5828 grad_norm: 4.0431 loss: 3.1294 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1294 2023/06/04 16:38:08 - mmengine - INFO - Epoch(train) [2][2140/2569] lr: 8.0000e-03 eta: 1 day, 4:20:44 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 4.0889 loss: 3.1155 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1155 2023/06/04 16:38:13 - mmengine - INFO - Epoch(train) [2][2160/2569] lr: 8.0000e-03 eta: 1 day, 4:20:25 time: 0.2595 data_time: 0.0082 memory: 5828 grad_norm: 4.0441 loss: 3.3668 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 3.3668 2023/06/04 16:38:19 - mmengine - INFO - Epoch(train) [2][2180/2569] lr: 8.0000e-03 eta: 1 day, 4:20:15 time: 0.2657 data_time: 0.0078 memory: 5828 grad_norm: 4.0275 loss: 3.2179 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.2179 2023/06/04 16:38:24 - mmengine - INFO - Epoch(train) [2][2200/2569] lr: 8.0000e-03 eta: 1 day, 4:20:05 time: 0.2648 data_time: 0.0070 memory: 5828 grad_norm: 4.0108 loss: 3.0301 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0301 2023/06/04 16:38:29 - mmengine - INFO - Epoch(train) [2][2220/2569] lr: 8.0000e-03 eta: 1 day, 4:20:14 time: 0.2774 data_time: 0.0072 memory: 5828 grad_norm: 4.0807 loss: 3.1750 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.1750 2023/06/04 16:38:35 - mmengine - INFO - Epoch(train) [2][2240/2569] lr: 8.0000e-03 eta: 1 day, 4:19:58 time: 0.2611 data_time: 0.0079 memory: 5828 grad_norm: 4.0870 loss: 3.3398 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.3398 2023/06/04 16:38:40 - mmengine - INFO - Epoch(train) [2][2260/2569] lr: 8.0000e-03 eta: 1 day, 4:19:42 time: 0.2610 data_time: 0.0080 memory: 5828 grad_norm: 4.1170 loss: 3.2083 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 3.2083 2023/06/04 16:38:45 - mmengine - INFO - Epoch(train) [2][2280/2569] lr: 8.0000e-03 eta: 1 day, 4:19:30 time: 0.2638 data_time: 0.0076 memory: 5828 grad_norm: 4.0716 loss: 3.2410 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.2410 2023/06/04 16:38:50 - mmengine - INFO - Epoch(train) [2][2300/2569] lr: 8.0000e-03 eta: 1 day, 4:19:19 time: 0.2645 data_time: 0.0077 memory: 5828 grad_norm: 4.1038 loss: 3.2022 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2022 2023/06/04 16:38:56 - mmengine - INFO - Epoch(train) [2][2320/2569] lr: 8.0000e-03 eta: 1 day, 4:19:10 time: 0.2657 data_time: 0.0078 memory: 5828 grad_norm: 4.0914 loss: 3.1109 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.1109 2023/06/04 16:39:01 - mmengine - INFO - Epoch(train) [2][2340/2569] lr: 8.0000e-03 eta: 1 day, 4:19:09 time: 0.2708 data_time: 0.0075 memory: 5828 grad_norm: 4.1215 loss: 3.2670 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 3.2670 2023/06/04 16:39:07 - mmengine - INFO - Epoch(train) [2][2360/2569] lr: 8.0000e-03 eta: 1 day, 4:19:11 time: 0.2727 data_time: 0.0074 memory: 5828 grad_norm: 4.0634 loss: 3.1317 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1317 2023/06/04 16:39:12 - mmengine - INFO - Epoch(train) [2][2380/2569] lr: 8.0000e-03 eta: 1 day, 4:19:00 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 4.1230 loss: 3.2793 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.2793 2023/06/04 16:39:17 - mmengine - INFO - Epoch(train) [2][2400/2569] lr: 8.0000e-03 eta: 1 day, 4:19:07 time: 0.2757 data_time: 0.0076 memory: 5828 grad_norm: 4.1249 loss: 3.3986 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 3.3986 2023/06/04 16:39:23 - mmengine - INFO - Epoch(train) [2][2420/2569] lr: 8.0000e-03 eta: 1 day, 4:18:56 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 4.1253 loss: 3.2433 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2433 2023/06/04 16:39:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 16:39:28 - mmengine - INFO - Epoch(train) [2][2440/2569] lr: 8.0000e-03 eta: 1 day, 4:18:53 time: 0.2695 data_time: 0.0075 memory: 5828 grad_norm: 4.0219 loss: 3.2848 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.2848 2023/06/04 16:39:33 - mmengine - INFO - Epoch(train) [2][2460/2569] lr: 8.0000e-03 eta: 1 day, 4:18:48 time: 0.2680 data_time: 0.0074 memory: 5828 grad_norm: 4.0478 loss: 3.0210 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0210 2023/06/04 16:39:39 - mmengine - INFO - Epoch(train) [2][2480/2569] lr: 8.0000e-03 eta: 1 day, 4:18:45 time: 0.2700 data_time: 0.0077 memory: 5828 grad_norm: 4.0572 loss: 3.3054 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.3054 2023/06/04 16:39:44 - mmengine - INFO - Epoch(train) [2][2500/2569] lr: 8.0000e-03 eta: 1 day, 4:18:53 time: 0.2764 data_time: 0.0069 memory: 5828 grad_norm: 4.0960 loss: 3.3253 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 3.3253 2023/06/04 16:39:50 - mmengine - INFO - Epoch(train) [2][2520/2569] lr: 8.0000e-03 eta: 1 day, 4:18:52 time: 0.2711 data_time: 0.0075 memory: 5828 grad_norm: 4.0774 loss: 3.0919 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0919 2023/06/04 16:39:55 - mmengine - INFO - Epoch(train) [2][2540/2569] lr: 8.0000e-03 eta: 1 day, 4:18:50 time: 0.2707 data_time: 0.0077 memory: 5828 grad_norm: 4.0914 loss: 3.2624 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.2624 2023/06/04 16:40:00 - mmengine - INFO - Epoch(train) [2][2560/2569] lr: 8.0000e-03 eta: 1 day, 4:18:27 time: 0.2559 data_time: 0.0078 memory: 5828 grad_norm: 4.0464 loss: 3.3634 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.3634 2023/06/04 16:40:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 16:40:03 - mmengine - INFO - Epoch(train) [2][2569/2569] lr: 8.0000e-03 eta: 1 day, 4:18:07 time: 0.2476 data_time: 0.0070 memory: 5828 grad_norm: 4.0783 loss: 3.1572 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 3.1572 2023/06/04 16:40:09 - mmengine - INFO - Epoch(train) [3][ 20/2569] lr: 1.2000e-02 eta: 1 day, 4:19:50 time: 0.3415 data_time: 0.0502 memory: 5828 grad_norm: 4.0859 loss: 3.0995 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0995 2023/06/04 16:40:15 - mmengine - INFO - Epoch(train) [3][ 40/2569] lr: 1.2000e-02 eta: 1 day, 4:19:42 time: 0.2665 data_time: 0.0073 memory: 5828 grad_norm: 4.1785 loss: 3.1694 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.1694 2023/06/04 16:40:20 - mmengine - INFO - Epoch(train) [3][ 60/2569] lr: 1.2000e-02 eta: 1 day, 4:19:24 time: 0.2596 data_time: 0.0074 memory: 5828 grad_norm: 4.1232 loss: 3.2350 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2350 2023/06/04 16:40:25 - mmengine - INFO - Epoch(train) [3][ 80/2569] lr: 1.2000e-02 eta: 1 day, 4:19:33 time: 0.2776 data_time: 0.0078 memory: 5828 grad_norm: 4.1395 loss: 3.2859 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.2859 2023/06/04 16:40:31 - mmengine - INFO - Epoch(train) [3][ 100/2569] lr: 1.2000e-02 eta: 1 day, 4:19:17 time: 0.2610 data_time: 0.0083 memory: 5828 grad_norm: 4.1016 loss: 3.1184 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 3.1184 2023/06/04 16:40:36 - mmengine - INFO - Epoch(train) [3][ 120/2569] lr: 1.2000e-02 eta: 1 day, 4:19:09 time: 0.2662 data_time: 0.0074 memory: 5828 grad_norm: 4.0618 loss: 3.2048 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.2048 2023/06/04 16:40:41 - mmengine - INFO - Epoch(train) [3][ 140/2569] lr: 1.2000e-02 eta: 1 day, 4:18:59 time: 0.2655 data_time: 0.0074 memory: 5828 grad_norm: 3.9938 loss: 3.1383 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.1383 2023/06/04 16:40:47 - mmengine - INFO - Epoch(train) [3][ 160/2569] lr: 1.2000e-02 eta: 1 day, 4:18:56 time: 0.2696 data_time: 0.0075 memory: 5828 grad_norm: 4.0452 loss: 3.2128 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.2128 2023/06/04 16:40:52 - mmengine - INFO - Epoch(train) [3][ 180/2569] lr: 1.2000e-02 eta: 1 day, 4:18:38 time: 0.2596 data_time: 0.0075 memory: 5828 grad_norm: 4.0412 loss: 3.2558 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2558 2023/06/04 16:40:57 - mmengine - INFO - Epoch(train) [3][ 200/2569] lr: 1.2000e-02 eta: 1 day, 4:18:31 time: 0.2669 data_time: 0.0078 memory: 5828 grad_norm: 3.9970 loss: 3.4067 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.4067 2023/06/04 16:41:03 - mmengine - INFO - Epoch(train) [3][ 220/2569] lr: 1.2000e-02 eta: 1 day, 4:18:22 time: 0.2653 data_time: 0.0079 memory: 5828 grad_norm: 4.0683 loss: 3.1279 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 3.1279 2023/06/04 16:41:08 - mmengine - INFO - Epoch(train) [3][ 240/2569] lr: 1.2000e-02 eta: 1 day, 4:18:15 time: 0.2676 data_time: 0.0077 memory: 5828 grad_norm: 3.9894 loss: 3.2322 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.2322 2023/06/04 16:41:13 - mmengine - INFO - Epoch(train) [3][ 260/2569] lr: 1.2000e-02 eta: 1 day, 4:18:06 time: 0.2655 data_time: 0.0078 memory: 5828 grad_norm: 4.0995 loss: 3.1843 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1843 2023/06/04 16:41:19 - mmengine - INFO - Epoch(train) [3][ 280/2569] lr: 1.2000e-02 eta: 1 day, 4:18:00 time: 0.2677 data_time: 0.0070 memory: 5828 grad_norm: 4.0347 loss: 3.4005 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.4005 2023/06/04 16:41:24 - mmengine - INFO - Epoch(train) [3][ 300/2569] lr: 1.2000e-02 eta: 1 day, 4:17:48 time: 0.2632 data_time: 0.0080 memory: 5828 grad_norm: 4.0229 loss: 3.0935 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.0935 2023/06/04 16:41:29 - mmengine - INFO - Epoch(train) [3][ 320/2569] lr: 1.2000e-02 eta: 1 day, 4:17:42 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 3.9909 loss: 2.9923 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9923 2023/06/04 16:41:34 - mmengine - INFO - Epoch(train) [3][ 340/2569] lr: 1.2000e-02 eta: 1 day, 4:17:25 time: 0.2597 data_time: 0.0077 memory: 5828 grad_norm: 4.0103 loss: 3.3017 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.3017 2023/06/04 16:41:40 - mmengine - INFO - Epoch(train) [3][ 360/2569] lr: 1.2000e-02 eta: 1 day, 4:17:13 time: 0.2634 data_time: 0.0076 memory: 5828 grad_norm: 4.0033 loss: 3.1921 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1921 2023/06/04 16:41:45 - mmengine - INFO - Epoch(train) [3][ 380/2569] lr: 1.2000e-02 eta: 1 day, 4:16:57 time: 0.2603 data_time: 0.0075 memory: 5828 grad_norm: 3.9484 loss: 3.0595 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 3.0595 2023/06/04 16:41:50 - mmengine - INFO - Epoch(train) [3][ 400/2569] lr: 1.2000e-02 eta: 1 day, 4:16:55 time: 0.2702 data_time: 0.0078 memory: 5828 grad_norm: 3.9978 loss: 3.3048 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.3048 2023/06/04 16:41:56 - mmengine - INFO - Epoch(train) [3][ 420/2569] lr: 1.2000e-02 eta: 1 day, 4:16:51 time: 0.2692 data_time: 0.0078 memory: 5828 grad_norm: 3.9957 loss: 3.2146 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 3.2146 2023/06/04 16:42:01 - mmengine - INFO - Epoch(train) [3][ 440/2569] lr: 1.2000e-02 eta: 1 day, 4:16:47 time: 0.2693 data_time: 0.0079 memory: 5828 grad_norm: 4.0116 loss: 3.6235 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.6235 2023/06/04 16:42:06 - mmengine - INFO - Epoch(train) [3][ 460/2569] lr: 1.2000e-02 eta: 1 day, 4:16:38 time: 0.2652 data_time: 0.0070 memory: 5828 grad_norm: 4.0273 loss: 3.3164 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.3164 2023/06/04 16:42:12 - mmengine - INFO - Epoch(train) [3][ 480/2569] lr: 1.2000e-02 eta: 1 day, 4:16:29 time: 0.2653 data_time: 0.0073 memory: 5828 grad_norm: 4.0483 loss: 3.5489 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.5489 2023/06/04 16:42:17 - mmengine - INFO - Epoch(train) [3][ 500/2569] lr: 1.2000e-02 eta: 1 day, 4:16:12 time: 0.2596 data_time: 0.0076 memory: 5828 grad_norm: 3.9500 loss: 3.4605 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.4605 2023/06/04 16:42:22 - mmengine - INFO - Epoch(train) [3][ 520/2569] lr: 1.2000e-02 eta: 1 day, 4:16:22 time: 0.2793 data_time: 0.0081 memory: 5828 grad_norm: 3.9950 loss: 3.2506 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.2506 2023/06/04 16:42:28 - mmengine - INFO - Epoch(train) [3][ 540/2569] lr: 1.2000e-02 eta: 1 day, 4:16:05 time: 0.2591 data_time: 0.0076 memory: 5828 grad_norm: 3.9758 loss: 3.3049 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.3049 2023/06/04 16:42:33 - mmengine - INFO - Epoch(train) [3][ 560/2569] lr: 1.2000e-02 eta: 1 day, 4:16:01 time: 0.2697 data_time: 0.0074 memory: 5828 grad_norm: 3.9280 loss: 2.7407 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7407 2023/06/04 16:42:38 - mmengine - INFO - Epoch(train) [3][ 580/2569] lr: 1.2000e-02 eta: 1 day, 4:15:44 time: 0.2592 data_time: 0.0083 memory: 5828 grad_norm: 3.9758 loss: 3.3917 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.3917 2023/06/04 16:42:43 - mmengine - INFO - Epoch(train) [3][ 600/2569] lr: 1.2000e-02 eta: 1 day, 4:15:34 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 3.9371 loss: 3.1460 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1460 2023/06/04 16:42:49 - mmengine - INFO - Epoch(train) [3][ 620/2569] lr: 1.2000e-02 eta: 1 day, 4:15:28 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 3.9541 loss: 3.6164 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.6164 2023/06/04 16:42:54 - mmengine - INFO - Epoch(train) [3][ 640/2569] lr: 1.2000e-02 eta: 1 day, 4:15:28 time: 0.2718 data_time: 0.0077 memory: 5828 grad_norm: 3.9313 loss: 2.9150 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.9150 2023/06/04 16:43:00 - mmengine - INFO - Epoch(train) [3][ 660/2569] lr: 1.2000e-02 eta: 1 day, 4:15:16 time: 0.2636 data_time: 0.0078 memory: 5828 grad_norm: 3.9827 loss: 3.1567 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1567 2023/06/04 16:43:05 - mmengine - INFO - Epoch(train) [3][ 680/2569] lr: 1.2000e-02 eta: 1 day, 4:15:02 time: 0.2612 data_time: 0.0079 memory: 5828 grad_norm: 3.9305 loss: 3.1975 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.1975 2023/06/04 16:43:10 - mmengine - INFO - Epoch(train) [3][ 700/2569] lr: 1.2000e-02 eta: 1 day, 4:14:46 time: 0.2594 data_time: 0.0082 memory: 5828 grad_norm: 3.9712 loss: 3.1185 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1185 2023/06/04 16:43:15 - mmengine - INFO - Epoch(train) [3][ 720/2569] lr: 1.2000e-02 eta: 1 day, 4:14:34 time: 0.2630 data_time: 0.0078 memory: 5828 grad_norm: 4.0083 loss: 3.2988 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.2988 2023/06/04 16:43:20 - mmengine - INFO - Epoch(train) [3][ 740/2569] lr: 1.2000e-02 eta: 1 day, 4:14:19 time: 0.2602 data_time: 0.0080 memory: 5828 grad_norm: 3.9885 loss: 3.1781 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.1781 2023/06/04 16:43:26 - mmengine - INFO - Epoch(train) [3][ 760/2569] lr: 1.2000e-02 eta: 1 day, 4:14:11 time: 0.2658 data_time: 0.0079 memory: 5828 grad_norm: 3.9689 loss: 3.0184 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0184 2023/06/04 16:43:31 - mmengine - INFO - Epoch(train) [3][ 780/2569] lr: 1.2000e-02 eta: 1 day, 4:13:53 time: 0.2587 data_time: 0.0077 memory: 5828 grad_norm: 3.9962 loss: 2.6950 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.6950 2023/06/04 16:43:36 - mmengine - INFO - Epoch(train) [3][ 800/2569] lr: 1.2000e-02 eta: 1 day, 4:13:42 time: 0.2632 data_time: 0.0078 memory: 5828 grad_norm: 3.9611 loss: 3.1336 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1336 2023/06/04 16:43:41 - mmengine - INFO - Epoch(train) [3][ 820/2569] lr: 1.2000e-02 eta: 1 day, 4:13:26 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 3.9863 loss: 3.2974 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2974 2023/06/04 16:43:47 - mmengine - INFO - Epoch(train) [3][ 840/2569] lr: 1.2000e-02 eta: 1 day, 4:13:16 time: 0.2645 data_time: 0.0076 memory: 5828 grad_norm: 3.9489 loss: 2.9943 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.9943 2023/06/04 16:43:52 - mmengine - INFO - Epoch(train) [3][ 860/2569] lr: 1.2000e-02 eta: 1 day, 4:13:01 time: 0.2602 data_time: 0.0085 memory: 5828 grad_norm: 3.9710 loss: 3.0601 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0601 2023/06/04 16:43:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 16:43:57 - mmengine - INFO - Epoch(train) [3][ 880/2569] lr: 1.2000e-02 eta: 1 day, 4:12:47 time: 0.2606 data_time: 0.0080 memory: 5828 grad_norm: 4.0498 loss: 3.3940 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.3940 2023/06/04 16:44:02 - mmengine - INFO - Epoch(train) [3][ 900/2569] lr: 1.2000e-02 eta: 1 day, 4:12:31 time: 0.2591 data_time: 0.0087 memory: 5828 grad_norm: 3.9256 loss: 3.1706 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.1706 2023/06/04 16:44:08 - mmengine - INFO - Epoch(train) [3][ 920/2569] lr: 1.2000e-02 eta: 1 day, 4:12:33 time: 0.2737 data_time: 0.0071 memory: 5828 grad_norm: 3.9615 loss: 3.2052 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.2052 2023/06/04 16:44:13 - mmengine - INFO - Epoch(train) [3][ 940/2569] lr: 1.2000e-02 eta: 1 day, 4:12:18 time: 0.2602 data_time: 0.0078 memory: 5828 grad_norm: 3.9918 loss: 3.2592 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.2592 2023/06/04 16:44:18 - mmengine - INFO - Epoch(train) [3][ 960/2569] lr: 1.2000e-02 eta: 1 day, 4:12:08 time: 0.2644 data_time: 0.0080 memory: 5828 grad_norm: 4.0210 loss: 3.1750 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.1750 2023/06/04 16:44:23 - mmengine - INFO - Epoch(train) [3][ 980/2569] lr: 1.2000e-02 eta: 1 day, 4:11:55 time: 0.2614 data_time: 0.0090 memory: 5828 grad_norm: 3.9616 loss: 3.1936 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.1936 2023/06/04 16:44:29 - mmengine - INFO - Epoch(train) [3][1000/2569] lr: 1.2000e-02 eta: 1 day, 4:11:40 time: 0.2599 data_time: 0.0078 memory: 5828 grad_norm: 3.9519 loss: 3.0860 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0860 2023/06/04 16:44:34 - mmengine - INFO - Epoch(train) [3][1020/2569] lr: 1.2000e-02 eta: 1 day, 4:11:38 time: 0.2705 data_time: 0.0074 memory: 5828 grad_norm: 3.9457 loss: 3.2325 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 3.2325 2023/06/04 16:44:39 - mmengine - INFO - Epoch(train) [3][1040/2569] lr: 1.2000e-02 eta: 1 day, 4:11:23 time: 0.2593 data_time: 0.0074 memory: 5828 grad_norm: 3.9597 loss: 2.9651 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.9651 2023/06/04 16:44:44 - mmengine - INFO - Epoch(train) [3][1060/2569] lr: 1.2000e-02 eta: 1 day, 4:11:09 time: 0.2605 data_time: 0.0079 memory: 5828 grad_norm: 3.9719 loss: 3.1588 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1588 2023/06/04 16:44:50 - mmengine - INFO - Epoch(train) [3][1080/2569] lr: 1.2000e-02 eta: 1 day, 4:10:53 time: 0.2592 data_time: 0.0081 memory: 5828 grad_norm: 3.9167 loss: 2.8274 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8274 2023/06/04 16:44:55 - mmengine - INFO - Epoch(train) [3][1100/2569] lr: 1.2000e-02 eta: 1 day, 4:10:46 time: 0.2660 data_time: 0.0079 memory: 5828 grad_norm: 3.9735 loss: 3.0434 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.0434 2023/06/04 16:45:00 - mmengine - INFO - Epoch(train) [3][1120/2569] lr: 1.2000e-02 eta: 1 day, 4:10:42 time: 0.2688 data_time: 0.0079 memory: 5828 grad_norm: 3.9445 loss: 3.0430 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0430 2023/06/04 16:45:06 - mmengine - INFO - Epoch(train) [3][1140/2569] lr: 1.2000e-02 eta: 1 day, 4:10:36 time: 0.2671 data_time: 0.0082 memory: 5828 grad_norm: 3.9114 loss: 2.8644 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8644 2023/06/04 16:45:11 - mmengine - INFO - Epoch(train) [3][1160/2569] lr: 1.2000e-02 eta: 1 day, 4:10:29 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 3.8950 loss: 2.9007 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.9007 2023/06/04 16:45:16 - mmengine - INFO - Epoch(train) [3][1180/2569] lr: 1.2000e-02 eta: 1 day, 4:10:25 time: 0.2692 data_time: 0.0071 memory: 5828 grad_norm: 3.9369 loss: 3.0713 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0713 2023/06/04 16:45:22 - mmengine - INFO - Epoch(train) [3][1200/2569] lr: 1.2000e-02 eta: 1 day, 4:10:17 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 3.9928 loss: 3.1747 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.1747 2023/06/04 16:45:27 - mmengine - INFO - Epoch(train) [3][1220/2569] lr: 1.2000e-02 eta: 1 day, 4:10:07 time: 0.2640 data_time: 0.0076 memory: 5828 grad_norm: 4.0438 loss: 3.1445 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1445 2023/06/04 16:45:32 - mmengine - INFO - Epoch(train) [3][1240/2569] lr: 1.2000e-02 eta: 1 day, 4:10:06 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 3.9414 loss: 3.2391 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.2391 2023/06/04 16:45:38 - mmengine - INFO - Epoch(train) [3][1260/2569] lr: 1.2000e-02 eta: 1 day, 4:10:02 time: 0.2691 data_time: 0.0075 memory: 5828 grad_norm: 3.9119 loss: 3.1899 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.1899 2023/06/04 16:45:43 - mmengine - INFO - Epoch(train) [3][1280/2569] lr: 1.2000e-02 eta: 1 day, 4:09:58 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 3.9138 loss: 3.2530 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2530 2023/06/04 16:45:48 - mmengine - INFO - Epoch(train) [3][1300/2569] lr: 1.2000e-02 eta: 1 day, 4:09:48 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 3.9877 loss: 3.2693 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 3.2693 2023/06/04 16:45:54 - mmengine - INFO - Epoch(train) [3][1320/2569] lr: 1.2000e-02 eta: 1 day, 4:09:32 time: 0.2587 data_time: 0.0074 memory: 5828 grad_norm: 3.9473 loss: 2.8146 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8146 2023/06/04 16:45:59 - mmengine - INFO - Epoch(train) [3][1340/2569] lr: 1.2000e-02 eta: 1 day, 4:09:31 time: 0.2711 data_time: 0.0071 memory: 5828 grad_norm: 3.9217 loss: 3.0913 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 3.0913 2023/06/04 16:46:04 - mmengine - INFO - Epoch(train) [3][1360/2569] lr: 1.2000e-02 eta: 1 day, 4:09:17 time: 0.2600 data_time: 0.0082 memory: 5828 grad_norm: 3.9671 loss: 2.7133 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7133 2023/06/04 16:46:09 - mmengine - INFO - Epoch(train) [3][1380/2569] lr: 1.2000e-02 eta: 1 day, 4:09:03 time: 0.2605 data_time: 0.0074 memory: 5828 grad_norm: 4.0357 loss: 3.3441 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.3441 2023/06/04 16:46:15 - mmengine - INFO - Epoch(train) [3][1400/2569] lr: 1.2000e-02 eta: 1 day, 4:09:01 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 3.9445 loss: 3.3094 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.3094 2023/06/04 16:46:20 - mmengine - INFO - Epoch(train) [3][1420/2569] lr: 1.2000e-02 eta: 1 day, 4:08:59 time: 0.2708 data_time: 0.0073 memory: 5828 grad_norm: 3.9375 loss: 3.1452 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1452 2023/06/04 16:46:26 - mmengine - INFO - Epoch(train) [3][1440/2569] lr: 1.2000e-02 eta: 1 day, 4:08:52 time: 0.2663 data_time: 0.0077 memory: 5828 grad_norm: 3.8655 loss: 2.9315 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9315 2023/06/04 16:46:31 - mmengine - INFO - Epoch(train) [3][1460/2569] lr: 1.2000e-02 eta: 1 day, 4:08:48 time: 0.2679 data_time: 0.0075 memory: 5828 grad_norm: 3.9612 loss: 3.1919 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 3.1919 2023/06/04 16:46:36 - mmengine - INFO - Epoch(train) [3][1480/2569] lr: 1.2000e-02 eta: 1 day, 4:08:35 time: 0.2615 data_time: 0.0077 memory: 5828 grad_norm: 3.9533 loss: 3.7097 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.7097 2023/06/04 16:46:41 - mmengine - INFO - Epoch(train) [3][1500/2569] lr: 1.2000e-02 eta: 1 day, 4:08:32 time: 0.2691 data_time: 0.0075 memory: 5828 grad_norm: 3.9004 loss: 2.8524 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8524 2023/06/04 16:46:47 - mmengine - INFO - Epoch(train) [3][1520/2569] lr: 1.2000e-02 eta: 1 day, 4:08:24 time: 0.2654 data_time: 0.0079 memory: 5828 grad_norm: 3.9924 loss: 3.3460 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.3460 2023/06/04 16:46:52 - mmengine - INFO - Epoch(train) [3][1540/2569] lr: 1.2000e-02 eta: 1 day, 4:08:14 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 3.9321 loss: 2.9391 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9391 2023/06/04 16:46:58 - mmengine - INFO - Epoch(train) [3][1560/2569] lr: 1.2000e-02 eta: 1 day, 4:08:17 time: 0.2745 data_time: 0.0072 memory: 5828 grad_norm: 3.9243 loss: 3.0514 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0514 2023/06/04 16:47:03 - mmengine - INFO - Epoch(train) [3][1580/2569] lr: 1.2000e-02 eta: 1 day, 4:08:09 time: 0.2651 data_time: 0.0078 memory: 5828 grad_norm: 3.9281 loss: 2.4221 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4221 2023/06/04 16:47:08 - mmengine - INFO - Epoch(train) [3][1600/2569] lr: 1.2000e-02 eta: 1 day, 4:08:05 time: 0.2694 data_time: 0.0076 memory: 5828 grad_norm: 3.9769 loss: 3.0003 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 3.0003 2023/06/04 16:47:14 - mmengine - INFO - Epoch(train) [3][1620/2569] lr: 1.2000e-02 eta: 1 day, 4:07:58 time: 0.2657 data_time: 0.0079 memory: 5828 grad_norm: 3.9049 loss: 3.1675 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1675 2023/06/04 16:47:19 - mmengine - INFO - Epoch(train) [3][1640/2569] lr: 1.2000e-02 eta: 1 day, 4:07:58 time: 0.2726 data_time: 0.0080 memory: 5828 grad_norm: 3.9713 loss: 2.9858 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9858 2023/06/04 16:47:24 - mmengine - INFO - Epoch(train) [3][1660/2569] lr: 1.2000e-02 eta: 1 day, 4:07:57 time: 0.2711 data_time: 0.0076 memory: 5828 grad_norm: 3.9275 loss: 2.8785 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8785 2023/06/04 16:47:30 - mmengine - INFO - Epoch(train) [3][1680/2569] lr: 1.2000e-02 eta: 1 day, 4:07:52 time: 0.2683 data_time: 0.0076 memory: 5828 grad_norm: 4.0198 loss: 2.8729 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8729 2023/06/04 16:47:35 - mmengine - INFO - Epoch(train) [3][1700/2569] lr: 1.2000e-02 eta: 1 day, 4:07:38 time: 0.2597 data_time: 0.0075 memory: 5828 grad_norm: 3.9953 loss: 2.8511 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8511 2023/06/04 16:47:40 - mmengine - INFO - Epoch(train) [3][1720/2569] lr: 1.2000e-02 eta: 1 day, 4:07:26 time: 0.2613 data_time: 0.0073 memory: 5828 grad_norm: 3.9123 loss: 2.8901 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8901 2023/06/04 16:47:45 - mmengine - INFO - Epoch(train) [3][1740/2569] lr: 1.2000e-02 eta: 1 day, 4:07:14 time: 0.2618 data_time: 0.0076 memory: 5828 grad_norm: 3.9329 loss: 3.2034 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.2034 2023/06/04 16:47:51 - mmengine - INFO - Epoch(train) [3][1760/2569] lr: 1.2000e-02 eta: 1 day, 4:07:01 time: 0.2597 data_time: 0.0074 memory: 5828 grad_norm: 3.9353 loss: 3.1330 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1330 2023/06/04 16:47:56 - mmengine - INFO - Epoch(train) [3][1780/2569] lr: 1.2000e-02 eta: 1 day, 4:06:53 time: 0.2654 data_time: 0.0078 memory: 5828 grad_norm: 3.9280 loss: 3.1005 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1005 2023/06/04 16:48:01 - mmengine - INFO - Epoch(train) [3][1800/2569] lr: 1.2000e-02 eta: 1 day, 4:06:43 time: 0.2629 data_time: 0.0074 memory: 5828 grad_norm: 3.9237 loss: 2.9641 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9641 2023/06/04 16:48:07 - mmengine - INFO - Epoch(train) [3][1820/2569] lr: 1.2000e-02 eta: 1 day, 4:06:34 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 3.8986 loss: 3.0251 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0251 2023/06/04 16:48:12 - mmengine - INFO - Epoch(train) [3][1840/2569] lr: 1.2000e-02 eta: 1 day, 4:06:23 time: 0.2623 data_time: 0.0081 memory: 5828 grad_norm: 3.8696 loss: 2.9070 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9070 2023/06/04 16:48:17 - mmengine - INFO - Epoch(train) [3][1860/2569] lr: 1.2000e-02 eta: 1 day, 4:06:18 time: 0.2678 data_time: 0.0077 memory: 5828 grad_norm: 3.9367 loss: 3.3045 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 3.3045 2023/06/04 16:48:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 16:48:22 - mmengine - INFO - Epoch(train) [3][1880/2569] lr: 1.2000e-02 eta: 1 day, 4:06:10 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 3.8992 loss: 2.9329 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9329 2023/06/04 16:48:28 - mmengine - INFO - Epoch(train) [3][1900/2569] lr: 1.2000e-02 eta: 1 day, 4:06:11 time: 0.2733 data_time: 0.0074 memory: 5828 grad_norm: 3.8892 loss: 2.9509 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9509 2023/06/04 16:48:33 - mmengine - INFO - Epoch(train) [3][1920/2569] lr: 1.2000e-02 eta: 1 day, 4:06:04 time: 0.2654 data_time: 0.0081 memory: 5828 grad_norm: 4.0022 loss: 3.0978 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0978 2023/06/04 16:48:38 - mmengine - INFO - Epoch(train) [3][1940/2569] lr: 1.2000e-02 eta: 1 day, 4:05:51 time: 0.2607 data_time: 0.0077 memory: 5828 grad_norm: 3.9414 loss: 2.9622 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9622 2023/06/04 16:48:44 - mmengine - INFO - Epoch(train) [3][1960/2569] lr: 1.2000e-02 eta: 1 day, 4:05:46 time: 0.2678 data_time: 0.0073 memory: 5828 grad_norm: 3.9798 loss: 3.0497 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0497 2023/06/04 16:48:49 - mmengine - INFO - Epoch(train) [3][1980/2569] lr: 1.2000e-02 eta: 1 day, 4:05:38 time: 0.2648 data_time: 0.0076 memory: 5828 grad_norm: 3.8601 loss: 2.4896 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4896 2023/06/04 16:48:55 - mmengine - INFO - Epoch(train) [3][2000/2569] lr: 1.2000e-02 eta: 1 day, 4:05:39 time: 0.2729 data_time: 0.0076 memory: 5828 grad_norm: 3.9727 loss: 2.6771 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6771 2023/06/04 16:49:00 - mmengine - INFO - Epoch(train) [3][2020/2569] lr: 1.2000e-02 eta: 1 day, 4:05:38 time: 0.2716 data_time: 0.0071 memory: 5828 grad_norm: 3.9498 loss: 3.2789 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2789 2023/06/04 16:49:05 - mmengine - INFO - Epoch(train) [3][2040/2569] lr: 1.2000e-02 eta: 1 day, 4:05:27 time: 0.2623 data_time: 0.0077 memory: 5828 grad_norm: 3.8534 loss: 3.0849 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.0849 2023/06/04 16:49:11 - mmengine - INFO - Epoch(train) [3][2060/2569] lr: 1.2000e-02 eta: 1 day, 4:05:26 time: 0.2719 data_time: 0.0075 memory: 5828 grad_norm: 3.9134 loss: 3.1838 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 3.1838 2023/06/04 16:49:16 - mmengine - INFO - Epoch(train) [3][2080/2569] lr: 1.2000e-02 eta: 1 day, 4:05:17 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 3.9827 loss: 2.7376 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7376 2023/06/04 16:49:21 - mmengine - INFO - Epoch(train) [3][2100/2569] lr: 1.2000e-02 eta: 1 day, 4:05:12 time: 0.2679 data_time: 0.0078 memory: 5828 grad_norm: 3.8475 loss: 3.1219 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1219 2023/06/04 16:49:26 - mmengine - INFO - Epoch(train) [3][2120/2569] lr: 1.2000e-02 eta: 1 day, 4:04:58 time: 0.2593 data_time: 0.0074 memory: 5828 grad_norm: 3.9312 loss: 3.0533 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.0533 2023/06/04 16:49:32 - mmengine - INFO - Epoch(train) [3][2140/2569] lr: 1.2000e-02 eta: 1 day, 4:05:00 time: 0.2740 data_time: 0.0075 memory: 5828 grad_norm: 3.9071 loss: 3.1352 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.1352 2023/06/04 16:49:37 - mmengine - INFO - Epoch(train) [3][2160/2569] lr: 1.2000e-02 eta: 1 day, 4:04:53 time: 0.2660 data_time: 0.0077 memory: 5828 grad_norm: 3.9553 loss: 2.9062 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9062 2023/06/04 16:49:43 - mmengine - INFO - Epoch(train) [3][2180/2569] lr: 1.2000e-02 eta: 1 day, 4:04:54 time: 0.2736 data_time: 0.0082 memory: 5828 grad_norm: 3.9306 loss: 3.0578 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0578 2023/06/04 16:49:48 - mmengine - INFO - Epoch(train) [3][2200/2569] lr: 1.2000e-02 eta: 1 day, 4:04:40 time: 0.2595 data_time: 0.0077 memory: 5828 grad_norm: 3.8798 loss: 2.8245 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8245 2023/06/04 16:49:53 - mmengine - INFO - Epoch(train) [3][2220/2569] lr: 1.2000e-02 eta: 1 day, 4:04:36 time: 0.2685 data_time: 0.0074 memory: 5828 grad_norm: 3.9154 loss: 2.7361 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7361 2023/06/04 16:49:59 - mmengine - INFO - Epoch(train) [3][2240/2569] lr: 1.2000e-02 eta: 1 day, 4:04:32 time: 0.2691 data_time: 0.0076 memory: 5828 grad_norm: 3.8939 loss: 2.8671 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8671 2023/06/04 16:50:04 - mmengine - INFO - Epoch(train) [3][2260/2569] lr: 1.2000e-02 eta: 1 day, 4:04:34 time: 0.2737 data_time: 0.0073 memory: 5828 grad_norm: 3.9266 loss: 2.8784 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8784 2023/06/04 16:50:09 - mmengine - INFO - Epoch(train) [3][2280/2569] lr: 1.2000e-02 eta: 1 day, 4:04:24 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.9016 loss: 2.8226 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8226 2023/06/04 16:50:15 - mmengine - INFO - Epoch(train) [3][2300/2569] lr: 1.2000e-02 eta: 1 day, 4:04:27 time: 0.2752 data_time: 0.0074 memory: 5828 grad_norm: 3.9394 loss: 3.0986 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0986 2023/06/04 16:50:20 - mmengine - INFO - Epoch(train) [3][2320/2569] lr: 1.2000e-02 eta: 1 day, 4:04:13 time: 0.2590 data_time: 0.0079 memory: 5828 grad_norm: 3.9185 loss: 3.0136 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0136 2023/06/04 16:50:25 - mmengine - INFO - Epoch(train) [3][2340/2569] lr: 1.2000e-02 eta: 1 day, 4:04:05 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 3.9198 loss: 3.1430 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1430 2023/06/04 16:50:31 - mmengine - INFO - Epoch(train) [3][2360/2569] lr: 1.2000e-02 eta: 1 day, 4:04:00 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 4.0183 loss: 3.2031 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.2031 2023/06/04 16:50:36 - mmengine - INFO - Epoch(train) [3][2380/2569] lr: 1.2000e-02 eta: 1 day, 4:03:54 time: 0.2665 data_time: 0.0076 memory: 5828 grad_norm: 3.9454 loss: 3.3115 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.3115 2023/06/04 16:50:41 - mmengine - INFO - Epoch(train) [3][2400/2569] lr: 1.2000e-02 eta: 1 day, 4:03:48 time: 0.2665 data_time: 0.0074 memory: 5828 grad_norm: 3.9033 loss: 3.0137 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0137 2023/06/04 16:50:47 - mmengine - INFO - Epoch(train) [3][2420/2569] lr: 1.2000e-02 eta: 1 day, 4:03:42 time: 0.2668 data_time: 0.0078 memory: 5828 grad_norm: 3.9286 loss: 3.0486 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0486 2023/06/04 16:50:52 - mmengine - INFO - Epoch(train) [3][2440/2569] lr: 1.2000e-02 eta: 1 day, 4:03:36 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 3.9103 loss: 3.2487 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.2487 2023/06/04 16:50:57 - mmengine - INFO - Epoch(train) [3][2460/2569] lr: 1.2000e-02 eta: 1 day, 4:03:28 time: 0.2645 data_time: 0.0077 memory: 5828 grad_norm: 3.9303 loss: 3.1981 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.1981 2023/06/04 16:51:03 - mmengine - INFO - Epoch(train) [3][2480/2569] lr: 1.2000e-02 eta: 1 day, 4:03:15 time: 0.2601 data_time: 0.0072 memory: 5828 grad_norm: 3.9864 loss: 3.2641 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 3.2641 2023/06/04 16:51:08 - mmengine - INFO - Epoch(train) [3][2500/2569] lr: 1.2000e-02 eta: 1 day, 4:03:13 time: 0.2705 data_time: 0.0071 memory: 5828 grad_norm: 3.8902 loss: 3.2513 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.2513 2023/06/04 16:51:13 - mmengine - INFO - Epoch(train) [3][2520/2569] lr: 1.2000e-02 eta: 1 day, 4:03:00 time: 0.2593 data_time: 0.0077 memory: 5828 grad_norm: 3.9498 loss: 2.6991 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6991 2023/06/04 16:51:19 - mmengine - INFO - Epoch(train) [3][2540/2569] lr: 1.2000e-02 eta: 1 day, 4:03:09 time: 0.2827 data_time: 0.0073 memory: 5828 grad_norm: 3.9527 loss: 2.8933 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8933 2023/06/04 16:51:24 - mmengine - INFO - Epoch(train) [3][2560/2569] lr: 1.2000e-02 eta: 1 day, 4:03:04 time: 0.2669 data_time: 0.0076 memory: 5828 grad_norm: 3.9574 loss: 3.4756 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.4756 2023/06/04 16:51:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 16:51:27 - mmengine - INFO - Epoch(train) [3][2569/2569] lr: 1.2000e-02 eta: 1 day, 4:02:57 time: 0.2604 data_time: 0.0069 memory: 5828 grad_norm: 3.9435 loss: 3.1356 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 3.1356 2023/06/04 16:51:33 - mmengine - INFO - Epoch(train) [4][ 20/2569] lr: 1.6000e-02 eta: 1 day, 4:04:10 time: 0.3478 data_time: 0.0710 memory: 5828 grad_norm: 3.9477 loss: 3.0721 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 3.0721 2023/06/04 16:51:39 - mmengine - INFO - Epoch(train) [4][ 40/2569] lr: 1.6000e-02 eta: 1 day, 4:04:17 time: 0.2800 data_time: 0.0075 memory: 5828 grad_norm: 4.0164 loss: 3.1277 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.1277 2023/06/04 16:51:44 - mmengine - INFO - Epoch(train) [4][ 60/2569] lr: 1.6000e-02 eta: 1 day, 4:04:03 time: 0.2588 data_time: 0.0075 memory: 5828 grad_norm: 3.8606 loss: 3.1681 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 3.1681 2023/06/04 16:51:50 - mmengine - INFO - Epoch(train) [4][ 80/2569] lr: 1.6000e-02 eta: 1 day, 4:04:01 time: 0.2710 data_time: 0.0077 memory: 5828 grad_norm: 3.9971 loss: 2.9582 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9582 2023/06/04 16:51:55 - mmengine - INFO - Epoch(train) [4][ 100/2569] lr: 1.6000e-02 eta: 1 day, 4:04:02 time: 0.2735 data_time: 0.0071 memory: 5828 grad_norm: 3.9627 loss: 2.8463 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8463 2023/06/04 16:52:00 - mmengine - INFO - Epoch(train) [4][ 120/2569] lr: 1.6000e-02 eta: 1 day, 4:03:55 time: 0.2669 data_time: 0.0075 memory: 5828 grad_norm: 3.9007 loss: 2.8296 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8296 2023/06/04 16:52:06 - mmengine - INFO - Epoch(train) [4][ 140/2569] lr: 1.6000e-02 eta: 1 day, 4:03:55 time: 0.2732 data_time: 0.0075 memory: 5828 grad_norm: 3.8824 loss: 3.0970 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.0970 2023/06/04 16:52:11 - mmengine - INFO - Epoch(train) [4][ 160/2569] lr: 1.6000e-02 eta: 1 day, 4:03:43 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 3.8898 loss: 2.8490 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8490 2023/06/04 16:52:16 - mmengine - INFO - Epoch(train) [4][ 180/2569] lr: 1.6000e-02 eta: 1 day, 4:03:31 time: 0.2607 data_time: 0.0071 memory: 5828 grad_norm: 3.8488 loss: 3.4277 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.4277 2023/06/04 16:52:22 - mmengine - INFO - Epoch(train) [4][ 200/2569] lr: 1.6000e-02 eta: 1 day, 4:03:23 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 3.9032 loss: 3.0629 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0629 2023/06/04 16:52:27 - mmengine - INFO - Epoch(train) [4][ 220/2569] lr: 1.6000e-02 eta: 1 day, 4:03:18 time: 0.2684 data_time: 0.0071 memory: 5828 grad_norm: 3.8743 loss: 2.9264 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.9264 2023/06/04 16:52:32 - mmengine - INFO - Epoch(train) [4][ 240/2569] lr: 1.6000e-02 eta: 1 day, 4:03:10 time: 0.2650 data_time: 0.0080 memory: 5828 grad_norm: 3.8723 loss: 2.9179 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.9179 2023/06/04 16:52:38 - mmengine - INFO - Epoch(train) [4][ 260/2569] lr: 1.6000e-02 eta: 1 day, 4:03:11 time: 0.2742 data_time: 0.0078 memory: 5828 grad_norm: 3.8650 loss: 2.6807 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6807 2023/06/04 16:52:43 - mmengine - INFO - Epoch(train) [4][ 280/2569] lr: 1.6000e-02 eta: 1 day, 4:02:58 time: 0.2595 data_time: 0.0077 memory: 5828 grad_norm: 3.8366 loss: 3.0951 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0951 2023/06/04 16:52:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 16:52:48 - mmengine - INFO - Epoch(train) [4][ 300/2569] lr: 1.6000e-02 eta: 1 day, 4:02:50 time: 0.2652 data_time: 0.0086 memory: 5828 grad_norm: 3.8617 loss: 3.1922 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1922 2023/06/04 16:52:54 - mmengine - INFO - Epoch(train) [4][ 320/2569] lr: 1.6000e-02 eta: 1 day, 4:02:39 time: 0.2606 data_time: 0.0074 memory: 5828 grad_norm: 3.8395 loss: 2.8195 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8195 2023/06/04 16:52:59 - mmengine - INFO - Epoch(train) [4][ 340/2569] lr: 1.6000e-02 eta: 1 day, 4:02:29 time: 0.2633 data_time: 0.0076 memory: 5828 grad_norm: 3.8200 loss: 3.1945 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 3.1945 2023/06/04 16:53:04 - mmengine - INFO - Epoch(train) [4][ 360/2569] lr: 1.6000e-02 eta: 1 day, 4:02:29 time: 0.2725 data_time: 0.0078 memory: 5828 grad_norm: 3.8680 loss: 2.8911 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8911 2023/06/04 16:53:10 - mmengine - INFO - Epoch(train) [4][ 380/2569] lr: 1.6000e-02 eta: 1 day, 4:02:20 time: 0.2645 data_time: 0.0082 memory: 5828 grad_norm: 3.8207 loss: 2.7844 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7844 2023/06/04 16:53:15 - mmengine - INFO - Epoch(train) [4][ 400/2569] lr: 1.6000e-02 eta: 1 day, 4:02:12 time: 0.2640 data_time: 0.0076 memory: 5828 grad_norm: 3.8407 loss: 3.0631 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0631 2023/06/04 16:53:20 - mmengine - INFO - Epoch(train) [4][ 420/2569] lr: 1.6000e-02 eta: 1 day, 4:02:04 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 3.8778 loss: 2.7634 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7634 2023/06/04 16:53:25 - mmengine - INFO - Epoch(train) [4][ 440/2569] lr: 1.6000e-02 eta: 1 day, 4:01:58 time: 0.2660 data_time: 0.0077 memory: 5828 grad_norm: 3.8213 loss: 3.0563 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0563 2023/06/04 16:53:31 - mmengine - INFO - Epoch(train) [4][ 460/2569] lr: 1.6000e-02 eta: 1 day, 4:01:50 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 3.8674 loss: 3.0048 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0048 2023/06/04 16:53:36 - mmengine - INFO - Epoch(train) [4][ 480/2569] lr: 1.6000e-02 eta: 1 day, 4:01:47 time: 0.2703 data_time: 0.0076 memory: 5828 grad_norm: 3.8046 loss: 3.2111 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2111 2023/06/04 16:53:41 - mmengine - INFO - Epoch(train) [4][ 500/2569] lr: 1.6000e-02 eta: 1 day, 4:01:35 time: 0.2604 data_time: 0.0076 memory: 5828 grad_norm: 3.8665 loss: 3.0712 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0712 2023/06/04 16:53:47 - mmengine - INFO - Epoch(train) [4][ 520/2569] lr: 1.6000e-02 eta: 1 day, 4:01:36 time: 0.2739 data_time: 0.0081 memory: 5828 grad_norm: 3.7794 loss: 2.6118 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6118 2023/06/04 16:53:52 - mmengine - INFO - Epoch(train) [4][ 540/2569] lr: 1.6000e-02 eta: 1 day, 4:01:29 time: 0.2654 data_time: 0.0079 memory: 5828 grad_norm: 3.8164 loss: 3.0918 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0918 2023/06/04 16:53:57 - mmengine - INFO - Epoch(train) [4][ 560/2569] lr: 1.6000e-02 eta: 1 day, 4:01:20 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.8415 loss: 2.8556 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8556 2023/06/04 16:54:03 - mmengine - INFO - Epoch(train) [4][ 580/2569] lr: 1.6000e-02 eta: 1 day, 4:01:10 time: 0.2617 data_time: 0.0077 memory: 5828 grad_norm: 3.7782 loss: 3.2142 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.2142 2023/06/04 16:54:08 - mmengine - INFO - Epoch(train) [4][ 600/2569] lr: 1.6000e-02 eta: 1 day, 4:01:13 time: 0.2764 data_time: 0.0075 memory: 5828 grad_norm: 3.8524 loss: 3.1947 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 3.1947 2023/06/04 16:54:14 - mmengine - INFO - Epoch(train) [4][ 620/2569] lr: 1.6000e-02 eta: 1 day, 4:01:08 time: 0.2687 data_time: 0.0079 memory: 5828 grad_norm: 3.8129 loss: 3.0198 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 3.0198 2023/06/04 16:54:19 - mmengine - INFO - Epoch(train) [4][ 640/2569] lr: 1.6000e-02 eta: 1 day, 4:01:02 time: 0.2664 data_time: 0.0083 memory: 5828 grad_norm: 3.8643 loss: 2.9486 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9486 2023/06/04 16:54:24 - mmengine - INFO - Epoch(train) [4][ 660/2569] lr: 1.6000e-02 eta: 1 day, 4:00:52 time: 0.2627 data_time: 0.0079 memory: 5828 grad_norm: 3.7869 loss: 3.2811 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.2811 2023/06/04 16:54:30 - mmengine - INFO - Epoch(train) [4][ 680/2569] lr: 1.6000e-02 eta: 1 day, 4:00:54 time: 0.2757 data_time: 0.0075 memory: 5828 grad_norm: 3.7739 loss: 3.0090 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0090 2023/06/04 16:54:35 - mmengine - INFO - Epoch(train) [4][ 700/2569] lr: 1.6000e-02 eta: 1 day, 4:00:43 time: 0.2614 data_time: 0.0076 memory: 5828 grad_norm: 3.8086 loss: 2.8338 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.8338 2023/06/04 16:54:40 - mmengine - INFO - Epoch(train) [4][ 720/2569] lr: 1.6000e-02 eta: 1 day, 4:00:37 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 3.8276 loss: 2.8091 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8091 2023/06/04 16:54:46 - mmengine - INFO - Epoch(train) [4][ 740/2569] lr: 1.6000e-02 eta: 1 day, 4:00:30 time: 0.2656 data_time: 0.0072 memory: 5828 grad_norm: 3.8168 loss: 3.0458 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0458 2023/06/04 16:54:51 - mmengine - INFO - Epoch(train) [4][ 760/2569] lr: 1.6000e-02 eta: 1 day, 4:00:28 time: 0.2711 data_time: 0.0078 memory: 5828 grad_norm: 3.8663 loss: 2.9789 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9789 2023/06/04 16:54:56 - mmengine - INFO - Epoch(train) [4][ 780/2569] lr: 1.6000e-02 eta: 1 day, 4:00:21 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 3.8032 loss: 3.0891 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0891 2023/06/04 16:55:02 - mmengine - INFO - Epoch(train) [4][ 800/2569] lr: 1.6000e-02 eta: 1 day, 4:00:14 time: 0.2663 data_time: 0.0079 memory: 5828 grad_norm: 3.8327 loss: 2.7718 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7718 2023/06/04 16:55:07 - mmengine - INFO - Epoch(train) [4][ 820/2569] lr: 1.6000e-02 eta: 1 day, 4:00:03 time: 0.2606 data_time: 0.0077 memory: 5828 grad_norm: 3.7873 loss: 2.6529 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6529 2023/06/04 16:55:12 - mmengine - INFO - Epoch(train) [4][ 840/2569] lr: 1.6000e-02 eta: 1 day, 3:59:54 time: 0.2637 data_time: 0.0074 memory: 5828 grad_norm: 3.8044 loss: 2.4556 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4556 2023/06/04 16:55:17 - mmengine - INFO - Epoch(train) [4][ 860/2569] lr: 1.6000e-02 eta: 1 day, 3:59:47 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 3.8235 loss: 3.0870 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.0870 2023/06/04 16:55:23 - mmengine - INFO - Epoch(train) [4][ 880/2569] lr: 1.6000e-02 eta: 1 day, 3:59:36 time: 0.2610 data_time: 0.0076 memory: 5828 grad_norm: 3.8295 loss: 3.1734 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.1734 2023/06/04 16:55:28 - mmengine - INFO - Epoch(train) [4][ 900/2569] lr: 1.6000e-02 eta: 1 day, 3:59:29 time: 0.2658 data_time: 0.0073 memory: 5828 grad_norm: 3.8136 loss: 3.0112 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0112 2023/06/04 16:55:33 - mmengine - INFO - Epoch(train) [4][ 920/2569] lr: 1.6000e-02 eta: 1 day, 3:59:26 time: 0.2706 data_time: 0.0076 memory: 5828 grad_norm: 3.7784 loss: 3.1784 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.1784 2023/06/04 16:55:39 - mmengine - INFO - Epoch(train) [4][ 940/2569] lr: 1.6000e-02 eta: 1 day, 3:59:19 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 3.7554 loss: 3.0331 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.0331 2023/06/04 16:55:44 - mmengine - INFO - Epoch(train) [4][ 960/2569] lr: 1.6000e-02 eta: 1 day, 3:59:11 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 3.7607 loss: 3.2658 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.2658 2023/06/04 16:55:49 - mmengine - INFO - Epoch(train) [4][ 980/2569] lr: 1.6000e-02 eta: 1 day, 3:59:09 time: 0.2721 data_time: 0.0076 memory: 5828 grad_norm: 3.8146 loss: 2.8484 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.8484 2023/06/04 16:55:55 - mmengine - INFO - Epoch(train) [4][1000/2569] lr: 1.6000e-02 eta: 1 day, 3:59:02 time: 0.2650 data_time: 0.0073 memory: 5828 grad_norm: 3.8018 loss: 2.6833 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6833 2023/06/04 16:56:00 - mmengine - INFO - Epoch(train) [4][1020/2569] lr: 1.6000e-02 eta: 1 day, 3:59:00 time: 0.2722 data_time: 0.0075 memory: 5828 grad_norm: 3.8514 loss: 2.9181 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9181 2023/06/04 16:56:05 - mmengine - INFO - Epoch(train) [4][1040/2569] lr: 1.6000e-02 eta: 1 day, 3:58:56 time: 0.2682 data_time: 0.0077 memory: 5828 grad_norm: 3.7808 loss: 3.0373 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0373 2023/06/04 16:56:11 - mmengine - INFO - Epoch(train) [4][1060/2569] lr: 1.6000e-02 eta: 1 day, 3:58:50 time: 0.2675 data_time: 0.0075 memory: 5828 grad_norm: 3.8254 loss: 3.1036 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 3.1036 2023/06/04 16:56:16 - mmengine - INFO - Epoch(train) [4][1080/2569] lr: 1.6000e-02 eta: 1 day, 3:58:45 time: 0.2678 data_time: 0.0076 memory: 5828 grad_norm: 3.7220 loss: 3.2597 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.2597 2023/06/04 16:56:21 - mmengine - INFO - Epoch(train) [4][1100/2569] lr: 1.6000e-02 eta: 1 day, 3:58:33 time: 0.2599 data_time: 0.0074 memory: 5828 grad_norm: 3.7758 loss: 2.7264 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7264 2023/06/04 16:56:27 - mmengine - INFO - Epoch(train) [4][1120/2569] lr: 1.6000e-02 eta: 1 day, 3:58:26 time: 0.2654 data_time: 0.0085 memory: 5828 grad_norm: 3.7741 loss: 2.6965 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6965 2023/06/04 16:56:32 - mmengine - INFO - Epoch(train) [4][1140/2569] lr: 1.6000e-02 eta: 1 day, 3:58:16 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 3.8219 loss: 3.0001 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0001 2023/06/04 16:56:37 - mmengine - INFO - Epoch(train) [4][1160/2569] lr: 1.6000e-02 eta: 1 day, 3:58:13 time: 0.2703 data_time: 0.0079 memory: 5828 grad_norm: 3.7521 loss: 3.1206 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 3.1206 2023/06/04 16:56:43 - mmengine - INFO - Epoch(train) [4][1180/2569] lr: 1.6000e-02 eta: 1 day, 3:58:07 time: 0.2663 data_time: 0.0075 memory: 5828 grad_norm: 3.7435 loss: 2.9593 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.9593 2023/06/04 16:56:48 - mmengine - INFO - Epoch(train) [4][1200/2569] lr: 1.6000e-02 eta: 1 day, 3:58:02 time: 0.2685 data_time: 0.0074 memory: 5828 grad_norm: 3.7692 loss: 3.2732 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.2732 2023/06/04 16:56:53 - mmengine - INFO - Epoch(train) [4][1220/2569] lr: 1.6000e-02 eta: 1 day, 3:57:56 time: 0.2666 data_time: 0.0074 memory: 5828 grad_norm: 3.7375 loss: 2.7532 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7532 2023/06/04 16:56:59 - mmengine - INFO - Epoch(train) [4][1240/2569] lr: 1.6000e-02 eta: 1 day, 3:57:51 time: 0.2677 data_time: 0.0075 memory: 5828 grad_norm: 3.8361 loss: 2.4617 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4617 2023/06/04 16:57:04 - mmengine - INFO - Epoch(train) [4][1260/2569] lr: 1.6000e-02 eta: 1 day, 3:57:49 time: 0.2713 data_time: 0.0073 memory: 5828 grad_norm: 3.7405 loss: 2.4759 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4759 2023/06/04 16:57:10 - mmengine - INFO - Epoch(train) [4][1280/2569] lr: 1.6000e-02 eta: 1 day, 3:57:45 time: 0.2695 data_time: 0.0074 memory: 5828 grad_norm: 3.7991 loss: 3.0968 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 3.0968 2023/06/04 16:57:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 16:57:15 - mmengine - INFO - Epoch(train) [4][1300/2569] lr: 1.6000e-02 eta: 1 day, 3:57:38 time: 0.2654 data_time: 0.0076 memory: 5828 grad_norm: 3.7802 loss: 3.1373 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.1373 2023/06/04 16:57:20 - mmengine - INFO - Epoch(train) [4][1320/2569] lr: 1.6000e-02 eta: 1 day, 3:57:33 time: 0.2671 data_time: 0.0091 memory: 5828 grad_norm: 3.7807 loss: 3.0372 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.0372 2023/06/04 16:57:26 - mmengine - INFO - Epoch(train) [4][1340/2569] lr: 1.6000e-02 eta: 1 day, 3:57:29 time: 0.2694 data_time: 0.0079 memory: 5828 grad_norm: 3.7449 loss: 3.1042 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.1042 2023/06/04 16:57:31 - mmengine - INFO - Epoch(train) [4][1360/2569] lr: 1.6000e-02 eta: 1 day, 3:57:22 time: 0.2656 data_time: 0.0070 memory: 5828 grad_norm: 3.7658 loss: 2.8720 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8720 2023/06/04 16:57:36 - mmengine - INFO - Epoch(train) [4][1380/2569] lr: 1.6000e-02 eta: 1 day, 3:57:13 time: 0.2631 data_time: 0.0079 memory: 5828 grad_norm: 3.7055 loss: 3.2938 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.2938 2023/06/04 16:57:41 - mmengine - INFO - Epoch(train) [4][1400/2569] lr: 1.6000e-02 eta: 1 day, 3:57:04 time: 0.2627 data_time: 0.0077 memory: 5828 grad_norm: 3.7698 loss: 2.6071 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6071 2023/06/04 16:57:47 - mmengine - INFO - Epoch(train) [4][1420/2569] lr: 1.6000e-02 eta: 1 day, 3:56:58 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 3.7793 loss: 3.1743 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 3.1743 2023/06/04 16:57:52 - mmengine - INFO - Epoch(train) [4][1440/2569] lr: 1.6000e-02 eta: 1 day, 3:57:02 time: 0.2788 data_time: 0.0075 memory: 5828 grad_norm: 3.7509 loss: 3.0123 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0123 2023/06/04 16:57:58 - mmengine - INFO - Epoch(train) [4][1460/2569] lr: 1.6000e-02 eta: 1 day, 3:56:57 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 3.7642 loss: 2.9756 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9756 2023/06/04 16:58:03 - mmengine - INFO - Epoch(train) [4][1480/2569] lr: 1.6000e-02 eta: 1 day, 3:57:01 time: 0.2784 data_time: 0.0078 memory: 5828 grad_norm: 3.8076 loss: 3.2405 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2405 2023/06/04 16:58:09 - mmengine - INFO - Epoch(train) [4][1500/2569] lr: 1.6000e-02 eta: 1 day, 3:56:58 time: 0.2698 data_time: 0.0077 memory: 5828 grad_norm: 3.8051 loss: 2.8228 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8228 2023/06/04 16:58:14 - mmengine - INFO - Epoch(train) [4][1520/2569] lr: 1.6000e-02 eta: 1 day, 3:56:55 time: 0.2704 data_time: 0.0071 memory: 5828 grad_norm: 3.7698 loss: 2.7512 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7512 2023/06/04 16:58:19 - mmengine - INFO - Epoch(train) [4][1540/2569] lr: 1.6000e-02 eta: 1 day, 3:56:43 time: 0.2604 data_time: 0.0076 memory: 5828 grad_norm: 3.7182 loss: 2.7387 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7387 2023/06/04 16:58:25 - mmengine - INFO - Epoch(train) [4][1560/2569] lr: 1.6000e-02 eta: 1 day, 3:56:40 time: 0.2695 data_time: 0.0076 memory: 5828 grad_norm: 3.7255 loss: 2.7881 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7881 2023/06/04 16:58:30 - mmengine - INFO - Epoch(train) [4][1580/2569] lr: 1.6000e-02 eta: 1 day, 3:56:32 time: 0.2648 data_time: 0.0077 memory: 5828 grad_norm: 3.7645 loss: 3.1181 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.1181 2023/06/04 16:58:35 - mmengine - INFO - Epoch(train) [4][1600/2569] lr: 1.6000e-02 eta: 1 day, 3:56:26 time: 0.2667 data_time: 0.0077 memory: 5828 grad_norm: 3.8156 loss: 2.6608 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6608 2023/06/04 16:58:41 - mmengine - INFO - Epoch(train) [4][1620/2569] lr: 1.6000e-02 eta: 1 day, 3:56:15 time: 0.2599 data_time: 0.0070 memory: 5828 grad_norm: 3.7333 loss: 3.1783 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.1783 2023/06/04 16:58:46 - mmengine - INFO - Epoch(train) [4][1640/2569] lr: 1.6000e-02 eta: 1 day, 3:56:04 time: 0.2612 data_time: 0.0076 memory: 5828 grad_norm: 3.7305 loss: 3.3087 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.3087 2023/06/04 16:58:51 - mmengine - INFO - Epoch(train) [4][1660/2569] lr: 1.6000e-02 eta: 1 day, 3:55:55 time: 0.2631 data_time: 0.0076 memory: 5828 grad_norm: 3.7630 loss: 2.6989 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6989 2023/06/04 16:58:56 - mmengine - INFO - Epoch(train) [4][1680/2569] lr: 1.6000e-02 eta: 1 day, 3:55:51 time: 0.2688 data_time: 0.0075 memory: 5828 grad_norm: 3.7483 loss: 3.1376 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1376 2023/06/04 16:59:02 - mmengine - INFO - Epoch(train) [4][1700/2569] lr: 1.6000e-02 eta: 1 day, 3:55:43 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 3.7923 loss: 3.2075 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 3.2075 2023/06/04 16:59:07 - mmengine - INFO - Epoch(train) [4][1720/2569] lr: 1.6000e-02 eta: 1 day, 3:55:47 time: 0.2794 data_time: 0.0080 memory: 5828 grad_norm: 3.7802 loss: 3.2265 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.2265 2023/06/04 16:59:12 - mmengine - INFO - Epoch(train) [4][1740/2569] lr: 1.6000e-02 eta: 1 day, 3:55:36 time: 0.2594 data_time: 0.0079 memory: 5828 grad_norm: 3.6917 loss: 2.8187 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.8187 2023/06/04 16:59:18 - mmengine - INFO - Epoch(train) [4][1760/2569] lr: 1.6000e-02 eta: 1 day, 3:55:25 time: 0.2607 data_time: 0.0082 memory: 5828 grad_norm: 3.7866 loss: 2.8170 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8170 2023/06/04 16:59:23 - mmengine - INFO - Epoch(train) [4][1780/2569] lr: 1.6000e-02 eta: 1 day, 3:55:12 time: 0.2585 data_time: 0.0077 memory: 5828 grad_norm: 3.7415 loss: 3.1552 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.1552 2023/06/04 16:59:28 - mmengine - INFO - Epoch(train) [4][1800/2569] lr: 1.6000e-02 eta: 1 day, 3:55:01 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 3.7330 loss: 3.2557 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.2557 2023/06/04 16:59:33 - mmengine - INFO - Epoch(train) [4][1820/2569] lr: 1.6000e-02 eta: 1 day, 3:54:55 time: 0.2663 data_time: 0.0078 memory: 5828 grad_norm: 3.7326 loss: 3.1281 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.1281 2023/06/04 16:59:39 - mmengine - INFO - Epoch(train) [4][1840/2569] lr: 1.6000e-02 eta: 1 day, 3:54:50 time: 0.2683 data_time: 0.0080 memory: 5828 grad_norm: 3.7715 loss: 2.6869 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6869 2023/06/04 16:59:44 - mmengine - INFO - Epoch(train) [4][1860/2569] lr: 1.6000e-02 eta: 1 day, 3:54:43 time: 0.2643 data_time: 0.0076 memory: 5828 grad_norm: 3.7938 loss: 2.9567 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.9567 2023/06/04 16:59:49 - mmengine - INFO - Epoch(train) [4][1880/2569] lr: 1.6000e-02 eta: 1 day, 3:54:32 time: 0.2602 data_time: 0.0078 memory: 5828 grad_norm: 3.7588 loss: 3.1552 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1552 2023/06/04 16:59:55 - mmengine - INFO - Epoch(train) [4][1900/2569] lr: 1.6000e-02 eta: 1 day, 3:54:28 time: 0.2690 data_time: 0.0077 memory: 5828 grad_norm: 3.7382 loss: 2.8983 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8983 2023/06/04 17:00:00 - mmengine - INFO - Epoch(train) [4][1920/2569] lr: 1.6000e-02 eta: 1 day, 3:54:21 time: 0.2655 data_time: 0.0076 memory: 5828 grad_norm: 3.6667 loss: 2.9062 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9062 2023/06/04 17:00:05 - mmengine - INFO - Epoch(train) [4][1940/2569] lr: 1.6000e-02 eta: 1 day, 3:54:19 time: 0.2715 data_time: 0.0074 memory: 5828 grad_norm: 3.7253 loss: 2.7107 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7107 2023/06/04 17:00:11 - mmengine - INFO - Epoch(train) [4][1960/2569] lr: 1.6000e-02 eta: 1 day, 3:54:10 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.7226 loss: 2.8434 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8434 2023/06/04 17:00:16 - mmengine - INFO - Epoch(train) [4][1980/2569] lr: 1.6000e-02 eta: 1 day, 3:54:03 time: 0.2653 data_time: 0.0078 memory: 5828 grad_norm: 3.7383 loss: 2.9170 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9170 2023/06/04 17:00:21 - mmengine - INFO - Epoch(train) [4][2000/2569] lr: 1.6000e-02 eta: 1 day, 3:53:53 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 3.6996 loss: 3.1496 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1496 2023/06/04 17:00:26 - mmengine - INFO - Epoch(train) [4][2020/2569] lr: 1.6000e-02 eta: 1 day, 3:53:47 time: 0.2659 data_time: 0.0077 memory: 5828 grad_norm: 3.6614 loss: 2.8920 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.8920 2023/06/04 17:00:32 - mmengine - INFO - Epoch(train) [4][2040/2569] lr: 1.6000e-02 eta: 1 day, 3:53:39 time: 0.2640 data_time: 0.0067 memory: 5828 grad_norm: 3.7386 loss: 2.9460 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9460 2023/06/04 17:00:37 - mmengine - INFO - Epoch(train) [4][2060/2569] lr: 1.6000e-02 eta: 1 day, 3:53:30 time: 0.2629 data_time: 0.0077 memory: 5828 grad_norm: 3.7503 loss: 3.0582 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.0582 2023/06/04 17:00:42 - mmengine - INFO - Epoch(train) [4][2080/2569] lr: 1.6000e-02 eta: 1 day, 3:53:20 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 3.7952 loss: 2.8592 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8592 2023/06/04 17:00:47 - mmengine - INFO - Epoch(train) [4][2100/2569] lr: 1.6000e-02 eta: 1 day, 3:53:10 time: 0.2606 data_time: 0.0076 memory: 5828 grad_norm: 3.7711 loss: 2.9242 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9242 2023/06/04 17:00:53 - mmengine - INFO - Epoch(train) [4][2120/2569] lr: 1.6000e-02 eta: 1 day, 3:53:10 time: 0.2739 data_time: 0.0085 memory: 5828 grad_norm: 3.7744 loss: 3.2012 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.2012 2023/06/04 17:00:58 - mmengine - INFO - Epoch(train) [4][2140/2569] lr: 1.6000e-02 eta: 1 day, 3:52:59 time: 0.2608 data_time: 0.0075 memory: 5828 grad_norm: 3.7655 loss: 3.1887 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.1887 2023/06/04 17:01:03 - mmengine - INFO - Epoch(train) [4][2160/2569] lr: 1.6000e-02 eta: 1 day, 3:52:49 time: 0.2614 data_time: 0.0075 memory: 5828 grad_norm: 3.7605 loss: 2.4020 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4020 2023/06/04 17:01:09 - mmengine - INFO - Epoch(train) [4][2180/2569] lr: 1.6000e-02 eta: 1 day, 3:52:42 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 3.7114 loss: 2.4048 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4048 2023/06/04 17:01:14 - mmengine - INFO - Epoch(train) [4][2200/2569] lr: 1.6000e-02 eta: 1 day, 3:52:31 time: 0.2598 data_time: 0.0073 memory: 5828 grad_norm: 3.7032 loss: 3.2016 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 3.2016 2023/06/04 17:01:19 - mmengine - INFO - Epoch(train) [4][2220/2569] lr: 1.6000e-02 eta: 1 day, 3:52:25 time: 0.2671 data_time: 0.0079 memory: 5828 grad_norm: 3.7016 loss: 2.9487 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9487 2023/06/04 17:01:25 - mmengine - INFO - Epoch(train) [4][2240/2569] lr: 1.6000e-02 eta: 1 day, 3:52:22 time: 0.2703 data_time: 0.0075 memory: 5828 grad_norm: 3.7202 loss: 2.8044 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.8044 2023/06/04 17:01:30 - mmengine - INFO - Epoch(train) [4][2260/2569] lr: 1.6000e-02 eta: 1 day, 3:52:21 time: 0.2736 data_time: 0.0077 memory: 5828 grad_norm: 3.7303 loss: 3.1011 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.1011 2023/06/04 17:01:35 - mmengine - INFO - Epoch(train) [4][2280/2569] lr: 1.6000e-02 eta: 1 day, 3:52:15 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 3.7612 loss: 2.6679 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6679 2023/06/04 17:01:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:01:41 - mmengine - INFO - Epoch(train) [4][2300/2569] lr: 1.6000e-02 eta: 1 day, 3:52:28 time: 0.2914 data_time: 0.0074 memory: 5828 grad_norm: 3.7075 loss: 3.0321 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 3.0321 2023/06/04 17:01:47 - mmengine - INFO - Epoch(train) [4][2320/2569] lr: 1.6000e-02 eta: 1 day, 3:52:23 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 3.7025 loss: 2.8799 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8799 2023/06/04 17:01:52 - mmengine - INFO - Epoch(train) [4][2340/2569] lr: 1.6000e-02 eta: 1 day, 3:52:15 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.6923 loss: 2.5658 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5658 2023/06/04 17:01:57 - mmengine - INFO - Epoch(train) [4][2360/2569] lr: 1.6000e-02 eta: 1 day, 3:52:05 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 3.6822 loss: 2.6152 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6152 2023/06/04 17:02:02 - mmengine - INFO - Epoch(train) [4][2380/2569] lr: 1.6000e-02 eta: 1 day, 3:52:00 time: 0.2669 data_time: 0.0080 memory: 5828 grad_norm: 3.7728 loss: 2.6602 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6602 2023/06/04 17:02:08 - mmengine - INFO - Epoch(train) [4][2400/2569] lr: 1.6000e-02 eta: 1 day, 3:51:50 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 3.7029 loss: 2.7599 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.7599 2023/06/04 17:02:13 - mmengine - INFO - Epoch(train) [4][2420/2569] lr: 1.6000e-02 eta: 1 day, 3:51:43 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 3.6957 loss: 3.0347 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0347 2023/06/04 17:02:18 - mmengine - INFO - Epoch(train) [4][2440/2569] lr: 1.6000e-02 eta: 1 day, 3:51:33 time: 0.2601 data_time: 0.0077 memory: 5828 grad_norm: 3.6739 loss: 3.2501 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 3.2501 2023/06/04 17:02:23 - mmengine - INFO - Epoch(train) [4][2460/2569] lr: 1.6000e-02 eta: 1 day, 3:51:25 time: 0.2637 data_time: 0.0077 memory: 5828 grad_norm: 3.6828 loss: 2.6441 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6441 2023/06/04 17:02:29 - mmengine - INFO - Epoch(train) [4][2480/2569] lr: 1.6000e-02 eta: 1 day, 3:51:23 time: 0.2715 data_time: 0.0076 memory: 5828 grad_norm: 3.6860 loss: 2.6718 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6718 2023/06/04 17:02:34 - mmengine - INFO - Epoch(train) [4][2500/2569] lr: 1.6000e-02 eta: 1 day, 3:51:16 time: 0.2659 data_time: 0.0078 memory: 5828 grad_norm: 3.6886 loss: 2.5905 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5905 2023/06/04 17:02:39 - mmengine - INFO - Epoch(train) [4][2520/2569] lr: 1.6000e-02 eta: 1 day, 3:51:09 time: 0.2645 data_time: 0.0082 memory: 5828 grad_norm: 3.7656 loss: 2.9328 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9328 2023/06/04 17:02:45 - mmengine - INFO - Epoch(train) [4][2540/2569] lr: 1.6000e-02 eta: 1 day, 3:51:00 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 3.7193 loss: 2.9099 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9099 2023/06/04 17:02:50 - mmengine - INFO - Epoch(train) [4][2560/2569] lr: 1.6000e-02 eta: 1 day, 3:50:56 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 3.6978 loss: 2.8657 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.8657 2023/06/04 17:02:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:02:52 - mmengine - INFO - Epoch(train) [4][2569/2569] lr: 1.6000e-02 eta: 1 day, 3:50:46 time: 0.2621 data_time: 0.0067 memory: 5828 grad_norm: 3.7015 loss: 2.9267 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.9267 2023/06/04 17:02:52 - mmengine - INFO - Saving checkpoint at 4 epochs 2023/06/04 17:03:01 - mmengine - INFO - Epoch(train) [5][ 20/2569] lr: 2.0000e-02 eta: 1 day, 3:51:11 time: 0.3081 data_time: 0.0583 memory: 5828 grad_norm: 3.7741 loss: 2.8696 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8696 2023/06/04 17:03:06 - mmengine - INFO - Epoch(train) [5][ 40/2569] lr: 2.0000e-02 eta: 1 day, 3:51:04 time: 0.2659 data_time: 0.0069 memory: 5828 grad_norm: 3.7096 loss: 2.9265 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9265 2023/06/04 17:03:11 - mmengine - INFO - Epoch(train) [5][ 60/2569] lr: 2.0000e-02 eta: 1 day, 3:50:57 time: 0.2644 data_time: 0.0084 memory: 5828 grad_norm: 3.6726 loss: 2.9703 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9703 2023/06/04 17:03:17 - mmengine - INFO - Epoch(train) [5][ 80/2569] lr: 2.0000e-02 eta: 1 day, 3:50:51 time: 0.2659 data_time: 0.0070 memory: 5828 grad_norm: 3.7315 loss: 2.8862 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8862 2023/06/04 17:03:22 - mmengine - INFO - Epoch(train) [5][ 100/2569] lr: 2.0000e-02 eta: 1 day, 3:50:44 time: 0.2655 data_time: 0.0080 memory: 5828 grad_norm: 3.7779 loss: 2.9870 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9870 2023/06/04 17:03:27 - mmengine - INFO - Epoch(train) [5][ 120/2569] lr: 2.0000e-02 eta: 1 day, 3:50:42 time: 0.2721 data_time: 0.0073 memory: 5828 grad_norm: 3.7101 loss: 2.5992 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5992 2023/06/04 17:03:33 - mmengine - INFO - Epoch(train) [5][ 140/2569] lr: 2.0000e-02 eta: 1 day, 3:50:31 time: 0.2600 data_time: 0.0073 memory: 5828 grad_norm: 3.6476 loss: 3.0251 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0251 2023/06/04 17:03:38 - mmengine - INFO - Epoch(train) [5][ 160/2569] lr: 2.0000e-02 eta: 1 day, 3:50:31 time: 0.2748 data_time: 0.0075 memory: 5828 grad_norm: 3.6528 loss: 2.7742 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7742 2023/06/04 17:03:43 - mmengine - INFO - Epoch(train) [5][ 180/2569] lr: 2.0000e-02 eta: 1 day, 3:50:24 time: 0.2651 data_time: 0.0075 memory: 5828 grad_norm: 3.6699 loss: 2.8434 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.8434 2023/06/04 17:03:49 - mmengine - INFO - Epoch(train) [5][ 200/2569] lr: 2.0000e-02 eta: 1 day, 3:50:16 time: 0.2623 data_time: 0.0078 memory: 5828 grad_norm: 3.6854 loss: 2.7350 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7350 2023/06/04 17:03:54 - mmengine - INFO - Epoch(train) [5][ 220/2569] lr: 2.0000e-02 eta: 1 day, 3:50:09 time: 0.2652 data_time: 0.0073 memory: 5828 grad_norm: 3.7091 loss: 2.8909 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8909 2023/06/04 17:03:59 - mmengine - INFO - Epoch(train) [5][ 240/2569] lr: 2.0000e-02 eta: 1 day, 3:50:06 time: 0.2710 data_time: 0.0077 memory: 5828 grad_norm: 3.7191 loss: 2.8724 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8724 2023/06/04 17:04:05 - mmengine - INFO - Epoch(train) [5][ 260/2569] lr: 2.0000e-02 eta: 1 day, 3:49:59 time: 0.2651 data_time: 0.0075 memory: 5828 grad_norm: 3.6122 loss: 2.6930 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6930 2023/06/04 17:04:10 - mmengine - INFO - Epoch(train) [5][ 280/2569] lr: 2.0000e-02 eta: 1 day, 3:49:59 time: 0.2749 data_time: 0.0083 memory: 5828 grad_norm: 3.7658 loss: 2.8758 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8758 2023/06/04 17:04:16 - mmengine - INFO - Epoch(train) [5][ 300/2569] lr: 2.0000e-02 eta: 1 day, 3:49:55 time: 0.2696 data_time: 0.0074 memory: 5828 grad_norm: 3.6628 loss: 3.0518 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.0518 2023/06/04 17:04:21 - mmengine - INFO - Epoch(train) [5][ 320/2569] lr: 2.0000e-02 eta: 1 day, 3:49:51 time: 0.2689 data_time: 0.0078 memory: 5828 grad_norm: 3.6588 loss: 2.9250 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9250 2023/06/04 17:04:26 - mmengine - INFO - Epoch(train) [5][ 340/2569] lr: 2.0000e-02 eta: 1 day, 3:49:40 time: 0.2593 data_time: 0.0076 memory: 5828 grad_norm: 3.6895 loss: 2.8425 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8425 2023/06/04 17:04:31 - mmengine - INFO - Epoch(train) [5][ 360/2569] lr: 2.0000e-02 eta: 1 day, 3:49:33 time: 0.2654 data_time: 0.0077 memory: 5828 grad_norm: 3.6296 loss: 3.0839 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0839 2023/06/04 17:04:37 - mmengine - INFO - Epoch(train) [5][ 380/2569] lr: 2.0000e-02 eta: 1 day, 3:49:29 time: 0.2689 data_time: 0.0071 memory: 5828 grad_norm: 3.6778 loss: 2.6210 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6210 2023/06/04 17:04:42 - mmengine - INFO - Epoch(train) [5][ 400/2569] lr: 2.0000e-02 eta: 1 day, 3:49:19 time: 0.2611 data_time: 0.0085 memory: 5828 grad_norm: 3.6538 loss: 3.1308 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.1308 2023/06/04 17:04:47 - mmengine - INFO - Epoch(train) [5][ 420/2569] lr: 2.0000e-02 eta: 1 day, 3:49:10 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 3.6003 loss: 2.4158 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4158 2023/06/04 17:04:53 - mmengine - INFO - Epoch(train) [5][ 440/2569] lr: 2.0000e-02 eta: 1 day, 3:49:01 time: 0.2618 data_time: 0.0077 memory: 5828 grad_norm: 3.6402 loss: 2.9410 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.9410 2023/06/04 17:04:58 - mmengine - INFO - Epoch(train) [5][ 460/2569] lr: 2.0000e-02 eta: 1 day, 3:48:58 time: 0.2699 data_time: 0.0075 memory: 5828 grad_norm: 3.5985 loss: 2.9339 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9339 2023/06/04 17:05:03 - mmengine - INFO - Epoch(train) [5][ 480/2569] lr: 2.0000e-02 eta: 1 day, 3:48:51 time: 0.2663 data_time: 0.0079 memory: 5828 grad_norm: 3.6624 loss: 2.8791 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8791 2023/06/04 17:05:08 - mmengine - INFO - Epoch(train) [5][ 500/2569] lr: 2.0000e-02 eta: 1 day, 3:48:42 time: 0.2617 data_time: 0.0077 memory: 5828 grad_norm: 3.5920 loss: 2.9933 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9933 2023/06/04 17:05:14 - mmengine - INFO - Epoch(train) [5][ 520/2569] lr: 2.0000e-02 eta: 1 day, 3:48:39 time: 0.2702 data_time: 0.0076 memory: 5828 grad_norm: 3.6857 loss: 2.7852 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7852 2023/06/04 17:05:19 - mmengine - INFO - Epoch(train) [5][ 540/2569] lr: 2.0000e-02 eta: 1 day, 3:48:32 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 3.6222 loss: 2.8953 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8953 2023/06/04 17:05:25 - mmengine - INFO - Epoch(train) [5][ 560/2569] lr: 2.0000e-02 eta: 1 day, 3:48:28 time: 0.2703 data_time: 0.0077 memory: 5828 grad_norm: 3.5854 loss: 2.6374 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6374 2023/06/04 17:05:30 - mmengine - INFO - Epoch(train) [5][ 580/2569] lr: 2.0000e-02 eta: 1 day, 3:48:21 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.6064 loss: 3.1559 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1559 2023/06/04 17:05:35 - mmengine - INFO - Epoch(train) [5][ 600/2569] lr: 2.0000e-02 eta: 1 day, 3:48:15 time: 0.2669 data_time: 0.0080 memory: 5828 grad_norm: 3.6594 loss: 2.7868 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7868 2023/06/04 17:05:40 - mmengine - INFO - Epoch(train) [5][ 620/2569] lr: 2.0000e-02 eta: 1 day, 3:48:06 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 3.6872 loss: 3.0539 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0539 2023/06/04 17:05:46 - mmengine - INFO - Epoch(train) [5][ 640/2569] lr: 2.0000e-02 eta: 1 day, 3:48:02 time: 0.2698 data_time: 0.0076 memory: 5828 grad_norm: 3.6539 loss: 2.6009 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6009 2023/06/04 17:05:51 - mmengine - INFO - Epoch(train) [5][ 660/2569] lr: 2.0000e-02 eta: 1 day, 3:47:55 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 3.6156 loss: 3.2337 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.2337 2023/06/04 17:05:57 - mmengine - INFO - Epoch(train) [5][ 680/2569] lr: 2.0000e-02 eta: 1 day, 3:47:57 time: 0.2785 data_time: 0.0075 memory: 5828 grad_norm: 3.6451 loss: 2.9568 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9568 2023/06/04 17:06:02 - mmengine - INFO - Epoch(train) [5][ 700/2569] lr: 2.0000e-02 eta: 1 day, 3:47:50 time: 0.2644 data_time: 0.0080 memory: 5828 grad_norm: 3.6350 loss: 2.5262 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5262 2023/06/04 17:06:07 - mmengine - INFO - Epoch(train) [5][ 720/2569] lr: 2.0000e-02 eta: 1 day, 3:47:49 time: 0.2736 data_time: 0.0074 memory: 5828 grad_norm: 3.6497 loss: 2.8758 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8758 2023/06/04 17:06:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:06:13 - mmengine - INFO - Epoch(train) [5][ 740/2569] lr: 2.0000e-02 eta: 1 day, 3:47:46 time: 0.2705 data_time: 0.0074 memory: 5828 grad_norm: 3.6390 loss: 2.5961 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5961 2023/06/04 17:06:18 - mmengine - INFO - Epoch(train) [5][ 760/2569] lr: 2.0000e-02 eta: 1 day, 3:47:43 time: 0.2708 data_time: 0.0075 memory: 5828 grad_norm: 3.5789 loss: 3.0202 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0202 2023/06/04 17:06:24 - mmengine - INFO - Epoch(train) [5][ 780/2569] lr: 2.0000e-02 eta: 1 day, 3:47:36 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 3.6130 loss: 2.8719 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.8719 2023/06/04 17:06:29 - mmengine - INFO - Epoch(train) [5][ 800/2569] lr: 2.0000e-02 eta: 1 day, 3:47:30 time: 0.2651 data_time: 0.0076 memory: 5828 grad_norm: 3.5946 loss: 2.9315 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9315 2023/06/04 17:06:34 - mmengine - INFO - Epoch(train) [5][ 820/2569] lr: 2.0000e-02 eta: 1 day, 3:47:28 time: 0.2722 data_time: 0.0075 memory: 5828 grad_norm: 3.6939 loss: 2.7539 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7539 2023/06/04 17:06:40 - mmengine - INFO - Epoch(train) [5][ 840/2569] lr: 2.0000e-02 eta: 1 day, 3:47:20 time: 0.2637 data_time: 0.0076 memory: 5828 grad_norm: 3.6283 loss: 2.6360 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6360 2023/06/04 17:06:45 - mmengine - INFO - Epoch(train) [5][ 860/2569] lr: 2.0000e-02 eta: 1 day, 3:47:18 time: 0.2721 data_time: 0.0075 memory: 5828 grad_norm: 3.5840 loss: 2.8856 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8856 2023/06/04 17:06:50 - mmengine - INFO - Epoch(train) [5][ 880/2569] lr: 2.0000e-02 eta: 1 day, 3:47:11 time: 0.2661 data_time: 0.0075 memory: 5828 grad_norm: 3.6435 loss: 2.9854 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.9854 2023/06/04 17:06:56 - mmengine - INFO - Epoch(train) [5][ 900/2569] lr: 2.0000e-02 eta: 1 day, 3:47:14 time: 0.2795 data_time: 0.0073 memory: 5828 grad_norm: 3.6119 loss: 3.0340 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0340 2023/06/04 17:07:02 - mmengine - INFO - Epoch(train) [5][ 920/2569] lr: 2.0000e-02 eta: 1 day, 3:47:19 time: 0.2821 data_time: 0.0073 memory: 5828 grad_norm: 3.5789 loss: 2.6682 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6682 2023/06/04 17:07:07 - mmengine - INFO - Epoch(train) [5][ 940/2569] lr: 2.0000e-02 eta: 1 day, 3:47:16 time: 0.2716 data_time: 0.0071 memory: 5828 grad_norm: 3.5810 loss: 2.8719 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8719 2023/06/04 17:07:12 - mmengine - INFO - Epoch(train) [5][ 960/2569] lr: 2.0000e-02 eta: 1 day, 3:47:12 time: 0.2691 data_time: 0.0077 memory: 5828 grad_norm: 3.6032 loss: 2.9090 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9090 2023/06/04 17:07:18 - mmengine - INFO - Epoch(train) [5][ 980/2569] lr: 2.0000e-02 eta: 1 day, 3:47:10 time: 0.2722 data_time: 0.0074 memory: 5828 grad_norm: 3.5763 loss: 2.9494 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9494 2023/06/04 17:07:23 - mmengine - INFO - Epoch(train) [5][1000/2569] lr: 2.0000e-02 eta: 1 day, 3:47:02 time: 0.2634 data_time: 0.0078 memory: 5828 grad_norm: 3.6389 loss: 2.7182 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7182 2023/06/04 17:07:29 - mmengine - INFO - Epoch(train) [5][1020/2569] lr: 2.0000e-02 eta: 1 day, 3:47:00 time: 0.2723 data_time: 0.0076 memory: 5828 grad_norm: 3.5817 loss: 2.8046 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8046 2023/06/04 17:07:34 - mmengine - INFO - Epoch(train) [5][1040/2569] lr: 2.0000e-02 eta: 1 day, 3:46:51 time: 0.2620 data_time: 0.0074 memory: 5828 grad_norm: 3.5423 loss: 2.4678 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4678 2023/06/04 17:07:39 - mmengine - INFO - Epoch(train) [5][1060/2569] lr: 2.0000e-02 eta: 1 day, 3:46:40 time: 0.2596 data_time: 0.0079 memory: 5828 grad_norm: 3.6020 loss: 2.7710 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7710 2023/06/04 17:07:44 - mmengine - INFO - Epoch(train) [5][1080/2569] lr: 2.0000e-02 eta: 1 day, 3:46:31 time: 0.2608 data_time: 0.0072 memory: 5828 grad_norm: 3.5764 loss: 2.7453 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7453 2023/06/04 17:07:49 - mmengine - INFO - Epoch(train) [5][1100/2569] lr: 2.0000e-02 eta: 1 day, 3:46:21 time: 0.2606 data_time: 0.0077 memory: 5828 grad_norm: 3.5412 loss: 2.7639 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7639 2023/06/04 17:07:55 - mmengine - INFO - Epoch(train) [5][1120/2569] lr: 2.0000e-02 eta: 1 day, 3:46:14 time: 0.2650 data_time: 0.0080 memory: 5828 grad_norm: 3.5917 loss: 3.0968 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0968 2023/06/04 17:08:00 - mmengine - INFO - Epoch(train) [5][1140/2569] lr: 2.0000e-02 eta: 1 day, 3:46:04 time: 0.2598 data_time: 0.0077 memory: 5828 grad_norm: 3.5387 loss: 2.7025 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7025 2023/06/04 17:08:05 - mmengine - INFO - Epoch(train) [5][1160/2569] lr: 2.0000e-02 eta: 1 day, 3:46:01 time: 0.2719 data_time: 0.0075 memory: 5828 grad_norm: 3.5516 loss: 2.8688 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8688 2023/06/04 17:08:11 - mmengine - INFO - Epoch(train) [5][1180/2569] lr: 2.0000e-02 eta: 1 day, 3:45:51 time: 0.2595 data_time: 0.0075 memory: 5828 grad_norm: 3.5619 loss: 3.1870 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.1870 2023/06/04 17:08:16 - mmengine - INFO - Epoch(train) [5][1200/2569] lr: 2.0000e-02 eta: 1 day, 3:45:42 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 3.5582 loss: 2.6888 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6888 2023/06/04 17:08:21 - mmengine - INFO - Epoch(train) [5][1220/2569] lr: 2.0000e-02 eta: 1 day, 3:45:32 time: 0.2596 data_time: 0.0073 memory: 5828 grad_norm: 3.5884 loss: 2.8080 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8080 2023/06/04 17:08:26 - mmengine - INFO - Epoch(train) [5][1240/2569] lr: 2.0000e-02 eta: 1 day, 3:45:23 time: 0.2612 data_time: 0.0084 memory: 5828 grad_norm: 3.6052 loss: 2.8294 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8294 2023/06/04 17:08:31 - mmengine - INFO - Epoch(train) [5][1260/2569] lr: 2.0000e-02 eta: 1 day, 3:45:13 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 3.6370 loss: 3.1340 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1340 2023/06/04 17:08:37 - mmengine - INFO - Epoch(train) [5][1280/2569] lr: 2.0000e-02 eta: 1 day, 3:45:07 time: 0.2665 data_time: 0.0072 memory: 5828 grad_norm: 3.6555 loss: 2.8950 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.8950 2023/06/04 17:08:42 - mmengine - INFO - Epoch(train) [5][1300/2569] lr: 2.0000e-02 eta: 1 day, 3:44:57 time: 0.2595 data_time: 0.0078 memory: 5828 grad_norm: 3.5749 loss: 2.7665 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7665 2023/06/04 17:08:47 - mmengine - INFO - Epoch(train) [5][1320/2569] lr: 2.0000e-02 eta: 1 day, 3:44:53 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 3.5575 loss: 2.7635 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7635 2023/06/04 17:08:53 - mmengine - INFO - Epoch(train) [5][1340/2569] lr: 2.0000e-02 eta: 1 day, 3:44:43 time: 0.2599 data_time: 0.0080 memory: 5828 grad_norm: 3.6265 loss: 2.7695 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7695 2023/06/04 17:08:58 - mmengine - INFO - Epoch(train) [5][1360/2569] lr: 2.0000e-02 eta: 1 day, 3:44:34 time: 0.2627 data_time: 0.0078 memory: 5828 grad_norm: 3.6159 loss: 3.1295 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1295 2023/06/04 17:09:03 - mmengine - INFO - Epoch(train) [5][1380/2569] lr: 2.0000e-02 eta: 1 day, 3:44:26 time: 0.2632 data_time: 0.0077 memory: 5828 grad_norm: 3.5986 loss: 2.7455 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7455 2023/06/04 17:09:08 - mmengine - INFO - Epoch(train) [5][1400/2569] lr: 2.0000e-02 eta: 1 day, 3:44:23 time: 0.2699 data_time: 0.0076 memory: 5828 grad_norm: 3.5793 loss: 2.6809 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6809 2023/06/04 17:09:14 - mmengine - INFO - Epoch(train) [5][1420/2569] lr: 2.0000e-02 eta: 1 day, 3:44:16 time: 0.2649 data_time: 0.0079 memory: 5828 grad_norm: 3.5754 loss: 2.9783 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9783 2023/06/04 17:09:19 - mmengine - INFO - Epoch(train) [5][1440/2569] lr: 2.0000e-02 eta: 1 day, 3:44:09 time: 0.2649 data_time: 0.0084 memory: 5828 grad_norm: 3.6089 loss: 3.0459 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 3.0459 2023/06/04 17:09:24 - mmengine - INFO - Epoch(train) [5][1460/2569] lr: 2.0000e-02 eta: 1 day, 3:43:59 time: 0.2592 data_time: 0.0076 memory: 5828 grad_norm: 3.5683 loss: 3.0970 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0970 2023/06/04 17:09:30 - mmengine - INFO - Epoch(train) [5][1480/2569] lr: 2.0000e-02 eta: 1 day, 3:43:59 time: 0.2762 data_time: 0.0072 memory: 5828 grad_norm: 3.5488 loss: 2.9381 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9381 2023/06/04 17:09:35 - mmengine - INFO - Epoch(train) [5][1500/2569] lr: 2.0000e-02 eta: 1 day, 3:43:51 time: 0.2637 data_time: 0.0077 memory: 5828 grad_norm: 3.5844 loss: 2.9862 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9862 2023/06/04 17:09:40 - mmengine - INFO - Epoch(train) [5][1520/2569] lr: 2.0000e-02 eta: 1 day, 3:43:43 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 3.5874 loss: 2.5339 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5339 2023/06/04 17:09:46 - mmengine - INFO - Epoch(train) [5][1540/2569] lr: 2.0000e-02 eta: 1 day, 3:43:37 time: 0.2658 data_time: 0.0073 memory: 5828 grad_norm: 3.5700 loss: 2.7184 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7184 2023/06/04 17:09:51 - mmengine - INFO - Epoch(train) [5][1560/2569] lr: 2.0000e-02 eta: 1 day, 3:43:28 time: 0.2614 data_time: 0.0077 memory: 5828 grad_norm: 3.5587 loss: 2.8127 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8127 2023/06/04 17:09:56 - mmengine - INFO - Epoch(train) [5][1580/2569] lr: 2.0000e-02 eta: 1 day, 3:43:20 time: 0.2625 data_time: 0.0076 memory: 5828 grad_norm: 3.5855 loss: 2.9252 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9252 2023/06/04 17:10:01 - mmengine - INFO - Epoch(train) [5][1600/2569] lr: 2.0000e-02 eta: 1 day, 3:43:10 time: 0.2604 data_time: 0.0073 memory: 5828 grad_norm: 3.5765 loss: 2.6870 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6870 2023/06/04 17:10:07 - mmengine - INFO - Epoch(train) [5][1620/2569] lr: 2.0000e-02 eta: 1 day, 3:43:01 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 3.5833 loss: 2.6555 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6555 2023/06/04 17:10:12 - mmengine - INFO - Epoch(train) [5][1640/2569] lr: 2.0000e-02 eta: 1 day, 3:42:55 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 3.6174 loss: 2.8571 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8571 2023/06/04 17:10:17 - mmengine - INFO - Epoch(train) [5][1660/2569] lr: 2.0000e-02 eta: 1 day, 3:42:51 time: 0.2692 data_time: 0.0074 memory: 5828 grad_norm: 3.5997 loss: 2.9192 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9192 2023/06/04 17:10:23 - mmengine - INFO - Epoch(train) [5][1680/2569] lr: 2.0000e-02 eta: 1 day, 3:42:45 time: 0.2669 data_time: 0.0076 memory: 5828 grad_norm: 3.5471 loss: 2.9701 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9701 2023/06/04 17:10:28 - mmengine - INFO - Epoch(train) [5][1700/2569] lr: 2.0000e-02 eta: 1 day, 3:42:36 time: 0.2614 data_time: 0.0080 memory: 5828 grad_norm: 3.6180 loss: 2.9928 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9928 2023/06/04 17:10:33 - mmengine - INFO - Epoch(train) [5][1720/2569] lr: 2.0000e-02 eta: 1 day, 3:42:36 time: 0.2744 data_time: 0.0078 memory: 5828 grad_norm: 3.6202 loss: 2.6932 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6932 2023/06/04 17:10:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:10:39 - mmengine - INFO - Epoch(train) [5][1740/2569] lr: 2.0000e-02 eta: 1 day, 3:42:27 time: 0.2626 data_time: 0.0078 memory: 5828 grad_norm: 3.5935 loss: 3.1303 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.1303 2023/06/04 17:10:44 - mmengine - INFO - Epoch(train) [5][1760/2569] lr: 2.0000e-02 eta: 1 day, 3:42:25 time: 0.2728 data_time: 0.0074 memory: 5828 grad_norm: 3.6041 loss: 2.8650 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8650 2023/06/04 17:10:49 - mmengine - INFO - Epoch(train) [5][1780/2569] lr: 2.0000e-02 eta: 1 day, 3:42:22 time: 0.2700 data_time: 0.0075 memory: 5828 grad_norm: 3.5496 loss: 3.1583 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 3.1583 2023/06/04 17:10:55 - mmengine - INFO - Epoch(train) [5][1800/2569] lr: 2.0000e-02 eta: 1 day, 3:42:13 time: 0.2618 data_time: 0.0080 memory: 5828 grad_norm: 3.5993 loss: 3.0828 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0828 2023/06/04 17:11:00 - mmengine - INFO - Epoch(train) [5][1820/2569] lr: 2.0000e-02 eta: 1 day, 3:42:03 time: 0.2586 data_time: 0.0077 memory: 5828 grad_norm: 3.6042 loss: 2.8736 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8736 2023/06/04 17:11:05 - mmengine - INFO - Epoch(train) [5][1840/2569] lr: 2.0000e-02 eta: 1 day, 3:41:56 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.5528 loss: 2.5624 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5624 2023/06/04 17:11:10 - mmengine - INFO - Epoch(train) [5][1860/2569] lr: 2.0000e-02 eta: 1 day, 3:41:47 time: 0.2611 data_time: 0.0076 memory: 5828 grad_norm: 3.5886 loss: 2.6541 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6541 2023/06/04 17:11:16 - mmengine - INFO - Epoch(train) [5][1880/2569] lr: 2.0000e-02 eta: 1 day, 3:41:42 time: 0.2688 data_time: 0.0079 memory: 5828 grad_norm: 3.5864 loss: 2.9460 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9460 2023/06/04 17:11:21 - mmengine - INFO - Epoch(train) [5][1900/2569] lr: 2.0000e-02 eta: 1 day, 3:41:39 time: 0.2702 data_time: 0.0079 memory: 5828 grad_norm: 3.5696 loss: 2.8859 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8859 2023/06/04 17:11:26 - mmengine - INFO - Epoch(train) [5][1920/2569] lr: 2.0000e-02 eta: 1 day, 3:41:33 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 3.5564 loss: 2.9080 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9080 2023/06/04 17:11:32 - mmengine - INFO - Epoch(train) [5][1940/2569] lr: 2.0000e-02 eta: 1 day, 3:41:30 time: 0.2707 data_time: 0.0071 memory: 5828 grad_norm: 3.6343 loss: 2.9718 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9718 2023/06/04 17:11:37 - mmengine - INFO - Epoch(train) [5][1960/2569] lr: 2.0000e-02 eta: 1 day, 3:41:24 time: 0.2668 data_time: 0.0074 memory: 5828 grad_norm: 3.5273 loss: 2.9269 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9269 2023/06/04 17:11:42 - mmengine - INFO - Epoch(train) [5][1980/2569] lr: 2.0000e-02 eta: 1 day, 3:41:14 time: 0.2596 data_time: 0.0079 memory: 5828 grad_norm: 3.5198 loss: 2.7471 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7471 2023/06/04 17:11:48 - mmengine - INFO - Epoch(train) [5][2000/2569] lr: 2.0000e-02 eta: 1 day, 3:41:06 time: 0.2625 data_time: 0.0077 memory: 5828 grad_norm: 3.4728 loss: 3.0436 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0436 2023/06/04 17:11:53 - mmengine - INFO - Epoch(train) [5][2020/2569] lr: 2.0000e-02 eta: 1 day, 3:40:59 time: 0.2648 data_time: 0.0087 memory: 5828 grad_norm: 3.5244 loss: 2.7321 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7321 2023/06/04 17:11:58 - mmengine - INFO - Epoch(train) [5][2040/2569] lr: 2.0000e-02 eta: 1 day, 3:40:50 time: 0.2598 data_time: 0.0070 memory: 5828 grad_norm: 3.5692 loss: 2.9990 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.9990 2023/06/04 17:12:03 - mmengine - INFO - Epoch(train) [5][2060/2569] lr: 2.0000e-02 eta: 1 day, 3:40:43 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 3.5515 loss: 2.5683 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5683 2023/06/04 17:12:09 - mmengine - INFO - Epoch(train) [5][2080/2569] lr: 2.0000e-02 eta: 1 day, 3:40:32 time: 0.2592 data_time: 0.0081 memory: 5828 grad_norm: 3.5812 loss: 2.7179 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7179 2023/06/04 17:12:14 - mmengine - INFO - Epoch(train) [5][2100/2569] lr: 2.0000e-02 eta: 1 day, 3:40:27 time: 0.2665 data_time: 0.0078 memory: 5828 grad_norm: 3.5266 loss: 2.9022 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9022 2023/06/04 17:12:19 - mmengine - INFO - Epoch(train) [5][2120/2569] lr: 2.0000e-02 eta: 1 day, 3:40:19 time: 0.2627 data_time: 0.0077 memory: 5828 grad_norm: 3.5100 loss: 2.8397 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8397 2023/06/04 17:12:25 - mmengine - INFO - Epoch(train) [5][2140/2569] lr: 2.0000e-02 eta: 1 day, 3:40:13 time: 0.2668 data_time: 0.0070 memory: 5828 grad_norm: 3.5863 loss: 2.8017 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8017 2023/06/04 17:12:30 - mmengine - INFO - Epoch(train) [5][2160/2569] lr: 2.0000e-02 eta: 1 day, 3:40:13 time: 0.2760 data_time: 0.0078 memory: 5828 grad_norm: 3.5553 loss: 2.7445 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7445 2023/06/04 17:12:35 - mmengine - INFO - Epoch(train) [5][2180/2569] lr: 2.0000e-02 eta: 1 day, 3:40:03 time: 0.2598 data_time: 0.0093 memory: 5828 grad_norm: 3.5365 loss: 2.8204 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8204 2023/06/04 17:12:41 - mmengine - INFO - Epoch(train) [5][2200/2569] lr: 2.0000e-02 eta: 1 day, 3:39:56 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 3.4764 loss: 2.7307 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7307 2023/06/04 17:12:46 - mmengine - INFO - Epoch(train) [5][2220/2569] lr: 2.0000e-02 eta: 1 day, 3:39:51 time: 0.2674 data_time: 0.0078 memory: 5828 grad_norm: 3.5503 loss: 2.8039 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8039 2023/06/04 17:12:51 - mmengine - INFO - Epoch(train) [5][2240/2569] lr: 2.0000e-02 eta: 1 day, 3:39:44 time: 0.2642 data_time: 0.0071 memory: 5828 grad_norm: 3.5495 loss: 2.7661 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7661 2023/06/04 17:12:57 - mmengine - INFO - Epoch(train) [5][2260/2569] lr: 2.0000e-02 eta: 1 day, 3:39:41 time: 0.2715 data_time: 0.0072 memory: 5828 grad_norm: 3.5062 loss: 2.9574 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9574 2023/06/04 17:13:02 - mmengine - INFO - Epoch(train) [5][2280/2569] lr: 2.0000e-02 eta: 1 day, 3:39:31 time: 0.2600 data_time: 0.0078 memory: 5828 grad_norm: 3.6175 loss: 2.9967 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9967 2023/06/04 17:13:07 - mmengine - INFO - Epoch(train) [5][2300/2569] lr: 2.0000e-02 eta: 1 day, 3:39:27 time: 0.2688 data_time: 0.0081 memory: 5828 grad_norm: 3.5752 loss: 2.8921 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8921 2023/06/04 17:13:12 - mmengine - INFO - Epoch(train) [5][2320/2569] lr: 2.0000e-02 eta: 1 day, 3:39:21 time: 0.2652 data_time: 0.0076 memory: 5828 grad_norm: 3.5569 loss: 2.9844 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9844 2023/06/04 17:13:18 - mmengine - INFO - Epoch(train) [5][2340/2569] lr: 2.0000e-02 eta: 1 day, 3:39:20 time: 0.2760 data_time: 0.0075 memory: 5828 grad_norm: 3.5539 loss: 2.9761 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.9761 2023/06/04 17:13:23 - mmengine - INFO - Epoch(train) [5][2360/2569] lr: 2.0000e-02 eta: 1 day, 3:39:10 time: 0.2590 data_time: 0.0077 memory: 5828 grad_norm: 3.4803 loss: 3.0049 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0049 2023/06/04 17:13:29 - mmengine - INFO - Epoch(train) [5][2380/2569] lr: 2.0000e-02 eta: 1 day, 3:39:07 time: 0.2703 data_time: 0.0079 memory: 5828 grad_norm: 3.5882 loss: 2.9510 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9510 2023/06/04 17:13:34 - mmengine - INFO - Epoch(train) [5][2400/2569] lr: 2.0000e-02 eta: 1 day, 3:38:59 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 3.5284 loss: 2.8188 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8188 2023/06/04 17:13:39 - mmengine - INFO - Epoch(train) [5][2420/2569] lr: 2.0000e-02 eta: 1 day, 3:38:52 time: 0.2650 data_time: 0.0077 memory: 5828 grad_norm: 3.5206 loss: 2.7459 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7459 2023/06/04 17:13:44 - mmengine - INFO - Epoch(train) [5][2440/2569] lr: 2.0000e-02 eta: 1 day, 3:38:46 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 3.5294 loss: 2.9633 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.9633 2023/06/04 17:13:50 - mmengine - INFO - Epoch(train) [5][2460/2569] lr: 2.0000e-02 eta: 1 day, 3:38:44 time: 0.2731 data_time: 0.0076 memory: 5828 grad_norm: 3.5588 loss: 2.8042 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8042 2023/06/04 17:13:55 - mmengine - INFO - Epoch(train) [5][2480/2569] lr: 2.0000e-02 eta: 1 day, 3:38:35 time: 0.2607 data_time: 0.0075 memory: 5828 grad_norm: 3.4702 loss: 2.7938 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7938 2023/06/04 17:14:00 - mmengine - INFO - Epoch(train) [5][2500/2569] lr: 2.0000e-02 eta: 1 day, 3:38:29 time: 0.2657 data_time: 0.0074 memory: 5828 grad_norm: 3.5795 loss: 2.6556 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6556 2023/06/04 17:14:06 - mmengine - INFO - Epoch(train) [5][2520/2569] lr: 2.0000e-02 eta: 1 day, 3:38:20 time: 0.2603 data_time: 0.0073 memory: 5828 grad_norm: 3.5089 loss: 2.7935 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7935 2023/06/04 17:14:11 - mmengine - INFO - Epoch(train) [5][2540/2569] lr: 2.0000e-02 eta: 1 day, 3:38:15 time: 0.2677 data_time: 0.0077 memory: 5828 grad_norm: 3.5311 loss: 2.9346 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9346 2023/06/04 17:14:16 - mmengine - INFO - Epoch(train) [5][2560/2569] lr: 2.0000e-02 eta: 1 day, 3:38:13 time: 0.2726 data_time: 0.0076 memory: 5828 grad_norm: 3.4890 loss: 2.5871 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5871 2023/06/04 17:14:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:14:19 - mmengine - INFO - Epoch(train) [5][2569/2569] lr: 2.0000e-02 eta: 1 day, 3:38:05 time: 0.2623 data_time: 0.0074 memory: 5828 grad_norm: 3.4652 loss: 2.4685 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.4685 2023/06/04 17:14:23 - mmengine - INFO - Epoch(val) [5][ 20/260] eta: 0:00:55 time: 0.2328 data_time: 0.1741 memory: 1238 2023/06/04 17:14:26 - mmengine - INFO - Epoch(val) [5][ 40/260] eta: 0:00:41 time: 0.1489 data_time: 0.0905 memory: 1238 2023/06/04 17:14:29 - mmengine - INFO - Epoch(val) [5][ 60/260] eta: 0:00:35 time: 0.1469 data_time: 0.0885 memory: 1238 2023/06/04 17:14:32 - mmengine - INFO - Epoch(val) [5][ 80/260] eta: 0:00:30 time: 0.1397 data_time: 0.0817 memory: 1238 2023/06/04 17:14:35 - mmengine - INFO - Epoch(val) [5][100/260] eta: 0:00:26 time: 0.1447 data_time: 0.0860 memory: 1238 2023/06/04 17:14:38 - mmengine - INFO - Epoch(val) [5][120/260] eta: 0:00:22 time: 0.1549 data_time: 0.0968 memory: 1238 2023/06/04 17:14:40 - mmengine - INFO - Epoch(val) [5][140/260] eta: 0:00:18 time: 0.1187 data_time: 0.0598 memory: 1238 2023/06/04 17:14:43 - mmengine - INFO - Epoch(val) [5][160/260] eta: 0:00:15 time: 0.1511 data_time: 0.0927 memory: 1238 2023/06/04 17:14:46 - mmengine - INFO - Epoch(val) [5][180/260] eta: 0:00:11 time: 0.1061 data_time: 0.0476 memory: 1238 2023/06/04 17:14:49 - mmengine - INFO - Epoch(val) [5][200/260] eta: 0:00:08 time: 0.1561 data_time: 0.0979 memory: 1238 2023/06/04 17:14:51 - mmengine - INFO - Epoch(val) [5][220/260] eta: 0:00:05 time: 0.1133 data_time: 0.0544 memory: 1238 2023/06/04 17:14:54 - mmengine - INFO - Epoch(val) [5][240/260] eta: 0:00:02 time: 0.1375 data_time: 0.0791 memory: 1238 2023/06/04 17:14:57 - mmengine - INFO - Epoch(val) [5][260/260] eta: 0:00:00 time: 0.1566 data_time: 0.0992 memory: 1238 2023/06/04 17:15:06 - mmengine - INFO - Epoch(val) [5][260/260] acc/top1: 0.4641 acc/top5: 0.7205 acc/mean1: 0.4539 data_time: 0.0883 time: 0.1467 2023/06/04 17:15:08 - mmengine - INFO - The best checkpoint with 0.4641 acc/top1 at 5 epoch is saved to best_acc_top1_epoch_5.pth. 2023/06/04 17:15:14 - mmengine - INFO - Epoch(train) [6][ 20/2569] lr: 2.4000e-02 eta: 1 day, 3:38:12 time: 0.2881 data_time: 0.0382 memory: 5828 grad_norm: 3.5051 loss: 3.0260 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 3.0260 2023/06/04 17:15:19 - mmengine - INFO - Epoch(train) [6][ 40/2569] lr: 2.4000e-02 eta: 1 day, 3:38:04 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 3.5691 loss: 2.7843 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7843 2023/06/04 17:15:25 - mmengine - INFO - Epoch(train) [6][ 60/2569] lr: 2.4000e-02 eta: 1 day, 3:38:02 time: 0.2733 data_time: 0.0071 memory: 5828 grad_norm: 3.4829 loss: 2.8789 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8789 2023/06/04 17:15:30 - mmengine - INFO - Epoch(train) [6][ 80/2569] lr: 2.4000e-02 eta: 1 day, 3:37:52 time: 0.2594 data_time: 0.0073 memory: 5828 grad_norm: 3.5663 loss: 2.9908 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.9908 2023/06/04 17:15:35 - mmengine - INFO - Epoch(train) [6][ 100/2569] lr: 2.4000e-02 eta: 1 day, 3:37:52 time: 0.2759 data_time: 0.0071 memory: 5828 grad_norm: 3.4567 loss: 2.7254 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7254 2023/06/04 17:15:40 - mmengine - INFO - Epoch(train) [6][ 120/2569] lr: 2.4000e-02 eta: 1 day, 3:37:44 time: 0.2626 data_time: 0.0075 memory: 5828 grad_norm: 3.5246 loss: 3.0628 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0628 2023/06/04 17:15:46 - mmengine - INFO - Epoch(train) [6][ 140/2569] lr: 2.4000e-02 eta: 1 day, 3:37:45 time: 0.2776 data_time: 0.0078 memory: 5828 grad_norm: 3.4969 loss: 2.7934 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7934 2023/06/04 17:15:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:15:52 - mmengine - INFO - Epoch(train) [6][ 160/2569] lr: 2.4000e-02 eta: 1 day, 3:37:46 time: 0.2786 data_time: 0.0072 memory: 5828 grad_norm: 3.5272 loss: 2.8460 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8460 2023/06/04 17:15:57 - mmengine - INFO - Epoch(train) [6][ 180/2569] lr: 2.4000e-02 eta: 1 day, 3:37:38 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 3.4958 loss: 3.4195 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.4195 2023/06/04 17:16:02 - mmengine - INFO - Epoch(train) [6][ 200/2569] lr: 2.4000e-02 eta: 1 day, 3:37:30 time: 0.2621 data_time: 0.0069 memory: 5828 grad_norm: 3.5492 loss: 3.0717 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.0717 2023/06/04 17:16:07 - mmengine - INFO - Epoch(train) [6][ 220/2569] lr: 2.4000e-02 eta: 1 day, 3:37:22 time: 0.2628 data_time: 0.0084 memory: 5828 grad_norm: 3.5058 loss: 2.6189 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6189 2023/06/04 17:16:13 - mmengine - INFO - Epoch(train) [6][ 240/2569] lr: 2.4000e-02 eta: 1 day, 3:37:17 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 3.5231 loss: 3.0136 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 3.0136 2023/06/04 17:16:18 - mmengine - INFO - Epoch(train) [6][ 260/2569] lr: 2.4000e-02 eta: 1 day, 3:37:10 time: 0.2649 data_time: 0.0076 memory: 5828 grad_norm: 3.4045 loss: 2.6883 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6883 2023/06/04 17:16:23 - mmengine - INFO - Epoch(train) [6][ 280/2569] lr: 2.4000e-02 eta: 1 day, 3:37:03 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 3.4771 loss: 3.0568 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0568 2023/06/04 17:16:29 - mmengine - INFO - Epoch(train) [6][ 300/2569] lr: 2.4000e-02 eta: 1 day, 3:36:57 time: 0.2655 data_time: 0.0072 memory: 5828 grad_norm: 3.4621 loss: 2.9189 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9189 2023/06/04 17:16:34 - mmengine - INFO - Epoch(train) [6][ 320/2569] lr: 2.4000e-02 eta: 1 day, 3:36:54 time: 0.2716 data_time: 0.0075 memory: 5828 grad_norm: 3.5019 loss: 2.8489 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8489 2023/06/04 17:16:39 - mmengine - INFO - Epoch(train) [6][ 340/2569] lr: 2.4000e-02 eta: 1 day, 3:36:46 time: 0.2616 data_time: 0.0075 memory: 5828 grad_norm: 3.5059 loss: 2.5528 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5528 2023/06/04 17:16:45 - mmengine - INFO - Epoch(train) [6][ 360/2569] lr: 2.4000e-02 eta: 1 day, 3:36:39 time: 0.2650 data_time: 0.0081 memory: 5828 grad_norm: 3.4441 loss: 2.4414 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4414 2023/06/04 17:16:50 - mmengine - INFO - Epoch(train) [6][ 380/2569] lr: 2.4000e-02 eta: 1 day, 3:36:32 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 3.5218 loss: 2.5262 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5262 2023/06/04 17:16:55 - mmengine - INFO - Epoch(train) [6][ 400/2569] lr: 2.4000e-02 eta: 1 day, 3:36:25 time: 0.2656 data_time: 0.0069 memory: 5828 grad_norm: 3.4677 loss: 2.7168 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7168 2023/06/04 17:17:00 - mmengine - INFO - Epoch(train) [6][ 420/2569] lr: 2.4000e-02 eta: 1 day, 3:36:20 time: 0.2671 data_time: 0.0077 memory: 5828 grad_norm: 3.4393 loss: 3.0829 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0829 2023/06/04 17:17:06 - mmengine - INFO - Epoch(train) [6][ 440/2569] lr: 2.4000e-02 eta: 1 day, 3:36:11 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 3.4223 loss: 2.7364 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 2.7364 2023/06/04 17:17:11 - mmengine - INFO - Epoch(train) [6][ 460/2569] lr: 2.4000e-02 eta: 1 day, 3:36:03 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 3.5247 loss: 2.8145 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8145 2023/06/04 17:17:16 - mmengine - INFO - Epoch(train) [6][ 480/2569] lr: 2.4000e-02 eta: 1 day, 3:35:55 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 3.5433 loss: 2.5565 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5565 2023/06/04 17:17:22 - mmengine - INFO - Epoch(train) [6][ 500/2569] lr: 2.4000e-02 eta: 1 day, 3:35:54 time: 0.2752 data_time: 0.0074 memory: 5828 grad_norm: 3.4699 loss: 3.1014 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.1014 2023/06/04 17:17:27 - mmengine - INFO - Epoch(train) [6][ 520/2569] lr: 2.4000e-02 eta: 1 day, 3:35:47 time: 0.2638 data_time: 0.0079 memory: 5828 grad_norm: 3.5216 loss: 2.8079 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8079 2023/06/04 17:17:32 - mmengine - INFO - Epoch(train) [6][ 540/2569] lr: 2.4000e-02 eta: 1 day, 3:35:40 time: 0.2645 data_time: 0.0079 memory: 5828 grad_norm: 3.4959 loss: 2.7377 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7377 2023/06/04 17:17:38 - mmengine - INFO - Epoch(train) [6][ 560/2569] lr: 2.4000e-02 eta: 1 day, 3:35:33 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.4470 loss: 2.7108 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7108 2023/06/04 17:17:43 - mmengine - INFO - Epoch(train) [6][ 580/2569] lr: 2.4000e-02 eta: 1 day, 3:35:30 time: 0.2717 data_time: 0.0073 memory: 5828 grad_norm: 3.5191 loss: 2.7939 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7939 2023/06/04 17:17:49 - mmengine - INFO - Epoch(train) [6][ 600/2569] lr: 2.4000e-02 eta: 1 day, 3:35:31 time: 0.2781 data_time: 0.0082 memory: 5828 grad_norm: 3.4559 loss: 2.5691 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5691 2023/06/04 17:17:54 - mmengine - INFO - Epoch(train) [6][ 620/2569] lr: 2.4000e-02 eta: 1 day, 3:35:27 time: 0.2700 data_time: 0.0079 memory: 5828 grad_norm: 3.4494 loss: 2.7110 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7110 2023/06/04 17:17:59 - mmengine - INFO - Epoch(train) [6][ 640/2569] lr: 2.4000e-02 eta: 1 day, 3:35:28 time: 0.2787 data_time: 0.0073 memory: 5828 grad_norm: 3.4283 loss: 2.7547 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7547 2023/06/04 17:18:05 - mmengine - INFO - Epoch(train) [6][ 660/2569] lr: 2.4000e-02 eta: 1 day, 3:35:19 time: 0.2606 data_time: 0.0076 memory: 5828 grad_norm: 3.4215 loss: 3.2247 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.2247 2023/06/04 17:18:10 - mmengine - INFO - Epoch(train) [6][ 680/2569] lr: 2.4000e-02 eta: 1 day, 3:35:13 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 3.4835 loss: 2.8054 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8054 2023/06/04 17:18:15 - mmengine - INFO - Epoch(train) [6][ 700/2569] lr: 2.4000e-02 eta: 1 day, 3:35:07 time: 0.2662 data_time: 0.0078 memory: 5828 grad_norm: 3.4500 loss: 2.5394 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5394 2023/06/04 17:18:21 - mmengine - INFO - Epoch(train) [6][ 720/2569] lr: 2.4000e-02 eta: 1 day, 3:35:03 time: 0.2689 data_time: 0.0083 memory: 5828 grad_norm: 3.4428 loss: 2.2957 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2957 2023/06/04 17:18:26 - mmengine - INFO - Epoch(train) [6][ 740/2569] lr: 2.4000e-02 eta: 1 day, 3:34:58 time: 0.2680 data_time: 0.0074 memory: 5828 grad_norm: 3.4033 loss: 2.5122 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5122 2023/06/04 17:18:31 - mmengine - INFO - Epoch(train) [6][ 760/2569] lr: 2.4000e-02 eta: 1 day, 3:34:49 time: 0.2603 data_time: 0.0078 memory: 5828 grad_norm: 3.5004 loss: 2.7575 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7575 2023/06/04 17:18:37 - mmengine - INFO - Epoch(train) [6][ 780/2569] lr: 2.4000e-02 eta: 1 day, 3:34:48 time: 0.2741 data_time: 0.0077 memory: 5828 grad_norm: 3.4599 loss: 2.6002 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6002 2023/06/04 17:18:42 - mmengine - INFO - Epoch(train) [6][ 800/2569] lr: 2.4000e-02 eta: 1 day, 3:34:39 time: 0.2605 data_time: 0.0080 memory: 5828 grad_norm: 3.4709 loss: 2.8401 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8401 2023/06/04 17:18:48 - mmengine - INFO - Epoch(train) [6][ 820/2569] lr: 2.4000e-02 eta: 1 day, 3:34:41 time: 0.2819 data_time: 0.0070 memory: 5828 grad_norm: 3.4605 loss: 2.5794 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5794 2023/06/04 17:18:53 - mmengine - INFO - Epoch(train) [6][ 840/2569] lr: 2.4000e-02 eta: 1 day, 3:34:35 time: 0.2646 data_time: 0.0080 memory: 5828 grad_norm: 3.4126 loss: 2.6988 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6988 2023/06/04 17:18:58 - mmengine - INFO - Epoch(train) [6][ 860/2569] lr: 2.4000e-02 eta: 1 day, 3:34:35 time: 0.2783 data_time: 0.0075 memory: 5828 grad_norm: 3.4141 loss: 2.4177 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4177 2023/06/04 17:19:04 - mmengine - INFO - Epoch(train) [6][ 880/2569] lr: 2.4000e-02 eta: 1 day, 3:34:28 time: 0.2642 data_time: 0.0076 memory: 5828 grad_norm: 3.4563 loss: 2.9378 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9378 2023/06/04 17:19:09 - mmengine - INFO - Epoch(train) [6][ 900/2569] lr: 2.4000e-02 eta: 1 day, 3:34:19 time: 0.2599 data_time: 0.0076 memory: 5828 grad_norm: 3.4329 loss: 3.0005 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0005 2023/06/04 17:19:14 - mmengine - INFO - Epoch(train) [6][ 920/2569] lr: 2.4000e-02 eta: 1 day, 3:34:15 time: 0.2685 data_time: 0.0076 memory: 5828 grad_norm: 3.4947 loss: 3.0166 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0166 2023/06/04 17:19:20 - mmengine - INFO - Epoch(train) [6][ 940/2569] lr: 2.4000e-02 eta: 1 day, 3:34:06 time: 0.2614 data_time: 0.0079 memory: 5828 grad_norm: 3.4558 loss: 2.8415 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8415 2023/06/04 17:19:25 - mmengine - INFO - Epoch(train) [6][ 960/2569] lr: 2.4000e-02 eta: 1 day, 3:34:03 time: 0.2709 data_time: 0.0076 memory: 5828 grad_norm: 3.4281 loss: 3.0809 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0809 2023/06/04 17:19:30 - mmengine - INFO - Epoch(train) [6][ 980/2569] lr: 2.4000e-02 eta: 1 day, 3:33:59 time: 0.2689 data_time: 0.0075 memory: 5828 grad_norm: 3.4509 loss: 2.7768 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7768 2023/06/04 17:19:36 - mmengine - INFO - Epoch(train) [6][1000/2569] lr: 2.4000e-02 eta: 1 day, 3:33:50 time: 0.2613 data_time: 0.0075 memory: 5828 grad_norm: 3.4271 loss: 2.7760 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7760 2023/06/04 17:19:41 - mmengine - INFO - Epoch(train) [6][1020/2569] lr: 2.4000e-02 eta: 1 day, 3:33:47 time: 0.2711 data_time: 0.0078 memory: 5828 grad_norm: 3.4650 loss: 3.1228 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1228 2023/06/04 17:19:46 - mmengine - INFO - Epoch(train) [6][1040/2569] lr: 2.4000e-02 eta: 1 day, 3:33:41 time: 0.2658 data_time: 0.0076 memory: 5828 grad_norm: 3.3707 loss: 2.6406 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6406 2023/06/04 17:19:52 - mmengine - INFO - Epoch(train) [6][1060/2569] lr: 2.4000e-02 eta: 1 day, 3:33:34 time: 0.2645 data_time: 0.0083 memory: 5828 grad_norm: 3.4282 loss: 3.0570 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 3.0570 2023/06/04 17:19:57 - mmengine - INFO - Epoch(train) [6][1080/2569] lr: 2.4000e-02 eta: 1 day, 3:33:26 time: 0.2615 data_time: 0.0080 memory: 5828 grad_norm: 3.4469 loss: 2.6695 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6695 2023/06/04 17:20:02 - mmengine - INFO - Epoch(train) [6][1100/2569] lr: 2.4000e-02 eta: 1 day, 3:33:17 time: 0.2604 data_time: 0.0078 memory: 5828 grad_norm: 3.4638 loss: 2.8380 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.8380 2023/06/04 17:20:07 - mmengine - INFO - Epoch(train) [6][1120/2569] lr: 2.4000e-02 eta: 1 day, 3:33:11 time: 0.2668 data_time: 0.0075 memory: 5828 grad_norm: 3.4068 loss: 2.7371 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7371 2023/06/04 17:20:13 - mmengine - INFO - Epoch(train) [6][1140/2569] lr: 2.4000e-02 eta: 1 day, 3:33:03 time: 0.2610 data_time: 0.0078 memory: 5828 grad_norm: 3.4123 loss: 2.7086 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7086 2023/06/04 17:20:17 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:20:18 - mmengine - INFO - Epoch(train) [6][1160/2569] lr: 2.4000e-02 eta: 1 day, 3:32:58 time: 0.2676 data_time: 0.0075 memory: 5828 grad_norm: 3.4239 loss: 2.8872 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8872 2023/06/04 17:20:23 - mmengine - INFO - Epoch(train) [6][1180/2569] lr: 2.4000e-02 eta: 1 day, 3:32:51 time: 0.2654 data_time: 0.0074 memory: 5828 grad_norm: 3.4312 loss: 2.7902 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7902 2023/06/04 17:20:29 - mmengine - INFO - Epoch(train) [6][1200/2569] lr: 2.4000e-02 eta: 1 day, 3:32:48 time: 0.2704 data_time: 0.0076 memory: 5828 grad_norm: 3.4386 loss: 3.0412 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0412 2023/06/04 17:20:34 - mmengine - INFO - Epoch(train) [6][1220/2569] lr: 2.4000e-02 eta: 1 day, 3:32:39 time: 0.2605 data_time: 0.0077 memory: 5828 grad_norm: 3.4651 loss: 2.7219 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7219 2023/06/04 17:20:39 - mmengine - INFO - Epoch(train) [6][1240/2569] lr: 2.4000e-02 eta: 1 day, 3:32:31 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 3.3964 loss: 2.5702 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5702 2023/06/04 17:20:44 - mmengine - INFO - Epoch(train) [6][1260/2569] lr: 2.4000e-02 eta: 1 day, 3:32:21 time: 0.2592 data_time: 0.0078 memory: 5828 grad_norm: 3.4328 loss: 2.6880 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6880 2023/06/04 17:20:50 - mmengine - INFO - Epoch(train) [6][1280/2569] lr: 2.4000e-02 eta: 1 day, 3:32:21 time: 0.2761 data_time: 0.0073 memory: 5828 grad_norm: 3.4092 loss: 2.5105 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5105 2023/06/04 17:20:55 - mmengine - INFO - Epoch(train) [6][1300/2569] lr: 2.4000e-02 eta: 1 day, 3:32:13 time: 0.2631 data_time: 0.0071 memory: 5828 grad_norm: 3.4494 loss: 2.7765 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7765 2023/06/04 17:21:00 - mmengine - INFO - Epoch(train) [6][1320/2569] lr: 2.4000e-02 eta: 1 day, 3:32:05 time: 0.2607 data_time: 0.0076 memory: 5828 grad_norm: 3.4112 loss: 2.6589 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6589 2023/06/04 17:21:06 - mmengine - INFO - Epoch(train) [6][1340/2569] lr: 2.4000e-02 eta: 1 day, 3:31:56 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 3.4417 loss: 2.9305 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.9305 2023/06/04 17:21:11 - mmengine - INFO - Epoch(train) [6][1360/2569] lr: 2.4000e-02 eta: 1 day, 3:31:48 time: 0.2607 data_time: 0.0075 memory: 5828 grad_norm: 3.3699 loss: 3.0141 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0141 2023/06/04 17:21:16 - mmengine - INFO - Epoch(train) [6][1380/2569] lr: 2.4000e-02 eta: 1 day, 3:31:42 time: 0.2664 data_time: 0.0075 memory: 5828 grad_norm: 3.4199 loss: 2.9816 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.9816 2023/06/04 17:21:21 - mmengine - INFO - Epoch(train) [6][1400/2569] lr: 2.4000e-02 eta: 1 day, 3:31:35 time: 0.2648 data_time: 0.0077 memory: 5828 grad_norm: 3.4752 loss: 3.0241 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.0241 2023/06/04 17:21:27 - mmengine - INFO - Epoch(train) [6][1420/2569] lr: 2.4000e-02 eta: 1 day, 3:31:35 time: 0.2762 data_time: 0.0075 memory: 5828 grad_norm: 3.4504 loss: 3.0694 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0694 2023/06/04 17:21:32 - mmengine - INFO - Epoch(train) [6][1440/2569] lr: 2.4000e-02 eta: 1 day, 3:31:31 time: 0.2695 data_time: 0.0077 memory: 5828 grad_norm: 3.4111 loss: 3.3163 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.3163 2023/06/04 17:21:38 - mmengine - INFO - Epoch(train) [6][1460/2569] lr: 2.4000e-02 eta: 1 day, 3:31:32 time: 0.2795 data_time: 0.0076 memory: 5828 grad_norm: 3.3812 loss: 3.0821 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.0821 2023/06/04 17:21:43 - mmengine - INFO - Epoch(train) [6][1480/2569] lr: 2.4000e-02 eta: 1 day, 3:31:24 time: 0.2619 data_time: 0.0070 memory: 5828 grad_norm: 3.4577 loss: 2.6636 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6636 2023/06/04 17:21:48 - mmengine - INFO - Epoch(train) [6][1500/2569] lr: 2.4000e-02 eta: 1 day, 3:31:18 time: 0.2654 data_time: 0.0078 memory: 5828 grad_norm: 3.4448 loss: 3.1287 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.1287 2023/06/04 17:21:54 - mmengine - INFO - Epoch(train) [6][1520/2569] lr: 2.4000e-02 eta: 1 day, 3:31:15 time: 0.2725 data_time: 0.0073 memory: 5828 grad_norm: 3.4159 loss: 2.4784 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4784 2023/06/04 17:21:59 - mmengine - INFO - Epoch(train) [6][1540/2569] lr: 2.4000e-02 eta: 1 day, 3:31:10 time: 0.2666 data_time: 0.0076 memory: 5828 grad_norm: 3.4018 loss: 2.6262 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6262 2023/06/04 17:22:05 - mmengine - INFO - Epoch(train) [6][1560/2569] lr: 2.4000e-02 eta: 1 day, 3:31:08 time: 0.2749 data_time: 0.0079 memory: 5828 grad_norm: 3.3824 loss: 2.9160 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9160 2023/06/04 17:22:10 - mmengine - INFO - Epoch(train) [6][1580/2569] lr: 2.4000e-02 eta: 1 day, 3:31:04 time: 0.2689 data_time: 0.0076 memory: 5828 grad_norm: 3.3306 loss: 2.4967 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4967 2023/06/04 17:22:15 - mmengine - INFO - Epoch(train) [6][1600/2569] lr: 2.4000e-02 eta: 1 day, 3:30:55 time: 0.2604 data_time: 0.0078 memory: 5828 grad_norm: 3.3707 loss: 2.7975 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7975 2023/06/04 17:22:21 - mmengine - INFO - Epoch(train) [6][1620/2569] lr: 2.4000e-02 eta: 1 day, 3:30:50 time: 0.2674 data_time: 0.0076 memory: 5828 grad_norm: 3.4302 loss: 3.0081 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0081 2023/06/04 17:22:26 - mmengine - INFO - Epoch(train) [6][1640/2569] lr: 2.4000e-02 eta: 1 day, 3:30:46 time: 0.2696 data_time: 0.0077 memory: 5828 grad_norm: 3.3580 loss: 2.7877 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7877 2023/06/04 17:22:31 - mmengine - INFO - Epoch(train) [6][1660/2569] lr: 2.4000e-02 eta: 1 day, 3:30:43 time: 0.2714 data_time: 0.0073 memory: 5828 grad_norm: 3.4831 loss: 2.5795 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5795 2023/06/04 17:22:37 - mmengine - INFO - Epoch(train) [6][1680/2569] lr: 2.4000e-02 eta: 1 day, 3:30:42 time: 0.2752 data_time: 0.0080 memory: 5828 grad_norm: 3.4652 loss: 2.8421 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8421 2023/06/04 17:22:42 - mmengine - INFO - Epoch(train) [6][1700/2569] lr: 2.4000e-02 eta: 1 day, 3:30:38 time: 0.2700 data_time: 0.0076 memory: 5828 grad_norm: 3.4259 loss: 2.9041 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9041 2023/06/04 17:22:48 - mmengine - INFO - Epoch(train) [6][1720/2569] lr: 2.4000e-02 eta: 1 day, 3:30:34 time: 0.2694 data_time: 0.0084 memory: 5828 grad_norm: 3.3934 loss: 2.7669 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7669 2023/06/04 17:22:53 - mmengine - INFO - Epoch(train) [6][1740/2569] lr: 2.4000e-02 eta: 1 day, 3:30:30 time: 0.2701 data_time: 0.0079 memory: 5828 grad_norm: 3.3811 loss: 2.7343 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7343 2023/06/04 17:22:59 - mmengine - INFO - Epoch(train) [6][1760/2569] lr: 2.4000e-02 eta: 1 day, 3:30:29 time: 0.2768 data_time: 0.0080 memory: 5828 grad_norm: 3.3822 loss: 2.7144 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7144 2023/06/04 17:23:04 - mmengine - INFO - Epoch(train) [6][1780/2569] lr: 2.4000e-02 eta: 1 day, 3:30:25 time: 0.2684 data_time: 0.0070 memory: 5828 grad_norm: 3.3559 loss: 2.6908 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6908 2023/06/04 17:23:09 - mmengine - INFO - Epoch(train) [6][1800/2569] lr: 2.4000e-02 eta: 1 day, 3:30:19 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 3.3999 loss: 2.9073 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9073 2023/06/04 17:23:15 - mmengine - INFO - Epoch(train) [6][1820/2569] lr: 2.4000e-02 eta: 1 day, 3:30:13 time: 0.2663 data_time: 0.0077 memory: 5828 grad_norm: 3.4451 loss: 2.8406 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8406 2023/06/04 17:23:20 - mmengine - INFO - Epoch(train) [6][1840/2569] lr: 2.4000e-02 eta: 1 day, 3:30:05 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 3.4277 loss: 2.6434 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6434 2023/06/04 17:23:25 - mmengine - INFO - Epoch(train) [6][1860/2569] lr: 2.4000e-02 eta: 1 day, 3:30:00 time: 0.2661 data_time: 0.0077 memory: 5828 grad_norm: 3.4084 loss: 2.8703 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8703 2023/06/04 17:23:31 - mmengine - INFO - Epoch(train) [6][1880/2569] lr: 2.4000e-02 eta: 1 day, 3:29:54 time: 0.2662 data_time: 0.0072 memory: 5828 grad_norm: 3.3814 loss: 2.8436 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8436 2023/06/04 17:23:36 - mmengine - INFO - Epoch(train) [6][1900/2569] lr: 2.4000e-02 eta: 1 day, 3:29:45 time: 0.2605 data_time: 0.0077 memory: 5828 grad_norm: 3.4601 loss: 2.6168 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6168 2023/06/04 17:23:41 - mmengine - INFO - Epoch(train) [6][1920/2569] lr: 2.4000e-02 eta: 1 day, 3:29:39 time: 0.2661 data_time: 0.0078 memory: 5828 grad_norm: 3.4191 loss: 2.4102 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4102 2023/06/04 17:23:47 - mmengine - INFO - Epoch(train) [6][1940/2569] lr: 2.4000e-02 eta: 1 day, 3:29:39 time: 0.2766 data_time: 0.0078 memory: 5828 grad_norm: 3.3554 loss: 2.7248 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7248 2023/06/04 17:23:52 - mmengine - INFO - Epoch(train) [6][1960/2569] lr: 2.4000e-02 eta: 1 day, 3:29:31 time: 0.2626 data_time: 0.0077 memory: 5828 grad_norm: 3.3759 loss: 2.9607 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9607 2023/06/04 17:23:57 - mmengine - INFO - Epoch(train) [6][1980/2569] lr: 2.4000e-02 eta: 1 day, 3:29:25 time: 0.2655 data_time: 0.0072 memory: 5828 grad_norm: 3.3666 loss: 2.7170 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7170 2023/06/04 17:24:03 - mmengine - INFO - Epoch(train) [6][2000/2569] lr: 2.4000e-02 eta: 1 day, 3:29:23 time: 0.2737 data_time: 0.0080 memory: 5828 grad_norm: 3.3214 loss: 2.7088 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7088 2023/06/04 17:24:08 - mmengine - INFO - Epoch(train) [6][2020/2569] lr: 2.4000e-02 eta: 1 day, 3:29:17 time: 0.2658 data_time: 0.0080 memory: 5828 grad_norm: 3.3459 loss: 2.7111 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7111 2023/06/04 17:24:13 - mmengine - INFO - Epoch(train) [6][2040/2569] lr: 2.4000e-02 eta: 1 day, 3:29:11 time: 0.2664 data_time: 0.0079 memory: 5828 grad_norm: 3.3932 loss: 2.6833 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6833 2023/06/04 17:24:19 - mmengine - INFO - Epoch(train) [6][2060/2569] lr: 2.4000e-02 eta: 1 day, 3:29:03 time: 0.2604 data_time: 0.0078 memory: 5828 grad_norm: 3.4350 loss: 2.9702 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9702 2023/06/04 17:24:24 - mmengine - INFO - Epoch(train) [6][2080/2569] lr: 2.4000e-02 eta: 1 day, 3:28:57 time: 0.2658 data_time: 0.0077 memory: 5828 grad_norm: 3.2912 loss: 2.7587 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7587 2023/06/04 17:24:30 - mmengine - INFO - Epoch(train) [6][2100/2569] lr: 2.4000e-02 eta: 1 day, 3:28:58 time: 0.2813 data_time: 0.0076 memory: 5828 grad_norm: 3.3550 loss: 2.4274 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4274 2023/06/04 17:24:35 - mmengine - INFO - Epoch(train) [6][2120/2569] lr: 2.4000e-02 eta: 1 day, 3:28:49 time: 0.2601 data_time: 0.0080 memory: 5828 grad_norm: 3.4388 loss: 3.1550 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.1550 2023/06/04 17:24:40 - mmengine - INFO - Epoch(train) [6][2140/2569] lr: 2.4000e-02 eta: 1 day, 3:28:41 time: 0.2601 data_time: 0.0078 memory: 5828 grad_norm: 3.3516 loss: 3.0280 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0280 2023/06/04 17:24:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:24:45 - mmengine - INFO - Epoch(train) [6][2160/2569] lr: 2.4000e-02 eta: 1 day, 3:28:35 time: 0.2658 data_time: 0.0075 memory: 5828 grad_norm: 3.3452 loss: 2.9456 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9456 2023/06/04 17:24:51 - mmengine - INFO - Epoch(train) [6][2180/2569] lr: 2.4000e-02 eta: 1 day, 3:28:27 time: 0.2629 data_time: 0.0077 memory: 5828 grad_norm: 3.3247 loss: 2.8042 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8042 2023/06/04 17:24:56 - mmengine - INFO - Epoch(train) [6][2200/2569] lr: 2.4000e-02 eta: 1 day, 3:28:19 time: 0.2610 data_time: 0.0073 memory: 5828 grad_norm: 3.3914 loss: 2.7783 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7783 2023/06/04 17:25:01 - mmengine - INFO - Epoch(train) [6][2220/2569] lr: 2.4000e-02 eta: 1 day, 3:28:11 time: 0.2619 data_time: 0.0071 memory: 5828 grad_norm: 3.3934 loss: 2.6409 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6409 2023/06/04 17:25:06 - mmengine - INFO - Epoch(train) [6][2240/2569] lr: 2.4000e-02 eta: 1 day, 3:28:04 time: 0.2625 data_time: 0.0077 memory: 5828 grad_norm: 3.3562 loss: 2.6825 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6825 2023/06/04 17:25:12 - mmengine - INFO - Epoch(train) [6][2260/2569] lr: 2.4000e-02 eta: 1 day, 3:27:58 time: 0.2658 data_time: 0.0079 memory: 5828 grad_norm: 3.4087 loss: 2.4160 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4160 2023/06/04 17:25:17 - mmengine - INFO - Epoch(train) [6][2280/2569] lr: 2.4000e-02 eta: 1 day, 3:27:53 time: 0.2683 data_time: 0.0085 memory: 5828 grad_norm: 3.4008 loss: 3.1127 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 3.1127 2023/06/04 17:25:22 - mmengine - INFO - Epoch(train) [6][2300/2569] lr: 2.4000e-02 eta: 1 day, 3:27:47 time: 0.2670 data_time: 0.0077 memory: 5828 grad_norm: 3.3480 loss: 3.0726 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0726 2023/06/04 17:25:27 - mmengine - INFO - Epoch(train) [6][2320/2569] lr: 2.4000e-02 eta: 1 day, 3:27:39 time: 0.2611 data_time: 0.0077 memory: 5828 grad_norm: 3.4267 loss: 3.0544 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0544 2023/06/04 17:25:33 - mmengine - INFO - Epoch(train) [6][2340/2569] lr: 2.4000e-02 eta: 1 day, 3:27:30 time: 0.2601 data_time: 0.0079 memory: 5828 grad_norm: 3.3605 loss: 2.6497 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6497 2023/06/04 17:25:38 - mmengine - INFO - Epoch(train) [6][2360/2569] lr: 2.4000e-02 eta: 1 day, 3:27:23 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 3.3299 loss: 2.6475 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6475 2023/06/04 17:25:43 - mmengine - INFO - Epoch(train) [6][2380/2569] lr: 2.4000e-02 eta: 1 day, 3:27:14 time: 0.2600 data_time: 0.0075 memory: 5828 grad_norm: 3.3919 loss: 2.7953 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7953 2023/06/04 17:25:48 - mmengine - INFO - Epoch(train) [6][2400/2569] lr: 2.4000e-02 eta: 1 day, 3:27:06 time: 0.2619 data_time: 0.0079 memory: 5828 grad_norm: 3.3882 loss: 2.7620 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7620 2023/06/04 17:25:54 - mmengine - INFO - Epoch(train) [6][2420/2569] lr: 2.4000e-02 eta: 1 day, 3:26:59 time: 0.2621 data_time: 0.0076 memory: 5828 grad_norm: 3.3485 loss: 2.9688 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9688 2023/06/04 17:25:59 - mmengine - INFO - Epoch(train) [6][2440/2569] lr: 2.4000e-02 eta: 1 day, 3:26:50 time: 0.2613 data_time: 0.0080 memory: 5828 grad_norm: 3.3809 loss: 2.7820 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.7820 2023/06/04 17:26:04 - mmengine - INFO - Epoch(train) [6][2460/2569] lr: 2.4000e-02 eta: 1 day, 3:26:50 time: 0.2770 data_time: 0.0076 memory: 5828 grad_norm: 3.3329 loss: 2.8047 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8047 2023/06/04 17:26:10 - mmengine - INFO - Epoch(train) [6][2480/2569] lr: 2.4000e-02 eta: 1 day, 3:26:41 time: 0.2599 data_time: 0.0078 memory: 5828 grad_norm: 3.3908 loss: 2.7180 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7180 2023/06/04 17:26:15 - mmengine - INFO - Epoch(train) [6][2500/2569] lr: 2.4000e-02 eta: 1 day, 3:26:38 time: 0.2707 data_time: 0.0073 memory: 5828 grad_norm: 3.3639 loss: 2.6176 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6176 2023/06/04 17:26:20 - mmengine - INFO - Epoch(train) [6][2520/2569] lr: 2.4000e-02 eta: 1 day, 3:26:31 time: 0.2649 data_time: 0.0076 memory: 5828 grad_norm: 3.3779 loss: 2.7506 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7506 2023/06/04 17:26:26 - mmengine - INFO - Epoch(train) [6][2540/2569] lr: 2.4000e-02 eta: 1 day, 3:26:28 time: 0.2724 data_time: 0.0078 memory: 5828 grad_norm: 3.3323 loss: 2.8184 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8184 2023/06/04 17:26:31 - mmengine - INFO - Epoch(train) [6][2560/2569] lr: 2.4000e-02 eta: 1 day, 3:26:27 time: 0.2749 data_time: 0.0075 memory: 5828 grad_norm: 3.3556 loss: 2.6039 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6039 2023/06/04 17:26:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:26:33 - mmengine - INFO - Epoch(train) [6][2569/2569] lr: 2.4000e-02 eta: 1 day, 3:26:19 time: 0.2472 data_time: 0.0073 memory: 5828 grad_norm: 3.3534 loss: 2.7053 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.7053 2023/06/04 17:26:40 - mmengine - INFO - Epoch(train) [7][ 20/2569] lr: 2.8000e-02 eta: 1 day, 3:26:54 time: 0.3510 data_time: 0.0510 memory: 5828 grad_norm: 3.3750 loss: 2.4082 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4082 2023/06/04 17:26:46 - mmengine - INFO - Epoch(train) [7][ 40/2569] lr: 2.8000e-02 eta: 1 day, 3:26:50 time: 0.2702 data_time: 0.0080 memory: 5828 grad_norm: 3.3819 loss: 2.8423 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8423 2023/06/04 17:26:51 - mmengine - INFO - Epoch(train) [7][ 60/2569] lr: 2.8000e-02 eta: 1 day, 3:26:44 time: 0.2656 data_time: 0.0076 memory: 5828 grad_norm: 3.3388 loss: 2.3918 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3918 2023/06/04 17:26:57 - mmengine - INFO - Epoch(train) [7][ 80/2569] lr: 2.8000e-02 eta: 1 day, 3:26:39 time: 0.2665 data_time: 0.0074 memory: 5828 grad_norm: 3.4351 loss: 2.7016 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7016 2023/06/04 17:27:02 - mmengine - INFO - Epoch(train) [7][ 100/2569] lr: 2.8000e-02 eta: 1 day, 3:26:35 time: 0.2714 data_time: 0.0085 memory: 5828 grad_norm: 3.2977 loss: 2.7758 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7758 2023/06/04 17:27:07 - mmengine - INFO - Epoch(train) [7][ 120/2569] lr: 2.8000e-02 eta: 1 day, 3:26:32 time: 0.2710 data_time: 0.0069 memory: 5828 grad_norm: 3.4084 loss: 3.0174 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0174 2023/06/04 17:27:13 - mmengine - INFO - Epoch(train) [7][ 140/2569] lr: 2.8000e-02 eta: 1 day, 3:26:25 time: 0.2634 data_time: 0.0076 memory: 5828 grad_norm: 3.3493 loss: 2.6714 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6714 2023/06/04 17:27:18 - mmengine - INFO - Epoch(train) [7][ 160/2569] lr: 2.8000e-02 eta: 1 day, 3:26:24 time: 0.2766 data_time: 0.0076 memory: 5828 grad_norm: 3.3910 loss: 2.8725 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8725 2023/06/04 17:27:23 - mmengine - INFO - Epoch(train) [7][ 180/2569] lr: 2.8000e-02 eta: 1 day, 3:26:18 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 3.3678 loss: 2.4821 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4821 2023/06/04 17:27:29 - mmengine - INFO - Epoch(train) [7][ 200/2569] lr: 2.8000e-02 eta: 1 day, 3:26:12 time: 0.2658 data_time: 0.0079 memory: 5828 grad_norm: 3.3064 loss: 2.7557 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7557 2023/06/04 17:27:35 - mmengine - INFO - Epoch(train) [7][ 220/2569] lr: 2.8000e-02 eta: 1 day, 3:26:16 time: 0.2884 data_time: 0.0076 memory: 5828 grad_norm: 3.3383 loss: 3.0728 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0728 2023/06/04 17:27:40 - mmengine - INFO - Epoch(train) [7][ 240/2569] lr: 2.8000e-02 eta: 1 day, 3:26:15 time: 0.2751 data_time: 0.0078 memory: 5828 grad_norm: 3.3061 loss: 2.6719 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6719 2023/06/04 17:27:45 - mmengine - INFO - Epoch(train) [7][ 260/2569] lr: 2.8000e-02 eta: 1 day, 3:26:11 time: 0.2696 data_time: 0.0079 memory: 5828 grad_norm: 3.3805 loss: 2.9012 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9012 2023/06/04 17:27:51 - mmengine - INFO - Epoch(train) [7][ 280/2569] lr: 2.8000e-02 eta: 1 day, 3:26:04 time: 0.2636 data_time: 0.0079 memory: 5828 grad_norm: 3.3370 loss: 2.5811 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5811 2023/06/04 17:27:56 - mmengine - INFO - Epoch(train) [7][ 300/2569] lr: 2.8000e-02 eta: 1 day, 3:25:58 time: 0.2665 data_time: 0.0077 memory: 5828 grad_norm: 3.3396 loss: 2.9386 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9386 2023/06/04 17:28:01 - mmengine - INFO - Epoch(train) [7][ 320/2569] lr: 2.8000e-02 eta: 1 day, 3:25:50 time: 0.2626 data_time: 0.0075 memory: 5828 grad_norm: 3.3534 loss: 2.5912 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5912 2023/06/04 17:28:07 - mmengine - INFO - Epoch(train) [7][ 340/2569] lr: 2.8000e-02 eta: 1 day, 3:25:44 time: 0.2648 data_time: 0.0078 memory: 5828 grad_norm: 3.3004 loss: 2.7368 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.7368 2023/06/04 17:28:12 - mmengine - INFO - Epoch(train) [7][ 360/2569] lr: 2.8000e-02 eta: 1 day, 3:25:37 time: 0.2639 data_time: 0.0076 memory: 5828 grad_norm: 3.3158 loss: 2.5290 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5290 2023/06/04 17:28:17 - mmengine - INFO - Epoch(train) [7][ 380/2569] lr: 2.8000e-02 eta: 1 day, 3:25:31 time: 0.2665 data_time: 0.0076 memory: 5828 grad_norm: 3.3077 loss: 2.7384 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7384 2023/06/04 17:28:23 - mmengine - INFO - Epoch(train) [7][ 400/2569] lr: 2.8000e-02 eta: 1 day, 3:25:28 time: 0.2713 data_time: 0.0074 memory: 5828 grad_norm: 3.3595 loss: 2.8330 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8330 2023/06/04 17:28:28 - mmengine - INFO - Epoch(train) [7][ 420/2569] lr: 2.8000e-02 eta: 1 day, 3:25:22 time: 0.2647 data_time: 0.0079 memory: 5828 grad_norm: 3.3398 loss: 2.8409 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8409 2023/06/04 17:28:33 - mmengine - INFO - Epoch(train) [7][ 440/2569] lr: 2.8000e-02 eta: 1 day, 3:25:14 time: 0.2623 data_time: 0.0077 memory: 5828 grad_norm: 3.3387 loss: 2.8630 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8630 2023/06/04 17:28:38 - mmengine - INFO - Epoch(train) [7][ 460/2569] lr: 2.8000e-02 eta: 1 day, 3:25:06 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 3.2747 loss: 2.5747 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5747 2023/06/04 17:28:44 - mmengine - INFO - Epoch(train) [7][ 480/2569] lr: 2.8000e-02 eta: 1 day, 3:24:59 time: 0.2629 data_time: 0.0074 memory: 5828 grad_norm: 3.2881 loss: 2.8620 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.8620 2023/06/04 17:28:49 - mmengine - INFO - Epoch(train) [7][ 500/2569] lr: 2.8000e-02 eta: 1 day, 3:24:53 time: 0.2655 data_time: 0.0082 memory: 5828 grad_norm: 3.2791 loss: 2.8373 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8373 2023/06/04 17:28:54 - mmengine - INFO - Epoch(train) [7][ 520/2569] lr: 2.8000e-02 eta: 1 day, 3:24:46 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.3625 loss: 3.0557 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0557 2023/06/04 17:28:59 - mmengine - INFO - Epoch(train) [7][ 540/2569] lr: 2.8000e-02 eta: 1 day, 3:24:38 time: 0.2608 data_time: 0.0077 memory: 5828 grad_norm: 3.3211 loss: 2.8175 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8175 2023/06/04 17:29:05 - mmengine - INFO - Epoch(train) [7][ 560/2569] lr: 2.8000e-02 eta: 1 day, 3:24:31 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 3.3513 loss: 3.3169 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.3169 2023/06/04 17:29:10 - mmengine - INFO - Epoch(train) [7][ 580/2569] lr: 2.8000e-02 eta: 1 day, 3:24:25 time: 0.2651 data_time: 0.0070 memory: 5828 grad_norm: 3.3159 loss: 2.3978 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3978 2023/06/04 17:29:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:29:16 - mmengine - INFO - Epoch(train) [7][ 600/2569] lr: 2.8000e-02 eta: 1 day, 3:24:22 time: 0.2728 data_time: 0.0074 memory: 5828 grad_norm: 3.2409 loss: 2.8802 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8802 2023/06/04 17:29:21 - mmengine - INFO - Epoch(train) [7][ 620/2569] lr: 2.8000e-02 eta: 1 day, 3:24:14 time: 0.2601 data_time: 0.0079 memory: 5828 grad_norm: 3.2589 loss: 2.8151 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8151 2023/06/04 17:29:26 - mmengine - INFO - Epoch(train) [7][ 640/2569] lr: 2.8000e-02 eta: 1 day, 3:24:07 time: 0.2645 data_time: 0.0084 memory: 5828 grad_norm: 3.2904 loss: 2.8176 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8176 2023/06/04 17:29:31 - mmengine - INFO - Epoch(train) [7][ 660/2569] lr: 2.8000e-02 eta: 1 day, 3:23:59 time: 0.2616 data_time: 0.0077 memory: 5828 grad_norm: 3.2587 loss: 2.7666 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7666 2023/06/04 17:29:37 - mmengine - INFO - Epoch(train) [7][ 680/2569] lr: 2.8000e-02 eta: 1 day, 3:23:57 time: 0.2738 data_time: 0.0078 memory: 5828 grad_norm: 3.2712 loss: 2.7227 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7227 2023/06/04 17:29:42 - mmengine - INFO - Epoch(train) [7][ 700/2569] lr: 2.8000e-02 eta: 1 day, 3:23:53 time: 0.2702 data_time: 0.0072 memory: 5828 grad_norm: 3.2606 loss: 2.6468 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6468 2023/06/04 17:29:47 - mmengine - INFO - Epoch(train) [7][ 720/2569] lr: 2.8000e-02 eta: 1 day, 3:23:47 time: 0.2651 data_time: 0.0080 memory: 5828 grad_norm: 3.2898 loss: 2.9544 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9544 2023/06/04 17:29:53 - mmengine - INFO - Epoch(train) [7][ 740/2569] lr: 2.8000e-02 eta: 1 day, 3:23:38 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 3.2681 loss: 2.8193 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8193 2023/06/04 17:29:58 - mmengine - INFO - Epoch(train) [7][ 760/2569] lr: 2.8000e-02 eta: 1 day, 3:23:33 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 3.2499 loss: 2.5443 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5443 2023/06/04 17:30:03 - mmengine - INFO - Epoch(train) [7][ 780/2569] lr: 2.8000e-02 eta: 1 day, 3:23:24 time: 0.2608 data_time: 0.0081 memory: 5828 grad_norm: 3.3040 loss: 2.7307 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7307 2023/06/04 17:30:08 - mmengine - INFO - Epoch(train) [7][ 800/2569] lr: 2.8000e-02 eta: 1 day, 3:23:17 time: 0.2632 data_time: 0.0082 memory: 5828 grad_norm: 3.3679 loss: 2.9159 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9159 2023/06/04 17:30:14 - mmengine - INFO - Epoch(train) [7][ 820/2569] lr: 2.8000e-02 eta: 1 day, 3:23:12 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 3.3362 loss: 2.7282 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7282 2023/06/04 17:30:19 - mmengine - INFO - Epoch(train) [7][ 840/2569] lr: 2.8000e-02 eta: 1 day, 3:23:11 time: 0.2787 data_time: 0.0073 memory: 5828 grad_norm: 3.2258 loss: 2.5125 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5125 2023/06/04 17:30:25 - mmengine - INFO - Epoch(train) [7][ 860/2569] lr: 2.8000e-02 eta: 1 day, 3:23:04 time: 0.2635 data_time: 0.0082 memory: 5828 grad_norm: 3.2747 loss: 2.7713 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.7713 2023/06/04 17:30:30 - mmengine - INFO - Epoch(train) [7][ 880/2569] lr: 2.8000e-02 eta: 1 day, 3:23:00 time: 0.2700 data_time: 0.0079 memory: 5828 grad_norm: 3.2282 loss: 2.5340 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5340 2023/06/04 17:30:35 - mmengine - INFO - Epoch(train) [7][ 900/2569] lr: 2.8000e-02 eta: 1 day, 3:22:54 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 3.2654 loss: 2.8236 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8236 2023/06/04 17:30:41 - mmengine - INFO - Epoch(train) [7][ 920/2569] lr: 2.8000e-02 eta: 1 day, 3:22:47 time: 0.2634 data_time: 0.0080 memory: 5828 grad_norm: 3.2687 loss: 2.6743 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6743 2023/06/04 17:30:46 - mmengine - INFO - Epoch(train) [7][ 940/2569] lr: 2.8000e-02 eta: 1 day, 3:22:42 time: 0.2667 data_time: 0.0071 memory: 5828 grad_norm: 3.3036 loss: 2.9015 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.9015 2023/06/04 17:30:51 - mmengine - INFO - Epoch(train) [7][ 960/2569] lr: 2.8000e-02 eta: 1 day, 3:22:40 time: 0.2738 data_time: 0.0078 memory: 5828 grad_norm: 3.2731 loss: 2.6645 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6645 2023/06/04 17:30:57 - mmengine - INFO - Epoch(train) [7][ 980/2569] lr: 2.8000e-02 eta: 1 day, 3:22:36 time: 0.2711 data_time: 0.0076 memory: 5828 grad_norm: 3.2943 loss: 2.9645 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.9645 2023/06/04 17:31:02 - mmengine - INFO - Epoch(train) [7][1000/2569] lr: 2.8000e-02 eta: 1 day, 3:22:31 time: 0.2683 data_time: 0.0079 memory: 5828 grad_norm: 3.3005 loss: 2.7608 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7608 2023/06/04 17:31:08 - mmengine - INFO - Epoch(train) [7][1020/2569] lr: 2.8000e-02 eta: 1 day, 3:22:27 time: 0.2705 data_time: 0.0076 memory: 5828 grad_norm: 3.3173 loss: 2.9061 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9061 2023/06/04 17:31:13 - mmengine - INFO - Epoch(train) [7][1040/2569] lr: 2.8000e-02 eta: 1 day, 3:22:23 time: 0.2692 data_time: 0.0084 memory: 5828 grad_norm: 3.3105 loss: 2.8847 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8847 2023/06/04 17:31:18 - mmengine - INFO - Epoch(train) [7][1060/2569] lr: 2.8000e-02 eta: 1 day, 3:22:16 time: 0.2637 data_time: 0.0069 memory: 5828 grad_norm: 3.2964 loss: 2.7591 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7591 2023/06/04 17:31:24 - mmengine - INFO - Epoch(train) [7][1080/2569] lr: 2.8000e-02 eta: 1 day, 3:22:13 time: 0.2716 data_time: 0.0077 memory: 5828 grad_norm: 3.2421 loss: 2.7574 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7574 2023/06/04 17:31:29 - mmengine - INFO - Epoch(train) [7][1100/2569] lr: 2.8000e-02 eta: 1 day, 3:22:05 time: 0.2622 data_time: 0.0078 memory: 5828 grad_norm: 3.2290 loss: 2.7490 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7490 2023/06/04 17:31:34 - mmengine - INFO - Epoch(train) [7][1120/2569] lr: 2.8000e-02 eta: 1 day, 3:22:01 time: 0.2696 data_time: 0.0084 memory: 5828 grad_norm: 3.2593 loss: 2.6727 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6727 2023/06/04 17:31:40 - mmengine - INFO - Epoch(train) [7][1140/2569] lr: 2.8000e-02 eta: 1 day, 3:21:54 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 3.2675 loss: 2.7810 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7810 2023/06/04 17:31:45 - mmengine - INFO - Epoch(train) [7][1160/2569] lr: 2.8000e-02 eta: 1 day, 3:21:46 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 3.3010 loss: 2.7359 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7359 2023/06/04 17:31:50 - mmengine - INFO - Epoch(train) [7][1180/2569] lr: 2.8000e-02 eta: 1 day, 3:21:38 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 3.2790 loss: 2.6967 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6967 2023/06/04 17:31:55 - mmengine - INFO - Epoch(train) [7][1200/2569] lr: 2.8000e-02 eta: 1 day, 3:21:31 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 3.2684 loss: 2.6210 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6210 2023/06/04 17:32:01 - mmengine - INFO - Epoch(train) [7][1220/2569] lr: 2.8000e-02 eta: 1 day, 3:21:22 time: 0.2601 data_time: 0.0079 memory: 5828 grad_norm: 3.1955 loss: 2.5199 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5199 2023/06/04 17:32:06 - mmengine - INFO - Epoch(train) [7][1240/2569] lr: 2.8000e-02 eta: 1 day, 3:21:20 time: 0.2753 data_time: 0.0078 memory: 5828 grad_norm: 3.3037 loss: 2.5679 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5679 2023/06/04 17:32:11 - mmengine - INFO - Epoch(train) [7][1260/2569] lr: 2.8000e-02 eta: 1 day, 3:21:12 time: 0.2599 data_time: 0.0074 memory: 5828 grad_norm: 3.2985 loss: 2.8965 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8965 2023/06/04 17:32:17 - mmengine - INFO - Epoch(train) [7][1280/2569] lr: 2.8000e-02 eta: 1 day, 3:21:08 time: 0.2698 data_time: 0.0079 memory: 5828 grad_norm: 3.3047 loss: 3.0198 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0198 2023/06/04 17:32:22 - mmengine - INFO - Epoch(train) [7][1300/2569] lr: 2.8000e-02 eta: 1 day, 3:21:01 time: 0.2628 data_time: 0.0081 memory: 5828 grad_norm: 3.3432 loss: 2.5342 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5342 2023/06/04 17:32:27 - mmengine - INFO - Epoch(train) [7][1320/2569] lr: 2.8000e-02 eta: 1 day, 3:20:52 time: 0.2596 data_time: 0.0074 memory: 5828 grad_norm: 3.2632 loss: 2.5102 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5102 2023/06/04 17:32:32 - mmengine - INFO - Epoch(train) [7][1340/2569] lr: 2.8000e-02 eta: 1 day, 3:20:45 time: 0.2637 data_time: 0.0078 memory: 5828 grad_norm: 3.3248 loss: 2.8275 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8275 2023/06/04 17:32:38 - mmengine - INFO - Epoch(train) [7][1360/2569] lr: 2.8000e-02 eta: 1 day, 3:20:37 time: 0.2605 data_time: 0.0083 memory: 5828 grad_norm: 3.2780 loss: 2.6818 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6818 2023/06/04 17:32:43 - mmengine - INFO - Epoch(train) [7][1380/2569] lr: 2.8000e-02 eta: 1 day, 3:20:32 time: 0.2677 data_time: 0.0092 memory: 5828 grad_norm: 3.2948 loss: 2.4655 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4655 2023/06/04 17:32:48 - mmengine - INFO - Epoch(train) [7][1400/2569] lr: 2.8000e-02 eta: 1 day, 3:20:23 time: 0.2592 data_time: 0.0081 memory: 5828 grad_norm: 3.2938 loss: 3.0734 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0734 2023/06/04 17:32:53 - mmengine - INFO - Epoch(train) [7][1420/2569] lr: 2.8000e-02 eta: 1 day, 3:20:18 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 3.2939 loss: 3.0140 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.0140 2023/06/04 17:32:59 - mmengine - INFO - Epoch(train) [7][1440/2569] lr: 2.8000e-02 eta: 1 day, 3:20:10 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 3.2515 loss: 2.8604 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8604 2023/06/04 17:33:04 - mmengine - INFO - Epoch(train) [7][1460/2569] lr: 2.8000e-02 eta: 1 day, 3:20:04 time: 0.2668 data_time: 0.0074 memory: 5828 grad_norm: 3.3191 loss: 2.8788 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8788 2023/06/04 17:33:09 - mmengine - INFO - Epoch(train) [7][1480/2569] lr: 2.8000e-02 eta: 1 day, 3:19:57 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 3.2451 loss: 2.6998 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6998 2023/06/04 17:33:14 - mmengine - INFO - Epoch(train) [7][1500/2569] lr: 2.8000e-02 eta: 1 day, 3:19:49 time: 0.2607 data_time: 0.0077 memory: 5828 grad_norm: 3.2865 loss: 2.9294 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9294 2023/06/04 17:33:20 - mmengine - INFO - Epoch(train) [7][1520/2569] lr: 2.8000e-02 eta: 1 day, 3:19:41 time: 0.2605 data_time: 0.0079 memory: 5828 grad_norm: 3.2507 loss: 2.9350 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9350 2023/06/04 17:33:25 - mmengine - INFO - Epoch(train) [7][1540/2569] lr: 2.8000e-02 eta: 1 day, 3:19:33 time: 0.2615 data_time: 0.0079 memory: 5828 grad_norm: 3.2123 loss: 2.5615 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5615 2023/06/04 17:33:30 - mmengine - INFO - Epoch(train) [7][1560/2569] lr: 2.8000e-02 eta: 1 day, 3:19:25 time: 0.2604 data_time: 0.0077 memory: 5828 grad_norm: 3.2467 loss: 2.8509 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8509 2023/06/04 17:33:36 - mmengine - INFO - Epoch(train) [7][1580/2569] lr: 2.8000e-02 eta: 1 day, 3:19:21 time: 0.2712 data_time: 0.0077 memory: 5828 grad_norm: 3.2709 loss: 2.8434 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8434 2023/06/04 17:33:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:33:41 - mmengine - INFO - Epoch(train) [7][1600/2569] lr: 2.8000e-02 eta: 1 day, 3:19:15 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 3.2350 loss: 2.9085 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9085 2023/06/04 17:33:46 - mmengine - INFO - Epoch(train) [7][1620/2569] lr: 2.8000e-02 eta: 1 day, 3:19:08 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 3.2721 loss: 2.9315 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.9315 2023/06/04 17:33:51 - mmengine - INFO - Epoch(train) [7][1640/2569] lr: 2.8000e-02 eta: 1 day, 3:19:00 time: 0.2612 data_time: 0.0079 memory: 5828 grad_norm: 3.2346 loss: 2.6890 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6890 2023/06/04 17:33:57 - mmengine - INFO - Epoch(train) [7][1660/2569] lr: 2.8000e-02 eta: 1 day, 3:18:57 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 3.2310 loss: 2.7409 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7409 2023/06/04 17:34:02 - mmengine - INFO - Epoch(train) [7][1680/2569] lr: 2.8000e-02 eta: 1 day, 3:18:49 time: 0.2614 data_time: 0.0087 memory: 5828 grad_norm: 3.3263 loss: 2.8006 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8006 2023/06/04 17:34:07 - mmengine - INFO - Epoch(train) [7][1700/2569] lr: 2.8000e-02 eta: 1 day, 3:18:41 time: 0.2616 data_time: 0.0077 memory: 5828 grad_norm: 3.2703 loss: 2.9729 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9729 2023/06/04 17:34:12 - mmengine - INFO - Epoch(train) [7][1720/2569] lr: 2.8000e-02 eta: 1 day, 3:18:34 time: 0.2620 data_time: 0.0080 memory: 5828 grad_norm: 3.2937 loss: 2.8447 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8447 2023/06/04 17:34:18 - mmengine - INFO - Epoch(train) [7][1740/2569] lr: 2.8000e-02 eta: 1 day, 3:18:27 time: 0.2647 data_time: 0.0079 memory: 5828 grad_norm: 3.2341 loss: 2.7618 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7618 2023/06/04 17:34:23 - mmengine - INFO - Epoch(train) [7][1760/2569] lr: 2.8000e-02 eta: 1 day, 3:18:21 time: 0.2646 data_time: 0.0082 memory: 5828 grad_norm: 3.2111 loss: 2.9356 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9356 2023/06/04 17:34:28 - mmengine - INFO - Epoch(train) [7][1780/2569] lr: 2.8000e-02 eta: 1 day, 3:18:15 time: 0.2649 data_time: 0.0075 memory: 5828 grad_norm: 3.2888 loss: 2.9870 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.9870 2023/06/04 17:34:34 - mmengine - INFO - Epoch(train) [7][1800/2569] lr: 2.8000e-02 eta: 1 day, 3:18:08 time: 0.2625 data_time: 0.0078 memory: 5828 grad_norm: 3.2381 loss: 2.7366 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7366 2023/06/04 17:34:39 - mmengine - INFO - Epoch(train) [7][1820/2569] lr: 2.8000e-02 eta: 1 day, 3:18:03 time: 0.2678 data_time: 0.0076 memory: 5828 grad_norm: 3.2727 loss: 2.4801 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4801 2023/06/04 17:34:44 - mmengine - INFO - Epoch(train) [7][1840/2569] lr: 2.8000e-02 eta: 1 day, 3:17:57 time: 0.2655 data_time: 0.0082 memory: 5828 grad_norm: 3.2419 loss: 2.8770 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8770 2023/06/04 17:34:50 - mmengine - INFO - Epoch(train) [7][1860/2569] lr: 2.8000e-02 eta: 1 day, 3:17:55 time: 0.2764 data_time: 0.0075 memory: 5828 grad_norm: 3.2613 loss: 2.6574 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6574 2023/06/04 17:34:55 - mmengine - INFO - Epoch(train) [7][1880/2569] lr: 2.8000e-02 eta: 1 day, 3:17:47 time: 0.2598 data_time: 0.0079 memory: 5828 grad_norm: 3.3025 loss: 2.8833 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8833 2023/06/04 17:35:01 - mmengine - INFO - Epoch(train) [7][1900/2569] lr: 2.8000e-02 eta: 1 day, 3:17:45 time: 0.2749 data_time: 0.0075 memory: 5828 grad_norm: 3.2563 loss: 2.8613 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8613 2023/06/04 17:35:06 - mmengine - INFO - Epoch(train) [7][1920/2569] lr: 2.8000e-02 eta: 1 day, 3:17:39 time: 0.2656 data_time: 0.0077 memory: 5828 grad_norm: 3.2648 loss: 2.5421 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5421 2023/06/04 17:35:11 - mmengine - INFO - Epoch(train) [7][1940/2569] lr: 2.8000e-02 eta: 1 day, 3:17:37 time: 0.2758 data_time: 0.0075 memory: 5828 grad_norm: 3.2185 loss: 2.8983 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8983 2023/06/04 17:35:17 - mmengine - INFO - Epoch(train) [7][1960/2569] lr: 2.8000e-02 eta: 1 day, 3:17:30 time: 0.2618 data_time: 0.0080 memory: 5828 grad_norm: 3.2108 loss: 2.7510 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7510 2023/06/04 17:35:22 - mmengine - INFO - Epoch(train) [7][1980/2569] lr: 2.8000e-02 eta: 1 day, 3:17:24 time: 0.2663 data_time: 0.0078 memory: 5828 grad_norm: 3.2287 loss: 2.6829 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6829 2023/06/04 17:35:27 - mmengine - INFO - Epoch(train) [7][2000/2569] lr: 2.8000e-02 eta: 1 day, 3:17:18 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 3.2248 loss: 2.3670 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3670 2023/06/04 17:35:32 - mmengine - INFO - Epoch(train) [7][2020/2569] lr: 2.8000e-02 eta: 1 day, 3:17:09 time: 0.2587 data_time: 0.0077 memory: 5828 grad_norm: 3.1686 loss: 3.0459 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.0459 2023/06/04 17:35:38 - mmengine - INFO - Epoch(train) [7][2040/2569] lr: 2.8000e-02 eta: 1 day, 3:17:02 time: 0.2629 data_time: 0.0080 memory: 5828 grad_norm: 3.2053 loss: 2.7835 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7835 2023/06/04 17:35:43 - mmengine - INFO - Epoch(train) [7][2060/2569] lr: 2.8000e-02 eta: 1 day, 3:16:56 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 3.2263 loss: 2.6129 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6129 2023/06/04 17:35:48 - mmengine - INFO - Epoch(train) [7][2080/2569] lr: 2.8000e-02 eta: 1 day, 3:16:51 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 3.2259 loss: 2.8641 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8641 2023/06/04 17:35:54 - mmengine - INFO - Epoch(train) [7][2100/2569] lr: 2.8000e-02 eta: 1 day, 3:16:43 time: 0.2606 data_time: 0.0081 memory: 5828 grad_norm: 3.2174 loss: 2.6552 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6552 2023/06/04 17:35:59 - mmengine - INFO - Epoch(train) [7][2120/2569] lr: 2.8000e-02 eta: 1 day, 3:16:34 time: 0.2594 data_time: 0.0075 memory: 5828 grad_norm: 3.2933 loss: 2.9647 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9647 2023/06/04 17:36:04 - mmengine - INFO - Epoch(train) [7][2140/2569] lr: 2.8000e-02 eta: 1 day, 3:16:32 time: 0.2752 data_time: 0.0074 memory: 5828 grad_norm: 3.3402 loss: 3.0210 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.0210 2023/06/04 17:36:10 - mmengine - INFO - Epoch(train) [7][2160/2569] lr: 2.8000e-02 eta: 1 day, 3:16:26 time: 0.2658 data_time: 0.0071 memory: 5828 grad_norm: 3.2419 loss: 2.7565 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7565 2023/06/04 17:36:15 - mmengine - INFO - Epoch(train) [7][2180/2569] lr: 2.8000e-02 eta: 1 day, 3:16:22 time: 0.2702 data_time: 0.0073 memory: 5828 grad_norm: 3.2063 loss: 3.0506 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 3.0506 2023/06/04 17:36:20 - mmengine - INFO - Epoch(train) [7][2200/2569] lr: 2.8000e-02 eta: 1 day, 3:16:19 time: 0.2727 data_time: 0.0079 memory: 5828 grad_norm: 3.2135 loss: 2.8920 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.8920 2023/06/04 17:36:26 - mmengine - INFO - Epoch(train) [7][2220/2569] lr: 2.8000e-02 eta: 1 day, 3:16:15 time: 0.2683 data_time: 0.0076 memory: 5828 grad_norm: 3.3134 loss: 2.5392 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5392 2023/06/04 17:36:31 - mmengine - INFO - Epoch(train) [7][2240/2569] lr: 2.8000e-02 eta: 1 day, 3:16:09 time: 0.2664 data_time: 0.0081 memory: 5828 grad_norm: 3.3189 loss: 2.5264 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5264 2023/06/04 17:36:36 - mmengine - INFO - Epoch(train) [7][2260/2569] lr: 2.8000e-02 eta: 1 day, 3:16:04 time: 0.2678 data_time: 0.0076 memory: 5828 grad_norm: 3.2350 loss: 2.1343 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1343 2023/06/04 17:36:42 - mmengine - INFO - Epoch(train) [7][2280/2569] lr: 2.8000e-02 eta: 1 day, 3:15:56 time: 0.2609 data_time: 0.0082 memory: 5828 grad_norm: 3.1851 loss: 2.6848 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6848 2023/06/04 17:36:47 - mmengine - INFO - Epoch(train) [7][2300/2569] lr: 2.8000e-02 eta: 1 day, 3:15:51 time: 0.2675 data_time: 0.0075 memory: 5828 grad_norm: 3.2304 loss: 2.4877 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4877 2023/06/04 17:36:52 - mmengine - INFO - Epoch(train) [7][2320/2569] lr: 2.8000e-02 eta: 1 day, 3:15:45 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.2811 loss: 3.0454 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.0454 2023/06/04 17:36:58 - mmengine - INFO - Epoch(train) [7][2340/2569] lr: 2.8000e-02 eta: 1 day, 3:15:38 time: 0.2648 data_time: 0.0075 memory: 5828 grad_norm: 3.1985 loss: 2.7113 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7113 2023/06/04 17:37:03 - mmengine - INFO - Epoch(train) [7][2360/2569] lr: 2.8000e-02 eta: 1 day, 3:15:33 time: 0.2675 data_time: 0.0078 memory: 5828 grad_norm: 3.2005 loss: 2.4567 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4567 2023/06/04 17:37:08 - mmengine - INFO - Epoch(train) [7][2380/2569] lr: 2.8000e-02 eta: 1 day, 3:15:27 time: 0.2644 data_time: 0.0073 memory: 5828 grad_norm: 3.2217 loss: 2.5501 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5501 2023/06/04 17:37:14 - mmengine - INFO - Epoch(train) [7][2400/2569] lr: 2.8000e-02 eta: 1 day, 3:15:23 time: 0.2713 data_time: 0.0078 memory: 5828 grad_norm: 3.2424 loss: 2.9756 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9756 2023/06/04 17:37:19 - mmengine - INFO - Epoch(train) [7][2420/2569] lr: 2.8000e-02 eta: 1 day, 3:15:17 time: 0.2641 data_time: 0.0083 memory: 5828 grad_norm: 3.2468 loss: 2.7660 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7660 2023/06/04 17:37:24 - mmengine - INFO - Epoch(train) [7][2440/2569] lr: 2.8000e-02 eta: 1 day, 3:15:14 time: 0.2738 data_time: 0.0075 memory: 5828 grad_norm: 3.2350 loss: 2.6532 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6532 2023/06/04 17:37:30 - mmengine - INFO - Epoch(train) [7][2460/2569] lr: 2.8000e-02 eta: 1 day, 3:15:06 time: 0.2602 data_time: 0.0072 memory: 5828 grad_norm: 3.2395 loss: 2.9851 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.9851 2023/06/04 17:37:35 - mmengine - INFO - Epoch(train) [7][2480/2569] lr: 2.8000e-02 eta: 1 day, 3:15:00 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 3.2307 loss: 2.7285 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7285 2023/06/04 17:37:40 - mmengine - INFO - Epoch(train) [7][2500/2569] lr: 2.8000e-02 eta: 1 day, 3:14:56 time: 0.2683 data_time: 0.0076 memory: 5828 grad_norm: 3.2518 loss: 2.7268 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7268 2023/06/04 17:37:46 - mmengine - INFO - Epoch(train) [7][2520/2569] lr: 2.8000e-02 eta: 1 day, 3:14:50 time: 0.2664 data_time: 0.0081 memory: 5828 grad_norm: 3.2424 loss: 2.8828 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8828 2023/06/04 17:37:51 - mmengine - INFO - Epoch(train) [7][2540/2569] lr: 2.8000e-02 eta: 1 day, 3:14:44 time: 0.2653 data_time: 0.0079 memory: 5828 grad_norm: 3.2534 loss: 2.8187 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.8187 2023/06/04 17:37:56 - mmengine - INFO - Epoch(train) [7][2560/2569] lr: 2.8000e-02 eta: 1 day, 3:14:35 time: 0.2575 data_time: 0.0075 memory: 5828 grad_norm: 3.3012 loss: 2.6229 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6229 2023/06/04 17:37:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:37:58 - mmengine - INFO - Epoch(train) [7][2569/2569] lr: 2.8000e-02 eta: 1 day, 3:14:28 time: 0.2486 data_time: 0.0073 memory: 5828 grad_norm: 3.3056 loss: 2.8478 top1_acc: 0.0000 top5_acc: 0.1667 loss_cls: 2.8478 2023/06/04 17:38:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:38:05 - mmengine - INFO - Epoch(train) [8][ 20/2569] lr: 3.2000e-02 eta: 1 day, 3:14:52 time: 0.3407 data_time: 0.0668 memory: 5828 grad_norm: 3.2330 loss: 2.9872 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.9872 2023/06/04 17:38:11 - mmengine - INFO - Epoch(train) [8][ 40/2569] lr: 3.2000e-02 eta: 1 day, 3:14:50 time: 0.2751 data_time: 0.0072 memory: 5828 grad_norm: 3.2592 loss: 2.6300 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6300 2023/06/04 17:38:16 - mmengine - INFO - Epoch(train) [8][ 60/2569] lr: 3.2000e-02 eta: 1 day, 3:14:44 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 3.2594 loss: 2.7333 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.7333 2023/06/04 17:38:21 - mmengine - INFO - Epoch(train) [8][ 80/2569] lr: 3.2000e-02 eta: 1 day, 3:14:37 time: 0.2619 data_time: 0.0076 memory: 5828 grad_norm: 3.1845 loss: 2.9397 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9397 2023/06/04 17:38:26 - mmengine - INFO - Epoch(train) [8][ 100/2569] lr: 3.2000e-02 eta: 1 day, 3:14:29 time: 0.2616 data_time: 0.0078 memory: 5828 grad_norm: 3.1878 loss: 2.5793 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5793 2023/06/04 17:38:32 - mmengine - INFO - Epoch(train) [8][ 120/2569] lr: 3.2000e-02 eta: 1 day, 3:14:27 time: 0.2761 data_time: 0.0073 memory: 5828 grad_norm: 3.2224 loss: 2.5302 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5302 2023/06/04 17:38:37 - mmengine - INFO - Epoch(train) [8][ 140/2569] lr: 3.2000e-02 eta: 1 day, 3:14:19 time: 0.2601 data_time: 0.0075 memory: 5828 grad_norm: 3.1737 loss: 2.5643 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5643 2023/06/04 17:38:42 - mmengine - INFO - Epoch(train) [8][ 160/2569] lr: 3.2000e-02 eta: 1 day, 3:14:14 time: 0.2677 data_time: 0.0080 memory: 5828 grad_norm: 3.2710 loss: 2.8610 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8610 2023/06/04 17:38:48 - mmengine - INFO - Epoch(train) [8][ 180/2569] lr: 3.2000e-02 eta: 1 day, 3:14:06 time: 0.2595 data_time: 0.0075 memory: 5828 grad_norm: 3.2728 loss: 2.7898 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7898 2023/06/04 17:38:53 - mmengine - INFO - Epoch(train) [8][ 200/2569] lr: 3.2000e-02 eta: 1 day, 3:14:01 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 3.1828 loss: 2.8253 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8253 2023/06/04 17:38:58 - mmengine - INFO - Epoch(train) [8][ 220/2569] lr: 3.2000e-02 eta: 1 day, 3:13:53 time: 0.2617 data_time: 0.0078 memory: 5828 grad_norm: 3.2082 loss: 2.8692 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8692 2023/06/04 17:39:04 - mmengine - INFO - Epoch(train) [8][ 240/2569] lr: 3.2000e-02 eta: 1 day, 3:13:53 time: 0.2801 data_time: 0.0076 memory: 5828 grad_norm: 3.2425 loss: 2.8949 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8949 2023/06/04 17:39:09 - mmengine - INFO - Epoch(train) [8][ 260/2569] lr: 3.2000e-02 eta: 1 day, 3:13:49 time: 0.2698 data_time: 0.0075 memory: 5828 grad_norm: 3.2164 loss: 2.8390 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.8390 2023/06/04 17:39:15 - mmengine - INFO - Epoch(train) [8][ 280/2569] lr: 3.2000e-02 eta: 1 day, 3:13:44 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 3.1514 loss: 2.9082 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9082 2023/06/04 17:39:20 - mmengine - INFO - Epoch(train) [8][ 300/2569] lr: 3.2000e-02 eta: 1 day, 3:13:44 time: 0.2795 data_time: 0.0076 memory: 5828 grad_norm: 3.1671 loss: 2.2627 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2627 2023/06/04 17:39:25 - mmengine - INFO - Epoch(train) [8][ 320/2569] lr: 3.2000e-02 eta: 1 day, 3:13:36 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 3.2294 loss: 2.8960 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8960 2023/06/04 17:39:31 - mmengine - INFO - Epoch(train) [8][ 340/2569] lr: 3.2000e-02 eta: 1 day, 3:13:34 time: 0.2748 data_time: 0.0079 memory: 5828 grad_norm: 3.1737 loss: 2.7626 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7626 2023/06/04 17:39:36 - mmengine - INFO - Epoch(train) [8][ 360/2569] lr: 3.2000e-02 eta: 1 day, 3:13:28 time: 0.2666 data_time: 0.0074 memory: 5828 grad_norm: 3.1640 loss: 2.7550 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7550 2023/06/04 17:39:41 - mmengine - INFO - Epoch(train) [8][ 380/2569] lr: 3.2000e-02 eta: 1 day, 3:13:21 time: 0.2621 data_time: 0.0078 memory: 5828 grad_norm: 3.2453 loss: 2.9650 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9650 2023/06/04 17:39:47 - mmengine - INFO - Epoch(train) [8][ 400/2569] lr: 3.2000e-02 eta: 1 day, 3:13:15 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 3.1352 loss: 2.7295 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7295 2023/06/04 17:39:52 - mmengine - INFO - Epoch(train) [8][ 420/2569] lr: 3.2000e-02 eta: 1 day, 3:13:08 time: 0.2645 data_time: 0.0079 memory: 5828 grad_norm: 3.2120 loss: 2.6637 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.6637 2023/06/04 17:39:58 - mmengine - INFO - Epoch(train) [8][ 440/2569] lr: 3.2000e-02 eta: 1 day, 3:13:06 time: 0.2735 data_time: 0.0079 memory: 5828 grad_norm: 3.2224 loss: 3.0491 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0491 2023/06/04 17:40:03 - mmengine - INFO - Epoch(train) [8][ 460/2569] lr: 3.2000e-02 eta: 1 day, 3:13:01 time: 0.2678 data_time: 0.0080 memory: 5828 grad_norm: 3.1675 loss: 2.7424 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7424 2023/06/04 17:40:08 - mmengine - INFO - Epoch(train) [8][ 480/2569] lr: 3.2000e-02 eta: 1 day, 3:12:53 time: 0.2602 data_time: 0.0080 memory: 5828 grad_norm: 3.1587 loss: 2.9278 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9278 2023/06/04 17:40:14 - mmengine - INFO - Epoch(train) [8][ 500/2569] lr: 3.2000e-02 eta: 1 day, 3:12:51 time: 0.2768 data_time: 0.0080 memory: 5828 grad_norm: 3.1715 loss: 2.7984 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7984 2023/06/04 17:40:19 - mmengine - INFO - Epoch(train) [8][ 520/2569] lr: 3.2000e-02 eta: 1 day, 3:12:43 time: 0.2609 data_time: 0.0082 memory: 5828 grad_norm: 3.2224 loss: 2.8507 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8507 2023/06/04 17:40:24 - mmengine - INFO - Epoch(train) [8][ 540/2569] lr: 3.2000e-02 eta: 1 day, 3:12:42 time: 0.2758 data_time: 0.0079 memory: 5828 grad_norm: 3.1291 loss: 2.8444 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8444 2023/06/04 17:40:30 - mmengine - INFO - Epoch(train) [8][ 560/2569] lr: 3.2000e-02 eta: 1 day, 3:12:36 time: 0.2668 data_time: 0.0078 memory: 5828 grad_norm: 3.1925 loss: 2.9898 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9898 2023/06/04 17:40:35 - mmengine - INFO - Epoch(train) [8][ 580/2569] lr: 3.2000e-02 eta: 1 day, 3:12:32 time: 0.2713 data_time: 0.0074 memory: 5828 grad_norm: 3.2123 loss: 2.7464 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7464 2023/06/04 17:40:40 - mmengine - INFO - Epoch(train) [8][ 600/2569] lr: 3.2000e-02 eta: 1 day, 3:12:27 time: 0.2671 data_time: 0.0080 memory: 5828 grad_norm: 3.2227 loss: 2.5282 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5282 2023/06/04 17:40:46 - mmengine - INFO - Epoch(train) [8][ 620/2569] lr: 3.2000e-02 eta: 1 day, 3:12:21 time: 0.2660 data_time: 0.0080 memory: 5828 grad_norm: 3.1955 loss: 2.9346 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9346 2023/06/04 17:40:51 - mmengine - INFO - Epoch(train) [8][ 640/2569] lr: 3.2000e-02 eta: 1 day, 3:12:17 time: 0.2692 data_time: 0.0075 memory: 5828 grad_norm: 3.1866 loss: 2.5978 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5978 2023/06/04 17:40:56 - mmengine - INFO - Epoch(train) [8][ 660/2569] lr: 3.2000e-02 eta: 1 day, 3:12:11 time: 0.2655 data_time: 0.0078 memory: 5828 grad_norm: 3.1927 loss: 2.5627 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5627 2023/06/04 17:41:02 - mmengine - INFO - Epoch(train) [8][ 680/2569] lr: 3.2000e-02 eta: 1 day, 3:12:04 time: 0.2629 data_time: 0.0076 memory: 5828 grad_norm: 3.2175 loss: 2.4738 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4738 2023/06/04 17:41:07 - mmengine - INFO - Epoch(train) [8][ 700/2569] lr: 3.2000e-02 eta: 1 day, 3:11:59 time: 0.2691 data_time: 0.0076 memory: 5828 grad_norm: 3.1662 loss: 2.8381 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.8381 2023/06/04 17:41:13 - mmengine - INFO - Epoch(train) [8][ 720/2569] lr: 3.2000e-02 eta: 1 day, 3:11:55 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 3.1650 loss: 2.6996 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6996 2023/06/04 17:41:18 - mmengine - INFO - Epoch(train) [8][ 740/2569] lr: 3.2000e-02 eta: 1 day, 3:11:48 time: 0.2618 data_time: 0.0084 memory: 5828 grad_norm: 3.1834 loss: 2.8166 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8166 2023/06/04 17:41:23 - mmengine - INFO - Epoch(train) [8][ 760/2569] lr: 3.2000e-02 eta: 1 day, 3:11:46 time: 0.2746 data_time: 0.0077 memory: 5828 grad_norm: 3.1690 loss: 2.8659 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8659 2023/06/04 17:41:28 - mmengine - INFO - Epoch(train) [8][ 780/2569] lr: 3.2000e-02 eta: 1 day, 3:11:38 time: 0.2608 data_time: 0.0074 memory: 5828 grad_norm: 3.1273 loss: 2.9736 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9736 2023/06/04 17:41:34 - mmengine - INFO - Epoch(train) [8][ 800/2569] lr: 3.2000e-02 eta: 1 day, 3:11:32 time: 0.2644 data_time: 0.0082 memory: 5828 grad_norm: 3.1643 loss: 2.3194 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3194 2023/06/04 17:41:39 - mmengine - INFO - Epoch(train) [8][ 820/2569] lr: 3.2000e-02 eta: 1 day, 3:11:25 time: 0.2648 data_time: 0.0077 memory: 5828 grad_norm: 3.1634 loss: 2.8574 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.8574 2023/06/04 17:41:44 - mmengine - INFO - Epoch(train) [8][ 840/2569] lr: 3.2000e-02 eta: 1 day, 3:11:17 time: 0.2597 data_time: 0.0080 memory: 5828 grad_norm: 3.1740 loss: 2.8264 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8264 2023/06/04 17:41:50 - mmengine - INFO - Epoch(train) [8][ 860/2569] lr: 3.2000e-02 eta: 1 day, 3:11:13 time: 0.2712 data_time: 0.0078 memory: 5828 grad_norm: 3.1588 loss: 2.6102 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6102 2023/06/04 17:41:55 - mmengine - INFO - Epoch(train) [8][ 880/2569] lr: 3.2000e-02 eta: 1 day, 3:11:11 time: 0.2741 data_time: 0.0077 memory: 5828 grad_norm: 3.1810 loss: 2.7426 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7426 2023/06/04 17:42:01 - mmengine - INFO - Epoch(train) [8][ 900/2569] lr: 3.2000e-02 eta: 1 day, 3:11:08 time: 0.2724 data_time: 0.0080 memory: 5828 grad_norm: 3.1326 loss: 2.5242 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5242 2023/06/04 17:42:06 - mmengine - INFO - Epoch(train) [8][ 920/2569] lr: 3.2000e-02 eta: 1 day, 3:10:59 time: 0.2594 data_time: 0.0085 memory: 5828 grad_norm: 3.1982 loss: 3.1877 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.1877 2023/06/04 17:42:11 - mmengine - INFO - Epoch(train) [8][ 940/2569] lr: 3.2000e-02 eta: 1 day, 3:10:57 time: 0.2755 data_time: 0.0078 memory: 5828 grad_norm: 3.1057 loss: 3.1225 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.1225 2023/06/04 17:42:17 - mmengine - INFO - Epoch(train) [8][ 960/2569] lr: 3.2000e-02 eta: 1 day, 3:10:50 time: 0.2630 data_time: 0.0080 memory: 5828 grad_norm: 3.1128 loss: 3.0243 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 3.0243 2023/06/04 17:42:22 - mmengine - INFO - Epoch(train) [8][ 980/2569] lr: 3.2000e-02 eta: 1 day, 3:10:44 time: 0.2649 data_time: 0.0077 memory: 5828 grad_norm: 3.0975 loss: 2.8643 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8643 2023/06/04 17:42:27 - mmengine - INFO - Epoch(train) [8][1000/2569] lr: 3.2000e-02 eta: 1 day, 3:10:40 time: 0.2702 data_time: 0.0073 memory: 5828 grad_norm: 3.1510 loss: 2.8048 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8048 2023/06/04 17:42:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:42:33 - mmengine - INFO - Epoch(train) [8][1020/2569] lr: 3.2000e-02 eta: 1 day, 3:10:34 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.1455 loss: 2.8615 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.8615 2023/06/04 17:42:38 - mmengine - INFO - Epoch(train) [8][1040/2569] lr: 3.2000e-02 eta: 1 day, 3:10:30 time: 0.2709 data_time: 0.0079 memory: 5828 grad_norm: 3.1470 loss: 2.8860 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8860 2023/06/04 17:42:43 - mmengine - INFO - Epoch(train) [8][1060/2569] lr: 3.2000e-02 eta: 1 day, 3:10:21 time: 0.2578 data_time: 0.0081 memory: 5828 grad_norm: 3.1266 loss: 3.1817 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 3.1817 2023/06/04 17:42:48 - mmengine - INFO - Epoch(train) [8][1080/2569] lr: 3.2000e-02 eta: 1 day, 3:10:13 time: 0.2605 data_time: 0.0076 memory: 5828 grad_norm: 3.1524 loss: 2.7318 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7318 2023/06/04 17:42:54 - mmengine - INFO - Epoch(train) [8][1100/2569] lr: 3.2000e-02 eta: 1 day, 3:10:06 time: 0.2638 data_time: 0.0076 memory: 5828 grad_norm: 3.1101 loss: 2.5778 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5778 2023/06/04 17:42:59 - mmengine - INFO - Epoch(train) [8][1120/2569] lr: 3.2000e-02 eta: 1 day, 3:10:01 time: 0.2668 data_time: 0.0079 memory: 5828 grad_norm: 3.1763 loss: 2.8438 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8438 2023/06/04 17:43:04 - mmengine - INFO - Epoch(train) [8][1140/2569] lr: 3.2000e-02 eta: 1 day, 3:09:59 time: 0.2749 data_time: 0.0078 memory: 5828 grad_norm: 3.1185 loss: 2.8302 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8302 2023/06/04 17:43:10 - mmengine - INFO - Epoch(train) [8][1160/2569] lr: 3.2000e-02 eta: 1 day, 3:09:51 time: 0.2603 data_time: 0.0076 memory: 5828 grad_norm: 3.1015 loss: 2.8420 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.8420 2023/06/04 17:43:15 - mmengine - INFO - Epoch(train) [8][1180/2569] lr: 3.2000e-02 eta: 1 day, 3:09:47 time: 0.2718 data_time: 0.0074 memory: 5828 grad_norm: 3.1372 loss: 2.4712 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4712 2023/06/04 17:43:21 - mmengine - INFO - Epoch(train) [8][1200/2569] lr: 3.2000e-02 eta: 1 day, 3:09:43 time: 0.2693 data_time: 0.0076 memory: 5828 grad_norm: 3.1402 loss: 2.9122 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9122 2023/06/04 17:43:26 - mmengine - INFO - Epoch(train) [8][1220/2569] lr: 3.2000e-02 eta: 1 day, 3:09:37 time: 0.2657 data_time: 0.0078 memory: 5828 grad_norm: 3.1632 loss: 2.7514 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7514 2023/06/04 17:43:31 - mmengine - INFO - Epoch(train) [8][1240/2569] lr: 3.2000e-02 eta: 1 day, 3:09:31 time: 0.2653 data_time: 0.0077 memory: 5828 grad_norm: 3.1736 loss: 3.1177 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.1177 2023/06/04 17:43:36 - mmengine - INFO - Epoch(train) [8][1260/2569] lr: 3.2000e-02 eta: 1 day, 3:09:23 time: 0.2593 data_time: 0.0078 memory: 5828 grad_norm: 3.2025 loss: 2.7170 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7170 2023/06/04 17:43:42 - mmengine - INFO - Epoch(train) [8][1280/2569] lr: 3.2000e-02 eta: 1 day, 3:09:21 time: 0.2776 data_time: 0.0080 memory: 5828 grad_norm: 3.1690 loss: 2.7063 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7063 2023/06/04 17:43:47 - mmengine - INFO - Epoch(train) [8][1300/2569] lr: 3.2000e-02 eta: 1 day, 3:09:18 time: 0.2715 data_time: 0.0078 memory: 5828 grad_norm: 3.1408 loss: 2.9437 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9437 2023/06/04 17:43:53 - mmengine - INFO - Epoch(train) [8][1320/2569] lr: 3.2000e-02 eta: 1 day, 3:09:11 time: 0.2630 data_time: 0.0078 memory: 5828 grad_norm: 3.1731 loss: 2.6855 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6855 2023/06/04 17:43:58 - mmengine - INFO - Epoch(train) [8][1340/2569] lr: 3.2000e-02 eta: 1 day, 3:09:07 time: 0.2723 data_time: 0.0072 memory: 5828 grad_norm: 3.1184 loss: 2.6546 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6546 2023/06/04 17:44:03 - mmengine - INFO - Epoch(train) [8][1360/2569] lr: 3.2000e-02 eta: 1 day, 3:09:03 time: 0.2706 data_time: 0.0073 memory: 5828 grad_norm: 3.1535 loss: 2.8345 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8345 2023/06/04 17:44:09 - mmengine - INFO - Epoch(train) [8][1380/2569] lr: 3.2000e-02 eta: 1 day, 3:09:01 time: 0.2740 data_time: 0.0076 memory: 5828 grad_norm: 3.1363 loss: 2.7006 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7006 2023/06/04 17:44:14 - mmengine - INFO - Epoch(train) [8][1400/2569] lr: 3.2000e-02 eta: 1 day, 3:08:53 time: 0.2604 data_time: 0.0085 memory: 5828 grad_norm: 3.1716 loss: 2.6478 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6478 2023/06/04 17:44:19 - mmengine - INFO - Epoch(train) [8][1420/2569] lr: 3.2000e-02 eta: 1 day, 3:08:46 time: 0.2629 data_time: 0.0078 memory: 5828 grad_norm: 3.1387 loss: 2.6131 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6131 2023/06/04 17:44:25 - mmengine - INFO - Epoch(train) [8][1440/2569] lr: 3.2000e-02 eta: 1 day, 3:08:38 time: 0.2615 data_time: 0.0074 memory: 5828 grad_norm: 3.1066 loss: 2.6784 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6784 2023/06/04 17:44:30 - mmengine - INFO - Epoch(train) [8][1460/2569] lr: 3.2000e-02 eta: 1 day, 3:08:31 time: 0.2610 data_time: 0.0078 memory: 5828 grad_norm: 3.1808 loss: 2.8719 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8719 2023/06/04 17:44:35 - mmengine - INFO - Epoch(train) [8][1480/2569] lr: 3.2000e-02 eta: 1 day, 3:08:23 time: 0.2607 data_time: 0.0084 memory: 5828 grad_norm: 3.1605 loss: 2.5911 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5911 2023/06/04 17:44:40 - mmengine - INFO - Epoch(train) [8][1500/2569] lr: 3.2000e-02 eta: 1 day, 3:08:18 time: 0.2683 data_time: 0.0079 memory: 5828 grad_norm: 3.1116 loss: 2.8403 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8403 2023/06/04 17:44:46 - mmengine - INFO - Epoch(train) [8][1520/2569] lr: 3.2000e-02 eta: 1 day, 3:08:13 time: 0.2664 data_time: 0.0079 memory: 5828 grad_norm: 3.0815 loss: 2.7313 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7313 2023/06/04 17:44:51 - mmengine - INFO - Epoch(train) [8][1540/2569] lr: 3.2000e-02 eta: 1 day, 3:08:08 time: 0.2699 data_time: 0.0077 memory: 5828 grad_norm: 3.0892 loss: 2.8943 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8943 2023/06/04 17:44:57 - mmengine - INFO - Epoch(train) [8][1560/2569] lr: 3.2000e-02 eta: 1 day, 3:08:05 time: 0.2713 data_time: 0.0082 memory: 5828 grad_norm: 3.1092 loss: 2.9045 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9045 2023/06/04 17:45:02 - mmengine - INFO - Epoch(train) [8][1580/2569] lr: 3.2000e-02 eta: 1 day, 3:07:56 time: 0.2592 data_time: 0.0082 memory: 5828 grad_norm: 3.0547 loss: 2.5251 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5251 2023/06/04 17:45:07 - mmengine - INFO - Epoch(train) [8][1600/2569] lr: 3.2000e-02 eta: 1 day, 3:07:55 time: 0.2763 data_time: 0.0072 memory: 5828 grad_norm: 3.1072 loss: 2.5211 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5211 2023/06/04 17:45:12 - mmengine - INFO - Epoch(train) [8][1620/2569] lr: 3.2000e-02 eta: 1 day, 3:07:47 time: 0.2601 data_time: 0.0073 memory: 5828 grad_norm: 3.1193 loss: 2.5064 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5064 2023/06/04 17:45:18 - mmengine - INFO - Epoch(train) [8][1640/2569] lr: 3.2000e-02 eta: 1 day, 3:07:41 time: 0.2657 data_time: 0.0077 memory: 5828 grad_norm: 3.0876 loss: 2.9556 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9556 2023/06/04 17:45:23 - mmengine - INFO - Epoch(train) [8][1660/2569] lr: 3.2000e-02 eta: 1 day, 3:07:34 time: 0.2640 data_time: 0.0081 memory: 5828 grad_norm: 3.1764 loss: 3.0790 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0790 2023/06/04 17:45:28 - mmengine - INFO - Epoch(train) [8][1680/2569] lr: 3.2000e-02 eta: 1 day, 3:07:30 time: 0.2691 data_time: 0.0075 memory: 5828 grad_norm: 3.1332 loss: 2.4900 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4900 2023/06/04 17:45:34 - mmengine - INFO - Epoch(train) [8][1700/2569] lr: 3.2000e-02 eta: 1 day, 3:07:23 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 3.1491 loss: 2.6935 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6935 2023/06/04 17:45:39 - mmengine - INFO - Epoch(train) [8][1720/2569] lr: 3.2000e-02 eta: 1 day, 3:07:20 time: 0.2734 data_time: 0.0072 memory: 5828 grad_norm: 3.0909 loss: 2.6045 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6045 2023/06/04 17:45:44 - mmengine - INFO - Epoch(train) [8][1740/2569] lr: 3.2000e-02 eta: 1 day, 3:07:12 time: 0.2598 data_time: 0.0083 memory: 5828 grad_norm: 3.1380 loss: 2.9815 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9815 2023/06/04 17:45:50 - mmengine - INFO - Epoch(train) [8][1760/2569] lr: 3.2000e-02 eta: 1 day, 3:07:06 time: 0.2662 data_time: 0.0083 memory: 5828 grad_norm: 3.2034 loss: 2.8423 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8423 2023/06/04 17:45:55 - mmengine - INFO - Epoch(train) [8][1780/2569] lr: 3.2000e-02 eta: 1 day, 3:06:59 time: 0.2609 data_time: 0.0079 memory: 5828 grad_norm: 3.1377 loss: 2.7170 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.7170 2023/06/04 17:46:00 - mmengine - INFO - Epoch(train) [8][1800/2569] lr: 3.2000e-02 eta: 1 day, 3:06:52 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 3.1174 loss: 2.7016 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.7016 2023/06/04 17:46:05 - mmengine - INFO - Epoch(train) [8][1820/2569] lr: 3.2000e-02 eta: 1 day, 3:06:44 time: 0.2602 data_time: 0.0077 memory: 5828 grad_norm: 3.0927 loss: 2.4759 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4759 2023/06/04 17:46:11 - mmengine - INFO - Epoch(train) [8][1840/2569] lr: 3.2000e-02 eta: 1 day, 3:06:36 time: 0.2619 data_time: 0.0076 memory: 5828 grad_norm: 3.1378 loss: 3.0130 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0130 2023/06/04 17:46:16 - mmengine - INFO - Epoch(train) [8][1860/2569] lr: 3.2000e-02 eta: 1 day, 3:06:30 time: 0.2646 data_time: 0.0084 memory: 5828 grad_norm: 3.1481 loss: 2.5904 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5904 2023/06/04 17:46:21 - mmengine - INFO - Epoch(train) [8][1880/2569] lr: 3.2000e-02 eta: 1 day, 3:06:27 time: 0.2726 data_time: 0.0075 memory: 5828 grad_norm: 3.1413 loss: 2.9509 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9509 2023/06/04 17:46:27 - mmengine - INFO - Epoch(train) [8][1900/2569] lr: 3.2000e-02 eta: 1 day, 3:06:21 time: 0.2656 data_time: 0.0075 memory: 5828 grad_norm: 3.1175 loss: 2.5535 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5535 2023/06/04 17:46:32 - mmengine - INFO - Epoch(train) [8][1920/2569] lr: 3.2000e-02 eta: 1 day, 3:06:17 time: 0.2715 data_time: 0.0076 memory: 5828 grad_norm: 3.1171 loss: 2.5783 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5783 2023/06/04 17:46:37 - mmengine - INFO - Epoch(train) [8][1940/2569] lr: 3.2000e-02 eta: 1 day, 3:06:11 time: 0.2651 data_time: 0.0080 memory: 5828 grad_norm: 3.1270 loss: 3.1091 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1091 2023/06/04 17:46:43 - mmengine - INFO - Epoch(train) [8][1960/2569] lr: 3.2000e-02 eta: 1 day, 3:06:04 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 3.1324 loss: 2.8766 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8766 2023/06/04 17:46:48 - mmengine - INFO - Epoch(train) [8][1980/2569] lr: 3.2000e-02 eta: 1 day, 3:05:59 time: 0.2686 data_time: 0.0080 memory: 5828 grad_norm: 3.1137 loss: 2.6960 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6960 2023/06/04 17:46:53 - mmengine - INFO - Epoch(train) [8][2000/2569] lr: 3.2000e-02 eta: 1 day, 3:05:51 time: 0.2600 data_time: 0.0077 memory: 5828 grad_norm: 3.0810 loss: 2.6470 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6470 2023/06/04 17:46:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:46:59 - mmengine - INFO - Epoch(train) [8][2020/2569] lr: 3.2000e-02 eta: 1 day, 3:05:46 time: 0.2685 data_time: 0.0076 memory: 5828 grad_norm: 3.0963 loss: 2.5397 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5397 2023/06/04 17:47:04 - mmengine - INFO - Epoch(train) [8][2040/2569] lr: 3.2000e-02 eta: 1 day, 3:05:40 time: 0.2649 data_time: 0.0076 memory: 5828 grad_norm: 3.1631 loss: 2.8283 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8283 2023/06/04 17:47:09 - mmengine - INFO - Epoch(train) [8][2060/2569] lr: 3.2000e-02 eta: 1 day, 3:05:32 time: 0.2599 data_time: 0.0079 memory: 5828 grad_norm: 3.1012 loss: 2.8655 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8655 2023/06/04 17:47:14 - mmengine - INFO - Epoch(train) [8][2080/2569] lr: 3.2000e-02 eta: 1 day, 3:05:27 time: 0.2659 data_time: 0.0085 memory: 5828 grad_norm: 3.1370 loss: 2.7477 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7477 2023/06/04 17:47:20 - mmengine - INFO - Epoch(train) [8][2100/2569] lr: 3.2000e-02 eta: 1 day, 3:05:21 time: 0.2665 data_time: 0.0077 memory: 5828 grad_norm: 3.1075 loss: 2.7421 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7421 2023/06/04 17:47:25 - mmengine - INFO - Epoch(train) [8][2120/2569] lr: 3.2000e-02 eta: 1 day, 3:05:16 time: 0.2687 data_time: 0.0077 memory: 5828 grad_norm: 3.1080 loss: 2.4892 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4892 2023/06/04 17:47:30 - mmengine - INFO - Epoch(train) [8][2140/2569] lr: 3.2000e-02 eta: 1 day, 3:05:10 time: 0.2640 data_time: 0.0078 memory: 5828 grad_norm: 3.1582 loss: 2.7710 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7710 2023/06/04 17:47:36 - mmengine - INFO - Epoch(train) [8][2160/2569] lr: 3.2000e-02 eta: 1 day, 3:05:06 time: 0.2705 data_time: 0.0077 memory: 5828 grad_norm: 3.1401 loss: 2.6706 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6706 2023/06/04 17:47:41 - mmengine - INFO - Epoch(train) [8][2180/2569] lr: 3.2000e-02 eta: 1 day, 3:05:03 time: 0.2738 data_time: 0.0077 memory: 5828 grad_norm: 3.0944 loss: 2.6838 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6838 2023/06/04 17:47:47 - mmengine - INFO - Epoch(train) [8][2200/2569] lr: 3.2000e-02 eta: 1 day, 3:04:57 time: 0.2651 data_time: 0.0078 memory: 5828 grad_norm: 3.1770 loss: 2.7964 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7964 2023/06/04 17:47:52 - mmengine - INFO - Epoch(train) [8][2220/2569] lr: 3.2000e-02 eta: 1 day, 3:04:56 time: 0.2795 data_time: 0.0079 memory: 5828 grad_norm: 3.0977 loss: 2.9326 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9326 2023/06/04 17:47:57 - mmengine - INFO - Epoch(train) [8][2240/2569] lr: 3.2000e-02 eta: 1 day, 3:04:48 time: 0.2595 data_time: 0.0078 memory: 5828 grad_norm: 3.1528 loss: 2.6501 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6501 2023/06/04 17:48:03 - mmengine - INFO - Epoch(train) [8][2260/2569] lr: 3.2000e-02 eta: 1 day, 3:04:46 time: 0.2766 data_time: 0.0078 memory: 5828 grad_norm: 3.0977 loss: 2.4942 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4942 2023/06/04 17:48:08 - mmengine - INFO - Epoch(train) [8][2280/2569] lr: 3.2000e-02 eta: 1 day, 3:04:39 time: 0.2614 data_time: 0.0075 memory: 5828 grad_norm: 3.0474 loss: 2.8326 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8326 2023/06/04 17:48:14 - mmengine - INFO - Epoch(train) [8][2300/2569] lr: 3.2000e-02 eta: 1 day, 3:04:36 time: 0.2744 data_time: 0.0079 memory: 5828 grad_norm: 3.0876 loss: 2.5505 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5505 2023/06/04 17:48:19 - mmengine - INFO - Epoch(train) [8][2320/2569] lr: 3.2000e-02 eta: 1 day, 3:04:28 time: 0.2603 data_time: 0.0080 memory: 5828 grad_norm: 3.0878 loss: 3.0136 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0136 2023/06/04 17:48:24 - mmengine - INFO - Epoch(train) [8][2340/2569] lr: 3.2000e-02 eta: 1 day, 3:04:23 time: 0.2663 data_time: 0.0079 memory: 5828 grad_norm: 3.0578 loss: 2.6298 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6298 2023/06/04 17:48:29 - mmengine - INFO - Epoch(train) [8][2360/2569] lr: 3.2000e-02 eta: 1 day, 3:04:17 time: 0.2649 data_time: 0.0077 memory: 5828 grad_norm: 3.1256 loss: 2.6431 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6431 2023/06/04 17:48:35 - mmengine - INFO - Epoch(train) [8][2380/2569] lr: 3.2000e-02 eta: 1 day, 3:04:11 time: 0.2645 data_time: 0.0077 memory: 5828 grad_norm: 3.0406 loss: 2.6341 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6341 2023/06/04 17:48:40 - mmengine - INFO - Epoch(train) [8][2400/2569] lr: 3.2000e-02 eta: 1 day, 3:04:03 time: 0.2611 data_time: 0.0081 memory: 5828 grad_norm: 3.0919 loss: 2.8238 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8238 2023/06/04 17:48:45 - mmengine - INFO - Epoch(train) [8][2420/2569] lr: 3.2000e-02 eta: 1 day, 3:03:58 time: 0.2680 data_time: 0.0075 memory: 5828 grad_norm: 3.1458 loss: 2.6619 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6619 2023/06/04 17:48:51 - mmengine - INFO - Epoch(train) [8][2440/2569] lr: 3.2000e-02 eta: 1 day, 3:03:50 time: 0.2604 data_time: 0.0076 memory: 5828 grad_norm: 3.1209 loss: 2.6642 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6642 2023/06/04 17:48:56 - mmengine - INFO - Epoch(train) [8][2460/2569] lr: 3.2000e-02 eta: 1 day, 3:03:45 time: 0.2661 data_time: 0.0078 memory: 5828 grad_norm: 3.0754 loss: 2.9263 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9263 2023/06/04 17:49:01 - mmengine - INFO - Epoch(train) [8][2480/2569] lr: 3.2000e-02 eta: 1 day, 3:03:37 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 3.1257 loss: 2.8263 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8263 2023/06/04 17:49:06 - mmengine - INFO - Epoch(train) [8][2500/2569] lr: 3.2000e-02 eta: 1 day, 3:03:32 time: 0.2665 data_time: 0.0080 memory: 5828 grad_norm: 3.1040 loss: 2.5799 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5799 2023/06/04 17:49:12 - mmengine - INFO - Epoch(train) [8][2520/2569] lr: 3.2000e-02 eta: 1 day, 3:03:25 time: 0.2614 data_time: 0.0081 memory: 5828 grad_norm: 3.0887 loss: 2.7586 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7586 2023/06/04 17:49:17 - mmengine - INFO - Epoch(train) [8][2540/2569] lr: 3.2000e-02 eta: 1 day, 3:03:18 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 3.1157 loss: 2.8389 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8389 2023/06/04 17:49:22 - mmengine - INFO - Epoch(train) [8][2560/2569] lr: 3.2000e-02 eta: 1 day, 3:03:09 time: 0.2570 data_time: 0.0082 memory: 5828 grad_norm: 3.1141 loss: 2.8885 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8885 2023/06/04 17:49:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:49:24 - mmengine - INFO - Epoch(train) [8][2569/2569] lr: 3.2000e-02 eta: 1 day, 3:03:04 time: 0.2523 data_time: 0.0072 memory: 5828 grad_norm: 3.1370 loss: 2.7089 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.7089 2023/06/04 17:49:24 - mmengine - INFO - Saving checkpoint at 8 epochs 2023/06/04 17:49:33 - mmengine - INFO - Epoch(train) [9][ 20/2569] lr: 3.6000e-02 eta: 1 day, 3:03:12 time: 0.3055 data_time: 0.0493 memory: 5828 grad_norm: 3.1240 loss: 2.9465 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9465 2023/06/04 17:49:38 - mmengine - INFO - Epoch(train) [9][ 40/2569] lr: 3.6000e-02 eta: 1 day, 3:03:05 time: 0.2616 data_time: 0.0075 memory: 5828 grad_norm: 3.0799 loss: 2.9117 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9117 2023/06/04 17:49:43 - mmengine - INFO - Epoch(train) [9][ 60/2569] lr: 3.6000e-02 eta: 1 day, 3:02:59 time: 0.2669 data_time: 0.0078 memory: 5828 grad_norm: 3.0826 loss: 2.6064 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6064 2023/06/04 17:49:48 - mmengine - INFO - Epoch(train) [9][ 80/2569] lr: 3.6000e-02 eta: 1 day, 3:02:52 time: 0.2600 data_time: 0.0076 memory: 5828 grad_norm: 3.1063 loss: 2.5477 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5477 2023/06/04 17:49:54 - mmengine - INFO - Epoch(train) [9][ 100/2569] lr: 3.6000e-02 eta: 1 day, 3:02:46 time: 0.2670 data_time: 0.0078 memory: 5828 grad_norm: 3.1753 loss: 2.6987 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6987 2023/06/04 17:49:59 - mmengine - INFO - Epoch(train) [9][ 120/2569] lr: 3.6000e-02 eta: 1 day, 3:02:43 time: 0.2733 data_time: 0.0077 memory: 5828 grad_norm: 3.0441 loss: 2.9860 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.9860 2023/06/04 17:50:04 - mmengine - INFO - Epoch(train) [9][ 140/2569] lr: 3.6000e-02 eta: 1 day, 3:02:35 time: 0.2599 data_time: 0.0079 memory: 5828 grad_norm: 3.1093 loss: 2.5540 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5540 2023/06/04 17:50:10 - mmengine - INFO - Epoch(train) [9][ 160/2569] lr: 3.6000e-02 eta: 1 day, 3:02:30 time: 0.2667 data_time: 0.0076 memory: 5828 grad_norm: 3.1086 loss: 2.6376 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6376 2023/06/04 17:50:15 - mmengine - INFO - Epoch(train) [9][ 180/2569] lr: 3.6000e-02 eta: 1 day, 3:02:24 time: 0.2651 data_time: 0.0076 memory: 5828 grad_norm: 3.0707 loss: 2.9330 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9330 2023/06/04 17:50:20 - mmengine - INFO - Epoch(train) [9][ 200/2569] lr: 3.6000e-02 eta: 1 day, 3:02:19 time: 0.2680 data_time: 0.0075 memory: 5828 grad_norm: 3.0276 loss: 2.3837 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3837 2023/06/04 17:50:26 - mmengine - INFO - Epoch(train) [9][ 220/2569] lr: 3.6000e-02 eta: 1 day, 3:02:14 time: 0.2675 data_time: 0.0077 memory: 5828 grad_norm: 3.0829 loss: 2.9547 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9547 2023/06/04 17:50:31 - mmengine - INFO - Epoch(train) [9][ 240/2569] lr: 3.6000e-02 eta: 1 day, 3:02:08 time: 0.2658 data_time: 0.0077 memory: 5828 grad_norm: 3.0435 loss: 2.8149 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8149 2023/06/04 17:50:36 - mmengine - INFO - Epoch(train) [9][ 260/2569] lr: 3.6000e-02 eta: 1 day, 3:02:03 time: 0.2671 data_time: 0.0079 memory: 5828 grad_norm: 3.0738 loss: 2.7450 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7450 2023/06/04 17:50:42 - mmengine - INFO - Epoch(train) [9][ 280/2569] lr: 3.6000e-02 eta: 1 day, 3:01:56 time: 0.2640 data_time: 0.0076 memory: 5828 grad_norm: 3.0986 loss: 2.9859 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9859 2023/06/04 17:50:47 - mmengine - INFO - Epoch(train) [9][ 300/2569] lr: 3.6000e-02 eta: 1 day, 3:01:54 time: 0.2742 data_time: 0.0076 memory: 5828 grad_norm: 3.0904 loss: 3.0657 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.0657 2023/06/04 17:50:53 - mmengine - INFO - Epoch(train) [9][ 320/2569] lr: 3.6000e-02 eta: 1 day, 3:01:51 time: 0.2762 data_time: 0.0077 memory: 5828 grad_norm: 3.0999 loss: 2.7304 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7304 2023/06/04 17:50:58 - mmengine - INFO - Epoch(train) [9][ 340/2569] lr: 3.6000e-02 eta: 1 day, 3:01:44 time: 0.2619 data_time: 0.0080 memory: 5828 grad_norm: 3.0992 loss: 2.7307 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7307 2023/06/04 17:51:03 - mmengine - INFO - Epoch(train) [9][ 360/2569] lr: 3.6000e-02 eta: 1 day, 3:01:38 time: 0.2645 data_time: 0.0079 memory: 5828 grad_norm: 3.0923 loss: 2.6293 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6293 2023/06/04 17:51:08 - mmengine - INFO - Epoch(train) [9][ 380/2569] lr: 3.6000e-02 eta: 1 day, 3:01:30 time: 0.2584 data_time: 0.0077 memory: 5828 grad_norm: 3.0326 loss: 2.7301 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7301 2023/06/04 17:51:14 - mmengine - INFO - Epoch(train) [9][ 400/2569] lr: 3.6000e-02 eta: 1 day, 3:01:26 time: 0.2721 data_time: 0.0074 memory: 5828 grad_norm: 3.0079 loss: 2.8654 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8654 2023/06/04 17:51:19 - mmengine - INFO - Epoch(train) [9][ 420/2569] lr: 3.6000e-02 eta: 1 day, 3:01:18 time: 0.2594 data_time: 0.0079 memory: 5828 grad_norm: 3.0530 loss: 2.5265 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5265 2023/06/04 17:51:24 - mmengine - INFO - Epoch(train) [9][ 440/2569] lr: 3.6000e-02 eta: 1 day, 3:01:11 time: 0.2618 data_time: 0.0079 memory: 5828 grad_norm: 3.0952 loss: 2.8480 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8480 2023/06/04 17:51:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:51:30 - mmengine - INFO - Epoch(train) [9][ 460/2569] lr: 3.6000e-02 eta: 1 day, 3:01:07 time: 0.2719 data_time: 0.0074 memory: 5828 grad_norm: 3.0095 loss: 2.6956 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6956 2023/06/04 17:51:35 - mmengine - INFO - Epoch(train) [9][ 480/2569] lr: 3.6000e-02 eta: 1 day, 3:00:59 time: 0.2589 data_time: 0.0078 memory: 5828 grad_norm: 3.0921 loss: 2.4440 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4440 2023/06/04 17:51:40 - mmengine - INFO - Epoch(train) [9][ 500/2569] lr: 3.6000e-02 eta: 1 day, 3:00:56 time: 0.2736 data_time: 0.0080 memory: 5828 grad_norm: 3.1135 loss: 2.5654 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5654 2023/06/04 17:51:45 - mmengine - INFO - Epoch(train) [9][ 520/2569] lr: 3.6000e-02 eta: 1 day, 3:00:48 time: 0.2594 data_time: 0.0074 memory: 5828 grad_norm: 3.0535 loss: 2.5930 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5930 2023/06/04 17:51:51 - mmengine - INFO - Epoch(train) [9][ 540/2569] lr: 3.6000e-02 eta: 1 day, 3:00:44 time: 0.2688 data_time: 0.0078 memory: 5828 grad_norm: 3.0602 loss: 2.6466 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6466 2023/06/04 17:51:56 - mmengine - INFO - Epoch(train) [9][ 560/2569] lr: 3.6000e-02 eta: 1 day, 3:00:38 time: 0.2654 data_time: 0.0077 memory: 5828 grad_norm: 3.1046 loss: 2.6699 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6699 2023/06/04 17:52:01 - mmengine - INFO - Epoch(train) [9][ 580/2569] lr: 3.6000e-02 eta: 1 day, 3:00:32 time: 0.2649 data_time: 0.0078 memory: 5828 grad_norm: 3.0328 loss: 2.7727 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7727 2023/06/04 17:52:07 - mmengine - INFO - Epoch(train) [9][ 600/2569] lr: 3.6000e-02 eta: 1 day, 3:00:26 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 3.0708 loss: 2.5548 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5548 2023/06/04 17:52:12 - mmengine - INFO - Epoch(train) [9][ 620/2569] lr: 3.6000e-02 eta: 1 day, 3:00:21 time: 0.2701 data_time: 0.0074 memory: 5828 grad_norm: 3.0591 loss: 2.6537 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6537 2023/06/04 17:52:17 - mmengine - INFO - Epoch(train) [9][ 640/2569] lr: 3.6000e-02 eta: 1 day, 3:00:15 time: 0.2650 data_time: 0.0077 memory: 5828 grad_norm: 3.0650 loss: 2.7545 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7545 2023/06/04 17:52:23 - mmengine - INFO - Epoch(train) [9][ 660/2569] lr: 3.6000e-02 eta: 1 day, 3:00:07 time: 0.2597 data_time: 0.0072 memory: 5828 grad_norm: 3.0315 loss: 2.7239 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.7239 2023/06/04 17:52:28 - mmengine - INFO - Epoch(train) [9][ 680/2569] lr: 3.6000e-02 eta: 1 day, 3:00:04 time: 0.2715 data_time: 0.0075 memory: 5828 grad_norm: 3.0158 loss: 2.7395 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.7395 2023/06/04 17:52:33 - mmengine - INFO - Epoch(train) [9][ 700/2569] lr: 3.6000e-02 eta: 1 day, 2:59:58 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 3.0629 loss: 2.7319 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7319 2023/06/04 17:52:39 - mmengine - INFO - Epoch(train) [9][ 720/2569] lr: 3.6000e-02 eta: 1 day, 2:59:54 time: 0.2708 data_time: 0.0077 memory: 5828 grad_norm: 3.0298 loss: 2.4652 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4652 2023/06/04 17:52:44 - mmengine - INFO - Epoch(train) [9][ 740/2569] lr: 3.6000e-02 eta: 1 day, 2:59:47 time: 0.2631 data_time: 0.0076 memory: 5828 grad_norm: 3.0680 loss: 2.7832 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7832 2023/06/04 17:52:49 - mmengine - INFO - Epoch(train) [9][ 760/2569] lr: 3.6000e-02 eta: 1 day, 2:59:39 time: 0.2579 data_time: 0.0082 memory: 5828 grad_norm: 3.1450 loss: 2.7785 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7785 2023/06/04 17:52:55 - mmengine - INFO - Epoch(train) [9][ 780/2569] lr: 3.6000e-02 eta: 1 day, 2:59:32 time: 0.2641 data_time: 0.0077 memory: 5828 grad_norm: 3.0740 loss: 2.8253 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8253 2023/06/04 17:53:00 - mmengine - INFO - Epoch(train) [9][ 800/2569] lr: 3.6000e-02 eta: 1 day, 2:59:26 time: 0.2647 data_time: 0.0077 memory: 5828 grad_norm: 3.0398 loss: 2.6955 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6955 2023/06/04 17:53:05 - mmengine - INFO - Epoch(train) [9][ 820/2569] lr: 3.6000e-02 eta: 1 day, 2:59:20 time: 0.2636 data_time: 0.0083 memory: 5828 grad_norm: 3.1071 loss: 2.9738 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9738 2023/06/04 17:53:10 - mmengine - INFO - Epoch(train) [9][ 840/2569] lr: 3.6000e-02 eta: 1 day, 2:59:14 time: 0.2654 data_time: 0.0078 memory: 5828 grad_norm: 2.9393 loss: 2.9010 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9010 2023/06/04 17:53:16 - mmengine - INFO - Epoch(train) [9][ 860/2569] lr: 3.6000e-02 eta: 1 day, 2:59:10 time: 0.2715 data_time: 0.0078 memory: 5828 grad_norm: 3.0635 loss: 2.7858 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7858 2023/06/04 17:53:21 - mmengine - INFO - Epoch(train) [9][ 880/2569] lr: 3.6000e-02 eta: 1 day, 2:59:06 time: 0.2716 data_time: 0.0081 memory: 5828 grad_norm: 3.0833 loss: 2.7671 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7671 2023/06/04 17:53:27 - mmengine - INFO - Epoch(train) [9][ 900/2569] lr: 3.6000e-02 eta: 1 day, 2:59:01 time: 0.2670 data_time: 0.0076 memory: 5828 grad_norm: 2.9998 loss: 2.6365 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6365 2023/06/04 17:53:32 - mmengine - INFO - Epoch(train) [9][ 920/2569] lr: 3.6000e-02 eta: 1 day, 2:58:55 time: 0.2658 data_time: 0.0083 memory: 5828 grad_norm: 3.1044 loss: 2.7540 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7540 2023/06/04 17:53:37 - mmengine - INFO - Epoch(train) [9][ 940/2569] lr: 3.6000e-02 eta: 1 day, 2:58:51 time: 0.2702 data_time: 0.0080 memory: 5828 grad_norm: 3.0414 loss: 2.6380 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6380 2023/06/04 17:53:43 - mmengine - INFO - Epoch(train) [9][ 960/2569] lr: 3.6000e-02 eta: 1 day, 2:58:45 time: 0.2661 data_time: 0.0080 memory: 5828 grad_norm: 3.0070 loss: 3.1986 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1986 2023/06/04 17:53:48 - mmengine - INFO - Epoch(train) [9][ 980/2569] lr: 3.6000e-02 eta: 1 day, 2:58:42 time: 0.2742 data_time: 0.0076 memory: 5828 grad_norm: 2.9898 loss: 2.8169 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8169 2023/06/04 17:53:53 - mmengine - INFO - Epoch(train) [9][1000/2569] lr: 3.6000e-02 eta: 1 day, 2:58:37 time: 0.2658 data_time: 0.0080 memory: 5828 grad_norm: 3.0233 loss: 2.7616 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7616 2023/06/04 17:53:59 - mmengine - INFO - Epoch(train) [9][1020/2569] lr: 3.6000e-02 eta: 1 day, 2:58:30 time: 0.2615 data_time: 0.0078 memory: 5828 grad_norm: 3.0857 loss: 2.5721 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5721 2023/06/04 17:54:04 - mmengine - INFO - Epoch(train) [9][1040/2569] lr: 3.6000e-02 eta: 1 day, 2:58:28 time: 0.2768 data_time: 0.0078 memory: 5828 grad_norm: 3.0290 loss: 2.9136 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9136 2023/06/04 17:54:10 - mmengine - INFO - Epoch(train) [9][1060/2569] lr: 3.6000e-02 eta: 1 day, 2:58:24 time: 0.2710 data_time: 0.0080 memory: 5828 grad_norm: 3.0343 loss: 2.6288 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6288 2023/06/04 17:54:15 - mmengine - INFO - Epoch(train) [9][1080/2569] lr: 3.6000e-02 eta: 1 day, 2:58:18 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 3.0085 loss: 2.6580 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6580 2023/06/04 17:54:20 - mmengine - INFO - Epoch(train) [9][1100/2569] lr: 3.6000e-02 eta: 1 day, 2:58:13 time: 0.2680 data_time: 0.0079 memory: 5828 grad_norm: 3.0015 loss: 2.5755 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5755 2023/06/04 17:54:26 - mmengine - INFO - Epoch(train) [9][1120/2569] lr: 3.6000e-02 eta: 1 day, 2:58:09 time: 0.2699 data_time: 0.0069 memory: 5828 grad_norm: 3.0285 loss: 2.9516 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9516 2023/06/04 17:54:31 - mmengine - INFO - Epoch(train) [9][1140/2569] lr: 3.6000e-02 eta: 1 day, 2:58:04 time: 0.2702 data_time: 0.0074 memory: 5828 grad_norm: 3.0043 loss: 2.7233 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7233 2023/06/04 17:54:36 - mmengine - INFO - Epoch(train) [9][1160/2569] lr: 3.6000e-02 eta: 1 day, 2:57:58 time: 0.2632 data_time: 0.0083 memory: 5828 grad_norm: 3.0411 loss: 2.6775 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6775 2023/06/04 17:54:42 - mmengine - INFO - Epoch(train) [9][1180/2569] lr: 3.6000e-02 eta: 1 day, 2:57:50 time: 0.2611 data_time: 0.0077 memory: 5828 grad_norm: 2.9839 loss: 2.8330 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8330 2023/06/04 17:54:47 - mmengine - INFO - Epoch(train) [9][1200/2569] lr: 3.6000e-02 eta: 1 day, 2:57:43 time: 0.2605 data_time: 0.0076 memory: 5828 grad_norm: 2.9628 loss: 2.8894 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8894 2023/06/04 17:54:52 - mmengine - INFO - Epoch(train) [9][1220/2569] lr: 3.6000e-02 eta: 1 day, 2:57:35 time: 0.2600 data_time: 0.0081 memory: 5828 grad_norm: 3.0436 loss: 3.3955 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.3955 2023/06/04 17:54:57 - mmengine - INFO - Epoch(train) [9][1240/2569] lr: 3.6000e-02 eta: 1 day, 2:57:29 time: 0.2647 data_time: 0.0084 memory: 5828 grad_norm: 3.0257 loss: 2.4544 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4544 2023/06/04 17:55:03 - mmengine - INFO - Epoch(train) [9][1260/2569] lr: 3.6000e-02 eta: 1 day, 2:57:23 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 3.0225 loss: 3.0185 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 3.0185 2023/06/04 17:55:08 - mmengine - INFO - Epoch(train) [9][1280/2569] lr: 3.6000e-02 eta: 1 day, 2:57:19 time: 0.2723 data_time: 0.0079 memory: 5828 grad_norm: 3.0543 loss: 2.7024 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7024 2023/06/04 17:55:13 - mmengine - INFO - Epoch(train) [9][1300/2569] lr: 3.6000e-02 eta: 1 day, 2:57:15 time: 0.2697 data_time: 0.0076 memory: 5828 grad_norm: 3.0250 loss: 3.0280 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 3.0280 2023/06/04 17:55:19 - mmengine - INFO - Epoch(train) [9][1320/2569] lr: 3.6000e-02 eta: 1 day, 2:57:09 time: 0.2662 data_time: 0.0079 memory: 5828 grad_norm: 2.9935 loss: 2.7504 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7504 2023/06/04 17:55:24 - mmengine - INFO - Epoch(train) [9][1340/2569] lr: 3.6000e-02 eta: 1 day, 2:57:04 time: 0.2678 data_time: 0.0079 memory: 5828 grad_norm: 3.0295 loss: 3.0566 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0566 2023/06/04 17:55:30 - mmengine - INFO - Epoch(train) [9][1360/2569] lr: 3.6000e-02 eta: 1 day, 2:57:00 time: 0.2713 data_time: 0.0081 memory: 5828 grad_norm: 3.0202 loss: 2.7635 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7635 2023/06/04 17:55:35 - mmengine - INFO - Epoch(train) [9][1380/2569] lr: 3.6000e-02 eta: 1 day, 2:56:55 time: 0.2667 data_time: 0.0077 memory: 5828 grad_norm: 3.0352 loss: 2.5141 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5141 2023/06/04 17:55:40 - mmengine - INFO - Epoch(train) [9][1400/2569] lr: 3.6000e-02 eta: 1 day, 2:56:51 time: 0.2732 data_time: 0.0075 memory: 5828 grad_norm: 3.0217 loss: 2.4065 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4065 2023/06/04 17:55:46 - mmengine - INFO - Epoch(train) [9][1420/2569] lr: 3.6000e-02 eta: 1 day, 2:56:46 time: 0.2662 data_time: 0.0080 memory: 5828 grad_norm: 3.0405 loss: 2.4791 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4791 2023/06/04 17:55:51 - mmengine - INFO - Epoch(train) [9][1440/2569] lr: 3.6000e-02 eta: 1 day, 2:56:39 time: 0.2613 data_time: 0.0076 memory: 5828 grad_norm: 3.0362 loss: 2.5775 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5775 2023/06/04 17:55:53 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 17:55:56 - mmengine - INFO - Epoch(train) [9][1460/2569] lr: 3.6000e-02 eta: 1 day, 2:56:31 time: 0.2605 data_time: 0.0079 memory: 5828 grad_norm: 3.0205 loss: 2.6777 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6777 2023/06/04 17:56:01 - mmengine - INFO - Epoch(train) [9][1480/2569] lr: 3.6000e-02 eta: 1 day, 2:56:24 time: 0.2608 data_time: 0.0083 memory: 5828 grad_norm: 3.0157 loss: 3.0032 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.0032 2023/06/04 17:56:07 - mmengine - INFO - Epoch(train) [9][1500/2569] lr: 3.6000e-02 eta: 1 day, 2:56:20 time: 0.2703 data_time: 0.0075 memory: 5828 grad_norm: 3.0453 loss: 2.7641 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7641 2023/06/04 17:56:12 - mmengine - INFO - Epoch(train) [9][1520/2569] lr: 3.6000e-02 eta: 1 day, 2:56:13 time: 0.2630 data_time: 0.0081 memory: 5828 grad_norm: 3.0487 loss: 2.9479 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9479 2023/06/04 17:56:17 - mmengine - INFO - Epoch(train) [9][1540/2569] lr: 3.6000e-02 eta: 1 day, 2:56:08 time: 0.2673 data_time: 0.0077 memory: 5828 grad_norm: 3.0582 loss: 2.7923 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.7923 2023/06/04 17:56:23 - mmengine - INFO - Epoch(train) [9][1560/2569] lr: 3.6000e-02 eta: 1 day, 2:56:03 time: 0.2702 data_time: 0.0074 memory: 5828 grad_norm: 2.9861 loss: 2.4869 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4869 2023/06/04 17:56:28 - mmengine - INFO - Epoch(train) [9][1580/2569] lr: 3.6000e-02 eta: 1 day, 2:55:59 time: 0.2694 data_time: 0.0079 memory: 5828 grad_norm: 2.9990 loss: 2.7428 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7428 2023/06/04 17:56:33 - mmengine - INFO - Epoch(train) [9][1600/2569] lr: 3.6000e-02 eta: 1 day, 2:55:53 time: 0.2656 data_time: 0.0072 memory: 5828 grad_norm: 2.9886 loss: 3.1623 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.1623 2023/06/04 17:56:39 - mmengine - INFO - Epoch(train) [9][1620/2569] lr: 3.6000e-02 eta: 1 day, 2:55:46 time: 0.2627 data_time: 0.0070 memory: 5828 grad_norm: 2.9949 loss: 2.4554 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4554 2023/06/04 17:56:44 - mmengine - INFO - Epoch(train) [9][1640/2569] lr: 3.6000e-02 eta: 1 day, 2:55:39 time: 0.2598 data_time: 0.0075 memory: 5828 grad_norm: 3.0627 loss: 2.7125 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7125 2023/06/04 17:56:49 - mmengine - INFO - Epoch(train) [9][1660/2569] lr: 3.6000e-02 eta: 1 day, 2:55:33 time: 0.2663 data_time: 0.0075 memory: 5828 grad_norm: 3.0955 loss: 2.7037 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7037 2023/06/04 17:56:54 - mmengine - INFO - Epoch(train) [9][1680/2569] lr: 3.6000e-02 eta: 1 day, 2:55:27 time: 0.2637 data_time: 0.0081 memory: 5828 grad_norm: 3.0553 loss: 2.6800 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6800 2023/06/04 17:57:00 - mmengine - INFO - Epoch(train) [9][1700/2569] lr: 3.6000e-02 eta: 1 day, 2:55:20 time: 0.2630 data_time: 0.0076 memory: 5828 grad_norm: 3.0119 loss: 2.8033 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8033 2023/06/04 17:57:05 - mmengine - INFO - Epoch(train) [9][1720/2569] lr: 3.6000e-02 eta: 1 day, 2:55:13 time: 0.2609 data_time: 0.0076 memory: 5828 grad_norm: 2.9581 loss: 2.4708 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4708 2023/06/04 17:57:10 - mmengine - INFO - Epoch(train) [9][1740/2569] lr: 3.6000e-02 eta: 1 day, 2:55:06 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 2.9763 loss: 3.2748 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.2748 2023/06/04 17:57:16 - mmengine - INFO - Epoch(train) [9][1760/2569] lr: 3.6000e-02 eta: 1 day, 2:55:00 time: 0.2660 data_time: 0.0077 memory: 5828 grad_norm: 3.0041 loss: 2.5857 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5857 2023/06/04 17:57:21 - mmengine - INFO - Epoch(train) [9][1780/2569] lr: 3.6000e-02 eta: 1 day, 2:54:53 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 2.9767 loss: 2.9702 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9702 2023/06/04 17:57:26 - mmengine - INFO - Epoch(train) [9][1800/2569] lr: 3.6000e-02 eta: 1 day, 2:54:47 time: 0.2652 data_time: 0.0078 memory: 5828 grad_norm: 3.0453 loss: 3.3312 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.3312 2023/06/04 17:57:32 - mmengine - INFO - Epoch(train) [9][1820/2569] lr: 3.6000e-02 eta: 1 day, 2:54:43 time: 0.2715 data_time: 0.0078 memory: 5828 grad_norm: 3.0271 loss: 2.7178 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7178 2023/06/04 17:57:37 - mmengine - INFO - Epoch(train) [9][1840/2569] lr: 3.6000e-02 eta: 1 day, 2:54:38 time: 0.2655 data_time: 0.0079 memory: 5828 grad_norm: 2.9675 loss: 2.6920 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6920 2023/06/04 17:57:42 - mmengine - INFO - Epoch(train) [9][1860/2569] lr: 3.6000e-02 eta: 1 day, 2:54:32 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 2.9663 loss: 2.4684 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4684 2023/06/04 17:57:48 - mmengine - INFO - Epoch(train) [9][1880/2569] lr: 3.6000e-02 eta: 1 day, 2:54:29 time: 0.2753 data_time: 0.0078 memory: 5828 grad_norm: 3.0017 loss: 2.6646 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6646 2023/06/04 17:57:53 - mmengine - INFO - Epoch(train) [9][1900/2569] lr: 3.6000e-02 eta: 1 day, 2:54:22 time: 0.2617 data_time: 0.0075 memory: 5828 grad_norm: 2.9650 loss: 2.7234 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.7234 2023/06/04 17:57:58 - mmengine - INFO - Epoch(train) [9][1920/2569] lr: 3.6000e-02 eta: 1 day, 2:54:15 time: 0.2627 data_time: 0.0076 memory: 5828 grad_norm: 3.0378 loss: 2.5877 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5877 2023/06/04 17:58:03 - mmengine - INFO - Epoch(train) [9][1940/2569] lr: 3.6000e-02 eta: 1 day, 2:54:08 time: 0.2618 data_time: 0.0076 memory: 5828 grad_norm: 2.9842 loss: 2.9092 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9092 2023/06/04 17:58:09 - mmengine - INFO - Epoch(train) [9][1960/2569] lr: 3.6000e-02 eta: 1 day, 2:54:03 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 3.0222 loss: 3.0150 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0150 2023/06/04 17:58:14 - mmengine - INFO - Epoch(train) [9][1980/2569] lr: 3.6000e-02 eta: 1 day, 2:53:57 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 2.9747 loss: 2.8854 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.8854 2023/06/04 17:58:19 - mmengine - INFO - Epoch(train) [9][2000/2569] lr: 3.6000e-02 eta: 1 day, 2:53:52 time: 0.2660 data_time: 0.0079 memory: 5828 grad_norm: 2.9832 loss: 2.6898 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6898 2023/06/04 17:58:25 - mmengine - INFO - Epoch(train) [9][2020/2569] lr: 3.6000e-02 eta: 1 day, 2:53:45 time: 0.2614 data_time: 0.0077 memory: 5828 grad_norm: 2.9984 loss: 2.7045 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7045 2023/06/04 17:58:30 - mmengine - INFO - Epoch(train) [9][2040/2569] lr: 3.6000e-02 eta: 1 day, 2:53:37 time: 0.2601 data_time: 0.0078 memory: 5828 grad_norm: 3.0005 loss: 2.5051 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5051 2023/06/04 17:58:35 - mmengine - INFO - Epoch(train) [9][2060/2569] lr: 3.6000e-02 eta: 1 day, 2:53:32 time: 0.2675 data_time: 0.0080 memory: 5828 grad_norm: 2.9881 loss: 2.7748 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7748 2023/06/04 17:58:40 - mmengine - INFO - Epoch(train) [9][2080/2569] lr: 3.6000e-02 eta: 1 day, 2:53:26 time: 0.2646 data_time: 0.0079 memory: 5828 grad_norm: 3.0023 loss: 2.7957 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7957 2023/06/04 17:58:46 - mmengine - INFO - Epoch(train) [9][2100/2569] lr: 3.6000e-02 eta: 1 day, 2:53:20 time: 0.2643 data_time: 0.0079 memory: 5828 grad_norm: 2.9969 loss: 2.6508 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6508 2023/06/04 17:58:51 - mmengine - INFO - Epoch(train) [9][2120/2569] lr: 3.6000e-02 eta: 1 day, 2:53:12 time: 0.2592 data_time: 0.0078 memory: 5828 grad_norm: 3.0671 loss: 2.7333 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7333 2023/06/04 17:58:56 - mmengine - INFO - Epoch(train) [9][2140/2569] lr: 3.6000e-02 eta: 1 day, 2:53:05 time: 0.2610 data_time: 0.0076 memory: 5828 grad_norm: 3.0210 loss: 2.9239 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9239 2023/06/04 17:59:01 - mmengine - INFO - Epoch(train) [9][2160/2569] lr: 3.6000e-02 eta: 1 day, 2:52:59 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 3.0657 loss: 2.6380 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6380 2023/06/04 17:59:07 - mmengine - INFO - Epoch(train) [9][2180/2569] lr: 3.6000e-02 eta: 1 day, 2:52:53 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.0075 loss: 3.0715 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 3.0715 2023/06/04 17:59:12 - mmengine - INFO - Epoch(train) [9][2200/2569] lr: 3.6000e-02 eta: 1 day, 2:52:45 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 3.0500 loss: 3.0004 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 3.0004 2023/06/04 17:59:17 - mmengine - INFO - Epoch(train) [9][2220/2569] lr: 3.6000e-02 eta: 1 day, 2:52:42 time: 0.2747 data_time: 0.0078 memory: 5828 grad_norm: 3.0022 loss: 2.8909 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8909 2023/06/04 17:59:23 - mmengine - INFO - Epoch(train) [9][2240/2569] lr: 3.6000e-02 eta: 1 day, 2:52:37 time: 0.2664 data_time: 0.0072 memory: 5828 grad_norm: 2.9781 loss: 2.6078 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6078 2023/06/04 17:59:28 - mmengine - INFO - Epoch(train) [9][2260/2569] lr: 3.6000e-02 eta: 1 day, 2:52:31 time: 0.2662 data_time: 0.0077 memory: 5828 grad_norm: 3.0101 loss: 2.5234 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5234 2023/06/04 17:59:33 - mmengine - INFO - Epoch(train) [9][2280/2569] lr: 3.6000e-02 eta: 1 day, 2:52:24 time: 0.2623 data_time: 0.0076 memory: 5828 grad_norm: 3.0362 loss: 2.6453 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6453 2023/06/04 17:59:39 - mmengine - INFO - Epoch(train) [9][2300/2569] lr: 3.6000e-02 eta: 1 day, 2:52:21 time: 0.2719 data_time: 0.0073 memory: 5828 grad_norm: 3.0313 loss: 2.5825 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5825 2023/06/04 17:59:44 - mmengine - INFO - Epoch(train) [9][2320/2569] lr: 3.6000e-02 eta: 1 day, 2:52:13 time: 0.2603 data_time: 0.0076 memory: 5828 grad_norm: 2.9602 loss: 2.6749 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6749 2023/06/04 17:59:49 - mmengine - INFO - Epoch(train) [9][2340/2569] lr: 3.6000e-02 eta: 1 day, 2:52:05 time: 0.2597 data_time: 0.0077 memory: 5828 grad_norm: 3.0175 loss: 2.7536 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7536 2023/06/04 17:59:54 - mmengine - INFO - Epoch(train) [9][2360/2569] lr: 3.6000e-02 eta: 1 day, 2:51:58 time: 0.2604 data_time: 0.0079 memory: 5828 grad_norm: 3.0550 loss: 2.5981 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5981 2023/06/04 18:00:00 - mmengine - INFO - Epoch(train) [9][2380/2569] lr: 3.6000e-02 eta: 1 day, 2:51:51 time: 0.2608 data_time: 0.0082 memory: 5828 grad_norm: 2.9981 loss: 3.0501 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 3.0501 2023/06/04 18:00:05 - mmengine - INFO - Epoch(train) [9][2400/2569] lr: 3.6000e-02 eta: 1 day, 2:51:49 time: 0.2763 data_time: 0.0079 memory: 5828 grad_norm: 2.9617 loss: 2.7735 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7735 2023/06/04 18:00:10 - mmengine - INFO - Epoch(train) [9][2420/2569] lr: 3.6000e-02 eta: 1 day, 2:51:41 time: 0.2588 data_time: 0.0083 memory: 5828 grad_norm: 3.0112 loss: 3.1012 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 3.1012 2023/06/04 18:00:16 - mmengine - INFO - Epoch(train) [9][2440/2569] lr: 3.6000e-02 eta: 1 day, 2:51:39 time: 0.2782 data_time: 0.0083 memory: 5828 grad_norm: 3.0085 loss: 2.9430 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9430 2023/06/04 18:00:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:00:21 - mmengine - INFO - Epoch(train) [9][2460/2569] lr: 3.6000e-02 eta: 1 day, 2:51:31 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 3.0052 loss: 2.5281 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5281 2023/06/04 18:00:26 - mmengine - INFO - Epoch(train) [9][2480/2569] lr: 3.6000e-02 eta: 1 day, 2:51:28 time: 0.2736 data_time: 0.0073 memory: 5828 grad_norm: 3.0105 loss: 2.6117 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6117 2023/06/04 18:00:32 - mmengine - INFO - Epoch(train) [9][2500/2569] lr: 3.6000e-02 eta: 1 day, 2:51:20 time: 0.2587 data_time: 0.0076 memory: 5828 grad_norm: 2.9597 loss: 2.7613 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7613 2023/06/04 18:00:37 - mmengine - INFO - Epoch(train) [9][2520/2569] lr: 3.6000e-02 eta: 1 day, 2:51:14 time: 0.2652 data_time: 0.0076 memory: 5828 grad_norm: 2.9781 loss: 2.4836 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4836 2023/06/04 18:00:42 - mmengine - INFO - Epoch(train) [9][2540/2569] lr: 3.6000e-02 eta: 1 day, 2:51:08 time: 0.2624 data_time: 0.0082 memory: 5828 grad_norm: 2.9855 loss: 2.6555 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6555 2023/06/04 18:00:47 - mmengine - INFO - Epoch(train) [9][2560/2569] lr: 3.6000e-02 eta: 1 day, 2:50:59 time: 0.2573 data_time: 0.0077 memory: 5828 grad_norm: 3.0071 loss: 2.6788 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6788 2023/06/04 18:00:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:00:50 - mmengine - INFO - Epoch(train) [9][2569/2569] lr: 3.6000e-02 eta: 1 day, 2:50:54 time: 0.2497 data_time: 0.0075 memory: 5828 grad_norm: 3.0044 loss: 2.6654 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6654 2023/06/04 18:00:57 - mmengine - INFO - Epoch(train) [10][ 20/2569] lr: 4.0000e-02 eta: 1 day, 2:51:14 time: 0.3488 data_time: 0.0589 memory: 5828 grad_norm: 3.0068 loss: 2.8736 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8736 2023/06/04 18:01:02 - mmengine - INFO - Epoch(train) [10][ 40/2569] lr: 4.0000e-02 eta: 1 day, 2:51:08 time: 0.2649 data_time: 0.0073 memory: 5828 grad_norm: 2.9927 loss: 3.1191 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1191 2023/06/04 18:01:07 - mmengine - INFO - Epoch(train) [10][ 60/2569] lr: 4.0000e-02 eta: 1 day, 2:51:02 time: 0.2648 data_time: 0.0077 memory: 5828 grad_norm: 3.0058 loss: 2.6110 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6110 2023/06/04 18:01:13 - mmengine - INFO - Epoch(train) [10][ 80/2569] lr: 4.0000e-02 eta: 1 day, 2:50:57 time: 0.2681 data_time: 0.0077 memory: 5828 grad_norm: 2.9643 loss: 2.4451 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4451 2023/06/04 18:01:18 - mmengine - INFO - Epoch(train) [10][ 100/2569] lr: 4.0000e-02 eta: 1 day, 2:50:53 time: 0.2693 data_time: 0.0075 memory: 5828 grad_norm: 2.9515 loss: 2.7383 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7383 2023/06/04 18:01:23 - mmengine - INFO - Epoch(train) [10][ 120/2569] lr: 4.0000e-02 eta: 1 day, 2:50:47 time: 0.2669 data_time: 0.0080 memory: 5828 grad_norm: 3.0038 loss: 3.0202 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0202 2023/06/04 18:01:29 - mmengine - INFO - Epoch(train) [10][ 140/2569] lr: 4.0000e-02 eta: 1 day, 2:50:41 time: 0.2641 data_time: 0.0076 memory: 5828 grad_norm: 3.0142 loss: 2.8263 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8263 2023/06/04 18:01:34 - mmengine - INFO - Epoch(train) [10][ 160/2569] lr: 4.0000e-02 eta: 1 day, 2:50:37 time: 0.2702 data_time: 0.0078 memory: 5828 grad_norm: 3.0179 loss: 2.4508 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4508 2023/06/04 18:01:39 - mmengine - INFO - Epoch(train) [10][ 180/2569] lr: 4.0000e-02 eta: 1 day, 2:50:31 time: 0.2663 data_time: 0.0079 memory: 5828 grad_norm: 2.9898 loss: 2.9151 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9151 2023/06/04 18:01:45 - mmengine - INFO - Epoch(train) [10][ 200/2569] lr: 4.0000e-02 eta: 1 day, 2:50:25 time: 0.2640 data_time: 0.0079 memory: 5828 grad_norm: 2.9950 loss: 2.6785 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6785 2023/06/04 18:01:50 - mmengine - INFO - Epoch(train) [10][ 220/2569] lr: 4.0000e-02 eta: 1 day, 2:50:17 time: 0.2597 data_time: 0.0072 memory: 5828 grad_norm: 2.9809 loss: 2.6387 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6387 2023/06/04 18:01:55 - mmengine - INFO - Epoch(train) [10][ 240/2569] lr: 4.0000e-02 eta: 1 day, 2:50:11 time: 0.2623 data_time: 0.0079 memory: 5828 grad_norm: 2.9396 loss: 2.7515 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7515 2023/06/04 18:02:00 - mmengine - INFO - Epoch(train) [10][ 260/2569] lr: 4.0000e-02 eta: 1 day, 2:50:06 time: 0.2704 data_time: 0.0075 memory: 5828 grad_norm: 2.9630 loss: 2.5852 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5852 2023/06/04 18:02:06 - mmengine - INFO - Epoch(train) [10][ 280/2569] lr: 4.0000e-02 eta: 1 day, 2:50:00 time: 0.2632 data_time: 0.0082 memory: 5828 grad_norm: 2.9607 loss: 2.8235 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8235 2023/06/04 18:02:11 - mmengine - INFO - Epoch(train) [10][ 300/2569] lr: 4.0000e-02 eta: 1 day, 2:49:56 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 2.9511 loss: 2.7581 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7581 2023/06/04 18:02:16 - mmengine - INFO - Epoch(train) [10][ 320/2569] lr: 4.0000e-02 eta: 1 day, 2:49:49 time: 0.2618 data_time: 0.0080 memory: 5828 grad_norm: 2.9504 loss: 2.7756 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7756 2023/06/04 18:02:22 - mmengine - INFO - Epoch(train) [10][ 340/2569] lr: 4.0000e-02 eta: 1 day, 2:49:42 time: 0.2614 data_time: 0.0078 memory: 5828 grad_norm: 2.9369 loss: 2.6727 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6727 2023/06/04 18:02:27 - mmengine - INFO - Epoch(train) [10][ 360/2569] lr: 4.0000e-02 eta: 1 day, 2:49:35 time: 0.2613 data_time: 0.0084 memory: 5828 grad_norm: 2.9723 loss: 2.7539 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7539 2023/06/04 18:02:32 - mmengine - INFO - Epoch(train) [10][ 380/2569] lr: 4.0000e-02 eta: 1 day, 2:49:28 time: 0.2613 data_time: 0.0073 memory: 5828 grad_norm: 2.9374 loss: 2.9097 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9097 2023/06/04 18:02:37 - mmengine - INFO - Epoch(train) [10][ 400/2569] lr: 4.0000e-02 eta: 1 day, 2:49:21 time: 0.2615 data_time: 0.0076 memory: 5828 grad_norm: 2.9719 loss: 2.6085 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6085 2023/06/04 18:02:42 - mmengine - INFO - Epoch(train) [10][ 420/2569] lr: 4.0000e-02 eta: 1 day, 2:49:14 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 2.9939 loss: 2.9211 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.9211 2023/06/04 18:02:48 - mmengine - INFO - Epoch(train) [10][ 440/2569] lr: 4.0000e-02 eta: 1 day, 2:49:07 time: 0.2604 data_time: 0.0080 memory: 5828 grad_norm: 2.9970 loss: 2.7660 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7660 2023/06/04 18:02:53 - mmengine - INFO - Epoch(train) [10][ 460/2569] lr: 4.0000e-02 eta: 1 day, 2:49:01 time: 0.2648 data_time: 0.0078 memory: 5828 grad_norm: 2.9508 loss: 2.6396 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6396 2023/06/04 18:02:58 - mmengine - INFO - Epoch(train) [10][ 480/2569] lr: 4.0000e-02 eta: 1 day, 2:48:57 time: 0.2698 data_time: 0.0078 memory: 5828 grad_norm: 2.8857 loss: 2.6352 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6352 2023/06/04 18:03:04 - mmengine - INFO - Epoch(train) [10][ 500/2569] lr: 4.0000e-02 eta: 1 day, 2:48:50 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 2.9523 loss: 2.8644 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8644 2023/06/04 18:03:09 - mmengine - INFO - Epoch(train) [10][ 520/2569] lr: 4.0000e-02 eta: 1 day, 2:48:43 time: 0.2598 data_time: 0.0076 memory: 5828 grad_norm: 2.9615 loss: 2.8631 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8631 2023/06/04 18:03:14 - mmengine - INFO - Epoch(train) [10][ 540/2569] lr: 4.0000e-02 eta: 1 day, 2:48:37 time: 0.2658 data_time: 0.0078 memory: 5828 grad_norm: 2.9981 loss: 2.6901 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6901 2023/06/04 18:03:20 - mmengine - INFO - Epoch(train) [10][ 560/2569] lr: 4.0000e-02 eta: 1 day, 2:48:32 time: 0.2656 data_time: 0.0079 memory: 5828 grad_norm: 2.9491 loss: 2.6061 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6061 2023/06/04 18:03:25 - mmengine - INFO - Epoch(train) [10][ 580/2569] lr: 4.0000e-02 eta: 1 day, 2:48:27 time: 0.2687 data_time: 0.0094 memory: 5828 grad_norm: 2.9364 loss: 2.8712 top1_acc: 0.0000 top5_acc: 0.7500 loss_cls: 2.8712 2023/06/04 18:03:30 - mmengine - INFO - Epoch(train) [10][ 600/2569] lr: 4.0000e-02 eta: 1 day, 2:48:23 time: 0.2710 data_time: 0.0075 memory: 5828 grad_norm: 2.9890 loss: 2.5579 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5579 2023/06/04 18:03:36 - mmengine - INFO - Epoch(train) [10][ 620/2569] lr: 4.0000e-02 eta: 1 day, 2:48:19 time: 0.2709 data_time: 0.0074 memory: 5828 grad_norm: 2.9064 loss: 2.8538 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8538 2023/06/04 18:03:41 - mmengine - INFO - Epoch(train) [10][ 640/2569] lr: 4.0000e-02 eta: 1 day, 2:48:12 time: 0.2635 data_time: 0.0082 memory: 5828 grad_norm: 2.9749 loss: 2.6592 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6592 2023/06/04 18:03:46 - mmengine - INFO - Epoch(train) [10][ 660/2569] lr: 4.0000e-02 eta: 1 day, 2:48:05 time: 0.2598 data_time: 0.0077 memory: 5828 grad_norm: 2.9708 loss: 2.8642 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.8642 2023/06/04 18:03:52 - mmengine - INFO - Epoch(train) [10][ 680/2569] lr: 4.0000e-02 eta: 1 day, 2:48:00 time: 0.2686 data_time: 0.0075 memory: 5828 grad_norm: 2.9139 loss: 2.4529 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4529 2023/06/04 18:03:57 - mmengine - INFO - Epoch(train) [10][ 700/2569] lr: 4.0000e-02 eta: 1 day, 2:47:54 time: 0.2661 data_time: 0.0077 memory: 5828 grad_norm: 2.9860 loss: 2.8856 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8856 2023/06/04 18:04:02 - mmengine - INFO - Epoch(train) [10][ 720/2569] lr: 4.0000e-02 eta: 1 day, 2:47:50 time: 0.2692 data_time: 0.0079 memory: 5828 grad_norm: 2.9129 loss: 2.5764 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5764 2023/06/04 18:04:08 - mmengine - INFO - Epoch(train) [10][ 740/2569] lr: 4.0000e-02 eta: 1 day, 2:47:44 time: 0.2663 data_time: 0.0073 memory: 5828 grad_norm: 2.9516 loss: 2.7381 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7381 2023/06/04 18:04:13 - mmengine - INFO - Epoch(train) [10][ 760/2569] lr: 4.0000e-02 eta: 1 day, 2:47:38 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 2.9622 loss: 3.1435 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1435 2023/06/04 18:04:18 - mmengine - INFO - Epoch(train) [10][ 780/2569] lr: 4.0000e-02 eta: 1 day, 2:47:32 time: 0.2667 data_time: 0.0077 memory: 5828 grad_norm: 2.9454 loss: 2.6016 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6016 2023/06/04 18:04:24 - mmengine - INFO - Epoch(train) [10][ 800/2569] lr: 4.0000e-02 eta: 1 day, 2:47:27 time: 0.2677 data_time: 0.0084 memory: 5828 grad_norm: 2.9685 loss: 2.8728 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8728 2023/06/04 18:04:29 - mmengine - INFO - Epoch(train) [10][ 820/2569] lr: 4.0000e-02 eta: 1 day, 2:47:20 time: 0.2605 data_time: 0.0078 memory: 5828 grad_norm: 2.9245 loss: 3.0907 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0907 2023/06/04 18:04:34 - mmengine - INFO - Epoch(train) [10][ 840/2569] lr: 4.0000e-02 eta: 1 day, 2:47:16 time: 0.2704 data_time: 0.0079 memory: 5828 grad_norm: 2.9096 loss: 2.3397 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3397 2023/06/04 18:04:39 - mmengine - INFO - Epoch(train) [10][ 860/2569] lr: 4.0000e-02 eta: 1 day, 2:47:08 time: 0.2588 data_time: 0.0081 memory: 5828 grad_norm: 2.9281 loss: 2.5442 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5442 2023/06/04 18:04:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:04:45 - mmengine - INFO - Epoch(train) [10][ 880/2569] lr: 4.0000e-02 eta: 1 day, 2:47:02 time: 0.2635 data_time: 0.0076 memory: 5828 grad_norm: 2.9841 loss: 2.8354 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8354 2023/06/04 18:04:50 - mmengine - INFO - Epoch(train) [10][ 900/2569] lr: 4.0000e-02 eta: 1 day, 2:46:57 time: 0.2675 data_time: 0.0089 memory: 5828 grad_norm: 2.9161 loss: 2.8149 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8149 2023/06/04 18:04:55 - mmengine - INFO - Epoch(train) [10][ 920/2569] lr: 4.0000e-02 eta: 1 day, 2:46:51 time: 0.2674 data_time: 0.0085 memory: 5828 grad_norm: 2.9394 loss: 3.0810 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0810 2023/06/04 18:05:01 - mmengine - INFO - Epoch(train) [10][ 940/2569] lr: 4.0000e-02 eta: 1 day, 2:46:45 time: 0.2634 data_time: 0.0077 memory: 5828 grad_norm: 2.9131 loss: 2.9006 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9006 2023/06/04 18:05:06 - mmengine - INFO - Epoch(train) [10][ 960/2569] lr: 4.0000e-02 eta: 1 day, 2:46:39 time: 0.2659 data_time: 0.0079 memory: 5828 grad_norm: 2.9213 loss: 2.6136 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6136 2023/06/04 18:05:11 - mmengine - INFO - Epoch(train) [10][ 980/2569] lr: 4.0000e-02 eta: 1 day, 2:46:34 time: 0.2663 data_time: 0.0075 memory: 5828 grad_norm: 2.9274 loss: 3.0539 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0539 2023/06/04 18:05:16 - mmengine - INFO - Epoch(train) [10][1000/2569] lr: 4.0000e-02 eta: 1 day, 2:46:27 time: 0.2617 data_time: 0.0081 memory: 5828 grad_norm: 2.9566 loss: 2.7814 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7814 2023/06/04 18:05:22 - mmengine - INFO - Epoch(train) [10][1020/2569] lr: 4.0000e-02 eta: 1 day, 2:46:23 time: 0.2711 data_time: 0.0078 memory: 5828 grad_norm: 2.9576 loss: 2.5376 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5376 2023/06/04 18:05:27 - mmengine - INFO - Epoch(train) [10][1040/2569] lr: 4.0000e-02 eta: 1 day, 2:46:15 time: 0.2591 data_time: 0.0080 memory: 5828 grad_norm: 2.9021 loss: 2.7579 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7579 2023/06/04 18:05:32 - mmengine - INFO - Epoch(train) [10][1060/2569] lr: 4.0000e-02 eta: 1 day, 2:46:11 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 2.9523 loss: 2.8693 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8693 2023/06/04 18:05:38 - mmengine - INFO - Epoch(train) [10][1080/2569] lr: 4.0000e-02 eta: 1 day, 2:46:05 time: 0.2659 data_time: 0.0081 memory: 5828 grad_norm: 2.8911 loss: 2.7126 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7126 2023/06/04 18:05:43 - mmengine - INFO - Epoch(train) [10][1100/2569] lr: 4.0000e-02 eta: 1 day, 2:45:58 time: 0.2598 data_time: 0.0072 memory: 5828 grad_norm: 2.9198 loss: 2.6996 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6996 2023/06/04 18:05:48 - mmengine - INFO - Epoch(train) [10][1120/2569] lr: 4.0000e-02 eta: 1 day, 2:45:52 time: 0.2663 data_time: 0.0077 memory: 5828 grad_norm: 2.9395 loss: 3.0367 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0367 2023/06/04 18:05:54 - mmengine - INFO - Epoch(train) [10][1140/2569] lr: 4.0000e-02 eta: 1 day, 2:45:46 time: 0.2629 data_time: 0.0079 memory: 5828 grad_norm: 2.8789 loss: 3.0443 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0443 2023/06/04 18:05:59 - mmengine - INFO - Epoch(train) [10][1160/2569] lr: 4.0000e-02 eta: 1 day, 2:45:41 time: 0.2684 data_time: 0.0077 memory: 5828 grad_norm: 2.8950 loss: 2.9082 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.9082 2023/06/04 18:06:04 - mmengine - INFO - Epoch(train) [10][1180/2569] lr: 4.0000e-02 eta: 1 day, 2:45:36 time: 0.2687 data_time: 0.0074 memory: 5828 grad_norm: 2.9421 loss: 2.9338 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9338 2023/06/04 18:06:10 - mmengine - INFO - Epoch(train) [10][1200/2569] lr: 4.0000e-02 eta: 1 day, 2:45:29 time: 0.2610 data_time: 0.0077 memory: 5828 grad_norm: 2.9276 loss: 2.8330 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8330 2023/06/04 18:06:15 - mmengine - INFO - Epoch(train) [10][1220/2569] lr: 4.0000e-02 eta: 1 day, 2:45:22 time: 0.2609 data_time: 0.0076 memory: 5828 grad_norm: 2.9679 loss: 2.5367 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5367 2023/06/04 18:06:20 - mmengine - INFO - Epoch(train) [10][1240/2569] lr: 4.0000e-02 eta: 1 day, 2:45:16 time: 0.2664 data_time: 0.0084 memory: 5828 grad_norm: 2.9094 loss: 2.5417 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5417 2023/06/04 18:06:25 - mmengine - INFO - Epoch(train) [10][1260/2569] lr: 4.0000e-02 eta: 1 day, 2:45:10 time: 0.2629 data_time: 0.0078 memory: 5828 grad_norm: 2.9037 loss: 2.8811 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8811 2023/06/04 18:06:31 - mmengine - INFO - Epoch(train) [10][1280/2569] lr: 4.0000e-02 eta: 1 day, 2:45:07 time: 0.2745 data_time: 0.0077 memory: 5828 grad_norm: 3.0145 loss: 2.7222 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7222 2023/06/04 18:06:36 - mmengine - INFO - Epoch(train) [10][1300/2569] lr: 4.0000e-02 eta: 1 day, 2:45:00 time: 0.2618 data_time: 0.0077 memory: 5828 grad_norm: 2.9408 loss: 2.8232 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8232 2023/06/04 18:06:42 - mmengine - INFO - Epoch(train) [10][1320/2569] lr: 4.0000e-02 eta: 1 day, 2:44:57 time: 0.2744 data_time: 0.0077 memory: 5828 grad_norm: 2.9784 loss: 3.0160 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0160 2023/06/04 18:06:47 - mmengine - INFO - Epoch(train) [10][1340/2569] lr: 4.0000e-02 eta: 1 day, 2:44:50 time: 0.2616 data_time: 0.0079 memory: 5828 grad_norm: 2.8845 loss: 2.7729 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7729 2023/06/04 18:06:52 - mmengine - INFO - Epoch(train) [10][1360/2569] lr: 4.0000e-02 eta: 1 day, 2:44:45 time: 0.2669 data_time: 0.0085 memory: 5828 grad_norm: 2.8282 loss: 2.8023 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8023 2023/06/04 18:06:57 - mmengine - INFO - Epoch(train) [10][1380/2569] lr: 4.0000e-02 eta: 1 day, 2:44:38 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 2.8898 loss: 2.5580 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5580 2023/06/04 18:07:03 - mmengine - INFO - Epoch(train) [10][1400/2569] lr: 4.0000e-02 eta: 1 day, 2:44:31 time: 0.2620 data_time: 0.0077 memory: 5828 grad_norm: 2.9178 loss: 2.8646 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.8646 2023/06/04 18:07:08 - mmengine - INFO - Epoch(train) [10][1420/2569] lr: 4.0000e-02 eta: 1 day, 2:44:25 time: 0.2651 data_time: 0.0081 memory: 5828 grad_norm: 2.9426 loss: 2.7896 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7896 2023/06/04 18:07:13 - mmengine - INFO - Epoch(train) [10][1440/2569] lr: 4.0000e-02 eta: 1 day, 2:44:20 time: 0.2673 data_time: 0.0081 memory: 5828 grad_norm: 2.9423 loss: 2.6668 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6668 2023/06/04 18:07:19 - mmengine - INFO - Epoch(train) [10][1460/2569] lr: 4.0000e-02 eta: 1 day, 2:44:15 time: 0.2697 data_time: 0.0090 memory: 5828 grad_norm: 2.8688 loss: 2.8154 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8154 2023/06/04 18:07:24 - mmengine - INFO - Epoch(train) [10][1480/2569] lr: 4.0000e-02 eta: 1 day, 2:44:09 time: 0.2639 data_time: 0.0079 memory: 5828 grad_norm: 2.9273 loss: 2.7242 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7242 2023/06/04 18:07:29 - mmengine - INFO - Epoch(train) [10][1500/2569] lr: 4.0000e-02 eta: 1 day, 2:44:02 time: 0.2622 data_time: 0.0078 memory: 5828 grad_norm: 2.9030 loss: 2.7333 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7333 2023/06/04 18:07:35 - mmengine - INFO - Epoch(train) [10][1520/2569] lr: 4.0000e-02 eta: 1 day, 2:43:57 time: 0.2672 data_time: 0.0080 memory: 5828 grad_norm: 2.9476 loss: 2.5624 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5624 2023/06/04 18:07:40 - mmengine - INFO - Epoch(train) [10][1540/2569] lr: 4.0000e-02 eta: 1 day, 2:43:50 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 2.9585 loss: 2.6906 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6906 2023/06/04 18:07:45 - mmengine - INFO - Epoch(train) [10][1560/2569] lr: 4.0000e-02 eta: 1 day, 2:43:47 time: 0.2740 data_time: 0.0076 memory: 5828 grad_norm: 2.9093 loss: 2.7878 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7878 2023/06/04 18:07:51 - mmengine - INFO - Epoch(train) [10][1580/2569] lr: 4.0000e-02 eta: 1 day, 2:43:41 time: 0.2650 data_time: 0.0081 memory: 5828 grad_norm: 2.8942 loss: 2.6342 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6342 2023/06/04 18:07:56 - mmengine - INFO - Epoch(train) [10][1600/2569] lr: 4.0000e-02 eta: 1 day, 2:43:36 time: 0.2686 data_time: 0.0082 memory: 5828 grad_norm: 2.9675 loss: 2.5731 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5731 2023/06/04 18:08:01 - mmengine - INFO - Epoch(train) [10][1620/2569] lr: 4.0000e-02 eta: 1 day, 2:43:30 time: 0.2622 data_time: 0.0078 memory: 5828 grad_norm: 2.9234 loss: 2.8654 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8654 2023/06/04 18:08:06 - mmengine - INFO - Epoch(train) [10][1640/2569] lr: 4.0000e-02 eta: 1 day, 2:43:23 time: 0.2637 data_time: 0.0081 memory: 5828 grad_norm: 2.8479 loss: 2.5960 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5960 2023/06/04 18:08:12 - mmengine - INFO - Epoch(train) [10][1660/2569] lr: 4.0000e-02 eta: 1 day, 2:43:16 time: 0.2610 data_time: 0.0076 memory: 5828 grad_norm: 2.8580 loss: 2.4515 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4515 2023/06/04 18:08:17 - mmengine - INFO - Epoch(train) [10][1680/2569] lr: 4.0000e-02 eta: 1 day, 2:43:12 time: 0.2715 data_time: 0.0077 memory: 5828 grad_norm: 2.9001 loss: 2.7359 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7359 2023/06/04 18:08:23 - mmengine - INFO - Epoch(train) [10][1700/2569] lr: 4.0000e-02 eta: 1 day, 2:43:09 time: 0.2743 data_time: 0.0075 memory: 5828 grad_norm: 2.8590 loss: 2.9262 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9262 2023/06/04 18:08:28 - mmengine - INFO - Epoch(train) [10][1720/2569] lr: 4.0000e-02 eta: 1 day, 2:43:06 time: 0.2744 data_time: 0.0070 memory: 5828 grad_norm: 2.9298 loss: 2.3933 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3933 2023/06/04 18:08:33 - mmengine - INFO - Epoch(train) [10][1740/2569] lr: 4.0000e-02 eta: 1 day, 2:43:00 time: 0.2641 data_time: 0.0080 memory: 5828 grad_norm: 2.9329 loss: 2.8020 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8020 2023/06/04 18:08:39 - mmengine - INFO - Epoch(train) [10][1760/2569] lr: 4.0000e-02 eta: 1 day, 2:42:55 time: 0.2680 data_time: 0.0074 memory: 5828 grad_norm: 2.8718 loss: 2.7124 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7124 2023/06/04 18:08:44 - mmengine - INFO - Epoch(train) [10][1780/2569] lr: 4.0000e-02 eta: 1 day, 2:42:48 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 2.8611 loss: 2.5855 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5855 2023/06/04 18:08:49 - mmengine - INFO - Epoch(train) [10][1800/2569] lr: 4.0000e-02 eta: 1 day, 2:42:42 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 2.9294 loss: 3.0103 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0103 2023/06/04 18:08:55 - mmengine - INFO - Epoch(train) [10][1820/2569] lr: 4.0000e-02 eta: 1 day, 2:42:37 time: 0.2687 data_time: 0.0080 memory: 5828 grad_norm: 2.9409 loss: 2.8385 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8385 2023/06/04 18:09:00 - mmengine - INFO - Epoch(train) [10][1840/2569] lr: 4.0000e-02 eta: 1 day, 2:42:31 time: 0.2648 data_time: 0.0077 memory: 5828 grad_norm: 2.8900 loss: 2.6789 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6789 2023/06/04 18:09:05 - mmengine - INFO - Epoch(train) [10][1860/2569] lr: 4.0000e-02 eta: 1 day, 2:42:25 time: 0.2649 data_time: 0.0083 memory: 5828 grad_norm: 2.8797 loss: 2.6065 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6065 2023/06/04 18:09:10 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:09:11 - mmengine - INFO - Epoch(train) [10][1880/2569] lr: 4.0000e-02 eta: 1 day, 2:42:20 time: 0.2673 data_time: 0.0081 memory: 5828 grad_norm: 2.8978 loss: 3.0236 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.0236 2023/06/04 18:09:16 - mmengine - INFO - Epoch(train) [10][1900/2569] lr: 4.0000e-02 eta: 1 day, 2:42:15 time: 0.2657 data_time: 0.0075 memory: 5828 grad_norm: 2.9146 loss: 2.8096 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8096 2023/06/04 18:09:21 - mmengine - INFO - Epoch(train) [10][1920/2569] lr: 4.0000e-02 eta: 1 day, 2:42:09 time: 0.2646 data_time: 0.0076 memory: 5828 grad_norm: 2.8980 loss: 2.6980 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6980 2023/06/04 18:09:26 - mmengine - INFO - Epoch(train) [10][1940/2569] lr: 4.0000e-02 eta: 1 day, 2:42:04 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 2.9080 loss: 2.8900 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8900 2023/06/04 18:09:32 - mmengine - INFO - Epoch(train) [10][1960/2569] lr: 4.0000e-02 eta: 1 day, 2:41:58 time: 0.2647 data_time: 0.0078 memory: 5828 grad_norm: 2.8986 loss: 3.0077 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0077 2023/06/04 18:09:37 - mmengine - INFO - Epoch(train) [10][1980/2569] lr: 4.0000e-02 eta: 1 day, 2:41:51 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 2.9303 loss: 2.8316 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8316 2023/06/04 18:09:42 - mmengine - INFO - Epoch(train) [10][2000/2569] lr: 4.0000e-02 eta: 1 day, 2:41:47 time: 0.2726 data_time: 0.0073 memory: 5828 grad_norm: 2.9137 loss: 2.5978 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5978 2023/06/04 18:09:48 - mmengine - INFO - Epoch(train) [10][2020/2569] lr: 4.0000e-02 eta: 1 day, 2:41:40 time: 0.2601 data_time: 0.0082 memory: 5828 grad_norm: 2.8717 loss: 2.6218 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6218 2023/06/04 18:09:53 - mmengine - INFO - Epoch(train) [10][2040/2569] lr: 4.0000e-02 eta: 1 day, 2:41:33 time: 0.2630 data_time: 0.0080 memory: 5828 grad_norm: 2.8381 loss: 2.5702 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5702 2023/06/04 18:09:58 - mmengine - INFO - Epoch(train) [10][2060/2569] lr: 4.0000e-02 eta: 1 day, 2:41:28 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 2.9330 loss: 2.6006 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6006 2023/06/04 18:10:04 - mmengine - INFO - Epoch(train) [10][2080/2569] lr: 4.0000e-02 eta: 1 day, 2:41:22 time: 0.2639 data_time: 0.0076 memory: 5828 grad_norm: 2.8572 loss: 2.8231 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8231 2023/06/04 18:10:09 - mmengine - INFO - Epoch(train) [10][2100/2569] lr: 4.0000e-02 eta: 1 day, 2:41:16 time: 0.2636 data_time: 0.0079 memory: 5828 grad_norm: 2.8661 loss: 3.0061 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0061 2023/06/04 18:10:14 - mmengine - INFO - Epoch(train) [10][2120/2569] lr: 4.0000e-02 eta: 1 day, 2:41:09 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 2.9185 loss: 2.8033 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8033 2023/06/04 18:10:19 - mmengine - INFO - Epoch(train) [10][2140/2569] lr: 4.0000e-02 eta: 1 day, 2:41:03 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 2.9412 loss: 2.7990 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7990 2023/06/04 18:10:25 - mmengine - INFO - Epoch(train) [10][2160/2569] lr: 4.0000e-02 eta: 1 day, 2:40:58 time: 0.2674 data_time: 0.0080 memory: 5828 grad_norm: 2.8566 loss: 2.5352 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5352 2023/06/04 18:10:30 - mmengine - INFO - Epoch(train) [10][2180/2569] lr: 4.0000e-02 eta: 1 day, 2:40:51 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 2.9233 loss: 2.4726 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4726 2023/06/04 18:10:35 - mmengine - INFO - Epoch(train) [10][2200/2569] lr: 4.0000e-02 eta: 1 day, 2:40:45 time: 0.2655 data_time: 0.0078 memory: 5828 grad_norm: 2.8970 loss: 2.7591 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7591 2023/06/04 18:10:40 - mmengine - INFO - Epoch(train) [10][2220/2569] lr: 4.0000e-02 eta: 1 day, 2:40:38 time: 0.2607 data_time: 0.0078 memory: 5828 grad_norm: 2.9659 loss: 2.4520 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4520 2023/06/04 18:10:46 - mmengine - INFO - Epoch(train) [10][2240/2569] lr: 4.0000e-02 eta: 1 day, 2:40:35 time: 0.2733 data_time: 0.0077 memory: 5828 grad_norm: 2.9023 loss: 2.3158 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3158 2023/06/04 18:10:51 - mmengine - INFO - Epoch(train) [10][2260/2569] lr: 4.0000e-02 eta: 1 day, 2:40:31 time: 0.2705 data_time: 0.0085 memory: 5828 grad_norm: 2.8865 loss: 2.5345 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5345 2023/06/04 18:10:57 - mmengine - INFO - Epoch(train) [10][2280/2569] lr: 4.0000e-02 eta: 1 day, 2:40:25 time: 0.2646 data_time: 0.0078 memory: 5828 grad_norm: 2.8827 loss: 2.7900 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7900 2023/06/04 18:11:02 - mmengine - INFO - Epoch(train) [10][2300/2569] lr: 4.0000e-02 eta: 1 day, 2:40:19 time: 0.2656 data_time: 0.0083 memory: 5828 grad_norm: 2.8240 loss: 2.5442 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5442 2023/06/04 18:11:07 - mmengine - INFO - Epoch(train) [10][2320/2569] lr: 4.0000e-02 eta: 1 day, 2:40:14 time: 0.2693 data_time: 0.0077 memory: 5828 grad_norm: 2.9161 loss: 3.0315 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0315 2023/06/04 18:11:13 - mmengine - INFO - Epoch(train) [10][2340/2569] lr: 4.0000e-02 eta: 1 day, 2:40:09 time: 0.2658 data_time: 0.0075 memory: 5828 grad_norm: 2.8680 loss: 2.6450 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6450 2023/06/04 18:11:18 - mmengine - INFO - Epoch(train) [10][2360/2569] lr: 4.0000e-02 eta: 1 day, 2:40:05 time: 0.2711 data_time: 0.0080 memory: 5828 grad_norm: 2.9369 loss: 2.8483 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.8483 2023/06/04 18:11:23 - mmengine - INFO - Epoch(train) [10][2380/2569] lr: 4.0000e-02 eta: 1 day, 2:40:00 time: 0.2678 data_time: 0.0079 memory: 5828 grad_norm: 2.8578 loss: 3.0675 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0675 2023/06/04 18:11:29 - mmengine - INFO - Epoch(train) [10][2400/2569] lr: 4.0000e-02 eta: 1 day, 2:39:55 time: 0.2685 data_time: 0.0080 memory: 5828 grad_norm: 2.8979 loss: 2.8582 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8582 2023/06/04 18:11:34 - mmengine - INFO - Epoch(train) [10][2420/2569] lr: 4.0000e-02 eta: 1 day, 2:39:49 time: 0.2668 data_time: 0.0078 memory: 5828 grad_norm: 2.8831 loss: 2.4564 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.4564 2023/06/04 18:11:40 - mmengine - INFO - Epoch(train) [10][2440/2569] lr: 4.0000e-02 eta: 1 day, 2:39:47 time: 0.2765 data_time: 0.0073 memory: 5828 grad_norm: 2.8690 loss: 2.8391 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8391 2023/06/04 18:11:45 - mmengine - INFO - Epoch(train) [10][2460/2569] lr: 4.0000e-02 eta: 1 day, 2:39:40 time: 0.2596 data_time: 0.0083 memory: 5828 grad_norm: 2.9053 loss: 2.4242 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4242 2023/06/04 18:11:50 - mmengine - INFO - Epoch(train) [10][2480/2569] lr: 4.0000e-02 eta: 1 day, 2:39:38 time: 0.2794 data_time: 0.0072 memory: 5828 grad_norm: 2.8751 loss: 2.8774 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8774 2023/06/04 18:11:56 - mmengine - INFO - Epoch(train) [10][2500/2569] lr: 4.0000e-02 eta: 1 day, 2:39:31 time: 0.2611 data_time: 0.0078 memory: 5828 grad_norm: 2.8437 loss: 2.4412 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4412 2023/06/04 18:12:01 - mmengine - INFO - Epoch(train) [10][2520/2569] lr: 4.0000e-02 eta: 1 day, 2:39:29 time: 0.2806 data_time: 0.0074 memory: 5828 grad_norm: 2.9051 loss: 2.3933 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3933 2023/06/04 18:12:07 - mmengine - INFO - Epoch(train) [10][2540/2569] lr: 4.0000e-02 eta: 1 day, 2:39:23 time: 0.2626 data_time: 0.0078 memory: 5828 grad_norm: 2.8649 loss: 2.7942 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7942 2023/06/04 18:12:12 - mmengine - INFO - Epoch(train) [10][2560/2569] lr: 4.0000e-02 eta: 1 day, 2:39:15 time: 0.2573 data_time: 0.0078 memory: 5828 grad_norm: 2.8479 loss: 2.6000 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6000 2023/06/04 18:12:14 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:12:14 - mmengine - INFO - Epoch(train) [10][2569/2569] lr: 4.0000e-02 eta: 1 day, 2:39:10 time: 0.2484 data_time: 0.0072 memory: 5828 grad_norm: 2.8580 loss: 2.8206 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8206 2023/06/04 18:12:18 - mmengine - INFO - Epoch(val) [10][ 20/260] eta: 0:00:49 time: 0.2046 data_time: 0.1457 memory: 1238 2023/06/04 18:12:21 - mmengine - INFO - Epoch(val) [10][ 40/260] eta: 0:00:38 time: 0.1477 data_time: 0.0892 memory: 1238 2023/06/04 18:12:24 - mmengine - INFO - Epoch(val) [10][ 60/260] eta: 0:00:33 time: 0.1487 data_time: 0.0901 memory: 1238 2023/06/04 18:12:26 - mmengine - INFO - Epoch(val) [10][ 80/260] eta: 0:00:28 time: 0.1272 data_time: 0.0685 memory: 1238 2023/06/04 18:12:30 - mmengine - INFO - Epoch(val) [10][100/260] eta: 0:00:24 time: 0.1522 data_time: 0.0932 memory: 1238 2023/06/04 18:12:32 - mmengine - INFO - Epoch(val) [10][120/260] eta: 0:00:21 time: 0.1231 data_time: 0.0646 memory: 1238 2023/06/04 18:12:35 - mmengine - INFO - Epoch(val) [10][140/260] eta: 0:00:18 time: 0.1491 data_time: 0.0906 memory: 1238 2023/06/04 18:12:37 - mmengine - INFO - Epoch(val) [10][160/260] eta: 0:00:14 time: 0.1239 data_time: 0.0651 memory: 1238 2023/06/04 18:12:41 - mmengine - INFO - Epoch(val) [10][180/260] eta: 0:00:12 time: 0.1778 data_time: 0.1194 memory: 1238 2023/06/04 18:12:44 - mmengine - INFO - Epoch(val) [10][200/260] eta: 0:00:08 time: 0.1343 data_time: 0.0759 memory: 1238 2023/06/04 18:12:47 - mmengine - INFO - Epoch(val) [10][220/260] eta: 0:00:05 time: 0.1537 data_time: 0.0953 memory: 1238 2023/06/04 18:12:50 - mmengine - INFO - Epoch(val) [10][240/260] eta: 0:00:02 time: 0.1402 data_time: 0.0820 memory: 1238 2023/06/04 18:12:52 - mmengine - INFO - Epoch(val) [10][260/260] eta: 0:00:00 time: 0.1310 data_time: 0.0746 memory: 1238 2023/06/04 18:12:59 - mmengine - INFO - Epoch(val) [10][260/260] acc/top1: 0.4742 acc/top5: 0.7245 acc/mean1: 0.4650 data_time: 0.0884 time: 0.1468 2023/06/04 18:12:59 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_5.pth is removed 2023/06/04 18:13:02 - mmengine - INFO - The best checkpoint with 0.4742 acc/top1 at 10 epoch is saved to best_acc_top1_epoch_10.pth. 2023/06/04 18:13:08 - mmengine - INFO - Epoch(train) [11][ 20/2569] lr: 4.0000e-02 eta: 1 day, 2:39:14 time: 0.3033 data_time: 0.0537 memory: 5828 grad_norm: 2.8678 loss: 2.7376 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7376 2023/06/04 18:13:13 - mmengine - INFO - Epoch(train) [11][ 40/2569] lr: 4.0000e-02 eta: 1 day, 2:39:08 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 2.9331 loss: 2.5814 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5814 2023/06/04 18:13:18 - mmengine - INFO - Epoch(train) [11][ 60/2569] lr: 4.0000e-02 eta: 1 day, 2:39:01 time: 0.2643 data_time: 0.0075 memory: 5828 grad_norm: 2.8772 loss: 2.8967 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8967 2023/06/04 18:13:24 - mmengine - INFO - Epoch(train) [11][ 80/2569] lr: 4.0000e-02 eta: 1 day, 2:38:54 time: 0.2608 data_time: 0.0084 memory: 5828 grad_norm: 2.8929 loss: 2.7298 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7298 2023/06/04 18:13:29 - mmengine - INFO - Epoch(train) [11][ 100/2569] lr: 4.0000e-02 eta: 1 day, 2:38:50 time: 0.2696 data_time: 0.0079 memory: 5828 grad_norm: 2.8662 loss: 2.6693 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6693 2023/06/04 18:13:34 - mmengine - INFO - Epoch(train) [11][ 120/2569] lr: 4.0000e-02 eta: 1 day, 2:38:44 time: 0.2631 data_time: 0.0077 memory: 5828 grad_norm: 2.8879 loss: 2.5881 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5881 2023/06/04 18:13:40 - mmengine - INFO - Epoch(train) [11][ 140/2569] lr: 4.0000e-02 eta: 1 day, 2:38:39 time: 0.2711 data_time: 0.0069 memory: 5828 grad_norm: 2.8643 loss: 2.8438 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8438 2023/06/04 18:13:45 - mmengine - INFO - Epoch(train) [11][ 160/2569] lr: 4.0000e-02 eta: 1 day, 2:38:32 time: 0.2609 data_time: 0.0074 memory: 5828 grad_norm: 2.8412 loss: 2.3663 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3663 2023/06/04 18:13:50 - mmengine - INFO - Epoch(train) [11][ 180/2569] lr: 4.0000e-02 eta: 1 day, 2:38:28 time: 0.2706 data_time: 0.0088 memory: 5828 grad_norm: 2.8761 loss: 2.8686 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.8686 2023/06/04 18:13:56 - mmengine - INFO - Epoch(train) [11][ 200/2569] lr: 4.0000e-02 eta: 1 day, 2:38:23 time: 0.2669 data_time: 0.0076 memory: 5828 grad_norm: 2.8096 loss: 2.5971 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5971 2023/06/04 18:14:01 - mmengine - INFO - Epoch(train) [11][ 220/2569] lr: 4.0000e-02 eta: 1 day, 2:38:16 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 2.8609 loss: 2.6634 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.6634 2023/06/04 18:14:06 - mmengine - INFO - Epoch(train) [11][ 240/2569] lr: 4.0000e-02 eta: 1 day, 2:38:10 time: 0.2657 data_time: 0.0075 memory: 5828 grad_norm: 2.8408 loss: 2.5550 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5550 2023/06/04 18:14:12 - mmengine - INFO - Epoch(train) [11][ 260/2569] lr: 4.0000e-02 eta: 1 day, 2:38:07 time: 0.2749 data_time: 0.0076 memory: 5828 grad_norm: 2.8114 loss: 2.7902 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7902 2023/06/04 18:14:17 - mmengine - INFO - Epoch(train) [11][ 280/2569] lr: 4.0000e-02 eta: 1 day, 2:38:04 time: 0.2745 data_time: 0.0078 memory: 5828 grad_norm: 2.8363 loss: 2.6467 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6467 2023/06/04 18:14:23 - mmengine - INFO - Epoch(train) [11][ 300/2569] lr: 4.0000e-02 eta: 1 day, 2:38:00 time: 0.2705 data_time: 0.0077 memory: 5828 grad_norm: 2.8990 loss: 2.9972 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9972 2023/06/04 18:14:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:14:28 - mmengine - INFO - Epoch(train) [11][ 320/2569] lr: 4.0000e-02 eta: 1 day, 2:37:56 time: 0.2710 data_time: 0.0076 memory: 5828 grad_norm: 2.8740 loss: 2.5878 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5878 2023/06/04 18:14:33 - mmengine - INFO - Epoch(train) [11][ 340/2569] lr: 4.0000e-02 eta: 1 day, 2:37:48 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 2.9007 loss: 2.5240 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5240 2023/06/04 18:14:39 - mmengine - INFO - Epoch(train) [11][ 360/2569] lr: 4.0000e-02 eta: 1 day, 2:37:42 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 2.8385 loss: 2.3690 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3690 2023/06/04 18:14:44 - mmengine - INFO - Epoch(train) [11][ 380/2569] lr: 4.0000e-02 eta: 1 day, 2:37:39 time: 0.2741 data_time: 0.0073 memory: 5828 grad_norm: 2.8636 loss: 2.5282 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5282 2023/06/04 18:14:49 - mmengine - INFO - Epoch(train) [11][ 400/2569] lr: 4.0000e-02 eta: 1 day, 2:37:34 time: 0.2695 data_time: 0.0076 memory: 5828 grad_norm: 2.8674 loss: 3.1041 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.1041 2023/06/04 18:14:55 - mmengine - INFO - Epoch(train) [11][ 420/2569] lr: 4.0000e-02 eta: 1 day, 2:37:31 time: 0.2757 data_time: 0.0078 memory: 5828 grad_norm: 2.8765 loss: 2.6414 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6414 2023/06/04 18:15:00 - mmengine - INFO - Epoch(train) [11][ 440/2569] lr: 4.0000e-02 eta: 1 day, 2:37:24 time: 0.2586 data_time: 0.0079 memory: 5828 grad_norm: 2.9305 loss: 2.7284 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7284 2023/06/04 18:15:05 - mmengine - INFO - Epoch(train) [11][ 460/2569] lr: 4.0000e-02 eta: 1 day, 2:37:18 time: 0.2665 data_time: 0.0075 memory: 5828 grad_norm: 2.8734 loss: 2.7231 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7231 2023/06/04 18:15:11 - mmengine - INFO - Epoch(train) [11][ 480/2569] lr: 4.0000e-02 eta: 1 day, 2:37:11 time: 0.2613 data_time: 0.0083 memory: 5828 grad_norm: 2.8551 loss: 2.5886 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5886 2023/06/04 18:15:16 - mmengine - INFO - Epoch(train) [11][ 500/2569] lr: 4.0000e-02 eta: 1 day, 2:37:06 time: 0.2648 data_time: 0.0077 memory: 5828 grad_norm: 2.8423 loss: 2.8696 top1_acc: 0.0000 top5_acc: 0.0000 loss_cls: 2.8696 2023/06/04 18:15:21 - mmengine - INFO - Epoch(train) [11][ 520/2569] lr: 4.0000e-02 eta: 1 day, 2:36:59 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 2.9041 loss: 2.7509 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7509 2023/06/04 18:15:27 - mmengine - INFO - Epoch(train) [11][ 540/2569] lr: 4.0000e-02 eta: 1 day, 2:36:53 time: 0.2637 data_time: 0.0079 memory: 5828 grad_norm: 2.8964 loss: 2.5644 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5644 2023/06/04 18:15:32 - mmengine - INFO - Epoch(train) [11][ 560/2569] lr: 4.0000e-02 eta: 1 day, 2:36:46 time: 0.2604 data_time: 0.0078 memory: 5828 grad_norm: 2.8797 loss: 2.5745 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5745 2023/06/04 18:15:37 - mmengine - INFO - Epoch(train) [11][ 580/2569] lr: 4.0000e-02 eta: 1 day, 2:36:39 time: 0.2618 data_time: 0.0078 memory: 5828 grad_norm: 2.8780 loss: 2.4877 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4877 2023/06/04 18:15:42 - mmengine - INFO - Epoch(train) [11][ 600/2569] lr: 4.0000e-02 eta: 1 day, 2:36:32 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 2.8435 loss: 2.5997 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5997 2023/06/04 18:15:47 - mmengine - INFO - Epoch(train) [11][ 620/2569] lr: 4.0000e-02 eta: 1 day, 2:36:25 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 2.8891 loss: 2.6690 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6690 2023/06/04 18:15:53 - mmengine - INFO - Epoch(train) [11][ 640/2569] lr: 4.0000e-02 eta: 1 day, 2:36:20 time: 0.2697 data_time: 0.0076 memory: 5828 grad_norm: 2.8983 loss: 2.6452 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6452 2023/06/04 18:15:58 - mmengine - INFO - Epoch(train) [11][ 660/2569] lr: 4.0000e-02 eta: 1 day, 2:36:14 time: 0.2617 data_time: 0.0077 memory: 5828 grad_norm: 2.8957 loss: 2.7867 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7867 2023/06/04 18:16:03 - mmengine - INFO - Epoch(train) [11][ 680/2569] lr: 4.0000e-02 eta: 1 day, 2:36:10 time: 0.2721 data_time: 0.0079 memory: 5828 grad_norm: 2.8680 loss: 2.6692 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6692 2023/06/04 18:16:09 - mmengine - INFO - Epoch(train) [11][ 700/2569] lr: 4.0000e-02 eta: 1 day, 2:36:05 time: 0.2706 data_time: 0.0079 memory: 5828 grad_norm: 2.8772 loss: 2.5205 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5205 2023/06/04 18:16:14 - mmengine - INFO - Epoch(train) [11][ 720/2569] lr: 4.0000e-02 eta: 1 day, 2:36:02 time: 0.2749 data_time: 0.0081 memory: 5828 grad_norm: 2.8738 loss: 2.9334 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9334 2023/06/04 18:16:20 - mmengine - INFO - Epoch(train) [11][ 740/2569] lr: 4.0000e-02 eta: 1 day, 2:35:58 time: 0.2698 data_time: 0.0076 memory: 5828 grad_norm: 2.8807 loss: 2.6755 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6755 2023/06/04 18:16:25 - mmengine - INFO - Epoch(train) [11][ 760/2569] lr: 4.0000e-02 eta: 1 day, 2:35:53 time: 0.2696 data_time: 0.0076 memory: 5828 grad_norm: 2.8980 loss: 2.9709 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9709 2023/06/04 18:16:31 - mmengine - INFO - Epoch(train) [11][ 780/2569] lr: 4.0000e-02 eta: 1 day, 2:35:49 time: 0.2710 data_time: 0.0076 memory: 5828 grad_norm: 2.8677 loss: 3.0335 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0335 2023/06/04 18:16:36 - mmengine - INFO - Epoch(train) [11][ 800/2569] lr: 4.0000e-02 eta: 1 day, 2:35:46 time: 0.2764 data_time: 0.0074 memory: 5828 grad_norm: 2.8346 loss: 2.4192 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4192 2023/06/04 18:16:41 - mmengine - INFO - Epoch(train) [11][ 820/2569] lr: 4.0000e-02 eta: 1 day, 2:35:39 time: 0.2593 data_time: 0.0078 memory: 5828 grad_norm: 2.8516 loss: 2.4879 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4879 2023/06/04 18:16:46 - mmengine - INFO - Epoch(train) [11][ 840/2569] lr: 4.0000e-02 eta: 1 day, 2:35:32 time: 0.2597 data_time: 0.0081 memory: 5828 grad_norm: 2.8750 loss: 2.9046 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9046 2023/06/04 18:16:52 - mmengine - INFO - Epoch(train) [11][ 860/2569] lr: 4.0000e-02 eta: 1 day, 2:35:25 time: 0.2613 data_time: 0.0079 memory: 5828 grad_norm: 2.8845 loss: 2.3668 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3668 2023/06/04 18:16:57 - mmengine - INFO - Epoch(train) [11][ 880/2569] lr: 4.0000e-02 eta: 1 day, 2:35:19 time: 0.2659 data_time: 0.0073 memory: 5828 grad_norm: 2.8550 loss: 2.7359 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7359 2023/06/04 18:17:02 - mmengine - INFO - Epoch(train) [11][ 900/2569] lr: 4.0000e-02 eta: 1 day, 2:35:15 time: 0.2708 data_time: 0.0085 memory: 5828 grad_norm: 2.8478 loss: 2.7593 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7593 2023/06/04 18:17:08 - mmengine - INFO - Epoch(train) [11][ 920/2569] lr: 4.0000e-02 eta: 1 day, 2:35:09 time: 0.2636 data_time: 0.0089 memory: 5828 grad_norm: 2.8175 loss: 3.2840 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2840 2023/06/04 18:17:13 - mmengine - INFO - Epoch(train) [11][ 940/2569] lr: 4.0000e-02 eta: 1 day, 2:35:02 time: 0.2604 data_time: 0.0079 memory: 5828 grad_norm: 2.9304 loss: 2.4565 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4565 2023/06/04 18:17:18 - mmengine - INFO - Epoch(train) [11][ 960/2569] lr: 4.0000e-02 eta: 1 day, 2:34:57 time: 0.2676 data_time: 0.0078 memory: 5828 grad_norm: 2.8627 loss: 2.7484 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7484 2023/06/04 18:17:23 - mmengine - INFO - Epoch(train) [11][ 980/2569] lr: 4.0000e-02 eta: 1 day, 2:34:49 time: 0.2595 data_time: 0.0076 memory: 5828 grad_norm: 2.8719 loss: 2.6171 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6171 2023/06/04 18:17:29 - mmengine - INFO - Epoch(train) [11][1000/2569] lr: 4.0000e-02 eta: 1 day, 2:34:44 time: 0.2662 data_time: 0.0079 memory: 5828 grad_norm: 2.9187 loss: 2.8049 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8049 2023/06/04 18:17:34 - mmengine - INFO - Epoch(train) [11][1020/2569] lr: 4.0000e-02 eta: 1 day, 2:34:37 time: 0.2611 data_time: 0.0082 memory: 5828 grad_norm: 2.8681 loss: 2.7808 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7808 2023/06/04 18:17:39 - mmengine - INFO - Epoch(train) [11][1040/2569] lr: 4.0000e-02 eta: 1 day, 2:34:31 time: 0.2653 data_time: 0.0083 memory: 5828 grad_norm: 2.8184 loss: 2.7822 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7822 2023/06/04 18:17:45 - mmengine - INFO - Epoch(train) [11][1060/2569] lr: 4.0000e-02 eta: 1 day, 2:34:24 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 2.9446 loss: 2.6496 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6496 2023/06/04 18:17:50 - mmengine - INFO - Epoch(train) [11][1080/2569] lr: 4.0000e-02 eta: 1 day, 2:34:17 time: 0.2611 data_time: 0.0080 memory: 5828 grad_norm: 2.8791 loss: 2.8474 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8474 2023/06/04 18:17:55 - mmengine - INFO - Epoch(train) [11][1100/2569] lr: 4.0000e-02 eta: 1 day, 2:34:11 time: 0.2636 data_time: 0.0081 memory: 5828 grad_norm: 2.8932 loss: 2.6068 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6068 2023/06/04 18:18:00 - mmengine - INFO - Epoch(train) [11][1120/2569] lr: 4.0000e-02 eta: 1 day, 2:34:04 time: 0.2598 data_time: 0.0073 memory: 5828 grad_norm: 2.8579 loss: 2.7868 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7868 2023/06/04 18:18:06 - mmengine - INFO - Epoch(train) [11][1140/2569] lr: 4.0000e-02 eta: 1 day, 2:33:58 time: 0.2658 data_time: 0.0074 memory: 5828 grad_norm: 2.8813 loss: 2.5569 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5569 2023/06/04 18:18:11 - mmengine - INFO - Epoch(train) [11][1160/2569] lr: 4.0000e-02 eta: 1 day, 2:33:54 time: 0.2704 data_time: 0.0078 memory: 5828 grad_norm: 2.8735 loss: 2.7235 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7235 2023/06/04 18:18:16 - mmengine - INFO - Epoch(train) [11][1180/2569] lr: 4.0000e-02 eta: 1 day, 2:33:49 time: 0.2658 data_time: 0.0075 memory: 5828 grad_norm: 2.8194 loss: 2.7847 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7847 2023/06/04 18:18:22 - mmengine - INFO - Epoch(train) [11][1200/2569] lr: 4.0000e-02 eta: 1 day, 2:33:44 time: 0.2697 data_time: 0.0076 memory: 5828 grad_norm: 2.8483 loss: 2.5495 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5495 2023/06/04 18:18:27 - mmengine - INFO - Epoch(train) [11][1220/2569] lr: 4.0000e-02 eta: 1 day, 2:33:38 time: 0.2658 data_time: 0.0080 memory: 5828 grad_norm: 2.8670 loss: 2.8974 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.8974 2023/06/04 18:18:32 - mmengine - INFO - Epoch(train) [11][1240/2569] lr: 4.0000e-02 eta: 1 day, 2:33:34 time: 0.2709 data_time: 0.0077 memory: 5828 grad_norm: 2.8603 loss: 2.5744 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5744 2023/06/04 18:18:38 - mmengine - INFO - Epoch(train) [11][1260/2569] lr: 4.0000e-02 eta: 1 day, 2:33:29 time: 0.2658 data_time: 0.0078 memory: 5828 grad_norm: 2.8477 loss: 2.6438 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6438 2023/06/04 18:18:43 - mmengine - INFO - Epoch(train) [11][1280/2569] lr: 4.0000e-02 eta: 1 day, 2:33:24 time: 0.2703 data_time: 0.0078 memory: 5828 grad_norm: 2.8456 loss: 2.7302 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7302 2023/06/04 18:18:49 - mmengine - INFO - Epoch(train) [11][1300/2569] lr: 4.0000e-02 eta: 1 day, 2:33:20 time: 0.2697 data_time: 0.0077 memory: 5828 grad_norm: 2.8191 loss: 2.8769 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8769 2023/06/04 18:18:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:18:54 - mmengine - INFO - Epoch(train) [11][1320/2569] lr: 4.0000e-02 eta: 1 day, 2:33:12 time: 0.2586 data_time: 0.0076 memory: 5828 grad_norm: 2.8694 loss: 2.7605 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7605 2023/06/04 18:18:59 - mmengine - INFO - Epoch(train) [11][1340/2569] lr: 4.0000e-02 eta: 1 day, 2:33:08 time: 0.2705 data_time: 0.0077 memory: 5828 grad_norm: 2.8849 loss: 2.6105 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6105 2023/06/04 18:19:04 - mmengine - INFO - Epoch(train) [11][1360/2569] lr: 4.0000e-02 eta: 1 day, 2:33:00 time: 0.2586 data_time: 0.0081 memory: 5828 grad_norm: 2.8391 loss: 2.6120 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6120 2023/06/04 18:19:10 - mmengine - INFO - Epoch(train) [11][1380/2569] lr: 4.0000e-02 eta: 1 day, 2:32:55 time: 0.2657 data_time: 0.0075 memory: 5828 grad_norm: 2.8220 loss: 2.9510 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9510 2023/06/04 18:19:15 - mmengine - INFO - Epoch(train) [11][1400/2569] lr: 4.0000e-02 eta: 1 day, 2:32:49 time: 0.2673 data_time: 0.0078 memory: 5828 grad_norm: 2.8728 loss: 2.5878 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5878 2023/06/04 18:19:20 - mmengine - INFO - Epoch(train) [11][1420/2569] lr: 4.0000e-02 eta: 1 day, 2:32:44 time: 0.2652 data_time: 0.0078 memory: 5828 grad_norm: 2.8556 loss: 2.5872 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5872 2023/06/04 18:19:26 - mmengine - INFO - Epoch(train) [11][1440/2569] lr: 4.0000e-02 eta: 1 day, 2:32:38 time: 0.2670 data_time: 0.0076 memory: 5828 grad_norm: 2.8548 loss: 2.7232 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7232 2023/06/04 18:19:31 - mmengine - INFO - Epoch(train) [11][1460/2569] lr: 4.0000e-02 eta: 1 day, 2:32:36 time: 0.2768 data_time: 0.0077 memory: 5828 grad_norm: 2.8828 loss: 2.6316 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6316 2023/06/04 18:19:37 - mmengine - INFO - Epoch(train) [11][1480/2569] lr: 4.0000e-02 eta: 1 day, 2:32:33 time: 0.2764 data_time: 0.0073 memory: 5828 grad_norm: 2.8456 loss: 2.7957 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7957 2023/06/04 18:19:42 - mmengine - INFO - Epoch(train) [11][1500/2569] lr: 4.0000e-02 eta: 1 day, 2:32:28 time: 0.2687 data_time: 0.0077 memory: 5828 grad_norm: 2.8599 loss: 2.6209 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6209 2023/06/04 18:19:48 - mmengine - INFO - Epoch(train) [11][1520/2569] lr: 4.0000e-02 eta: 1 day, 2:32:27 time: 0.2843 data_time: 0.0079 memory: 5828 grad_norm: 2.8454 loss: 2.2841 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2841 2023/06/04 18:19:53 - mmengine - INFO - Epoch(train) [11][1540/2569] lr: 4.0000e-02 eta: 1 day, 2:32:21 time: 0.2633 data_time: 0.0082 memory: 5828 grad_norm: 2.8645 loss: 2.4587 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4587 2023/06/04 18:19:58 - mmengine - INFO - Epoch(train) [11][1560/2569] lr: 4.0000e-02 eta: 1 day, 2:32:16 time: 0.2674 data_time: 0.0075 memory: 5828 grad_norm: 2.8845 loss: 2.7897 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7897 2023/06/04 18:20:04 - mmengine - INFO - Epoch(train) [11][1580/2569] lr: 4.0000e-02 eta: 1 day, 2:32:10 time: 0.2653 data_time: 0.0071 memory: 5828 grad_norm: 2.8880 loss: 2.8021 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8021 2023/06/04 18:20:09 - mmengine - INFO - Epoch(train) [11][1600/2569] lr: 4.0000e-02 eta: 1 day, 2:32:06 time: 0.2717 data_time: 0.0082 memory: 5828 grad_norm: 2.8517 loss: 2.5200 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5200 2023/06/04 18:20:14 - mmengine - INFO - Epoch(train) [11][1620/2569] lr: 4.0000e-02 eta: 1 day, 2:31:59 time: 0.2615 data_time: 0.0074 memory: 5828 grad_norm: 2.9010 loss: 2.9262 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9262 2023/06/04 18:20:20 - mmengine - INFO - Epoch(train) [11][1640/2569] lr: 4.0000e-02 eta: 1 day, 2:31:53 time: 0.2622 data_time: 0.0081 memory: 5828 grad_norm: 2.8762 loss: 2.5761 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5761 2023/06/04 18:20:25 - mmengine - INFO - Epoch(train) [11][1660/2569] lr: 4.0000e-02 eta: 1 day, 2:31:46 time: 0.2616 data_time: 0.0071 memory: 5828 grad_norm: 2.8997 loss: 2.4389 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4389 2023/06/04 18:20:30 - mmengine - INFO - Epoch(train) [11][1680/2569] lr: 4.0000e-02 eta: 1 day, 2:31:42 time: 0.2708 data_time: 0.0076 memory: 5828 grad_norm: 2.8823 loss: 2.6349 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6349 2023/06/04 18:20:35 - mmengine - INFO - Epoch(train) [11][1700/2569] lr: 4.0000e-02 eta: 1 day, 2:31:35 time: 0.2604 data_time: 0.0080 memory: 5828 grad_norm: 2.8328 loss: 2.6454 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6454 2023/06/04 18:20:41 - mmengine - INFO - Epoch(train) [11][1720/2569] lr: 4.0000e-02 eta: 1 day, 2:31:30 time: 0.2681 data_time: 0.0082 memory: 5828 grad_norm: 2.8392 loss: 2.7009 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7009 2023/06/04 18:20:46 - mmengine - INFO - Epoch(train) [11][1740/2569] lr: 4.0000e-02 eta: 1 day, 2:31:23 time: 0.2603 data_time: 0.0083 memory: 5828 grad_norm: 2.8028 loss: 2.6605 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6605 2023/06/04 18:20:51 - mmengine - INFO - Epoch(train) [11][1760/2569] lr: 4.0000e-02 eta: 1 day, 2:31:18 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 2.8158 loss: 2.6441 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6441 2023/06/04 18:20:57 - mmengine - INFO - Epoch(train) [11][1780/2569] lr: 4.0000e-02 eta: 1 day, 2:31:13 time: 0.2658 data_time: 0.0074 memory: 5828 grad_norm: 2.9507 loss: 2.6398 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6398 2023/06/04 18:21:02 - mmengine - INFO - Epoch(train) [11][1800/2569] lr: 4.0000e-02 eta: 1 day, 2:31:05 time: 0.2600 data_time: 0.0078 memory: 5828 grad_norm: 2.9089 loss: 2.9873 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9873 2023/06/04 18:21:07 - mmengine - INFO - Epoch(train) [11][1820/2569] lr: 4.0000e-02 eta: 1 day, 2:31:02 time: 0.2753 data_time: 0.0075 memory: 5828 grad_norm: 2.8338 loss: 2.9581 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9581 2023/06/04 18:21:13 - mmengine - INFO - Epoch(train) [11][1840/2569] lr: 4.0000e-02 eta: 1 day, 2:30:55 time: 0.2591 data_time: 0.0080 memory: 5828 grad_norm: 2.8897 loss: 2.7703 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7703 2023/06/04 18:21:18 - mmengine - INFO - Epoch(train) [11][1860/2569] lr: 4.0000e-02 eta: 1 day, 2:30:52 time: 0.2751 data_time: 0.0079 memory: 5828 grad_norm: 2.8804 loss: 2.6675 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6675 2023/06/04 18:21:23 - mmengine - INFO - Epoch(train) [11][1880/2569] lr: 4.0000e-02 eta: 1 day, 2:30:45 time: 0.2613 data_time: 0.0075 memory: 5828 grad_norm: 2.8710 loss: 2.8063 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8063 2023/06/04 18:21:29 - mmengine - INFO - Epoch(train) [11][1900/2569] lr: 4.0000e-02 eta: 1 day, 2:30:41 time: 0.2700 data_time: 0.0089 memory: 5828 grad_norm: 2.8642 loss: 2.5448 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5448 2023/06/04 18:21:34 - mmengine - INFO - Epoch(train) [11][1920/2569] lr: 4.0000e-02 eta: 1 day, 2:30:33 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 2.8940 loss: 2.7169 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7169 2023/06/04 18:21:39 - mmengine - INFO - Epoch(train) [11][1940/2569] lr: 4.0000e-02 eta: 1 day, 2:30:27 time: 0.2633 data_time: 0.0080 memory: 5828 grad_norm: 2.8614 loss: 2.6490 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6490 2023/06/04 18:21:44 - mmengine - INFO - Epoch(train) [11][1960/2569] lr: 4.0000e-02 eta: 1 day, 2:30:20 time: 0.2591 data_time: 0.0074 memory: 5828 grad_norm: 2.8748 loss: 2.6485 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6485 2023/06/04 18:21:50 - mmengine - INFO - Epoch(train) [11][1980/2569] lr: 4.0000e-02 eta: 1 day, 2:30:16 time: 0.2716 data_time: 0.0084 memory: 5828 grad_norm: 2.8278 loss: 2.7715 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7715 2023/06/04 18:21:55 - mmengine - INFO - Epoch(train) [11][2000/2569] lr: 4.0000e-02 eta: 1 day, 2:30:13 time: 0.2770 data_time: 0.0072 memory: 5828 grad_norm: 2.8156 loss: 2.8332 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8332 2023/06/04 18:22:01 - mmengine - INFO - Epoch(train) [11][2020/2569] lr: 4.0000e-02 eta: 1 day, 2:30:07 time: 0.2648 data_time: 0.0079 memory: 5828 grad_norm: 2.8392 loss: 2.7757 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7757 2023/06/04 18:22:06 - mmengine - INFO - Epoch(train) [11][2040/2569] lr: 4.0000e-02 eta: 1 day, 2:30:01 time: 0.2636 data_time: 0.0079 memory: 5828 grad_norm: 2.7836 loss: 2.5843 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5843 2023/06/04 18:22:11 - mmengine - INFO - Epoch(train) [11][2060/2569] lr: 4.0000e-02 eta: 1 day, 2:29:54 time: 0.2609 data_time: 0.0081 memory: 5828 grad_norm: 2.8363 loss: 2.7147 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7147 2023/06/04 18:22:17 - mmengine - INFO - Epoch(train) [11][2080/2569] lr: 4.0000e-02 eta: 1 day, 2:29:51 time: 0.2766 data_time: 0.0075 memory: 5828 grad_norm: 2.7622 loss: 2.8316 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8316 2023/06/04 18:22:22 - mmengine - INFO - Epoch(train) [11][2100/2569] lr: 4.0000e-02 eta: 1 day, 2:29:46 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 2.8393 loss: 2.9955 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9955 2023/06/04 18:22:27 - mmengine - INFO - Epoch(train) [11][2120/2569] lr: 4.0000e-02 eta: 1 day, 2:29:42 time: 0.2708 data_time: 0.0075 memory: 5828 grad_norm: 2.8904 loss: 2.6758 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6758 2023/06/04 18:22:33 - mmengine - INFO - Epoch(train) [11][2140/2569] lr: 4.0000e-02 eta: 1 day, 2:29:35 time: 0.2618 data_time: 0.0076 memory: 5828 grad_norm: 2.8115 loss: 2.9751 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9751 2023/06/04 18:22:38 - mmengine - INFO - Epoch(train) [11][2160/2569] lr: 4.0000e-02 eta: 1 day, 2:29:31 time: 0.2711 data_time: 0.0077 memory: 5828 grad_norm: 2.8180 loss: 2.9764 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.9764 2023/06/04 18:22:43 - mmengine - INFO - Epoch(train) [11][2180/2569] lr: 4.0000e-02 eta: 1 day, 2:29:26 time: 0.2703 data_time: 0.0077 memory: 5828 grad_norm: 2.8794 loss: 3.0055 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0055 2023/06/04 18:22:49 - mmengine - INFO - Epoch(train) [11][2200/2569] lr: 4.0000e-02 eta: 1 day, 2:29:21 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 2.8672 loss: 2.6500 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6500 2023/06/04 18:22:54 - mmengine - INFO - Epoch(train) [11][2220/2569] lr: 4.0000e-02 eta: 1 day, 2:29:15 time: 0.2615 data_time: 0.0077 memory: 5828 grad_norm: 2.8521 loss: 2.6759 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6759 2023/06/04 18:23:00 - mmengine - INFO - Epoch(train) [11][2240/2569] lr: 4.0000e-02 eta: 1 day, 2:29:12 time: 0.2760 data_time: 0.0077 memory: 5828 grad_norm: 2.8693 loss: 2.7177 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7177 2023/06/04 18:23:05 - mmengine - INFO - Epoch(train) [11][2260/2569] lr: 4.0000e-02 eta: 1 day, 2:29:06 time: 0.2651 data_time: 0.0079 memory: 5828 grad_norm: 2.8583 loss: 2.5776 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5776 2023/06/04 18:23:10 - mmengine - INFO - Epoch(train) [11][2280/2569] lr: 4.0000e-02 eta: 1 day, 2:29:01 time: 0.2688 data_time: 0.0078 memory: 5828 grad_norm: 2.8727 loss: 2.6413 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6413 2023/06/04 18:23:16 - mmengine - INFO - Epoch(train) [11][2300/2569] lr: 4.0000e-02 eta: 1 day, 2:28:55 time: 0.2658 data_time: 0.0076 memory: 5828 grad_norm: 2.8420 loss: 2.6987 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6987 2023/06/04 18:23:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:23:21 - mmengine - INFO - Epoch(train) [11][2320/2569] lr: 4.0000e-02 eta: 1 day, 2:28:51 time: 0.2700 data_time: 0.0078 memory: 5828 grad_norm: 2.8190 loss: 2.5470 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5470 2023/06/04 18:23:26 - mmengine - INFO - Epoch(train) [11][2340/2569] lr: 4.0000e-02 eta: 1 day, 2:28:47 time: 0.2710 data_time: 0.0080 memory: 5828 grad_norm: 2.8344 loss: 3.0042 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0042 2023/06/04 18:23:32 - mmengine - INFO - Epoch(train) [11][2360/2569] lr: 4.0000e-02 eta: 1 day, 2:28:40 time: 0.2616 data_time: 0.0079 memory: 5828 grad_norm: 2.8596 loss: 2.7306 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7306 2023/06/04 18:23:37 - mmengine - INFO - Epoch(train) [11][2380/2569] lr: 4.0000e-02 eta: 1 day, 2:28:33 time: 0.2602 data_time: 0.0083 memory: 5828 grad_norm: 2.8817 loss: 2.6820 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6820 2023/06/04 18:23:42 - mmengine - INFO - Epoch(train) [11][2400/2569] lr: 4.0000e-02 eta: 1 day, 2:28:30 time: 0.2776 data_time: 0.0076 memory: 5828 grad_norm: 2.8528 loss: 2.6311 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6311 2023/06/04 18:23:48 - mmengine - INFO - Epoch(train) [11][2420/2569] lr: 4.0000e-02 eta: 1 day, 2:28:25 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 2.8442 loss: 2.7752 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7752 2023/06/04 18:23:53 - mmengine - INFO - Epoch(train) [11][2440/2569] lr: 4.0000e-02 eta: 1 day, 2:28:19 time: 0.2647 data_time: 0.0075 memory: 5828 grad_norm: 2.8187 loss: 2.2989 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2989 2023/06/04 18:23:58 - mmengine - INFO - Epoch(train) [11][2460/2569] lr: 4.0000e-02 eta: 1 day, 2:28:12 time: 0.2614 data_time: 0.0082 memory: 5828 grad_norm: 2.9040 loss: 2.7528 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7528 2023/06/04 18:24:04 - mmengine - INFO - Epoch(train) [11][2480/2569] lr: 4.0000e-02 eta: 1 day, 2:28:08 time: 0.2714 data_time: 0.0081 memory: 5828 grad_norm: 2.8379 loss: 2.8484 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8484 2023/06/04 18:24:09 - mmengine - INFO - Epoch(train) [11][2500/2569] lr: 4.0000e-02 eta: 1 day, 2:28:04 time: 0.2708 data_time: 0.0077 memory: 5828 grad_norm: 2.9021 loss: 2.7083 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7083 2023/06/04 18:24:14 - mmengine - INFO - Epoch(train) [11][2520/2569] lr: 4.0000e-02 eta: 1 day, 2:27:58 time: 0.2644 data_time: 0.0095 memory: 5828 grad_norm: 2.8276 loss: 2.5650 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5650 2023/06/04 18:24:20 - mmengine - INFO - Epoch(train) [11][2540/2569] lr: 4.0000e-02 eta: 1 day, 2:27:54 time: 0.2725 data_time: 0.0086 memory: 5828 grad_norm: 2.8145 loss: 2.7028 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7028 2023/06/04 18:24:25 - mmengine - INFO - Epoch(train) [11][2560/2569] lr: 4.0000e-02 eta: 1 day, 2:27:47 time: 0.2600 data_time: 0.0078 memory: 5828 grad_norm: 2.8606 loss: 2.4786 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4786 2023/06/04 18:24:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:24:27 - mmengine - INFO - Epoch(train) [11][2569/2569] lr: 4.0000e-02 eta: 1 day, 2:27:42 time: 0.2530 data_time: 0.0068 memory: 5828 grad_norm: 2.8743 loss: 2.6542 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6542 2023/06/04 18:24:34 - mmengine - INFO - Epoch(train) [12][ 20/2569] lr: 4.0000e-02 eta: 1 day, 2:27:56 time: 0.3448 data_time: 0.0698 memory: 5828 grad_norm: 2.8377 loss: 2.9574 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9574 2023/06/04 18:24:40 - mmengine - INFO - Epoch(train) [12][ 40/2569] lr: 4.0000e-02 eta: 1 day, 2:27:54 time: 0.2775 data_time: 0.0068 memory: 5828 grad_norm: 2.8188 loss: 2.6109 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6109 2023/06/04 18:24:45 - mmengine - INFO - Epoch(train) [12][ 60/2569] lr: 4.0000e-02 eta: 1 day, 2:27:48 time: 0.2657 data_time: 0.0074 memory: 5828 grad_norm: 2.8309 loss: 2.7030 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7030 2023/06/04 18:24:50 - mmengine - INFO - Epoch(train) [12][ 80/2569] lr: 4.0000e-02 eta: 1 day, 2:27:43 time: 0.2674 data_time: 0.0079 memory: 5828 grad_norm: 2.8385 loss: 2.7932 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7932 2023/06/04 18:24:56 - mmengine - INFO - Epoch(train) [12][ 100/2569] lr: 4.0000e-02 eta: 1 day, 2:27:36 time: 0.2609 data_time: 0.0078 memory: 5828 grad_norm: 2.8660 loss: 2.4977 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4977 2023/06/04 18:25:01 - mmengine - INFO - Epoch(train) [12][ 120/2569] lr: 4.0000e-02 eta: 1 day, 2:27:30 time: 0.2634 data_time: 0.0077 memory: 5828 grad_norm: 2.8268 loss: 2.6694 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6694 2023/06/04 18:25:06 - mmengine - INFO - Epoch(train) [12][ 140/2569] lr: 4.0000e-02 eta: 1 day, 2:27:26 time: 0.2712 data_time: 0.0074 memory: 5828 grad_norm: 2.8604 loss: 2.7200 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7200 2023/06/04 18:25:12 - mmengine - INFO - Epoch(train) [12][ 160/2569] lr: 4.0000e-02 eta: 1 day, 2:27:20 time: 0.2667 data_time: 0.0075 memory: 5828 grad_norm: 2.8201 loss: 2.5570 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5570 2023/06/04 18:25:17 - mmengine - INFO - Epoch(train) [12][ 180/2569] lr: 4.0000e-02 eta: 1 day, 2:27:18 time: 0.2782 data_time: 0.0081 memory: 5828 grad_norm: 2.8591 loss: 2.4669 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4669 2023/06/04 18:25:23 - mmengine - INFO - Epoch(train) [12][ 200/2569] lr: 4.0000e-02 eta: 1 day, 2:27:12 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 2.8249 loss: 2.4923 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4923 2023/06/04 18:25:28 - mmengine - INFO - Epoch(train) [12][ 220/2569] lr: 4.0000e-02 eta: 1 day, 2:27:06 time: 0.2640 data_time: 0.0078 memory: 5828 grad_norm: 2.8786 loss: 2.6973 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6973 2023/06/04 18:25:33 - mmengine - INFO - Epoch(train) [12][ 240/2569] lr: 4.0000e-02 eta: 1 day, 2:27:01 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 2.8683 loss: 2.5089 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5089 2023/06/04 18:25:38 - mmengine - INFO - Epoch(train) [12][ 260/2569] lr: 4.0000e-02 eta: 1 day, 2:26:56 time: 0.2653 data_time: 0.0080 memory: 5828 grad_norm: 2.8948 loss: 2.7382 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7382 2023/06/04 18:25:44 - mmengine - INFO - Epoch(train) [12][ 280/2569] lr: 4.0000e-02 eta: 1 day, 2:26:50 time: 0.2658 data_time: 0.0079 memory: 5828 grad_norm: 2.7665 loss: 2.9102 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9102 2023/06/04 18:25:49 - mmengine - INFO - Epoch(train) [12][ 300/2569] lr: 4.0000e-02 eta: 1 day, 2:26:43 time: 0.2603 data_time: 0.0079 memory: 5828 grad_norm: 2.8564 loss: 2.9439 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9439 2023/06/04 18:25:54 - mmengine - INFO - Epoch(train) [12][ 320/2569] lr: 4.0000e-02 eta: 1 day, 2:26:36 time: 0.2617 data_time: 0.0080 memory: 5828 grad_norm: 2.8885 loss: 2.6433 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.6433 2023/06/04 18:26:00 - mmengine - INFO - Epoch(train) [12][ 340/2569] lr: 4.0000e-02 eta: 1 day, 2:26:31 time: 0.2654 data_time: 0.0077 memory: 5828 grad_norm: 2.8486 loss: 2.7834 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7834 2023/06/04 18:26:05 - mmengine - INFO - Epoch(train) [12][ 360/2569] lr: 4.0000e-02 eta: 1 day, 2:26:25 time: 0.2637 data_time: 0.0080 memory: 5828 grad_norm: 2.8740 loss: 2.9228 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9228 2023/06/04 18:26:10 - mmengine - INFO - Epoch(train) [12][ 380/2569] lr: 4.0000e-02 eta: 1 day, 2:26:22 time: 0.2758 data_time: 0.0074 memory: 5828 grad_norm: 2.8013 loss: 2.7903 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7903 2023/06/04 18:26:16 - mmengine - INFO - Epoch(train) [12][ 400/2569] lr: 4.0000e-02 eta: 1 day, 2:26:17 time: 0.2700 data_time: 0.0083 memory: 5828 grad_norm: 2.8194 loss: 2.5558 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5558 2023/06/04 18:26:21 - mmengine - INFO - Epoch(train) [12][ 420/2569] lr: 4.0000e-02 eta: 1 day, 2:26:11 time: 0.2636 data_time: 0.0080 memory: 5828 grad_norm: 2.8179 loss: 2.6685 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6685 2023/06/04 18:26:26 - mmengine - INFO - Epoch(train) [12][ 440/2569] lr: 4.0000e-02 eta: 1 day, 2:26:05 time: 0.2642 data_time: 0.0077 memory: 5828 grad_norm: 2.8339 loss: 2.5441 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5441 2023/06/04 18:26:32 - mmengine - INFO - Epoch(train) [12][ 460/2569] lr: 4.0000e-02 eta: 1 day, 2:26:01 time: 0.2713 data_time: 0.0076 memory: 5828 grad_norm: 2.8406 loss: 2.5126 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5126 2023/06/04 18:26:37 - mmengine - INFO - Epoch(train) [12][ 480/2569] lr: 4.0000e-02 eta: 1 day, 2:25:55 time: 0.2645 data_time: 0.0077 memory: 5828 grad_norm: 2.8971 loss: 2.5570 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5570 2023/06/04 18:26:43 - mmengine - INFO - Epoch(train) [12][ 500/2569] lr: 4.0000e-02 eta: 1 day, 2:25:52 time: 0.2775 data_time: 0.0075 memory: 5828 grad_norm: 2.8770 loss: 3.0693 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0693 2023/06/04 18:26:48 - mmengine - INFO - Epoch(train) [12][ 520/2569] lr: 4.0000e-02 eta: 1 day, 2:25:45 time: 0.2615 data_time: 0.0076 memory: 5828 grad_norm: 2.8643 loss: 2.5586 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5586 2023/06/04 18:26:53 - mmengine - INFO - Epoch(train) [12][ 540/2569] lr: 4.0000e-02 eta: 1 day, 2:25:41 time: 0.2703 data_time: 0.0077 memory: 5828 grad_norm: 2.9102 loss: 2.6057 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6057 2023/06/04 18:26:58 - mmengine - INFO - Epoch(train) [12][ 560/2569] lr: 4.0000e-02 eta: 1 day, 2:25:35 time: 0.2636 data_time: 0.0072 memory: 5828 grad_norm: 2.8621 loss: 2.4427 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4427 2023/06/04 18:27:04 - mmengine - INFO - Epoch(train) [12][ 580/2569] lr: 4.0000e-02 eta: 1 day, 2:25:28 time: 0.2612 data_time: 0.0075 memory: 5828 grad_norm: 2.8108 loss: 2.6820 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6820 2023/06/04 18:27:09 - mmengine - INFO - Epoch(train) [12][ 600/2569] lr: 4.0000e-02 eta: 1 day, 2:25:22 time: 0.2623 data_time: 0.0078 memory: 5828 grad_norm: 2.7925 loss: 2.7896 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7896 2023/06/04 18:27:14 - mmengine - INFO - Epoch(train) [12][ 620/2569] lr: 4.0000e-02 eta: 1 day, 2:25:15 time: 0.2612 data_time: 0.0077 memory: 5828 grad_norm: 2.8655 loss: 2.3937 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3937 2023/06/04 18:27:20 - mmengine - INFO - Epoch(train) [12][ 640/2569] lr: 4.0000e-02 eta: 1 day, 2:25:11 time: 0.2731 data_time: 0.0083 memory: 5828 grad_norm: 2.8844 loss: 2.9355 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9355 2023/06/04 18:27:25 - mmengine - INFO - Epoch(train) [12][ 660/2569] lr: 4.0000e-02 eta: 1 day, 2:25:07 time: 0.2716 data_time: 0.0076 memory: 5828 grad_norm: 2.9160 loss: 2.8085 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8085 2023/06/04 18:27:30 - mmengine - INFO - Epoch(train) [12][ 680/2569] lr: 4.0000e-02 eta: 1 day, 2:25:00 time: 0.2597 data_time: 0.0073 memory: 5828 grad_norm: 2.8056 loss: 2.5623 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5623 2023/06/04 18:27:36 - mmengine - INFO - Epoch(train) [12][ 700/2569] lr: 4.0000e-02 eta: 1 day, 2:24:54 time: 0.2652 data_time: 0.0076 memory: 5828 grad_norm: 2.8450 loss: 2.4569 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4569 2023/06/04 18:27:41 - mmengine - INFO - Epoch(train) [12][ 720/2569] lr: 4.0000e-02 eta: 1 day, 2:24:47 time: 0.2603 data_time: 0.0077 memory: 5828 grad_norm: 2.7834 loss: 2.6228 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6228 2023/06/04 18:27:46 - mmengine - INFO - Epoch(train) [12][ 740/2569] lr: 4.0000e-02 eta: 1 day, 2:24:43 time: 0.2724 data_time: 0.0073 memory: 5828 grad_norm: 2.8516 loss: 2.8162 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8162 2023/06/04 18:27:47 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:27:52 - mmengine - INFO - Epoch(train) [12][ 760/2569] lr: 4.0000e-02 eta: 1 day, 2:24:40 time: 0.2742 data_time: 0.0080 memory: 5828 grad_norm: 2.8714 loss: 2.8408 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8408 2023/06/04 18:27:57 - mmengine - INFO - Epoch(train) [12][ 780/2569] lr: 4.0000e-02 eta: 1 day, 2:24:34 time: 0.2638 data_time: 0.0078 memory: 5828 grad_norm: 2.8242 loss: 2.8432 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8432 2023/06/04 18:28:02 - mmengine - INFO - Epoch(train) [12][ 800/2569] lr: 4.0000e-02 eta: 1 day, 2:24:28 time: 0.2650 data_time: 0.0082 memory: 5828 grad_norm: 2.8584 loss: 2.4779 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4779 2023/06/04 18:28:08 - mmengine - INFO - Epoch(train) [12][ 820/2569] lr: 4.0000e-02 eta: 1 day, 2:24:22 time: 0.2667 data_time: 0.0076 memory: 5828 grad_norm: 2.8422 loss: 2.4278 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4278 2023/06/04 18:28:13 - mmengine - INFO - Epoch(train) [12][ 840/2569] lr: 4.0000e-02 eta: 1 day, 2:24:16 time: 0.2617 data_time: 0.0081 memory: 5828 grad_norm: 2.8998 loss: 2.6135 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6135 2023/06/04 18:28:18 - mmengine - INFO - Epoch(train) [12][ 860/2569] lr: 4.0000e-02 eta: 1 day, 2:24:12 time: 0.2732 data_time: 0.0084 memory: 5828 grad_norm: 2.8509 loss: 2.4196 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4196 2023/06/04 18:28:24 - mmengine - INFO - Epoch(train) [12][ 880/2569] lr: 4.0000e-02 eta: 1 day, 2:24:06 time: 0.2658 data_time: 0.0076 memory: 5828 grad_norm: 2.8419 loss: 2.9917 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.9917 2023/06/04 18:28:29 - mmengine - INFO - Epoch(train) [12][ 900/2569] lr: 4.0000e-02 eta: 1 day, 2:24:01 time: 0.2649 data_time: 0.0079 memory: 5828 grad_norm: 2.8325 loss: 2.6343 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6343 2023/06/04 18:28:34 - mmengine - INFO - Epoch(train) [12][ 920/2569] lr: 4.0000e-02 eta: 1 day, 2:23:56 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 2.8695 loss: 3.0076 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 3.0076 2023/06/04 18:28:40 - mmengine - INFO - Epoch(train) [12][ 940/2569] lr: 4.0000e-02 eta: 1 day, 2:23:50 time: 0.2671 data_time: 0.0077 memory: 5828 grad_norm: 2.8554 loss: 2.5363 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5363 2023/06/04 18:28:45 - mmengine - INFO - Epoch(train) [12][ 960/2569] lr: 4.0000e-02 eta: 1 day, 2:23:46 time: 0.2710 data_time: 0.0078 memory: 5828 grad_norm: 2.8326 loss: 2.7766 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7766 2023/06/04 18:28:50 - mmengine - INFO - Epoch(train) [12][ 980/2569] lr: 4.0000e-02 eta: 1 day, 2:23:39 time: 0.2587 data_time: 0.0080 memory: 5828 grad_norm: 2.8520 loss: 2.2038 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2038 2023/06/04 18:28:56 - mmengine - INFO - Epoch(train) [12][1000/2569] lr: 4.0000e-02 eta: 1 day, 2:23:33 time: 0.2651 data_time: 0.0082 memory: 5828 grad_norm: 2.8050 loss: 2.8059 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8059 2023/06/04 18:29:01 - mmengine - INFO - Epoch(train) [12][1020/2569] lr: 4.0000e-02 eta: 1 day, 2:23:29 time: 0.2705 data_time: 0.0078 memory: 5828 grad_norm: 2.8285 loss: 2.8345 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8345 2023/06/04 18:29:07 - mmengine - INFO - Epoch(train) [12][1040/2569] lr: 4.0000e-02 eta: 1 day, 2:23:26 time: 0.2775 data_time: 0.0076 memory: 5828 grad_norm: 2.8445 loss: 2.7955 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7955 2023/06/04 18:29:12 - mmengine - INFO - Epoch(train) [12][1060/2569] lr: 4.0000e-02 eta: 1 day, 2:23:19 time: 0.2600 data_time: 0.0076 memory: 5828 grad_norm: 2.8088 loss: 2.4981 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4981 2023/06/04 18:29:17 - mmengine - INFO - Epoch(train) [12][1080/2569] lr: 4.0000e-02 eta: 1 day, 2:23:13 time: 0.2665 data_time: 0.0080 memory: 5828 grad_norm: 2.8615 loss: 2.7250 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7250 2023/06/04 18:29:22 - mmengine - INFO - Epoch(train) [12][1100/2569] lr: 4.0000e-02 eta: 1 day, 2:23:08 time: 0.2683 data_time: 0.0078 memory: 5828 grad_norm: 2.8208 loss: 2.9927 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9927 2023/06/04 18:29:28 - mmengine - INFO - Epoch(train) [12][1120/2569] lr: 4.0000e-02 eta: 1 day, 2:23:04 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 2.8932 loss: 2.9255 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9255 2023/06/04 18:29:33 - mmengine - INFO - Epoch(train) [12][1140/2569] lr: 4.0000e-02 eta: 1 day, 2:22:59 time: 0.2695 data_time: 0.0079 memory: 5828 grad_norm: 2.8401 loss: 2.6707 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6707 2023/06/04 18:29:38 - mmengine - INFO - Epoch(train) [12][1160/2569] lr: 4.0000e-02 eta: 1 day, 2:22:52 time: 0.2612 data_time: 0.0078 memory: 5828 grad_norm: 2.8825 loss: 2.7292 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7292 2023/06/04 18:29:44 - mmengine - INFO - Epoch(train) [12][1180/2569] lr: 4.0000e-02 eta: 1 day, 2:22:50 time: 0.2792 data_time: 0.0077 memory: 5828 grad_norm: 2.7917 loss: 3.0765 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0765 2023/06/04 18:29:49 - mmengine - INFO - Epoch(train) [12][1200/2569] lr: 4.0000e-02 eta: 1 day, 2:22:44 time: 0.2654 data_time: 0.0073 memory: 5828 grad_norm: 2.8080 loss: 2.6428 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6428 2023/06/04 18:29:55 - mmengine - INFO - Epoch(train) [12][1220/2569] lr: 4.0000e-02 eta: 1 day, 2:22:38 time: 0.2653 data_time: 0.0080 memory: 5828 grad_norm: 2.7495 loss: 2.5379 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5379 2023/06/04 18:30:00 - mmengine - INFO - Epoch(train) [12][1240/2569] lr: 4.0000e-02 eta: 1 day, 2:22:34 time: 0.2710 data_time: 0.0077 memory: 5828 grad_norm: 2.8508 loss: 2.5245 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5245 2023/06/04 18:30:05 - mmengine - INFO - Epoch(train) [12][1260/2569] lr: 4.0000e-02 eta: 1 day, 2:22:30 time: 0.2724 data_time: 0.0077 memory: 5828 grad_norm: 2.8721 loss: 2.4545 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4545 2023/06/04 18:30:11 - mmengine - INFO - Epoch(train) [12][1280/2569] lr: 4.0000e-02 eta: 1 day, 2:22:24 time: 0.2633 data_time: 0.0079 memory: 5828 grad_norm: 2.8069 loss: 2.1439 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1439 2023/06/04 18:30:16 - mmengine - INFO - Epoch(train) [12][1300/2569] lr: 4.0000e-02 eta: 1 day, 2:22:17 time: 0.2609 data_time: 0.0078 memory: 5828 grad_norm: 2.8762 loss: 2.6498 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6498 2023/06/04 18:30:21 - mmengine - INFO - Epoch(train) [12][1320/2569] lr: 4.0000e-02 eta: 1 day, 2:22:12 time: 0.2667 data_time: 0.0076 memory: 5828 grad_norm: 2.8243 loss: 2.3182 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3182 2023/06/04 18:30:27 - mmengine - INFO - Epoch(train) [12][1340/2569] lr: 4.0000e-02 eta: 1 day, 2:22:05 time: 0.2608 data_time: 0.0080 memory: 5828 grad_norm: 2.8440 loss: 2.5981 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5981 2023/06/04 18:30:32 - mmengine - INFO - Epoch(train) [12][1360/2569] lr: 4.0000e-02 eta: 1 day, 2:21:58 time: 0.2610 data_time: 0.0079 memory: 5828 grad_norm: 2.8502 loss: 2.8351 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8351 2023/06/04 18:30:37 - mmengine - INFO - Epoch(train) [12][1380/2569] lr: 4.0000e-02 eta: 1 day, 2:21:51 time: 0.2604 data_time: 0.0076 memory: 5828 grad_norm: 2.8020 loss: 3.0537 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 3.0537 2023/06/04 18:30:42 - mmengine - INFO - Epoch(train) [12][1400/2569] lr: 4.0000e-02 eta: 1 day, 2:21:45 time: 0.2609 data_time: 0.0076 memory: 5828 grad_norm: 2.8234 loss: 2.5166 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5166 2023/06/04 18:30:47 - mmengine - INFO - Epoch(train) [12][1420/2569] lr: 4.0000e-02 eta: 1 day, 2:21:38 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 2.7853 loss: 2.4759 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4759 2023/06/04 18:30:53 - mmengine - INFO - Epoch(train) [12][1440/2569] lr: 4.0000e-02 eta: 1 day, 2:21:33 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 2.7589 loss: 2.6391 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6391 2023/06/04 18:30:58 - mmengine - INFO - Epoch(train) [12][1460/2569] lr: 4.0000e-02 eta: 1 day, 2:21:26 time: 0.2626 data_time: 0.0078 memory: 5828 grad_norm: 2.8721 loss: 2.6785 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6785 2023/06/04 18:31:03 - mmengine - INFO - Epoch(train) [12][1480/2569] lr: 4.0000e-02 eta: 1 day, 2:21:23 time: 0.2748 data_time: 0.0076 memory: 5828 grad_norm: 2.8830 loss: 2.8081 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8081 2023/06/04 18:31:09 - mmengine - INFO - Epoch(train) [12][1500/2569] lr: 4.0000e-02 eta: 1 day, 2:21:20 time: 0.2760 data_time: 0.0085 memory: 5828 grad_norm: 2.8560 loss: 2.9332 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9332 2023/06/04 18:31:14 - mmengine - INFO - Epoch(train) [12][1520/2569] lr: 4.0000e-02 eta: 1 day, 2:21:14 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 2.8674 loss: 2.4375 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4375 2023/06/04 18:31:20 - mmengine - INFO - Epoch(train) [12][1540/2569] lr: 4.0000e-02 eta: 1 day, 2:21:07 time: 0.2638 data_time: 0.0082 memory: 5828 grad_norm: 2.8488 loss: 2.7606 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7606 2023/06/04 18:31:25 - mmengine - INFO - Epoch(train) [12][1560/2569] lr: 4.0000e-02 eta: 1 day, 2:21:04 time: 0.2728 data_time: 0.0078 memory: 5828 grad_norm: 2.8410 loss: 2.6151 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6151 2023/06/04 18:31:30 - mmengine - INFO - Epoch(train) [12][1580/2569] lr: 4.0000e-02 eta: 1 day, 2:20:58 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 2.8265 loss: 2.7707 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7707 2023/06/04 18:31:36 - mmengine - INFO - Epoch(train) [12][1600/2569] lr: 4.0000e-02 eta: 1 day, 2:20:53 time: 0.2711 data_time: 0.0077 memory: 5828 grad_norm: 2.8325 loss: 2.6331 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6331 2023/06/04 18:31:41 - mmengine - INFO - Epoch(train) [12][1620/2569] lr: 4.0000e-02 eta: 1 day, 2:20:48 time: 0.2684 data_time: 0.0070 memory: 5828 grad_norm: 2.8389 loss: 2.5783 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5783 2023/06/04 18:31:46 - mmengine - INFO - Epoch(train) [12][1640/2569] lr: 4.0000e-02 eta: 1 day, 2:20:41 time: 0.2604 data_time: 0.0081 memory: 5828 grad_norm: 2.9002 loss: 2.7590 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7590 2023/06/04 18:31:52 - mmengine - INFO - Epoch(train) [12][1660/2569] lr: 4.0000e-02 eta: 1 day, 2:20:39 time: 0.2769 data_time: 0.0079 memory: 5828 grad_norm: 2.8060 loss: 2.4940 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4940 2023/06/04 18:31:57 - mmengine - INFO - Epoch(train) [12][1680/2569] lr: 4.0000e-02 eta: 1 day, 2:20:34 time: 0.2697 data_time: 0.0076 memory: 5828 grad_norm: 2.8585 loss: 2.8306 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8306 2023/06/04 18:32:03 - mmengine - INFO - Epoch(train) [12][1700/2569] lr: 4.0000e-02 eta: 1 day, 2:20:28 time: 0.2649 data_time: 0.0077 memory: 5828 grad_norm: 2.8562 loss: 2.5311 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5311 2023/06/04 18:32:08 - mmengine - INFO - Epoch(train) [12][1720/2569] lr: 4.0000e-02 eta: 1 day, 2:20:21 time: 0.2598 data_time: 0.0076 memory: 5828 grad_norm: 2.8072 loss: 2.8383 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8383 2023/06/04 18:32:13 - mmengine - INFO - Epoch(train) [12][1740/2569] lr: 4.0000e-02 eta: 1 day, 2:20:14 time: 0.2613 data_time: 0.0077 memory: 5828 grad_norm: 2.8611 loss: 2.5796 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5796 2023/06/04 18:32:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:32:18 - mmengine - INFO - Epoch(train) [12][1760/2569] lr: 4.0000e-02 eta: 1 day, 2:20:08 time: 0.2602 data_time: 0.0079 memory: 5828 grad_norm: 2.8245 loss: 2.8096 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8096 2023/06/04 18:32:24 - mmengine - INFO - Epoch(train) [12][1780/2569] lr: 4.0000e-02 eta: 1 day, 2:20:03 time: 0.2686 data_time: 0.0079 memory: 5828 grad_norm: 2.8232 loss: 2.5061 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5061 2023/06/04 18:32:29 - mmengine - INFO - Epoch(train) [12][1800/2569] lr: 4.0000e-02 eta: 1 day, 2:19:56 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 2.7872 loss: 2.5648 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5648 2023/06/04 18:32:34 - mmengine - INFO - Epoch(train) [12][1820/2569] lr: 4.0000e-02 eta: 1 day, 2:19:50 time: 0.2631 data_time: 0.0076 memory: 5828 grad_norm: 2.7740 loss: 2.2852 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2852 2023/06/04 18:32:39 - mmengine - INFO - Epoch(train) [12][1840/2569] lr: 4.0000e-02 eta: 1 day, 2:19:44 time: 0.2620 data_time: 0.0078 memory: 5828 grad_norm: 2.8103 loss: 2.7036 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7036 2023/06/04 18:32:45 - mmengine - INFO - Epoch(train) [12][1860/2569] lr: 4.0000e-02 eta: 1 day, 2:19:38 time: 0.2665 data_time: 0.0077 memory: 5828 grad_norm: 2.8216 loss: 2.4137 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4137 2023/06/04 18:32:50 - mmengine - INFO - Epoch(train) [12][1880/2569] lr: 4.0000e-02 eta: 1 day, 2:19:33 time: 0.2687 data_time: 0.0085 memory: 5828 grad_norm: 2.7840 loss: 2.6578 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6578 2023/06/04 18:32:55 - mmengine - INFO - Epoch(train) [12][1900/2569] lr: 4.0000e-02 eta: 1 day, 2:19:26 time: 0.2598 data_time: 0.0073 memory: 5828 grad_norm: 2.8572 loss: 2.5965 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5965 2023/06/04 18:33:00 - mmengine - INFO - Epoch(train) [12][1920/2569] lr: 4.0000e-02 eta: 1 day, 2:19:19 time: 0.2603 data_time: 0.0079 memory: 5828 grad_norm: 2.8725 loss: 2.6196 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6196 2023/06/04 18:33:06 - mmengine - INFO - Epoch(train) [12][1940/2569] lr: 4.0000e-02 eta: 1 day, 2:19:13 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 2.8138 loss: 2.6283 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6283 2023/06/04 18:33:11 - mmengine - INFO - Epoch(train) [12][1960/2569] lr: 4.0000e-02 eta: 1 day, 2:19:06 time: 0.2597 data_time: 0.0079 memory: 5828 grad_norm: 2.8853 loss: 2.6751 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6751 2023/06/04 18:33:16 - mmengine - INFO - Epoch(train) [12][1980/2569] lr: 4.0000e-02 eta: 1 day, 2:19:00 time: 0.2649 data_time: 0.0077 memory: 5828 grad_norm: 2.8345 loss: 3.0896 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0896 2023/06/04 18:33:21 - mmengine - INFO - Epoch(train) [12][2000/2569] lr: 4.0000e-02 eta: 1 day, 2:18:54 time: 0.2637 data_time: 0.0077 memory: 5828 grad_norm: 2.8254 loss: 2.4421 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4421 2023/06/04 18:33:27 - mmengine - INFO - Epoch(train) [12][2020/2569] lr: 4.0000e-02 eta: 1 day, 2:18:48 time: 0.2642 data_time: 0.0083 memory: 5828 grad_norm: 2.8550 loss: 2.6124 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6124 2023/06/04 18:33:32 - mmengine - INFO - Epoch(train) [12][2040/2569] lr: 4.0000e-02 eta: 1 day, 2:18:43 time: 0.2688 data_time: 0.0077 memory: 5828 grad_norm: 2.8684 loss: 2.4080 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4080 2023/06/04 18:33:38 - mmengine - INFO - Epoch(train) [12][2060/2569] lr: 4.0000e-02 eta: 1 day, 2:18:41 time: 0.2792 data_time: 0.0080 memory: 5828 grad_norm: 2.8360 loss: 2.8047 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8047 2023/06/04 18:33:43 - mmengine - INFO - Epoch(train) [12][2080/2569] lr: 4.0000e-02 eta: 1 day, 2:18:35 time: 0.2665 data_time: 0.0080 memory: 5828 grad_norm: 2.8601 loss: 2.6111 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6111 2023/06/04 18:33:48 - mmengine - INFO - Epoch(train) [12][2100/2569] lr: 4.0000e-02 eta: 1 day, 2:18:31 time: 0.2688 data_time: 0.0075 memory: 5828 grad_norm: 2.8222 loss: 2.8429 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8429 2023/06/04 18:33:54 - mmengine - INFO - Epoch(train) [12][2120/2569] lr: 4.0000e-02 eta: 1 day, 2:18:27 time: 0.2725 data_time: 0.0077 memory: 5828 grad_norm: 2.7808 loss: 2.3241 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3241 2023/06/04 18:33:59 - mmengine - INFO - Epoch(train) [12][2140/2569] lr: 4.0000e-02 eta: 1 day, 2:18:24 time: 0.2783 data_time: 0.0072 memory: 5828 grad_norm: 2.8109 loss: 2.5728 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5728 2023/06/04 18:34:05 - mmengine - INFO - Epoch(train) [12][2160/2569] lr: 4.0000e-02 eta: 1 day, 2:18:20 time: 0.2717 data_time: 0.0090 memory: 5828 grad_norm: 2.7561 loss: 2.6566 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6566 2023/06/04 18:34:10 - mmengine - INFO - Epoch(train) [12][2180/2569] lr: 4.0000e-02 eta: 1 day, 2:18:13 time: 0.2605 data_time: 0.0078 memory: 5828 grad_norm: 2.8330 loss: 2.4377 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4377 2023/06/04 18:34:16 - mmengine - INFO - Epoch(train) [12][2200/2569] lr: 4.0000e-02 eta: 1 day, 2:18:10 time: 0.2767 data_time: 0.0075 memory: 5828 grad_norm: 2.8166 loss: 2.5491 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5491 2023/06/04 18:34:21 - mmengine - INFO - Epoch(train) [12][2220/2569] lr: 4.0000e-02 eta: 1 day, 2:18:03 time: 0.2603 data_time: 0.0080 memory: 5828 grad_norm: 2.8755 loss: 2.6940 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6940 2023/06/04 18:34:26 - mmengine - INFO - Epoch(train) [12][2240/2569] lr: 4.0000e-02 eta: 1 day, 2:17:59 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 2.8649 loss: 2.4975 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4975 2023/06/04 18:34:31 - mmengine - INFO - Epoch(train) [12][2260/2569] lr: 4.0000e-02 eta: 1 day, 2:17:53 time: 0.2647 data_time: 0.0080 memory: 5828 grad_norm: 2.8185 loss: 2.6356 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6356 2023/06/04 18:34:37 - mmengine - INFO - Epoch(train) [12][2280/2569] lr: 4.0000e-02 eta: 1 day, 2:17:47 time: 0.2639 data_time: 0.0083 memory: 5828 grad_norm: 2.7954 loss: 2.7183 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7183 2023/06/04 18:34:42 - mmengine - INFO - Epoch(train) [12][2300/2569] lr: 4.0000e-02 eta: 1 day, 2:17:42 time: 0.2712 data_time: 0.0073 memory: 5828 grad_norm: 2.8146 loss: 2.5765 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5765 2023/06/04 18:34:48 - mmengine - INFO - Epoch(train) [12][2320/2569] lr: 4.0000e-02 eta: 1 day, 2:17:37 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 2.7550 loss: 2.8121 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8121 2023/06/04 18:34:53 - mmengine - INFO - Epoch(train) [12][2340/2569] lr: 4.0000e-02 eta: 1 day, 2:17:37 time: 0.2914 data_time: 0.0075 memory: 5828 grad_norm: 2.8315 loss: 2.5533 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5533 2023/06/04 18:34:59 - mmengine - INFO - Epoch(train) [12][2360/2569] lr: 4.0000e-02 eta: 1 day, 2:17:32 time: 0.2675 data_time: 0.0080 memory: 5828 grad_norm: 2.8343 loss: 2.6394 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6394 2023/06/04 18:35:04 - mmengine - INFO - Epoch(train) [12][2380/2569] lr: 4.0000e-02 eta: 1 day, 2:17:28 time: 0.2744 data_time: 0.0073 memory: 5828 grad_norm: 2.8126 loss: 2.6448 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6448 2023/06/04 18:35:10 - mmengine - INFO - Epoch(train) [12][2400/2569] lr: 4.0000e-02 eta: 1 day, 2:17:25 time: 0.2743 data_time: 0.0077 memory: 5828 grad_norm: 2.8200 loss: 2.6487 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6487 2023/06/04 18:35:15 - mmengine - INFO - Epoch(train) [12][2420/2569] lr: 4.0000e-02 eta: 1 day, 2:17:21 time: 0.2728 data_time: 0.0075 memory: 5828 grad_norm: 2.8874 loss: 2.5601 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5601 2023/06/04 18:35:21 - mmengine - INFO - Epoch(train) [12][2440/2569] lr: 4.0000e-02 eta: 1 day, 2:17:18 time: 0.2769 data_time: 0.0075 memory: 5828 grad_norm: 2.8484 loss: 2.8292 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8292 2023/06/04 18:35:26 - mmengine - INFO - Epoch(train) [12][2460/2569] lr: 4.0000e-02 eta: 1 day, 2:17:12 time: 0.2642 data_time: 0.0077 memory: 5828 grad_norm: 2.8173 loss: 2.8466 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8466 2023/06/04 18:35:31 - mmengine - INFO - Epoch(train) [12][2480/2569] lr: 4.0000e-02 eta: 1 day, 2:17:05 time: 0.2603 data_time: 0.0076 memory: 5828 grad_norm: 2.8044 loss: 2.2991 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2991 2023/06/04 18:35:37 - mmengine - INFO - Epoch(train) [12][2500/2569] lr: 4.0000e-02 eta: 1 day, 2:17:02 time: 0.2775 data_time: 0.0071 memory: 5828 grad_norm: 2.7764 loss: 2.3029 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3029 2023/06/04 18:35:42 - mmengine - INFO - Epoch(train) [12][2520/2569] lr: 4.0000e-02 eta: 1 day, 2:16:55 time: 0.2599 data_time: 0.0081 memory: 5828 grad_norm: 2.8908 loss: 2.3544 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3544 2023/06/04 18:35:47 - mmengine - INFO - Epoch(train) [12][2540/2569] lr: 4.0000e-02 eta: 1 day, 2:16:52 time: 0.2758 data_time: 0.0090 memory: 5828 grad_norm: 2.8211 loss: 2.6449 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6449 2023/06/04 18:35:53 - mmengine - INFO - Epoch(train) [12][2560/2569] lr: 4.0000e-02 eta: 1 day, 2:16:47 time: 0.2667 data_time: 0.0081 memory: 5828 grad_norm: 2.7612 loss: 2.4599 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4599 2023/06/04 18:35:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:35:55 - mmengine - INFO - Epoch(train) [12][2569/2569] lr: 4.0000e-02 eta: 1 day, 2:16:42 time: 0.2529 data_time: 0.0078 memory: 5828 grad_norm: 2.8176 loss: 2.5255 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.5255 2023/06/04 18:35:55 - mmengine - INFO - Saving checkpoint at 12 epochs 2023/06/04 18:36:03 - mmengine - INFO - Epoch(train) [13][ 20/2569] lr: 4.0000e-02 eta: 1 day, 2:16:46 time: 0.3071 data_time: 0.0487 memory: 5828 grad_norm: 2.7482 loss: 2.8413 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8413 2023/06/04 18:36:09 - mmengine - INFO - Epoch(train) [13][ 40/2569] lr: 4.0000e-02 eta: 1 day, 2:16:42 time: 0.2740 data_time: 0.0079 memory: 5828 grad_norm: 2.8598 loss: 2.7865 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7865 2023/06/04 18:36:14 - mmengine - INFO - Epoch(train) [13][ 60/2569] lr: 4.0000e-02 eta: 1 day, 2:16:36 time: 0.2637 data_time: 0.0078 memory: 5828 grad_norm: 2.7420 loss: 2.7693 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7693 2023/06/04 18:36:20 - mmengine - INFO - Epoch(train) [13][ 80/2569] lr: 4.0000e-02 eta: 1 day, 2:16:32 time: 0.2741 data_time: 0.0075 memory: 5828 grad_norm: 2.8301 loss: 2.7024 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7024 2023/06/04 18:36:25 - mmengine - INFO - Epoch(train) [13][ 100/2569] lr: 4.0000e-02 eta: 1 day, 2:16:28 time: 0.2712 data_time: 0.0071 memory: 5828 grad_norm: 2.8531 loss: 2.6727 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6727 2023/06/04 18:36:30 - mmengine - INFO - Epoch(train) [13][ 120/2569] lr: 4.0000e-02 eta: 1 day, 2:16:24 time: 0.2725 data_time: 0.0081 memory: 5828 grad_norm: 2.8151 loss: 2.9489 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9489 2023/06/04 18:36:36 - mmengine - INFO - Epoch(train) [13][ 140/2569] lr: 4.0000e-02 eta: 1 day, 2:16:18 time: 0.2641 data_time: 0.0079 memory: 5828 grad_norm: 2.8373 loss: 2.9784 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9784 2023/06/04 18:36:41 - mmengine - INFO - Epoch(train) [13][ 160/2569] lr: 4.0000e-02 eta: 1 day, 2:16:12 time: 0.2659 data_time: 0.0076 memory: 5828 grad_norm: 2.8447 loss: 2.4263 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4263 2023/06/04 18:36:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:36:47 - mmengine - INFO - Epoch(train) [13][ 180/2569] lr: 4.0000e-02 eta: 1 day, 2:16:08 time: 0.2724 data_time: 0.0081 memory: 5828 grad_norm: 2.8658 loss: 2.4084 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4084 2023/06/04 18:36:52 - mmengine - INFO - Epoch(train) [13][ 200/2569] lr: 4.0000e-02 eta: 1 day, 2:16:04 time: 0.2726 data_time: 0.0079 memory: 5828 grad_norm: 2.7570 loss: 2.6920 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6920 2023/06/04 18:36:57 - mmengine - INFO - Epoch(train) [13][ 220/2569] lr: 4.0000e-02 eta: 1 day, 2:16:00 time: 0.2721 data_time: 0.0077 memory: 5828 grad_norm: 2.8134 loss: 2.2910 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2910 2023/06/04 18:37:03 - mmengine - INFO - Epoch(train) [13][ 240/2569] lr: 4.0000e-02 eta: 1 day, 2:15:53 time: 0.2591 data_time: 0.0076 memory: 5828 grad_norm: 2.8030 loss: 3.1752 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.1752 2023/06/04 18:37:08 - mmengine - INFO - Epoch(train) [13][ 260/2569] lr: 4.0000e-02 eta: 1 day, 2:15:48 time: 0.2703 data_time: 0.0079 memory: 5828 grad_norm: 2.8104 loss: 2.6524 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6524 2023/06/04 18:37:13 - mmengine - INFO - Epoch(train) [13][ 280/2569] lr: 4.0000e-02 eta: 1 day, 2:15:41 time: 0.2588 data_time: 0.0072 memory: 5828 grad_norm: 2.8508 loss: 2.6582 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6582 2023/06/04 18:37:18 - mmengine - INFO - Epoch(train) [13][ 300/2569] lr: 4.0000e-02 eta: 1 day, 2:15:34 time: 0.2598 data_time: 0.0076 memory: 5828 grad_norm: 2.8100 loss: 2.5548 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5548 2023/06/04 18:37:24 - mmengine - INFO - Epoch(train) [13][ 320/2569] lr: 4.0000e-02 eta: 1 day, 2:15:30 time: 0.2720 data_time: 0.0077 memory: 5828 grad_norm: 2.8043 loss: 2.2540 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2540 2023/06/04 18:37:29 - mmengine - INFO - Epoch(train) [13][ 340/2569] lr: 4.0000e-02 eta: 1 day, 2:15:25 time: 0.2662 data_time: 0.0082 memory: 5828 grad_norm: 2.8384 loss: 2.4235 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4235 2023/06/04 18:37:34 - mmengine - INFO - Epoch(train) [13][ 360/2569] lr: 4.0000e-02 eta: 1 day, 2:15:18 time: 0.2626 data_time: 0.0078 memory: 5828 grad_norm: 2.8247 loss: 2.6632 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6632 2023/06/04 18:37:40 - mmengine - INFO - Epoch(train) [13][ 380/2569] lr: 4.0000e-02 eta: 1 day, 2:15:12 time: 0.2618 data_time: 0.0078 memory: 5828 grad_norm: 2.8423 loss: 3.0002 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.0002 2023/06/04 18:37:45 - mmengine - INFO - Epoch(train) [13][ 400/2569] lr: 4.0000e-02 eta: 1 day, 2:15:06 time: 0.2668 data_time: 0.0075 memory: 5828 grad_norm: 2.8373 loss: 2.7892 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7892 2023/06/04 18:37:50 - mmengine - INFO - Epoch(train) [13][ 420/2569] lr: 4.0000e-02 eta: 1 day, 2:15:02 time: 0.2689 data_time: 0.0077 memory: 5828 grad_norm: 2.7722 loss: 2.8200 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8200 2023/06/04 18:37:56 - mmengine - INFO - Epoch(train) [13][ 440/2569] lr: 4.0000e-02 eta: 1 day, 2:14:56 time: 0.2647 data_time: 0.0076 memory: 5828 grad_norm: 2.8342 loss: 2.4052 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4052 2023/06/04 18:38:01 - mmengine - INFO - Epoch(train) [13][ 460/2569] lr: 4.0000e-02 eta: 1 day, 2:14:52 time: 0.2743 data_time: 0.0080 memory: 5828 grad_norm: 2.8243 loss: 2.4589 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4589 2023/06/04 18:38:07 - mmengine - INFO - Epoch(train) [13][ 480/2569] lr: 4.0000e-02 eta: 1 day, 2:14:47 time: 0.2692 data_time: 0.0075 memory: 5828 grad_norm: 2.8111 loss: 2.2780 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2780 2023/06/04 18:38:12 - mmengine - INFO - Epoch(train) [13][ 500/2569] lr: 4.0000e-02 eta: 1 day, 2:14:40 time: 0.2594 data_time: 0.0080 memory: 5828 grad_norm: 2.8006 loss: 2.7385 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7385 2023/06/04 18:38:17 - mmengine - INFO - Epoch(train) [13][ 520/2569] lr: 4.0000e-02 eta: 1 day, 2:14:34 time: 0.2616 data_time: 0.0081 memory: 5828 grad_norm: 2.7781 loss: 2.5192 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5192 2023/06/04 18:38:22 - mmengine - INFO - Epoch(train) [13][ 540/2569] lr: 4.0000e-02 eta: 1 day, 2:14:29 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 2.8048 loss: 2.5231 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5231 2023/06/04 18:38:28 - mmengine - INFO - Epoch(train) [13][ 560/2569] lr: 4.0000e-02 eta: 1 day, 2:14:24 time: 0.2675 data_time: 0.0082 memory: 5828 grad_norm: 2.8686 loss: 2.6511 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6511 2023/06/04 18:38:33 - mmengine - INFO - Epoch(train) [13][ 580/2569] lr: 4.0000e-02 eta: 1 day, 2:14:17 time: 0.2602 data_time: 0.0079 memory: 5828 grad_norm: 2.8386 loss: 2.9320 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9320 2023/06/04 18:38:38 - mmengine - INFO - Epoch(train) [13][ 600/2569] lr: 4.0000e-02 eta: 1 day, 2:14:10 time: 0.2598 data_time: 0.0073 memory: 5828 grad_norm: 2.8238 loss: 2.6621 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6621 2023/06/04 18:38:43 - mmengine - INFO - Epoch(train) [13][ 620/2569] lr: 4.0000e-02 eta: 1 day, 2:14:04 time: 0.2641 data_time: 0.0077 memory: 5828 grad_norm: 2.7997 loss: 2.5358 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5358 2023/06/04 18:38:49 - mmengine - INFO - Epoch(train) [13][ 640/2569] lr: 4.0000e-02 eta: 1 day, 2:14:00 time: 0.2707 data_time: 0.0076 memory: 5828 grad_norm: 2.8222 loss: 2.6842 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6842 2023/06/04 18:38:54 - mmengine - INFO - Epoch(train) [13][ 660/2569] lr: 4.0000e-02 eta: 1 day, 2:13:54 time: 0.2650 data_time: 0.0090 memory: 5828 grad_norm: 2.8757 loss: 2.5529 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5529 2023/06/04 18:38:59 - mmengine - INFO - Epoch(train) [13][ 680/2569] lr: 4.0000e-02 eta: 1 day, 2:13:49 time: 0.2662 data_time: 0.0073 memory: 5828 grad_norm: 2.8227 loss: 2.3779 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3779 2023/06/04 18:39:05 - mmengine - INFO - Epoch(train) [13][ 700/2569] lr: 4.0000e-02 eta: 1 day, 2:13:44 time: 0.2707 data_time: 0.0077 memory: 5828 grad_norm: 2.9019 loss: 2.6944 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6944 2023/06/04 18:39:10 - mmengine - INFO - Epoch(train) [13][ 720/2569] lr: 4.0000e-02 eta: 1 day, 2:13:37 time: 0.2601 data_time: 0.0079 memory: 5828 grad_norm: 2.8496 loss: 2.9922 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9922 2023/06/04 18:39:16 - mmengine - INFO - Epoch(train) [13][ 740/2569] lr: 4.0000e-02 eta: 1 day, 2:13:35 time: 0.2819 data_time: 0.0071 memory: 5828 grad_norm: 2.8210 loss: 2.8361 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8361 2023/06/04 18:39:21 - mmengine - INFO - Epoch(train) [13][ 760/2569] lr: 4.0000e-02 eta: 1 day, 2:13:29 time: 0.2609 data_time: 0.0078 memory: 5828 grad_norm: 2.8563 loss: 2.8604 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8604 2023/06/04 18:39:26 - mmengine - INFO - Epoch(train) [13][ 780/2569] lr: 4.0000e-02 eta: 1 day, 2:13:25 time: 0.2755 data_time: 0.0075 memory: 5828 grad_norm: 2.8601 loss: 2.7780 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7780 2023/06/04 18:39:32 - mmengine - INFO - Epoch(train) [13][ 800/2569] lr: 4.0000e-02 eta: 1 day, 2:13:19 time: 0.2620 data_time: 0.0078 memory: 5828 grad_norm: 2.8079 loss: 2.5690 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5690 2023/06/04 18:39:37 - mmengine - INFO - Epoch(train) [13][ 820/2569] lr: 4.0000e-02 eta: 1 day, 2:13:14 time: 0.2671 data_time: 0.0079 memory: 5828 grad_norm: 2.8522 loss: 2.6694 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6694 2023/06/04 18:39:42 - mmengine - INFO - Epoch(train) [13][ 840/2569] lr: 4.0000e-02 eta: 1 day, 2:13:07 time: 0.2607 data_time: 0.0079 memory: 5828 grad_norm: 2.7808 loss: 2.2882 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.2882 2023/06/04 18:39:48 - mmengine - INFO - Epoch(train) [13][ 860/2569] lr: 4.0000e-02 eta: 1 day, 2:13:01 time: 0.2630 data_time: 0.0072 memory: 5828 grad_norm: 2.7949 loss: 2.4809 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4809 2023/06/04 18:39:53 - mmengine - INFO - Epoch(train) [13][ 880/2569] lr: 4.0000e-02 eta: 1 day, 2:12:55 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 2.8885 loss: 3.0799 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.0799 2023/06/04 18:39:58 - mmengine - INFO - Epoch(train) [13][ 900/2569] lr: 4.0000e-02 eta: 1 day, 2:12:49 time: 0.2620 data_time: 0.0084 memory: 5828 grad_norm: 2.8439 loss: 2.9430 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.9430 2023/06/04 18:40:03 - mmengine - INFO - Epoch(train) [13][ 920/2569] lr: 4.0000e-02 eta: 1 day, 2:12:42 time: 0.2603 data_time: 0.0077 memory: 5828 grad_norm: 2.8533 loss: 2.7372 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7372 2023/06/04 18:40:09 - mmengine - INFO - Epoch(train) [13][ 940/2569] lr: 4.0000e-02 eta: 1 day, 2:12:36 time: 0.2668 data_time: 0.0077 memory: 5828 grad_norm: 2.8644 loss: 2.9254 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9254 2023/06/04 18:40:14 - mmengine - INFO - Epoch(train) [13][ 960/2569] lr: 4.0000e-02 eta: 1 day, 2:12:30 time: 0.2615 data_time: 0.0077 memory: 5828 grad_norm: 2.7995 loss: 2.7791 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7791 2023/06/04 18:40:19 - mmengine - INFO - Epoch(train) [13][ 980/2569] lr: 4.0000e-02 eta: 1 day, 2:12:26 time: 0.2736 data_time: 0.0073 memory: 5828 grad_norm: 2.8268 loss: 2.7613 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7613 2023/06/04 18:40:25 - mmengine - INFO - Epoch(train) [13][1000/2569] lr: 4.0000e-02 eta: 1 day, 2:12:22 time: 0.2718 data_time: 0.0078 memory: 5828 grad_norm: 2.8351 loss: 2.5433 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5433 2023/06/04 18:40:30 - mmengine - INFO - Epoch(train) [13][1020/2569] lr: 4.0000e-02 eta: 1 day, 2:12:15 time: 0.2594 data_time: 0.0075 memory: 5828 grad_norm: 2.8361 loss: 2.3081 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3081 2023/06/04 18:40:35 - mmengine - INFO - Epoch(train) [13][1040/2569] lr: 4.0000e-02 eta: 1 day, 2:12:09 time: 0.2642 data_time: 0.0075 memory: 5828 grad_norm: 2.8995 loss: 2.4300 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4300 2023/06/04 18:40:41 - mmengine - INFO - Epoch(train) [13][1060/2569] lr: 4.0000e-02 eta: 1 day, 2:12:03 time: 0.2644 data_time: 0.0077 memory: 5828 grad_norm: 2.8221 loss: 2.8123 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8123 2023/06/04 18:40:46 - mmengine - INFO - Epoch(train) [13][1080/2569] lr: 4.0000e-02 eta: 1 day, 2:11:57 time: 0.2632 data_time: 0.0080 memory: 5828 grad_norm: 2.7998 loss: 2.7350 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7350 2023/06/04 18:40:51 - mmengine - INFO - Epoch(train) [13][1100/2569] lr: 4.0000e-02 eta: 1 day, 2:11:53 time: 0.2723 data_time: 0.0077 memory: 5828 grad_norm: 2.8384 loss: 3.0921 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0921 2023/06/04 18:40:56 - mmengine - INFO - Epoch(train) [13][1120/2569] lr: 4.0000e-02 eta: 1 day, 2:11:46 time: 0.2610 data_time: 0.0077 memory: 5828 grad_norm: 2.8187 loss: 2.3122 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3122 2023/06/04 18:41:02 - mmengine - INFO - Epoch(train) [13][1140/2569] lr: 4.0000e-02 eta: 1 day, 2:11:40 time: 0.2623 data_time: 0.0080 memory: 5828 grad_norm: 2.8511 loss: 2.6202 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6202 2023/06/04 18:41:07 - mmengine - INFO - Epoch(train) [13][1160/2569] lr: 4.0000e-02 eta: 1 day, 2:11:34 time: 0.2647 data_time: 0.0076 memory: 5828 grad_norm: 2.8772 loss: 2.5051 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.5051 2023/06/04 18:41:10 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:41:12 - mmengine - INFO - Epoch(train) [13][1180/2569] lr: 4.0000e-02 eta: 1 day, 2:11:29 time: 0.2676 data_time: 0.0082 memory: 5828 grad_norm: 2.8816 loss: 2.3671 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3671 2023/06/04 18:41:18 - mmengine - INFO - Epoch(train) [13][1200/2569] lr: 4.0000e-02 eta: 1 day, 2:11:23 time: 0.2654 data_time: 0.0077 memory: 5828 grad_norm: 2.7989 loss: 2.7774 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.7774 2023/06/04 18:41:23 - mmengine - INFO - Epoch(train) [13][1220/2569] lr: 4.0000e-02 eta: 1 day, 2:11:17 time: 0.2654 data_time: 0.0076 memory: 5828 grad_norm: 2.8764 loss: 2.5788 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5788 2023/06/04 18:41:28 - mmengine - INFO - Epoch(train) [13][1240/2569] lr: 4.0000e-02 eta: 1 day, 2:11:12 time: 0.2642 data_time: 0.0076 memory: 5828 grad_norm: 2.8056 loss: 2.6060 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6060 2023/06/04 18:41:34 - mmengine - INFO - Epoch(train) [13][1260/2569] lr: 4.0000e-02 eta: 1 day, 2:11:06 time: 0.2647 data_time: 0.0077 memory: 5828 grad_norm: 2.8347 loss: 2.8413 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8413 2023/06/04 18:41:39 - mmengine - INFO - Epoch(train) [13][1280/2569] lr: 4.0000e-02 eta: 1 day, 2:11:01 time: 0.2695 data_time: 0.0077 memory: 5828 grad_norm: 2.8382 loss: 2.5399 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5399 2023/06/04 18:41:44 - mmengine - INFO - Epoch(train) [13][1300/2569] lr: 4.0000e-02 eta: 1 day, 2:10:57 time: 0.2711 data_time: 0.0081 memory: 5828 grad_norm: 2.7855 loss: 2.7032 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7032 2023/06/04 18:41:50 - mmengine - INFO - Epoch(train) [13][1320/2569] lr: 4.0000e-02 eta: 1 day, 2:10:52 time: 0.2695 data_time: 0.0082 memory: 5828 grad_norm: 2.8347 loss: 2.6610 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6610 2023/06/04 18:41:55 - mmengine - INFO - Epoch(train) [13][1340/2569] lr: 4.0000e-02 eta: 1 day, 2:10:50 time: 0.2814 data_time: 0.0073 memory: 5828 grad_norm: 2.8451 loss: 2.7149 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7149 2023/06/04 18:42:01 - mmengine - INFO - Epoch(train) [13][1360/2569] lr: 4.0000e-02 eta: 1 day, 2:10:45 time: 0.2691 data_time: 0.0077 memory: 5828 grad_norm: 2.8082 loss: 2.4722 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4722 2023/06/04 18:42:06 - mmengine - INFO - Epoch(train) [13][1380/2569] lr: 4.0000e-02 eta: 1 day, 2:10:42 time: 0.2793 data_time: 0.0072 memory: 5828 grad_norm: 2.7944 loss: 2.8541 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8541 2023/06/04 18:42:12 - mmengine - INFO - Epoch(train) [13][1400/2569] lr: 4.0000e-02 eta: 1 day, 2:10:36 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 2.7822 loss: 2.4992 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4992 2023/06/04 18:42:17 - mmengine - INFO - Epoch(train) [13][1420/2569] lr: 4.0000e-02 eta: 1 day, 2:10:31 time: 0.2713 data_time: 0.0078 memory: 5828 grad_norm: 2.8628 loss: 2.3868 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3868 2023/06/04 18:42:22 - mmengine - INFO - Epoch(train) [13][1440/2569] lr: 4.0000e-02 eta: 1 day, 2:10:27 time: 0.2729 data_time: 0.0077 memory: 5828 grad_norm: 2.7901 loss: 2.4893 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4893 2023/06/04 18:42:28 - mmengine - INFO - Epoch(train) [13][1460/2569] lr: 4.0000e-02 eta: 1 day, 2:10:22 time: 0.2652 data_time: 0.0076 memory: 5828 grad_norm: 2.8256 loss: 2.6820 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6820 2023/06/04 18:42:33 - mmengine - INFO - Epoch(train) [13][1480/2569] lr: 4.0000e-02 eta: 1 day, 2:10:16 time: 0.2666 data_time: 0.0080 memory: 5828 grad_norm: 2.7891 loss: 2.6757 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6757 2023/06/04 18:42:38 - mmengine - INFO - Epoch(train) [13][1500/2569] lr: 4.0000e-02 eta: 1 day, 2:10:11 time: 0.2680 data_time: 0.0077 memory: 5828 grad_norm: 2.8255 loss: 2.3753 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3753 2023/06/04 18:42:44 - mmengine - INFO - Epoch(train) [13][1520/2569] lr: 4.0000e-02 eta: 1 day, 2:10:06 time: 0.2658 data_time: 0.0076 memory: 5828 grad_norm: 2.8640 loss: 2.7493 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7493 2023/06/04 18:42:49 - mmengine - INFO - Epoch(train) [13][1540/2569] lr: 4.0000e-02 eta: 1 day, 2:10:02 time: 0.2750 data_time: 0.0074 memory: 5828 grad_norm: 2.8429 loss: 2.7029 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7029 2023/06/04 18:42:55 - mmengine - INFO - Epoch(train) [13][1560/2569] lr: 4.0000e-02 eta: 1 day, 2:09:56 time: 0.2619 data_time: 0.0076 memory: 5828 grad_norm: 2.8315 loss: 2.5794 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5794 2023/06/04 18:43:00 - mmengine - INFO - Epoch(train) [13][1580/2569] lr: 4.0000e-02 eta: 1 day, 2:09:52 time: 0.2767 data_time: 0.0076 memory: 5828 grad_norm: 2.8161 loss: 2.7173 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7173 2023/06/04 18:43:05 - mmengine - INFO - Epoch(train) [13][1600/2569] lr: 4.0000e-02 eta: 1 day, 2:09:46 time: 0.2610 data_time: 0.0080 memory: 5828 grad_norm: 2.8412 loss: 2.2841 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2841 2023/06/04 18:43:11 - mmengine - INFO - Epoch(train) [13][1620/2569] lr: 4.0000e-02 eta: 1 day, 2:09:39 time: 0.2609 data_time: 0.0080 memory: 5828 grad_norm: 2.8197 loss: 2.3480 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3480 2023/06/04 18:43:16 - mmengine - INFO - Epoch(train) [13][1640/2569] lr: 4.0000e-02 eta: 1 day, 2:09:33 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 2.8091 loss: 2.6813 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6813 2023/06/04 18:43:21 - mmengine - INFO - Epoch(train) [13][1660/2569] lr: 4.0000e-02 eta: 1 day, 2:09:26 time: 0.2618 data_time: 0.0078 memory: 5828 grad_norm: 2.7734 loss: 2.5999 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5999 2023/06/04 18:43:26 - mmengine - INFO - Epoch(train) [13][1680/2569] lr: 4.0000e-02 eta: 1 day, 2:09:20 time: 0.2608 data_time: 0.0076 memory: 5828 grad_norm: 2.8480 loss: 2.6362 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6362 2023/06/04 18:43:32 - mmengine - INFO - Epoch(train) [13][1700/2569] lr: 4.0000e-02 eta: 1 day, 2:09:14 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 2.8225 loss: 2.6073 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6073 2023/06/04 18:43:37 - mmengine - INFO - Epoch(train) [13][1720/2569] lr: 4.0000e-02 eta: 1 day, 2:09:08 time: 0.2609 data_time: 0.0076 memory: 5828 grad_norm: 2.8506 loss: 2.4271 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4271 2023/06/04 18:43:42 - mmengine - INFO - Epoch(train) [13][1740/2569] lr: 4.0000e-02 eta: 1 day, 2:09:01 time: 0.2608 data_time: 0.0080 memory: 5828 grad_norm: 2.8087 loss: 2.4748 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4748 2023/06/04 18:43:48 - mmengine - INFO - Epoch(train) [13][1760/2569] lr: 4.0000e-02 eta: 1 day, 2:08:58 time: 0.2763 data_time: 0.0080 memory: 5828 grad_norm: 2.8102 loss: 2.5608 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5608 2023/06/04 18:43:53 - mmengine - INFO - Epoch(train) [13][1780/2569] lr: 4.0000e-02 eta: 1 day, 2:08:51 time: 0.2616 data_time: 0.0076 memory: 5828 grad_norm: 2.8479 loss: 2.5532 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5532 2023/06/04 18:43:58 - mmengine - INFO - Epoch(train) [13][1800/2569] lr: 4.0000e-02 eta: 1 day, 2:08:50 time: 0.2868 data_time: 0.0080 memory: 5828 grad_norm: 2.7774 loss: 2.7375 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7375 2023/06/04 18:44:04 - mmengine - INFO - Epoch(train) [13][1820/2569] lr: 4.0000e-02 eta: 1 day, 2:08:44 time: 0.2607 data_time: 0.0081 memory: 5828 grad_norm: 2.8141 loss: 2.6695 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6695 2023/06/04 18:44:09 - mmengine - INFO - Epoch(train) [13][1840/2569] lr: 4.0000e-02 eta: 1 day, 2:08:40 time: 0.2737 data_time: 0.0075 memory: 5828 grad_norm: 2.8210 loss: 2.5027 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5027 2023/06/04 18:44:14 - mmengine - INFO - Epoch(train) [13][1860/2569] lr: 4.0000e-02 eta: 1 day, 2:08:33 time: 0.2616 data_time: 0.0075 memory: 5828 grad_norm: 2.8570 loss: 2.6846 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6846 2023/06/04 18:44:20 - mmengine - INFO - Epoch(train) [13][1880/2569] lr: 4.0000e-02 eta: 1 day, 2:08:28 time: 0.2666 data_time: 0.0080 memory: 5828 grad_norm: 2.7763 loss: 2.5971 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5971 2023/06/04 18:44:25 - mmengine - INFO - Epoch(train) [13][1900/2569] lr: 4.0000e-02 eta: 1 day, 2:08:22 time: 0.2630 data_time: 0.0074 memory: 5828 grad_norm: 2.8237 loss: 2.5894 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5894 2023/06/04 18:44:30 - mmengine - INFO - Epoch(train) [13][1920/2569] lr: 4.0000e-02 eta: 1 day, 2:08:15 time: 0.2630 data_time: 0.0074 memory: 5828 grad_norm: 2.8546 loss: 3.0798 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0798 2023/06/04 18:44:36 - mmengine - INFO - Epoch(train) [13][1940/2569] lr: 4.0000e-02 eta: 1 day, 2:08:10 time: 0.2662 data_time: 0.0074 memory: 5828 grad_norm: 2.8406 loss: 2.7427 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7427 2023/06/04 18:44:41 - mmengine - INFO - Epoch(train) [13][1960/2569] lr: 4.0000e-02 eta: 1 day, 2:08:05 time: 0.2704 data_time: 0.0077 memory: 5828 grad_norm: 2.8295 loss: 2.6467 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6467 2023/06/04 18:44:46 - mmengine - INFO - Epoch(train) [13][1980/2569] lr: 4.0000e-02 eta: 1 day, 2:07:58 time: 0.2575 data_time: 0.0076 memory: 5828 grad_norm: 2.8329 loss: 2.9056 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.9056 2023/06/04 18:44:52 - mmengine - INFO - Epoch(train) [13][2000/2569] lr: 4.0000e-02 eta: 1 day, 2:07:53 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 2.7655 loss: 2.8045 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.8045 2023/06/04 18:44:57 - mmengine - INFO - Epoch(train) [13][2020/2569] lr: 4.0000e-02 eta: 1 day, 2:07:47 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 2.8326 loss: 2.4406 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4406 2023/06/04 18:45:02 - mmengine - INFO - Epoch(train) [13][2040/2569] lr: 4.0000e-02 eta: 1 day, 2:07:41 time: 0.2661 data_time: 0.0084 memory: 5828 grad_norm: 2.8725 loss: 2.7864 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7864 2023/06/04 18:45:07 - mmengine - INFO - Epoch(train) [13][2060/2569] lr: 4.0000e-02 eta: 1 day, 2:07:35 time: 0.2651 data_time: 0.0088 memory: 5828 grad_norm: 2.8285 loss: 2.6782 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6782 2023/06/04 18:45:13 - mmengine - INFO - Epoch(train) [13][2080/2569] lr: 4.0000e-02 eta: 1 day, 2:07:30 time: 0.2652 data_time: 0.0080 memory: 5828 grad_norm: 2.8446 loss: 2.6171 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6171 2023/06/04 18:45:18 - mmengine - INFO - Epoch(train) [13][2100/2569] lr: 4.0000e-02 eta: 1 day, 2:07:25 time: 0.2702 data_time: 0.0078 memory: 5828 grad_norm: 2.8355 loss: 2.9426 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.9426 2023/06/04 18:45:23 - mmengine - INFO - Epoch(train) [13][2120/2569] lr: 4.0000e-02 eta: 1 day, 2:07:20 time: 0.2691 data_time: 0.0094 memory: 5828 grad_norm: 2.7970 loss: 2.5664 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5664 2023/06/04 18:45:29 - mmengine - INFO - Epoch(train) [13][2140/2569] lr: 4.0000e-02 eta: 1 day, 2:07:14 time: 0.2650 data_time: 0.0067 memory: 5828 grad_norm: 2.7942 loss: 2.4437 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4437 2023/06/04 18:45:34 - mmengine - INFO - Epoch(train) [13][2160/2569] lr: 4.0000e-02 eta: 1 day, 2:07:08 time: 0.2609 data_time: 0.0089 memory: 5828 grad_norm: 2.8768 loss: 2.9025 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9025 2023/06/04 18:45:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:45:39 - mmengine - INFO - Epoch(train) [13][2180/2569] lr: 4.0000e-02 eta: 1 day, 2:07:03 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 2.8154 loss: 2.4160 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4160 2023/06/04 18:45:45 - mmengine - INFO - Epoch(train) [13][2200/2569] lr: 4.0000e-02 eta: 1 day, 2:06:57 time: 0.2666 data_time: 0.0078 memory: 5828 grad_norm: 2.7834 loss: 2.2923 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2923 2023/06/04 18:45:50 - mmengine - INFO - Epoch(train) [13][2220/2569] lr: 4.0000e-02 eta: 1 day, 2:06:52 time: 0.2658 data_time: 0.0081 memory: 5828 grad_norm: 2.8387 loss: 2.7266 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7266 2023/06/04 18:45:55 - mmengine - INFO - Epoch(train) [13][2240/2569] lr: 4.0000e-02 eta: 1 day, 2:06:45 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 2.8114 loss: 2.6592 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6592 2023/06/04 18:46:00 - mmengine - INFO - Epoch(train) [13][2260/2569] lr: 4.0000e-02 eta: 1 day, 2:06:39 time: 0.2605 data_time: 0.0078 memory: 5828 grad_norm: 2.8069 loss: 2.6122 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6122 2023/06/04 18:46:06 - mmengine - INFO - Epoch(train) [13][2280/2569] lr: 4.0000e-02 eta: 1 day, 2:06:32 time: 0.2622 data_time: 0.0078 memory: 5828 grad_norm: 2.8423 loss: 2.4217 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4217 2023/06/04 18:46:11 - mmengine - INFO - Epoch(train) [13][2300/2569] lr: 4.0000e-02 eta: 1 day, 2:06:26 time: 0.2633 data_time: 0.0078 memory: 5828 grad_norm: 2.7920 loss: 2.9858 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9858 2023/06/04 18:46:16 - mmengine - INFO - Epoch(train) [13][2320/2569] lr: 4.0000e-02 eta: 1 day, 2:06:22 time: 0.2717 data_time: 0.0079 memory: 5828 grad_norm: 2.8234 loss: 2.6829 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6829 2023/06/04 18:46:22 - mmengine - INFO - Epoch(train) [13][2340/2569] lr: 4.0000e-02 eta: 1 day, 2:06:15 time: 0.2613 data_time: 0.0075 memory: 5828 grad_norm: 2.7879 loss: 2.6101 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6101 2023/06/04 18:46:27 - mmengine - INFO - Epoch(train) [13][2360/2569] lr: 4.0000e-02 eta: 1 day, 2:06:11 time: 0.2717 data_time: 0.0080 memory: 5828 grad_norm: 2.8481 loss: 2.6173 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6173 2023/06/04 18:46:32 - mmengine - INFO - Epoch(train) [13][2380/2569] lr: 4.0000e-02 eta: 1 day, 2:06:05 time: 0.2621 data_time: 0.0079 memory: 5828 grad_norm: 2.8247 loss: 2.6016 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6016 2023/06/04 18:46:38 - mmengine - INFO - Epoch(train) [13][2400/2569] lr: 4.0000e-02 eta: 1 day, 2:05:58 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 2.8282 loss: 2.6135 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6135 2023/06/04 18:46:43 - mmengine - INFO - Epoch(train) [13][2420/2569] lr: 4.0000e-02 eta: 1 day, 2:05:51 time: 0.2589 data_time: 0.0085 memory: 5828 grad_norm: 2.8718 loss: 2.5853 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5853 2023/06/04 18:46:48 - mmengine - INFO - Epoch(train) [13][2440/2569] lr: 4.0000e-02 eta: 1 day, 2:05:48 time: 0.2795 data_time: 0.0077 memory: 5828 grad_norm: 2.8192 loss: 2.8513 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8513 2023/06/04 18:46:54 - mmengine - INFO - Epoch(train) [13][2460/2569] lr: 4.0000e-02 eta: 1 day, 2:05:43 time: 0.2653 data_time: 0.0076 memory: 5828 grad_norm: 2.8136 loss: 2.9288 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9288 2023/06/04 18:46:59 - mmengine - INFO - Epoch(train) [13][2480/2569] lr: 4.0000e-02 eta: 1 day, 2:05:40 time: 0.2774 data_time: 0.0090 memory: 5828 grad_norm: 2.8804 loss: 2.5620 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5620 2023/06/04 18:47:05 - mmengine - INFO - Epoch(train) [13][2500/2569] lr: 4.0000e-02 eta: 1 day, 2:05:35 time: 0.2723 data_time: 0.0076 memory: 5828 grad_norm: 2.8312 loss: 2.6949 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6949 2023/06/04 18:47:10 - mmengine - INFO - Epoch(train) [13][2520/2569] lr: 4.0000e-02 eta: 1 day, 2:05:30 time: 0.2672 data_time: 0.0079 memory: 5828 grad_norm: 2.8269 loss: 2.5814 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.5814 2023/06/04 18:47:15 - mmengine - INFO - Epoch(train) [13][2540/2569] lr: 4.0000e-02 eta: 1 day, 2:05:25 time: 0.2653 data_time: 0.0076 memory: 5828 grad_norm: 2.7432 loss: 2.4879 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4879 2023/06/04 18:47:21 - mmengine - INFO - Epoch(train) [13][2560/2569] lr: 4.0000e-02 eta: 1 day, 2:05:19 time: 0.2662 data_time: 0.0075 memory: 5828 grad_norm: 2.8062 loss: 2.7950 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7950 2023/06/04 18:47:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:47:23 - mmengine - INFO - Epoch(train) [13][2569/2569] lr: 4.0000e-02 eta: 1 day, 2:05:15 time: 0.2530 data_time: 0.0070 memory: 5828 grad_norm: 2.8338 loss: 2.6654 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.6654 2023/06/04 18:47:30 - mmengine - INFO - Epoch(train) [14][ 20/2569] lr: 4.0000e-02 eta: 1 day, 2:05:24 time: 0.3359 data_time: 0.0548 memory: 5828 grad_norm: 2.7575 loss: 2.6710 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6710 2023/06/04 18:47:35 - mmengine - INFO - Epoch(train) [14][ 40/2569] lr: 4.0000e-02 eta: 1 day, 2:05:20 time: 0.2722 data_time: 0.0078 memory: 5828 grad_norm: 2.7611 loss: 2.8697 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8697 2023/06/04 18:47:40 - mmengine - INFO - Epoch(train) [14][ 60/2569] lr: 4.0000e-02 eta: 1 day, 2:05:15 time: 0.2703 data_time: 0.0073 memory: 5828 grad_norm: 2.8374 loss: 2.6797 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6797 2023/06/04 18:47:46 - mmengine - INFO - Epoch(train) [14][ 80/2569] lr: 4.0000e-02 eta: 1 day, 2:05:10 time: 0.2667 data_time: 0.0078 memory: 5828 grad_norm: 2.8312 loss: 2.6650 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6650 2023/06/04 18:47:51 - mmengine - INFO - Epoch(train) [14][ 100/2569] lr: 4.0000e-02 eta: 1 day, 2:05:05 time: 0.2666 data_time: 0.0079 memory: 5828 grad_norm: 2.8175 loss: 2.8971 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8971 2023/06/04 18:47:56 - mmengine - INFO - Epoch(train) [14][ 120/2569] lr: 4.0000e-02 eta: 1 day, 2:05:00 time: 0.2688 data_time: 0.0076 memory: 5828 grad_norm: 2.8085 loss: 2.4238 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4238 2023/06/04 18:48:02 - mmengine - INFO - Epoch(train) [14][ 140/2569] lr: 4.0000e-02 eta: 1 day, 2:04:55 time: 0.2672 data_time: 0.0076 memory: 5828 grad_norm: 2.8627 loss: 2.6644 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6644 2023/06/04 18:48:07 - mmengine - INFO - Epoch(train) [14][ 160/2569] lr: 4.0000e-02 eta: 1 day, 2:04:50 time: 0.2695 data_time: 0.0078 memory: 5828 grad_norm: 2.8093 loss: 2.6179 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6179 2023/06/04 18:48:13 - mmengine - INFO - Epoch(train) [14][ 180/2569] lr: 4.0000e-02 eta: 1 day, 2:04:44 time: 0.2656 data_time: 0.0081 memory: 5828 grad_norm: 2.8415 loss: 2.6916 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6916 2023/06/04 18:48:18 - mmengine - INFO - Epoch(train) [14][ 200/2569] lr: 4.0000e-02 eta: 1 day, 2:04:39 time: 0.2662 data_time: 0.0080 memory: 5828 grad_norm: 2.8491 loss: 2.8577 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8577 2023/06/04 18:48:23 - mmengine - INFO - Epoch(train) [14][ 220/2569] lr: 4.0000e-02 eta: 1 day, 2:04:32 time: 0.2612 data_time: 0.0090 memory: 5828 grad_norm: 2.7950 loss: 2.6406 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6406 2023/06/04 18:48:29 - mmengine - INFO - Epoch(train) [14][ 240/2569] lr: 4.0000e-02 eta: 1 day, 2:04:29 time: 0.2769 data_time: 0.0077 memory: 5828 grad_norm: 2.8720 loss: 2.6622 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6622 2023/06/04 18:48:34 - mmengine - INFO - Epoch(train) [14][ 260/2569] lr: 4.0000e-02 eta: 1 day, 2:04:23 time: 0.2650 data_time: 0.0077 memory: 5828 grad_norm: 2.8394 loss: 2.6254 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6254 2023/06/04 18:48:40 - mmengine - INFO - Epoch(train) [14][ 280/2569] lr: 4.0000e-02 eta: 1 day, 2:04:21 time: 0.2834 data_time: 0.0078 memory: 5828 grad_norm: 2.7743 loss: 2.4130 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4130 2023/06/04 18:48:45 - mmengine - INFO - Epoch(train) [14][ 300/2569] lr: 4.0000e-02 eta: 1 day, 2:04:16 time: 0.2668 data_time: 0.0081 memory: 5828 grad_norm: 2.8004 loss: 2.7224 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7224 2023/06/04 18:48:50 - mmengine - INFO - Epoch(train) [14][ 320/2569] lr: 4.0000e-02 eta: 1 day, 2:04:11 time: 0.2669 data_time: 0.0084 memory: 5828 grad_norm: 2.8048 loss: 2.3675 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3675 2023/06/04 18:48:56 - mmengine - INFO - Epoch(train) [14][ 340/2569] lr: 4.0000e-02 eta: 1 day, 2:04:06 time: 0.2712 data_time: 0.0078 memory: 5828 grad_norm: 2.8078 loss: 2.6878 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6878 2023/06/04 18:49:01 - mmengine - INFO - Epoch(train) [14][ 360/2569] lr: 4.0000e-02 eta: 1 day, 2:04:00 time: 0.2649 data_time: 0.0078 memory: 5828 grad_norm: 2.8027 loss: 2.6612 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6612 2023/06/04 18:49:06 - mmengine - INFO - Epoch(train) [14][ 380/2569] lr: 4.0000e-02 eta: 1 day, 2:03:56 time: 0.2706 data_time: 0.0080 memory: 5828 grad_norm: 2.7481 loss: 2.9144 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9144 2023/06/04 18:49:12 - mmengine - INFO - Epoch(train) [14][ 400/2569] lr: 4.0000e-02 eta: 1 day, 2:03:49 time: 0.2621 data_time: 0.0095 memory: 5828 grad_norm: 2.8589 loss: 2.7093 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7093 2023/06/04 18:49:17 - mmengine - INFO - Epoch(train) [14][ 420/2569] lr: 4.0000e-02 eta: 1 day, 2:03:42 time: 0.2591 data_time: 0.0075 memory: 5828 grad_norm: 2.8250 loss: 2.6819 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6819 2023/06/04 18:49:22 - mmengine - INFO - Epoch(train) [14][ 440/2569] lr: 4.0000e-02 eta: 1 day, 2:03:38 time: 0.2730 data_time: 0.0081 memory: 5828 grad_norm: 2.7992 loss: 2.5279 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5279 2023/06/04 18:49:27 - mmengine - INFO - Epoch(train) [14][ 460/2569] lr: 4.0000e-02 eta: 1 day, 2:03:32 time: 0.2603 data_time: 0.0079 memory: 5828 grad_norm: 2.7762 loss: 2.3619 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3619 2023/06/04 18:49:33 - mmengine - INFO - Epoch(train) [14][ 480/2569] lr: 4.0000e-02 eta: 1 day, 2:03:26 time: 0.2633 data_time: 0.0082 memory: 5828 grad_norm: 2.8413 loss: 2.5673 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5673 2023/06/04 18:49:38 - mmengine - INFO - Epoch(train) [14][ 500/2569] lr: 4.0000e-02 eta: 1 day, 2:03:20 time: 0.2635 data_time: 0.0080 memory: 5828 grad_norm: 2.7915 loss: 2.7950 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7950 2023/06/04 18:49:43 - mmengine - INFO - Epoch(train) [14][ 520/2569] lr: 4.0000e-02 eta: 1 day, 2:03:15 time: 0.2689 data_time: 0.0087 memory: 5828 grad_norm: 2.7596 loss: 2.2776 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2776 2023/06/04 18:49:49 - mmengine - INFO - Epoch(train) [14][ 540/2569] lr: 4.0000e-02 eta: 1 day, 2:03:08 time: 0.2606 data_time: 0.0077 memory: 5828 grad_norm: 2.8208 loss: 2.6093 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6093 2023/06/04 18:49:54 - mmengine - INFO - Epoch(train) [14][ 560/2569] lr: 4.0000e-02 eta: 1 day, 2:03:03 time: 0.2696 data_time: 0.0076 memory: 5828 grad_norm: 2.8457 loss: 2.1520 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1520 2023/06/04 18:49:59 - mmengine - INFO - Epoch(train) [14][ 580/2569] lr: 4.0000e-02 eta: 1 day, 2:02:58 time: 0.2700 data_time: 0.0075 memory: 5828 grad_norm: 2.7756 loss: 2.7220 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7220 2023/06/04 18:50:05 - mmengine - INFO - Epoch(train) [14][ 600/2569] lr: 4.0000e-02 eta: 1 day, 2:02:53 time: 0.2660 data_time: 0.0080 memory: 5828 grad_norm: 2.8022 loss: 2.4331 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4331 2023/06/04 18:50:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:50:10 - mmengine - INFO - Epoch(train) [14][ 620/2569] lr: 4.0000e-02 eta: 1 day, 2:02:49 time: 0.2721 data_time: 0.0075 memory: 5828 grad_norm: 2.8036 loss: 2.6645 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6645 2023/06/04 18:50:16 - mmengine - INFO - Epoch(train) [14][ 640/2569] lr: 4.0000e-02 eta: 1 day, 2:02:43 time: 0.2675 data_time: 0.0081 memory: 5828 grad_norm: 2.8171 loss: 2.5802 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5802 2023/06/04 18:50:21 - mmengine - INFO - Epoch(train) [14][ 660/2569] lr: 4.0000e-02 eta: 1 day, 2:02:38 time: 0.2653 data_time: 0.0080 memory: 5828 grad_norm: 2.8009 loss: 2.4469 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4469 2023/06/04 18:50:26 - mmengine - INFO - Epoch(train) [14][ 680/2569] lr: 4.0000e-02 eta: 1 day, 2:02:33 time: 0.2707 data_time: 0.0076 memory: 5828 grad_norm: 2.7976 loss: 2.3911 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3911 2023/06/04 18:50:32 - mmengine - INFO - Epoch(train) [14][ 700/2569] lr: 4.0000e-02 eta: 1 day, 2:02:29 time: 0.2707 data_time: 0.0077 memory: 5828 grad_norm: 2.7762 loss: 2.8772 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8772 2023/06/04 18:50:37 - mmengine - INFO - Epoch(train) [14][ 720/2569] lr: 4.0000e-02 eta: 1 day, 2:02:22 time: 0.2614 data_time: 0.0080 memory: 5828 grad_norm: 2.8219 loss: 2.4086 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4086 2023/06/04 18:50:42 - mmengine - INFO - Epoch(train) [14][ 740/2569] lr: 4.0000e-02 eta: 1 day, 2:02:17 time: 0.2669 data_time: 0.0079 memory: 5828 grad_norm: 2.8197 loss: 2.4880 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4880 2023/06/04 18:50:48 - mmengine - INFO - Epoch(train) [14][ 760/2569] lr: 4.0000e-02 eta: 1 day, 2:02:11 time: 0.2667 data_time: 0.0078 memory: 5828 grad_norm: 2.8041 loss: 2.5069 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5069 2023/06/04 18:50:53 - mmengine - INFO - Epoch(train) [14][ 780/2569] lr: 4.0000e-02 eta: 1 day, 2:02:08 time: 0.2750 data_time: 0.0075 memory: 5828 grad_norm: 2.7936 loss: 2.5678 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5678 2023/06/04 18:50:59 - mmengine - INFO - Epoch(train) [14][ 800/2569] lr: 4.0000e-02 eta: 1 day, 2:02:05 time: 0.2790 data_time: 0.0079 memory: 5828 grad_norm: 2.8657 loss: 2.1092 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1092 2023/06/04 18:51:04 - mmengine - INFO - Epoch(train) [14][ 820/2569] lr: 4.0000e-02 eta: 1 day, 2:02:03 time: 0.2819 data_time: 0.0076 memory: 5828 grad_norm: 2.8004 loss: 2.4233 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4233 2023/06/04 18:51:10 - mmengine - INFO - Epoch(train) [14][ 840/2569] lr: 4.0000e-02 eta: 1 day, 2:01:56 time: 0.2612 data_time: 0.0080 memory: 5828 grad_norm: 2.8263 loss: 2.5486 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5486 2023/06/04 18:51:15 - mmengine - INFO - Epoch(train) [14][ 860/2569] lr: 4.0000e-02 eta: 1 day, 2:01:53 time: 0.2784 data_time: 0.0077 memory: 5828 grad_norm: 2.7878 loss: 2.6468 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6468 2023/06/04 18:51:20 - mmengine - INFO - Epoch(train) [14][ 880/2569] lr: 4.0000e-02 eta: 1 day, 2:01:48 time: 0.2652 data_time: 0.0080 memory: 5828 grad_norm: 2.7740 loss: 2.7717 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7717 2023/06/04 18:51:26 - mmengine - INFO - Epoch(train) [14][ 900/2569] lr: 4.0000e-02 eta: 1 day, 2:01:42 time: 0.2660 data_time: 0.0081 memory: 5828 grad_norm: 2.7709 loss: 2.5391 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5391 2023/06/04 18:51:31 - mmengine - INFO - Epoch(train) [14][ 920/2569] lr: 4.0000e-02 eta: 1 day, 2:01:36 time: 0.2618 data_time: 0.0079 memory: 5828 grad_norm: 2.8384 loss: 2.4196 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4196 2023/06/04 18:51:36 - mmengine - INFO - Epoch(train) [14][ 940/2569] lr: 4.0000e-02 eta: 1 day, 2:01:29 time: 0.2606 data_time: 0.0081 memory: 5828 grad_norm: 2.8155 loss: 2.7395 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7395 2023/06/04 18:51:41 - mmengine - INFO - Epoch(train) [14][ 960/2569] lr: 4.0000e-02 eta: 1 day, 2:01:22 time: 0.2610 data_time: 0.0078 memory: 5828 grad_norm: 2.8379 loss: 2.4673 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4673 2023/06/04 18:51:47 - mmengine - INFO - Epoch(train) [14][ 980/2569] lr: 4.0000e-02 eta: 1 day, 2:01:16 time: 0.2610 data_time: 0.0078 memory: 5828 grad_norm: 2.8014 loss: 2.2917 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2917 2023/06/04 18:51:52 - mmengine - INFO - Epoch(train) [14][1000/2569] lr: 4.0000e-02 eta: 1 day, 2:01:10 time: 0.2658 data_time: 0.0079 memory: 5828 grad_norm: 2.8231 loss: 2.6139 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6139 2023/06/04 18:51:57 - mmengine - INFO - Epoch(train) [14][1020/2569] lr: 4.0000e-02 eta: 1 day, 2:01:04 time: 0.2644 data_time: 0.0080 memory: 5828 grad_norm: 2.8209 loss: 2.7061 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7061 2023/06/04 18:52:02 - mmengine - INFO - Epoch(train) [14][1040/2569] lr: 4.0000e-02 eta: 1 day, 2:00:58 time: 0.2594 data_time: 0.0075 memory: 5828 grad_norm: 2.8717 loss: 2.1949 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1949 2023/06/04 18:52:08 - mmengine - INFO - Epoch(train) [14][1060/2569] lr: 4.0000e-02 eta: 1 day, 2:00:52 time: 0.2649 data_time: 0.0079 memory: 5828 grad_norm: 2.8111 loss: 2.4905 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4905 2023/06/04 18:52:13 - mmengine - INFO - Epoch(train) [14][1080/2569] lr: 4.0000e-02 eta: 1 day, 2:00:47 time: 0.2715 data_time: 0.0078 memory: 5828 grad_norm: 2.8216 loss: 2.7677 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7677 2023/06/04 18:52:18 - mmengine - INFO - Epoch(train) [14][1100/2569] lr: 4.0000e-02 eta: 1 day, 2:00:41 time: 0.2596 data_time: 0.0077 memory: 5828 grad_norm: 2.7847 loss: 2.4934 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4934 2023/06/04 18:52:24 - mmengine - INFO - Epoch(train) [14][1120/2569] lr: 4.0000e-02 eta: 1 day, 2:00:35 time: 0.2664 data_time: 0.0078 memory: 5828 grad_norm: 2.7801 loss: 2.5767 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5767 2023/06/04 18:52:29 - mmengine - INFO - Epoch(train) [14][1140/2569] lr: 4.0000e-02 eta: 1 day, 2:00:31 time: 0.2702 data_time: 0.0088 memory: 5828 grad_norm: 2.8227 loss: 2.4398 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4398 2023/06/04 18:52:34 - mmengine - INFO - Epoch(train) [14][1160/2569] lr: 4.0000e-02 eta: 1 day, 2:00:26 time: 0.2718 data_time: 0.0078 memory: 5828 grad_norm: 2.8198 loss: 2.6829 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6829 2023/06/04 18:52:40 - mmengine - INFO - Epoch(train) [14][1180/2569] lr: 4.0000e-02 eta: 1 day, 2:00:21 time: 0.2666 data_time: 0.0086 memory: 5828 grad_norm: 2.8035 loss: 2.5554 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5554 2023/06/04 18:52:45 - mmengine - INFO - Epoch(train) [14][1200/2569] lr: 4.0000e-02 eta: 1 day, 2:00:16 time: 0.2707 data_time: 0.0079 memory: 5828 grad_norm: 2.8491 loss: 2.7198 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7198 2023/06/04 18:52:51 - mmengine - INFO - Epoch(train) [14][1220/2569] lr: 4.0000e-02 eta: 1 day, 2:00:12 time: 0.2726 data_time: 0.0081 memory: 5828 grad_norm: 2.8073 loss: 2.4580 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4580 2023/06/04 18:52:56 - mmengine - INFO - Epoch(train) [14][1240/2569] lr: 4.0000e-02 eta: 1 day, 2:00:06 time: 0.2630 data_time: 0.0077 memory: 5828 grad_norm: 2.8305 loss: 2.4272 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4272 2023/06/04 18:53:01 - mmengine - INFO - Epoch(train) [14][1260/2569] lr: 4.0000e-02 eta: 1 day, 2:00:02 time: 0.2728 data_time: 0.0080 memory: 5828 grad_norm: 2.8489 loss: 2.5091 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5091 2023/06/04 18:53:07 - mmengine - INFO - Epoch(train) [14][1280/2569] lr: 4.0000e-02 eta: 1 day, 1:59:55 time: 0.2615 data_time: 0.0084 memory: 5828 grad_norm: 2.8181 loss: 2.7007 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7007 2023/06/04 18:53:12 - mmengine - INFO - Epoch(train) [14][1300/2569] lr: 4.0000e-02 eta: 1 day, 1:59:50 time: 0.2655 data_time: 0.0077 memory: 5828 grad_norm: 2.8333 loss: 2.8759 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.8759 2023/06/04 18:53:17 - mmengine - INFO - Epoch(train) [14][1320/2569] lr: 4.0000e-02 eta: 1 day, 1:59:44 time: 0.2644 data_time: 0.0078 memory: 5828 grad_norm: 2.8671 loss: 2.6484 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6484 2023/06/04 18:53:22 - mmengine - INFO - Epoch(train) [14][1340/2569] lr: 4.0000e-02 eta: 1 day, 1:59:38 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 2.8570 loss: 2.5707 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5707 2023/06/04 18:53:28 - mmengine - INFO - Epoch(train) [14][1360/2569] lr: 4.0000e-02 eta: 1 day, 1:59:32 time: 0.2674 data_time: 0.0080 memory: 5828 grad_norm: 2.8255 loss: 2.5174 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5174 2023/06/04 18:53:33 - mmengine - INFO - Epoch(train) [14][1380/2569] lr: 4.0000e-02 eta: 1 day, 1:59:27 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 2.8520 loss: 2.4226 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4226 2023/06/04 18:53:39 - mmengine - INFO - Epoch(train) [14][1400/2569] lr: 4.0000e-02 eta: 1 day, 1:59:24 time: 0.2798 data_time: 0.0074 memory: 5828 grad_norm: 2.8412 loss: 2.3698 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3698 2023/06/04 18:53:44 - mmengine - INFO - Epoch(train) [14][1420/2569] lr: 4.0000e-02 eta: 1 day, 1:59:18 time: 0.2642 data_time: 0.0080 memory: 5828 grad_norm: 2.8322 loss: 2.6481 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6481 2023/06/04 18:53:49 - mmengine - INFO - Epoch(train) [14][1440/2569] lr: 4.0000e-02 eta: 1 day, 1:59:14 time: 0.2718 data_time: 0.0077 memory: 5828 grad_norm: 2.7774 loss: 2.5112 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5112 2023/06/04 18:53:55 - mmengine - INFO - Epoch(train) [14][1460/2569] lr: 4.0000e-02 eta: 1 day, 1:59:07 time: 0.2603 data_time: 0.0077 memory: 5828 grad_norm: 2.7556 loss: 2.4736 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4736 2023/06/04 18:54:00 - mmengine - INFO - Epoch(train) [14][1480/2569] lr: 4.0000e-02 eta: 1 day, 1:59:01 time: 0.2644 data_time: 0.0080 memory: 5828 grad_norm: 2.8251 loss: 2.4527 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4527 2023/06/04 18:54:05 - mmengine - INFO - Epoch(train) [14][1500/2569] lr: 4.0000e-02 eta: 1 day, 1:58:56 time: 0.2664 data_time: 0.0075 memory: 5828 grad_norm: 2.8730 loss: 2.6409 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6409 2023/06/04 18:54:11 - mmengine - INFO - Epoch(train) [14][1520/2569] lr: 4.0000e-02 eta: 1 day, 1:58:50 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 2.8318 loss: 2.8218 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8218 2023/06/04 18:54:16 - mmengine - INFO - Epoch(train) [14][1540/2569] lr: 4.0000e-02 eta: 1 day, 1:58:46 time: 0.2708 data_time: 0.0079 memory: 5828 grad_norm: 2.8077 loss: 2.6134 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6134 2023/06/04 18:54:22 - mmengine - INFO - Epoch(train) [14][1560/2569] lr: 4.0000e-02 eta: 1 day, 1:58:42 time: 0.2742 data_time: 0.0077 memory: 5828 grad_norm: 2.8263 loss: 2.5999 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5999 2023/06/04 18:54:27 - mmengine - INFO - Epoch(train) [14][1580/2569] lr: 4.0000e-02 eta: 1 day, 1:58:37 time: 0.2681 data_time: 0.0076 memory: 5828 grad_norm: 2.8312 loss: 2.6400 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6400 2023/06/04 18:54:32 - mmengine - INFO - Epoch(train) [14][1600/2569] lr: 4.0000e-02 eta: 1 day, 1:58:31 time: 0.2649 data_time: 0.0077 memory: 5828 grad_norm: 2.8039 loss: 2.6976 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6976 2023/06/04 18:54:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:54:38 - mmengine - INFO - Epoch(train) [14][1620/2569] lr: 4.0000e-02 eta: 1 day, 1:58:29 time: 0.2834 data_time: 0.0083 memory: 5828 grad_norm: 2.7912 loss: 2.6307 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6307 2023/06/04 18:54:43 - mmengine - INFO - Epoch(train) [14][1640/2569] lr: 4.0000e-02 eta: 1 day, 1:58:23 time: 0.2650 data_time: 0.0083 memory: 5828 grad_norm: 2.8305 loss: 2.5394 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5394 2023/06/04 18:54:48 - mmengine - INFO - Epoch(train) [14][1660/2569] lr: 4.0000e-02 eta: 1 day, 1:58:18 time: 0.2659 data_time: 0.0081 memory: 5828 grad_norm: 2.8321 loss: 2.5785 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5785 2023/06/04 18:54:54 - mmengine - INFO - Epoch(train) [14][1680/2569] lr: 4.0000e-02 eta: 1 day, 1:58:13 time: 0.2702 data_time: 0.0080 memory: 5828 grad_norm: 2.8490 loss: 2.4701 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4701 2023/06/04 18:54:59 - mmengine - INFO - Epoch(train) [14][1700/2569] lr: 4.0000e-02 eta: 1 day, 1:58:07 time: 0.2668 data_time: 0.0088 memory: 5828 grad_norm: 2.8177 loss: 2.5611 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5611 2023/06/04 18:55:05 - mmengine - INFO - Epoch(train) [14][1720/2569] lr: 4.0000e-02 eta: 1 day, 1:58:02 time: 0.2672 data_time: 0.0080 memory: 5828 grad_norm: 2.8019 loss: 2.6262 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6262 2023/06/04 18:55:10 - mmengine - INFO - Epoch(train) [14][1740/2569] lr: 4.0000e-02 eta: 1 day, 1:57:58 time: 0.2721 data_time: 0.0082 memory: 5828 grad_norm: 2.8188 loss: 2.8547 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8547 2023/06/04 18:55:16 - mmengine - INFO - Epoch(train) [14][1760/2569] lr: 4.0000e-02 eta: 1 day, 1:57:55 time: 0.2807 data_time: 0.0082 memory: 5828 grad_norm: 2.8932 loss: 2.7297 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.7297 2023/06/04 18:55:21 - mmengine - INFO - Epoch(train) [14][1780/2569] lr: 4.0000e-02 eta: 1 day, 1:57:50 time: 0.2660 data_time: 0.0077 memory: 5828 grad_norm: 2.8055 loss: 2.3809 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3809 2023/06/04 18:55:26 - mmengine - INFO - Epoch(train) [14][1800/2569] lr: 4.0000e-02 eta: 1 day, 1:57:45 time: 0.2722 data_time: 0.0083 memory: 5828 grad_norm: 2.8274 loss: 2.6434 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6434 2023/06/04 18:55:32 - mmengine - INFO - Epoch(train) [14][1820/2569] lr: 4.0000e-02 eta: 1 day, 1:57:42 time: 0.2749 data_time: 0.0078 memory: 5828 grad_norm: 2.8292 loss: 2.2512 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2512 2023/06/04 18:55:37 - mmengine - INFO - Epoch(train) [14][1840/2569] lr: 4.0000e-02 eta: 1 day, 1:57:37 time: 0.2692 data_time: 0.0074 memory: 5828 grad_norm: 2.7708 loss: 2.6810 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6810 2023/06/04 18:55:43 - mmengine - INFO - Epoch(train) [14][1860/2569] lr: 4.0000e-02 eta: 1 day, 1:57:31 time: 0.2646 data_time: 0.0076 memory: 5828 grad_norm: 2.8028 loss: 2.4107 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4107 2023/06/04 18:55:48 - mmengine - INFO - Epoch(train) [14][1880/2569] lr: 4.0000e-02 eta: 1 day, 1:57:26 time: 0.2706 data_time: 0.0077 memory: 5828 grad_norm: 2.8440 loss: 2.7314 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7314 2023/06/04 18:55:53 - mmengine - INFO - Epoch(train) [14][1900/2569] lr: 4.0000e-02 eta: 1 day, 1:57:21 time: 0.2662 data_time: 0.0082 memory: 5828 grad_norm: 2.8245 loss: 2.1533 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1533 2023/06/04 18:55:59 - mmengine - INFO - Epoch(train) [14][1920/2569] lr: 4.0000e-02 eta: 1 day, 1:57:16 time: 0.2703 data_time: 0.0079 memory: 5828 grad_norm: 2.7811 loss: 2.3605 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3605 2023/06/04 18:56:04 - mmengine - INFO - Epoch(train) [14][1940/2569] lr: 4.0000e-02 eta: 1 day, 1:57:13 time: 0.2753 data_time: 0.0080 memory: 5828 grad_norm: 2.7805 loss: 2.6725 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6725 2023/06/04 18:56:09 - mmengine - INFO - Epoch(train) [14][1960/2569] lr: 4.0000e-02 eta: 1 day, 1:57:06 time: 0.2606 data_time: 0.0078 memory: 5828 grad_norm: 2.7633 loss: 2.5585 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5585 2023/06/04 18:56:15 - mmengine - INFO - Epoch(train) [14][1980/2569] lr: 4.0000e-02 eta: 1 day, 1:57:02 time: 0.2726 data_time: 0.0077 memory: 5828 grad_norm: 2.8520 loss: 2.6186 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6186 2023/06/04 18:56:20 - mmengine - INFO - Epoch(train) [14][2000/2569] lr: 4.0000e-02 eta: 1 day, 1:56:56 time: 0.2653 data_time: 0.0083 memory: 5828 grad_norm: 2.8725 loss: 2.5371 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5371 2023/06/04 18:56:25 - mmengine - INFO - Epoch(train) [14][2020/2569] lr: 4.0000e-02 eta: 1 day, 1:56:50 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 2.8164 loss: 2.5855 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5855 2023/06/04 18:56:31 - mmengine - INFO - Epoch(train) [14][2040/2569] lr: 4.0000e-02 eta: 1 day, 1:56:46 time: 0.2705 data_time: 0.0079 memory: 5828 grad_norm: 2.7774 loss: 2.6363 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6363 2023/06/04 18:56:36 - mmengine - INFO - Epoch(train) [14][2060/2569] lr: 4.0000e-02 eta: 1 day, 1:56:41 time: 0.2726 data_time: 0.0074 memory: 5828 grad_norm: 2.8293 loss: 2.3471 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3471 2023/06/04 18:56:42 - mmengine - INFO - Epoch(train) [14][2080/2569] lr: 4.0000e-02 eta: 1 day, 1:56:36 time: 0.2653 data_time: 0.0077 memory: 5828 grad_norm: 2.8119 loss: 2.7813 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7813 2023/06/04 18:56:47 - mmengine - INFO - Epoch(train) [14][2100/2569] lr: 4.0000e-02 eta: 1 day, 1:56:31 time: 0.2682 data_time: 0.0076 memory: 5828 grad_norm: 2.7908 loss: 2.7098 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7098 2023/06/04 18:56:53 - mmengine - INFO - Epoch(train) [14][2120/2569] lr: 4.0000e-02 eta: 1 day, 1:56:28 time: 0.2816 data_time: 0.0078 memory: 5828 grad_norm: 2.8082 loss: 2.8404 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8404 2023/06/04 18:56:58 - mmengine - INFO - Epoch(train) [14][2140/2569] lr: 4.0000e-02 eta: 1 day, 1:56:24 time: 0.2722 data_time: 0.0077 memory: 5828 grad_norm: 2.8570 loss: 2.8640 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8640 2023/06/04 18:57:04 - mmengine - INFO - Epoch(train) [14][2160/2569] lr: 4.0000e-02 eta: 1 day, 1:56:20 time: 0.2768 data_time: 0.0078 memory: 5828 grad_norm: 2.8143 loss: 2.5814 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5814 2023/06/04 18:57:09 - mmengine - INFO - Epoch(train) [14][2180/2569] lr: 4.0000e-02 eta: 1 day, 1:56:15 time: 0.2643 data_time: 0.0085 memory: 5828 grad_norm: 2.8293 loss: 2.9230 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9230 2023/06/04 18:57:14 - mmengine - INFO - Epoch(train) [14][2200/2569] lr: 4.0000e-02 eta: 1 day, 1:56:09 time: 0.2661 data_time: 0.0075 memory: 5828 grad_norm: 2.7790 loss: 2.5474 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5474 2023/06/04 18:57:20 - mmengine - INFO - Epoch(train) [14][2220/2569] lr: 4.0000e-02 eta: 1 day, 1:56:04 time: 0.2676 data_time: 0.0080 memory: 5828 grad_norm: 2.7826 loss: 2.3817 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3817 2023/06/04 18:57:25 - mmengine - INFO - Epoch(train) [14][2240/2569] lr: 4.0000e-02 eta: 1 day, 1:55:57 time: 0.2615 data_time: 0.0085 memory: 5828 grad_norm: 2.8335 loss: 2.5595 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5595 2023/06/04 18:57:30 - mmengine - INFO - Epoch(train) [14][2260/2569] lr: 4.0000e-02 eta: 1 day, 1:55:51 time: 0.2611 data_time: 0.0076 memory: 5828 grad_norm: 2.8312 loss: 2.9182 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9182 2023/06/04 18:57:35 - mmengine - INFO - Epoch(train) [14][2280/2569] lr: 4.0000e-02 eta: 1 day, 1:55:45 time: 0.2617 data_time: 0.0080 memory: 5828 grad_norm: 2.8437 loss: 2.5832 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5832 2023/06/04 18:57:41 - mmengine - INFO - Epoch(train) [14][2300/2569] lr: 4.0000e-02 eta: 1 day, 1:55:39 time: 0.2671 data_time: 0.0075 memory: 5828 grad_norm: 2.8469 loss: 2.4836 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4836 2023/06/04 18:57:46 - mmengine - INFO - Epoch(train) [14][2320/2569] lr: 4.0000e-02 eta: 1 day, 1:55:34 time: 0.2657 data_time: 0.0080 memory: 5828 grad_norm: 2.8259 loss: 2.5074 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5074 2023/06/04 18:57:51 - mmengine - INFO - Epoch(train) [14][2340/2569] lr: 4.0000e-02 eta: 1 day, 1:55:28 time: 0.2625 data_time: 0.0084 memory: 5828 grad_norm: 2.8088 loss: 2.6635 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6635 2023/06/04 18:57:57 - mmengine - INFO - Epoch(train) [14][2360/2569] lr: 4.0000e-02 eta: 1 day, 1:55:23 time: 0.2715 data_time: 0.0076 memory: 5828 grad_norm: 2.8000 loss: 2.4411 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4411 2023/06/04 18:58:02 - mmengine - INFO - Epoch(train) [14][2380/2569] lr: 4.0000e-02 eta: 1 day, 1:55:18 time: 0.2683 data_time: 0.0095 memory: 5828 grad_norm: 2.8822 loss: 2.4077 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.4077 2023/06/04 18:58:07 - mmengine - INFO - Epoch(train) [14][2400/2569] lr: 4.0000e-02 eta: 1 day, 1:55:13 time: 0.2667 data_time: 0.0078 memory: 5828 grad_norm: 2.8575 loss: 2.4038 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4038 2023/06/04 18:58:13 - mmengine - INFO - Epoch(train) [14][2420/2569] lr: 4.0000e-02 eta: 1 day, 1:55:07 time: 0.2662 data_time: 0.0076 memory: 5828 grad_norm: 2.8151 loss: 2.6250 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6250 2023/06/04 18:58:18 - mmengine - INFO - Epoch(train) [14][2440/2569] lr: 4.0000e-02 eta: 1 day, 1:55:01 time: 0.2639 data_time: 0.0077 memory: 5828 grad_norm: 2.8165 loss: 2.7557 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7557 2023/06/04 18:58:23 - mmengine - INFO - Epoch(train) [14][2460/2569] lr: 4.0000e-02 eta: 1 day, 1:54:55 time: 0.2608 data_time: 0.0079 memory: 5828 grad_norm: 2.8161 loss: 2.4746 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4746 2023/06/04 18:58:29 - mmengine - INFO - Epoch(train) [14][2480/2569] lr: 4.0000e-02 eta: 1 day, 1:54:51 time: 0.2752 data_time: 0.0077 memory: 5828 grad_norm: 2.8522 loss: 2.6362 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6362 2023/06/04 18:58:34 - mmengine - INFO - Epoch(train) [14][2500/2569] lr: 4.0000e-02 eta: 1 day, 1:54:45 time: 0.2663 data_time: 0.0077 memory: 5828 grad_norm: 2.8204 loss: 2.7697 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7697 2023/06/04 18:58:39 - mmengine - INFO - Epoch(train) [14][2520/2569] lr: 4.0000e-02 eta: 1 day, 1:54:41 time: 0.2695 data_time: 0.0077 memory: 5828 grad_norm: 2.8130 loss: 2.5567 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5567 2023/06/04 18:58:45 - mmengine - INFO - Epoch(train) [14][2540/2569] lr: 4.0000e-02 eta: 1 day, 1:54:37 time: 0.2738 data_time: 0.0081 memory: 5828 grad_norm: 2.8052 loss: 2.7328 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7328 2023/06/04 18:58:50 - mmengine - INFO - Epoch(train) [14][2560/2569] lr: 4.0000e-02 eta: 1 day, 1:54:29 time: 0.2576 data_time: 0.0078 memory: 5828 grad_norm: 2.8158 loss: 2.5020 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5020 2023/06/04 18:58:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:58:52 - mmengine - INFO - Epoch(train) [14][2569/2569] lr: 4.0000e-02 eta: 1 day, 1:54:25 time: 0.2486 data_time: 0.0074 memory: 5828 grad_norm: 2.8361 loss: 2.3805 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3805 2023/06/04 18:58:59 - mmengine - INFO - Epoch(train) [15][ 20/2569] lr: 4.0000e-02 eta: 1 day, 1:54:34 time: 0.3402 data_time: 0.0760 memory: 5828 grad_norm: 2.8034 loss: 2.2654 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2654 2023/06/04 18:59:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 18:59:04 - mmengine - INFO - Epoch(train) [15][ 40/2569] lr: 4.0000e-02 eta: 1 day, 1:54:28 time: 0.2637 data_time: 0.0078 memory: 5828 grad_norm: 2.8352 loss: 2.9350 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9350 2023/06/04 18:59:10 - mmengine - INFO - Epoch(train) [15][ 60/2569] lr: 4.0000e-02 eta: 1 day, 1:54:22 time: 0.2665 data_time: 0.0079 memory: 5828 grad_norm: 2.8109 loss: 2.6898 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6898 2023/06/04 18:59:15 - mmengine - INFO - Epoch(train) [15][ 80/2569] lr: 4.0000e-02 eta: 1 day, 1:54:16 time: 0.2622 data_time: 0.0077 memory: 5828 grad_norm: 2.8177 loss: 2.5628 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5628 2023/06/04 18:59:20 - mmengine - INFO - Epoch(train) [15][ 100/2569] lr: 4.0000e-02 eta: 1 day, 1:54:09 time: 0.2597 data_time: 0.0076 memory: 5828 grad_norm: 2.8378 loss: 2.7103 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7103 2023/06/04 18:59:25 - mmengine - INFO - Epoch(train) [15][ 120/2569] lr: 4.0000e-02 eta: 1 day, 1:54:04 time: 0.2678 data_time: 0.0078 memory: 5828 grad_norm: 2.8311 loss: 2.6042 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6042 2023/06/04 18:59:31 - mmengine - INFO - Epoch(train) [15][ 140/2569] lr: 4.0000e-02 eta: 1 day, 1:53:57 time: 0.2590 data_time: 0.0077 memory: 5828 grad_norm: 2.8118 loss: 2.7423 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7423 2023/06/04 18:59:36 - mmengine - INFO - Epoch(train) [15][ 160/2569] lr: 4.0000e-02 eta: 1 day, 1:53:53 time: 0.2713 data_time: 0.0084 memory: 5828 grad_norm: 2.8752 loss: 2.7415 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7415 2023/06/04 18:59:41 - mmengine - INFO - Epoch(train) [15][ 180/2569] lr: 4.0000e-02 eta: 1 day, 1:53:48 time: 0.2700 data_time: 0.0077 memory: 5828 grad_norm: 2.8057 loss: 2.4649 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4649 2023/06/04 18:59:47 - mmengine - INFO - Epoch(train) [15][ 200/2569] lr: 4.0000e-02 eta: 1 day, 1:53:43 time: 0.2657 data_time: 0.0080 memory: 5828 grad_norm: 2.8216 loss: 2.7514 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7514 2023/06/04 18:59:52 - mmengine - INFO - Epoch(train) [15][ 220/2569] lr: 4.0000e-02 eta: 1 day, 1:53:37 time: 0.2632 data_time: 0.0080 memory: 5828 grad_norm: 2.7984 loss: 2.4901 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4901 2023/06/04 18:59:57 - mmengine - INFO - Epoch(train) [15][ 240/2569] lr: 4.0000e-02 eta: 1 day, 1:53:31 time: 0.2669 data_time: 0.0075 memory: 5828 grad_norm: 2.8505 loss: 2.8408 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8408 2023/06/04 19:00:03 - mmengine - INFO - Epoch(train) [15][ 260/2569] lr: 4.0000e-02 eta: 1 day, 1:53:25 time: 0.2608 data_time: 0.0077 memory: 5828 grad_norm: 2.7993 loss: 2.6501 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6501 2023/06/04 19:00:08 - mmengine - INFO - Epoch(train) [15][ 280/2569] lr: 4.0000e-02 eta: 1 day, 1:53:19 time: 0.2680 data_time: 0.0078 memory: 5828 grad_norm: 2.8358 loss: 2.6120 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6120 2023/06/04 19:00:13 - mmengine - INFO - Epoch(train) [15][ 300/2569] lr: 4.0000e-02 eta: 1 day, 1:53:14 time: 0.2645 data_time: 0.0080 memory: 5828 grad_norm: 2.8195 loss: 2.8216 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.8216 2023/06/04 19:00:18 - mmengine - INFO - Epoch(train) [15][ 320/2569] lr: 4.0000e-02 eta: 1 day, 1:53:08 time: 0.2630 data_time: 0.0079 memory: 5828 grad_norm: 2.8359 loss: 2.8428 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8428 2023/06/04 19:00:24 - mmengine - INFO - Epoch(train) [15][ 340/2569] lr: 4.0000e-02 eta: 1 day, 1:53:02 time: 0.2662 data_time: 0.0077 memory: 5828 grad_norm: 2.7915 loss: 2.6537 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6537 2023/06/04 19:00:29 - mmengine - INFO - Epoch(train) [15][ 360/2569] lr: 4.0000e-02 eta: 1 day, 1:52:56 time: 0.2614 data_time: 0.0080 memory: 5828 grad_norm: 2.8577 loss: 2.6585 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6585 2023/06/04 19:00:34 - mmengine - INFO - Epoch(train) [15][ 380/2569] lr: 4.0000e-02 eta: 1 day, 1:52:49 time: 0.2609 data_time: 0.0079 memory: 5828 grad_norm: 2.8613 loss: 3.0255 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 3.0255 2023/06/04 19:00:40 - mmengine - INFO - Epoch(train) [15][ 400/2569] lr: 4.0000e-02 eta: 1 day, 1:52:43 time: 0.2653 data_time: 0.0076 memory: 5828 grad_norm: 2.8425 loss: 2.3198 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3198 2023/06/04 19:00:45 - mmengine - INFO - Epoch(train) [15][ 420/2569] lr: 4.0000e-02 eta: 1 day, 1:52:39 time: 0.2707 data_time: 0.0077 memory: 5828 grad_norm: 2.8052 loss: 2.4695 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4695 2023/06/04 19:00:50 - mmengine - INFO - Epoch(train) [15][ 440/2569] lr: 4.0000e-02 eta: 1 day, 1:52:32 time: 0.2604 data_time: 0.0075 memory: 5828 grad_norm: 2.7886 loss: 2.5143 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5143 2023/06/04 19:00:56 - mmengine - INFO - Epoch(train) [15][ 460/2569] lr: 4.0000e-02 eta: 1 day, 1:52:27 time: 0.2659 data_time: 0.0078 memory: 5828 grad_norm: 2.8118 loss: 2.8005 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8005 2023/06/04 19:01:01 - mmengine - INFO - Epoch(train) [15][ 480/2569] lr: 4.0000e-02 eta: 1 day, 1:52:20 time: 0.2616 data_time: 0.0080 memory: 5828 grad_norm: 2.7986 loss: 2.6166 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6166 2023/06/04 19:01:06 - mmengine - INFO - Epoch(train) [15][ 500/2569] lr: 4.0000e-02 eta: 1 day, 1:52:15 time: 0.2662 data_time: 0.0080 memory: 5828 grad_norm: 2.8320 loss: 2.3810 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3810 2023/06/04 19:01:11 - mmengine - INFO - Epoch(train) [15][ 520/2569] lr: 4.0000e-02 eta: 1 day, 1:52:08 time: 0.2593 data_time: 0.0079 memory: 5828 grad_norm: 2.7765 loss: 2.6507 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.6507 2023/06/04 19:01:17 - mmengine - INFO - Epoch(train) [15][ 540/2569] lr: 4.0000e-02 eta: 1 day, 1:52:04 time: 0.2712 data_time: 0.0086 memory: 5828 grad_norm: 2.8447 loss: 2.5659 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5659 2023/06/04 19:01:22 - mmengine - INFO - Epoch(train) [15][ 560/2569] lr: 4.0000e-02 eta: 1 day, 1:51:58 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 2.8599 loss: 2.5856 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5856 2023/06/04 19:01:27 - mmengine - INFO - Epoch(train) [15][ 580/2569] lr: 4.0000e-02 eta: 1 day, 1:51:54 time: 0.2732 data_time: 0.0079 memory: 5828 grad_norm: 2.7728 loss: 2.7556 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7556 2023/06/04 19:01:33 - mmengine - INFO - Epoch(train) [15][ 600/2569] lr: 4.0000e-02 eta: 1 day, 1:51:47 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 2.8115 loss: 2.6793 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6793 2023/06/04 19:01:38 - mmengine - INFO - Epoch(train) [15][ 620/2569] lr: 4.0000e-02 eta: 1 day, 1:51:41 time: 0.2621 data_time: 0.0080 memory: 5828 grad_norm: 2.8165 loss: 2.4485 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4485 2023/06/04 19:01:43 - mmengine - INFO - Epoch(train) [15][ 640/2569] lr: 4.0000e-02 eta: 1 day, 1:51:36 time: 0.2679 data_time: 0.0075 memory: 5828 grad_norm: 2.8619 loss: 2.6866 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6866 2023/06/04 19:01:49 - mmengine - INFO - Epoch(train) [15][ 660/2569] lr: 4.0000e-02 eta: 1 day, 1:51:32 time: 0.2769 data_time: 0.0078 memory: 5828 grad_norm: 2.8091 loss: 2.6773 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6773 2023/06/04 19:01:54 - mmengine - INFO - Epoch(train) [15][ 680/2569] lr: 4.0000e-02 eta: 1 day, 1:51:26 time: 0.2606 data_time: 0.0076 memory: 5828 grad_norm: 2.7793 loss: 2.5662 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5662 2023/06/04 19:02:00 - mmengine - INFO - Epoch(train) [15][ 700/2569] lr: 4.0000e-02 eta: 1 day, 1:51:22 time: 0.2729 data_time: 0.0077 memory: 5828 grad_norm: 2.8279 loss: 2.7277 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7277 2023/06/04 19:02:05 - mmengine - INFO - Epoch(train) [15][ 720/2569] lr: 4.0000e-02 eta: 1 day, 1:51:19 time: 0.2798 data_time: 0.0082 memory: 5828 grad_norm: 2.7609 loss: 2.4010 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4010 2023/06/04 19:02:10 - mmengine - INFO - Epoch(train) [15][ 740/2569] lr: 4.0000e-02 eta: 1 day, 1:51:13 time: 0.2661 data_time: 0.0077 memory: 5828 grad_norm: 2.8169 loss: 2.7803 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7803 2023/06/04 19:02:16 - mmengine - INFO - Epoch(train) [15][ 760/2569] lr: 4.0000e-02 eta: 1 day, 1:51:09 time: 0.2707 data_time: 0.0079 memory: 5828 grad_norm: 2.7663 loss: 2.8659 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8659 2023/06/04 19:02:21 - mmengine - INFO - Epoch(train) [15][ 780/2569] lr: 4.0000e-02 eta: 1 day, 1:51:03 time: 0.2662 data_time: 0.0080 memory: 5828 grad_norm: 2.8247 loss: 2.8194 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8194 2023/06/04 19:02:27 - mmengine - INFO - Epoch(train) [15][ 800/2569] lr: 4.0000e-02 eta: 1 day, 1:51:00 time: 0.2798 data_time: 0.0079 memory: 5828 grad_norm: 2.8519 loss: 2.6459 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6459 2023/06/04 19:02:32 - mmengine - INFO - Epoch(train) [15][ 820/2569] lr: 4.0000e-02 eta: 1 day, 1:50:55 time: 0.2656 data_time: 0.0079 memory: 5828 grad_norm: 2.8224 loss: 2.2091 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2091 2023/06/04 19:02:37 - mmengine - INFO - Epoch(train) [15][ 840/2569] lr: 4.0000e-02 eta: 1 day, 1:50:49 time: 0.2679 data_time: 0.0075 memory: 5828 grad_norm: 2.8396 loss: 2.5534 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5534 2023/06/04 19:02:43 - mmengine - INFO - Epoch(train) [15][ 860/2569] lr: 4.0000e-02 eta: 1 day, 1:50:43 time: 0.2598 data_time: 0.0076 memory: 5828 grad_norm: 2.8292 loss: 2.8033 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8033 2023/06/04 19:02:48 - mmengine - INFO - Epoch(train) [15][ 880/2569] lr: 4.0000e-02 eta: 1 day, 1:50:37 time: 0.2662 data_time: 0.0079 memory: 5828 grad_norm: 2.7899 loss: 2.4439 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4439 2023/06/04 19:02:53 - mmengine - INFO - Epoch(train) [15][ 900/2569] lr: 4.0000e-02 eta: 1 day, 1:50:31 time: 0.2610 data_time: 0.0076 memory: 5828 grad_norm: 2.7882 loss: 2.6015 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6015 2023/06/04 19:02:59 - mmengine - INFO - Epoch(train) [15][ 920/2569] lr: 4.0000e-02 eta: 1 day, 1:50:26 time: 0.2678 data_time: 0.0076 memory: 5828 grad_norm: 2.8201 loss: 2.5820 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5820 2023/06/04 19:03:04 - mmengine - INFO - Epoch(train) [15][ 940/2569] lr: 4.0000e-02 eta: 1 day, 1:50:20 time: 0.2653 data_time: 0.0081 memory: 5828 grad_norm: 2.8007 loss: 2.4972 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4972 2023/06/04 19:03:09 - mmengine - INFO - Epoch(train) [15][ 960/2569] lr: 4.0000e-02 eta: 1 day, 1:50:15 time: 0.2665 data_time: 0.0082 memory: 5828 grad_norm: 2.8426 loss: 2.6980 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6980 2023/06/04 19:03:14 - mmengine - INFO - Epoch(train) [15][ 980/2569] lr: 4.0000e-02 eta: 1 day, 1:50:08 time: 0.2618 data_time: 0.0081 memory: 5828 grad_norm: 2.8494 loss: 2.5109 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5109 2023/06/04 19:03:20 - mmengine - INFO - Epoch(train) [15][1000/2569] lr: 4.0000e-02 eta: 1 day, 1:50:04 time: 0.2753 data_time: 0.0074 memory: 5828 grad_norm: 2.8682 loss: 2.4381 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4381 2023/06/04 19:03:25 - mmengine - INFO - Epoch(train) [15][1020/2569] lr: 4.0000e-02 eta: 1 day, 1:49:58 time: 0.2596 data_time: 0.0081 memory: 5828 grad_norm: 2.8562 loss: 2.5983 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5983 2023/06/04 19:03:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:03:31 - mmengine - INFO - Epoch(train) [15][1040/2569] lr: 4.0000e-02 eta: 1 day, 1:49:56 time: 0.2844 data_time: 0.0072 memory: 5828 grad_norm: 2.8038 loss: 2.6869 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6869 2023/06/04 19:03:36 - mmengine - INFO - Epoch(train) [15][1060/2569] lr: 4.0000e-02 eta: 1 day, 1:49:50 time: 0.2668 data_time: 0.0078 memory: 5828 grad_norm: 2.7883 loss: 2.7275 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7275 2023/06/04 19:03:41 - mmengine - INFO - Epoch(train) [15][1080/2569] lr: 4.0000e-02 eta: 1 day, 1:49:45 time: 0.2665 data_time: 0.0081 memory: 5828 grad_norm: 2.8525 loss: 2.5522 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5522 2023/06/04 19:03:47 - mmengine - INFO - Epoch(train) [15][1100/2569] lr: 4.0000e-02 eta: 1 day, 1:49:39 time: 0.2637 data_time: 0.0078 memory: 5828 grad_norm: 2.8835 loss: 2.5297 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5297 2023/06/04 19:03:52 - mmengine - INFO - Epoch(train) [15][1120/2569] lr: 4.0000e-02 eta: 1 day, 1:49:32 time: 0.2608 data_time: 0.0079 memory: 5828 grad_norm: 2.8479 loss: 3.0829 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.0829 2023/06/04 19:03:57 - mmengine - INFO - Epoch(train) [15][1140/2569] lr: 4.0000e-02 eta: 1 day, 1:49:27 time: 0.2647 data_time: 0.0081 memory: 5828 grad_norm: 2.8242 loss: 2.4272 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4272 2023/06/04 19:04:03 - mmengine - INFO - Epoch(train) [15][1160/2569] lr: 4.0000e-02 eta: 1 day, 1:49:21 time: 0.2662 data_time: 0.0080 memory: 5828 grad_norm: 2.8285 loss: 2.7325 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7325 2023/06/04 19:04:08 - mmengine - INFO - Epoch(train) [15][1180/2569] lr: 4.0000e-02 eta: 1 day, 1:49:16 time: 0.2680 data_time: 0.0079 memory: 5828 grad_norm: 2.8661 loss: 2.3920 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3920 2023/06/04 19:04:13 - mmengine - INFO - Epoch(train) [15][1200/2569] lr: 4.0000e-02 eta: 1 day, 1:49:10 time: 0.2620 data_time: 0.0078 memory: 5828 grad_norm: 2.8303 loss: 2.6730 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6730 2023/06/04 19:04:18 - mmengine - INFO - Epoch(train) [15][1220/2569] lr: 4.0000e-02 eta: 1 day, 1:49:03 time: 0.2609 data_time: 0.0073 memory: 5828 grad_norm: 2.8470 loss: 2.8170 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8170 2023/06/04 19:04:24 - mmengine - INFO - Epoch(train) [15][1240/2569] lr: 4.0000e-02 eta: 1 day, 1:48:57 time: 0.2613 data_time: 0.0073 memory: 5828 grad_norm: 2.8546 loss: 2.5120 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5120 2023/06/04 19:04:29 - mmengine - INFO - Epoch(train) [15][1260/2569] lr: 4.0000e-02 eta: 1 day, 1:48:52 time: 0.2675 data_time: 0.0079 memory: 5828 grad_norm: 2.8952 loss: 2.3950 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3950 2023/06/04 19:04:34 - mmengine - INFO - Epoch(train) [15][1280/2569] lr: 4.0000e-02 eta: 1 day, 1:48:47 time: 0.2681 data_time: 0.0076 memory: 5828 grad_norm: 2.8350 loss: 2.8173 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8173 2023/06/04 19:04:40 - mmengine - INFO - Epoch(train) [15][1300/2569] lr: 4.0000e-02 eta: 1 day, 1:48:40 time: 0.2607 data_time: 0.0080 memory: 5828 grad_norm: 2.8363 loss: 2.4117 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4117 2023/06/04 19:04:45 - mmengine - INFO - Epoch(train) [15][1320/2569] lr: 4.0000e-02 eta: 1 day, 1:48:35 time: 0.2672 data_time: 0.0078 memory: 5828 grad_norm: 2.8530 loss: 3.0159 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0159 2023/06/04 19:04:50 - mmengine - INFO - Epoch(train) [15][1340/2569] lr: 4.0000e-02 eta: 1 day, 1:48:29 time: 0.2651 data_time: 0.0079 memory: 5828 grad_norm: 2.7909 loss: 2.4176 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4176 2023/06/04 19:04:56 - mmengine - INFO - Epoch(train) [15][1360/2569] lr: 4.0000e-02 eta: 1 day, 1:48:24 time: 0.2675 data_time: 0.0076 memory: 5828 grad_norm: 2.7945 loss: 3.0386 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0386 2023/06/04 19:05:01 - mmengine - INFO - Epoch(train) [15][1380/2569] lr: 4.0000e-02 eta: 1 day, 1:48:21 time: 0.2798 data_time: 0.0079 memory: 5828 grad_norm: 2.8592 loss: 2.6373 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6373 2023/06/04 19:05:06 - mmengine - INFO - Epoch(train) [15][1400/2569] lr: 4.0000e-02 eta: 1 day, 1:48:14 time: 0.2595 data_time: 0.0076 memory: 5828 grad_norm: 2.8516 loss: 2.5483 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5483 2023/06/04 19:05:12 - mmengine - INFO - Epoch(train) [15][1420/2569] lr: 4.0000e-02 eta: 1 day, 1:48:08 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 2.8742 loss: 2.2336 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2336 2023/06/04 19:05:17 - mmengine - INFO - Epoch(train) [15][1440/2569] lr: 4.0000e-02 eta: 1 day, 1:48:02 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 2.7940 loss: 2.3589 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3589 2023/06/04 19:05:22 - mmengine - INFO - Epoch(train) [15][1460/2569] lr: 4.0000e-02 eta: 1 day, 1:47:58 time: 0.2731 data_time: 0.0081 memory: 5828 grad_norm: 2.8702 loss: 2.8239 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8239 2023/06/04 19:05:28 - mmengine - INFO - Epoch(train) [15][1480/2569] lr: 4.0000e-02 eta: 1 day, 1:47:52 time: 0.2639 data_time: 0.0080 memory: 5828 grad_norm: 2.8353 loss: 2.5351 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5351 2023/06/04 19:05:33 - mmengine - INFO - Epoch(train) [15][1500/2569] lr: 4.0000e-02 eta: 1 day, 1:47:46 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 2.8107 loss: 2.3950 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3950 2023/06/04 19:05:38 - mmengine - INFO - Epoch(train) [15][1520/2569] lr: 4.0000e-02 eta: 1 day, 1:47:41 time: 0.2705 data_time: 0.0077 memory: 5828 grad_norm: 2.8590 loss: 2.7074 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7074 2023/06/04 19:05:44 - mmengine - INFO - Epoch(train) [15][1540/2569] lr: 4.0000e-02 eta: 1 day, 1:47:35 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 2.8951 loss: 2.6469 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6469 2023/06/04 19:05:49 - mmengine - INFO - Epoch(train) [15][1560/2569] lr: 4.0000e-02 eta: 1 day, 1:47:31 time: 0.2728 data_time: 0.0074 memory: 5828 grad_norm: 2.8474 loss: 2.7347 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7347 2023/06/04 19:05:54 - mmengine - INFO - Epoch(train) [15][1580/2569] lr: 4.0000e-02 eta: 1 day, 1:47:25 time: 0.2662 data_time: 0.0076 memory: 5828 grad_norm: 2.8296 loss: 2.6248 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6248 2023/06/04 19:06:00 - mmengine - INFO - Epoch(train) [15][1600/2569] lr: 4.0000e-02 eta: 1 day, 1:47:22 time: 0.2759 data_time: 0.0077 memory: 5828 grad_norm: 2.7751 loss: 2.7052 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.7052 2023/06/04 19:06:05 - mmengine - INFO - Epoch(train) [15][1620/2569] lr: 4.0000e-02 eta: 1 day, 1:47:15 time: 0.2591 data_time: 0.0081 memory: 5828 grad_norm: 2.8018 loss: 2.3930 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3930 2023/06/04 19:06:10 - mmengine - INFO - Epoch(train) [15][1640/2569] lr: 4.0000e-02 eta: 1 day, 1:47:09 time: 0.2661 data_time: 0.0074 memory: 5828 grad_norm: 2.8210 loss: 2.2102 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2102 2023/06/04 19:06:16 - mmengine - INFO - Epoch(train) [15][1660/2569] lr: 4.0000e-02 eta: 1 day, 1:47:04 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 2.7877 loss: 3.2791 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.2791 2023/06/04 19:06:21 - mmengine - INFO - Epoch(train) [15][1680/2569] lr: 4.0000e-02 eta: 1 day, 1:46:59 time: 0.2702 data_time: 0.0082 memory: 5828 grad_norm: 2.8385 loss: 2.5691 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5691 2023/06/04 19:06:27 - mmengine - INFO - Epoch(train) [15][1700/2569] lr: 4.0000e-02 eta: 1 day, 1:46:54 time: 0.2704 data_time: 0.0073 memory: 5828 grad_norm: 2.7967 loss: 2.7272 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7272 2023/06/04 19:06:32 - mmengine - INFO - Epoch(train) [15][1720/2569] lr: 4.0000e-02 eta: 1 day, 1:46:51 time: 0.2775 data_time: 0.0077 memory: 5828 grad_norm: 2.8009 loss: 2.6611 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6611 2023/06/04 19:06:37 - mmengine - INFO - Epoch(train) [15][1740/2569] lr: 4.0000e-02 eta: 1 day, 1:46:46 time: 0.2706 data_time: 0.0075 memory: 5828 grad_norm: 2.7773 loss: 2.4243 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4243 2023/06/04 19:06:43 - mmengine - INFO - Epoch(train) [15][1760/2569] lr: 4.0000e-02 eta: 1 day, 1:46:43 time: 0.2786 data_time: 0.0078 memory: 5828 grad_norm: 2.7922 loss: 2.6758 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6758 2023/06/04 19:06:48 - mmengine - INFO - Epoch(train) [15][1780/2569] lr: 4.0000e-02 eta: 1 day, 1:46:38 time: 0.2703 data_time: 0.0079 memory: 5828 grad_norm: 2.8674 loss: 2.5940 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5940 2023/06/04 19:06:54 - mmengine - INFO - Epoch(train) [15][1800/2569] lr: 4.0000e-02 eta: 1 day, 1:46:33 time: 0.2658 data_time: 0.0080 memory: 5828 grad_norm: 2.8963 loss: 2.9246 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.9246 2023/06/04 19:06:59 - mmengine - INFO - Epoch(train) [15][1820/2569] lr: 4.0000e-02 eta: 1 day, 1:46:28 time: 0.2706 data_time: 0.0074 memory: 5828 grad_norm: 2.8217 loss: 2.5582 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5582 2023/06/04 19:07:05 - mmengine - INFO - Epoch(train) [15][1840/2569] lr: 4.0000e-02 eta: 1 day, 1:46:24 time: 0.2735 data_time: 0.0079 memory: 5828 grad_norm: 2.7798 loss: 2.6438 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6438 2023/06/04 19:07:10 - mmengine - INFO - Epoch(train) [15][1860/2569] lr: 4.0000e-02 eta: 1 day, 1:46:20 time: 0.2755 data_time: 0.0079 memory: 5828 grad_norm: 2.8171 loss: 2.3757 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3757 2023/06/04 19:07:16 - mmengine - INFO - Epoch(train) [15][1880/2569] lr: 4.0000e-02 eta: 1 day, 1:46:16 time: 0.2756 data_time: 0.0077 memory: 5828 grad_norm: 2.8364 loss: 2.5081 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5081 2023/06/04 19:07:21 - mmengine - INFO - Epoch(train) [15][1900/2569] lr: 4.0000e-02 eta: 1 day, 1:46:12 time: 0.2702 data_time: 0.0084 memory: 5828 grad_norm: 2.7430 loss: 2.5105 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5105 2023/06/04 19:07:26 - mmengine - INFO - Epoch(train) [15][1920/2569] lr: 4.0000e-02 eta: 1 day, 1:46:06 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 2.8128 loss: 2.2764 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2764 2023/06/04 19:07:32 - mmengine - INFO - Epoch(train) [15][1940/2569] lr: 4.0000e-02 eta: 1 day, 1:46:00 time: 0.2647 data_time: 0.0080 memory: 5828 grad_norm: 2.8504 loss: 2.6042 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6042 2023/06/04 19:07:37 - mmengine - INFO - Epoch(train) [15][1960/2569] lr: 4.0000e-02 eta: 1 day, 1:45:53 time: 0.2604 data_time: 0.0076 memory: 5828 grad_norm: 2.7733 loss: 2.1809 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1809 2023/06/04 19:07:42 - mmengine - INFO - Epoch(train) [15][1980/2569] lr: 4.0000e-02 eta: 1 day, 1:45:47 time: 0.2587 data_time: 0.0082 memory: 5828 grad_norm: 2.8209 loss: 2.4582 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4582 2023/06/04 19:07:47 - mmengine - INFO - Epoch(train) [15][2000/2569] lr: 4.0000e-02 eta: 1 day, 1:45:41 time: 0.2647 data_time: 0.0077 memory: 5828 grad_norm: 2.8127 loss: 2.3946 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3946 2023/06/04 19:07:53 - mmengine - INFO - Epoch(train) [15][2020/2569] lr: 4.0000e-02 eta: 1 day, 1:45:35 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 2.8728 loss: 2.8533 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8533 2023/06/04 19:07:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:07:58 - mmengine - INFO - Epoch(train) [15][2040/2569] lr: 4.0000e-02 eta: 1 day, 1:45:29 time: 0.2623 data_time: 0.0079 memory: 5828 grad_norm: 2.8334 loss: 2.9284 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9284 2023/06/04 19:08:03 - mmengine - INFO - Epoch(train) [15][2060/2569] lr: 4.0000e-02 eta: 1 day, 1:45:23 time: 0.2613 data_time: 0.0075 memory: 5828 grad_norm: 2.8198 loss: 2.5504 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5504 2023/06/04 19:08:08 - mmengine - INFO - Epoch(train) [15][2080/2569] lr: 4.0000e-02 eta: 1 day, 1:45:17 time: 0.2659 data_time: 0.0070 memory: 5828 grad_norm: 2.8856 loss: 2.9962 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.9962 2023/06/04 19:08:14 - mmengine - INFO - Epoch(train) [15][2100/2569] lr: 4.0000e-02 eta: 1 day, 1:45:11 time: 0.2652 data_time: 0.0080 memory: 5828 grad_norm: 2.8246 loss: 2.7034 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7034 2023/06/04 19:08:19 - mmengine - INFO - Epoch(train) [15][2120/2569] lr: 4.0000e-02 eta: 1 day, 1:45:07 time: 0.2705 data_time: 0.0077 memory: 5828 grad_norm: 2.7984 loss: 2.2329 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2329 2023/06/04 19:08:25 - mmengine - INFO - Epoch(train) [15][2140/2569] lr: 4.0000e-02 eta: 1 day, 1:45:02 time: 0.2703 data_time: 0.0075 memory: 5828 grad_norm: 2.8212 loss: 2.3117 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3117 2023/06/04 19:08:30 - mmengine - INFO - Epoch(train) [15][2160/2569] lr: 4.0000e-02 eta: 1 day, 1:44:56 time: 0.2657 data_time: 0.0079 memory: 5828 grad_norm: 2.7850 loss: 2.5085 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5085 2023/06/04 19:08:35 - mmengine - INFO - Epoch(train) [15][2180/2569] lr: 4.0000e-02 eta: 1 day, 1:44:51 time: 0.2671 data_time: 0.0076 memory: 5828 grad_norm: 2.7968 loss: 2.8703 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8703 2023/06/04 19:08:41 - mmengine - INFO - Epoch(train) [15][2200/2569] lr: 4.0000e-02 eta: 1 day, 1:44:47 time: 0.2721 data_time: 0.0076 memory: 5828 grad_norm: 2.7996 loss: 2.6212 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6212 2023/06/04 19:08:46 - mmengine - INFO - Epoch(train) [15][2220/2569] lr: 4.0000e-02 eta: 1 day, 1:44:41 time: 0.2637 data_time: 0.0078 memory: 5828 grad_norm: 2.8293 loss: 2.6104 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6104 2023/06/04 19:08:51 - mmengine - INFO - Epoch(train) [15][2240/2569] lr: 4.0000e-02 eta: 1 day, 1:44:36 time: 0.2701 data_time: 0.0079 memory: 5828 grad_norm: 2.7715 loss: 2.5092 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5092 2023/06/04 19:08:57 - mmengine - INFO - Epoch(train) [15][2260/2569] lr: 4.0000e-02 eta: 1 day, 1:44:31 time: 0.2712 data_time: 0.0081 memory: 5828 grad_norm: 2.8532 loss: 2.6249 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6249 2023/06/04 19:09:02 - mmengine - INFO - Epoch(train) [15][2280/2569] lr: 4.0000e-02 eta: 1 day, 1:44:25 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 2.8006 loss: 2.5040 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5040 2023/06/04 19:09:07 - mmengine - INFO - Epoch(train) [15][2300/2569] lr: 4.0000e-02 eta: 1 day, 1:44:19 time: 0.2599 data_time: 0.0084 memory: 5828 grad_norm: 2.7953 loss: 2.1345 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1345 2023/06/04 19:09:13 - mmengine - INFO - Epoch(train) [15][2320/2569] lr: 4.0000e-02 eta: 1 day, 1:44:15 time: 0.2757 data_time: 0.0075 memory: 5828 grad_norm: 2.8223 loss: 2.7121 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7121 2023/06/04 19:09:18 - mmengine - INFO - Epoch(train) [15][2340/2569] lr: 4.0000e-02 eta: 1 day, 1:44:10 time: 0.2726 data_time: 0.0082 memory: 5828 grad_norm: 2.7899 loss: 2.9724 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9724 2023/06/04 19:09:24 - mmengine - INFO - Epoch(train) [15][2360/2569] lr: 4.0000e-02 eta: 1 day, 1:44:05 time: 0.2661 data_time: 0.0074 memory: 5828 grad_norm: 2.7523 loss: 2.5654 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5654 2023/06/04 19:09:29 - mmengine - INFO - Epoch(train) [15][2380/2569] lr: 4.0000e-02 eta: 1 day, 1:44:00 time: 0.2695 data_time: 0.0081 memory: 5828 grad_norm: 2.8578 loss: 2.6813 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6813 2023/06/04 19:09:34 - mmengine - INFO - Epoch(train) [15][2400/2569] lr: 4.0000e-02 eta: 1 day, 1:43:54 time: 0.2614 data_time: 0.0079 memory: 5828 grad_norm: 2.7812 loss: 2.3869 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3869 2023/06/04 19:09:39 - mmengine - INFO - Epoch(train) [15][2420/2569] lr: 4.0000e-02 eta: 1 day, 1:43:48 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 2.8323 loss: 2.5565 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5565 2023/06/04 19:09:45 - mmengine - INFO - Epoch(train) [15][2440/2569] lr: 4.0000e-02 eta: 1 day, 1:43:43 time: 0.2658 data_time: 0.0081 memory: 5828 grad_norm: 2.8073 loss: 2.7285 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7285 2023/06/04 19:09:50 - mmengine - INFO - Epoch(train) [15][2460/2569] lr: 4.0000e-02 eta: 1 day, 1:43:38 time: 0.2695 data_time: 0.0075 memory: 5828 grad_norm: 2.8093 loss: 2.7494 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7494 2023/06/04 19:09:56 - mmengine - INFO - Epoch(train) [15][2480/2569] lr: 4.0000e-02 eta: 1 day, 1:43:33 time: 0.2669 data_time: 0.0079 memory: 5828 grad_norm: 2.7829 loss: 2.4211 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4211 2023/06/04 19:10:01 - mmengine - INFO - Epoch(train) [15][2500/2569] lr: 4.0000e-02 eta: 1 day, 1:43:29 time: 0.2772 data_time: 0.0082 memory: 5828 grad_norm: 2.8048 loss: 2.7354 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7354 2023/06/04 19:10:06 - mmengine - INFO - Epoch(train) [15][2520/2569] lr: 4.0000e-02 eta: 1 day, 1:43:24 time: 0.2707 data_time: 0.0078 memory: 5828 grad_norm: 2.8914 loss: 2.6719 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6719 2023/06/04 19:10:12 - mmengine - INFO - Epoch(train) [15][2540/2569] lr: 4.0000e-02 eta: 1 day, 1:43:20 time: 0.2743 data_time: 0.0078 memory: 5828 grad_norm: 2.8817 loss: 2.5869 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5869 2023/06/04 19:10:17 - mmengine - INFO - Epoch(train) [15][2560/2569] lr: 4.0000e-02 eta: 1 day, 1:43:13 time: 0.2572 data_time: 0.0076 memory: 5828 grad_norm: 2.8488 loss: 2.3084 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3084 2023/06/04 19:10:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:10:19 - mmengine - INFO - Epoch(train) [15][2569/2569] lr: 4.0000e-02 eta: 1 day, 1:43:10 time: 0.2572 data_time: 0.0074 memory: 5828 grad_norm: 2.8000 loss: 2.2823 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.2823 2023/06/04 19:10:23 - mmengine - INFO - Epoch(val) [15][ 20/260] eta: 0:00:43 time: 0.1831 data_time: 0.1244 memory: 1238 2023/06/04 19:10:26 - mmengine - INFO - Epoch(val) [15][ 40/260] eta: 0:00:35 time: 0.1440 data_time: 0.0851 memory: 1238 2023/06/04 19:10:30 - mmengine - INFO - Epoch(val) [15][ 60/260] eta: 0:00:33 time: 0.1748 data_time: 0.1164 memory: 1238 2023/06/04 19:10:32 - mmengine - INFO - Epoch(val) [15][ 80/260] eta: 0:00:28 time: 0.1306 data_time: 0.0717 memory: 1238 2023/06/04 19:10:35 - mmengine - INFO - Epoch(val) [15][100/260] eta: 0:00:25 time: 0.1553 data_time: 0.0966 memory: 1238 2023/06/04 19:10:38 - mmengine - INFO - Epoch(val) [15][120/260] eta: 0:00:21 time: 0.1276 data_time: 0.0691 memory: 1238 2023/06/04 19:10:40 - mmengine - INFO - Epoch(val) [15][140/260] eta: 0:00:17 time: 0.1273 data_time: 0.0689 memory: 1238 2023/06/04 19:10:44 - mmengine - INFO - Epoch(val) [15][160/260] eta: 0:00:15 time: 0.1585 data_time: 0.0993 memory: 1238 2023/06/04 19:10:46 - mmengine - INFO - Epoch(val) [15][180/260] eta: 0:00:11 time: 0.1359 data_time: 0.0772 memory: 1238 2023/06/04 19:10:49 - mmengine - INFO - Epoch(val) [15][200/260] eta: 0:00:08 time: 0.1491 data_time: 0.0903 memory: 1238 2023/06/04 19:10:52 - mmengine - INFO - Epoch(val) [15][220/260] eta: 0:00:05 time: 0.1482 data_time: 0.0902 memory: 1238 2023/06/04 19:10:55 - mmengine - INFO - Epoch(val) [15][240/260] eta: 0:00:02 time: 0.1357 data_time: 0.0776 memory: 1238 2023/06/04 19:10:58 - mmengine - INFO - Epoch(val) [15][260/260] eta: 0:00:00 time: 0.1317 data_time: 0.0756 memory: 1238 2023/06/04 19:11:05 - mmengine - INFO - Epoch(val) [15][260/260] acc/top1: 0.4817 acc/top5: 0.7325 acc/mean1: 0.4722 data_time: 0.0875 time: 0.1459 2023/06/04 19:11:05 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_10.pth is removed 2023/06/04 19:11:07 - mmengine - INFO - The best checkpoint with 0.4817 acc/top1 at 15 epoch is saved to best_acc_top1_epoch_15.pth. 2023/06/04 19:11:13 - mmengine - INFO - Epoch(train) [16][ 20/2569] lr: 4.0000e-02 eta: 1 day, 1:43:10 time: 0.2974 data_time: 0.0467 memory: 5828 grad_norm: 2.7817 loss: 2.4469 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4469 2023/06/04 19:11:18 - mmengine - INFO - Epoch(train) [16][ 40/2569] lr: 4.0000e-02 eta: 1 day, 1:43:04 time: 0.2622 data_time: 0.0067 memory: 5828 grad_norm: 2.7843 loss: 2.4876 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4876 2023/06/04 19:11:23 - mmengine - INFO - Epoch(train) [16][ 60/2569] lr: 4.0000e-02 eta: 1 day, 1:42:58 time: 0.2636 data_time: 0.0081 memory: 5828 grad_norm: 2.7736 loss: 2.6604 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6604 2023/06/04 19:11:29 - mmengine - INFO - Epoch(train) [16][ 80/2569] lr: 4.0000e-02 eta: 1 day, 1:42:54 time: 0.2703 data_time: 0.0074 memory: 5828 grad_norm: 2.7900 loss: 2.8411 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8411 2023/06/04 19:11:34 - mmengine - INFO - Epoch(train) [16][ 100/2569] lr: 4.0000e-02 eta: 1 day, 1:42:50 time: 0.2767 data_time: 0.0081 memory: 5828 grad_norm: 2.8172 loss: 2.4470 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4470 2023/06/04 19:11:39 - mmengine - INFO - Epoch(train) [16][ 120/2569] lr: 4.0000e-02 eta: 1 day, 1:42:44 time: 0.2627 data_time: 0.0080 memory: 5828 grad_norm: 2.8186 loss: 2.5354 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5354 2023/06/04 19:11:45 - mmengine - INFO - Epoch(train) [16][ 140/2569] lr: 4.0000e-02 eta: 1 day, 1:42:38 time: 0.2614 data_time: 0.0077 memory: 5828 grad_norm: 2.8450 loss: 2.7546 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7546 2023/06/04 19:11:50 - mmengine - INFO - Epoch(train) [16][ 160/2569] lr: 4.0000e-02 eta: 1 day, 1:42:33 time: 0.2710 data_time: 0.0079 memory: 5828 grad_norm: 2.8213 loss: 2.4436 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4436 2023/06/04 19:11:55 - mmengine - INFO - Epoch(train) [16][ 180/2569] lr: 4.0000e-02 eta: 1 day, 1:42:27 time: 0.2652 data_time: 0.0080 memory: 5828 grad_norm: 2.9294 loss: 2.5538 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5538 2023/06/04 19:12:01 - mmengine - INFO - Epoch(train) [16][ 200/2569] lr: 4.0000e-02 eta: 1 day, 1:42:21 time: 0.2601 data_time: 0.0076 memory: 5828 grad_norm: 2.8292 loss: 2.6627 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6627 2023/06/04 19:12:06 - mmengine - INFO - Epoch(train) [16][ 220/2569] lr: 4.0000e-02 eta: 1 day, 1:42:16 time: 0.2708 data_time: 0.0077 memory: 5828 grad_norm: 2.7911 loss: 2.7648 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7648 2023/06/04 19:12:11 - mmengine - INFO - Epoch(train) [16][ 240/2569] lr: 4.0000e-02 eta: 1 day, 1:42:10 time: 0.2614 data_time: 0.0077 memory: 5828 grad_norm: 2.8747 loss: 2.3696 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3696 2023/06/04 19:12:17 - mmengine - INFO - Epoch(train) [16][ 260/2569] lr: 4.0000e-02 eta: 1 day, 1:42:05 time: 0.2701 data_time: 0.0078 memory: 5828 grad_norm: 2.8540 loss: 2.6321 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6321 2023/06/04 19:12:22 - mmengine - INFO - Epoch(train) [16][ 280/2569] lr: 4.0000e-02 eta: 1 day, 1:42:00 time: 0.2680 data_time: 0.0082 memory: 5828 grad_norm: 2.8646 loss: 2.8622 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8622 2023/06/04 19:12:27 - mmengine - INFO - Epoch(train) [16][ 300/2569] lr: 4.0000e-02 eta: 1 day, 1:41:54 time: 0.2672 data_time: 0.0078 memory: 5828 grad_norm: 2.8549 loss: 2.7543 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7543 2023/06/04 19:12:33 - mmengine - INFO - Epoch(train) [16][ 320/2569] lr: 4.0000e-02 eta: 1 day, 1:41:49 time: 0.2677 data_time: 0.0084 memory: 5828 grad_norm: 2.7752 loss: 2.6341 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6341 2023/06/04 19:12:38 - mmengine - INFO - Epoch(train) [16][ 340/2569] lr: 4.0000e-02 eta: 1 day, 1:41:44 time: 0.2659 data_time: 0.0083 memory: 5828 grad_norm: 2.8103 loss: 2.3339 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3339 2023/06/04 19:12:43 - mmengine - INFO - Epoch(train) [16][ 360/2569] lr: 4.0000e-02 eta: 1 day, 1:41:38 time: 0.2670 data_time: 0.0077 memory: 5828 grad_norm: 2.8304 loss: 2.5396 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5396 2023/06/04 19:12:49 - mmengine - INFO - Epoch(train) [16][ 380/2569] lr: 4.0000e-02 eta: 1 day, 1:41:33 time: 0.2686 data_time: 0.0078 memory: 5828 grad_norm: 2.8559 loss: 2.4786 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4786 2023/06/04 19:12:54 - mmengine - INFO - Epoch(train) [16][ 400/2569] lr: 4.0000e-02 eta: 1 day, 1:41:28 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 2.8562 loss: 2.6642 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6642 2023/06/04 19:13:00 - mmengine - INFO - Epoch(train) [16][ 420/2569] lr: 4.0000e-02 eta: 1 day, 1:41:23 time: 0.2662 data_time: 0.0077 memory: 5828 grad_norm: 2.8730 loss: 2.6198 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6198 2023/06/04 19:13:05 - mmengine - INFO - Epoch(train) [16][ 440/2569] lr: 4.0000e-02 eta: 1 day, 1:41:17 time: 0.2647 data_time: 0.0077 memory: 5828 grad_norm: 2.7903 loss: 2.8418 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8418 2023/06/04 19:13:10 - mmengine - INFO - Epoch(train) [16][ 460/2569] lr: 4.0000e-02 eta: 1 day, 1:41:12 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 2.8901 loss: 2.7066 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7066 2023/06/04 19:13:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:13:16 - mmengine - INFO - Epoch(train) [16][ 480/2569] lr: 4.0000e-02 eta: 1 day, 1:41:07 time: 0.2710 data_time: 0.0076 memory: 5828 grad_norm: 2.8956 loss: 2.5492 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5492 2023/06/04 19:13:21 - mmengine - INFO - Epoch(train) [16][ 500/2569] lr: 4.0000e-02 eta: 1 day, 1:41:02 time: 0.2683 data_time: 0.0077 memory: 5828 grad_norm: 2.8427 loss: 2.3552 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3552 2023/06/04 19:13:26 - mmengine - INFO - Epoch(train) [16][ 520/2569] lr: 4.0000e-02 eta: 1 day, 1:40:57 time: 0.2704 data_time: 0.0080 memory: 5828 grad_norm: 2.8210 loss: 2.5552 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5552 2023/06/04 19:13:32 - mmengine - INFO - Epoch(train) [16][ 540/2569] lr: 4.0000e-02 eta: 1 day, 1:40:52 time: 0.2658 data_time: 0.0075 memory: 5828 grad_norm: 2.8856 loss: 2.4261 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4261 2023/06/04 19:13:37 - mmengine - INFO - Epoch(train) [16][ 560/2569] lr: 4.0000e-02 eta: 1 day, 1:40:48 time: 0.2757 data_time: 0.0081 memory: 5828 grad_norm: 2.8250 loss: 2.5472 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5472 2023/06/04 19:13:42 - mmengine - INFO - Epoch(train) [16][ 580/2569] lr: 4.0000e-02 eta: 1 day, 1:40:42 time: 0.2622 data_time: 0.0081 memory: 5828 grad_norm: 2.7933 loss: 2.3617 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3617 2023/06/04 19:13:48 - mmengine - INFO - Epoch(train) [16][ 600/2569] lr: 4.0000e-02 eta: 1 day, 1:40:35 time: 0.2596 data_time: 0.0078 memory: 5828 grad_norm: 2.8327 loss: 2.6652 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.6652 2023/06/04 19:13:53 - mmengine - INFO - Epoch(train) [16][ 620/2569] lr: 4.0000e-02 eta: 1 day, 1:40:29 time: 0.2619 data_time: 0.0079 memory: 5828 grad_norm: 2.8439 loss: 2.8189 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8189 2023/06/04 19:13:58 - mmengine - INFO - Epoch(train) [16][ 640/2569] lr: 4.0000e-02 eta: 1 day, 1:40:24 time: 0.2663 data_time: 0.0078 memory: 5828 grad_norm: 2.8208 loss: 2.4368 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4368 2023/06/04 19:14:03 - mmengine - INFO - Epoch(train) [16][ 660/2569] lr: 4.0000e-02 eta: 1 day, 1:40:17 time: 0.2609 data_time: 0.0079 memory: 5828 grad_norm: 2.8172 loss: 2.5500 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5500 2023/06/04 19:14:09 - mmengine - INFO - Epoch(train) [16][ 680/2569] lr: 4.0000e-02 eta: 1 day, 1:40:10 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 2.8284 loss: 2.6274 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6274 2023/06/04 19:14:14 - mmengine - INFO - Epoch(train) [16][ 700/2569] lr: 4.0000e-02 eta: 1 day, 1:40:05 time: 0.2662 data_time: 0.0077 memory: 5828 grad_norm: 2.8667 loss: 2.6740 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6740 2023/06/04 19:14:19 - mmengine - INFO - Epoch(train) [16][ 720/2569] lr: 4.0000e-02 eta: 1 day, 1:40:01 time: 0.2742 data_time: 0.0076 memory: 5828 grad_norm: 2.8127 loss: 2.9029 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.9029 2023/06/04 19:14:25 - mmengine - INFO - Epoch(train) [16][ 740/2569] lr: 4.0000e-02 eta: 1 day, 1:39:56 time: 0.2706 data_time: 0.0078 memory: 5828 grad_norm: 2.8435 loss: 2.7189 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7189 2023/06/04 19:14:30 - mmengine - INFO - Epoch(train) [16][ 760/2569] lr: 4.0000e-02 eta: 1 day, 1:39:50 time: 0.2605 data_time: 0.0081 memory: 5828 grad_norm: 2.8448 loss: 2.8449 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8449 2023/06/04 19:14:36 - mmengine - INFO - Epoch(train) [16][ 780/2569] lr: 4.0000e-02 eta: 1 day, 1:39:47 time: 0.2804 data_time: 0.0076 memory: 5828 grad_norm: 2.8269 loss: 2.3643 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3643 2023/06/04 19:14:41 - mmengine - INFO - Epoch(train) [16][ 800/2569] lr: 4.0000e-02 eta: 1 day, 1:39:42 time: 0.2694 data_time: 0.0078 memory: 5828 grad_norm: 2.8162 loss: 2.6046 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6046 2023/06/04 19:14:47 - mmengine - INFO - Epoch(train) [16][ 820/2569] lr: 4.0000e-02 eta: 1 day, 1:39:40 time: 0.2856 data_time: 0.0077 memory: 5828 grad_norm: 2.8005 loss: 2.7482 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7482 2023/06/04 19:14:52 - mmengine - INFO - Epoch(train) [16][ 840/2569] lr: 4.0000e-02 eta: 1 day, 1:39:34 time: 0.2646 data_time: 0.0077 memory: 5828 grad_norm: 2.7955 loss: 2.3604 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3604 2023/06/04 19:14:57 - mmengine - INFO - Epoch(train) [16][ 860/2569] lr: 4.0000e-02 eta: 1 day, 1:39:28 time: 0.2627 data_time: 0.0080 memory: 5828 grad_norm: 2.8241 loss: 2.3079 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3079 2023/06/04 19:15:03 - mmengine - INFO - Epoch(train) [16][ 880/2569] lr: 4.0000e-02 eta: 1 day, 1:39:23 time: 0.2694 data_time: 0.0077 memory: 5828 grad_norm: 2.8721 loss: 2.7850 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7850 2023/06/04 19:15:08 - mmengine - INFO - Epoch(train) [16][ 900/2569] lr: 4.0000e-02 eta: 1 day, 1:39:19 time: 0.2722 data_time: 0.0074 memory: 5828 grad_norm: 2.7927 loss: 2.5172 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5172 2023/06/04 19:15:14 - mmengine - INFO - Epoch(train) [16][ 920/2569] lr: 4.0000e-02 eta: 1 day, 1:39:14 time: 0.2713 data_time: 0.0078 memory: 5828 grad_norm: 2.7903 loss: 2.7516 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7516 2023/06/04 19:15:19 - mmengine - INFO - Epoch(train) [16][ 940/2569] lr: 4.0000e-02 eta: 1 day, 1:39:09 time: 0.2680 data_time: 0.0080 memory: 5828 grad_norm: 2.8778 loss: 2.5463 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5463 2023/06/04 19:15:24 - mmengine - INFO - Epoch(train) [16][ 960/2569] lr: 4.0000e-02 eta: 1 day, 1:39:04 time: 0.2711 data_time: 0.0086 memory: 5828 grad_norm: 2.8764 loss: 2.7702 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7702 2023/06/04 19:15:30 - mmengine - INFO - Epoch(train) [16][ 980/2569] lr: 4.0000e-02 eta: 1 day, 1:39:00 time: 0.2747 data_time: 0.0075 memory: 5828 grad_norm: 2.8368 loss: 2.5274 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5274 2023/06/04 19:15:35 - mmengine - INFO - Epoch(train) [16][1000/2569] lr: 4.0000e-02 eta: 1 day, 1:38:56 time: 0.2725 data_time: 0.0076 memory: 5828 grad_norm: 2.8122 loss: 2.7982 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7982 2023/06/04 19:15:41 - mmengine - INFO - Epoch(train) [16][1020/2569] lr: 4.0000e-02 eta: 1 day, 1:38:51 time: 0.2707 data_time: 0.0072 memory: 5828 grad_norm: 2.7673 loss: 2.4822 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4822 2023/06/04 19:15:46 - mmengine - INFO - Epoch(train) [16][1040/2569] lr: 4.0000e-02 eta: 1 day, 1:38:45 time: 0.2613 data_time: 0.0077 memory: 5828 grad_norm: 2.8109 loss: 2.6111 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6111 2023/06/04 19:15:51 - mmengine - INFO - Epoch(train) [16][1060/2569] lr: 4.0000e-02 eta: 1 day, 1:38:41 time: 0.2747 data_time: 0.0079 memory: 5828 grad_norm: 2.8583 loss: 2.3520 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3520 2023/06/04 19:15:57 - mmengine - INFO - Epoch(train) [16][1080/2569] lr: 4.0000e-02 eta: 1 day, 1:38:35 time: 0.2650 data_time: 0.0080 memory: 5828 grad_norm: 2.8795 loss: 2.6349 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6349 2023/06/04 19:16:02 - mmengine - INFO - Epoch(train) [16][1100/2569] lr: 4.0000e-02 eta: 1 day, 1:38:31 time: 0.2766 data_time: 0.0075 memory: 5828 grad_norm: 2.8569 loss: 2.3657 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3657 2023/06/04 19:16:08 - mmengine - INFO - Epoch(train) [16][1120/2569] lr: 4.0000e-02 eta: 1 day, 1:38:27 time: 0.2717 data_time: 0.0078 memory: 5828 grad_norm: 2.8388 loss: 2.4704 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4704 2023/06/04 19:16:13 - mmengine - INFO - Epoch(train) [16][1140/2569] lr: 4.0000e-02 eta: 1 day, 1:38:21 time: 0.2653 data_time: 0.0082 memory: 5828 grad_norm: 2.8155 loss: 2.4232 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4232 2023/06/04 19:16:18 - mmengine - INFO - Epoch(train) [16][1160/2569] lr: 4.0000e-02 eta: 1 day, 1:38:16 time: 0.2653 data_time: 0.0078 memory: 5828 grad_norm: 2.7876 loss: 2.3736 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3736 2023/06/04 19:16:24 - mmengine - INFO - Epoch(train) [16][1180/2569] lr: 4.0000e-02 eta: 1 day, 1:38:11 time: 0.2707 data_time: 0.0072 memory: 5828 grad_norm: 2.8301 loss: 2.9130 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9130 2023/06/04 19:16:29 - mmengine - INFO - Epoch(train) [16][1200/2569] lr: 4.0000e-02 eta: 1 day, 1:38:05 time: 0.2637 data_time: 0.0077 memory: 5828 grad_norm: 2.7956 loss: 2.7006 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7006 2023/06/04 19:16:34 - mmengine - INFO - Epoch(train) [16][1220/2569] lr: 4.0000e-02 eta: 1 day, 1:37:59 time: 0.2607 data_time: 0.0083 memory: 5828 grad_norm: 2.8360 loss: 2.4244 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4244 2023/06/04 19:16:40 - mmengine - INFO - Epoch(train) [16][1240/2569] lr: 4.0000e-02 eta: 1 day, 1:37:53 time: 0.2631 data_time: 0.0080 memory: 5828 grad_norm: 2.8372 loss: 2.3407 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3407 2023/06/04 19:16:45 - mmengine - INFO - Epoch(train) [16][1260/2569] lr: 4.0000e-02 eta: 1 day, 1:37:47 time: 0.2662 data_time: 0.0078 memory: 5828 grad_norm: 2.8198 loss: 2.8034 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8034 2023/06/04 19:16:50 - mmengine - INFO - Epoch(train) [16][1280/2569] lr: 4.0000e-02 eta: 1 day, 1:37:41 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 2.9020 loss: 2.5750 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5750 2023/06/04 19:16:56 - mmengine - INFO - Epoch(train) [16][1300/2569] lr: 4.0000e-02 eta: 1 day, 1:37:37 time: 0.2720 data_time: 0.0077 memory: 5828 grad_norm: 2.8544 loss: 2.9657 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.9657 2023/06/04 19:17:01 - mmengine - INFO - Epoch(train) [16][1320/2569] lr: 4.0000e-02 eta: 1 day, 1:37:31 time: 0.2613 data_time: 0.0080 memory: 5828 grad_norm: 2.8231 loss: 2.6904 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6904 2023/06/04 19:17:06 - mmengine - INFO - Epoch(train) [16][1340/2569] lr: 4.0000e-02 eta: 1 day, 1:37:26 time: 0.2690 data_time: 0.0079 memory: 5828 grad_norm: 2.8348 loss: 2.5187 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5187 2023/06/04 19:17:11 - mmengine - INFO - Epoch(train) [16][1360/2569] lr: 4.0000e-02 eta: 1 day, 1:37:19 time: 0.2601 data_time: 0.0075 memory: 5828 grad_norm: 2.8208 loss: 2.9270 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9270 2023/06/04 19:17:17 - mmengine - INFO - Epoch(train) [16][1380/2569] lr: 4.0000e-02 eta: 1 day, 1:37:14 time: 0.2695 data_time: 0.0073 memory: 5828 grad_norm: 2.8399 loss: 2.4846 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4846 2023/06/04 19:17:22 - mmengine - INFO - Epoch(train) [16][1400/2569] lr: 4.0000e-02 eta: 1 day, 1:37:09 time: 0.2669 data_time: 0.0076 memory: 5828 grad_norm: 2.8253 loss: 2.6633 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6633 2023/06/04 19:17:27 - mmengine - INFO - Epoch(train) [16][1420/2569] lr: 4.0000e-02 eta: 1 day, 1:37:03 time: 0.2650 data_time: 0.0082 memory: 5828 grad_norm: 2.8546 loss: 2.5601 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5601 2023/06/04 19:17:33 - mmengine - INFO - Epoch(train) [16][1440/2569] lr: 4.0000e-02 eta: 1 day, 1:36:57 time: 0.2624 data_time: 0.0080 memory: 5828 grad_norm: 2.8240 loss: 2.5981 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5981 2023/06/04 19:17:38 - mmengine - INFO - Epoch(train) [16][1460/2569] lr: 4.0000e-02 eta: 1 day, 1:36:52 time: 0.2675 data_time: 0.0082 memory: 5828 grad_norm: 2.8145 loss: 2.3973 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3973 2023/06/04 19:17:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:17:43 - mmengine - INFO - Epoch(train) [16][1480/2569] lr: 4.0000e-02 eta: 1 day, 1:36:46 time: 0.2653 data_time: 0.0075 memory: 5828 grad_norm: 2.8347 loss: 2.7393 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7393 2023/06/04 19:17:49 - mmengine - INFO - Epoch(train) [16][1500/2569] lr: 4.0000e-02 eta: 1 day, 1:36:42 time: 0.2735 data_time: 0.0077 memory: 5828 grad_norm: 2.8219 loss: 2.8628 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8628 2023/06/04 19:17:54 - mmengine - INFO - Epoch(train) [16][1520/2569] lr: 4.0000e-02 eta: 1 day, 1:36:36 time: 0.2660 data_time: 0.0080 memory: 5828 grad_norm: 2.8107 loss: 2.4351 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4351 2023/06/04 19:17:59 - mmengine - INFO - Epoch(train) [16][1540/2569] lr: 4.0000e-02 eta: 1 day, 1:36:31 time: 0.2658 data_time: 0.0082 memory: 5828 grad_norm: 2.8536 loss: 2.4005 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4005 2023/06/04 19:18:05 - mmengine - INFO - Epoch(train) [16][1560/2569] lr: 4.0000e-02 eta: 1 day, 1:36:26 time: 0.2715 data_time: 0.0079 memory: 5828 grad_norm: 2.8419 loss: 2.7631 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7631 2023/06/04 19:18:10 - mmengine - INFO - Epoch(train) [16][1580/2569] lr: 4.0000e-02 eta: 1 day, 1:36:21 time: 0.2677 data_time: 0.0082 memory: 5828 grad_norm: 2.8322 loss: 2.7889 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7889 2023/06/04 19:18:15 - mmengine - INFO - Epoch(train) [16][1600/2569] lr: 4.0000e-02 eta: 1 day, 1:36:15 time: 0.2602 data_time: 0.0088 memory: 5828 grad_norm: 2.8047 loss: 2.6174 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6174 2023/06/04 19:18:21 - mmengine - INFO - Epoch(train) [16][1620/2569] lr: 4.0000e-02 eta: 1 day, 1:36:08 time: 0.2616 data_time: 0.0078 memory: 5828 grad_norm: 2.7792 loss: 2.7378 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7378 2023/06/04 19:18:26 - mmengine - INFO - Epoch(train) [16][1640/2569] lr: 4.0000e-02 eta: 1 day, 1:36:02 time: 0.2623 data_time: 0.0076 memory: 5828 grad_norm: 2.8351 loss: 2.9274 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9274 2023/06/04 19:18:31 - mmengine - INFO - Epoch(train) [16][1660/2569] lr: 4.0000e-02 eta: 1 day, 1:35:57 time: 0.2706 data_time: 0.0075 memory: 5828 grad_norm: 2.8379 loss: 2.4863 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4863 2023/06/04 19:18:37 - mmengine - INFO - Epoch(train) [16][1680/2569] lr: 4.0000e-02 eta: 1 day, 1:35:51 time: 0.2615 data_time: 0.0080 memory: 5828 grad_norm: 2.8314 loss: 2.8984 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.8984 2023/06/04 19:18:42 - mmengine - INFO - Epoch(train) [16][1700/2569] lr: 4.0000e-02 eta: 1 day, 1:35:47 time: 0.2751 data_time: 0.0077 memory: 5828 grad_norm: 2.8259 loss: 2.5854 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5854 2023/06/04 19:18:47 - mmengine - INFO - Epoch(train) [16][1720/2569] lr: 4.0000e-02 eta: 1 day, 1:35:41 time: 0.2603 data_time: 0.0082 memory: 5828 grad_norm: 2.8300 loss: 2.5479 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5479 2023/06/04 19:18:53 - mmengine - INFO - Epoch(train) [16][1740/2569] lr: 4.0000e-02 eta: 1 day, 1:35:36 time: 0.2700 data_time: 0.0078 memory: 5828 grad_norm: 2.8474 loss: 2.2981 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2981 2023/06/04 19:18:58 - mmengine - INFO - Epoch(train) [16][1760/2569] lr: 4.0000e-02 eta: 1 day, 1:35:30 time: 0.2608 data_time: 0.0080 memory: 5828 grad_norm: 2.8756 loss: 2.7430 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.7430 2023/06/04 19:19:03 - mmengine - INFO - Epoch(train) [16][1780/2569] lr: 4.0000e-02 eta: 1 day, 1:35:23 time: 0.2616 data_time: 0.0079 memory: 5828 grad_norm: 2.8483 loss: 2.5032 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5032 2023/06/04 19:19:08 - mmengine - INFO - Epoch(train) [16][1800/2569] lr: 4.0000e-02 eta: 1 day, 1:35:18 time: 0.2662 data_time: 0.0073 memory: 5828 grad_norm: 2.8039 loss: 2.4763 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4763 2023/06/04 19:19:14 - mmengine - INFO - Epoch(train) [16][1820/2569] lr: 4.0000e-02 eta: 1 day, 1:35:12 time: 0.2658 data_time: 0.0080 memory: 5828 grad_norm: 2.8035 loss: 2.3188 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3188 2023/06/04 19:19:19 - mmengine - INFO - Epoch(train) [16][1840/2569] lr: 4.0000e-02 eta: 1 day, 1:35:07 time: 0.2661 data_time: 0.0080 memory: 5828 grad_norm: 2.8466 loss: 2.4383 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4383 2023/06/04 19:19:25 - mmengine - INFO - Epoch(train) [16][1860/2569] lr: 4.0000e-02 eta: 1 day, 1:35:03 time: 0.2771 data_time: 0.0081 memory: 5828 grad_norm: 2.7935 loss: 2.5037 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5037 2023/06/04 19:19:30 - mmengine - INFO - Epoch(train) [16][1880/2569] lr: 4.0000e-02 eta: 1 day, 1:34:57 time: 0.2598 data_time: 0.0084 memory: 5828 grad_norm: 2.8056 loss: 2.8329 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8329 2023/06/04 19:19:35 - mmengine - INFO - Epoch(train) [16][1900/2569] lr: 4.0000e-02 eta: 1 day, 1:34:52 time: 0.2702 data_time: 0.0080 memory: 5828 grad_norm: 2.8684 loss: 2.8771 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8771 2023/06/04 19:19:41 - mmengine - INFO - Epoch(train) [16][1920/2569] lr: 4.0000e-02 eta: 1 day, 1:34:47 time: 0.2720 data_time: 0.0084 memory: 5828 grad_norm: 2.7907 loss: 2.7577 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7577 2023/06/04 19:19:46 - mmengine - INFO - Epoch(train) [16][1940/2569] lr: 4.0000e-02 eta: 1 day, 1:34:41 time: 0.2644 data_time: 0.0076 memory: 5828 grad_norm: 2.8499 loss: 2.7421 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7421 2023/06/04 19:19:51 - mmengine - INFO - Epoch(train) [16][1960/2569] lr: 4.0000e-02 eta: 1 day, 1:34:37 time: 0.2710 data_time: 0.0075 memory: 5828 grad_norm: 2.7916 loss: 2.6770 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6770 2023/06/04 19:19:57 - mmengine - INFO - Epoch(train) [16][1980/2569] lr: 4.0000e-02 eta: 1 day, 1:34:31 time: 0.2623 data_time: 0.0081 memory: 5828 grad_norm: 2.8417 loss: 2.9094 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.9094 2023/06/04 19:20:02 - mmengine - INFO - Epoch(train) [16][2000/2569] lr: 4.0000e-02 eta: 1 day, 1:34:24 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 2.8149 loss: 2.5115 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5115 2023/06/04 19:20:07 - mmengine - INFO - Epoch(train) [16][2020/2569] lr: 4.0000e-02 eta: 1 day, 1:34:20 time: 0.2726 data_time: 0.0078 memory: 5828 grad_norm: 2.8233 loss: 2.7936 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7936 2023/06/04 19:20:13 - mmengine - INFO - Epoch(train) [16][2040/2569] lr: 4.0000e-02 eta: 1 day, 1:34:15 time: 0.2659 data_time: 0.0077 memory: 5828 grad_norm: 2.8412 loss: 2.4793 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4793 2023/06/04 19:20:18 - mmengine - INFO - Epoch(train) [16][2060/2569] lr: 4.0000e-02 eta: 1 day, 1:34:10 time: 0.2739 data_time: 0.0076 memory: 5828 grad_norm: 2.8624 loss: 2.3284 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3284 2023/06/04 19:20:24 - mmengine - INFO - Epoch(train) [16][2080/2569] lr: 4.0000e-02 eta: 1 day, 1:34:06 time: 0.2715 data_time: 0.0077 memory: 5828 grad_norm: 2.8366 loss: 2.4240 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4240 2023/06/04 19:20:29 - mmengine - INFO - Epoch(train) [16][2100/2569] lr: 4.0000e-02 eta: 1 day, 1:34:00 time: 0.2613 data_time: 0.0083 memory: 5828 grad_norm: 2.8449 loss: 2.6275 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6275 2023/06/04 19:20:34 - mmengine - INFO - Epoch(train) [16][2120/2569] lr: 4.0000e-02 eta: 1 day, 1:33:56 time: 0.2794 data_time: 0.0081 memory: 5828 grad_norm: 2.8723 loss: 2.7970 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7970 2023/06/04 19:20:40 - mmengine - INFO - Epoch(train) [16][2140/2569] lr: 4.0000e-02 eta: 1 day, 1:33:50 time: 0.2614 data_time: 0.0079 memory: 5828 grad_norm: 2.7826 loss: 2.7252 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7252 2023/06/04 19:20:45 - mmengine - INFO - Epoch(train) [16][2160/2569] lr: 4.0000e-02 eta: 1 day, 1:33:46 time: 0.2756 data_time: 0.0079 memory: 5828 grad_norm: 2.8715 loss: 2.5753 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5753 2023/06/04 19:20:50 - mmengine - INFO - Epoch(train) [16][2180/2569] lr: 4.0000e-02 eta: 1 day, 1:33:41 time: 0.2669 data_time: 0.0079 memory: 5828 grad_norm: 2.8307 loss: 2.5878 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5878 2023/06/04 19:20:56 - mmengine - INFO - Epoch(train) [16][2200/2569] lr: 4.0000e-02 eta: 1 day, 1:33:36 time: 0.2699 data_time: 0.0077 memory: 5828 grad_norm: 2.8062 loss: 2.6338 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6338 2023/06/04 19:21:01 - mmengine - INFO - Epoch(train) [16][2220/2569] lr: 4.0000e-02 eta: 1 day, 1:33:30 time: 0.2634 data_time: 0.0081 memory: 5828 grad_norm: 2.8201 loss: 2.7208 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7208 2023/06/04 19:21:06 - mmengine - INFO - Epoch(train) [16][2240/2569] lr: 4.0000e-02 eta: 1 day, 1:33:24 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 2.8374 loss: 2.7244 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7244 2023/06/04 19:21:12 - mmengine - INFO - Epoch(train) [16][2260/2569] lr: 4.0000e-02 eta: 1 day, 1:33:18 time: 0.2671 data_time: 0.0081 memory: 5828 grad_norm: 2.8173 loss: 2.6947 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6947 2023/06/04 19:21:17 - mmengine - INFO - Epoch(train) [16][2280/2569] lr: 4.0000e-02 eta: 1 day, 1:33:13 time: 0.2667 data_time: 0.0075 memory: 5828 grad_norm: 2.7881 loss: 2.6976 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6976 2023/06/04 19:21:22 - mmengine - INFO - Epoch(train) [16][2300/2569] lr: 4.0000e-02 eta: 1 day, 1:33:08 time: 0.2693 data_time: 0.0080 memory: 5828 grad_norm: 2.7977 loss: 2.3506 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3506 2023/06/04 19:21:28 - mmengine - INFO - Epoch(train) [16][2320/2569] lr: 4.0000e-02 eta: 1 day, 1:33:04 time: 0.2765 data_time: 0.0076 memory: 5828 grad_norm: 2.8420 loss: 2.8248 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8248 2023/06/04 19:21:33 - mmengine - INFO - Epoch(train) [16][2340/2569] lr: 4.0000e-02 eta: 1 day, 1:32:59 time: 0.2655 data_time: 0.0082 memory: 5828 grad_norm: 2.8076 loss: 2.4962 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4962 2023/06/04 19:21:39 - mmengine - INFO - Epoch(train) [16][2360/2569] lr: 4.0000e-02 eta: 1 day, 1:32:54 time: 0.2737 data_time: 0.0095 memory: 5828 grad_norm: 2.7989 loss: 2.6471 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6471 2023/06/04 19:21:44 - mmengine - INFO - Epoch(train) [16][2380/2569] lr: 4.0000e-02 eta: 1 day, 1:32:50 time: 0.2699 data_time: 0.0083 memory: 5828 grad_norm: 2.8514 loss: 2.5887 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5887 2023/06/04 19:21:50 - mmengine - INFO - Epoch(train) [16][2400/2569] lr: 4.0000e-02 eta: 1 day, 1:32:45 time: 0.2707 data_time: 0.0080 memory: 5828 grad_norm: 2.8632 loss: 2.5363 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.5363 2023/06/04 19:21:55 - mmengine - INFO - Epoch(train) [16][2420/2569] lr: 4.0000e-02 eta: 1 day, 1:32:38 time: 0.2603 data_time: 0.0076 memory: 5828 grad_norm: 2.8258 loss: 2.7204 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7204 2023/06/04 19:22:00 - mmengine - INFO - Epoch(train) [16][2440/2569] lr: 4.0000e-02 eta: 1 day, 1:32:32 time: 0.2606 data_time: 0.0075 memory: 5828 grad_norm: 2.8736 loss: 2.4418 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4418 2023/06/04 19:22:05 - mmengine - INFO - Epoch(train) [16][2460/2569] lr: 4.0000e-02 eta: 1 day, 1:32:27 time: 0.2684 data_time: 0.0080 memory: 5828 grad_norm: 2.8404 loss: 2.7828 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7828 2023/06/04 19:22:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:22:11 - mmengine - INFO - Epoch(train) [16][2480/2569] lr: 4.0000e-02 eta: 1 day, 1:32:21 time: 0.2610 data_time: 0.0072 memory: 5828 grad_norm: 2.9241 loss: 3.0433 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.0433 2023/06/04 19:22:16 - mmengine - INFO - Epoch(train) [16][2500/2569] lr: 4.0000e-02 eta: 1 day, 1:32:15 time: 0.2643 data_time: 0.0081 memory: 5828 grad_norm: 2.8288 loss: 2.0693 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0693 2023/06/04 19:22:21 - mmengine - INFO - Epoch(train) [16][2520/2569] lr: 4.0000e-02 eta: 1 day, 1:32:11 time: 0.2741 data_time: 0.0077 memory: 5828 grad_norm: 2.8306 loss: 2.5046 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5046 2023/06/04 19:22:27 - mmengine - INFO - Epoch(train) [16][2540/2569] lr: 4.0000e-02 eta: 1 day, 1:32:06 time: 0.2736 data_time: 0.0082 memory: 5828 grad_norm: 2.8346 loss: 2.8012 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8012 2023/06/04 19:22:32 - mmengine - INFO - Epoch(train) [16][2560/2569] lr: 4.0000e-02 eta: 1 day, 1:32:00 time: 0.2610 data_time: 0.0082 memory: 5828 grad_norm: 2.8335 loss: 2.4629 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4629 2023/06/04 19:22:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:22:34 - mmengine - INFO - Epoch(train) [16][2569/2569] lr: 4.0000e-02 eta: 1 day, 1:31:56 time: 0.2547 data_time: 0.0080 memory: 5828 grad_norm: 2.8422 loss: 2.5820 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.5820 2023/06/04 19:22:34 - mmengine - INFO - Saving checkpoint at 16 epochs 2023/06/04 19:22:43 - mmengine - INFO - Epoch(train) [17][ 20/2569] lr: 4.0000e-02 eta: 1 day, 1:31:57 time: 0.3074 data_time: 0.0425 memory: 5828 grad_norm: 2.8134 loss: 2.3800 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3800 2023/06/04 19:22:49 - mmengine - INFO - Epoch(train) [17][ 40/2569] lr: 4.0000e-02 eta: 1 day, 1:31:53 time: 0.2741 data_time: 0.0079 memory: 5828 grad_norm: 2.8154 loss: 2.4427 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4427 2023/06/04 19:22:54 - mmengine - INFO - Epoch(train) [17][ 60/2569] lr: 4.0000e-02 eta: 1 day, 1:31:47 time: 0.2616 data_time: 0.0080 memory: 5828 grad_norm: 2.7912 loss: 2.4874 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4874 2023/06/04 19:23:00 - mmengine - INFO - Epoch(train) [17][ 80/2569] lr: 4.0000e-02 eta: 1 day, 1:31:42 time: 0.2704 data_time: 0.0076 memory: 5828 grad_norm: 2.8682 loss: 2.1465 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1465 2023/06/04 19:23:05 - mmengine - INFO - Epoch(train) [17][ 100/2569] lr: 4.0000e-02 eta: 1 day, 1:31:38 time: 0.2732 data_time: 0.0073 memory: 5828 grad_norm: 2.7889 loss: 2.6170 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6170 2023/06/04 19:23:10 - mmengine - INFO - Epoch(train) [17][ 120/2569] lr: 4.0000e-02 eta: 1 day, 1:31:32 time: 0.2629 data_time: 0.0079 memory: 5828 grad_norm: 2.7969 loss: 2.5317 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.5317 2023/06/04 19:23:16 - mmengine - INFO - Epoch(train) [17][ 140/2569] lr: 4.0000e-02 eta: 1 day, 1:31:27 time: 0.2704 data_time: 0.0077 memory: 5828 grad_norm: 2.8050 loss: 2.3584 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3584 2023/06/04 19:23:21 - mmengine - INFO - Epoch(train) [17][ 160/2569] lr: 4.0000e-02 eta: 1 day, 1:31:21 time: 0.2631 data_time: 0.0076 memory: 5828 grad_norm: 2.8291 loss: 2.2842 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.2842 2023/06/04 19:23:26 - mmengine - INFO - Epoch(train) [17][ 180/2569] lr: 4.0000e-02 eta: 1 day, 1:31:16 time: 0.2713 data_time: 0.0071 memory: 5828 grad_norm: 2.8603 loss: 2.7449 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7449 2023/06/04 19:23:32 - mmengine - INFO - Epoch(train) [17][ 200/2569] lr: 4.0000e-02 eta: 1 day, 1:31:10 time: 0.2616 data_time: 0.0076 memory: 5828 grad_norm: 2.8170 loss: 2.5648 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5648 2023/06/04 19:23:37 - mmengine - INFO - Epoch(train) [17][ 220/2569] lr: 4.0000e-02 eta: 1 day, 1:31:05 time: 0.2686 data_time: 0.0082 memory: 5828 grad_norm: 2.8506 loss: 2.3453 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3453 2023/06/04 19:23:42 - mmengine - INFO - Epoch(train) [17][ 240/2569] lr: 4.0000e-02 eta: 1 day, 1:31:01 time: 0.2760 data_time: 0.0080 memory: 5828 grad_norm: 2.7831 loss: 2.6607 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6607 2023/06/04 19:23:48 - mmengine - INFO - Epoch(train) [17][ 260/2569] lr: 4.0000e-02 eta: 1 day, 1:30:56 time: 0.2671 data_time: 0.0078 memory: 5828 grad_norm: 2.8277 loss: 2.5927 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5927 2023/06/04 19:23:53 - mmengine - INFO - Epoch(train) [17][ 280/2569] lr: 4.0000e-02 eta: 1 day, 1:30:51 time: 0.2715 data_time: 0.0076 memory: 5828 grad_norm: 2.8392 loss: 2.2252 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2252 2023/06/04 19:23:58 - mmengine - INFO - Epoch(train) [17][ 300/2569] lr: 4.0000e-02 eta: 1 day, 1:30:45 time: 0.2599 data_time: 0.0079 memory: 5828 grad_norm: 2.8249 loss: 2.7496 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7496 2023/06/04 19:24:04 - mmengine - INFO - Epoch(train) [17][ 320/2569] lr: 4.0000e-02 eta: 1 day, 1:30:41 time: 0.2736 data_time: 0.0071 memory: 5828 grad_norm: 2.8077 loss: 2.5063 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5063 2023/06/04 19:24:09 - mmengine - INFO - Epoch(train) [17][ 340/2569] lr: 4.0000e-02 eta: 1 day, 1:30:34 time: 0.2594 data_time: 0.0077 memory: 5828 grad_norm: 2.8749 loss: 2.8286 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8286 2023/06/04 19:24:14 - mmengine - INFO - Epoch(train) [17][ 360/2569] lr: 4.0000e-02 eta: 1 day, 1:30:28 time: 0.2653 data_time: 0.0075 memory: 5828 grad_norm: 2.8048 loss: 2.2303 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2303 2023/06/04 19:24:20 - mmengine - INFO - Epoch(train) [17][ 380/2569] lr: 4.0000e-02 eta: 1 day, 1:30:22 time: 0.2631 data_time: 0.0072 memory: 5828 grad_norm: 2.8025 loss: 2.5161 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5161 2023/06/04 19:24:25 - mmengine - INFO - Epoch(train) [17][ 400/2569] lr: 4.0000e-02 eta: 1 day, 1:30:17 time: 0.2658 data_time: 0.0075 memory: 5828 grad_norm: 2.8471 loss: 2.6992 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6992 2023/06/04 19:24:30 - mmengine - INFO - Epoch(train) [17][ 420/2569] lr: 4.0000e-02 eta: 1 day, 1:30:11 time: 0.2649 data_time: 0.0083 memory: 5828 grad_norm: 2.8600 loss: 2.8123 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8123 2023/06/04 19:24:36 - mmengine - INFO - Epoch(train) [17][ 440/2569] lr: 4.0000e-02 eta: 1 day, 1:30:06 time: 0.2711 data_time: 0.0075 memory: 5828 grad_norm: 2.8352 loss: 2.7242 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7242 2023/06/04 19:24:41 - mmengine - INFO - Epoch(train) [17][ 460/2569] lr: 4.0000e-02 eta: 1 day, 1:30:01 time: 0.2687 data_time: 0.0079 memory: 5828 grad_norm: 2.8551 loss: 2.3936 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3936 2023/06/04 19:24:47 - mmengine - INFO - Epoch(train) [17][ 480/2569] lr: 4.0000e-02 eta: 1 day, 1:29:57 time: 0.2712 data_time: 0.0074 memory: 5828 grad_norm: 2.8831 loss: 2.6957 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6957 2023/06/04 19:24:52 - mmengine - INFO - Epoch(train) [17][ 500/2569] lr: 4.0000e-02 eta: 1 day, 1:29:50 time: 0.2597 data_time: 0.0078 memory: 5828 grad_norm: 2.8884 loss: 2.5963 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5963 2023/06/04 19:24:57 - mmengine - INFO - Epoch(train) [17][ 520/2569] lr: 4.0000e-02 eta: 1 day, 1:29:44 time: 0.2631 data_time: 0.0081 memory: 5828 grad_norm: 2.8202 loss: 2.5470 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5470 2023/06/04 19:25:02 - mmengine - INFO - Epoch(train) [17][ 540/2569] lr: 4.0000e-02 eta: 1 day, 1:29:38 time: 0.2626 data_time: 0.0081 memory: 5828 grad_norm: 2.8589 loss: 2.3972 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3972 2023/06/04 19:25:07 - mmengine - INFO - Epoch(train) [17][ 560/2569] lr: 4.0000e-02 eta: 1 day, 1:29:32 time: 0.2614 data_time: 0.0081 memory: 5828 grad_norm: 2.8469 loss: 2.5975 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5975 2023/06/04 19:25:13 - mmengine - INFO - Epoch(train) [17][ 580/2569] lr: 4.0000e-02 eta: 1 day, 1:29:27 time: 0.2718 data_time: 0.0078 memory: 5828 grad_norm: 2.8309 loss: 2.5339 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5339 2023/06/04 19:25:18 - mmengine - INFO - Epoch(train) [17][ 600/2569] lr: 4.0000e-02 eta: 1 day, 1:29:23 time: 0.2722 data_time: 0.0081 memory: 5828 grad_norm: 2.8065 loss: 2.3562 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3562 2023/06/04 19:25:24 - mmengine - INFO - Epoch(train) [17][ 620/2569] lr: 4.0000e-02 eta: 1 day, 1:29:17 time: 0.2667 data_time: 0.0079 memory: 5828 grad_norm: 2.7774 loss: 2.2639 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2639 2023/06/04 19:25:29 - mmengine - INFO - Epoch(train) [17][ 640/2569] lr: 4.0000e-02 eta: 1 day, 1:29:12 time: 0.2690 data_time: 0.0077 memory: 5828 grad_norm: 2.7915 loss: 2.4353 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4353 2023/06/04 19:25:34 - mmengine - INFO - Epoch(train) [17][ 660/2569] lr: 4.0000e-02 eta: 1 day, 1:29:07 time: 0.2651 data_time: 0.0076 memory: 5828 grad_norm: 2.8915 loss: 2.2991 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2991 2023/06/04 19:25:40 - mmengine - INFO - Epoch(train) [17][ 680/2569] lr: 4.0000e-02 eta: 1 day, 1:29:00 time: 0.2613 data_time: 0.0077 memory: 5828 grad_norm: 2.8034 loss: 2.6959 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6959 2023/06/04 19:25:45 - mmengine - INFO - Epoch(train) [17][ 700/2569] lr: 4.0000e-02 eta: 1 day, 1:28:54 time: 0.2599 data_time: 0.0076 memory: 5828 grad_norm: 2.7896 loss: 2.4012 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4012 2023/06/04 19:25:50 - mmengine - INFO - Epoch(train) [17][ 720/2569] lr: 4.0000e-02 eta: 1 day, 1:28:48 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 2.8753 loss: 2.9391 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9391 2023/06/04 19:25:55 - mmengine - INFO - Epoch(train) [17][ 740/2569] lr: 4.0000e-02 eta: 1 day, 1:28:43 time: 0.2659 data_time: 0.0083 memory: 5828 grad_norm: 2.8166 loss: 2.7077 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7077 2023/06/04 19:26:01 - mmengine - INFO - Epoch(train) [17][ 760/2569] lr: 4.0000e-02 eta: 1 day, 1:28:37 time: 0.2672 data_time: 0.0076 memory: 5828 grad_norm: 2.8799 loss: 2.8955 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8955 2023/06/04 19:26:06 - mmengine - INFO - Epoch(train) [17][ 780/2569] lr: 4.0000e-02 eta: 1 day, 1:28:31 time: 0.2599 data_time: 0.0080 memory: 5828 grad_norm: 2.8442 loss: 2.2781 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2781 2023/06/04 19:26:11 - mmengine - INFO - Epoch(train) [17][ 800/2569] lr: 4.0000e-02 eta: 1 day, 1:28:25 time: 0.2619 data_time: 0.0089 memory: 5828 grad_norm: 2.7663 loss: 2.6575 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6575 2023/06/04 19:26:17 - mmengine - INFO - Epoch(train) [17][ 820/2569] lr: 4.0000e-02 eta: 1 day, 1:28:19 time: 0.2654 data_time: 0.0079 memory: 5828 grad_norm: 2.8188 loss: 2.5430 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5430 2023/06/04 19:26:22 - mmengine - INFO - Epoch(train) [17][ 840/2569] lr: 4.0000e-02 eta: 1 day, 1:28:14 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 2.8241 loss: 2.8148 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8148 2023/06/04 19:26:27 - mmengine - INFO - Epoch(train) [17][ 860/2569] lr: 4.0000e-02 eta: 1 day, 1:28:07 time: 0.2615 data_time: 0.0078 memory: 5828 grad_norm: 2.8459 loss: 2.6689 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6689 2023/06/04 19:26:32 - mmengine - INFO - Epoch(train) [17][ 880/2569] lr: 4.0000e-02 eta: 1 day, 1:28:01 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 2.8207 loss: 2.5519 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5519 2023/06/04 19:26:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:26:38 - mmengine - INFO - Epoch(train) [17][ 900/2569] lr: 4.0000e-02 eta: 1 day, 1:27:55 time: 0.2665 data_time: 0.0072 memory: 5828 grad_norm: 2.9055 loss: 2.3154 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3154 2023/06/04 19:26:43 - mmengine - INFO - Epoch(train) [17][ 920/2569] lr: 4.0000e-02 eta: 1 day, 1:27:50 time: 0.2641 data_time: 0.0077 memory: 5828 grad_norm: 2.8304 loss: 2.9806 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9806 2023/06/04 19:26:48 - mmengine - INFO - Epoch(train) [17][ 940/2569] lr: 4.0000e-02 eta: 1 day, 1:27:46 time: 0.2755 data_time: 0.0081 memory: 5828 grad_norm: 2.8358 loss: 2.8968 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8968 2023/06/04 19:26:54 - mmengine - INFO - Epoch(train) [17][ 960/2569] lr: 4.0000e-02 eta: 1 day, 1:27:42 time: 0.2751 data_time: 0.0074 memory: 5828 grad_norm: 2.7836 loss: 2.4715 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4715 2023/06/04 19:26:59 - mmengine - INFO - Epoch(train) [17][ 980/2569] lr: 4.0000e-02 eta: 1 day, 1:27:37 time: 0.2710 data_time: 0.0075 memory: 5828 grad_norm: 2.7904 loss: 2.4301 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4301 2023/06/04 19:27:05 - mmengine - INFO - Epoch(train) [17][1000/2569] lr: 4.0000e-02 eta: 1 day, 1:27:32 time: 0.2672 data_time: 0.0071 memory: 5828 grad_norm: 2.8384 loss: 3.0341 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.0341 2023/06/04 19:27:10 - mmengine - INFO - Epoch(train) [17][1020/2569] lr: 4.0000e-02 eta: 1 day, 1:27:27 time: 0.2684 data_time: 0.0084 memory: 5828 grad_norm: 2.8530 loss: 2.1937 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1937 2023/06/04 19:27:15 - mmengine - INFO - Epoch(train) [17][1040/2569] lr: 4.0000e-02 eta: 1 day, 1:27:21 time: 0.2659 data_time: 0.0086 memory: 5828 grad_norm: 2.8463 loss: 2.7448 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7448 2023/06/04 19:27:21 - mmengine - INFO - Epoch(train) [17][1060/2569] lr: 4.0000e-02 eta: 1 day, 1:27:16 time: 0.2661 data_time: 0.0075 memory: 5828 grad_norm: 2.8490 loss: 2.2560 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2560 2023/06/04 19:27:26 - mmengine - INFO - Epoch(train) [17][1080/2569] lr: 4.0000e-02 eta: 1 day, 1:27:12 time: 0.2756 data_time: 0.0079 memory: 5828 grad_norm: 2.8223 loss: 2.6547 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6547 2023/06/04 19:27:32 - mmengine - INFO - Epoch(train) [17][1100/2569] lr: 4.0000e-02 eta: 1 day, 1:27:07 time: 0.2688 data_time: 0.0077 memory: 5828 grad_norm: 2.8402 loss: 2.6701 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6701 2023/06/04 19:27:37 - mmengine - INFO - Epoch(train) [17][1120/2569] lr: 4.0000e-02 eta: 1 day, 1:27:01 time: 0.2682 data_time: 0.0079 memory: 5828 grad_norm: 2.8599 loss: 2.7976 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7976 2023/06/04 19:27:42 - mmengine - INFO - Epoch(train) [17][1140/2569] lr: 4.0000e-02 eta: 1 day, 1:26:56 time: 0.2660 data_time: 0.0078 memory: 5828 grad_norm: 2.8552 loss: 2.5314 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5314 2023/06/04 19:27:48 - mmengine - INFO - Epoch(train) [17][1160/2569] lr: 4.0000e-02 eta: 1 day, 1:26:50 time: 0.2621 data_time: 0.0078 memory: 5828 grad_norm: 2.8491 loss: 2.5491 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5491 2023/06/04 19:27:53 - mmengine - INFO - Epoch(train) [17][1180/2569] lr: 4.0000e-02 eta: 1 day, 1:26:44 time: 0.2673 data_time: 0.0082 memory: 5828 grad_norm: 2.8582 loss: 2.7606 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7606 2023/06/04 19:27:58 - mmengine - INFO - Epoch(train) [17][1200/2569] lr: 4.0000e-02 eta: 1 day, 1:26:38 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 2.8653 loss: 2.8185 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8185 2023/06/04 19:28:03 - mmengine - INFO - Epoch(train) [17][1220/2569] lr: 4.0000e-02 eta: 1 day, 1:26:32 time: 0.2638 data_time: 0.0086 memory: 5828 grad_norm: 2.8379 loss: 2.8141 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8141 2023/06/04 19:28:09 - mmengine - INFO - Epoch(train) [17][1240/2569] lr: 4.0000e-02 eta: 1 day, 1:26:28 time: 0.2749 data_time: 0.0082 memory: 5828 grad_norm: 2.8539 loss: 2.4097 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4097 2023/06/04 19:28:14 - mmengine - INFO - Epoch(train) [17][1260/2569] lr: 4.0000e-02 eta: 1 day, 1:26:23 time: 0.2663 data_time: 0.0081 memory: 5828 grad_norm: 2.8299 loss: 2.4285 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4285 2023/06/04 19:28:20 - mmengine - INFO - Epoch(train) [17][1280/2569] lr: 4.0000e-02 eta: 1 day, 1:26:18 time: 0.2693 data_time: 0.0083 memory: 5828 grad_norm: 2.8252 loss: 2.3686 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3686 2023/06/04 19:28:25 - mmengine - INFO - Epoch(train) [17][1300/2569] lr: 4.0000e-02 eta: 1 day, 1:26:12 time: 0.2661 data_time: 0.0084 memory: 5828 grad_norm: 2.8391 loss: 2.4204 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4204 2023/06/04 19:28:30 - mmengine - INFO - Epoch(train) [17][1320/2569] lr: 4.0000e-02 eta: 1 day, 1:26:07 time: 0.2639 data_time: 0.0081 memory: 5828 grad_norm: 2.8328 loss: 2.6878 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6878 2023/06/04 19:28:35 - mmengine - INFO - Epoch(train) [17][1340/2569] lr: 4.0000e-02 eta: 1 day, 1:26:01 time: 0.2641 data_time: 0.0076 memory: 5828 grad_norm: 2.8273 loss: 2.6213 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6213 2023/06/04 19:28:41 - mmengine - INFO - Epoch(train) [17][1360/2569] lr: 4.0000e-02 eta: 1 day, 1:25:54 time: 0.2600 data_time: 0.0080 memory: 5828 grad_norm: 2.8091 loss: 2.7366 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7366 2023/06/04 19:28:46 - mmengine - INFO - Epoch(train) [17][1380/2569] lr: 4.0000e-02 eta: 1 day, 1:25:48 time: 0.2640 data_time: 0.0080 memory: 5828 grad_norm: 2.8544 loss: 2.6595 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6595 2023/06/04 19:28:51 - mmengine - INFO - Epoch(train) [17][1400/2569] lr: 4.0000e-02 eta: 1 day, 1:25:44 time: 0.2713 data_time: 0.0076 memory: 5828 grad_norm: 2.8409 loss: 2.4307 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4307 2023/06/04 19:28:57 - mmengine - INFO - Epoch(train) [17][1420/2569] lr: 4.0000e-02 eta: 1 day, 1:25:38 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 2.8121 loss: 2.4666 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4666 2023/06/04 19:29:02 - mmengine - INFO - Epoch(train) [17][1440/2569] lr: 4.0000e-02 eta: 1 day, 1:25:33 time: 0.2689 data_time: 0.0075 memory: 5828 grad_norm: 2.8370 loss: 2.3764 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3764 2023/06/04 19:29:07 - mmengine - INFO - Epoch(train) [17][1460/2569] lr: 4.0000e-02 eta: 1 day, 1:25:27 time: 0.2614 data_time: 0.0076 memory: 5828 grad_norm: 2.8354 loss: 2.3779 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3779 2023/06/04 19:29:13 - mmengine - INFO - Epoch(train) [17][1480/2569] lr: 4.0000e-02 eta: 1 day, 1:25:21 time: 0.2672 data_time: 0.0078 memory: 5828 grad_norm: 2.8520 loss: 2.7022 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7022 2023/06/04 19:29:18 - mmengine - INFO - Epoch(train) [17][1500/2569] lr: 4.0000e-02 eta: 1 day, 1:25:16 time: 0.2683 data_time: 0.0077 memory: 5828 grad_norm: 2.8106 loss: 2.5300 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5300 2023/06/04 19:29:23 - mmengine - INFO - Epoch(train) [17][1520/2569] lr: 4.0000e-02 eta: 1 day, 1:25:11 time: 0.2665 data_time: 0.0076 memory: 5828 grad_norm: 2.8579 loss: 2.3773 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3773 2023/06/04 19:29:29 - mmengine - INFO - Epoch(train) [17][1540/2569] lr: 4.0000e-02 eta: 1 day, 1:25:05 time: 0.2662 data_time: 0.0077 memory: 5828 grad_norm: 2.8545 loss: 2.5484 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5484 2023/06/04 19:29:34 - mmengine - INFO - Epoch(train) [17][1560/2569] lr: 4.0000e-02 eta: 1 day, 1:25:02 time: 0.2767 data_time: 0.0082 memory: 5828 grad_norm: 2.8246 loss: 2.6593 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6593 2023/06/04 19:29:40 - mmengine - INFO - Epoch(train) [17][1580/2569] lr: 4.0000e-02 eta: 1 day, 1:24:58 time: 0.2751 data_time: 0.0082 memory: 5828 grad_norm: 2.8136 loss: 2.7149 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7149 2023/06/04 19:29:45 - mmengine - INFO - Epoch(train) [17][1600/2569] lr: 4.0000e-02 eta: 1 day, 1:24:54 time: 0.2768 data_time: 0.0080 memory: 5828 grad_norm: 2.7854 loss: 2.7012 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7012 2023/06/04 19:29:51 - mmengine - INFO - Epoch(train) [17][1620/2569] lr: 4.0000e-02 eta: 1 day, 1:24:49 time: 0.2735 data_time: 0.0076 memory: 5828 grad_norm: 2.7741 loss: 2.3488 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3488 2023/06/04 19:29:56 - mmengine - INFO - Epoch(train) [17][1640/2569] lr: 4.0000e-02 eta: 1 day, 1:24:44 time: 0.2637 data_time: 0.0081 memory: 5828 grad_norm: 2.8432 loss: 2.5567 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5567 2023/06/04 19:30:01 - mmengine - INFO - Epoch(train) [17][1660/2569] lr: 4.0000e-02 eta: 1 day, 1:24:38 time: 0.2627 data_time: 0.0076 memory: 5828 grad_norm: 2.8394 loss: 2.7212 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7212 2023/06/04 19:30:07 - mmengine - INFO - Epoch(train) [17][1680/2569] lr: 4.0000e-02 eta: 1 day, 1:24:33 time: 0.2699 data_time: 0.0085 memory: 5828 grad_norm: 2.7869 loss: 2.9808 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9808 2023/06/04 19:30:12 - mmengine - INFO - Epoch(train) [17][1700/2569] lr: 4.0000e-02 eta: 1 day, 1:24:27 time: 0.2641 data_time: 0.0082 memory: 5828 grad_norm: 2.7939 loss: 3.0024 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0024 2023/06/04 19:30:17 - mmengine - INFO - Epoch(train) [17][1720/2569] lr: 4.0000e-02 eta: 1 day, 1:24:22 time: 0.2704 data_time: 0.0076 memory: 5828 grad_norm: 2.8736 loss: 2.6492 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6492 2023/06/04 19:30:23 - mmengine - INFO - Epoch(train) [17][1740/2569] lr: 4.0000e-02 eta: 1 day, 1:24:16 time: 0.2615 data_time: 0.0078 memory: 5828 grad_norm: 2.8396 loss: 2.3962 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3962 2023/06/04 19:30:28 - mmengine - INFO - Epoch(train) [17][1760/2569] lr: 4.0000e-02 eta: 1 day, 1:24:11 time: 0.2692 data_time: 0.0074 memory: 5828 grad_norm: 2.8248 loss: 2.5571 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5571 2023/06/04 19:30:33 - mmengine - INFO - Epoch(train) [17][1780/2569] lr: 4.0000e-02 eta: 1 day, 1:24:05 time: 0.2654 data_time: 0.0084 memory: 5828 grad_norm: 2.8166 loss: 2.5725 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5725 2023/06/04 19:30:39 - mmengine - INFO - Epoch(train) [17][1800/2569] lr: 4.0000e-02 eta: 1 day, 1:24:00 time: 0.2695 data_time: 0.0082 memory: 5828 grad_norm: 2.7891 loss: 2.2799 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2799 2023/06/04 19:30:44 - mmengine - INFO - Epoch(train) [17][1820/2569] lr: 4.0000e-02 eta: 1 day, 1:23:56 time: 0.2721 data_time: 0.0080 memory: 5828 grad_norm: 2.8371 loss: 2.2533 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2533 2023/06/04 19:30:49 - mmengine - INFO - Epoch(train) [17][1840/2569] lr: 4.0000e-02 eta: 1 day, 1:23:50 time: 0.2653 data_time: 0.0083 memory: 5828 grad_norm: 2.8755 loss: 2.7165 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7165 2023/06/04 19:30:55 - mmengine - INFO - Epoch(train) [17][1860/2569] lr: 4.0000e-02 eta: 1 day, 1:23:46 time: 0.2736 data_time: 0.0079 memory: 5828 grad_norm: 2.7782 loss: 2.5898 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5898 2023/06/04 19:31:00 - mmengine - INFO - Epoch(train) [17][1880/2569] lr: 4.0000e-02 eta: 1 day, 1:23:40 time: 0.2634 data_time: 0.0082 memory: 5828 grad_norm: 2.8358 loss: 2.6974 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6974 2023/06/04 19:31:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:31:05 - mmengine - INFO - Epoch(train) [17][1900/2569] lr: 4.0000e-02 eta: 1 day, 1:23:34 time: 0.2619 data_time: 0.0080 memory: 5828 grad_norm: 2.8098 loss: 2.3908 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3908 2023/06/04 19:31:11 - mmengine - INFO - Epoch(train) [17][1920/2569] lr: 4.0000e-02 eta: 1 day, 1:23:29 time: 0.2732 data_time: 0.0075 memory: 5828 grad_norm: 2.8279 loss: 2.6980 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6980 2023/06/04 19:31:16 - mmengine - INFO - Epoch(train) [17][1940/2569] lr: 4.0000e-02 eta: 1 day, 1:23:25 time: 0.2734 data_time: 0.0078 memory: 5828 grad_norm: 2.8739 loss: 2.6327 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6327 2023/06/04 19:31:22 - mmengine - INFO - Epoch(train) [17][1960/2569] lr: 4.0000e-02 eta: 1 day, 1:23:19 time: 0.2644 data_time: 0.0076 memory: 5828 grad_norm: 2.7693 loss: 2.4795 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4795 2023/06/04 19:31:27 - mmengine - INFO - Epoch(train) [17][1980/2569] lr: 4.0000e-02 eta: 1 day, 1:23:13 time: 0.2608 data_time: 0.0077 memory: 5828 grad_norm: 2.8436 loss: 2.6881 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6881 2023/06/04 19:31:32 - mmengine - INFO - Epoch(train) [17][2000/2569] lr: 4.0000e-02 eta: 1 day, 1:23:07 time: 0.2612 data_time: 0.0078 memory: 5828 grad_norm: 2.8788 loss: 2.3806 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3806 2023/06/04 19:31:37 - mmengine - INFO - Epoch(train) [17][2020/2569] lr: 4.0000e-02 eta: 1 day, 1:23:00 time: 0.2607 data_time: 0.0081 memory: 5828 grad_norm: 2.8206 loss: 2.4778 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4778 2023/06/04 19:31:43 - mmengine - INFO - Epoch(train) [17][2040/2569] lr: 4.0000e-02 eta: 1 day, 1:22:55 time: 0.2636 data_time: 0.0079 memory: 5828 grad_norm: 2.8433 loss: 2.4350 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4350 2023/06/04 19:31:48 - mmengine - INFO - Epoch(train) [17][2060/2569] lr: 4.0000e-02 eta: 1 day, 1:22:50 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 2.8542 loss: 2.8499 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8499 2023/06/04 19:31:53 - mmengine - INFO - Epoch(train) [17][2080/2569] lr: 4.0000e-02 eta: 1 day, 1:22:45 time: 0.2707 data_time: 0.0078 memory: 5828 grad_norm: 2.8453 loss: 2.7408 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7408 2023/06/04 19:31:59 - mmengine - INFO - Epoch(train) [17][2100/2569] lr: 4.0000e-02 eta: 1 day, 1:22:40 time: 0.2708 data_time: 0.0075 memory: 5828 grad_norm: 2.8286 loss: 2.6486 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6486 2023/06/04 19:32:04 - mmengine - INFO - Epoch(train) [17][2120/2569] lr: 4.0000e-02 eta: 1 day, 1:22:36 time: 0.2720 data_time: 0.0078 memory: 5828 grad_norm: 2.8541 loss: 2.6058 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6058 2023/06/04 19:32:10 - mmengine - INFO - Epoch(train) [17][2140/2569] lr: 4.0000e-02 eta: 1 day, 1:22:31 time: 0.2683 data_time: 0.0086 memory: 5828 grad_norm: 2.8119 loss: 2.4498 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4498 2023/06/04 19:32:15 - mmengine - INFO - Epoch(train) [17][2160/2569] lr: 4.0000e-02 eta: 1 day, 1:22:25 time: 0.2647 data_time: 0.0084 memory: 5828 grad_norm: 2.8489 loss: 2.3380 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3380 2023/06/04 19:32:20 - mmengine - INFO - Epoch(train) [17][2180/2569] lr: 4.0000e-02 eta: 1 day, 1:22:20 time: 0.2674 data_time: 0.0078 memory: 5828 grad_norm: 2.8207 loss: 3.0007 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0007 2023/06/04 19:32:25 - mmengine - INFO - Epoch(train) [17][2200/2569] lr: 4.0000e-02 eta: 1 day, 1:22:13 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 2.8470 loss: 2.5060 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5060 2023/06/04 19:32:31 - mmengine - INFO - Epoch(train) [17][2220/2569] lr: 4.0000e-02 eta: 1 day, 1:22:07 time: 0.2615 data_time: 0.0083 memory: 5828 grad_norm: 2.8270 loss: 2.6993 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6993 2023/06/04 19:32:36 - mmengine - INFO - Epoch(train) [17][2240/2569] lr: 4.0000e-02 eta: 1 day, 1:22:00 time: 0.2600 data_time: 0.0078 memory: 5828 grad_norm: 2.7831 loss: 2.5241 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5241 2023/06/04 19:32:41 - mmengine - INFO - Epoch(train) [17][2260/2569] lr: 4.0000e-02 eta: 1 day, 1:21:55 time: 0.2664 data_time: 0.0079 memory: 5828 grad_norm: 2.7799 loss: 2.5986 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5986 2023/06/04 19:32:46 - mmengine - INFO - Epoch(train) [17][2280/2569] lr: 4.0000e-02 eta: 1 day, 1:21:49 time: 0.2594 data_time: 0.0087 memory: 5828 grad_norm: 2.8349 loss: 2.6092 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6092 2023/06/04 19:32:52 - mmengine - INFO - Epoch(train) [17][2300/2569] lr: 4.0000e-02 eta: 1 day, 1:21:43 time: 0.2631 data_time: 0.0077 memory: 5828 grad_norm: 2.8556 loss: 2.6140 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6140 2023/06/04 19:32:57 - mmengine - INFO - Epoch(train) [17][2320/2569] lr: 4.0000e-02 eta: 1 day, 1:21:37 time: 0.2649 data_time: 0.0081 memory: 5828 grad_norm: 2.7913 loss: 2.6489 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6489 2023/06/04 19:33:02 - mmengine - INFO - Epoch(train) [17][2340/2569] lr: 4.0000e-02 eta: 1 day, 1:21:33 time: 0.2733 data_time: 0.0077 memory: 5828 grad_norm: 2.7929 loss: 3.0138 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0138 2023/06/04 19:33:08 - mmengine - INFO - Epoch(train) [17][2360/2569] lr: 4.0000e-02 eta: 1 day, 1:21:26 time: 0.2616 data_time: 0.0076 memory: 5828 grad_norm: 2.8583 loss: 2.7202 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7202 2023/06/04 19:33:13 - mmengine - INFO - Epoch(train) [17][2380/2569] lr: 4.0000e-02 eta: 1 day, 1:21:23 time: 0.2778 data_time: 0.0076 memory: 5828 grad_norm: 2.8635 loss: 2.4829 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4829 2023/06/04 19:33:19 - mmengine - INFO - Epoch(train) [17][2400/2569] lr: 4.0000e-02 eta: 1 day, 1:21:17 time: 0.2655 data_time: 0.0081 memory: 5828 grad_norm: 2.8653 loss: 2.5601 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5601 2023/06/04 19:33:24 - mmengine - INFO - Epoch(train) [17][2420/2569] lr: 4.0000e-02 eta: 1 day, 1:21:13 time: 0.2736 data_time: 0.0076 memory: 5828 grad_norm: 2.8473 loss: 2.9089 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9089 2023/06/04 19:33:29 - mmengine - INFO - Epoch(train) [17][2440/2569] lr: 4.0000e-02 eta: 1 day, 1:21:07 time: 0.2649 data_time: 0.0080 memory: 5828 grad_norm: 2.8749 loss: 2.5217 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5217 2023/06/04 19:33:35 - mmengine - INFO - Epoch(train) [17][2460/2569] lr: 4.0000e-02 eta: 1 day, 1:21:02 time: 0.2711 data_time: 0.0079 memory: 5828 grad_norm: 2.8143 loss: 2.6823 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6823 2023/06/04 19:33:40 - mmengine - INFO - Epoch(train) [17][2480/2569] lr: 4.0000e-02 eta: 1 day, 1:20:56 time: 0.2624 data_time: 0.0083 memory: 5828 grad_norm: 2.7976 loss: 2.6840 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6840 2023/06/04 19:33:45 - mmengine - INFO - Epoch(train) [17][2500/2569] lr: 4.0000e-02 eta: 1 day, 1:20:51 time: 0.2672 data_time: 0.0079 memory: 5828 grad_norm: 2.8430 loss: 2.6813 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6813 2023/06/04 19:33:51 - mmengine - INFO - Epoch(train) [17][2520/2569] lr: 4.0000e-02 eta: 1 day, 1:20:46 time: 0.2668 data_time: 0.0082 memory: 5828 grad_norm: 2.8498 loss: 2.5462 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5462 2023/06/04 19:33:56 - mmengine - INFO - Epoch(train) [17][2540/2569] lr: 4.0000e-02 eta: 1 day, 1:20:40 time: 0.2663 data_time: 0.0078 memory: 5828 grad_norm: 2.8406 loss: 2.2520 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2520 2023/06/04 19:34:01 - mmengine - INFO - Epoch(train) [17][2560/2569] lr: 4.0000e-02 eta: 1 day, 1:20:33 time: 0.2577 data_time: 0.0080 memory: 5828 grad_norm: 2.8421 loss: 2.6011 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6011 2023/06/04 19:34:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:34:03 - mmengine - INFO - Epoch(train) [17][2569/2569] lr: 4.0000e-02 eta: 1 day, 1:20:29 time: 0.2493 data_time: 0.0080 memory: 5828 grad_norm: 2.8405 loss: 2.5368 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5368 2023/06/04 19:34:10 - mmengine - INFO - Epoch(train) [18][ 20/2569] lr: 4.0000e-02 eta: 1 day, 1:20:37 time: 0.3491 data_time: 0.0661 memory: 5828 grad_norm: 2.8513 loss: 2.4588 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4588 2023/06/04 19:34:16 - mmengine - INFO - Epoch(train) [18][ 40/2569] lr: 4.0000e-02 eta: 1 day, 1:20:32 time: 0.2708 data_time: 0.0077 memory: 5828 grad_norm: 2.8839 loss: 2.1103 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1103 2023/06/04 19:34:21 - mmengine - INFO - Epoch(train) [18][ 60/2569] lr: 4.0000e-02 eta: 1 day, 1:20:27 time: 0.2656 data_time: 0.0082 memory: 5828 grad_norm: 2.7968 loss: 2.6967 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6967 2023/06/04 19:34:26 - mmengine - INFO - Epoch(train) [18][ 80/2569] lr: 4.0000e-02 eta: 1 day, 1:20:21 time: 0.2680 data_time: 0.0082 memory: 5828 grad_norm: 2.8212 loss: 2.4271 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4271 2023/06/04 19:34:32 - mmengine - INFO - Epoch(train) [18][ 100/2569] lr: 4.0000e-02 eta: 1 day, 1:20:15 time: 0.2617 data_time: 0.0076 memory: 5828 grad_norm: 2.8416 loss: 2.2199 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2199 2023/06/04 19:34:37 - mmengine - INFO - Epoch(train) [18][ 120/2569] lr: 4.0000e-02 eta: 1 day, 1:20:09 time: 0.2625 data_time: 0.0082 memory: 5828 grad_norm: 2.8495 loss: 2.6653 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6653 2023/06/04 19:34:42 - mmengine - INFO - Epoch(train) [18][ 140/2569] lr: 4.0000e-02 eta: 1 day, 1:20:05 time: 0.2724 data_time: 0.0082 memory: 5828 grad_norm: 2.8463 loss: 2.5823 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5823 2023/06/04 19:34:48 - mmengine - INFO - Epoch(train) [18][ 160/2569] lr: 4.0000e-02 eta: 1 day, 1:19:58 time: 0.2609 data_time: 0.0079 memory: 5828 grad_norm: 2.8894 loss: 2.6364 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6364 2023/06/04 19:34:53 - mmengine - INFO - Epoch(train) [18][ 180/2569] lr: 4.0000e-02 eta: 1 day, 1:19:52 time: 0.2605 data_time: 0.0083 memory: 5828 grad_norm: 2.7850 loss: 2.8201 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8201 2023/06/04 19:34:58 - mmengine - INFO - Epoch(train) [18][ 200/2569] lr: 4.0000e-02 eta: 1 day, 1:19:46 time: 0.2649 data_time: 0.0079 memory: 5828 grad_norm: 2.8643 loss: 2.4096 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4096 2023/06/04 19:35:04 - mmengine - INFO - Epoch(train) [18][ 220/2569] lr: 4.0000e-02 eta: 1 day, 1:19:42 time: 0.2714 data_time: 0.0085 memory: 5828 grad_norm: 2.8602 loss: 2.5720 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5720 2023/06/04 19:35:09 - mmengine - INFO - Epoch(train) [18][ 240/2569] lr: 4.0000e-02 eta: 1 day, 1:19:36 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 2.8385 loss: 2.4825 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4825 2023/06/04 19:35:14 - mmengine - INFO - Epoch(train) [18][ 260/2569] lr: 4.0000e-02 eta: 1 day, 1:19:31 time: 0.2715 data_time: 0.0078 memory: 5828 grad_norm: 2.8612 loss: 2.7029 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7029 2023/06/04 19:35:20 - mmengine - INFO - Epoch(train) [18][ 280/2569] lr: 4.0000e-02 eta: 1 day, 1:19:25 time: 0.2621 data_time: 0.0081 memory: 5828 grad_norm: 2.8111 loss: 2.6816 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6816 2023/06/04 19:35:25 - mmengine - INFO - Epoch(train) [18][ 300/2569] lr: 4.0000e-02 eta: 1 day, 1:19:21 time: 0.2761 data_time: 0.0079 memory: 5828 grad_norm: 2.8127 loss: 2.6267 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6267 2023/06/04 19:35:30 - mmengine - INFO - Epoch(train) [18][ 320/2569] lr: 4.0000e-02 eta: 1 day, 1:19:16 time: 0.2690 data_time: 0.0079 memory: 5828 grad_norm: 2.8413 loss: 2.7452 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7452 2023/06/04 19:35:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:35:36 - mmengine - INFO - Epoch(train) [18][ 340/2569] lr: 4.0000e-02 eta: 1 day, 1:19:11 time: 0.2669 data_time: 0.0077 memory: 5828 grad_norm: 2.8239 loss: 2.5725 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5725 2023/06/04 19:35:41 - mmengine - INFO - Epoch(train) [18][ 360/2569] lr: 4.0000e-02 eta: 1 day, 1:19:05 time: 0.2657 data_time: 0.0071 memory: 5828 grad_norm: 2.8438 loss: 2.7514 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7514 2023/06/04 19:35:47 - mmengine - INFO - Epoch(train) [18][ 380/2569] lr: 4.0000e-02 eta: 1 day, 1:19:02 time: 0.2782 data_time: 0.0076 memory: 5828 grad_norm: 2.8312 loss: 2.7998 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7998 2023/06/04 19:35:52 - mmengine - INFO - Epoch(train) [18][ 400/2569] lr: 4.0000e-02 eta: 1 day, 1:18:57 time: 0.2723 data_time: 0.0077 memory: 5828 grad_norm: 2.7980 loss: 2.4908 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4908 2023/06/04 19:35:58 - mmengine - INFO - Epoch(train) [18][ 420/2569] lr: 4.0000e-02 eta: 1 day, 1:18:52 time: 0.2706 data_time: 0.0078 memory: 5828 grad_norm: 2.8499 loss: 2.6407 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6407 2023/06/04 19:36:03 - mmengine - INFO - Epoch(train) [18][ 440/2569] lr: 4.0000e-02 eta: 1 day, 1:18:47 time: 0.2691 data_time: 0.0079 memory: 5828 grad_norm: 2.8061 loss: 2.7735 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7735 2023/06/04 19:36:08 - mmengine - INFO - Epoch(train) [18][ 460/2569] lr: 4.0000e-02 eta: 1 day, 1:18:42 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 2.8650 loss: 2.7385 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7385 2023/06/04 19:36:13 - mmengine - INFO - Epoch(train) [18][ 480/2569] lr: 4.0000e-02 eta: 1 day, 1:18:36 time: 0.2598 data_time: 0.0083 memory: 5828 grad_norm: 2.8189 loss: 2.4097 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4097 2023/06/04 19:36:19 - mmengine - INFO - Epoch(train) [18][ 500/2569] lr: 4.0000e-02 eta: 1 day, 1:18:31 time: 0.2708 data_time: 0.0079 memory: 5828 grad_norm: 2.8225 loss: 2.4682 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4682 2023/06/04 19:36:24 - mmengine - INFO - Epoch(train) [18][ 520/2569] lr: 4.0000e-02 eta: 1 day, 1:18:25 time: 0.2619 data_time: 0.0083 memory: 5828 grad_norm: 2.8474 loss: 2.7558 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7558 2023/06/04 19:36:29 - mmengine - INFO - Epoch(train) [18][ 540/2569] lr: 4.0000e-02 eta: 1 day, 1:18:20 time: 0.2709 data_time: 0.0076 memory: 5828 grad_norm: 2.8518 loss: 2.5133 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5133 2023/06/04 19:36:35 - mmengine - INFO - Epoch(train) [18][ 560/2569] lr: 4.0000e-02 eta: 1 day, 1:18:14 time: 0.2610 data_time: 0.0079 memory: 5828 grad_norm: 2.8375 loss: 2.6887 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6887 2023/06/04 19:36:40 - mmengine - INFO - Epoch(train) [18][ 580/2569] lr: 4.0000e-02 eta: 1 day, 1:18:08 time: 0.2663 data_time: 0.0081 memory: 5828 grad_norm: 2.8139 loss: 2.6017 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6017 2023/06/04 19:36:45 - mmengine - INFO - Epoch(train) [18][ 600/2569] lr: 4.0000e-02 eta: 1 day, 1:18:02 time: 0.2619 data_time: 0.0081 memory: 5828 grad_norm: 2.8349 loss: 2.7161 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7161 2023/06/04 19:36:51 - mmengine - INFO - Epoch(train) [18][ 620/2569] lr: 4.0000e-02 eta: 1 day, 1:17:56 time: 0.2608 data_time: 0.0082 memory: 5828 grad_norm: 2.8396 loss: 2.6904 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6904 2023/06/04 19:36:56 - mmengine - INFO - Epoch(train) [18][ 640/2569] lr: 4.0000e-02 eta: 1 day, 1:17:52 time: 0.2771 data_time: 0.0077 memory: 5828 grad_norm: 2.8359 loss: 2.6347 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.6347 2023/06/04 19:37:02 - mmengine - INFO - Epoch(train) [18][ 660/2569] lr: 4.0000e-02 eta: 1 day, 1:17:48 time: 0.2777 data_time: 0.0079 memory: 5828 grad_norm: 2.8636 loss: 2.3920 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3920 2023/06/04 19:37:07 - mmengine - INFO - Epoch(train) [18][ 680/2569] lr: 4.0000e-02 eta: 1 day, 1:17:42 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 2.8842 loss: 2.4744 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4744 2023/06/04 19:37:12 - mmengine - INFO - Epoch(train) [18][ 700/2569] lr: 4.0000e-02 eta: 1 day, 1:17:36 time: 0.2636 data_time: 0.0076 memory: 5828 grad_norm: 2.8219 loss: 2.5989 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5989 2023/06/04 19:37:17 - mmengine - INFO - Epoch(train) [18][ 720/2569] lr: 4.0000e-02 eta: 1 day, 1:17:30 time: 0.2597 data_time: 0.0085 memory: 5828 grad_norm: 2.8614 loss: 2.4486 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4486 2023/06/04 19:37:23 - mmengine - INFO - Epoch(train) [18][ 740/2569] lr: 4.0000e-02 eta: 1 day, 1:17:26 time: 0.2820 data_time: 0.0072 memory: 5828 grad_norm: 2.8243 loss: 2.7941 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7941 2023/06/04 19:37:28 - mmengine - INFO - Epoch(train) [18][ 760/2569] lr: 4.0000e-02 eta: 1 day, 1:17:21 time: 0.2670 data_time: 0.0080 memory: 5828 grad_norm: 2.8594 loss: 2.7045 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7045 2023/06/04 19:37:34 - mmengine - INFO - Epoch(train) [18][ 780/2569] lr: 4.0000e-02 eta: 1 day, 1:17:16 time: 0.2667 data_time: 0.0083 memory: 5828 grad_norm: 2.8294 loss: 2.4191 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4191 2023/06/04 19:37:39 - mmengine - INFO - Epoch(train) [18][ 800/2569] lr: 4.0000e-02 eta: 1 day, 1:17:10 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 2.8167 loss: 2.5309 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5309 2023/06/04 19:37:44 - mmengine - INFO - Epoch(train) [18][ 820/2569] lr: 4.0000e-02 eta: 1 day, 1:17:05 time: 0.2724 data_time: 0.0078 memory: 5828 grad_norm: 2.8841 loss: 2.6399 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6399 2023/06/04 19:37:50 - mmengine - INFO - Epoch(train) [18][ 840/2569] lr: 4.0000e-02 eta: 1 day, 1:16:59 time: 0.2610 data_time: 0.0082 memory: 5828 grad_norm: 2.8691 loss: 2.5862 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5862 2023/06/04 19:37:55 - mmengine - INFO - Epoch(train) [18][ 860/2569] lr: 4.0000e-02 eta: 1 day, 1:16:53 time: 0.2645 data_time: 0.0075 memory: 5828 grad_norm: 2.8244 loss: 2.4613 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4613 2023/06/04 19:38:00 - mmengine - INFO - Epoch(train) [18][ 880/2569] lr: 4.0000e-02 eta: 1 day, 1:16:47 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 2.8215 loss: 2.6438 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6438 2023/06/04 19:38:05 - mmengine - INFO - Epoch(train) [18][ 900/2569] lr: 4.0000e-02 eta: 1 day, 1:16:42 time: 0.2709 data_time: 0.0078 memory: 5828 grad_norm: 2.8190 loss: 2.4957 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4957 2023/06/04 19:38:11 - mmengine - INFO - Epoch(train) [18][ 920/2569] lr: 4.0000e-02 eta: 1 day, 1:16:36 time: 0.2604 data_time: 0.0075 memory: 5828 grad_norm: 2.7938 loss: 2.7097 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7097 2023/06/04 19:38:16 - mmengine - INFO - Epoch(train) [18][ 940/2569] lr: 4.0000e-02 eta: 1 day, 1:16:31 time: 0.2671 data_time: 0.0080 memory: 5828 grad_norm: 2.8169 loss: 2.7923 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7923 2023/06/04 19:38:21 - mmengine - INFO - Epoch(train) [18][ 960/2569] lr: 4.0000e-02 eta: 1 day, 1:16:26 time: 0.2713 data_time: 0.0077 memory: 5828 grad_norm: 2.8107 loss: 2.8609 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8609 2023/06/04 19:38:27 - mmengine - INFO - Epoch(train) [18][ 980/2569] lr: 4.0000e-02 eta: 1 day, 1:16:20 time: 0.2670 data_time: 0.0080 memory: 5828 grad_norm: 2.8225 loss: 2.7617 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7617 2023/06/04 19:38:32 - mmengine - INFO - Epoch(train) [18][1000/2569] lr: 4.0000e-02 eta: 1 day, 1:16:16 time: 0.2698 data_time: 0.0079 memory: 5828 grad_norm: 2.8684 loss: 2.6992 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6992 2023/06/04 19:38:38 - mmengine - INFO - Epoch(train) [18][1020/2569] lr: 4.0000e-02 eta: 1 day, 1:16:10 time: 0.2688 data_time: 0.0081 memory: 5828 grad_norm: 2.8545 loss: 2.8879 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8879 2023/06/04 19:38:43 - mmengine - INFO - Epoch(train) [18][1040/2569] lr: 4.0000e-02 eta: 1 day, 1:16:06 time: 0.2717 data_time: 0.0079 memory: 5828 grad_norm: 2.7998 loss: 2.5266 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5266 2023/06/04 19:38:48 - mmengine - INFO - Epoch(train) [18][1060/2569] lr: 4.0000e-02 eta: 1 day, 1:16:00 time: 0.2621 data_time: 0.0079 memory: 5828 grad_norm: 2.8815 loss: 2.4302 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4302 2023/06/04 19:38:54 - mmengine - INFO - Epoch(train) [18][1080/2569] lr: 4.0000e-02 eta: 1 day, 1:15:54 time: 0.2674 data_time: 0.0083 memory: 5828 grad_norm: 2.7994 loss: 2.4282 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4282 2023/06/04 19:38:59 - mmengine - INFO - Epoch(train) [18][1100/2569] lr: 4.0000e-02 eta: 1 day, 1:15:48 time: 0.2622 data_time: 0.0081 memory: 5828 grad_norm: 2.8312 loss: 2.6638 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6638 2023/06/04 19:39:04 - mmengine - INFO - Epoch(train) [18][1120/2569] lr: 4.0000e-02 eta: 1 day, 1:15:43 time: 0.2652 data_time: 0.0076 memory: 5828 grad_norm: 2.8310 loss: 2.5341 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5341 2023/06/04 19:39:09 - mmengine - INFO - Epoch(train) [18][1140/2569] lr: 4.0000e-02 eta: 1 day, 1:15:37 time: 0.2667 data_time: 0.0078 memory: 5828 grad_norm: 2.8066 loss: 2.4875 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4875 2023/06/04 19:39:15 - mmengine - INFO - Epoch(train) [18][1160/2569] lr: 4.0000e-02 eta: 1 day, 1:15:31 time: 0.2603 data_time: 0.0078 memory: 5828 grad_norm: 2.9025 loss: 2.7644 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7644 2023/06/04 19:39:20 - mmengine - INFO - Epoch(train) [18][1180/2569] lr: 4.0000e-02 eta: 1 day, 1:15:25 time: 0.2604 data_time: 0.0081 memory: 5828 grad_norm: 2.8047 loss: 2.7442 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7442 2023/06/04 19:39:25 - mmengine - INFO - Epoch(train) [18][1200/2569] lr: 4.0000e-02 eta: 1 day, 1:15:20 time: 0.2697 data_time: 0.0084 memory: 5828 grad_norm: 2.8318 loss: 2.6812 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6812 2023/06/04 19:39:31 - mmengine - INFO - Epoch(train) [18][1220/2569] lr: 4.0000e-02 eta: 1 day, 1:15:14 time: 0.2618 data_time: 0.0078 memory: 5828 grad_norm: 2.9058 loss: 2.7778 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7778 2023/06/04 19:39:36 - mmengine - INFO - Epoch(train) [18][1240/2569] lr: 4.0000e-02 eta: 1 day, 1:15:09 time: 0.2707 data_time: 0.0076 memory: 5828 grad_norm: 2.8759 loss: 3.2797 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.2797 2023/06/04 19:39:41 - mmengine - INFO - Epoch(train) [18][1260/2569] lr: 4.0000e-02 eta: 1 day, 1:15:02 time: 0.2602 data_time: 0.0082 memory: 5828 grad_norm: 2.8790 loss: 2.7314 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7314 2023/06/04 19:39:47 - mmengine - INFO - Epoch(train) [18][1280/2569] lr: 4.0000e-02 eta: 1 day, 1:14:58 time: 0.2733 data_time: 0.0074 memory: 5828 grad_norm: 2.8336 loss: 2.6007 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6007 2023/06/04 19:39:52 - mmengine - INFO - Epoch(train) [18][1300/2569] lr: 4.0000e-02 eta: 1 day, 1:14:52 time: 0.2606 data_time: 0.0083 memory: 5828 grad_norm: 2.8674 loss: 2.6676 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6676 2023/06/04 19:39:57 - mmengine - INFO - Epoch(train) [18][1320/2569] lr: 4.0000e-02 eta: 1 day, 1:14:47 time: 0.2689 data_time: 0.0078 memory: 5828 grad_norm: 2.8155 loss: 2.4689 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4689 2023/06/04 19:39:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:40:03 - mmengine - INFO - Epoch(train) [18][1340/2569] lr: 4.0000e-02 eta: 1 day, 1:14:41 time: 0.2680 data_time: 0.0077 memory: 5828 grad_norm: 2.8717 loss: 2.4646 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4646 2023/06/04 19:40:08 - mmengine - INFO - Epoch(train) [18][1360/2569] lr: 4.0000e-02 eta: 1 day, 1:14:35 time: 0.2607 data_time: 0.0080 memory: 5828 grad_norm: 2.8057 loss: 2.6941 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6941 2023/06/04 19:40:13 - mmengine - INFO - Epoch(train) [18][1380/2569] lr: 4.0000e-02 eta: 1 day, 1:14:30 time: 0.2657 data_time: 0.0084 memory: 5828 grad_norm: 2.8710 loss: 2.3731 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3731 2023/06/04 19:40:19 - mmengine - INFO - Epoch(train) [18][1400/2569] lr: 4.0000e-02 eta: 1 day, 1:14:25 time: 0.2747 data_time: 0.0075 memory: 5828 grad_norm: 2.8932 loss: 2.5662 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5662 2023/06/04 19:40:24 - mmengine - INFO - Epoch(train) [18][1420/2569] lr: 4.0000e-02 eta: 1 day, 1:14:21 time: 0.2731 data_time: 0.0076 memory: 5828 grad_norm: 2.8095 loss: 2.5592 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5592 2023/06/04 19:40:29 - mmengine - INFO - Epoch(train) [18][1440/2569] lr: 4.0000e-02 eta: 1 day, 1:14:15 time: 0.2628 data_time: 0.0077 memory: 5828 grad_norm: 2.8170 loss: 2.7953 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7953 2023/06/04 19:40:35 - mmengine - INFO - Epoch(train) [18][1460/2569] lr: 4.0000e-02 eta: 1 day, 1:14:10 time: 0.2714 data_time: 0.0080 memory: 5828 grad_norm: 2.8246 loss: 2.4533 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4533 2023/06/04 19:40:40 - mmengine - INFO - Epoch(train) [18][1480/2569] lr: 4.0000e-02 eta: 1 day, 1:14:05 time: 0.2697 data_time: 0.0080 memory: 5828 grad_norm: 2.8939 loss: 2.6696 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6696 2023/06/04 19:40:46 - mmengine - INFO - Epoch(train) [18][1500/2569] lr: 4.0000e-02 eta: 1 day, 1:14:00 time: 0.2689 data_time: 0.0077 memory: 5828 grad_norm: 2.8305 loss: 2.7249 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7249 2023/06/04 19:40:51 - mmengine - INFO - Epoch(train) [18][1520/2569] lr: 4.0000e-02 eta: 1 day, 1:13:55 time: 0.2663 data_time: 0.0079 memory: 5828 grad_norm: 2.7978 loss: 2.5570 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5570 2023/06/04 19:40:56 - mmengine - INFO - Epoch(train) [18][1540/2569] lr: 4.0000e-02 eta: 1 day, 1:13:49 time: 0.2660 data_time: 0.0080 memory: 5828 grad_norm: 2.8489 loss: 2.5854 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5854 2023/06/04 19:41:02 - mmengine - INFO - Epoch(train) [18][1560/2569] lr: 4.0000e-02 eta: 1 day, 1:13:44 time: 0.2682 data_time: 0.0080 memory: 5828 grad_norm: 2.8746 loss: 2.5980 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5980 2023/06/04 19:41:07 - mmengine - INFO - Epoch(train) [18][1580/2569] lr: 4.0000e-02 eta: 1 day, 1:13:38 time: 0.2626 data_time: 0.0078 memory: 5828 grad_norm: 2.9017 loss: 3.0253 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.0253 2023/06/04 19:41:12 - mmengine - INFO - Epoch(train) [18][1600/2569] lr: 4.0000e-02 eta: 1 day, 1:13:33 time: 0.2664 data_time: 0.0082 memory: 5828 grad_norm: 2.8151 loss: 2.4091 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4091 2023/06/04 19:41:18 - mmengine - INFO - Epoch(train) [18][1620/2569] lr: 4.0000e-02 eta: 1 day, 1:13:28 time: 0.2683 data_time: 0.0080 memory: 5828 grad_norm: 2.8129 loss: 2.2853 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2853 2023/06/04 19:41:23 - mmengine - INFO - Epoch(train) [18][1640/2569] lr: 4.0000e-02 eta: 1 day, 1:13:22 time: 0.2631 data_time: 0.0077 memory: 5828 grad_norm: 2.8059 loss: 2.7036 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7036 2023/06/04 19:41:28 - mmengine - INFO - Epoch(train) [18][1660/2569] lr: 4.0000e-02 eta: 1 day, 1:13:16 time: 0.2653 data_time: 0.0078 memory: 5828 grad_norm: 2.8278 loss: 2.6891 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6891 2023/06/04 19:41:33 - mmengine - INFO - Epoch(train) [18][1680/2569] lr: 4.0000e-02 eta: 1 day, 1:13:10 time: 0.2612 data_time: 0.0081 memory: 5828 grad_norm: 2.8278 loss: 2.6647 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6647 2023/06/04 19:41:38 - mmengine - INFO - Epoch(train) [18][1700/2569] lr: 4.0000e-02 eta: 1 day, 1:13:03 time: 0.2596 data_time: 0.0083 memory: 5828 grad_norm: 2.8421 loss: 2.9095 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9095 2023/06/04 19:41:44 - mmengine - INFO - Epoch(train) [18][1720/2569] lr: 4.0000e-02 eta: 1 day, 1:12:57 time: 0.2618 data_time: 0.0079 memory: 5828 grad_norm: 2.8923 loss: 2.8369 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8369 2023/06/04 19:41:49 - mmengine - INFO - Epoch(train) [18][1740/2569] lr: 4.0000e-02 eta: 1 day, 1:12:51 time: 0.2614 data_time: 0.0078 memory: 5828 grad_norm: 2.9025 loss: 2.5397 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5397 2023/06/04 19:41:54 - mmengine - INFO - Epoch(train) [18][1760/2569] lr: 4.0000e-02 eta: 1 day, 1:12:45 time: 0.2606 data_time: 0.0080 memory: 5828 grad_norm: 2.8183 loss: 2.5043 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5043 2023/06/04 19:41:59 - mmengine - INFO - Epoch(train) [18][1780/2569] lr: 4.0000e-02 eta: 1 day, 1:12:39 time: 0.2622 data_time: 0.0076 memory: 5828 grad_norm: 2.8273 loss: 2.5297 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5297 2023/06/04 19:42:05 - mmengine - INFO - Epoch(train) [18][1800/2569] lr: 4.0000e-02 eta: 1 day, 1:12:34 time: 0.2737 data_time: 0.0077 memory: 5828 grad_norm: 2.8594 loss: 2.7739 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7739 2023/06/04 19:42:10 - mmengine - INFO - Epoch(train) [18][1820/2569] lr: 4.0000e-02 eta: 1 day, 1:12:30 time: 0.2718 data_time: 0.0079 memory: 5828 grad_norm: 2.8443 loss: 2.7956 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7956 2023/06/04 19:42:16 - mmengine - INFO - Epoch(train) [18][1840/2569] lr: 4.0000e-02 eta: 1 day, 1:12:26 time: 0.2771 data_time: 0.0075 memory: 5828 grad_norm: 2.8704 loss: 2.5702 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5702 2023/06/04 19:42:21 - mmengine - INFO - Epoch(train) [18][1860/2569] lr: 4.0000e-02 eta: 1 day, 1:12:20 time: 0.2660 data_time: 0.0082 memory: 5828 grad_norm: 2.8765 loss: 2.3675 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3675 2023/06/04 19:42:27 - mmengine - INFO - Epoch(train) [18][1880/2569] lr: 4.0000e-02 eta: 1 day, 1:12:17 time: 0.2810 data_time: 0.0080 memory: 5828 grad_norm: 2.8444 loss: 2.6826 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6826 2023/06/04 19:42:32 - mmengine - INFO - Epoch(train) [18][1900/2569] lr: 4.0000e-02 eta: 1 day, 1:12:11 time: 0.2621 data_time: 0.0080 memory: 5828 grad_norm: 2.8365 loss: 2.4762 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4762 2023/06/04 19:42:37 - mmengine - INFO - Epoch(train) [18][1920/2569] lr: 4.0000e-02 eta: 1 day, 1:12:06 time: 0.2697 data_time: 0.0079 memory: 5828 grad_norm: 2.8831 loss: 2.4607 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4607 2023/06/04 19:42:43 - mmengine - INFO - Epoch(train) [18][1940/2569] lr: 4.0000e-02 eta: 1 day, 1:12:01 time: 0.2662 data_time: 0.0079 memory: 5828 grad_norm: 2.8262 loss: 2.7536 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7536 2023/06/04 19:42:48 - mmengine - INFO - Epoch(train) [18][1960/2569] lr: 4.0000e-02 eta: 1 day, 1:11:57 time: 0.2766 data_time: 0.0083 memory: 5828 grad_norm: 2.8223 loss: 2.8116 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8116 2023/06/04 19:42:54 - mmengine - INFO - Epoch(train) [18][1980/2569] lr: 4.0000e-02 eta: 1 day, 1:11:53 time: 0.2792 data_time: 0.0080 memory: 5828 grad_norm: 2.8289 loss: 2.3961 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3961 2023/06/04 19:42:59 - mmengine - INFO - Epoch(train) [18][2000/2569] lr: 4.0000e-02 eta: 1 day, 1:11:48 time: 0.2659 data_time: 0.0079 memory: 5828 grad_norm: 2.8135 loss: 2.7644 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7644 2023/06/04 19:43:05 - mmengine - INFO - Epoch(train) [18][2020/2569] lr: 4.0000e-02 eta: 1 day, 1:11:42 time: 0.2642 data_time: 0.0072 memory: 5828 grad_norm: 2.8403 loss: 2.5557 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5557 2023/06/04 19:43:10 - mmengine - INFO - Epoch(train) [18][2040/2569] lr: 4.0000e-02 eta: 1 day, 1:11:36 time: 0.2640 data_time: 0.0078 memory: 5828 grad_norm: 2.8249 loss: 2.4248 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4248 2023/06/04 19:43:15 - mmengine - INFO - Epoch(train) [18][2060/2569] lr: 4.0000e-02 eta: 1 day, 1:11:30 time: 0.2641 data_time: 0.0078 memory: 5828 grad_norm: 2.8650 loss: 2.7214 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7214 2023/06/04 19:43:20 - mmengine - INFO - Epoch(train) [18][2080/2569] lr: 4.0000e-02 eta: 1 day, 1:11:24 time: 0.2607 data_time: 0.0074 memory: 5828 grad_norm: 2.8445 loss: 2.4822 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4822 2023/06/04 19:43:26 - mmengine - INFO - Epoch(train) [18][2100/2569] lr: 4.0000e-02 eta: 1 day, 1:11:19 time: 0.2689 data_time: 0.0077 memory: 5828 grad_norm: 2.8742 loss: 2.6623 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6623 2023/06/04 19:43:31 - mmengine - INFO - Epoch(train) [18][2120/2569] lr: 4.0000e-02 eta: 1 day, 1:11:14 time: 0.2717 data_time: 0.0075 memory: 5828 grad_norm: 2.8759 loss: 2.7730 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7730 2023/06/04 19:43:37 - mmengine - INFO - Epoch(train) [18][2140/2569] lr: 4.0000e-02 eta: 1 day, 1:11:10 time: 0.2706 data_time: 0.0083 memory: 5828 grad_norm: 2.8554 loss: 2.7516 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7516 2023/06/04 19:43:42 - mmengine - INFO - Epoch(train) [18][2160/2569] lr: 4.0000e-02 eta: 1 day, 1:11:03 time: 0.2610 data_time: 0.0084 memory: 5828 grad_norm: 2.8111 loss: 2.5778 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5778 2023/06/04 19:43:47 - mmengine - INFO - Epoch(train) [18][2180/2569] lr: 4.0000e-02 eta: 1 day, 1:10:58 time: 0.2659 data_time: 0.0087 memory: 5828 grad_norm: 2.8662 loss: 2.4881 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4881 2023/06/04 19:43:52 - mmengine - INFO - Epoch(train) [18][2200/2569] lr: 4.0000e-02 eta: 1 day, 1:10:52 time: 0.2626 data_time: 0.0075 memory: 5828 grad_norm: 2.8602 loss: 2.7139 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 2.7139 2023/06/04 19:43:58 - mmengine - INFO - Epoch(train) [18][2220/2569] lr: 4.0000e-02 eta: 1 day, 1:10:47 time: 0.2688 data_time: 0.0079 memory: 5828 grad_norm: 2.7972 loss: 2.6897 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6897 2023/06/04 19:44:03 - mmengine - INFO - Epoch(train) [18][2240/2569] lr: 4.0000e-02 eta: 1 day, 1:10:41 time: 0.2613 data_time: 0.0078 memory: 5828 grad_norm: 2.8413 loss: 2.7772 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7772 2023/06/04 19:44:09 - mmengine - INFO - Epoch(train) [18][2260/2569] lr: 4.0000e-02 eta: 1 day, 1:10:38 time: 0.2827 data_time: 0.0079 memory: 5828 grad_norm: 2.8708 loss: 2.4487 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.4487 2023/06/04 19:44:14 - mmengine - INFO - Epoch(train) [18][2280/2569] lr: 4.0000e-02 eta: 1 day, 1:10:32 time: 0.2658 data_time: 0.0084 memory: 5828 grad_norm: 2.8771 loss: 2.7540 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7540 2023/06/04 19:44:20 - mmengine - INFO - Epoch(train) [18][2300/2569] lr: 4.0000e-02 eta: 1 day, 1:10:29 time: 0.2798 data_time: 0.0076 memory: 5828 grad_norm: 2.8233 loss: 2.5668 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5668 2023/06/04 19:44:25 - mmengine - INFO - Epoch(train) [18][2320/2569] lr: 4.0000e-02 eta: 1 day, 1:10:23 time: 0.2665 data_time: 0.0077 memory: 5828 grad_norm: 2.9000 loss: 2.2255 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2255 2023/06/04 19:44:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:44:30 - mmengine - INFO - Epoch(train) [18][2340/2569] lr: 4.0000e-02 eta: 1 day, 1:10:18 time: 0.2663 data_time: 0.0082 memory: 5828 grad_norm: 2.8024 loss: 2.3810 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3810 2023/06/04 19:44:36 - mmengine - INFO - Epoch(train) [18][2360/2569] lr: 4.0000e-02 eta: 1 day, 1:10:14 time: 0.2765 data_time: 0.0078 memory: 5828 grad_norm: 2.8133 loss: 2.6164 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6164 2023/06/04 19:44:41 - mmengine - INFO - Epoch(train) [18][2380/2569] lr: 4.0000e-02 eta: 1 day, 1:10:08 time: 0.2637 data_time: 0.0078 memory: 5828 grad_norm: 2.8292 loss: 2.8866 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8866 2023/06/04 19:44:46 - mmengine - INFO - Epoch(train) [18][2400/2569] lr: 4.0000e-02 eta: 1 day, 1:10:04 time: 0.2733 data_time: 0.0078 memory: 5828 grad_norm: 2.9218 loss: 2.4775 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4775 2023/06/04 19:44:52 - mmengine - INFO - Epoch(train) [18][2420/2569] lr: 4.0000e-02 eta: 1 day, 1:09:58 time: 0.2636 data_time: 0.0081 memory: 5828 grad_norm: 2.7958 loss: 2.8140 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8140 2023/06/04 19:44:57 - mmengine - INFO - Epoch(train) [18][2440/2569] lr: 4.0000e-02 eta: 1 day, 1:09:52 time: 0.2652 data_time: 0.0076 memory: 5828 grad_norm: 2.8581 loss: 2.5209 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5209 2023/06/04 19:45:02 - mmengine - INFO - Epoch(train) [18][2460/2569] lr: 4.0000e-02 eta: 1 day, 1:09:47 time: 0.2675 data_time: 0.0082 memory: 5828 grad_norm: 2.7977 loss: 2.5791 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5791 2023/06/04 19:45:08 - mmengine - INFO - Epoch(train) [18][2480/2569] lr: 4.0000e-02 eta: 1 day, 1:09:41 time: 0.2666 data_time: 0.0079 memory: 5828 grad_norm: 2.9113 loss: 2.4004 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4004 2023/06/04 19:45:13 - mmengine - INFO - Epoch(train) [18][2500/2569] lr: 4.0000e-02 eta: 1 day, 1:09:36 time: 0.2680 data_time: 0.0079 memory: 5828 grad_norm: 2.8738 loss: 2.8812 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8812 2023/06/04 19:45:19 - mmengine - INFO - Epoch(train) [18][2520/2569] lr: 4.0000e-02 eta: 1 day, 1:09:32 time: 0.2749 data_time: 0.0077 memory: 5828 grad_norm: 2.8330 loss: 2.6199 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6199 2023/06/04 19:45:24 - mmengine - INFO - Epoch(train) [18][2540/2569] lr: 4.0000e-02 eta: 1 day, 1:09:26 time: 0.2601 data_time: 0.0081 memory: 5828 grad_norm: 2.8653 loss: 2.5071 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5071 2023/06/04 19:45:29 - mmengine - INFO - Epoch(train) [18][2560/2569] lr: 4.0000e-02 eta: 1 day, 1:09:20 time: 0.2678 data_time: 0.0084 memory: 5828 grad_norm: 2.8467 loss: 2.5097 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5097 2023/06/04 19:45:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:45:31 - mmengine - INFO - Epoch(train) [18][2569/2569] lr: 4.0000e-02 eta: 1 day, 1:09:16 time: 0.2537 data_time: 0.0086 memory: 5828 grad_norm: 2.8562 loss: 2.7278 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.7278 2023/06/04 19:45:38 - mmengine - INFO - Epoch(train) [19][ 20/2569] lr: 4.0000e-02 eta: 1 day, 1:09:22 time: 0.3417 data_time: 0.0834 memory: 5828 grad_norm: 2.8834 loss: 2.7634 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7634 2023/06/04 19:45:44 - mmengine - INFO - Epoch(train) [19][ 40/2569] lr: 4.0000e-02 eta: 1 day, 1:09:18 time: 0.2769 data_time: 0.0079 memory: 5828 grad_norm: 2.7916 loss: 2.6494 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6494 2023/06/04 19:45:49 - mmengine - INFO - Epoch(train) [19][ 60/2569] lr: 4.0000e-02 eta: 1 day, 1:09:12 time: 0.2626 data_time: 0.0079 memory: 5828 grad_norm: 2.8312 loss: 2.5086 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5086 2023/06/04 19:45:54 - mmengine - INFO - Epoch(train) [19][ 80/2569] lr: 4.0000e-02 eta: 1 day, 1:09:06 time: 0.2638 data_time: 0.0079 memory: 5828 grad_norm: 2.8515 loss: 2.4135 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4135 2023/06/04 19:45:59 - mmengine - INFO - Epoch(train) [19][ 100/2569] lr: 4.0000e-02 eta: 1 day, 1:09:00 time: 0.2605 data_time: 0.0076 memory: 5828 grad_norm: 2.8183 loss: 2.8894 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8894 2023/06/04 19:46:05 - mmengine - INFO - Epoch(train) [19][ 120/2569] lr: 4.0000e-02 eta: 1 day, 1:08:57 time: 0.2821 data_time: 0.0084 memory: 5828 grad_norm: 2.8446 loss: 2.7060 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7060 2023/06/04 19:46:10 - mmengine - INFO - Epoch(train) [19][ 140/2569] lr: 4.0000e-02 eta: 1 day, 1:08:51 time: 0.2637 data_time: 0.0078 memory: 5828 grad_norm: 2.8231 loss: 2.7837 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7837 2023/06/04 19:46:16 - mmengine - INFO - Epoch(train) [19][ 160/2569] lr: 4.0000e-02 eta: 1 day, 1:08:46 time: 0.2688 data_time: 0.0085 memory: 5828 grad_norm: 2.8638 loss: 2.5017 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5017 2023/06/04 19:46:21 - mmengine - INFO - Epoch(train) [19][ 180/2569] lr: 4.0000e-02 eta: 1 day, 1:08:40 time: 0.2605 data_time: 0.0072 memory: 5828 grad_norm: 2.9083 loss: 2.4731 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4731 2023/06/04 19:46:26 - mmengine - INFO - Epoch(train) [19][ 200/2569] lr: 4.0000e-02 eta: 1 day, 1:08:35 time: 0.2695 data_time: 0.0078 memory: 5828 grad_norm: 2.8507 loss: 2.8473 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8473 2023/06/04 19:46:32 - mmengine - INFO - Epoch(train) [19][ 220/2569] lr: 4.0000e-02 eta: 1 day, 1:08:31 time: 0.2778 data_time: 0.0078 memory: 5828 grad_norm: 2.8211 loss: 2.4465 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4465 2023/06/04 19:46:37 - mmengine - INFO - Epoch(train) [19][ 240/2569] lr: 4.0000e-02 eta: 1 day, 1:08:25 time: 0.2631 data_time: 0.0078 memory: 5828 grad_norm: 2.8166 loss: 2.4534 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4534 2023/06/04 19:46:43 - mmengine - INFO - Epoch(train) [19][ 260/2569] lr: 4.0000e-02 eta: 1 day, 1:08:21 time: 0.2757 data_time: 0.0076 memory: 5828 grad_norm: 2.8790 loss: 2.7632 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7632 2023/06/04 19:46:48 - mmengine - INFO - Epoch(train) [19][ 280/2569] lr: 4.0000e-02 eta: 1 day, 1:08:15 time: 0.2607 data_time: 0.0074 memory: 5828 grad_norm: 2.8804 loss: 2.6630 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6630 2023/06/04 19:46:53 - mmengine - INFO - Epoch(train) [19][ 300/2569] lr: 4.0000e-02 eta: 1 day, 1:08:09 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 2.8899 loss: 2.4367 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4367 2023/06/04 19:46:59 - mmengine - INFO - Epoch(train) [19][ 320/2569] lr: 4.0000e-02 eta: 1 day, 1:08:04 time: 0.2691 data_time: 0.0076 memory: 5828 grad_norm: 2.7967 loss: 2.4973 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4973 2023/06/04 19:47:04 - mmengine - INFO - Epoch(train) [19][ 340/2569] lr: 4.0000e-02 eta: 1 day, 1:07:57 time: 0.2611 data_time: 0.0078 memory: 5828 grad_norm: 2.8689 loss: 2.1808 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1808 2023/06/04 19:47:09 - mmengine - INFO - Epoch(train) [19][ 360/2569] lr: 4.0000e-02 eta: 1 day, 1:07:52 time: 0.2658 data_time: 0.0080 memory: 5828 grad_norm: 2.8617 loss: 2.7004 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7004 2023/06/04 19:47:14 - mmengine - INFO - Epoch(train) [19][ 380/2569] lr: 4.0000e-02 eta: 1 day, 1:07:47 time: 0.2685 data_time: 0.0082 memory: 5828 grad_norm: 2.8269 loss: 2.1571 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1571 2023/06/04 19:47:20 - mmengine - INFO - Epoch(train) [19][ 400/2569] lr: 4.0000e-02 eta: 1 day, 1:07:44 time: 0.2834 data_time: 0.0078 memory: 5828 grad_norm: 2.8111 loss: 2.4712 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4712 2023/06/04 19:47:25 - mmengine - INFO - Epoch(train) [19][ 420/2569] lr: 4.0000e-02 eta: 1 day, 1:07:37 time: 0.2602 data_time: 0.0095 memory: 5828 grad_norm: 2.8632 loss: 2.5579 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5579 2023/06/04 19:47:31 - mmengine - INFO - Epoch(train) [19][ 440/2569] lr: 4.0000e-02 eta: 1 day, 1:07:32 time: 0.2690 data_time: 0.0083 memory: 5828 grad_norm: 2.8447 loss: 2.6907 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6907 2023/06/04 19:47:36 - mmengine - INFO - Epoch(train) [19][ 460/2569] lr: 4.0000e-02 eta: 1 day, 1:07:27 time: 0.2644 data_time: 0.0077 memory: 5828 grad_norm: 2.8527 loss: 2.4333 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4333 2023/06/04 19:47:41 - mmengine - INFO - Epoch(train) [19][ 480/2569] lr: 4.0000e-02 eta: 1 day, 1:07:21 time: 0.2658 data_time: 0.0083 memory: 5828 grad_norm: 2.8376 loss: 2.4017 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4017 2023/06/04 19:47:47 - mmengine - INFO - Epoch(train) [19][ 500/2569] lr: 4.0000e-02 eta: 1 day, 1:07:15 time: 0.2630 data_time: 0.0080 memory: 5828 grad_norm: 2.8935 loss: 2.5325 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5325 2023/06/04 19:47:52 - mmengine - INFO - Epoch(train) [19][ 520/2569] lr: 4.0000e-02 eta: 1 day, 1:07:10 time: 0.2668 data_time: 0.0077 memory: 5828 grad_norm: 2.8351 loss: 2.7822 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7822 2023/06/04 19:47:57 - mmengine - INFO - Epoch(train) [19][ 540/2569] lr: 4.0000e-02 eta: 1 day, 1:07:04 time: 0.2676 data_time: 0.0079 memory: 5828 grad_norm: 2.8459 loss: 2.7190 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7190 2023/06/04 19:48:03 - mmengine - INFO - Epoch(train) [19][ 560/2569] lr: 4.0000e-02 eta: 1 day, 1:06:59 time: 0.2694 data_time: 0.0078 memory: 5828 grad_norm: 2.9025 loss: 2.2645 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2645 2023/06/04 19:48:08 - mmengine - INFO - Epoch(train) [19][ 580/2569] lr: 4.0000e-02 eta: 1 day, 1:06:54 time: 0.2631 data_time: 0.0078 memory: 5828 grad_norm: 2.8575 loss: 2.5413 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5413 2023/06/04 19:48:13 - mmengine - INFO - Epoch(train) [19][ 600/2569] lr: 4.0000e-02 eta: 1 day, 1:06:48 time: 0.2643 data_time: 0.0079 memory: 5828 grad_norm: 2.8741 loss: 2.5371 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5371 2023/06/04 19:48:19 - mmengine - INFO - Epoch(train) [19][ 620/2569] lr: 4.0000e-02 eta: 1 day, 1:06:43 time: 0.2706 data_time: 0.0082 memory: 5828 grad_norm: 2.8342 loss: 2.8400 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8400 2023/06/04 19:48:24 - mmengine - INFO - Epoch(train) [19][ 640/2569] lr: 4.0000e-02 eta: 1 day, 1:06:38 time: 0.2711 data_time: 0.0078 memory: 5828 grad_norm: 2.7973 loss: 2.5603 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5603 2023/06/04 19:48:30 - mmengine - INFO - Epoch(train) [19][ 660/2569] lr: 4.0000e-02 eta: 1 day, 1:06:34 time: 0.2730 data_time: 0.0082 memory: 5828 grad_norm: 2.8569 loss: 2.6371 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.6371 2023/06/04 19:48:35 - mmengine - INFO - Epoch(train) [19][ 680/2569] lr: 4.0000e-02 eta: 1 day, 1:06:29 time: 0.2717 data_time: 0.0079 memory: 5828 grad_norm: 2.8542 loss: 2.6561 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6561 2023/06/04 19:48:40 - mmengine - INFO - Epoch(train) [19][ 700/2569] lr: 4.0000e-02 eta: 1 day, 1:06:24 time: 0.2690 data_time: 0.0081 memory: 5828 grad_norm: 2.8972 loss: 2.7046 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7046 2023/06/04 19:48:46 - mmengine - INFO - Epoch(train) [19][ 720/2569] lr: 4.0000e-02 eta: 1 day, 1:06:18 time: 0.2608 data_time: 0.0076 memory: 5828 grad_norm: 2.8954 loss: 2.6754 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6754 2023/06/04 19:48:51 - mmengine - INFO - Epoch(train) [19][ 740/2569] lr: 4.0000e-02 eta: 1 day, 1:06:12 time: 0.2610 data_time: 0.0076 memory: 5828 grad_norm: 2.8534 loss: 2.4692 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4692 2023/06/04 19:48:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:48:56 - mmengine - INFO - Epoch(train) [19][ 760/2569] lr: 4.0000e-02 eta: 1 day, 1:06:05 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 2.8457 loss: 2.4419 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4419 2023/06/04 19:49:01 - mmengine - INFO - Epoch(train) [19][ 780/2569] lr: 4.0000e-02 eta: 1 day, 1:06:00 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 2.8563 loss: 2.4656 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4656 2023/06/04 19:49:07 - mmengine - INFO - Epoch(train) [19][ 800/2569] lr: 4.0000e-02 eta: 1 day, 1:05:54 time: 0.2656 data_time: 0.0076 memory: 5828 grad_norm: 2.8747 loss: 2.4633 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4633 2023/06/04 19:49:12 - mmengine - INFO - Epoch(train) [19][ 820/2569] lr: 4.0000e-02 eta: 1 day, 1:05:49 time: 0.2668 data_time: 0.0079 memory: 5828 grad_norm: 2.8461 loss: 2.5913 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5913 2023/06/04 19:49:17 - mmengine - INFO - Epoch(train) [19][ 840/2569] lr: 4.0000e-02 eta: 1 day, 1:05:43 time: 0.2604 data_time: 0.0083 memory: 5828 grad_norm: 2.8779 loss: 2.5949 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5949 2023/06/04 19:49:23 - mmengine - INFO - Epoch(train) [19][ 860/2569] lr: 4.0000e-02 eta: 1 day, 1:05:37 time: 0.2658 data_time: 0.0076 memory: 5828 grad_norm: 2.8539 loss: 2.7046 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7046 2023/06/04 19:49:28 - mmengine - INFO - Epoch(train) [19][ 880/2569] lr: 4.0000e-02 eta: 1 day, 1:05:31 time: 0.2627 data_time: 0.0077 memory: 5828 grad_norm: 2.8279 loss: 2.2848 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2848 2023/06/04 19:49:33 - mmengine - INFO - Epoch(train) [19][ 900/2569] lr: 4.0000e-02 eta: 1 day, 1:05:25 time: 0.2616 data_time: 0.0076 memory: 5828 grad_norm: 2.7814 loss: 2.7260 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7260 2023/06/04 19:49:38 - mmengine - INFO - Epoch(train) [19][ 920/2569] lr: 4.0000e-02 eta: 1 day, 1:05:20 time: 0.2699 data_time: 0.0075 memory: 5828 grad_norm: 2.8189 loss: 2.5728 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5728 2023/06/04 19:49:44 - mmengine - INFO - Epoch(train) [19][ 940/2569] lr: 4.0000e-02 eta: 1 day, 1:05:14 time: 0.2619 data_time: 0.0082 memory: 5828 grad_norm: 2.8427 loss: 2.7082 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7082 2023/06/04 19:49:49 - mmengine - INFO - Epoch(train) [19][ 960/2569] lr: 4.0000e-02 eta: 1 day, 1:05:08 time: 0.2611 data_time: 0.0084 memory: 5828 grad_norm: 2.8169 loss: 2.5670 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5670 2023/06/04 19:49:54 - mmengine - INFO - Epoch(train) [19][ 980/2569] lr: 4.0000e-02 eta: 1 day, 1:05:02 time: 0.2614 data_time: 0.0078 memory: 5828 grad_norm: 2.8215 loss: 2.4067 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4067 2023/06/04 19:49:59 - mmengine - INFO - Epoch(train) [19][1000/2569] lr: 4.0000e-02 eta: 1 day, 1:04:56 time: 0.2647 data_time: 0.0077 memory: 5828 grad_norm: 2.8581 loss: 2.6054 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6054 2023/06/04 19:50:05 - mmengine - INFO - Epoch(train) [19][1020/2569] lr: 4.0000e-02 eta: 1 day, 1:04:51 time: 0.2659 data_time: 0.0080 memory: 5828 grad_norm: 2.9037 loss: 2.7600 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7600 2023/06/04 19:50:10 - mmengine - INFO - Epoch(train) [19][1040/2569] lr: 4.0000e-02 eta: 1 day, 1:04:46 time: 0.2709 data_time: 0.0076 memory: 5828 grad_norm: 2.8349 loss: 2.8320 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8320 2023/06/04 19:50:16 - mmengine - INFO - Epoch(train) [19][1060/2569] lr: 4.0000e-02 eta: 1 day, 1:04:40 time: 0.2661 data_time: 0.0077 memory: 5828 grad_norm: 2.8847 loss: 2.2760 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.2760 2023/06/04 19:50:21 - mmengine - INFO - Epoch(train) [19][1080/2569] lr: 4.0000e-02 eta: 1 day, 1:04:35 time: 0.2669 data_time: 0.0081 memory: 5828 grad_norm: 2.8069 loss: 2.7804 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7804 2023/06/04 19:50:26 - mmengine - INFO - Epoch(train) [19][1100/2569] lr: 4.0000e-02 eta: 1 day, 1:04:29 time: 0.2604 data_time: 0.0081 memory: 5828 grad_norm: 2.8403 loss: 2.4014 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4014 2023/06/04 19:50:31 - mmengine - INFO - Epoch(train) [19][1120/2569] lr: 4.0000e-02 eta: 1 day, 1:04:23 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 2.8420 loss: 2.8052 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8052 2023/06/04 19:50:37 - mmengine - INFO - Epoch(train) [19][1140/2569] lr: 4.0000e-02 eta: 1 day, 1:04:17 time: 0.2600 data_time: 0.0082 memory: 5828 grad_norm: 2.8011 loss: 2.7376 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7376 2023/06/04 19:50:42 - mmengine - INFO - Epoch(train) [19][1160/2569] lr: 4.0000e-02 eta: 1 day, 1:04:13 time: 0.2762 data_time: 0.0079 memory: 5828 grad_norm: 2.8683 loss: 2.8021 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8021 2023/06/04 19:50:47 - mmengine - INFO - Epoch(train) [19][1180/2569] lr: 4.0000e-02 eta: 1 day, 1:04:07 time: 0.2626 data_time: 0.0083 memory: 5828 grad_norm: 2.8683 loss: 2.6025 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6025 2023/06/04 19:50:53 - mmengine - INFO - Epoch(train) [19][1200/2569] lr: 4.0000e-02 eta: 1 day, 1:04:02 time: 0.2735 data_time: 0.0081 memory: 5828 grad_norm: 2.8052 loss: 2.8636 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8636 2023/06/04 19:50:58 - mmengine - INFO - Epoch(train) [19][1220/2569] lr: 4.0000e-02 eta: 1 day, 1:03:56 time: 0.2602 data_time: 0.0080 memory: 5828 grad_norm: 2.8775 loss: 2.6778 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6778 2023/06/04 19:51:04 - mmengine - INFO - Epoch(train) [19][1240/2569] lr: 4.0000e-02 eta: 1 day, 1:03:52 time: 0.2763 data_time: 0.0077 memory: 5828 grad_norm: 2.9123 loss: 2.7523 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7523 2023/06/04 19:51:09 - mmengine - INFO - Epoch(train) [19][1260/2569] lr: 4.0000e-02 eta: 1 day, 1:03:46 time: 0.2619 data_time: 0.0077 memory: 5828 grad_norm: 2.8249 loss: 2.3608 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3608 2023/06/04 19:51:14 - mmengine - INFO - Epoch(train) [19][1280/2569] lr: 4.0000e-02 eta: 1 day, 1:03:40 time: 0.2608 data_time: 0.0082 memory: 5828 grad_norm: 2.9135 loss: 2.8903 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8903 2023/06/04 19:51:19 - mmengine - INFO - Epoch(train) [19][1300/2569] lr: 4.0000e-02 eta: 1 day, 1:03:35 time: 0.2748 data_time: 0.0071 memory: 5828 grad_norm: 2.9053 loss: 2.5094 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5094 2023/06/04 19:51:25 - mmengine - INFO - Epoch(train) [19][1320/2569] lr: 4.0000e-02 eta: 1 day, 1:03:31 time: 0.2708 data_time: 0.0079 memory: 5828 grad_norm: 2.8590 loss: 2.3403 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3403 2023/06/04 19:51:30 - mmengine - INFO - Epoch(train) [19][1340/2569] lr: 4.0000e-02 eta: 1 day, 1:03:25 time: 0.2646 data_time: 0.0080 memory: 5828 grad_norm: 2.8525 loss: 2.7147 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7147 2023/06/04 19:51:36 - mmengine - INFO - Epoch(train) [19][1360/2569] lr: 4.0000e-02 eta: 1 day, 1:03:19 time: 0.2668 data_time: 0.0085 memory: 5828 grad_norm: 2.9130 loss: 2.5989 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5989 2023/06/04 19:51:41 - mmengine - INFO - Epoch(train) [19][1380/2569] lr: 4.0000e-02 eta: 1 day, 1:03:13 time: 0.2608 data_time: 0.0075 memory: 5828 grad_norm: 2.9325 loss: 2.4671 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4671 2023/06/04 19:51:46 - mmengine - INFO - Epoch(train) [19][1400/2569] lr: 4.0000e-02 eta: 1 day, 1:03:07 time: 0.2621 data_time: 0.0080 memory: 5828 grad_norm: 2.8597 loss: 2.3427 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3427 2023/06/04 19:51:51 - mmengine - INFO - Epoch(train) [19][1420/2569] lr: 4.0000e-02 eta: 1 day, 1:03:01 time: 0.2620 data_time: 0.0076 memory: 5828 grad_norm: 2.8917 loss: 2.5297 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5297 2023/06/04 19:51:57 - mmengine - INFO - Epoch(train) [19][1440/2569] lr: 4.0000e-02 eta: 1 day, 1:02:57 time: 0.2744 data_time: 0.0075 memory: 5828 grad_norm: 2.8504 loss: 2.5058 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5058 2023/06/04 19:52:02 - mmengine - INFO - Epoch(train) [19][1460/2569] lr: 4.0000e-02 eta: 1 day, 1:02:51 time: 0.2654 data_time: 0.0079 memory: 5828 grad_norm: 2.8406 loss: 2.6025 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6025 2023/06/04 19:52:08 - mmengine - INFO - Epoch(train) [19][1480/2569] lr: 4.0000e-02 eta: 1 day, 1:02:47 time: 0.2769 data_time: 0.0078 memory: 5828 grad_norm: 2.8206 loss: 2.4600 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4600 2023/06/04 19:52:13 - mmengine - INFO - Epoch(train) [19][1500/2569] lr: 4.0000e-02 eta: 1 day, 1:02:41 time: 0.2602 data_time: 0.0082 memory: 5828 grad_norm: 2.8248 loss: 2.7327 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7327 2023/06/04 19:52:18 - mmengine - INFO - Epoch(train) [19][1520/2569] lr: 4.0000e-02 eta: 1 day, 1:02:37 time: 0.2734 data_time: 0.0081 memory: 5828 grad_norm: 2.8757 loss: 2.5925 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5925 2023/06/04 19:52:23 - mmengine - INFO - Epoch(train) [19][1540/2569] lr: 4.0000e-02 eta: 1 day, 1:02:30 time: 0.2619 data_time: 0.0083 memory: 5828 grad_norm: 2.9013 loss: 2.5842 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5842 2023/06/04 19:52:29 - mmengine - INFO - Epoch(train) [19][1560/2569] lr: 4.0000e-02 eta: 1 day, 1:02:26 time: 0.2720 data_time: 0.0074 memory: 5828 grad_norm: 2.8485 loss: 2.9824 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9824 2023/06/04 19:52:34 - mmengine - INFO - Epoch(train) [19][1580/2569] lr: 4.0000e-02 eta: 1 day, 1:02:21 time: 0.2682 data_time: 0.0077 memory: 5828 grad_norm: 2.8590 loss: 2.6127 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6127 2023/06/04 19:52:40 - mmengine - INFO - Epoch(train) [19][1600/2569] lr: 4.0000e-02 eta: 1 day, 1:02:16 time: 0.2715 data_time: 0.0076 memory: 5828 grad_norm: 2.9483 loss: 2.4570 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4570 2023/06/04 19:52:45 - mmengine - INFO - Epoch(train) [19][1620/2569] lr: 4.0000e-02 eta: 1 day, 1:02:11 time: 0.2732 data_time: 0.0080 memory: 5828 grad_norm: 2.8948 loss: 2.5880 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5880 2023/06/04 19:52:51 - mmengine - INFO - Epoch(train) [19][1640/2569] lr: 4.0000e-02 eta: 1 day, 1:02:06 time: 0.2678 data_time: 0.0083 memory: 5828 grad_norm: 2.8483 loss: 2.4835 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4835 2023/06/04 19:52:56 - mmengine - INFO - Epoch(train) [19][1660/2569] lr: 4.0000e-02 eta: 1 day, 1:02:01 time: 0.2704 data_time: 0.0079 memory: 5828 grad_norm: 2.8113 loss: 2.3818 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3818 2023/06/04 19:53:02 - mmengine - INFO - Epoch(train) [19][1680/2569] lr: 4.0000e-02 eta: 1 day, 1:01:57 time: 0.2770 data_time: 0.0079 memory: 5828 grad_norm: 2.8602 loss: 2.2117 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2117 2023/06/04 19:53:07 - mmengine - INFO - Epoch(train) [19][1700/2569] lr: 4.0000e-02 eta: 1 day, 1:01:52 time: 0.2648 data_time: 0.0084 memory: 5828 grad_norm: 2.8482 loss: 2.5813 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5813 2023/06/04 19:53:12 - mmengine - INFO - Epoch(train) [19][1720/2569] lr: 4.0000e-02 eta: 1 day, 1:01:47 time: 0.2730 data_time: 0.0080 memory: 5828 grad_norm: 2.8859 loss: 2.6357 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6357 2023/06/04 19:53:18 - mmengine - INFO - Epoch(train) [19][1740/2569] lr: 4.0000e-02 eta: 1 day, 1:01:42 time: 0.2684 data_time: 0.0081 memory: 5828 grad_norm: 2.8089 loss: 2.3714 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3714 2023/06/04 19:53:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:53:23 - mmengine - INFO - Epoch(train) [19][1760/2569] lr: 4.0000e-02 eta: 1 day, 1:01:36 time: 0.2640 data_time: 0.0083 memory: 5828 grad_norm: 2.8832 loss: 2.4120 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4120 2023/06/04 19:53:28 - mmengine - INFO - Epoch(train) [19][1780/2569] lr: 4.0000e-02 eta: 1 day, 1:01:31 time: 0.2697 data_time: 0.0078 memory: 5828 grad_norm: 2.8849 loss: 2.6442 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6442 2023/06/04 19:53:34 - mmengine - INFO - Epoch(train) [19][1800/2569] lr: 4.0000e-02 eta: 1 day, 1:01:27 time: 0.2754 data_time: 0.0077 memory: 5828 grad_norm: 2.8480 loss: 2.6659 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.6659 2023/06/04 19:53:39 - mmengine - INFO - Epoch(train) [19][1820/2569] lr: 4.0000e-02 eta: 1 day, 1:01:23 time: 0.2774 data_time: 0.0081 memory: 5828 grad_norm: 2.7829 loss: 2.3587 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3587 2023/06/04 19:53:45 - mmengine - INFO - Epoch(train) [19][1840/2569] lr: 4.0000e-02 eta: 1 day, 1:01:18 time: 0.2707 data_time: 0.0079 memory: 5828 grad_norm: 2.8509 loss: 2.4808 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4808 2023/06/04 19:53:50 - mmengine - INFO - Epoch(train) [19][1860/2569] lr: 4.0000e-02 eta: 1 day, 1:01:13 time: 0.2640 data_time: 0.0079 memory: 5828 grad_norm: 2.8166 loss: 2.4407 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4407 2023/06/04 19:53:56 - mmengine - INFO - Epoch(train) [19][1880/2569] lr: 4.0000e-02 eta: 1 day, 1:01:08 time: 0.2729 data_time: 0.0080 memory: 5828 grad_norm: 2.8326 loss: 2.8871 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8871 2023/06/04 19:54:01 - mmengine - INFO - Epoch(train) [19][1900/2569] lr: 4.0000e-02 eta: 1 day, 1:01:04 time: 0.2783 data_time: 0.0077 memory: 5828 grad_norm: 2.8593 loss: 2.8379 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8379 2023/06/04 19:54:06 - mmengine - INFO - Epoch(train) [19][1920/2569] lr: 4.0000e-02 eta: 1 day, 1:00:58 time: 0.2620 data_time: 0.0083 memory: 5828 grad_norm: 2.8861 loss: 2.8538 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8538 2023/06/04 19:54:12 - mmengine - INFO - Epoch(train) [19][1940/2569] lr: 4.0000e-02 eta: 1 day, 1:00:53 time: 0.2655 data_time: 0.0077 memory: 5828 grad_norm: 2.8505 loss: 2.2666 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2666 2023/06/04 19:54:17 - mmengine - INFO - Epoch(train) [19][1960/2569] lr: 4.0000e-02 eta: 1 day, 1:00:47 time: 0.2630 data_time: 0.0074 memory: 5828 grad_norm: 2.8803 loss: 2.8156 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.8156 2023/06/04 19:54:22 - mmengine - INFO - Epoch(train) [19][1980/2569] lr: 4.0000e-02 eta: 1 day, 1:00:43 time: 0.2755 data_time: 0.0078 memory: 5828 grad_norm: 2.9194 loss: 2.7272 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7272 2023/06/04 19:54:28 - mmengine - INFO - Epoch(train) [19][2000/2569] lr: 4.0000e-02 eta: 1 day, 1:00:36 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 2.8670 loss: 2.3574 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3574 2023/06/04 19:54:33 - mmengine - INFO - Epoch(train) [19][2020/2569] lr: 4.0000e-02 eta: 1 day, 1:00:31 time: 0.2668 data_time: 0.0079 memory: 5828 grad_norm: 2.8477 loss: 2.9448 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.9448 2023/06/04 19:54:38 - mmengine - INFO - Epoch(train) [19][2040/2569] lr: 4.0000e-02 eta: 1 day, 1:00:25 time: 0.2622 data_time: 0.0083 memory: 5828 grad_norm: 2.9143 loss: 2.5258 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5258 2023/06/04 19:54:44 - mmengine - INFO - Epoch(train) [19][2060/2569] lr: 4.0000e-02 eta: 1 day, 1:00:21 time: 0.2759 data_time: 0.0079 memory: 5828 grad_norm: 2.8381 loss: 2.5360 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5360 2023/06/04 19:54:49 - mmengine - INFO - Epoch(train) [19][2080/2569] lr: 4.0000e-02 eta: 1 day, 1:00:15 time: 0.2621 data_time: 0.0077 memory: 5828 grad_norm: 2.8894 loss: 2.8748 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8748 2023/06/04 19:54:55 - mmengine - INFO - Epoch(train) [19][2100/2569] lr: 4.0000e-02 eta: 1 day, 1:00:11 time: 0.2760 data_time: 0.0079 memory: 5828 grad_norm: 2.8613 loss: 2.5100 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5100 2023/06/04 19:55:00 - mmengine - INFO - Epoch(train) [19][2120/2569] lr: 4.0000e-02 eta: 1 day, 1:00:05 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 2.8939 loss: 2.6227 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6227 2023/06/04 19:55:05 - mmengine - INFO - Epoch(train) [19][2140/2569] lr: 4.0000e-02 eta: 1 day, 1:00:01 time: 0.2771 data_time: 0.0074 memory: 5828 grad_norm: 2.8572 loss: 2.5356 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.5356 2023/06/04 19:55:11 - mmengine - INFO - Epoch(train) [19][2160/2569] lr: 4.0000e-02 eta: 1 day, 0:59:57 time: 0.2706 data_time: 0.0081 memory: 5828 grad_norm: 2.8778 loss: 2.7254 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7254 2023/06/04 19:55:16 - mmengine - INFO - Epoch(train) [19][2180/2569] lr: 4.0000e-02 eta: 1 day, 0:59:51 time: 0.2689 data_time: 0.0082 memory: 5828 grad_norm: 2.7853 loss: 2.8384 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.8384 2023/06/04 19:55:21 - mmengine - INFO - Epoch(train) [19][2200/2569] lr: 4.0000e-02 eta: 1 day, 0:59:46 time: 0.2643 data_time: 0.0079 memory: 5828 grad_norm: 2.8807 loss: 2.9253 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9253 2023/06/04 19:55:27 - mmengine - INFO - Epoch(train) [19][2220/2569] lr: 4.0000e-02 eta: 1 day, 0:59:40 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 2.8059 loss: 3.0064 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0064 2023/06/04 19:55:32 - mmengine - INFO - Epoch(train) [19][2240/2569] lr: 4.0000e-02 eta: 1 day, 0:59:34 time: 0.2679 data_time: 0.0077 memory: 5828 grad_norm: 2.9060 loss: 2.5294 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5294 2023/06/04 19:55:37 - mmengine - INFO - Epoch(train) [19][2260/2569] lr: 4.0000e-02 eta: 1 day, 0:59:29 time: 0.2650 data_time: 0.0081 memory: 5828 grad_norm: 2.8747 loss: 2.4927 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4927 2023/06/04 19:55:43 - mmengine - INFO - Epoch(train) [19][2280/2569] lr: 4.0000e-02 eta: 1 day, 0:59:23 time: 0.2666 data_time: 0.0079 memory: 5828 grad_norm: 2.9458 loss: 2.7387 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7387 2023/06/04 19:55:48 - mmengine - INFO - Epoch(train) [19][2300/2569] lr: 4.0000e-02 eta: 1 day, 0:59:19 time: 0.2712 data_time: 0.0076 memory: 5828 grad_norm: 2.8401 loss: 2.3417 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3417 2023/06/04 19:55:53 - mmengine - INFO - Epoch(train) [19][2320/2569] lr: 4.0000e-02 eta: 1 day, 0:59:13 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 2.8592 loss: 2.1747 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1747 2023/06/04 19:55:59 - mmengine - INFO - Epoch(train) [19][2340/2569] lr: 4.0000e-02 eta: 1 day, 0:59:07 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 2.9138 loss: 2.5637 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5637 2023/06/04 19:56:04 - mmengine - INFO - Epoch(train) [19][2360/2569] lr: 4.0000e-02 eta: 1 day, 0:59:03 time: 0.2763 data_time: 0.0080 memory: 5828 grad_norm: 2.8750 loss: 2.8184 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8184 2023/06/04 19:56:10 - mmengine - INFO - Epoch(train) [19][2380/2569] lr: 4.0000e-02 eta: 1 day, 0:58:58 time: 0.2659 data_time: 0.0083 memory: 5828 grad_norm: 2.8501 loss: 2.0983 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0983 2023/06/04 19:56:15 - mmengine - INFO - Epoch(train) [19][2400/2569] lr: 4.0000e-02 eta: 1 day, 0:58:53 time: 0.2764 data_time: 0.0080 memory: 5828 grad_norm: 2.9074 loss: 2.6051 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.6051 2023/06/04 19:56:21 - mmengine - INFO - Epoch(train) [19][2420/2569] lr: 4.0000e-02 eta: 1 day, 0:58:49 time: 0.2739 data_time: 0.0079 memory: 5828 grad_norm: 2.8848 loss: 2.5999 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5999 2023/06/04 19:56:26 - mmengine - INFO - Epoch(train) [19][2440/2569] lr: 4.0000e-02 eta: 1 day, 0:58:44 time: 0.2682 data_time: 0.0079 memory: 5828 grad_norm: 2.8526 loss: 2.6084 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6084 2023/06/04 19:56:31 - mmengine - INFO - Epoch(train) [19][2460/2569] lr: 4.0000e-02 eta: 1 day, 0:58:38 time: 0.2649 data_time: 0.0077 memory: 5828 grad_norm: 2.8710 loss: 2.7123 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7123 2023/06/04 19:56:37 - mmengine - INFO - Epoch(train) [19][2480/2569] lr: 4.0000e-02 eta: 1 day, 0:58:33 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 2.8515 loss: 2.6480 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6480 2023/06/04 19:56:42 - mmengine - INFO - Epoch(train) [19][2500/2569] lr: 4.0000e-02 eta: 1 day, 0:58:27 time: 0.2632 data_time: 0.0078 memory: 5828 grad_norm: 2.8459 loss: 2.6198 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6198 2023/06/04 19:56:47 - mmengine - INFO - Epoch(train) [19][2520/2569] lr: 4.0000e-02 eta: 1 day, 0:58:22 time: 0.2693 data_time: 0.0081 memory: 5828 grad_norm: 2.8479 loss: 2.8144 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8144 2023/06/04 19:56:52 - mmengine - INFO - Epoch(train) [19][2540/2569] lr: 4.0000e-02 eta: 1 day, 0:58:16 time: 0.2616 data_time: 0.0080 memory: 5828 grad_norm: 2.8340 loss: 2.5132 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5132 2023/06/04 19:56:58 - mmengine - INFO - Epoch(train) [19][2560/2569] lr: 4.0000e-02 eta: 1 day, 0:58:10 time: 0.2665 data_time: 0.0077 memory: 5828 grad_norm: 2.9256 loss: 2.5461 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5461 2023/06/04 19:57:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:57:00 - mmengine - INFO - Epoch(train) [19][2569/2569] lr: 4.0000e-02 eta: 1 day, 0:58:07 time: 0.2587 data_time: 0.0077 memory: 5828 grad_norm: 2.9449 loss: 2.6103 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.6103 2023/06/04 19:57:07 - mmengine - INFO - Epoch(train) [20][ 20/2569] lr: 4.0000e-02 eta: 1 day, 0:58:12 time: 0.3403 data_time: 0.0561 memory: 5828 grad_norm: 2.8830 loss: 2.4509 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4509 2023/06/04 19:57:12 - mmengine - INFO - Epoch(train) [20][ 40/2569] lr: 4.0000e-02 eta: 1 day, 0:58:07 time: 0.2661 data_time: 0.0079 memory: 5828 grad_norm: 2.8494 loss: 2.4060 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4060 2023/06/04 19:57:18 - mmengine - INFO - Epoch(train) [20][ 60/2569] lr: 4.0000e-02 eta: 1 day, 0:58:02 time: 0.2710 data_time: 0.0081 memory: 5828 grad_norm: 2.9044 loss: 2.5099 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5099 2023/06/04 19:57:23 - mmengine - INFO - Epoch(train) [20][ 80/2569] lr: 4.0000e-02 eta: 1 day, 0:57:56 time: 0.2657 data_time: 0.0081 memory: 5828 grad_norm: 2.8882 loss: 2.8165 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8165 2023/06/04 19:57:28 - mmengine - INFO - Epoch(train) [20][ 100/2569] lr: 4.0000e-02 eta: 1 day, 0:57:51 time: 0.2695 data_time: 0.0075 memory: 5828 grad_norm: 2.8058 loss: 2.5302 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5302 2023/06/04 19:57:34 - mmengine - INFO - Epoch(train) [20][ 120/2569] lr: 4.0000e-02 eta: 1 day, 0:57:45 time: 0.2621 data_time: 0.0077 memory: 5828 grad_norm: 2.9112 loss: 2.6059 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6059 2023/06/04 19:57:39 - mmengine - INFO - Epoch(train) [20][ 140/2569] lr: 4.0000e-02 eta: 1 day, 0:57:40 time: 0.2678 data_time: 0.0080 memory: 5828 grad_norm: 2.8106 loss: 2.2453 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2453 2023/06/04 19:57:44 - mmengine - INFO - Epoch(train) [20][ 160/2569] lr: 4.0000e-02 eta: 1 day, 0:57:34 time: 0.2622 data_time: 0.0078 memory: 5828 grad_norm: 2.8237 loss: 2.3821 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3821 2023/06/04 19:57:50 - mmengine - INFO - Epoch(train) [20][ 180/2569] lr: 4.0000e-02 eta: 1 day, 0:57:29 time: 0.2696 data_time: 0.0077 memory: 5828 grad_norm: 2.8622 loss: 2.3813 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3813 2023/06/04 19:57:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 19:57:55 - mmengine - INFO - Epoch(train) [20][ 200/2569] lr: 4.0000e-02 eta: 1 day, 0:57:23 time: 0.2636 data_time: 0.0076 memory: 5828 grad_norm: 2.8511 loss: 2.5385 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5385 2023/06/04 19:58:01 - mmengine - INFO - Epoch(train) [20][ 220/2569] lr: 4.0000e-02 eta: 1 day, 0:57:20 time: 0.2816 data_time: 0.0080 memory: 5828 grad_norm: 2.8294 loss: 2.6684 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6684 2023/06/04 19:58:06 - mmengine - INFO - Epoch(train) [20][ 240/2569] lr: 4.0000e-02 eta: 1 day, 0:57:14 time: 0.2618 data_time: 0.0080 memory: 5828 grad_norm: 2.8546 loss: 2.7346 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7346 2023/06/04 19:58:11 - mmengine - INFO - Epoch(train) [20][ 260/2569] lr: 4.0000e-02 eta: 1 day, 0:57:09 time: 0.2734 data_time: 0.0078 memory: 5828 grad_norm: 2.9066 loss: 2.8416 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8416 2023/06/04 19:58:16 - mmengine - INFO - Epoch(train) [20][ 280/2569] lr: 4.0000e-02 eta: 1 day, 0:57:03 time: 0.2602 data_time: 0.0081 memory: 5828 grad_norm: 2.8703 loss: 2.4411 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4411 2023/06/04 19:58:22 - mmengine - INFO - Epoch(train) [20][ 300/2569] lr: 4.0000e-02 eta: 1 day, 0:56:57 time: 0.2636 data_time: 0.0079 memory: 5828 grad_norm: 2.9010 loss: 2.8879 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8879 2023/06/04 19:58:27 - mmengine - INFO - Epoch(train) [20][ 320/2569] lr: 4.0000e-02 eta: 1 day, 0:56:51 time: 0.2641 data_time: 0.0082 memory: 5828 grad_norm: 2.8389 loss: 2.5451 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5451 2023/06/04 19:58:32 - mmengine - INFO - Epoch(train) [20][ 340/2569] lr: 4.0000e-02 eta: 1 day, 0:56:45 time: 0.2593 data_time: 0.0081 memory: 5828 grad_norm: 2.8335 loss: 2.6540 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6540 2023/06/04 19:58:38 - mmengine - INFO - Epoch(train) [20][ 360/2569] lr: 4.0000e-02 eta: 1 day, 0:56:39 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 2.8716 loss: 2.4472 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4472 2023/06/04 19:58:43 - mmengine - INFO - Epoch(train) [20][ 380/2569] lr: 4.0000e-02 eta: 1 day, 0:56:34 time: 0.2662 data_time: 0.0080 memory: 5828 grad_norm: 2.8559 loss: 2.5348 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5348 2023/06/04 19:58:48 - mmengine - INFO - Epoch(train) [20][ 400/2569] lr: 4.0000e-02 eta: 1 day, 0:56:29 time: 0.2697 data_time: 0.0085 memory: 5828 grad_norm: 2.8482 loss: 2.5479 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5479 2023/06/04 19:58:54 - mmengine - INFO - Epoch(train) [20][ 420/2569] lr: 4.0000e-02 eta: 1 day, 0:56:24 time: 0.2734 data_time: 0.0077 memory: 5828 grad_norm: 2.8688 loss: 2.5349 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5349 2023/06/04 19:58:59 - mmengine - INFO - Epoch(train) [20][ 440/2569] lr: 4.0000e-02 eta: 1 day, 0:56:19 time: 0.2672 data_time: 0.0076 memory: 5828 grad_norm: 2.8787 loss: 2.1590 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1590 2023/06/04 19:59:04 - mmengine - INFO - Epoch(train) [20][ 460/2569] lr: 4.0000e-02 eta: 1 day, 0:56:13 time: 0.2642 data_time: 0.0078 memory: 5828 grad_norm: 2.8068 loss: 2.4088 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4088 2023/06/04 19:59:10 - mmengine - INFO - Epoch(train) [20][ 480/2569] lr: 4.0000e-02 eta: 1 day, 0:56:07 time: 0.2606 data_time: 0.0076 memory: 5828 grad_norm: 2.9281 loss: 2.4073 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4073 2023/06/04 19:59:15 - mmengine - INFO - Epoch(train) [20][ 500/2569] lr: 4.0000e-02 eta: 1 day, 0:56:03 time: 0.2725 data_time: 0.0073 memory: 5828 grad_norm: 2.8777 loss: 2.1950 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1950 2023/06/04 19:59:20 - mmengine - INFO - Epoch(train) [20][ 520/2569] lr: 4.0000e-02 eta: 1 day, 0:55:57 time: 0.2659 data_time: 0.0080 memory: 5828 grad_norm: 2.8639 loss: 2.6649 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6649 2023/06/04 19:59:26 - mmengine - INFO - Epoch(train) [20][ 540/2569] lr: 4.0000e-02 eta: 1 day, 0:55:53 time: 0.2749 data_time: 0.0079 memory: 5828 grad_norm: 2.9081 loss: 2.9386 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.9386 2023/06/04 19:59:31 - mmengine - INFO - Epoch(train) [20][ 560/2569] lr: 4.0000e-02 eta: 1 day, 0:55:47 time: 0.2628 data_time: 0.0080 memory: 5828 grad_norm: 2.8338 loss: 2.1500 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1500 2023/06/04 19:59:36 - mmengine - INFO - Epoch(train) [20][ 580/2569] lr: 4.0000e-02 eta: 1 day, 0:55:41 time: 0.2628 data_time: 0.0079 memory: 5828 grad_norm: 2.8779 loss: 2.5233 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5233 2023/06/04 19:59:42 - mmengine - INFO - Epoch(train) [20][ 600/2569] lr: 4.0000e-02 eta: 1 day, 0:55:36 time: 0.2715 data_time: 0.0080 memory: 5828 grad_norm: 2.8160 loss: 2.4626 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4626 2023/06/04 19:59:47 - mmengine - INFO - Epoch(train) [20][ 620/2569] lr: 4.0000e-02 eta: 1 day, 0:55:31 time: 0.2693 data_time: 0.0082 memory: 5828 grad_norm: 2.8331 loss: 2.7345 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7345 2023/06/04 19:59:53 - mmengine - INFO - Epoch(train) [20][ 640/2569] lr: 4.0000e-02 eta: 1 day, 0:55:27 time: 0.2730 data_time: 0.0080 memory: 5828 grad_norm: 2.8450 loss: 2.4629 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4629 2023/06/04 19:59:58 - mmengine - INFO - Epoch(train) [20][ 660/2569] lr: 4.0000e-02 eta: 1 day, 0:55:22 time: 0.2727 data_time: 0.0075 memory: 5828 grad_norm: 2.8733 loss: 2.6519 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6519 2023/06/04 20:00:03 - mmengine - INFO - Epoch(train) [20][ 680/2569] lr: 4.0000e-02 eta: 1 day, 0:55:16 time: 0.2624 data_time: 0.0079 memory: 5828 grad_norm: 2.8205 loss: 2.6010 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6010 2023/06/04 20:00:09 - mmengine - INFO - Epoch(train) [20][ 700/2569] lr: 4.0000e-02 eta: 1 day, 0:55:10 time: 0.2651 data_time: 0.0080 memory: 5828 grad_norm: 2.8402 loss: 2.4925 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4925 2023/06/04 20:00:14 - mmengine - INFO - Epoch(train) [20][ 720/2569] lr: 4.0000e-02 eta: 1 day, 0:55:04 time: 0.2629 data_time: 0.0078 memory: 5828 grad_norm: 2.8843 loss: 2.7522 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7522 2023/06/04 20:00:19 - mmengine - INFO - Epoch(train) [20][ 740/2569] lr: 4.0000e-02 eta: 1 day, 0:55:00 time: 0.2712 data_time: 0.0077 memory: 5828 grad_norm: 2.8337 loss: 2.7088 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7088 2023/06/04 20:00:25 - mmengine - INFO - Epoch(train) [20][ 760/2569] lr: 4.0000e-02 eta: 1 day, 0:54:54 time: 0.2669 data_time: 0.0080 memory: 5828 grad_norm: 2.8791 loss: 2.5913 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5913 2023/06/04 20:00:30 - mmengine - INFO - Epoch(train) [20][ 780/2569] lr: 4.0000e-02 eta: 1 day, 0:54:49 time: 0.2706 data_time: 0.0076 memory: 5828 grad_norm: 2.7938 loss: 2.4695 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4695 2023/06/04 20:00:35 - mmengine - INFO - Epoch(train) [20][ 800/2569] lr: 4.0000e-02 eta: 1 day, 0:54:44 time: 0.2655 data_time: 0.0077 memory: 5828 grad_norm: 2.8588 loss: 2.6792 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6792 2023/06/04 20:00:41 - mmengine - INFO - Epoch(train) [20][ 820/2569] lr: 4.0000e-02 eta: 1 day, 0:54:38 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 2.9043 loss: 2.3365 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3365 2023/06/04 20:00:46 - mmengine - INFO - Epoch(train) [20][ 840/2569] lr: 4.0000e-02 eta: 1 day, 0:54:34 time: 0.2755 data_time: 0.0076 memory: 5828 grad_norm: 2.8536 loss: 2.4163 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4163 2023/06/04 20:00:52 - mmengine - INFO - Epoch(train) [20][ 860/2569] lr: 4.0000e-02 eta: 1 day, 0:54:28 time: 0.2681 data_time: 0.0074 memory: 5828 grad_norm: 2.9054 loss: 2.3748 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3748 2023/06/04 20:00:57 - mmengine - INFO - Epoch(train) [20][ 880/2569] lr: 4.0000e-02 eta: 1 day, 0:54:24 time: 0.2739 data_time: 0.0079 memory: 5828 grad_norm: 2.9102 loss: 2.5277 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5277 2023/06/04 20:01:02 - mmengine - INFO - Epoch(train) [20][ 900/2569] lr: 4.0000e-02 eta: 1 day, 0:54:19 time: 0.2699 data_time: 0.0077 memory: 5828 grad_norm: 2.8768 loss: 2.6892 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6892 2023/06/04 20:01:08 - mmengine - INFO - Epoch(train) [20][ 920/2569] lr: 4.0000e-02 eta: 1 day, 0:54:14 time: 0.2681 data_time: 0.0083 memory: 5828 grad_norm: 2.8950 loss: 2.7590 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7590 2023/06/04 20:01:13 - mmengine - INFO - Epoch(train) [20][ 940/2569] lr: 4.0000e-02 eta: 1 day, 0:54:09 time: 0.2696 data_time: 0.0080 memory: 5828 grad_norm: 2.8448 loss: 2.2149 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2149 2023/06/04 20:01:18 - mmengine - INFO - Epoch(train) [20][ 960/2569] lr: 4.0000e-02 eta: 1 day, 0:54:03 time: 0.2654 data_time: 0.0079 memory: 5828 grad_norm: 2.9117 loss: 2.6484 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6484 2023/06/04 20:01:24 - mmengine - INFO - Epoch(train) [20][ 980/2569] lr: 4.0000e-02 eta: 1 day, 0:53:57 time: 0.2627 data_time: 0.0076 memory: 5828 grad_norm: 2.8580 loss: 2.3646 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3646 2023/06/04 20:01:29 - mmengine - INFO - Epoch(train) [20][1000/2569] lr: 4.0000e-02 eta: 1 day, 0:53:52 time: 0.2648 data_time: 0.0075 memory: 5828 grad_norm: 2.8920 loss: 2.4496 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4496 2023/06/04 20:01:34 - mmengine - INFO - Epoch(train) [20][1020/2569] lr: 4.0000e-02 eta: 1 day, 0:53:46 time: 0.2668 data_time: 0.0077 memory: 5828 grad_norm: 2.8906 loss: 2.7858 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7858 2023/06/04 20:01:40 - mmengine - INFO - Epoch(train) [20][1040/2569] lr: 4.0000e-02 eta: 1 day, 0:53:40 time: 0.2638 data_time: 0.0076 memory: 5828 grad_norm: 2.8776 loss: 2.7122 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7122 2023/06/04 20:01:45 - mmengine - INFO - Epoch(train) [20][1060/2569] lr: 4.0000e-02 eta: 1 day, 0:53:34 time: 0.2606 data_time: 0.0080 memory: 5828 grad_norm: 2.8678 loss: 2.4762 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4762 2023/06/04 20:01:50 - mmengine - INFO - Epoch(train) [20][1080/2569] lr: 4.0000e-02 eta: 1 day, 0:53:29 time: 0.2704 data_time: 0.0076 memory: 5828 grad_norm: 2.8833 loss: 2.6830 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6830 2023/06/04 20:01:56 - mmengine - INFO - Epoch(train) [20][1100/2569] lr: 4.0000e-02 eta: 1 day, 0:53:24 time: 0.2676 data_time: 0.0083 memory: 5828 grad_norm: 2.8580 loss: 2.9455 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9455 2023/06/04 20:02:01 - mmengine - INFO - Epoch(train) [20][1120/2569] lr: 4.0000e-02 eta: 1 day, 0:53:21 time: 0.2817 data_time: 0.0078 memory: 5828 grad_norm: 2.8300 loss: 2.6716 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6716 2023/06/04 20:02:07 - mmengine - INFO - Epoch(train) [20][1140/2569] lr: 4.0000e-02 eta: 1 day, 0:53:16 time: 0.2728 data_time: 0.0078 memory: 5828 grad_norm: 2.8686 loss: 2.7391 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7391 2023/06/04 20:02:12 - mmengine - INFO - Epoch(train) [20][1160/2569] lr: 4.0000e-02 eta: 1 day, 0:53:10 time: 0.2610 data_time: 0.0083 memory: 5828 grad_norm: 2.8901 loss: 2.8021 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8021 2023/06/04 20:02:17 - mmengine - INFO - Epoch(train) [20][1180/2569] lr: 4.0000e-02 eta: 1 day, 0:53:04 time: 0.2622 data_time: 0.0077 memory: 5828 grad_norm: 2.8756 loss: 2.5392 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5392 2023/06/04 20:02:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:02:22 - mmengine - INFO - Epoch(train) [20][1200/2569] lr: 4.0000e-02 eta: 1 day, 0:52:58 time: 0.2654 data_time: 0.0083 memory: 5828 grad_norm: 2.8759 loss: 2.6764 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6764 2023/06/04 20:02:28 - mmengine - INFO - Epoch(train) [20][1220/2569] lr: 4.0000e-02 eta: 1 day, 0:52:52 time: 0.2620 data_time: 0.0080 memory: 5828 grad_norm: 2.9115 loss: 2.6694 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6694 2023/06/04 20:02:33 - mmengine - INFO - Epoch(train) [20][1240/2569] lr: 4.0000e-02 eta: 1 day, 0:52:47 time: 0.2692 data_time: 0.0079 memory: 5828 grad_norm: 2.8531 loss: 2.4896 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4896 2023/06/04 20:02:38 - mmengine - INFO - Epoch(train) [20][1260/2569] lr: 4.0000e-02 eta: 1 day, 0:52:42 time: 0.2677 data_time: 0.0080 memory: 5828 grad_norm: 2.8723 loss: 2.7668 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7668 2023/06/04 20:02:44 - mmengine - INFO - Epoch(train) [20][1280/2569] lr: 4.0000e-02 eta: 1 day, 0:52:36 time: 0.2609 data_time: 0.0087 memory: 5828 grad_norm: 2.8815 loss: 2.3283 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3283 2023/06/04 20:02:49 - mmengine - INFO - Epoch(train) [20][1300/2569] lr: 4.0000e-02 eta: 1 day, 0:52:32 time: 0.2768 data_time: 0.0081 memory: 5828 grad_norm: 2.8367 loss: 2.4048 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4048 2023/06/04 20:02:54 - mmengine - INFO - Epoch(train) [20][1320/2569] lr: 4.0000e-02 eta: 1 day, 0:52:26 time: 0.2610 data_time: 0.0081 memory: 5828 grad_norm: 2.8292 loss: 2.8013 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8013 2023/06/04 20:03:00 - mmengine - INFO - Epoch(train) [20][1340/2569] lr: 4.0000e-02 eta: 1 day, 0:52:21 time: 0.2728 data_time: 0.0076 memory: 5828 grad_norm: 2.8559 loss: 2.5903 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5903 2023/06/04 20:03:05 - mmengine - INFO - Epoch(train) [20][1360/2569] lr: 4.0000e-02 eta: 1 day, 0:52:15 time: 0.2616 data_time: 0.0084 memory: 5828 grad_norm: 2.8484 loss: 2.5370 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5370 2023/06/04 20:03:11 - mmengine - INFO - Epoch(train) [20][1380/2569] lr: 4.0000e-02 eta: 1 day, 0:52:10 time: 0.2713 data_time: 0.0081 memory: 5828 grad_norm: 2.8636 loss: 2.6411 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6411 2023/06/04 20:03:16 - mmengine - INFO - Epoch(train) [20][1400/2569] lr: 4.0000e-02 eta: 1 day, 0:52:04 time: 0.2610 data_time: 0.0083 memory: 5828 grad_norm: 2.7969 loss: 2.4407 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4407 2023/06/04 20:03:21 - mmengine - INFO - Epoch(train) [20][1420/2569] lr: 4.0000e-02 eta: 1 day, 0:51:58 time: 0.2621 data_time: 0.0079 memory: 5828 grad_norm: 2.9170 loss: 2.5441 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5441 2023/06/04 20:03:26 - mmengine - INFO - Epoch(train) [20][1440/2569] lr: 4.0000e-02 eta: 1 day, 0:51:52 time: 0.2644 data_time: 0.0078 memory: 5828 grad_norm: 2.8450 loss: 2.5166 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5166 2023/06/04 20:03:32 - mmengine - INFO - Epoch(train) [20][1460/2569] lr: 4.0000e-02 eta: 1 day, 0:51:47 time: 0.2708 data_time: 0.0074 memory: 5828 grad_norm: 2.8323 loss: 2.1910 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1910 2023/06/04 20:03:37 - mmengine - INFO - Epoch(train) [20][1480/2569] lr: 4.0000e-02 eta: 1 day, 0:51:42 time: 0.2680 data_time: 0.0079 memory: 5828 grad_norm: 2.8509 loss: 2.7190 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7190 2023/06/04 20:03:42 - mmengine - INFO - Epoch(train) [20][1500/2569] lr: 4.0000e-02 eta: 1 day, 0:51:36 time: 0.2628 data_time: 0.0082 memory: 5828 grad_norm: 2.8923 loss: 2.5119 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5119 2023/06/04 20:03:48 - mmengine - INFO - Epoch(train) [20][1520/2569] lr: 4.0000e-02 eta: 1 day, 0:51:31 time: 0.2683 data_time: 0.0076 memory: 5828 grad_norm: 2.8419 loss: 2.8187 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8187 2023/06/04 20:03:53 - mmengine - INFO - Epoch(train) [20][1540/2569] lr: 4.0000e-02 eta: 1 day, 0:51:26 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 2.8885 loss: 2.6131 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6131 2023/06/04 20:03:58 - mmengine - INFO - Epoch(train) [20][1560/2569] lr: 4.0000e-02 eta: 1 day, 0:51:20 time: 0.2630 data_time: 0.0073 memory: 5828 grad_norm: 2.8652 loss: 2.5692 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5692 2023/06/04 20:04:04 - mmengine - INFO - Epoch(train) [20][1580/2569] lr: 4.0000e-02 eta: 1 day, 0:51:14 time: 0.2643 data_time: 0.0078 memory: 5828 grad_norm: 2.8303 loss: 2.5960 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.5960 2023/06/04 20:04:09 - mmengine - INFO - Epoch(train) [20][1600/2569] lr: 4.0000e-02 eta: 1 day, 0:51:09 time: 0.2678 data_time: 0.0078 memory: 5828 grad_norm: 2.8468 loss: 2.1449 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1449 2023/06/04 20:04:14 - mmengine - INFO - Epoch(train) [20][1620/2569] lr: 4.0000e-02 eta: 1 day, 0:51:03 time: 0.2659 data_time: 0.0080 memory: 5828 grad_norm: 2.8885 loss: 2.6520 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6520 2023/06/04 20:04:20 - mmengine - INFO - Epoch(train) [20][1640/2569] lr: 4.0000e-02 eta: 1 day, 0:50:58 time: 0.2697 data_time: 0.0074 memory: 5828 grad_norm: 2.9041 loss: 2.2958 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2958 2023/06/04 20:04:25 - mmengine - INFO - Epoch(train) [20][1660/2569] lr: 4.0000e-02 eta: 1 day, 0:50:54 time: 0.2714 data_time: 0.0076 memory: 5828 grad_norm: 2.8943 loss: 2.8288 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.8288 2023/06/04 20:04:30 - mmengine - INFO - Epoch(train) [20][1680/2569] lr: 4.0000e-02 eta: 1 day, 0:50:48 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 2.8549 loss: 2.8217 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8217 2023/06/04 20:04:36 - mmengine - INFO - Epoch(train) [20][1700/2569] lr: 4.0000e-02 eta: 1 day, 0:50:43 time: 0.2734 data_time: 0.0075 memory: 5828 grad_norm: 2.8136 loss: 2.7223 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7223 2023/06/04 20:04:41 - mmengine - INFO - Epoch(train) [20][1720/2569] lr: 4.0000e-02 eta: 1 day, 0:50:39 time: 0.2720 data_time: 0.0076 memory: 5828 grad_norm: 2.8375 loss: 2.3944 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3944 2023/06/04 20:04:47 - mmengine - INFO - Epoch(train) [20][1740/2569] lr: 4.0000e-02 eta: 1 day, 0:50:33 time: 0.2675 data_time: 0.0076 memory: 5828 grad_norm: 2.8352 loss: 2.4950 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4950 2023/06/04 20:04:52 - mmengine - INFO - Epoch(train) [20][1760/2569] lr: 4.0000e-02 eta: 1 day, 0:50:28 time: 0.2653 data_time: 0.0076 memory: 5828 grad_norm: 2.8537 loss: 2.7598 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7598 2023/06/04 20:04:57 - mmengine - INFO - Epoch(train) [20][1780/2569] lr: 4.0000e-02 eta: 1 day, 0:50:23 time: 0.2684 data_time: 0.0077 memory: 5828 grad_norm: 2.8406 loss: 2.6356 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.6356 2023/06/04 20:05:03 - mmengine - INFO - Epoch(train) [20][1800/2569] lr: 4.0000e-02 eta: 1 day, 0:50:18 time: 0.2685 data_time: 0.0077 memory: 5828 grad_norm: 2.8898 loss: 2.8533 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8533 2023/06/04 20:05:08 - mmengine - INFO - Epoch(train) [20][1820/2569] lr: 4.0000e-02 eta: 1 day, 0:50:11 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 2.9121 loss: 2.1781 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1781 2023/06/04 20:05:13 - mmengine - INFO - Epoch(train) [20][1840/2569] lr: 4.0000e-02 eta: 1 day, 0:50:06 time: 0.2693 data_time: 0.0077 memory: 5828 grad_norm: 2.8643 loss: 2.6953 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6953 2023/06/04 20:05:19 - mmengine - INFO - Epoch(train) [20][1860/2569] lr: 4.0000e-02 eta: 1 day, 0:50:01 time: 0.2658 data_time: 0.0078 memory: 5828 grad_norm: 2.8470 loss: 2.8739 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8739 2023/06/04 20:05:24 - mmengine - INFO - Epoch(train) [20][1880/2569] lr: 4.0000e-02 eta: 1 day, 0:49:56 time: 0.2689 data_time: 0.0078 memory: 5828 grad_norm: 2.8663 loss: 2.2441 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2441 2023/06/04 20:05:29 - mmengine - INFO - Epoch(train) [20][1900/2569] lr: 4.0000e-02 eta: 1 day, 0:49:51 time: 0.2695 data_time: 0.0077 memory: 5828 grad_norm: 2.8560 loss: 2.5003 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5003 2023/06/04 20:05:35 - mmengine - INFO - Epoch(train) [20][1920/2569] lr: 4.0000e-02 eta: 1 day, 0:49:45 time: 0.2680 data_time: 0.0078 memory: 5828 grad_norm: 2.8483 loss: 2.4756 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.4756 2023/06/04 20:05:40 - mmengine - INFO - Epoch(train) [20][1940/2569] lr: 4.0000e-02 eta: 1 day, 0:49:40 time: 0.2632 data_time: 0.0079 memory: 5828 grad_norm: 2.8775 loss: 2.4615 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4615 2023/06/04 20:05:45 - mmengine - INFO - Epoch(train) [20][1960/2569] lr: 4.0000e-02 eta: 1 day, 0:49:34 time: 0.2686 data_time: 0.0080 memory: 5828 grad_norm: 2.8174 loss: 2.7575 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.7575 2023/06/04 20:05:51 - mmengine - INFO - Epoch(train) [20][1980/2569] lr: 4.0000e-02 eta: 1 day, 0:49:30 time: 0.2758 data_time: 0.0081 memory: 5828 grad_norm: 2.8689 loss: 2.1726 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1726 2023/06/04 20:05:56 - mmengine - INFO - Epoch(train) [20][2000/2569] lr: 4.0000e-02 eta: 1 day, 0:49:25 time: 0.2654 data_time: 0.0080 memory: 5828 grad_norm: 2.8803 loss: 2.7949 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7949 2023/06/04 20:06:02 - mmengine - INFO - Epoch(train) [20][2020/2569] lr: 4.0000e-02 eta: 1 day, 0:49:20 time: 0.2742 data_time: 0.0072 memory: 5828 grad_norm: 2.8949 loss: 2.6644 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6644 2023/06/04 20:06:07 - mmengine - INFO - Epoch(train) [20][2040/2569] lr: 4.0000e-02 eta: 1 day, 0:49:14 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 2.8761 loss: 2.3445 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3445 2023/06/04 20:06:12 - mmengine - INFO - Epoch(train) [20][2060/2569] lr: 4.0000e-02 eta: 1 day, 0:49:09 time: 0.2685 data_time: 0.0081 memory: 5828 grad_norm: 2.9253 loss: 2.5755 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5755 2023/06/04 20:06:18 - mmengine - INFO - Epoch(train) [20][2080/2569] lr: 4.0000e-02 eta: 1 day, 0:49:04 time: 0.2672 data_time: 0.0077 memory: 5828 grad_norm: 2.8600 loss: 2.4077 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4077 2023/06/04 20:06:23 - mmengine - INFO - Epoch(train) [20][2100/2569] lr: 4.0000e-02 eta: 1 day, 0:49:00 time: 0.2765 data_time: 0.0078 memory: 5828 grad_norm: 2.8028 loss: 2.3672 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3672 2023/06/04 20:06:28 - mmengine - INFO - Epoch(train) [20][2120/2569] lr: 4.0000e-02 eta: 1 day, 0:48:53 time: 0.2607 data_time: 0.0078 memory: 5828 grad_norm: 2.8450 loss: 2.6957 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6957 2023/06/04 20:06:34 - mmengine - INFO - Epoch(train) [20][2140/2569] lr: 4.0000e-02 eta: 1 day, 0:48:49 time: 0.2721 data_time: 0.0072 memory: 5828 grad_norm: 2.8990 loss: 2.9228 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.9228 2023/06/04 20:06:39 - mmengine - INFO - Epoch(train) [20][2160/2569] lr: 4.0000e-02 eta: 1 day, 0:48:43 time: 0.2610 data_time: 0.0079 memory: 5828 grad_norm: 2.8682 loss: 2.5150 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5150 2023/06/04 20:06:44 - mmengine - INFO - Epoch(train) [20][2180/2569] lr: 4.0000e-02 eta: 1 day, 0:48:37 time: 0.2686 data_time: 0.0078 memory: 5828 grad_norm: 2.8335 loss: 2.7954 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7954 2023/06/04 20:06:47 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:06:50 - mmengine - INFO - Epoch(train) [20][2200/2569] lr: 4.0000e-02 eta: 1 day, 0:48:32 time: 0.2634 data_time: 0.0079 memory: 5828 grad_norm: 2.8408 loss: 2.5821 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5821 2023/06/04 20:06:55 - mmengine - INFO - Epoch(train) [20][2220/2569] lr: 4.0000e-02 eta: 1 day, 0:48:27 time: 0.2731 data_time: 0.0074 memory: 5828 grad_norm: 2.8633 loss: 2.6792 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6792 2023/06/04 20:07:00 - mmengine - INFO - Epoch(train) [20][2240/2569] lr: 4.0000e-02 eta: 1 day, 0:48:21 time: 0.2598 data_time: 0.0078 memory: 5828 grad_norm: 2.8668 loss: 2.7470 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7470 2023/06/04 20:07:06 - mmengine - INFO - Epoch(train) [20][2260/2569] lr: 4.0000e-02 eta: 1 day, 0:48:16 time: 0.2694 data_time: 0.0084 memory: 5828 grad_norm: 2.8289 loss: 2.8991 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8991 2023/06/04 20:07:11 - mmengine - INFO - Epoch(train) [20][2280/2569] lr: 4.0000e-02 eta: 1 day, 0:48:10 time: 0.2613 data_time: 0.0081 memory: 5828 grad_norm: 2.8589 loss: 2.7251 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7251 2023/06/04 20:07:16 - mmengine - INFO - Epoch(train) [20][2300/2569] lr: 4.0000e-02 eta: 1 day, 0:48:04 time: 0.2679 data_time: 0.0085 memory: 5828 grad_norm: 2.8916 loss: 2.5026 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5026 2023/06/04 20:07:22 - mmengine - INFO - Epoch(train) [20][2320/2569] lr: 4.0000e-02 eta: 1 day, 0:47:59 time: 0.2681 data_time: 0.0076 memory: 5828 grad_norm: 2.8679 loss: 2.4819 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4819 2023/06/04 20:07:27 - mmengine - INFO - Epoch(train) [20][2340/2569] lr: 4.0000e-02 eta: 1 day, 0:47:56 time: 0.2807 data_time: 0.0075 memory: 5828 grad_norm: 2.8174 loss: 2.7549 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7549 2023/06/04 20:07:33 - mmengine - INFO - Epoch(train) [20][2360/2569] lr: 4.0000e-02 eta: 1 day, 0:47:50 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 2.8160 loss: 2.8790 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8790 2023/06/04 20:07:38 - mmengine - INFO - Epoch(train) [20][2380/2569] lr: 4.0000e-02 eta: 1 day, 0:47:45 time: 0.2761 data_time: 0.0075 memory: 5828 grad_norm: 2.8624 loss: 2.4571 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4571 2023/06/04 20:07:43 - mmengine - INFO - Epoch(train) [20][2400/2569] lr: 4.0000e-02 eta: 1 day, 0:47:40 time: 0.2660 data_time: 0.0083 memory: 5828 grad_norm: 2.8682 loss: 2.5614 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5614 2023/06/04 20:07:49 - mmengine - INFO - Epoch(train) [20][2420/2569] lr: 4.0000e-02 eta: 1 day, 0:47:36 time: 0.2791 data_time: 0.0081 memory: 5828 grad_norm: 2.8227 loss: 2.3018 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3018 2023/06/04 20:07:54 - mmengine - INFO - Epoch(train) [20][2440/2569] lr: 4.0000e-02 eta: 1 day, 0:47:30 time: 0.2645 data_time: 0.0085 memory: 5828 grad_norm: 2.8735 loss: 2.7655 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7655 2023/06/04 20:08:00 - mmengine - INFO - Epoch(train) [20][2460/2569] lr: 4.0000e-02 eta: 1 day, 0:47:26 time: 0.2750 data_time: 0.0078 memory: 5828 grad_norm: 2.8466 loss: 2.6487 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6487 2023/06/04 20:08:05 - mmengine - INFO - Epoch(train) [20][2480/2569] lr: 4.0000e-02 eta: 1 day, 0:47:21 time: 0.2720 data_time: 0.0075 memory: 5828 grad_norm: 2.8825 loss: 2.3943 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3943 2023/06/04 20:08:11 - mmengine - INFO - Epoch(train) [20][2500/2569] lr: 4.0000e-02 eta: 1 day, 0:47:16 time: 0.2659 data_time: 0.0080 memory: 5828 grad_norm: 2.8373 loss: 2.6758 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6758 2023/06/04 20:08:16 - mmengine - INFO - Epoch(train) [20][2520/2569] lr: 4.0000e-02 eta: 1 day, 0:47:11 time: 0.2712 data_time: 0.0077 memory: 5828 grad_norm: 2.9377 loss: 2.5203 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5203 2023/06/04 20:08:21 - mmengine - INFO - Epoch(train) [20][2540/2569] lr: 4.0000e-02 eta: 1 day, 0:47:05 time: 0.2610 data_time: 0.0076 memory: 5828 grad_norm: 2.8179 loss: 2.5239 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5239 2023/06/04 20:08:27 - mmengine - INFO - Epoch(train) [20][2560/2569] lr: 4.0000e-02 eta: 1 day, 0:46:59 time: 0.2623 data_time: 0.0078 memory: 5828 grad_norm: 2.8659 loss: 2.5171 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5171 2023/06/04 20:08:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:08:29 - mmengine - INFO - Epoch(train) [20][2569/2569] lr: 4.0000e-02 eta: 1 day, 0:46:55 time: 0.2491 data_time: 0.0079 memory: 5828 grad_norm: 2.8901 loss: 2.6262 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.6262 2023/06/04 20:08:29 - mmengine - INFO - Saving checkpoint at 20 epochs 2023/06/04 20:08:36 - mmengine - INFO - Epoch(val) [20][ 20/260] eta: 0:00:43 time: 0.1820 data_time: 0.1233 memory: 1238 2023/06/04 20:08:39 - mmengine - INFO - Epoch(val) [20][ 40/260] eta: 0:00:35 time: 0.1429 data_time: 0.0841 memory: 1238 2023/06/04 20:08:42 - mmengine - INFO - Epoch(val) [20][ 60/260] eta: 0:00:32 time: 0.1552 data_time: 0.0970 memory: 1238 2023/06/04 20:08:44 - mmengine - INFO - Epoch(val) [20][ 80/260] eta: 0:00:27 time: 0.1300 data_time: 0.0716 memory: 1238 2023/06/04 20:08:47 - mmengine - INFO - Epoch(val) [20][100/260] eta: 0:00:24 time: 0.1536 data_time: 0.0950 memory: 1238 2023/06/04 20:08:50 - mmengine - INFO - Epoch(val) [20][120/260] eta: 0:00:21 time: 0.1443 data_time: 0.0852 memory: 1238 2023/06/04 20:08:53 - mmengine - INFO - Epoch(val) [20][140/260] eta: 0:00:18 time: 0.1426 data_time: 0.0840 memory: 1238 2023/06/04 20:08:56 - mmengine - INFO - Epoch(val) [20][160/260] eta: 0:00:14 time: 0.1326 data_time: 0.0737 memory: 1238 2023/06/04 20:08:59 - mmengine - INFO - Epoch(val) [20][180/260] eta: 0:00:11 time: 0.1323 data_time: 0.0740 memory: 1238 2023/06/04 20:09:01 - mmengine - INFO - Epoch(val) [20][200/260] eta: 0:00:08 time: 0.1277 data_time: 0.0696 memory: 1238 2023/06/04 20:09:04 - mmengine - INFO - Epoch(val) [20][220/260] eta: 0:00:05 time: 0.1559 data_time: 0.0976 memory: 1238 2023/06/04 20:09:06 - mmengine - INFO - Epoch(val) [20][240/260] eta: 0:00:02 time: 0.1129 data_time: 0.0558 memory: 1238 2023/06/04 20:09:09 - mmengine - INFO - Epoch(val) [20][260/260] eta: 0:00:00 time: 0.1057 data_time: 0.0498 memory: 1238 2023/06/04 20:09:15 - mmengine - INFO - Epoch(val) [20][260/260] acc/top1: 0.4781 acc/top5: 0.7277 acc/mean1: 0.4702 data_time: 0.0813 time: 0.1395 2023/06/04 20:09:22 - mmengine - INFO - Epoch(train) [21][ 20/2569] lr: 4.0000e-02 eta: 1 day, 0:47:01 time: 0.3521 data_time: 0.0617 memory: 5828 grad_norm: 2.9065 loss: 2.4089 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4089 2023/06/04 20:09:28 - mmengine - INFO - Epoch(train) [21][ 40/2569] lr: 4.0000e-02 eta: 1 day, 0:46:55 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 2.8985 loss: 3.0754 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 3.0754 2023/06/04 20:09:33 - mmengine - INFO - Epoch(train) [21][ 60/2569] lr: 4.0000e-02 eta: 1 day, 0:46:49 time: 0.2593 data_time: 0.0074 memory: 5828 grad_norm: 2.8460 loss: 2.7089 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7089 2023/06/04 20:09:38 - mmengine - INFO - Epoch(train) [21][ 80/2569] lr: 4.0000e-02 eta: 1 day, 0:46:43 time: 0.2658 data_time: 0.0080 memory: 5828 grad_norm: 2.8849 loss: 2.2795 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2795 2023/06/04 20:09:43 - mmengine - INFO - Epoch(train) [21][ 100/2569] lr: 4.0000e-02 eta: 1 day, 0:46:38 time: 0.2664 data_time: 0.0075 memory: 5828 grad_norm: 2.8592 loss: 2.5080 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5080 2023/06/04 20:09:49 - mmengine - INFO - Epoch(train) [21][ 120/2569] lr: 4.0000e-02 eta: 1 day, 0:46:34 time: 0.2746 data_time: 0.0077 memory: 5828 grad_norm: 2.8235 loss: 2.5244 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5244 2023/06/04 20:09:54 - mmengine - INFO - Epoch(train) [21][ 140/2569] lr: 4.0000e-02 eta: 1 day, 0:46:28 time: 0.2632 data_time: 0.0071 memory: 5828 grad_norm: 2.9137 loss: 2.6679 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6679 2023/06/04 20:10:00 - mmengine - INFO - Epoch(train) [21][ 160/2569] lr: 4.0000e-02 eta: 1 day, 0:46:24 time: 0.2805 data_time: 0.0077 memory: 5828 grad_norm: 2.8753 loss: 2.6237 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6237 2023/06/04 20:10:05 - mmengine - INFO - Epoch(train) [21][ 180/2569] lr: 4.0000e-02 eta: 1 day, 0:46:18 time: 0.2629 data_time: 0.0080 memory: 5828 grad_norm: 2.8479 loss: 2.6552 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6552 2023/06/04 20:10:11 - mmengine - INFO - Epoch(train) [21][ 200/2569] lr: 4.0000e-02 eta: 1 day, 0:46:15 time: 0.2839 data_time: 0.0076 memory: 5828 grad_norm: 2.9046 loss: 2.6229 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6229 2023/06/04 20:10:16 - mmengine - INFO - Epoch(train) [21][ 220/2569] lr: 4.0000e-02 eta: 1 day, 0:46:09 time: 0.2615 data_time: 0.0080 memory: 5828 grad_norm: 2.8739 loss: 2.4956 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4956 2023/06/04 20:10:22 - mmengine - INFO - Epoch(train) [21][ 240/2569] lr: 4.0000e-02 eta: 1 day, 0:46:05 time: 0.2744 data_time: 0.0078 memory: 5828 grad_norm: 2.9632 loss: 2.6948 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6948 2023/06/04 20:10:27 - mmengine - INFO - Epoch(train) [21][ 260/2569] lr: 4.0000e-02 eta: 1 day, 0:45:59 time: 0.2638 data_time: 0.0076 memory: 5828 grad_norm: 2.8430 loss: 2.6141 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6141 2023/06/04 20:10:32 - mmengine - INFO - Epoch(train) [21][ 280/2569] lr: 4.0000e-02 eta: 1 day, 0:45:53 time: 0.2620 data_time: 0.0082 memory: 5828 grad_norm: 2.8745 loss: 2.6779 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6779 2023/06/04 20:10:37 - mmengine - INFO - Epoch(train) [21][ 300/2569] lr: 4.0000e-02 eta: 1 day, 0:45:47 time: 0.2658 data_time: 0.0078 memory: 5828 grad_norm: 2.8469 loss: 2.7412 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7412 2023/06/04 20:10:43 - mmengine - INFO - Epoch(train) [21][ 320/2569] lr: 4.0000e-02 eta: 1 day, 0:45:42 time: 0.2660 data_time: 0.0079 memory: 5828 grad_norm: 2.9210 loss: 2.0455 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0455 2023/06/04 20:10:48 - mmengine - INFO - Epoch(train) [21][ 340/2569] lr: 4.0000e-02 eta: 1 day, 0:45:37 time: 0.2729 data_time: 0.0084 memory: 5828 grad_norm: 2.9266 loss: 2.5217 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5217 2023/06/04 20:10:53 - mmengine - INFO - Epoch(train) [21][ 360/2569] lr: 4.0000e-02 eta: 1 day, 0:45:31 time: 0.2649 data_time: 0.0081 memory: 5828 grad_norm: 2.9010 loss: 2.6544 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6544 2023/06/04 20:10:59 - mmengine - INFO - Epoch(train) [21][ 380/2569] lr: 4.0000e-02 eta: 1 day, 0:45:26 time: 0.2696 data_time: 0.0082 memory: 5828 grad_norm: 2.8578 loss: 2.6426 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6426 2023/06/04 20:11:04 - mmengine - INFO - Epoch(train) [21][ 400/2569] lr: 4.0000e-02 eta: 1 day, 0:45:20 time: 0.2623 data_time: 0.0076 memory: 5828 grad_norm: 2.9107 loss: 2.4379 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4379 2023/06/04 20:11:09 - mmengine - INFO - Epoch(train) [21][ 420/2569] lr: 4.0000e-02 eta: 1 day, 0:45:14 time: 0.2619 data_time: 0.0083 memory: 5828 grad_norm: 2.8962 loss: 2.4617 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4617 2023/06/04 20:11:15 - mmengine - INFO - Epoch(train) [21][ 440/2569] lr: 4.0000e-02 eta: 1 day, 0:45:08 time: 0.2614 data_time: 0.0075 memory: 5828 grad_norm: 2.8765 loss: 2.8053 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8053 2023/06/04 20:11:20 - mmengine - INFO - Epoch(train) [21][ 460/2569] lr: 4.0000e-02 eta: 1 day, 0:45:03 time: 0.2676 data_time: 0.0081 memory: 5828 grad_norm: 2.9366 loss: 2.6044 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6044 2023/06/04 20:11:25 - mmengine - INFO - Epoch(train) [21][ 480/2569] lr: 4.0000e-02 eta: 1 day, 0:44:57 time: 0.2618 data_time: 0.0083 memory: 5828 grad_norm: 2.9087 loss: 2.3633 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3633 2023/06/04 20:11:30 - mmengine - INFO - Epoch(train) [21][ 500/2569] lr: 4.0000e-02 eta: 1 day, 0:44:52 time: 0.2681 data_time: 0.0077 memory: 5828 grad_norm: 2.8319 loss: 2.5393 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5393 2023/06/04 20:11:36 - mmengine - INFO - Epoch(train) [21][ 520/2569] lr: 4.0000e-02 eta: 1 day, 0:44:46 time: 0.2634 data_time: 0.0079 memory: 5828 grad_norm: 2.8677 loss: 2.3565 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3565 2023/06/04 20:11:41 - mmengine - INFO - Epoch(train) [21][ 540/2569] lr: 4.0000e-02 eta: 1 day, 0:44:41 time: 0.2669 data_time: 0.0079 memory: 5828 grad_norm: 2.8601 loss: 2.6897 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6897 2023/06/04 20:11:46 - mmengine - INFO - Epoch(train) [21][ 560/2569] lr: 4.0000e-02 eta: 1 day, 0:44:34 time: 0.2608 data_time: 0.0077 memory: 5828 grad_norm: 2.7928 loss: 2.7159 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7159 2023/06/04 20:11:52 - mmengine - INFO - Epoch(train) [21][ 580/2569] lr: 4.0000e-02 eta: 1 day, 0:44:29 time: 0.2644 data_time: 0.0079 memory: 5828 grad_norm: 2.8461 loss: 2.2996 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2996 2023/06/04 20:11:57 - mmengine - INFO - Epoch(train) [21][ 600/2569] lr: 4.0000e-02 eta: 1 day, 0:44:23 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 2.8526 loss: 2.7898 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7898 2023/06/04 20:12:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:12:02 - mmengine - INFO - Epoch(train) [21][ 620/2569] lr: 4.0000e-02 eta: 1 day, 0:44:18 time: 0.2710 data_time: 0.0076 memory: 5828 grad_norm: 2.8627 loss: 2.2068 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2068 2023/06/04 20:12:08 - mmengine - INFO - Epoch(train) [21][ 640/2569] lr: 4.0000e-02 eta: 1 day, 0:44:13 time: 0.2685 data_time: 0.0079 memory: 5828 grad_norm: 2.9184 loss: 2.9722 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9722 2023/06/04 20:12:13 - mmengine - INFO - Epoch(train) [21][ 660/2569] lr: 4.0000e-02 eta: 1 day, 0:44:07 time: 0.2642 data_time: 0.0072 memory: 5828 grad_norm: 2.8835 loss: 2.6337 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6337 2023/06/04 20:12:19 - mmengine - INFO - Epoch(train) [21][ 680/2569] lr: 4.0000e-02 eta: 1 day, 0:44:03 time: 0.2775 data_time: 0.0081 memory: 5828 grad_norm: 2.8558 loss: 2.7234 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7234 2023/06/04 20:12:24 - mmengine - INFO - Epoch(train) [21][ 700/2569] lr: 4.0000e-02 eta: 1 day, 0:43:58 time: 0.2661 data_time: 0.0078 memory: 5828 grad_norm: 2.8777 loss: 2.9785 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9785 2023/06/04 20:12:29 - mmengine - INFO - Epoch(train) [21][ 720/2569] lr: 4.0000e-02 eta: 1 day, 0:43:53 time: 0.2682 data_time: 0.0081 memory: 5828 grad_norm: 2.8926 loss: 2.8855 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8855 2023/06/04 20:12:35 - mmengine - INFO - Epoch(train) [21][ 740/2569] lr: 4.0000e-02 eta: 1 day, 0:43:47 time: 0.2641 data_time: 0.0082 memory: 5828 grad_norm: 2.9266 loss: 2.6382 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6382 2023/06/04 20:12:40 - mmengine - INFO - Epoch(train) [21][ 760/2569] lr: 4.0000e-02 eta: 1 day, 0:43:42 time: 0.2708 data_time: 0.0080 memory: 5828 grad_norm: 2.8465 loss: 2.5657 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5657 2023/06/04 20:12:45 - mmengine - INFO - Epoch(train) [21][ 780/2569] lr: 4.0000e-02 eta: 1 day, 0:43:37 time: 0.2672 data_time: 0.0077 memory: 5828 grad_norm: 2.8766 loss: 2.5386 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5386 2023/06/04 20:12:51 - mmengine - INFO - Epoch(train) [21][ 800/2569] lr: 4.0000e-02 eta: 1 day, 0:43:31 time: 0.2671 data_time: 0.0076 memory: 5828 grad_norm: 2.8838 loss: 2.6501 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6501 2023/06/04 20:12:56 - mmengine - INFO - Epoch(train) [21][ 820/2569] lr: 4.0000e-02 eta: 1 day, 0:43:25 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 2.8549 loss: 2.6703 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6703 2023/06/04 20:13:01 - mmengine - INFO - Epoch(train) [21][ 840/2569] lr: 4.0000e-02 eta: 1 day, 0:43:20 time: 0.2649 data_time: 0.0088 memory: 5828 grad_norm: 2.9168 loss: 2.5554 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5554 2023/06/04 20:13:07 - mmengine - INFO - Epoch(train) [21][ 860/2569] lr: 4.0000e-02 eta: 1 day, 0:43:15 time: 0.2744 data_time: 0.0082 memory: 5828 grad_norm: 2.8688 loss: 2.6651 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.6651 2023/06/04 20:13:12 - mmengine - INFO - Epoch(train) [21][ 880/2569] lr: 4.0000e-02 eta: 1 day, 0:43:09 time: 0.2621 data_time: 0.0076 memory: 5828 grad_norm: 2.8395 loss: 2.5591 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5591 2023/06/04 20:13:17 - mmengine - INFO - Epoch(train) [21][ 900/2569] lr: 4.0000e-02 eta: 1 day, 0:43:04 time: 0.2698 data_time: 0.0073 memory: 5828 grad_norm: 2.8662 loss: 2.7185 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7185 2023/06/04 20:13:23 - mmengine - INFO - Epoch(train) [21][ 920/2569] lr: 4.0000e-02 eta: 1 day, 0:42:59 time: 0.2710 data_time: 0.0078 memory: 5828 grad_norm: 2.9600 loss: 2.5096 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5096 2023/06/04 20:13:28 - mmengine - INFO - Epoch(train) [21][ 940/2569] lr: 4.0000e-02 eta: 1 day, 0:42:54 time: 0.2646 data_time: 0.0083 memory: 5828 grad_norm: 2.9025 loss: 2.6661 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6661 2023/06/04 20:13:34 - mmengine - INFO - Epoch(train) [21][ 960/2569] lr: 4.0000e-02 eta: 1 day, 0:42:49 time: 0.2757 data_time: 0.0083 memory: 5828 grad_norm: 2.8659 loss: 2.6499 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6499 2023/06/04 20:13:39 - mmengine - INFO - Epoch(train) [21][ 980/2569] lr: 4.0000e-02 eta: 1 day, 0:42:44 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 2.8345 loss: 2.4995 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4995 2023/06/04 20:13:44 - mmengine - INFO - Epoch(train) [21][1000/2569] lr: 4.0000e-02 eta: 1 day, 0:42:39 time: 0.2711 data_time: 0.0076 memory: 5828 grad_norm: 2.8626 loss: 2.4429 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4429 2023/06/04 20:13:50 - mmengine - INFO - Epoch(train) [21][1020/2569] lr: 4.0000e-02 eta: 1 day, 0:42:35 time: 0.2770 data_time: 0.0078 memory: 5828 grad_norm: 2.8124 loss: 2.6650 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6650 2023/06/04 20:13:55 - mmengine - INFO - Epoch(train) [21][1040/2569] lr: 4.0000e-02 eta: 1 day, 0:42:29 time: 0.2647 data_time: 0.0083 memory: 5828 grad_norm: 2.9261 loss: 2.7539 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7539 2023/06/04 20:14:00 - mmengine - INFO - Epoch(train) [21][1060/2569] lr: 4.0000e-02 eta: 1 day, 0:42:23 time: 0.2605 data_time: 0.0073 memory: 5828 grad_norm: 2.8412 loss: 2.4000 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4000 2023/06/04 20:14:06 - mmengine - INFO - Epoch(train) [21][1080/2569] lr: 4.0000e-02 eta: 1 day, 0:42:18 time: 0.2723 data_time: 0.0077 memory: 5828 grad_norm: 2.9088 loss: 2.4488 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4488 2023/06/04 20:14:11 - mmengine - INFO - Epoch(train) [21][1100/2569] lr: 4.0000e-02 eta: 1 day, 0:42:13 time: 0.2677 data_time: 0.0076 memory: 5828 grad_norm: 2.9580 loss: 2.4511 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4511 2023/06/04 20:14:16 - mmengine - INFO - Epoch(train) [21][1120/2569] lr: 4.0000e-02 eta: 1 day, 0:42:08 time: 0.2674 data_time: 0.0077 memory: 5828 grad_norm: 2.8511 loss: 2.5006 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5006 2023/06/04 20:14:22 - mmengine - INFO - Epoch(train) [21][1140/2569] lr: 4.0000e-02 eta: 1 day, 0:42:02 time: 0.2670 data_time: 0.0071 memory: 5828 grad_norm: 2.8666 loss: 2.5939 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5939 2023/06/04 20:14:27 - mmengine - INFO - Epoch(train) [21][1160/2569] lr: 4.0000e-02 eta: 1 day, 0:41:57 time: 0.2670 data_time: 0.0082 memory: 5828 grad_norm: 2.8659 loss: 2.6187 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6187 2023/06/04 20:14:32 - mmengine - INFO - Epoch(train) [21][1180/2569] lr: 4.0000e-02 eta: 1 day, 0:41:52 time: 0.2690 data_time: 0.0080 memory: 5828 grad_norm: 2.8881 loss: 2.6492 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6492 2023/06/04 20:14:38 - mmengine - INFO - Epoch(train) [21][1200/2569] lr: 4.0000e-02 eta: 1 day, 0:41:46 time: 0.2665 data_time: 0.0080 memory: 5828 grad_norm: 2.9392 loss: 2.6732 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6732 2023/06/04 20:14:43 - mmengine - INFO - Epoch(train) [21][1220/2569] lr: 4.0000e-02 eta: 1 day, 0:41:40 time: 0.2623 data_time: 0.0077 memory: 5828 grad_norm: 2.8602 loss: 2.6832 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6832 2023/06/04 20:14:48 - mmengine - INFO - Epoch(train) [21][1240/2569] lr: 4.0000e-02 eta: 1 day, 0:41:35 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 2.9249 loss: 2.7842 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7842 2023/06/04 20:14:54 - mmengine - INFO - Epoch(train) [21][1260/2569] lr: 4.0000e-02 eta: 1 day, 0:41:29 time: 0.2657 data_time: 0.0082 memory: 5828 grad_norm: 2.8596 loss: 2.9161 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9161 2023/06/04 20:14:59 - mmengine - INFO - Epoch(train) [21][1280/2569] lr: 4.0000e-02 eta: 1 day, 0:41:24 time: 0.2689 data_time: 0.0076 memory: 5828 grad_norm: 2.8125 loss: 2.4883 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4883 2023/06/04 20:15:04 - mmengine - INFO - Epoch(train) [21][1300/2569] lr: 4.0000e-02 eta: 1 day, 0:41:19 time: 0.2654 data_time: 0.0077 memory: 5828 grad_norm: 2.8625 loss: 2.7553 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7553 2023/06/04 20:15:10 - mmengine - INFO - Epoch(train) [21][1320/2569] lr: 4.0000e-02 eta: 1 day, 0:41:13 time: 0.2667 data_time: 0.0077 memory: 5828 grad_norm: 2.9009 loss: 2.4213 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4213 2023/06/04 20:15:15 - mmengine - INFO - Epoch(train) [21][1340/2569] lr: 4.0000e-02 eta: 1 day, 0:41:08 time: 0.2676 data_time: 0.0070 memory: 5828 grad_norm: 2.8541 loss: 2.4914 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4914 2023/06/04 20:15:21 - mmengine - INFO - Epoch(train) [21][1360/2569] lr: 4.0000e-02 eta: 1 day, 0:41:03 time: 0.2711 data_time: 0.0077 memory: 5828 grad_norm: 2.9514 loss: 2.6495 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6495 2023/06/04 20:15:26 - mmengine - INFO - Epoch(train) [21][1380/2569] lr: 4.0000e-02 eta: 1 day, 0:40:58 time: 0.2726 data_time: 0.0073 memory: 5828 grad_norm: 2.8774 loss: 2.9247 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9247 2023/06/04 20:15:31 - mmengine - INFO - Epoch(train) [21][1400/2569] lr: 4.0000e-02 eta: 1 day, 0:40:54 time: 0.2768 data_time: 0.0083 memory: 5828 grad_norm: 2.8793 loss: 2.6091 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6091 2023/06/04 20:15:37 - mmengine - INFO - Epoch(train) [21][1420/2569] lr: 4.0000e-02 eta: 1 day, 0:40:49 time: 0.2665 data_time: 0.0073 memory: 5828 grad_norm: 2.9012 loss: 2.7964 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7964 2023/06/04 20:15:42 - mmengine - INFO - Epoch(train) [21][1440/2569] lr: 4.0000e-02 eta: 1 day, 0:40:44 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 2.9235 loss: 2.6086 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6086 2023/06/04 20:15:48 - mmengine - INFO - Epoch(train) [21][1460/2569] lr: 4.0000e-02 eta: 1 day, 0:40:38 time: 0.2664 data_time: 0.0078 memory: 5828 grad_norm: 2.8561 loss: 2.5489 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5489 2023/06/04 20:15:53 - mmengine - INFO - Epoch(train) [21][1480/2569] lr: 4.0000e-02 eta: 1 day, 0:40:32 time: 0.2610 data_time: 0.0077 memory: 5828 grad_norm: 2.8301 loss: 2.3570 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3570 2023/06/04 20:15:58 - mmengine - INFO - Epoch(train) [21][1500/2569] lr: 4.0000e-02 eta: 1 day, 0:40:28 time: 0.2736 data_time: 0.0078 memory: 5828 grad_norm: 2.8990 loss: 2.5702 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5702 2023/06/04 20:16:03 - mmengine - INFO - Epoch(train) [21][1520/2569] lr: 4.0000e-02 eta: 1 day, 0:40:22 time: 0.2604 data_time: 0.0085 memory: 5828 grad_norm: 2.8470 loss: 2.8726 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8726 2023/06/04 20:16:09 - mmengine - INFO - Epoch(train) [21][1540/2569] lr: 4.0000e-02 eta: 1 day, 0:40:16 time: 0.2641 data_time: 0.0078 memory: 5828 grad_norm: 2.8476 loss: 2.5579 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5579 2023/06/04 20:16:14 - mmengine - INFO - Epoch(train) [21][1560/2569] lr: 4.0000e-02 eta: 1 day, 0:40:11 time: 0.2698 data_time: 0.0081 memory: 5828 grad_norm: 2.8357 loss: 2.7515 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7515 2023/06/04 20:16:19 - mmengine - INFO - Epoch(train) [21][1580/2569] lr: 4.0000e-02 eta: 1 day, 0:40:05 time: 0.2647 data_time: 0.0077 memory: 5828 grad_norm: 2.8946 loss: 2.6555 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6555 2023/06/04 20:16:25 - mmengine - INFO - Epoch(train) [21][1600/2569] lr: 4.0000e-02 eta: 1 day, 0:40:01 time: 0.2733 data_time: 0.0077 memory: 5828 grad_norm: 2.9129 loss: 2.7738 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7738 2023/06/04 20:16:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:16:30 - mmengine - INFO - Epoch(train) [21][1620/2569] lr: 4.0000e-02 eta: 1 day, 0:39:56 time: 0.2726 data_time: 0.0079 memory: 5828 grad_norm: 2.8854 loss: 2.6494 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6494 2023/06/04 20:16:36 - mmengine - INFO - Epoch(train) [21][1640/2569] lr: 4.0000e-02 eta: 1 day, 0:39:51 time: 0.2736 data_time: 0.0076 memory: 5828 grad_norm: 2.8664 loss: 2.8060 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8060 2023/06/04 20:16:41 - mmengine - INFO - Epoch(train) [21][1660/2569] lr: 4.0000e-02 eta: 1 day, 0:39:45 time: 0.2620 data_time: 0.0078 memory: 5828 grad_norm: 2.8863 loss: 2.5220 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5220 2023/06/04 20:16:46 - mmengine - INFO - Epoch(train) [21][1680/2569] lr: 4.0000e-02 eta: 1 day, 0:39:39 time: 0.2617 data_time: 0.0079 memory: 5828 grad_norm: 2.9106 loss: 2.6814 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6814 2023/06/04 20:16:52 - mmengine - INFO - Epoch(train) [21][1700/2569] lr: 4.0000e-02 eta: 1 day, 0:39:34 time: 0.2697 data_time: 0.0076 memory: 5828 grad_norm: 2.8900 loss: 2.7700 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7700 2023/06/04 20:16:57 - mmengine - INFO - Epoch(train) [21][1720/2569] lr: 4.0000e-02 eta: 1 day, 0:39:29 time: 0.2651 data_time: 0.0081 memory: 5828 grad_norm: 2.8488 loss: 2.5472 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5472 2023/06/04 20:17:02 - mmengine - INFO - Epoch(train) [21][1740/2569] lr: 4.0000e-02 eta: 1 day, 0:39:23 time: 0.2628 data_time: 0.0073 memory: 5828 grad_norm: 2.8635 loss: 2.5122 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5122 2023/06/04 20:17:08 - mmengine - INFO - Epoch(train) [21][1760/2569] lr: 4.0000e-02 eta: 1 day, 0:39:17 time: 0.2663 data_time: 0.0081 memory: 5828 grad_norm: 2.8546 loss: 2.7599 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7599 2023/06/04 20:17:13 - mmengine - INFO - Epoch(train) [21][1780/2569] lr: 4.0000e-02 eta: 1 day, 0:39:11 time: 0.2611 data_time: 0.0073 memory: 5828 grad_norm: 2.9122 loss: 2.7223 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7223 2023/06/04 20:17:18 - mmengine - INFO - Epoch(train) [21][1800/2569] lr: 4.0000e-02 eta: 1 day, 0:39:05 time: 0.2631 data_time: 0.0077 memory: 5828 grad_norm: 2.9152 loss: 2.8949 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8949 2023/06/04 20:17:24 - mmengine - INFO - Epoch(train) [21][1820/2569] lr: 4.0000e-02 eta: 1 day, 0:39:01 time: 0.2720 data_time: 0.0076 memory: 5828 grad_norm: 2.8827 loss: 2.5255 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5255 2023/06/04 20:17:29 - mmengine - INFO - Epoch(train) [21][1840/2569] lr: 4.0000e-02 eta: 1 day, 0:38:55 time: 0.2643 data_time: 0.0079 memory: 5828 grad_norm: 2.9334 loss: 2.6657 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6657 2023/06/04 20:17:35 - mmengine - INFO - Epoch(train) [21][1860/2569] lr: 4.0000e-02 eta: 1 day, 0:38:52 time: 0.2829 data_time: 0.0077 memory: 5828 grad_norm: 2.8405 loss: 2.9889 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9889 2023/06/04 20:17:40 - mmengine - INFO - Epoch(train) [21][1880/2569] lr: 4.0000e-02 eta: 1 day, 0:38:46 time: 0.2681 data_time: 0.0080 memory: 5828 grad_norm: 2.8827 loss: 2.4708 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4708 2023/06/04 20:17:45 - mmengine - INFO - Epoch(train) [21][1900/2569] lr: 4.0000e-02 eta: 1 day, 0:38:41 time: 0.2668 data_time: 0.0078 memory: 5828 grad_norm: 2.8908 loss: 2.6101 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6101 2023/06/04 20:17:51 - mmengine - INFO - Epoch(train) [21][1920/2569] lr: 4.0000e-02 eta: 1 day, 0:38:36 time: 0.2655 data_time: 0.0072 memory: 5828 grad_norm: 2.8327 loss: 2.4115 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4115 2023/06/04 20:17:56 - mmengine - INFO - Epoch(train) [21][1940/2569] lr: 4.0000e-02 eta: 1 day, 0:38:30 time: 0.2690 data_time: 0.0076 memory: 5828 grad_norm: 2.9140 loss: 2.6664 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6664 2023/06/04 20:18:01 - mmengine - INFO - Epoch(train) [21][1960/2569] lr: 4.0000e-02 eta: 1 day, 0:38:25 time: 0.2668 data_time: 0.0077 memory: 5828 grad_norm: 2.9135 loss: 2.5883 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5883 2023/06/04 20:18:07 - mmengine - INFO - Epoch(train) [21][1980/2569] lr: 4.0000e-02 eta: 1 day, 0:38:20 time: 0.2725 data_time: 0.0081 memory: 5828 grad_norm: 2.9124 loss: 2.5704 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5704 2023/06/04 20:18:12 - mmengine - INFO - Epoch(train) [21][2000/2569] lr: 4.0000e-02 eta: 1 day, 0:38:15 time: 0.2661 data_time: 0.0081 memory: 5828 grad_norm: 2.8418 loss: 2.5517 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5517 2023/06/04 20:18:17 - mmengine - INFO - Epoch(train) [21][2020/2569] lr: 4.0000e-02 eta: 1 day, 0:38:09 time: 0.2663 data_time: 0.0080 memory: 5828 grad_norm: 2.8665 loss: 2.5366 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5366 2023/06/04 20:18:23 - mmengine - INFO - Epoch(train) [21][2040/2569] lr: 4.0000e-02 eta: 1 day, 0:38:04 time: 0.2684 data_time: 0.0078 memory: 5828 grad_norm: 2.8970 loss: 2.2980 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2980 2023/06/04 20:18:28 - mmengine - INFO - Epoch(train) [21][2060/2569] lr: 4.0000e-02 eta: 1 day, 0:37:59 time: 0.2683 data_time: 0.0079 memory: 5828 grad_norm: 2.9444 loss: 2.6371 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6371 2023/06/04 20:18:33 - mmengine - INFO - Epoch(train) [21][2080/2569] lr: 4.0000e-02 eta: 1 day, 0:37:54 time: 0.2678 data_time: 0.0078 memory: 5828 grad_norm: 2.8803 loss: 2.4063 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4063 2023/06/04 20:18:39 - mmengine - INFO - Epoch(train) [21][2100/2569] lr: 4.0000e-02 eta: 1 day, 0:37:48 time: 0.2668 data_time: 0.0077 memory: 5828 grad_norm: 2.8678 loss: 2.9170 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9170 2023/06/04 20:18:44 - mmengine - INFO - Epoch(train) [21][2120/2569] lr: 4.0000e-02 eta: 1 day, 0:37:43 time: 0.2649 data_time: 0.0080 memory: 5828 grad_norm: 2.9012 loss: 2.5612 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5612 2023/06/04 20:18:49 - mmengine - INFO - Epoch(train) [21][2140/2569] lr: 4.0000e-02 eta: 1 day, 0:37:36 time: 0.2586 data_time: 0.0078 memory: 5828 grad_norm: 2.9490 loss: 2.6111 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6111 2023/06/04 20:18:55 - mmengine - INFO - Epoch(train) [21][2160/2569] lr: 4.0000e-02 eta: 1 day, 0:37:30 time: 0.2631 data_time: 0.0077 memory: 5828 grad_norm: 2.9142 loss: 3.0374 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0374 2023/06/04 20:19:00 - mmengine - INFO - Epoch(train) [21][2180/2569] lr: 4.0000e-02 eta: 1 day, 0:37:26 time: 0.2757 data_time: 0.0070 memory: 5828 grad_norm: 2.8592 loss: 2.4208 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4208 2023/06/04 20:19:05 - mmengine - INFO - Epoch(train) [21][2200/2569] lr: 4.0000e-02 eta: 1 day, 0:37:20 time: 0.2623 data_time: 0.0077 memory: 5828 grad_norm: 2.8461 loss: 2.6824 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6824 2023/06/04 20:19:11 - mmengine - INFO - Epoch(train) [21][2220/2569] lr: 4.0000e-02 eta: 1 day, 0:37:14 time: 0.2610 data_time: 0.0077 memory: 5828 grad_norm: 2.9041 loss: 2.7079 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7079 2023/06/04 20:19:16 - mmengine - INFO - Epoch(train) [21][2240/2569] lr: 4.0000e-02 eta: 1 day, 0:37:10 time: 0.2739 data_time: 0.0081 memory: 5828 grad_norm: 2.9467 loss: 2.5898 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5898 2023/06/04 20:19:21 - mmengine - INFO - Epoch(train) [21][2260/2569] lr: 4.0000e-02 eta: 1 day, 0:37:03 time: 0.2595 data_time: 0.0078 memory: 5828 grad_norm: 2.7967 loss: 2.4106 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4106 2023/06/04 20:19:27 - mmengine - INFO - Epoch(train) [21][2280/2569] lr: 4.0000e-02 eta: 1 day, 0:36:58 time: 0.2695 data_time: 0.0076 memory: 5828 grad_norm: 2.9008 loss: 2.5552 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5552 2023/06/04 20:19:32 - mmengine - INFO - Epoch(train) [21][2300/2569] lr: 4.0000e-02 eta: 1 day, 0:36:52 time: 0.2593 data_time: 0.0078 memory: 5828 grad_norm: 2.8499 loss: 2.3981 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3981 2023/06/04 20:19:37 - mmengine - INFO - Epoch(train) [21][2320/2569] lr: 4.0000e-02 eta: 1 day, 0:36:47 time: 0.2670 data_time: 0.0075 memory: 5828 grad_norm: 2.8996 loss: 2.6311 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6311 2023/06/04 20:19:42 - mmengine - INFO - Epoch(train) [21][2340/2569] lr: 4.0000e-02 eta: 1 day, 0:36:41 time: 0.2618 data_time: 0.0076 memory: 5828 grad_norm: 2.8824 loss: 2.6414 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6414 2023/06/04 20:19:48 - mmengine - INFO - Epoch(train) [21][2360/2569] lr: 4.0000e-02 eta: 1 day, 0:36:36 time: 0.2720 data_time: 0.0075 memory: 5828 grad_norm: 2.8594 loss: 2.6127 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6127 2023/06/04 20:19:53 - mmengine - INFO - Epoch(train) [21][2380/2569] lr: 4.0000e-02 eta: 1 day, 0:36:30 time: 0.2598 data_time: 0.0078 memory: 5828 grad_norm: 2.8807 loss: 2.5711 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5711 2023/06/04 20:19:58 - mmengine - INFO - Epoch(train) [21][2400/2569] lr: 4.0000e-02 eta: 1 day, 0:36:24 time: 0.2682 data_time: 0.0079 memory: 5828 grad_norm: 2.9578 loss: 2.5824 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5824 2023/06/04 20:20:04 - mmengine - INFO - Epoch(train) [21][2420/2569] lr: 4.0000e-02 eta: 1 day, 0:36:19 time: 0.2677 data_time: 0.0077 memory: 5828 grad_norm: 2.8360 loss: 2.8937 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.8937 2023/06/04 20:20:09 - mmengine - INFO - Epoch(train) [21][2440/2569] lr: 4.0000e-02 eta: 1 day, 0:36:14 time: 0.2666 data_time: 0.0077 memory: 5828 grad_norm: 2.8276 loss: 2.3883 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3883 2023/06/04 20:20:14 - mmengine - INFO - Epoch(train) [21][2460/2569] lr: 4.0000e-02 eta: 1 day, 0:36:08 time: 0.2657 data_time: 0.0077 memory: 5828 grad_norm: 2.8739 loss: 2.7142 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7142 2023/06/04 20:20:20 - mmengine - INFO - Epoch(train) [21][2480/2569] lr: 4.0000e-02 eta: 1 day, 0:36:03 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 2.8822 loss: 2.4694 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4694 2023/06/04 20:20:25 - mmengine - INFO - Epoch(train) [21][2500/2569] lr: 4.0000e-02 eta: 1 day, 0:35:57 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 2.8970 loss: 2.4515 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4515 2023/06/04 20:20:30 - mmengine - INFO - Epoch(train) [21][2520/2569] lr: 4.0000e-02 eta: 1 day, 0:35:52 time: 0.2709 data_time: 0.0074 memory: 5828 grad_norm: 2.9393 loss: 2.7042 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7042 2023/06/04 20:20:36 - mmengine - INFO - Epoch(train) [21][2540/2569] lr: 4.0000e-02 eta: 1 day, 0:35:46 time: 0.2614 data_time: 0.0078 memory: 5828 grad_norm: 2.8726 loss: 2.6056 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.6056 2023/06/04 20:20:41 - mmengine - INFO - Epoch(train) [21][2560/2569] lr: 4.0000e-02 eta: 1 day, 0:35:40 time: 0.2625 data_time: 0.0079 memory: 5828 grad_norm: 2.8939 loss: 2.3118 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3118 2023/06/04 20:20:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:20:43 - mmengine - INFO - Epoch(train) [21][2569/2569] lr: 4.0000e-02 eta: 1 day, 0:35:37 time: 0.2490 data_time: 0.0077 memory: 5828 grad_norm: 2.9440 loss: 2.5716 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.5716 2023/06/04 20:20:50 - mmengine - INFO - Epoch(train) [22][ 20/2569] lr: 4.0000e-02 eta: 1 day, 0:35:41 time: 0.3455 data_time: 0.0688 memory: 5828 grad_norm: 2.8553 loss: 2.4783 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4783 2023/06/04 20:20:56 - mmengine - INFO - Epoch(train) [22][ 40/2569] lr: 4.0000e-02 eta: 1 day, 0:35:36 time: 0.2755 data_time: 0.0085 memory: 5828 grad_norm: 2.9664 loss: 2.5501 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5501 2023/06/04 20:20:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:21:01 - mmengine - INFO - Epoch(train) [22][ 60/2569] lr: 4.0000e-02 eta: 1 day, 0:35:30 time: 0.2611 data_time: 0.0076 memory: 5828 grad_norm: 2.8801 loss: 2.9703 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.9703 2023/06/04 20:21:06 - mmengine - INFO - Epoch(train) [22][ 80/2569] lr: 4.0000e-02 eta: 1 day, 0:35:24 time: 0.2627 data_time: 0.0080 memory: 5828 grad_norm: 2.9480 loss: 2.7964 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7964 2023/06/04 20:21:11 - mmengine - INFO - Epoch(train) [22][ 100/2569] lr: 4.0000e-02 eta: 1 day, 0:35:18 time: 0.2617 data_time: 0.0078 memory: 5828 grad_norm: 2.9433 loss: 2.5742 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5742 2023/06/04 20:21:17 - mmengine - INFO - Epoch(train) [22][ 120/2569] lr: 4.0000e-02 eta: 1 day, 0:35:13 time: 0.2646 data_time: 0.0077 memory: 5828 grad_norm: 2.8699 loss: 2.7417 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7417 2023/06/04 20:21:22 - mmengine - INFO - Epoch(train) [22][ 140/2569] lr: 4.0000e-02 eta: 1 day, 0:35:08 time: 0.2720 data_time: 0.0076 memory: 5828 grad_norm: 2.8112 loss: 2.5684 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5684 2023/06/04 20:21:27 - mmengine - INFO - Epoch(train) [22][ 160/2569] lr: 4.0000e-02 eta: 1 day, 0:35:02 time: 0.2629 data_time: 0.0080 memory: 5828 grad_norm: 2.9051 loss: 2.8280 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8280 2023/06/04 20:21:33 - mmengine - INFO - Epoch(train) [22][ 180/2569] lr: 4.0000e-02 eta: 1 day, 0:34:57 time: 0.2712 data_time: 0.0077 memory: 5828 grad_norm: 2.8959 loss: 2.4672 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4672 2023/06/04 20:21:38 - mmengine - INFO - Epoch(train) [22][ 200/2569] lr: 4.0000e-02 eta: 1 day, 0:34:52 time: 0.2665 data_time: 0.0080 memory: 5828 grad_norm: 2.8819 loss: 2.4343 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4343 2023/06/04 20:21:43 - mmengine - INFO - Epoch(train) [22][ 220/2569] lr: 4.0000e-02 eta: 1 day, 0:34:47 time: 0.2723 data_time: 0.0080 memory: 5828 grad_norm: 2.9295 loss: 2.4033 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4033 2023/06/04 20:21:49 - mmengine - INFO - Epoch(train) [22][ 240/2569] lr: 4.0000e-02 eta: 1 day, 0:34:42 time: 0.2675 data_time: 0.0084 memory: 5828 grad_norm: 2.8530 loss: 2.5461 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5461 2023/06/04 20:21:54 - mmengine - INFO - Epoch(train) [22][ 260/2569] lr: 4.0000e-02 eta: 1 day, 0:34:36 time: 0.2653 data_time: 0.0079 memory: 5828 grad_norm: 2.9555 loss: 2.6364 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6364 2023/06/04 20:21:59 - mmengine - INFO - Epoch(train) [22][ 280/2569] lr: 4.0000e-02 eta: 1 day, 0:34:30 time: 0.2590 data_time: 0.0080 memory: 5828 grad_norm: 2.9031 loss: 2.4663 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4663 2023/06/04 20:22:05 - mmengine - INFO - Epoch(train) [22][ 300/2569] lr: 4.0000e-02 eta: 1 day, 0:34:25 time: 0.2681 data_time: 0.0078 memory: 5828 grad_norm: 2.8623 loss: 2.7069 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7069 2023/06/04 20:22:10 - mmengine - INFO - Epoch(train) [22][ 320/2569] lr: 4.0000e-02 eta: 1 day, 0:34:19 time: 0.2670 data_time: 0.0085 memory: 5828 grad_norm: 2.8525 loss: 2.4919 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4919 2023/06/04 20:22:15 - mmengine - INFO - Epoch(train) [22][ 340/2569] lr: 4.0000e-02 eta: 1 day, 0:34:14 time: 0.2702 data_time: 0.0079 memory: 5828 grad_norm: 2.8859 loss: 2.7758 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7758 2023/06/04 20:22:21 - mmengine - INFO - Epoch(train) [22][ 360/2569] lr: 4.0000e-02 eta: 1 day, 0:34:09 time: 0.2697 data_time: 0.0080 memory: 5828 grad_norm: 2.9018 loss: 2.3547 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3547 2023/06/04 20:22:26 - mmengine - INFO - Epoch(train) [22][ 380/2569] lr: 4.0000e-02 eta: 1 day, 0:34:04 time: 0.2702 data_time: 0.0078 memory: 5828 grad_norm: 2.8437 loss: 2.7324 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7324 2023/06/04 20:22:31 - mmengine - INFO - Epoch(train) [22][ 400/2569] lr: 4.0000e-02 eta: 1 day, 0:33:59 time: 0.2645 data_time: 0.0078 memory: 5828 grad_norm: 2.8969 loss: 2.6500 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6500 2023/06/04 20:22:37 - mmengine - INFO - Epoch(train) [22][ 420/2569] lr: 4.0000e-02 eta: 1 day, 0:33:53 time: 0.2661 data_time: 0.0082 memory: 5828 grad_norm: 2.8551 loss: 2.4870 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4870 2023/06/04 20:22:42 - mmengine - INFO - Epoch(train) [22][ 440/2569] lr: 4.0000e-02 eta: 1 day, 0:33:48 time: 0.2720 data_time: 0.0082 memory: 5828 grad_norm: 2.8644 loss: 2.5435 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5435 2023/06/04 20:22:48 - mmengine - INFO - Epoch(train) [22][ 460/2569] lr: 4.0000e-02 eta: 1 day, 0:33:43 time: 0.2630 data_time: 0.0077 memory: 5828 grad_norm: 2.9038 loss: 2.7636 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7636 2023/06/04 20:22:53 - mmengine - INFO - Epoch(train) [22][ 480/2569] lr: 4.0000e-02 eta: 1 day, 0:33:39 time: 0.2777 data_time: 0.0075 memory: 5828 grad_norm: 2.8580 loss: 2.6226 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6226 2023/06/04 20:22:58 - mmengine - INFO - Epoch(train) [22][ 500/2569] lr: 4.0000e-02 eta: 1 day, 0:33:33 time: 0.2614 data_time: 0.0078 memory: 5828 grad_norm: 2.8645 loss: 2.5938 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5938 2023/06/04 20:23:04 - mmengine - INFO - Epoch(train) [22][ 520/2569] lr: 4.0000e-02 eta: 1 day, 0:33:29 time: 0.2798 data_time: 0.0077 memory: 5828 grad_norm: 2.8737 loss: 2.8162 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8162 2023/06/04 20:23:09 - mmengine - INFO - Epoch(train) [22][ 540/2569] lr: 4.0000e-02 eta: 1 day, 0:33:23 time: 0.2609 data_time: 0.0079 memory: 5828 grad_norm: 2.8636 loss: 2.7643 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7643 2023/06/04 20:23:14 - mmengine - INFO - Epoch(train) [22][ 560/2569] lr: 4.0000e-02 eta: 1 day, 0:33:17 time: 0.2664 data_time: 0.0082 memory: 5828 grad_norm: 2.8663 loss: 2.5858 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5858 2023/06/04 20:23:20 - mmengine - INFO - Epoch(train) [22][ 580/2569] lr: 4.0000e-02 eta: 1 day, 0:33:11 time: 0.2606 data_time: 0.0077 memory: 5828 grad_norm: 2.9396 loss: 2.6717 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6717 2023/06/04 20:23:25 - mmengine - INFO - Epoch(train) [22][ 600/2569] lr: 4.0000e-02 eta: 1 day, 0:33:06 time: 0.2676 data_time: 0.0078 memory: 5828 grad_norm: 2.8581 loss: 2.6813 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6813 2023/06/04 20:23:30 - mmengine - INFO - Epoch(train) [22][ 620/2569] lr: 4.0000e-02 eta: 1 day, 0:33:00 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 2.8561 loss: 2.5011 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5011 2023/06/04 20:23:36 - mmengine - INFO - Epoch(train) [22][ 640/2569] lr: 4.0000e-02 eta: 1 day, 0:32:55 time: 0.2684 data_time: 0.0079 memory: 5828 grad_norm: 2.8714 loss: 2.9336 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9336 2023/06/04 20:23:41 - mmengine - INFO - Epoch(train) [22][ 660/2569] lr: 4.0000e-02 eta: 1 day, 0:32:49 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 2.9549 loss: 2.4908 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4908 2023/06/04 20:23:46 - mmengine - INFO - Epoch(train) [22][ 680/2569] lr: 4.0000e-02 eta: 1 day, 0:32:44 time: 0.2725 data_time: 0.0078 memory: 5828 grad_norm: 2.8564 loss: 2.4679 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4679 2023/06/04 20:23:52 - mmengine - INFO - Epoch(train) [22][ 700/2569] lr: 4.0000e-02 eta: 1 day, 0:32:40 time: 0.2750 data_time: 0.0074 memory: 5828 grad_norm: 2.8661 loss: 2.5964 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5964 2023/06/04 20:23:57 - mmengine - INFO - Epoch(train) [22][ 720/2569] lr: 4.0000e-02 eta: 1 day, 0:32:34 time: 0.2609 data_time: 0.0070 memory: 5828 grad_norm: 2.8758 loss: 2.6646 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6646 2023/06/04 20:24:03 - mmengine - INFO - Epoch(train) [22][ 740/2569] lr: 4.0000e-02 eta: 1 day, 0:32:30 time: 0.2814 data_time: 0.0078 memory: 5828 grad_norm: 2.9152 loss: 2.8081 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8081 2023/06/04 20:24:08 - mmengine - INFO - Epoch(train) [22][ 760/2569] lr: 4.0000e-02 eta: 1 day, 0:32:24 time: 0.2621 data_time: 0.0080 memory: 5828 grad_norm: 2.8945 loss: 2.7137 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7137 2023/06/04 20:24:13 - mmengine - INFO - Epoch(train) [22][ 780/2569] lr: 4.0000e-02 eta: 1 day, 0:32:19 time: 0.2700 data_time: 0.0079 memory: 5828 grad_norm: 2.8846 loss: 2.2490 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2490 2023/06/04 20:24:19 - mmengine - INFO - Epoch(train) [22][ 800/2569] lr: 4.0000e-02 eta: 1 day, 0:32:14 time: 0.2667 data_time: 0.0080 memory: 5828 grad_norm: 2.9235 loss: 2.5447 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5447 2023/06/04 20:24:24 - mmengine - INFO - Epoch(train) [22][ 820/2569] lr: 4.0000e-02 eta: 1 day, 0:32:09 time: 0.2710 data_time: 0.0082 memory: 5828 grad_norm: 2.8122 loss: 2.3866 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3866 2023/06/04 20:24:29 - mmengine - INFO - Epoch(train) [22][ 840/2569] lr: 4.0000e-02 eta: 1 day, 0:32:03 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 2.8744 loss: 2.4568 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4568 2023/06/04 20:24:35 - mmengine - INFO - Epoch(train) [22][ 860/2569] lr: 4.0000e-02 eta: 1 day, 0:31:58 time: 0.2697 data_time: 0.0074 memory: 5828 grad_norm: 2.8936 loss: 2.5554 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5554 2023/06/04 20:24:40 - mmengine - INFO - Epoch(train) [22][ 880/2569] lr: 4.0000e-02 eta: 1 day, 0:31:53 time: 0.2670 data_time: 0.0079 memory: 5828 grad_norm: 2.9036 loss: 2.3960 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3960 2023/06/04 20:24:45 - mmengine - INFO - Epoch(train) [22][ 900/2569] lr: 4.0000e-02 eta: 1 day, 0:31:47 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 2.8929 loss: 2.5883 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5883 2023/06/04 20:24:51 - mmengine - INFO - Epoch(train) [22][ 920/2569] lr: 4.0000e-02 eta: 1 day, 0:31:42 time: 0.2743 data_time: 0.0077 memory: 5828 grad_norm: 2.8930 loss: 2.1633 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.1633 2023/06/04 20:24:56 - mmengine - INFO - Epoch(train) [22][ 940/2569] lr: 4.0000e-02 eta: 1 day, 0:31:36 time: 0.2636 data_time: 0.0078 memory: 5828 grad_norm: 2.9093 loss: 2.5346 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5346 2023/06/04 20:25:02 - mmengine - INFO - Epoch(train) [22][ 960/2569] lr: 4.0000e-02 eta: 1 day, 0:31:31 time: 0.2694 data_time: 0.0082 memory: 5828 grad_norm: 2.9225 loss: 2.4854 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4854 2023/06/04 20:25:07 - mmengine - INFO - Epoch(train) [22][ 980/2569] lr: 4.0000e-02 eta: 1 day, 0:31:26 time: 0.2670 data_time: 0.0078 memory: 5828 grad_norm: 2.8987 loss: 2.7646 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7646 2023/06/04 20:25:12 - mmengine - INFO - Epoch(train) [22][1000/2569] lr: 4.0000e-02 eta: 1 day, 0:31:21 time: 0.2709 data_time: 0.0076 memory: 5828 grad_norm: 2.8933 loss: 2.3963 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3963 2023/06/04 20:25:18 - mmengine - INFO - Epoch(train) [22][1020/2569] lr: 4.0000e-02 eta: 1 day, 0:31:16 time: 0.2681 data_time: 0.0080 memory: 5828 grad_norm: 2.8645 loss: 2.4588 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4588 2023/06/04 20:25:23 - mmengine - INFO - Epoch(train) [22][1040/2569] lr: 4.0000e-02 eta: 1 day, 0:31:11 time: 0.2724 data_time: 0.0079 memory: 5828 grad_norm: 2.8872 loss: 2.5847 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5847 2023/06/04 20:25:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:25:28 - mmengine - INFO - Epoch(train) [22][1060/2569] lr: 4.0000e-02 eta: 1 day, 0:31:05 time: 0.2609 data_time: 0.0076 memory: 5828 grad_norm: 2.9486 loss: 2.3129 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3129 2023/06/04 20:25:34 - mmengine - INFO - Epoch(train) [22][1080/2569] lr: 4.0000e-02 eta: 1 day, 0:31:00 time: 0.2669 data_time: 0.0076 memory: 5828 grad_norm: 2.8877 loss: 2.6738 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6738 2023/06/04 20:25:39 - mmengine - INFO - Epoch(train) [22][1100/2569] lr: 4.0000e-02 eta: 1 day, 0:30:56 time: 0.2826 data_time: 0.0080 memory: 5828 grad_norm: 2.9086 loss: 2.1344 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1344 2023/06/04 20:25:45 - mmengine - INFO - Epoch(train) [22][1120/2569] lr: 4.0000e-02 eta: 1 day, 0:30:51 time: 0.2663 data_time: 0.0083 memory: 5828 grad_norm: 2.8510 loss: 2.6514 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6514 2023/06/04 20:25:50 - mmengine - INFO - Epoch(train) [22][1140/2569] lr: 4.0000e-02 eta: 1 day, 0:30:46 time: 0.2732 data_time: 0.0073 memory: 5828 grad_norm: 2.9443 loss: 2.4886 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4886 2023/06/04 20:25:55 - mmengine - INFO - Epoch(train) [22][1160/2569] lr: 4.0000e-02 eta: 1 day, 0:30:40 time: 0.2630 data_time: 0.0083 memory: 5828 grad_norm: 2.9719 loss: 2.6951 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6951 2023/06/04 20:26:01 - mmengine - INFO - Epoch(train) [22][1180/2569] lr: 4.0000e-02 eta: 1 day, 0:30:35 time: 0.2715 data_time: 0.0076 memory: 5828 grad_norm: 2.9408 loss: 2.8477 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8477 2023/06/04 20:26:06 - mmengine - INFO - Epoch(train) [22][1200/2569] lr: 4.0000e-02 eta: 1 day, 0:30:30 time: 0.2673 data_time: 0.0076 memory: 5828 grad_norm: 2.8587 loss: 2.5546 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5546 2023/06/04 20:26:12 - mmengine - INFO - Epoch(train) [22][1220/2569] lr: 4.0000e-02 eta: 1 day, 0:30:25 time: 0.2685 data_time: 0.0076 memory: 5828 grad_norm: 2.8659 loss: 2.8173 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8173 2023/06/04 20:26:17 - mmengine - INFO - Epoch(train) [22][1240/2569] lr: 4.0000e-02 eta: 1 day, 0:30:19 time: 0.2611 data_time: 0.0079 memory: 5828 grad_norm: 2.8918 loss: 2.4102 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4102 2023/06/04 20:26:22 - mmengine - INFO - Epoch(train) [22][1260/2569] lr: 4.0000e-02 eta: 1 day, 0:30:13 time: 0.2638 data_time: 0.0083 memory: 5828 grad_norm: 2.9419 loss: 2.7807 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7807 2023/06/04 20:26:27 - mmengine - INFO - Epoch(train) [22][1280/2569] lr: 4.0000e-02 eta: 1 day, 0:30:08 time: 0.2660 data_time: 0.0089 memory: 5828 grad_norm: 2.9317 loss: 2.6866 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6866 2023/06/04 20:26:33 - mmengine - INFO - Epoch(train) [22][1300/2569] lr: 4.0000e-02 eta: 1 day, 0:30:02 time: 0.2669 data_time: 0.0084 memory: 5828 grad_norm: 2.9356 loss: 2.5390 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5390 2023/06/04 20:26:38 - mmengine - INFO - Epoch(train) [22][1320/2569] lr: 4.0000e-02 eta: 1 day, 0:29:57 time: 0.2660 data_time: 0.0079 memory: 5828 grad_norm: 2.8915 loss: 2.5741 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5741 2023/06/04 20:26:43 - mmengine - INFO - Epoch(train) [22][1340/2569] lr: 4.0000e-02 eta: 1 day, 0:29:51 time: 0.2666 data_time: 0.0077 memory: 5828 grad_norm: 2.8031 loss: 2.9063 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9063 2023/06/04 20:26:49 - mmengine - INFO - Epoch(train) [22][1360/2569] lr: 4.0000e-02 eta: 1 day, 0:29:46 time: 0.2648 data_time: 0.0078 memory: 5828 grad_norm: 2.8344 loss: 2.7536 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7536 2023/06/04 20:26:54 - mmengine - INFO - Epoch(train) [22][1380/2569] lr: 4.0000e-02 eta: 1 day, 0:29:40 time: 0.2678 data_time: 0.0071 memory: 5828 grad_norm: 2.8970 loss: 2.5665 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5665 2023/06/04 20:26:59 - mmengine - INFO - Epoch(train) [22][1400/2569] lr: 4.0000e-02 eta: 1 day, 0:29:34 time: 0.2610 data_time: 0.0079 memory: 5828 grad_norm: 2.9293 loss: 2.7414 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7414 2023/06/04 20:27:05 - mmengine - INFO - Epoch(train) [22][1420/2569] lr: 4.0000e-02 eta: 1 day, 0:29:30 time: 0.2751 data_time: 0.0078 memory: 5828 grad_norm: 2.8461 loss: 2.7763 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7763 2023/06/04 20:27:10 - mmengine - INFO - Epoch(train) [22][1440/2569] lr: 4.0000e-02 eta: 1 day, 0:29:24 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 2.8959 loss: 2.3334 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3334 2023/06/04 20:27:15 - mmengine - INFO - Epoch(train) [22][1460/2569] lr: 4.0000e-02 eta: 1 day, 0:29:19 time: 0.2735 data_time: 0.0076 memory: 5828 grad_norm: 2.9234 loss: 2.5874 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5874 2023/06/04 20:27:21 - mmengine - INFO - Epoch(train) [22][1480/2569] lr: 4.0000e-02 eta: 1 day, 0:29:14 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 2.8775 loss: 2.6681 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6681 2023/06/04 20:27:26 - mmengine - INFO - Epoch(train) [22][1500/2569] lr: 4.0000e-02 eta: 1 day, 0:29:09 time: 0.2768 data_time: 0.0075 memory: 5828 grad_norm: 2.9206 loss: 2.5021 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5021 2023/06/04 20:27:32 - mmengine - INFO - Epoch(train) [22][1520/2569] lr: 4.0000e-02 eta: 1 day, 0:29:04 time: 0.2683 data_time: 0.0080 memory: 5828 grad_norm: 2.8885 loss: 2.5119 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5119 2023/06/04 20:27:37 - mmengine - INFO - Epoch(train) [22][1540/2569] lr: 4.0000e-02 eta: 1 day, 0:28:58 time: 0.2611 data_time: 0.0080 memory: 5828 grad_norm: 2.8695 loss: 2.6456 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6456 2023/06/04 20:27:42 - mmengine - INFO - Epoch(train) [22][1560/2569] lr: 4.0000e-02 eta: 1 day, 0:28:53 time: 0.2702 data_time: 0.0076 memory: 5828 grad_norm: 2.8855 loss: 2.5341 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5341 2023/06/04 20:27:48 - mmengine - INFO - Epoch(train) [22][1580/2569] lr: 4.0000e-02 eta: 1 day, 0:28:48 time: 0.2671 data_time: 0.0076 memory: 5828 grad_norm: 2.9217 loss: 2.5680 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5680 2023/06/04 20:27:53 - mmengine - INFO - Epoch(train) [22][1600/2569] lr: 4.0000e-02 eta: 1 day, 0:28:42 time: 0.2658 data_time: 0.0077 memory: 5828 grad_norm: 2.9246 loss: 2.4442 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4442 2023/06/04 20:27:58 - mmengine - INFO - Epoch(train) [22][1620/2569] lr: 4.0000e-02 eta: 1 day, 0:28:37 time: 0.2722 data_time: 0.0075 memory: 5828 grad_norm: 2.9309 loss: 2.4312 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4312 2023/06/04 20:28:04 - mmengine - INFO - Epoch(train) [22][1640/2569] lr: 4.0000e-02 eta: 1 day, 0:28:32 time: 0.2631 data_time: 0.0079 memory: 5828 grad_norm: 2.8523 loss: 2.7240 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7240 2023/06/04 20:28:09 - mmengine - INFO - Epoch(train) [22][1660/2569] lr: 4.0000e-02 eta: 1 day, 0:28:26 time: 0.2649 data_time: 0.0080 memory: 5828 grad_norm: 2.9003 loss: 2.6161 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6161 2023/06/04 20:28:14 - mmengine - INFO - Epoch(train) [22][1680/2569] lr: 4.0000e-02 eta: 1 day, 0:28:21 time: 0.2721 data_time: 0.0080 memory: 5828 grad_norm: 2.9069 loss: 2.3325 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3325 2023/06/04 20:28:20 - mmengine - INFO - Epoch(train) [22][1700/2569] lr: 4.0000e-02 eta: 1 day, 0:28:15 time: 0.2625 data_time: 0.0079 memory: 5828 grad_norm: 2.9162 loss: 2.3422 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3422 2023/06/04 20:28:25 - mmengine - INFO - Epoch(train) [22][1720/2569] lr: 4.0000e-02 eta: 1 day, 0:28:11 time: 0.2729 data_time: 0.0079 memory: 5828 grad_norm: 2.9053 loss: 2.6660 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6660 2023/06/04 20:28:31 - mmengine - INFO - Epoch(train) [22][1740/2569] lr: 4.0000e-02 eta: 1 day, 0:28:06 time: 0.2712 data_time: 0.0081 memory: 5828 grad_norm: 2.8847 loss: 2.3580 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3580 2023/06/04 20:28:36 - mmengine - INFO - Epoch(train) [22][1760/2569] lr: 4.0000e-02 eta: 1 day, 0:28:00 time: 0.2613 data_time: 0.0080 memory: 5828 grad_norm: 2.9291 loss: 2.3992 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3992 2023/06/04 20:28:41 - mmengine - INFO - Epoch(train) [22][1780/2569] lr: 4.0000e-02 eta: 1 day, 0:27:56 time: 0.2815 data_time: 0.0078 memory: 5828 grad_norm: 2.8826 loss: 2.2978 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2978 2023/06/04 20:28:47 - mmengine - INFO - Epoch(train) [22][1800/2569] lr: 4.0000e-02 eta: 1 day, 0:27:51 time: 0.2673 data_time: 0.0081 memory: 5828 grad_norm: 2.8825 loss: 2.7928 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7928 2023/06/04 20:28:52 - mmengine - INFO - Epoch(train) [22][1820/2569] lr: 4.0000e-02 eta: 1 day, 0:27:45 time: 0.2642 data_time: 0.0078 memory: 5828 grad_norm: 2.8747 loss: 2.9406 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9406 2023/06/04 20:28:57 - mmengine - INFO - Epoch(train) [22][1840/2569] lr: 4.0000e-02 eta: 1 day, 0:27:39 time: 0.2631 data_time: 0.0079 memory: 5828 grad_norm: 2.8969 loss: 2.5099 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5099 2023/06/04 20:29:03 - mmengine - INFO - Epoch(train) [22][1860/2569] lr: 4.0000e-02 eta: 1 day, 0:27:34 time: 0.2684 data_time: 0.0079 memory: 5828 grad_norm: 2.9322 loss: 2.5269 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5269 2023/06/04 20:29:08 - mmengine - INFO - Epoch(train) [22][1880/2569] lr: 4.0000e-02 eta: 1 day, 0:27:30 time: 0.2742 data_time: 0.0078 memory: 5828 grad_norm: 2.9378 loss: 2.9892 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9892 2023/06/04 20:29:13 - mmengine - INFO - Epoch(train) [22][1900/2569] lr: 4.0000e-02 eta: 1 day, 0:27:24 time: 0.2666 data_time: 0.0076 memory: 5828 grad_norm: 2.9252 loss: 2.5867 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5867 2023/06/04 20:29:19 - mmengine - INFO - Epoch(train) [22][1920/2569] lr: 4.0000e-02 eta: 1 day, 0:27:19 time: 0.2702 data_time: 0.0081 memory: 5828 grad_norm: 2.8663 loss: 2.7034 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7034 2023/06/04 20:29:24 - mmengine - INFO - Epoch(train) [22][1940/2569] lr: 4.0000e-02 eta: 1 day, 0:27:14 time: 0.2672 data_time: 0.0077 memory: 5828 grad_norm: 2.8917 loss: 2.5351 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5351 2023/06/04 20:29:30 - mmengine - INFO - Epoch(train) [22][1960/2569] lr: 4.0000e-02 eta: 1 day, 0:27:09 time: 0.2685 data_time: 0.0079 memory: 5828 grad_norm: 2.9694 loss: 2.7155 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7155 2023/06/04 20:29:35 - mmengine - INFO - Epoch(train) [22][1980/2569] lr: 4.0000e-02 eta: 1 day, 0:27:04 time: 0.2697 data_time: 0.0081 memory: 5828 grad_norm: 2.9226 loss: 2.5096 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5096 2023/06/04 20:29:40 - mmengine - INFO - Epoch(train) [22][2000/2569] lr: 4.0000e-02 eta: 1 day, 0:26:58 time: 0.2653 data_time: 0.0075 memory: 5828 grad_norm: 2.9297 loss: 2.6270 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6270 2023/06/04 20:29:46 - mmengine - INFO - Epoch(train) [22][2020/2569] lr: 4.0000e-02 eta: 1 day, 0:26:53 time: 0.2712 data_time: 0.0075 memory: 5828 grad_norm: 2.8916 loss: 2.8020 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8020 2023/06/04 20:29:51 - mmengine - INFO - Epoch(train) [22][2040/2569] lr: 4.0000e-02 eta: 1 day, 0:26:48 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 2.8473 loss: 2.8045 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8045 2023/06/04 20:29:54 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:29:56 - mmengine - INFO - Epoch(train) [22][2060/2569] lr: 4.0000e-02 eta: 1 day, 0:26:41 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 2.8610 loss: 3.0516 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0516 2023/06/04 20:30:02 - mmengine - INFO - Epoch(train) [22][2080/2569] lr: 4.0000e-02 eta: 1 day, 0:26:36 time: 0.2698 data_time: 0.0078 memory: 5828 grad_norm: 2.9703 loss: 2.3848 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3848 2023/06/04 20:30:07 - mmengine - INFO - Epoch(train) [22][2100/2569] lr: 4.0000e-02 eta: 1 day, 0:26:31 time: 0.2656 data_time: 0.0078 memory: 5828 grad_norm: 2.9028 loss: 2.5773 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5773 2023/06/04 20:30:13 - mmengine - INFO - Epoch(train) [22][2120/2569] lr: 4.0000e-02 eta: 1 day, 0:26:27 time: 0.2796 data_time: 0.0075 memory: 5828 grad_norm: 2.8603 loss: 2.5225 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5225 2023/06/04 20:30:18 - mmengine - INFO - Epoch(train) [22][2140/2569] lr: 4.0000e-02 eta: 1 day, 0:26:21 time: 0.2608 data_time: 0.0074 memory: 5828 grad_norm: 2.8718 loss: 2.4925 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4925 2023/06/04 20:30:23 - mmengine - INFO - Epoch(train) [22][2160/2569] lr: 4.0000e-02 eta: 1 day, 0:26:16 time: 0.2753 data_time: 0.0075 memory: 5828 grad_norm: 2.9739 loss: 2.5094 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5094 2023/06/04 20:30:29 - mmengine - INFO - Epoch(train) [22][2180/2569] lr: 4.0000e-02 eta: 1 day, 0:26:10 time: 0.2602 data_time: 0.0081 memory: 5828 grad_norm: 2.8747 loss: 2.9191 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9191 2023/06/04 20:30:34 - mmengine - INFO - Epoch(train) [22][2200/2569] lr: 4.0000e-02 eta: 1 day, 0:26:06 time: 0.2731 data_time: 0.0076 memory: 5828 grad_norm: 2.9019 loss: 2.5204 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5204 2023/06/04 20:30:39 - mmengine - INFO - Epoch(train) [22][2220/2569] lr: 4.0000e-02 eta: 1 day, 0:26:00 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 2.9247 loss: 2.6117 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6117 2023/06/04 20:30:44 - mmengine - INFO - Epoch(train) [22][2240/2569] lr: 4.0000e-02 eta: 1 day, 0:25:54 time: 0.2609 data_time: 0.0082 memory: 5828 grad_norm: 2.9278 loss: 2.5626 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5626 2023/06/04 20:30:50 - mmengine - INFO - Epoch(train) [22][2260/2569] lr: 4.0000e-02 eta: 1 day, 0:25:49 time: 0.2740 data_time: 0.0077 memory: 5828 grad_norm: 2.8694 loss: 2.5248 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5248 2023/06/04 20:30:55 - mmengine - INFO - Epoch(train) [22][2280/2569] lr: 4.0000e-02 eta: 1 day, 0:25:43 time: 0.2615 data_time: 0.0073 memory: 5828 grad_norm: 2.8699 loss: 2.6073 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6073 2023/06/04 20:31:01 - mmengine - INFO - Epoch(train) [22][2300/2569] lr: 4.0000e-02 eta: 1 day, 0:25:38 time: 0.2700 data_time: 0.0078 memory: 5828 grad_norm: 2.8408 loss: 2.6754 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6754 2023/06/04 20:31:06 - mmengine - INFO - Epoch(train) [22][2320/2569] lr: 4.0000e-02 eta: 1 day, 0:25:33 time: 0.2670 data_time: 0.0077 memory: 5828 grad_norm: 2.8998 loss: 2.8482 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8482 2023/06/04 20:31:11 - mmengine - INFO - Epoch(train) [22][2340/2569] lr: 4.0000e-02 eta: 1 day, 0:25:27 time: 0.2668 data_time: 0.0074 memory: 5828 grad_norm: 2.8751 loss: 2.3668 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3668 2023/06/04 20:31:17 - mmengine - INFO - Epoch(train) [22][2360/2569] lr: 4.0000e-02 eta: 1 day, 0:25:23 time: 0.2731 data_time: 0.0078 memory: 5828 grad_norm: 2.9190 loss: 2.5224 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5224 2023/06/04 20:31:22 - mmengine - INFO - Epoch(train) [22][2380/2569] lr: 4.0000e-02 eta: 1 day, 0:25:17 time: 0.2640 data_time: 0.0079 memory: 5828 grad_norm: 2.9038 loss: 2.3973 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3973 2023/06/04 20:31:27 - mmengine - INFO - Epoch(train) [22][2400/2569] lr: 4.0000e-02 eta: 1 day, 0:25:11 time: 0.2652 data_time: 0.0076 memory: 5828 grad_norm: 2.8737 loss: 2.5334 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5334 2023/06/04 20:31:33 - mmengine - INFO - Epoch(train) [22][2420/2569] lr: 4.0000e-02 eta: 1 day, 0:25:06 time: 0.2649 data_time: 0.0078 memory: 5828 grad_norm: 2.9331 loss: 2.3990 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3990 2023/06/04 20:31:38 - mmengine - INFO - Epoch(train) [22][2440/2569] lr: 4.0000e-02 eta: 1 day, 0:25:00 time: 0.2645 data_time: 0.0079 memory: 5828 grad_norm: 2.8748 loss: 2.7296 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7296 2023/06/04 20:31:43 - mmengine - INFO - Epoch(train) [22][2460/2569] lr: 4.0000e-02 eta: 1 day, 0:24:55 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 2.8930 loss: 2.1990 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1990 2023/06/04 20:31:48 - mmengine - INFO - Epoch(train) [22][2480/2569] lr: 4.0000e-02 eta: 1 day, 0:24:49 time: 0.2624 data_time: 0.0077 memory: 5828 grad_norm: 2.8861 loss: 2.4741 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4741 2023/06/04 20:31:54 - mmengine - INFO - Epoch(train) [22][2500/2569] lr: 4.0000e-02 eta: 1 day, 0:24:44 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 2.8886 loss: 2.8315 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8315 2023/06/04 20:31:59 - mmengine - INFO - Epoch(train) [22][2520/2569] lr: 4.0000e-02 eta: 1 day, 0:24:38 time: 0.2604 data_time: 0.0080 memory: 5828 grad_norm: 2.9187 loss: 2.6733 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6733 2023/06/04 20:32:04 - mmengine - INFO - Epoch(train) [22][2540/2569] lr: 4.0000e-02 eta: 1 day, 0:24:32 time: 0.2673 data_time: 0.0074 memory: 5828 grad_norm: 2.8915 loss: 2.3972 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3972 2023/06/04 20:32:10 - mmengine - INFO - Epoch(train) [22][2560/2569] lr: 4.0000e-02 eta: 1 day, 0:24:26 time: 0.2568 data_time: 0.0079 memory: 5828 grad_norm: 2.8843 loss: 2.4014 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4014 2023/06/04 20:32:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:32:12 - mmengine - INFO - Epoch(train) [22][2569/2569] lr: 4.0000e-02 eta: 1 day, 0:24:23 time: 0.2550 data_time: 0.0080 memory: 5828 grad_norm: 2.8866 loss: 2.5978 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.5978 2023/06/04 20:32:19 - mmengine - INFO - Epoch(train) [23][ 20/2569] lr: 4.0000e-02 eta: 1 day, 0:24:25 time: 0.3358 data_time: 0.0606 memory: 5828 grad_norm: 2.9517 loss: 2.4715 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4715 2023/06/04 20:32:24 - mmengine - INFO - Epoch(train) [23][ 40/2569] lr: 4.0000e-02 eta: 1 day, 0:24:21 time: 0.2738 data_time: 0.0083 memory: 5828 grad_norm: 2.9380 loss: 2.3774 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3774 2023/06/04 20:32:29 - mmengine - INFO - Epoch(train) [23][ 60/2569] lr: 4.0000e-02 eta: 1 day, 0:24:15 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 2.8851 loss: 2.6134 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6134 2023/06/04 20:32:35 - mmengine - INFO - Epoch(train) [23][ 80/2569] lr: 4.0000e-02 eta: 1 day, 0:24:10 time: 0.2718 data_time: 0.0078 memory: 5828 grad_norm: 2.8212 loss: 2.2634 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2634 2023/06/04 20:32:40 - mmengine - INFO - Epoch(train) [23][ 100/2569] lr: 4.0000e-02 eta: 1 day, 0:24:04 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 2.9001 loss: 2.8127 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8127 2023/06/04 20:32:45 - mmengine - INFO - Epoch(train) [23][ 120/2569] lr: 4.0000e-02 eta: 1 day, 0:23:59 time: 0.2678 data_time: 0.0079 memory: 5828 grad_norm: 2.8790 loss: 2.4928 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4928 2023/06/04 20:32:51 - mmengine - INFO - Epoch(train) [23][ 140/2569] lr: 4.0000e-02 eta: 1 day, 0:23:53 time: 0.2620 data_time: 0.0078 memory: 5828 grad_norm: 2.9078 loss: 2.3855 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3855 2023/06/04 20:32:56 - mmengine - INFO - Epoch(train) [23][ 160/2569] lr: 4.0000e-02 eta: 1 day, 0:23:48 time: 0.2736 data_time: 0.0072 memory: 5828 grad_norm: 2.9354 loss: 2.6159 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6159 2023/06/04 20:33:01 - mmengine - INFO - Epoch(train) [23][ 180/2569] lr: 4.0000e-02 eta: 1 day, 0:23:43 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 2.8339 loss: 2.6819 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6819 2023/06/04 20:33:07 - mmengine - INFO - Epoch(train) [23][ 200/2569] lr: 4.0000e-02 eta: 1 day, 0:23:37 time: 0.2653 data_time: 0.0086 memory: 5828 grad_norm: 2.8765 loss: 2.5900 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5900 2023/06/04 20:33:12 - mmengine - INFO - Epoch(train) [23][ 220/2569] lr: 4.0000e-02 eta: 1 day, 0:23:31 time: 0.2618 data_time: 0.0080 memory: 5828 grad_norm: 2.9345 loss: 2.9380 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9380 2023/06/04 20:33:17 - mmengine - INFO - Epoch(train) [23][ 240/2569] lr: 4.0000e-02 eta: 1 day, 0:23:25 time: 0.2623 data_time: 0.0076 memory: 5828 grad_norm: 2.9293 loss: 2.6842 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6842 2023/06/04 20:33:22 - mmengine - INFO - Epoch(train) [23][ 260/2569] lr: 4.0000e-02 eta: 1 day, 0:23:19 time: 0.2613 data_time: 0.0080 memory: 5828 grad_norm: 2.7635 loss: 2.6140 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6140 2023/06/04 20:33:28 - mmengine - INFO - Epoch(train) [23][ 280/2569] lr: 4.0000e-02 eta: 1 day, 0:23:14 time: 0.2663 data_time: 0.0081 memory: 5828 grad_norm: 2.8986 loss: 2.5996 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5996 2023/06/04 20:33:33 - mmengine - INFO - Epoch(train) [23][ 300/2569] lr: 4.0000e-02 eta: 1 day, 0:23:08 time: 0.2622 data_time: 0.0079 memory: 5828 grad_norm: 2.8836 loss: 2.5008 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5008 2023/06/04 20:33:38 - mmengine - INFO - Epoch(train) [23][ 320/2569] lr: 4.0000e-02 eta: 1 day, 0:23:03 time: 0.2665 data_time: 0.0076 memory: 5828 grad_norm: 2.8947 loss: 2.6420 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6420 2023/06/04 20:33:44 - mmengine - INFO - Epoch(train) [23][ 340/2569] lr: 4.0000e-02 eta: 1 day, 0:22:57 time: 0.2666 data_time: 0.0075 memory: 5828 grad_norm: 2.9263 loss: 2.2937 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2937 2023/06/04 20:33:49 - mmengine - INFO - Epoch(train) [23][ 360/2569] lr: 4.0000e-02 eta: 1 day, 0:22:52 time: 0.2667 data_time: 0.0082 memory: 5828 grad_norm: 2.8952 loss: 2.3465 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3465 2023/06/04 20:33:54 - mmengine - INFO - Epoch(train) [23][ 380/2569] lr: 4.0000e-02 eta: 1 day, 0:22:46 time: 0.2626 data_time: 0.0078 memory: 5828 grad_norm: 2.9296 loss: 2.3023 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3023 2023/06/04 20:34:00 - mmengine - INFO - Epoch(train) [23][ 400/2569] lr: 4.0000e-02 eta: 1 day, 0:22:40 time: 0.2611 data_time: 0.0079 memory: 5828 grad_norm: 2.8730 loss: 2.4730 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4730 2023/06/04 20:34:05 - mmengine - INFO - Epoch(train) [23][ 420/2569] lr: 4.0000e-02 eta: 1 day, 0:22:35 time: 0.2708 data_time: 0.0077 memory: 5828 grad_norm: 2.8765 loss: 2.7690 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7690 2023/06/04 20:34:10 - mmengine - INFO - Epoch(train) [23][ 440/2569] lr: 4.0000e-02 eta: 1 day, 0:22:29 time: 0.2628 data_time: 0.0078 memory: 5828 grad_norm: 2.9405 loss: 2.8156 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8156 2023/06/04 20:34:16 - mmengine - INFO - Epoch(train) [23][ 460/2569] lr: 4.0000e-02 eta: 1 day, 0:22:24 time: 0.2668 data_time: 0.0081 memory: 5828 grad_norm: 2.9393 loss: 2.5059 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5059 2023/06/04 20:34:21 - mmengine - INFO - Epoch(train) [23][ 480/2569] lr: 4.0000e-02 eta: 1 day, 0:22:19 time: 0.2686 data_time: 0.0080 memory: 5828 grad_norm: 2.8743 loss: 2.2483 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2483 2023/06/04 20:34:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:34:26 - mmengine - INFO - Epoch(train) [23][ 500/2569] lr: 4.0000e-02 eta: 1 day, 0:22:14 time: 0.2708 data_time: 0.0075 memory: 5828 grad_norm: 2.8998 loss: 2.5571 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5571 2023/06/04 20:34:32 - mmengine - INFO - Epoch(train) [23][ 520/2569] lr: 4.0000e-02 eta: 1 day, 0:22:09 time: 0.2751 data_time: 0.0078 memory: 5828 grad_norm: 2.8754 loss: 2.4329 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4329 2023/06/04 20:34:37 - mmengine - INFO - Epoch(train) [23][ 540/2569] lr: 4.0000e-02 eta: 1 day, 0:22:04 time: 0.2690 data_time: 0.0079 memory: 5828 grad_norm: 2.8838 loss: 2.4121 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4121 2023/06/04 20:34:43 - mmengine - INFO - Epoch(train) [23][ 560/2569] lr: 4.0000e-02 eta: 1 day, 0:21:59 time: 0.2680 data_time: 0.0075 memory: 5828 grad_norm: 2.9002 loss: 2.9245 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9245 2023/06/04 20:34:48 - mmengine - INFO - Epoch(train) [23][ 580/2569] lr: 4.0000e-02 eta: 1 day, 0:21:54 time: 0.2703 data_time: 0.0076 memory: 5828 grad_norm: 2.9599 loss: 2.7127 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7127 2023/06/04 20:34:53 - mmengine - INFO - Epoch(train) [23][ 600/2569] lr: 4.0000e-02 eta: 1 day, 0:21:48 time: 0.2639 data_time: 0.0077 memory: 5828 grad_norm: 2.8992 loss: 2.5398 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5398 2023/06/04 20:34:59 - mmengine - INFO - Epoch(train) [23][ 620/2569] lr: 4.0000e-02 eta: 1 day, 0:21:43 time: 0.2718 data_time: 0.0078 memory: 5828 grad_norm: 2.8248 loss: 2.5210 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5210 2023/06/04 20:35:04 - mmengine - INFO - Epoch(train) [23][ 640/2569] lr: 4.0000e-02 eta: 1 day, 0:21:38 time: 0.2713 data_time: 0.0080 memory: 5828 grad_norm: 2.8806 loss: 2.6608 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6608 2023/06/04 20:35:10 - mmengine - INFO - Epoch(train) [23][ 660/2569] lr: 4.0000e-02 eta: 1 day, 0:21:33 time: 0.2707 data_time: 0.0082 memory: 5828 grad_norm: 2.8547 loss: 2.5739 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5739 2023/06/04 20:35:15 - mmengine - INFO - Epoch(train) [23][ 680/2569] lr: 4.0000e-02 eta: 1 day, 0:21:29 time: 0.2781 data_time: 0.0079 memory: 5828 grad_norm: 2.9075 loss: 2.6802 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.6802 2023/06/04 20:35:20 - mmengine - INFO - Epoch(train) [23][ 700/2569] lr: 4.0000e-02 eta: 1 day, 0:21:24 time: 0.2645 data_time: 0.0080 memory: 5828 grad_norm: 2.9556 loss: 2.6399 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6399 2023/06/04 20:35:26 - mmengine - INFO - Epoch(train) [23][ 720/2569] lr: 4.0000e-02 eta: 1 day, 0:21:19 time: 0.2738 data_time: 0.0074 memory: 5828 grad_norm: 2.8336 loss: 2.6021 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6021 2023/06/04 20:35:31 - mmengine - INFO - Epoch(train) [23][ 740/2569] lr: 4.0000e-02 eta: 1 day, 0:21:14 time: 0.2661 data_time: 0.0079 memory: 5828 grad_norm: 2.9323 loss: 2.4087 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4087 2023/06/04 20:35:37 - mmengine - INFO - Epoch(train) [23][ 760/2569] lr: 4.0000e-02 eta: 1 day, 0:21:09 time: 0.2703 data_time: 0.0076 memory: 5828 grad_norm: 2.9213 loss: 2.7112 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7112 2023/06/04 20:35:42 - mmengine - INFO - Epoch(train) [23][ 780/2569] lr: 4.0000e-02 eta: 1 day, 0:21:03 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 2.8795 loss: 2.2721 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2721 2023/06/04 20:35:47 - mmengine - INFO - Epoch(train) [23][ 800/2569] lr: 4.0000e-02 eta: 1 day, 0:20:58 time: 0.2757 data_time: 0.0074 memory: 5828 grad_norm: 2.9044 loss: 2.6178 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6178 2023/06/04 20:35:53 - mmengine - INFO - Epoch(train) [23][ 820/2569] lr: 4.0000e-02 eta: 1 day, 0:20:53 time: 0.2707 data_time: 0.0078 memory: 5828 grad_norm: 2.9204 loss: 2.3459 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3459 2023/06/04 20:35:58 - mmengine - INFO - Epoch(train) [23][ 840/2569] lr: 4.0000e-02 eta: 1 day, 0:20:47 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 2.8841 loss: 2.3180 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3180 2023/06/04 20:36:04 - mmengine - INFO - Epoch(train) [23][ 860/2569] lr: 4.0000e-02 eta: 1 day, 0:20:44 time: 0.2840 data_time: 0.0082 memory: 5828 grad_norm: 2.8979 loss: 2.4218 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4218 2023/06/04 20:36:09 - mmengine - INFO - Epoch(train) [23][ 880/2569] lr: 4.0000e-02 eta: 1 day, 0:20:38 time: 0.2607 data_time: 0.0079 memory: 5828 grad_norm: 2.9335 loss: 2.9648 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9648 2023/06/04 20:36:14 - mmengine - INFO - Epoch(train) [23][ 900/2569] lr: 4.0000e-02 eta: 1 day, 0:20:33 time: 0.2729 data_time: 0.0077 memory: 5828 grad_norm: 2.9255 loss: 2.6784 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.6784 2023/06/04 20:36:20 - mmengine - INFO - Epoch(train) [23][ 920/2569] lr: 4.0000e-02 eta: 1 day, 0:20:29 time: 0.2758 data_time: 0.0079 memory: 5828 grad_norm: 2.9051 loss: 2.8597 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8597 2023/06/04 20:36:25 - mmengine - INFO - Epoch(train) [23][ 940/2569] lr: 4.0000e-02 eta: 1 day, 0:20:25 time: 0.2780 data_time: 0.0077 memory: 5828 grad_norm: 2.9325 loss: 2.5373 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5373 2023/06/04 20:36:31 - mmengine - INFO - Epoch(train) [23][ 960/2569] lr: 4.0000e-02 eta: 1 day, 0:20:20 time: 0.2699 data_time: 0.0080 memory: 5828 grad_norm: 2.9033 loss: 2.6039 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6039 2023/06/04 20:36:36 - mmengine - INFO - Epoch(train) [23][ 980/2569] lr: 4.0000e-02 eta: 1 day, 0:20:14 time: 0.2670 data_time: 0.0077 memory: 5828 grad_norm: 2.9529 loss: 2.5290 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5290 2023/06/04 20:36:42 - mmengine - INFO - Epoch(train) [23][1000/2569] lr: 4.0000e-02 eta: 1 day, 0:20:09 time: 0.2676 data_time: 0.0076 memory: 5828 grad_norm: 2.9728 loss: 2.4587 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4587 2023/06/04 20:36:47 - mmengine - INFO - Epoch(train) [23][1020/2569] lr: 4.0000e-02 eta: 1 day, 0:20:03 time: 0.2662 data_time: 0.0085 memory: 5828 grad_norm: 2.9430 loss: 2.7666 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7666 2023/06/04 20:36:52 - mmengine - INFO - Epoch(train) [23][1040/2569] lr: 4.0000e-02 eta: 1 day, 0:19:58 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 2.8844 loss: 2.5560 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5560 2023/06/04 20:36:58 - mmengine - INFO - Epoch(train) [23][1060/2569] lr: 4.0000e-02 eta: 1 day, 0:19:54 time: 0.2741 data_time: 0.0074 memory: 5828 grad_norm: 2.9161 loss: 2.5473 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5473 2023/06/04 20:37:03 - mmengine - INFO - Epoch(train) [23][1080/2569] lr: 4.0000e-02 eta: 1 day, 0:19:48 time: 0.2628 data_time: 0.0078 memory: 5828 grad_norm: 2.9173 loss: 2.4800 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4800 2023/06/04 20:37:08 - mmengine - INFO - Epoch(train) [23][1100/2569] lr: 4.0000e-02 eta: 1 day, 0:19:43 time: 0.2713 data_time: 0.0079 memory: 5828 grad_norm: 2.8742 loss: 2.6823 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6823 2023/06/04 20:37:14 - mmengine - INFO - Epoch(train) [23][1120/2569] lr: 4.0000e-02 eta: 1 day, 0:19:37 time: 0.2598 data_time: 0.0081 memory: 5828 grad_norm: 2.9224 loss: 2.3893 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3893 2023/06/04 20:37:19 - mmengine - INFO - Epoch(train) [23][1140/2569] lr: 4.0000e-02 eta: 1 day, 0:19:31 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 2.9358 loss: 2.6180 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.6180 2023/06/04 20:37:24 - mmengine - INFO - Epoch(train) [23][1160/2569] lr: 4.0000e-02 eta: 1 day, 0:19:26 time: 0.2720 data_time: 0.0079 memory: 5828 grad_norm: 2.8945 loss: 2.4737 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4737 2023/06/04 20:37:30 - mmengine - INFO - Epoch(train) [23][1180/2569] lr: 4.0000e-02 eta: 1 day, 0:19:22 time: 0.2768 data_time: 0.0080 memory: 5828 grad_norm: 2.9154 loss: 2.3504 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3504 2023/06/04 20:37:35 - mmengine - INFO - Epoch(train) [23][1200/2569] lr: 4.0000e-02 eta: 1 day, 0:19:18 time: 0.2750 data_time: 0.0080 memory: 5828 grad_norm: 2.9388 loss: 2.5002 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5002 2023/06/04 20:37:41 - mmengine - INFO - Epoch(train) [23][1220/2569] lr: 4.0000e-02 eta: 1 day, 0:19:12 time: 0.2664 data_time: 0.0075 memory: 5828 grad_norm: 2.9043 loss: 2.7782 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7782 2023/06/04 20:37:46 - mmengine - INFO - Epoch(train) [23][1240/2569] lr: 4.0000e-02 eta: 1 day, 0:19:07 time: 0.2659 data_time: 0.0079 memory: 5828 grad_norm: 2.9137 loss: 2.7038 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7038 2023/06/04 20:37:51 - mmengine - INFO - Epoch(train) [23][1260/2569] lr: 4.0000e-02 eta: 1 day, 0:19:01 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 2.8820 loss: 2.5918 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5918 2023/06/04 20:37:57 - mmengine - INFO - Epoch(train) [23][1280/2569] lr: 4.0000e-02 eta: 1 day, 0:18:55 time: 0.2620 data_time: 0.0081 memory: 5828 grad_norm: 2.8438 loss: 2.4917 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4917 2023/06/04 20:38:02 - mmengine - INFO - Epoch(train) [23][1300/2569] lr: 4.0000e-02 eta: 1 day, 0:18:49 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 2.9761 loss: 2.5541 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5541 2023/06/04 20:38:07 - mmengine - INFO - Epoch(train) [23][1320/2569] lr: 4.0000e-02 eta: 1 day, 0:18:44 time: 0.2710 data_time: 0.0080 memory: 5828 grad_norm: 2.9003 loss: 2.4832 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4832 2023/06/04 20:38:12 - mmengine - INFO - Epoch(train) [23][1340/2569] lr: 4.0000e-02 eta: 1 day, 0:18:38 time: 0.2599 data_time: 0.0078 memory: 5828 grad_norm: 2.8861 loss: 2.6155 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6155 2023/06/04 20:38:18 - mmengine - INFO - Epoch(train) [23][1360/2569] lr: 4.0000e-02 eta: 1 day, 0:18:32 time: 0.2636 data_time: 0.0078 memory: 5828 grad_norm: 2.8858 loss: 2.7267 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7267 2023/06/04 20:38:23 - mmengine - INFO - Epoch(train) [23][1380/2569] lr: 4.0000e-02 eta: 1 day, 0:18:27 time: 0.2640 data_time: 0.0078 memory: 5828 grad_norm: 2.9011 loss: 2.6106 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6106 2023/06/04 20:38:28 - mmengine - INFO - Epoch(train) [23][1400/2569] lr: 4.0000e-02 eta: 1 day, 0:18:22 time: 0.2725 data_time: 0.0080 memory: 5828 grad_norm: 2.9295 loss: 2.3443 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3443 2023/06/04 20:38:34 - mmengine - INFO - Epoch(train) [23][1420/2569] lr: 4.0000e-02 eta: 1 day, 0:18:17 time: 0.2701 data_time: 0.0076 memory: 5828 grad_norm: 2.9121 loss: 2.7278 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.7278 2023/06/04 20:38:40 - mmengine - INFO - Epoch(train) [23][1440/2569] lr: 4.0000e-02 eta: 1 day, 0:18:13 time: 0.2846 data_time: 0.0079 memory: 5828 grad_norm: 2.8394 loss: 2.6873 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6873 2023/06/04 20:38:45 - mmengine - INFO - Epoch(train) [23][1460/2569] lr: 4.0000e-02 eta: 1 day, 0:18:09 time: 0.2740 data_time: 0.0077 memory: 5828 grad_norm: 2.9046 loss: 2.4982 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4982 2023/06/04 20:38:51 - mmengine - INFO - Epoch(train) [23][1480/2569] lr: 4.0000e-02 eta: 1 day, 0:18:05 time: 0.2830 data_time: 0.0080 memory: 5828 grad_norm: 2.8845 loss: 2.6539 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6539 2023/06/04 20:38:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:38:56 - mmengine - INFO - Epoch(train) [23][1500/2569] lr: 4.0000e-02 eta: 1 day, 0:17:59 time: 0.2608 data_time: 0.0076 memory: 5828 grad_norm: 2.9149 loss: 2.5786 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5786 2023/06/04 20:39:02 - mmengine - INFO - Epoch(train) [23][1520/2569] lr: 4.0000e-02 eta: 1 day, 0:17:56 time: 0.2824 data_time: 0.0079 memory: 5828 grad_norm: 2.8705 loss: 2.7184 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7184 2023/06/04 20:39:07 - mmengine - INFO - Epoch(train) [23][1540/2569] lr: 4.0000e-02 eta: 1 day, 0:17:50 time: 0.2680 data_time: 0.0077 memory: 5828 grad_norm: 2.8759 loss: 2.9335 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.9335 2023/06/04 20:39:12 - mmengine - INFO - Epoch(train) [23][1560/2569] lr: 4.0000e-02 eta: 1 day, 0:17:45 time: 0.2664 data_time: 0.0078 memory: 5828 grad_norm: 2.9396 loss: 2.8644 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8644 2023/06/04 20:39:18 - mmengine - INFO - Epoch(train) [23][1580/2569] lr: 4.0000e-02 eta: 1 day, 0:17:40 time: 0.2716 data_time: 0.0080 memory: 5828 grad_norm: 2.9446 loss: 2.8952 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8952 2023/06/04 20:39:23 - mmengine - INFO - Epoch(train) [23][1600/2569] lr: 4.0000e-02 eta: 1 day, 0:17:35 time: 0.2665 data_time: 0.0078 memory: 5828 grad_norm: 2.8461 loss: 2.5464 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5464 2023/06/04 20:39:28 - mmengine - INFO - Epoch(train) [23][1620/2569] lr: 4.0000e-02 eta: 1 day, 0:17:29 time: 0.2659 data_time: 0.0077 memory: 5828 grad_norm: 2.9558 loss: 2.6243 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6243 2023/06/04 20:39:34 - mmengine - INFO - Epoch(train) [23][1640/2569] lr: 4.0000e-02 eta: 1 day, 0:17:23 time: 0.2632 data_time: 0.0077 memory: 5828 grad_norm: 2.8968 loss: 2.6667 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6667 2023/06/04 20:39:39 - mmengine - INFO - Epoch(train) [23][1660/2569] lr: 4.0000e-02 eta: 1 day, 0:17:18 time: 0.2709 data_time: 0.0079 memory: 5828 grad_norm: 2.8840 loss: 2.8529 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8529 2023/06/04 20:39:44 - mmengine - INFO - Epoch(train) [23][1680/2569] lr: 4.0000e-02 eta: 1 day, 0:17:12 time: 0.2596 data_time: 0.0078 memory: 5828 grad_norm: 2.9055 loss: 2.9328 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9328 2023/06/04 20:39:50 - mmengine - INFO - Epoch(train) [23][1700/2569] lr: 4.0000e-02 eta: 1 day, 0:17:08 time: 0.2749 data_time: 0.0079 memory: 5828 grad_norm: 2.8913 loss: 2.6732 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6732 2023/06/04 20:39:55 - mmengine - INFO - Epoch(train) [23][1720/2569] lr: 4.0000e-02 eta: 1 day, 0:17:02 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 2.9023 loss: 2.7168 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7168 2023/06/04 20:40:00 - mmengine - INFO - Epoch(train) [23][1740/2569] lr: 4.0000e-02 eta: 1 day, 0:16:57 time: 0.2720 data_time: 0.0078 memory: 5828 grad_norm: 2.9175 loss: 2.6021 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6021 2023/06/04 20:40:06 - mmengine - INFO - Epoch(train) [23][1760/2569] lr: 4.0000e-02 eta: 1 day, 0:16:52 time: 0.2678 data_time: 0.0080 memory: 5828 grad_norm: 2.8772 loss: 2.6494 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6494 2023/06/04 20:40:11 - mmengine - INFO - Epoch(train) [23][1780/2569] lr: 4.0000e-02 eta: 1 day, 0:16:47 time: 0.2709 data_time: 0.0078 memory: 5828 grad_norm: 2.9059 loss: 2.7010 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7010 2023/06/04 20:40:17 - mmengine - INFO - Epoch(train) [23][1800/2569] lr: 4.0000e-02 eta: 1 day, 0:16:42 time: 0.2684 data_time: 0.0077 memory: 5828 grad_norm: 2.9722 loss: 2.3869 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3869 2023/06/04 20:40:22 - mmengine - INFO - Epoch(train) [23][1820/2569] lr: 4.0000e-02 eta: 1 day, 0:16:35 time: 0.2609 data_time: 0.0082 memory: 5828 grad_norm: 2.9201 loss: 2.5387 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5387 2023/06/04 20:40:27 - mmengine - INFO - Epoch(train) [23][1840/2569] lr: 4.0000e-02 eta: 1 day, 0:16:30 time: 0.2623 data_time: 0.0078 memory: 5828 grad_norm: 2.8942 loss: 2.7513 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7513 2023/06/04 20:40:32 - mmengine - INFO - Epoch(train) [23][1860/2569] lr: 4.0000e-02 eta: 1 day, 0:16:24 time: 0.2620 data_time: 0.0076 memory: 5828 grad_norm: 2.9698 loss: 2.7695 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.7695 2023/06/04 20:40:38 - mmengine - INFO - Epoch(train) [23][1880/2569] lr: 4.0000e-02 eta: 1 day, 0:16:18 time: 0.2630 data_time: 0.0082 memory: 5828 grad_norm: 2.9340 loss: 2.7177 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7177 2023/06/04 20:40:43 - mmengine - INFO - Epoch(train) [23][1900/2569] lr: 4.0000e-02 eta: 1 day, 0:16:13 time: 0.2717 data_time: 0.0079 memory: 5828 grad_norm: 2.9549 loss: 2.4948 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4948 2023/06/04 20:40:49 - mmengine - INFO - Epoch(train) [23][1920/2569] lr: 4.0000e-02 eta: 1 day, 0:16:09 time: 0.2808 data_time: 0.0078 memory: 5828 grad_norm: 2.9053 loss: 2.7676 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7676 2023/06/04 20:40:54 - mmengine - INFO - Epoch(train) [23][1940/2569] lr: 4.0000e-02 eta: 1 day, 0:16:04 time: 0.2649 data_time: 0.0076 memory: 5828 grad_norm: 2.8927 loss: 2.6132 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6132 2023/06/04 20:40:59 - mmengine - INFO - Epoch(train) [23][1960/2569] lr: 4.0000e-02 eta: 1 day, 0:15:59 time: 0.2729 data_time: 0.0076 memory: 5828 grad_norm: 3.0352 loss: 2.6783 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6783 2023/06/04 20:41:05 - mmengine - INFO - Epoch(train) [23][1980/2569] lr: 4.0000e-02 eta: 1 day, 0:15:53 time: 0.2664 data_time: 0.0078 memory: 5828 grad_norm: 2.9067 loss: 2.7355 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.7355 2023/06/04 20:41:10 - mmengine - INFO - Epoch(train) [23][2000/2569] lr: 4.0000e-02 eta: 1 day, 0:15:48 time: 0.2693 data_time: 0.0075 memory: 5828 grad_norm: 2.8820 loss: 2.5215 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5215 2023/06/04 20:41:15 - mmengine - INFO - Epoch(train) [23][2020/2569] lr: 4.0000e-02 eta: 1 day, 0:15:42 time: 0.2630 data_time: 0.0076 memory: 5828 grad_norm: 2.9143 loss: 2.7776 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7776 2023/06/04 20:41:21 - mmengine - INFO - Epoch(train) [23][2040/2569] lr: 4.0000e-02 eta: 1 day, 0:15:38 time: 0.2729 data_time: 0.0077 memory: 5828 grad_norm: 2.9063 loss: 2.3255 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3255 2023/06/04 20:41:26 - mmengine - INFO - Epoch(train) [23][2060/2569] lr: 4.0000e-02 eta: 1 day, 0:15:32 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 2.9289 loss: 2.8041 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 2.8041 2023/06/04 20:41:31 - mmengine - INFO - Epoch(train) [23][2080/2569] lr: 4.0000e-02 eta: 1 day, 0:15:26 time: 0.2633 data_time: 0.0078 memory: 5828 grad_norm: 2.9202 loss: 2.6301 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6301 2023/06/04 20:41:37 - mmengine - INFO - Epoch(train) [23][2100/2569] lr: 4.0000e-02 eta: 1 day, 0:15:21 time: 0.2629 data_time: 0.0071 memory: 5828 grad_norm: 2.9239 loss: 2.5309 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5309 2023/06/04 20:41:42 - mmengine - INFO - Epoch(train) [23][2120/2569] lr: 4.0000e-02 eta: 1 day, 0:15:15 time: 0.2628 data_time: 0.0077 memory: 5828 grad_norm: 2.9549 loss: 2.2884 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2884 2023/06/04 20:41:47 - mmengine - INFO - Epoch(train) [23][2140/2569] lr: 4.0000e-02 eta: 1 day, 0:15:10 time: 0.2743 data_time: 0.0077 memory: 5828 grad_norm: 2.9038 loss: 2.6820 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6820 2023/06/04 20:41:53 - mmengine - INFO - Epoch(train) [23][2160/2569] lr: 4.0000e-02 eta: 1 day, 0:15:05 time: 0.2666 data_time: 0.0076 memory: 5828 grad_norm: 2.9543 loss: 2.7599 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7599 2023/06/04 20:41:58 - mmengine - INFO - Epoch(train) [23][2180/2569] lr: 4.0000e-02 eta: 1 day, 0:15:00 time: 0.2709 data_time: 0.0074 memory: 5828 grad_norm: 2.9132 loss: 2.4563 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4563 2023/06/04 20:42:04 - mmengine - INFO - Epoch(train) [23][2200/2569] lr: 4.0000e-02 eta: 1 day, 0:14:54 time: 0.2661 data_time: 0.0080 memory: 5828 grad_norm: 2.8965 loss: 2.5107 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5107 2023/06/04 20:42:09 - mmengine - INFO - Epoch(train) [23][2220/2569] lr: 4.0000e-02 eta: 1 day, 0:14:49 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 2.8607 loss: 2.6046 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6046 2023/06/04 20:42:14 - mmengine - INFO - Epoch(train) [23][2240/2569] lr: 4.0000e-02 eta: 1 day, 0:14:44 time: 0.2740 data_time: 0.0079 memory: 5828 grad_norm: 2.9673 loss: 2.5824 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5824 2023/06/04 20:42:20 - mmengine - INFO - Epoch(train) [23][2260/2569] lr: 4.0000e-02 eta: 1 day, 0:14:39 time: 0.2687 data_time: 0.0077 memory: 5828 grad_norm: 2.9317 loss: 2.9956 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9956 2023/06/04 20:42:25 - mmengine - INFO - Epoch(train) [23][2280/2569] lr: 4.0000e-02 eta: 1 day, 0:14:34 time: 0.2666 data_time: 0.0082 memory: 5828 grad_norm: 2.8816 loss: 2.3508 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3508 2023/06/04 20:42:30 - mmengine - INFO - Epoch(train) [23][2300/2569] lr: 4.0000e-02 eta: 1 day, 0:14:28 time: 0.2611 data_time: 0.0070 memory: 5828 grad_norm: 2.9291 loss: 2.4685 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4685 2023/06/04 20:42:35 - mmengine - INFO - Epoch(train) [23][2320/2569] lr: 4.0000e-02 eta: 1 day, 0:14:22 time: 0.2607 data_time: 0.0076 memory: 5828 grad_norm: 2.8406 loss: 2.6597 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6597 2023/06/04 20:42:41 - mmengine - INFO - Epoch(train) [23][2340/2569] lr: 4.0000e-02 eta: 1 day, 0:14:16 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 2.8953 loss: 2.7138 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.7138 2023/06/04 20:42:46 - mmengine - INFO - Epoch(train) [23][2360/2569] lr: 4.0000e-02 eta: 1 day, 0:14:10 time: 0.2617 data_time: 0.0075 memory: 5828 grad_norm: 2.9228 loss: 2.4818 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4818 2023/06/04 20:42:51 - mmengine - INFO - Epoch(train) [23][2380/2569] lr: 4.0000e-02 eta: 1 day, 0:14:04 time: 0.2609 data_time: 0.0078 memory: 5828 grad_norm: 2.8769 loss: 2.2611 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.2611 2023/06/04 20:42:56 - mmengine - INFO - Epoch(train) [23][2400/2569] lr: 4.0000e-02 eta: 1 day, 0:13:58 time: 0.2618 data_time: 0.0083 memory: 5828 grad_norm: 2.9631 loss: 2.7811 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7811 2023/06/04 20:43:02 - mmengine - INFO - Epoch(train) [23][2420/2569] lr: 4.0000e-02 eta: 1 day, 0:13:51 time: 0.2606 data_time: 0.0079 memory: 5828 grad_norm: 2.8561 loss: 2.7068 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7068 2023/06/04 20:43:07 - mmengine - INFO - Epoch(train) [23][2440/2569] lr: 4.0000e-02 eta: 1 day, 0:13:46 time: 0.2632 data_time: 0.0079 memory: 5828 grad_norm: 2.8773 loss: 2.4550 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4550 2023/06/04 20:43:12 - mmengine - INFO - Epoch(train) [23][2460/2569] lr: 4.0000e-02 eta: 1 day, 0:13:40 time: 0.2656 data_time: 0.0077 memory: 5828 grad_norm: 2.9326 loss: 2.7000 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7000 2023/06/04 20:43:18 - mmengine - INFO - Epoch(train) [23][2480/2569] lr: 4.0000e-02 eta: 1 day, 0:13:35 time: 0.2710 data_time: 0.0075 memory: 5828 grad_norm: 2.9085 loss: 2.5978 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5978 2023/06/04 20:43:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:43:23 - mmengine - INFO - Epoch(train) [23][2500/2569] lr: 4.0000e-02 eta: 1 day, 0:13:29 time: 0.2613 data_time: 0.0083 memory: 5828 grad_norm: 2.9364 loss: 2.5966 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5966 2023/06/04 20:43:28 - mmengine - INFO - Epoch(train) [23][2520/2569] lr: 4.0000e-02 eta: 1 day, 0:13:24 time: 0.2707 data_time: 0.0075 memory: 5828 grad_norm: 2.8946 loss: 2.3616 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3616 2023/06/04 20:43:33 - mmengine - INFO - Epoch(train) [23][2540/2569] lr: 4.0000e-02 eta: 1 day, 0:13:18 time: 0.2627 data_time: 0.0079 memory: 5828 grad_norm: 2.9116 loss: 2.2192 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.2192 2023/06/04 20:43:39 - mmengine - INFO - Epoch(train) [23][2560/2569] lr: 4.0000e-02 eta: 1 day, 0:13:12 time: 0.2582 data_time: 0.0080 memory: 5828 grad_norm: 2.9768 loss: 2.5357 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5357 2023/06/04 20:43:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:43:41 - mmengine - INFO - Epoch(train) [23][2569/2569] lr: 4.0000e-02 eta: 1 day, 0:13:09 time: 0.2548 data_time: 0.0079 memory: 5828 grad_norm: 2.9565 loss: 2.3777 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.3777 2023/06/04 20:43:48 - mmengine - INFO - Epoch(train) [24][ 20/2569] lr: 4.0000e-02 eta: 1 day, 0:13:12 time: 0.3431 data_time: 0.0517 memory: 5828 grad_norm: 2.8825 loss: 2.5688 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.5688 2023/06/04 20:43:53 - mmengine - INFO - Epoch(train) [24][ 40/2569] lr: 4.0000e-02 eta: 1 day, 0:13:08 time: 0.2752 data_time: 0.0075 memory: 5828 grad_norm: 2.8918 loss: 2.6902 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6902 2023/06/04 20:43:59 - mmengine - INFO - Epoch(train) [24][ 60/2569] lr: 4.0000e-02 eta: 1 day, 0:13:02 time: 0.2615 data_time: 0.0076 memory: 5828 grad_norm: 2.8902 loss: 2.5151 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5151 2023/06/04 20:44:04 - mmengine - INFO - Epoch(train) [24][ 80/2569] lr: 4.0000e-02 eta: 1 day, 0:12:58 time: 0.2781 data_time: 0.0073 memory: 5828 grad_norm: 2.9235 loss: 2.4614 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4614 2023/06/04 20:44:10 - mmengine - INFO - Epoch(train) [24][ 100/2569] lr: 4.0000e-02 eta: 1 day, 0:12:52 time: 0.2677 data_time: 0.0079 memory: 5828 grad_norm: 2.9073 loss: 2.1465 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1465 2023/06/04 20:44:15 - mmengine - INFO - Epoch(train) [24][ 120/2569] lr: 4.0000e-02 eta: 1 day, 0:12:47 time: 0.2673 data_time: 0.0085 memory: 5828 grad_norm: 2.9381 loss: 2.7853 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7853 2023/06/04 20:44:20 - mmengine - INFO - Epoch(train) [24][ 140/2569] lr: 4.0000e-02 eta: 1 day, 0:12:42 time: 0.2711 data_time: 0.0078 memory: 5828 grad_norm: 2.8938 loss: 2.7979 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7979 2023/06/04 20:44:26 - mmengine - INFO - Epoch(train) [24][ 160/2569] lr: 4.0000e-02 eta: 1 day, 0:12:36 time: 0.2611 data_time: 0.0078 memory: 5828 grad_norm: 2.9580 loss: 2.6907 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6907 2023/06/04 20:44:31 - mmengine - INFO - Epoch(train) [24][ 180/2569] lr: 4.0000e-02 eta: 1 day, 0:12:31 time: 0.2718 data_time: 0.0083 memory: 5828 grad_norm: 2.9058 loss: 2.5823 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5823 2023/06/04 20:44:36 - mmengine - INFO - Epoch(train) [24][ 200/2569] lr: 4.0000e-02 eta: 1 day, 0:12:25 time: 0.2641 data_time: 0.0082 memory: 5828 grad_norm: 2.9338 loss: 2.7509 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7509 2023/06/04 20:44:42 - mmengine - INFO - Epoch(train) [24][ 220/2569] lr: 4.0000e-02 eta: 1 day, 0:12:20 time: 0.2706 data_time: 0.0075 memory: 5828 grad_norm: 3.0182 loss: 2.6590 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6590 2023/06/04 20:44:47 - mmengine - INFO - Epoch(train) [24][ 240/2569] lr: 4.0000e-02 eta: 1 day, 0:12:16 time: 0.2761 data_time: 0.0078 memory: 5828 grad_norm: 2.8843 loss: 2.7085 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.7085 2023/06/04 20:44:53 - mmengine - INFO - Epoch(train) [24][ 260/2569] lr: 4.0000e-02 eta: 1 day, 0:12:11 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 2.8880 loss: 2.9816 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9816 2023/06/04 20:44:58 - mmengine - INFO - Epoch(train) [24][ 280/2569] lr: 4.0000e-02 eta: 1 day, 0:12:05 time: 0.2667 data_time: 0.0077 memory: 5828 grad_norm: 2.8779 loss: 2.2223 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2223 2023/06/04 20:45:03 - mmengine - INFO - Epoch(train) [24][ 300/2569] lr: 4.0000e-02 eta: 1 day, 0:12:00 time: 0.2649 data_time: 0.0077 memory: 5828 grad_norm: 2.9049 loss: 2.3879 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3879 2023/06/04 20:45:09 - mmengine - INFO - Epoch(train) [24][ 320/2569] lr: 4.0000e-02 eta: 1 day, 0:11:55 time: 0.2689 data_time: 0.0077 memory: 5828 grad_norm: 2.9101 loss: 2.3079 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3079 2023/06/04 20:45:14 - mmengine - INFO - Epoch(train) [24][ 340/2569] lr: 4.0000e-02 eta: 1 day, 0:11:49 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 2.9180 loss: 2.4291 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4291 2023/06/04 20:45:19 - mmengine - INFO - Epoch(train) [24][ 360/2569] lr: 4.0000e-02 eta: 1 day, 0:11:44 time: 0.2667 data_time: 0.0080 memory: 5828 grad_norm: 2.9345 loss: 2.6386 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.6386 2023/06/04 20:45:25 - mmengine - INFO - Epoch(train) [24][ 380/2569] lr: 4.0000e-02 eta: 1 day, 0:11:38 time: 0.2648 data_time: 0.0080 memory: 5828 grad_norm: 2.9492 loss: 2.6655 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6655 2023/06/04 20:45:30 - mmengine - INFO - Epoch(train) [24][ 400/2569] lr: 4.0000e-02 eta: 1 day, 0:11:33 time: 0.2643 data_time: 0.0082 memory: 5828 grad_norm: 2.9744 loss: 3.0044 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 3.0044 2023/06/04 20:45:35 - mmengine - INFO - Epoch(train) [24][ 420/2569] lr: 4.0000e-02 eta: 1 day, 0:11:28 time: 0.2732 data_time: 0.0075 memory: 5828 grad_norm: 2.9288 loss: 2.3162 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3162 2023/06/04 20:45:41 - mmengine - INFO - Epoch(train) [24][ 440/2569] lr: 4.0000e-02 eta: 1 day, 0:11:22 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 2.9264 loss: 2.3910 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3910 2023/06/04 20:45:46 - mmengine - INFO - Epoch(train) [24][ 460/2569] lr: 4.0000e-02 eta: 1 day, 0:11:17 time: 0.2670 data_time: 0.0077 memory: 5828 grad_norm: 2.9030 loss: 2.3313 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3313 2023/06/04 20:45:51 - mmengine - INFO - Epoch(train) [24][ 480/2569] lr: 4.0000e-02 eta: 1 day, 0:11:12 time: 0.2714 data_time: 0.0075 memory: 5828 grad_norm: 2.8895 loss: 2.8214 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.8214 2023/06/04 20:45:57 - mmengine - INFO - Epoch(train) [24][ 500/2569] lr: 4.0000e-02 eta: 1 day, 0:11:06 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 2.8498 loss: 2.7477 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7477 2023/06/04 20:46:02 - mmengine - INFO - Epoch(train) [24][ 520/2569] lr: 4.0000e-02 eta: 1 day, 0:11:01 time: 0.2719 data_time: 0.0076 memory: 5828 grad_norm: 2.9006 loss: 2.6324 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6324 2023/06/04 20:46:07 - mmengine - INFO - Epoch(train) [24][ 540/2569] lr: 4.0000e-02 eta: 1 day, 0:10:56 time: 0.2694 data_time: 0.0084 memory: 5828 grad_norm: 2.9251 loss: 2.8982 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8982 2023/06/04 20:46:13 - mmengine - INFO - Epoch(train) [24][ 560/2569] lr: 4.0000e-02 eta: 1 day, 0:10:51 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 2.9485 loss: 2.7981 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7981 2023/06/04 20:46:18 - mmengine - INFO - Epoch(train) [24][ 580/2569] lr: 4.0000e-02 eta: 1 day, 0:10:45 time: 0.2653 data_time: 0.0077 memory: 5828 grad_norm: 2.9207 loss: 2.6981 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6981 2023/06/04 20:46:23 - mmengine - INFO - Epoch(train) [24][ 600/2569] lr: 4.0000e-02 eta: 1 day, 0:10:40 time: 0.2661 data_time: 0.0080 memory: 5828 grad_norm: 2.9830 loss: 2.6174 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6174 2023/06/04 20:46:29 - mmengine - INFO - Epoch(train) [24][ 620/2569] lr: 4.0000e-02 eta: 1 day, 0:10:34 time: 0.2614 data_time: 0.0076 memory: 5828 grad_norm: 2.9227 loss: 2.4357 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4357 2023/06/04 20:46:34 - mmengine - INFO - Epoch(train) [24][ 640/2569] lr: 4.0000e-02 eta: 1 day, 0:10:28 time: 0.2611 data_time: 0.0079 memory: 5828 grad_norm: 2.9646 loss: 2.6172 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6172 2023/06/04 20:46:39 - mmengine - INFO - Epoch(train) [24][ 660/2569] lr: 4.0000e-02 eta: 1 day, 0:10:22 time: 0.2623 data_time: 0.0078 memory: 5828 grad_norm: 2.9162 loss: 2.1912 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1912 2023/06/04 20:46:45 - mmengine - INFO - Epoch(train) [24][ 680/2569] lr: 4.0000e-02 eta: 1 day, 0:10:17 time: 0.2751 data_time: 0.0080 memory: 5828 grad_norm: 2.9037 loss: 2.4719 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4719 2023/06/04 20:46:50 - mmengine - INFO - Epoch(train) [24][ 700/2569] lr: 4.0000e-02 eta: 1 day, 0:10:12 time: 0.2617 data_time: 0.0082 memory: 5828 grad_norm: 2.9813 loss: 3.0187 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0187 2023/06/04 20:46:55 - mmengine - INFO - Epoch(train) [24][ 720/2569] lr: 4.0000e-02 eta: 1 day, 0:10:07 time: 0.2724 data_time: 0.0084 memory: 5828 grad_norm: 2.8765 loss: 2.6338 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6338 2023/06/04 20:47:01 - mmengine - INFO - Epoch(train) [24][ 740/2569] lr: 4.0000e-02 eta: 1 day, 0:10:01 time: 0.2617 data_time: 0.0078 memory: 5828 grad_norm: 2.9148 loss: 2.6180 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6180 2023/06/04 20:47:06 - mmengine - INFO - Epoch(train) [24][ 760/2569] lr: 4.0000e-02 eta: 1 day, 0:09:56 time: 0.2705 data_time: 0.0079 memory: 5828 grad_norm: 2.8977 loss: 2.3042 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3042 2023/06/04 20:47:11 - mmengine - INFO - Epoch(train) [24][ 780/2569] lr: 4.0000e-02 eta: 1 day, 0:09:50 time: 0.2626 data_time: 0.0078 memory: 5828 grad_norm: 2.9539 loss: 2.4467 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4467 2023/06/04 20:47:17 - mmengine - INFO - Epoch(train) [24][ 800/2569] lr: 4.0000e-02 eta: 1 day, 0:09:44 time: 0.2659 data_time: 0.0079 memory: 5828 grad_norm: 2.9531 loss: 2.7768 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7768 2023/06/04 20:47:22 - mmengine - INFO - Epoch(train) [24][ 820/2569] lr: 4.0000e-02 eta: 1 day, 0:09:39 time: 0.2622 data_time: 0.0076 memory: 5828 grad_norm: 2.8889 loss: 2.4903 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4903 2023/06/04 20:47:27 - mmengine - INFO - Epoch(train) [24][ 840/2569] lr: 4.0000e-02 eta: 1 day, 0:09:33 time: 0.2629 data_time: 0.0076 memory: 5828 grad_norm: 2.9358 loss: 2.5611 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5611 2023/06/04 20:47:32 - mmengine - INFO - Epoch(train) [24][ 860/2569] lr: 4.0000e-02 eta: 1 day, 0:09:27 time: 0.2641 data_time: 0.0079 memory: 5828 grad_norm: 2.9211 loss: 2.4968 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4968 2023/06/04 20:47:38 - mmengine - INFO - Epoch(train) [24][ 880/2569] lr: 4.0000e-02 eta: 1 day, 0:09:21 time: 0.2644 data_time: 0.0076 memory: 5828 grad_norm: 2.9594 loss: 2.7059 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7059 2023/06/04 20:47:43 - mmengine - INFO - Epoch(train) [24][ 900/2569] lr: 4.0000e-02 eta: 1 day, 0:09:17 time: 0.2774 data_time: 0.0078 memory: 5828 grad_norm: 2.9273 loss: 2.6344 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.6344 2023/06/04 20:47:47 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:47:49 - mmengine - INFO - Epoch(train) [24][ 920/2569] lr: 4.0000e-02 eta: 1 day, 0:09:12 time: 0.2687 data_time: 0.0079 memory: 5828 grad_norm: 2.9508 loss: 2.7673 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7673 2023/06/04 20:47:54 - mmengine - INFO - Epoch(train) [24][ 940/2569] lr: 4.0000e-02 eta: 1 day, 0:09:08 time: 0.2794 data_time: 0.0080 memory: 5828 grad_norm: 2.8660 loss: 2.4583 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4583 2023/06/04 20:48:00 - mmengine - INFO - Epoch(train) [24][ 960/2569] lr: 4.0000e-02 eta: 1 day, 0:09:03 time: 0.2678 data_time: 0.0089 memory: 5828 grad_norm: 2.9530 loss: 2.8702 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8702 2023/06/04 20:48:05 - mmengine - INFO - Epoch(train) [24][ 980/2569] lr: 4.0000e-02 eta: 1 day, 0:08:57 time: 0.2669 data_time: 0.0075 memory: 5828 grad_norm: 2.9556 loss: 2.8528 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8528 2023/06/04 20:48:10 - mmengine - INFO - Epoch(train) [24][1000/2569] lr: 4.0000e-02 eta: 1 day, 0:08:53 time: 0.2811 data_time: 0.0081 memory: 5828 grad_norm: 2.8790 loss: 2.4488 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.4488 2023/06/04 20:48:16 - mmengine - INFO - Epoch(train) [24][1020/2569] lr: 4.0000e-02 eta: 1 day, 0:08:48 time: 0.2662 data_time: 0.0077 memory: 5828 grad_norm: 2.8578 loss: 2.7483 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7483 2023/06/04 20:48:21 - mmengine - INFO - Epoch(train) [24][1040/2569] lr: 4.0000e-02 eta: 1 day, 0:08:42 time: 0.2657 data_time: 0.0083 memory: 5828 grad_norm: 2.9251 loss: 2.4772 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4772 2023/06/04 20:48:26 - mmengine - INFO - Epoch(train) [24][1060/2569] lr: 4.0000e-02 eta: 1 day, 0:08:37 time: 0.2669 data_time: 0.0079 memory: 5828 grad_norm: 2.9110 loss: 2.9452 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9452 2023/06/04 20:48:32 - mmengine - INFO - Epoch(train) [24][1080/2569] lr: 4.0000e-02 eta: 1 day, 0:08:32 time: 0.2669 data_time: 0.0079 memory: 5828 grad_norm: 2.9068 loss: 2.6675 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6675 2023/06/04 20:48:37 - mmengine - INFO - Epoch(train) [24][1100/2569] lr: 4.0000e-02 eta: 1 day, 0:08:26 time: 0.2620 data_time: 0.0075 memory: 5828 grad_norm: 2.9113 loss: 2.7701 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7701 2023/06/04 20:48:42 - mmengine - INFO - Epoch(train) [24][1120/2569] lr: 4.0000e-02 eta: 1 day, 0:08:20 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 2.9426 loss: 2.2573 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2573 2023/06/04 20:48:48 - mmengine - INFO - Epoch(train) [24][1140/2569] lr: 4.0000e-02 eta: 1 day, 0:08:14 time: 0.2603 data_time: 0.0081 memory: 5828 grad_norm: 2.9228 loss: 2.4842 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4842 2023/06/04 20:48:53 - mmengine - INFO - Epoch(train) [24][1160/2569] lr: 4.0000e-02 eta: 1 day, 0:08:09 time: 0.2701 data_time: 0.0074 memory: 5828 grad_norm: 2.9212 loss: 2.7685 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7685 2023/06/04 20:48:58 - mmengine - INFO - Epoch(train) [24][1180/2569] lr: 4.0000e-02 eta: 1 day, 0:08:03 time: 0.2655 data_time: 0.0078 memory: 5828 grad_norm: 2.9488 loss: 2.5509 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5509 2023/06/04 20:49:04 - mmengine - INFO - Epoch(train) [24][1200/2569] lr: 4.0000e-02 eta: 1 day, 0:07:58 time: 0.2656 data_time: 0.0080 memory: 5828 grad_norm: 2.8569 loss: 2.4309 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4309 2023/06/04 20:49:09 - mmengine - INFO - Epoch(train) [24][1220/2569] lr: 4.0000e-02 eta: 1 day, 0:07:52 time: 0.2658 data_time: 0.0081 memory: 5828 grad_norm: 2.9235 loss: 2.4237 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4237 2023/06/04 20:49:14 - mmengine - INFO - Epoch(train) [24][1240/2569] lr: 4.0000e-02 eta: 1 day, 0:07:46 time: 0.2608 data_time: 0.0086 memory: 5828 grad_norm: 2.9107 loss: 2.6368 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6368 2023/06/04 20:49:20 - mmengine - INFO - Epoch(train) [24][1260/2569] lr: 4.0000e-02 eta: 1 day, 0:07:42 time: 0.2738 data_time: 0.0081 memory: 5828 grad_norm: 2.9265 loss: 2.7839 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.7839 2023/06/04 20:49:25 - mmengine - INFO - Epoch(train) [24][1280/2569] lr: 4.0000e-02 eta: 1 day, 0:07:35 time: 0.2589 data_time: 0.0077 memory: 5828 grad_norm: 2.9301 loss: 2.6567 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6567 2023/06/04 20:49:30 - mmengine - INFO - Epoch(train) [24][1300/2569] lr: 4.0000e-02 eta: 1 day, 0:07:30 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 2.9724 loss: 2.1756 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1756 2023/06/04 20:49:35 - mmengine - INFO - Epoch(train) [24][1320/2569] lr: 4.0000e-02 eta: 1 day, 0:07:25 time: 0.2699 data_time: 0.0078 memory: 5828 grad_norm: 2.9109 loss: 2.7665 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7665 2023/06/04 20:49:41 - mmengine - INFO - Epoch(train) [24][1340/2569] lr: 4.0000e-02 eta: 1 day, 0:07:19 time: 0.2609 data_time: 0.0078 memory: 5828 grad_norm: 2.8953 loss: 2.4913 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4913 2023/06/04 20:49:46 - mmengine - INFO - Epoch(train) [24][1360/2569] lr: 4.0000e-02 eta: 1 day, 0:07:14 time: 0.2705 data_time: 0.0080 memory: 5828 grad_norm: 2.9289 loss: 2.3774 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3774 2023/06/04 20:49:51 - mmengine - INFO - Epoch(train) [24][1380/2569] lr: 4.0000e-02 eta: 1 day, 0:07:09 time: 0.2682 data_time: 0.0080 memory: 5828 grad_norm: 2.9169 loss: 2.7162 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7162 2023/06/04 20:49:57 - mmengine - INFO - Epoch(train) [24][1400/2569] lr: 4.0000e-02 eta: 1 day, 0:07:03 time: 0.2610 data_time: 0.0084 memory: 5828 grad_norm: 2.9365 loss: 2.6502 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6502 2023/06/04 20:50:02 - mmengine - INFO - Epoch(train) [24][1420/2569] lr: 4.0000e-02 eta: 1 day, 0:06:58 time: 0.2763 data_time: 0.0078 memory: 5828 grad_norm: 2.9135 loss: 2.5976 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5976 2023/06/04 20:50:07 - mmengine - INFO - Epoch(train) [24][1440/2569] lr: 4.0000e-02 eta: 1 day, 0:06:52 time: 0.2595 data_time: 0.0080 memory: 5828 grad_norm: 2.9276 loss: 2.6865 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6865 2023/06/04 20:50:13 - mmengine - INFO - Epoch(train) [24][1460/2569] lr: 4.0000e-02 eta: 1 day, 0:06:47 time: 0.2688 data_time: 0.0075 memory: 5828 grad_norm: 2.9575 loss: 2.4254 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4254 2023/06/04 20:50:18 - mmengine - INFO - Epoch(train) [24][1480/2569] lr: 4.0000e-02 eta: 1 day, 0:06:41 time: 0.2641 data_time: 0.0076 memory: 5828 grad_norm: 2.8753 loss: 2.3688 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3688 2023/06/04 20:50:23 - mmengine - INFO - Epoch(train) [24][1500/2569] lr: 4.0000e-02 eta: 1 day, 0:06:36 time: 0.2665 data_time: 0.0078 memory: 5828 grad_norm: 2.9471 loss: 2.7772 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7772 2023/06/04 20:50:29 - mmengine - INFO - Epoch(train) [24][1520/2569] lr: 4.0000e-02 eta: 1 day, 0:06:30 time: 0.2651 data_time: 0.0078 memory: 5828 grad_norm: 2.8632 loss: 2.6441 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6441 2023/06/04 20:50:34 - mmengine - INFO - Epoch(train) [24][1540/2569] lr: 4.0000e-02 eta: 1 day, 0:06:24 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 2.9160 loss: 2.3703 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3703 2023/06/04 20:50:39 - mmengine - INFO - Epoch(train) [24][1560/2569] lr: 4.0000e-02 eta: 1 day, 0:06:19 time: 0.2675 data_time: 0.0078 memory: 5828 grad_norm: 2.9326 loss: 2.8067 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8067 2023/06/04 20:50:45 - mmengine - INFO - Epoch(train) [24][1580/2569] lr: 4.0000e-02 eta: 1 day, 0:06:13 time: 0.2610 data_time: 0.0081 memory: 5828 grad_norm: 2.8921 loss: 2.5065 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5065 2023/06/04 20:50:50 - mmengine - INFO - Epoch(train) [24][1600/2569] lr: 4.0000e-02 eta: 1 day, 0:06:07 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 2.8820 loss: 2.1696 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1696 2023/06/04 20:50:55 - mmengine - INFO - Epoch(train) [24][1620/2569] lr: 4.0000e-02 eta: 1 day, 0:06:01 time: 0.2618 data_time: 0.0082 memory: 5828 grad_norm: 2.8817 loss: 2.5965 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5965 2023/06/04 20:51:00 - mmengine - INFO - Epoch(train) [24][1640/2569] lr: 4.0000e-02 eta: 1 day, 0:05:55 time: 0.2618 data_time: 0.0076 memory: 5828 grad_norm: 2.8483 loss: 2.7327 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7327 2023/06/04 20:51:06 - mmengine - INFO - Epoch(train) [24][1660/2569] lr: 4.0000e-02 eta: 1 day, 0:05:49 time: 0.2657 data_time: 0.0078 memory: 5828 grad_norm: 2.9492 loss: 2.6614 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6614 2023/06/04 20:51:11 - mmengine - INFO - Epoch(train) [24][1680/2569] lr: 4.0000e-02 eta: 1 day, 0:05:43 time: 0.2615 data_time: 0.0082 memory: 5828 grad_norm: 2.9335 loss: 2.8498 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8498 2023/06/04 20:51:16 - mmengine - INFO - Epoch(train) [24][1700/2569] lr: 4.0000e-02 eta: 1 day, 0:05:38 time: 0.2709 data_time: 0.0077 memory: 5828 grad_norm: 2.9546 loss: 2.7205 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7205 2023/06/04 20:51:22 - mmengine - INFO - Epoch(train) [24][1720/2569] lr: 4.0000e-02 eta: 1 day, 0:05:33 time: 0.2659 data_time: 0.0080 memory: 5828 grad_norm: 2.9323 loss: 2.7110 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7110 2023/06/04 20:51:27 - mmengine - INFO - Epoch(train) [24][1740/2569] lr: 4.0000e-02 eta: 1 day, 0:05:28 time: 0.2669 data_time: 0.0086 memory: 5828 grad_norm: 2.9022 loss: 2.8602 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.8602 2023/06/04 20:51:32 - mmengine - INFO - Epoch(train) [24][1760/2569] lr: 4.0000e-02 eta: 1 day, 0:05:22 time: 0.2614 data_time: 0.0078 memory: 5828 grad_norm: 2.8756 loss: 2.3973 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3973 2023/06/04 20:51:37 - mmengine - INFO - Epoch(train) [24][1780/2569] lr: 4.0000e-02 eta: 1 day, 0:05:16 time: 0.2630 data_time: 0.0082 memory: 5828 grad_norm: 2.8907 loss: 2.3766 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3766 2023/06/04 20:51:43 - mmengine - INFO - Epoch(train) [24][1800/2569] lr: 4.0000e-02 eta: 1 day, 0:05:10 time: 0.2623 data_time: 0.0076 memory: 5828 grad_norm: 2.8996 loss: 2.4808 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.4808 2023/06/04 20:51:48 - mmengine - INFO - Epoch(train) [24][1820/2569] lr: 4.0000e-02 eta: 1 day, 0:05:05 time: 0.2667 data_time: 0.0080 memory: 5828 grad_norm: 2.9270 loss: 2.5850 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5850 2023/06/04 20:51:53 - mmengine - INFO - Epoch(train) [24][1840/2569] lr: 4.0000e-02 eta: 1 day, 0:04:59 time: 0.2664 data_time: 0.0079 memory: 5828 grad_norm: 2.8459 loss: 2.4007 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4007 2023/06/04 20:51:59 - mmengine - INFO - Epoch(train) [24][1860/2569] lr: 4.0000e-02 eta: 1 day, 0:04:54 time: 0.2659 data_time: 0.0080 memory: 5828 grad_norm: 2.9693 loss: 2.8467 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.8467 2023/06/04 20:52:04 - mmengine - INFO - Epoch(train) [24][1880/2569] lr: 4.0000e-02 eta: 1 day, 0:04:49 time: 0.2690 data_time: 0.0081 memory: 5828 grad_norm: 2.8438 loss: 2.4697 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4697 2023/06/04 20:52:09 - mmengine - INFO - Epoch(train) [24][1900/2569] lr: 4.0000e-02 eta: 1 day, 0:04:43 time: 0.2697 data_time: 0.0080 memory: 5828 grad_norm: 2.8865 loss: 2.4971 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4971 2023/06/04 20:52:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:52:15 - mmengine - INFO - Epoch(train) [24][1920/2569] lr: 4.0000e-02 eta: 1 day, 0:04:38 time: 0.2655 data_time: 0.0078 memory: 5828 grad_norm: 2.9158 loss: 2.7557 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.7557 2023/06/04 20:52:20 - mmengine - INFO - Epoch(train) [24][1940/2569] lr: 4.0000e-02 eta: 1 day, 0:04:34 time: 0.2771 data_time: 0.0076 memory: 5828 grad_norm: 2.9125 loss: 2.8459 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8459 2023/06/04 20:52:26 - mmengine - INFO - Epoch(train) [24][1960/2569] lr: 4.0000e-02 eta: 1 day, 0:04:28 time: 0.2644 data_time: 0.0077 memory: 5828 grad_norm: 2.8403 loss: 2.8610 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8610 2023/06/04 20:52:31 - mmengine - INFO - Epoch(train) [24][1980/2569] lr: 4.0000e-02 eta: 1 day, 0:04:22 time: 0.2655 data_time: 0.0073 memory: 5828 grad_norm: 2.9053 loss: 2.3999 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3999 2023/06/04 20:52:36 - mmengine - INFO - Epoch(train) [24][2000/2569] lr: 4.0000e-02 eta: 1 day, 0:04:17 time: 0.2627 data_time: 0.0078 memory: 5828 grad_norm: 2.8394 loss: 2.6304 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6304 2023/06/04 20:52:41 - mmengine - INFO - Epoch(train) [24][2020/2569] lr: 4.0000e-02 eta: 1 day, 0:04:11 time: 0.2620 data_time: 0.0079 memory: 5828 grad_norm: 2.8978 loss: 2.7205 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7205 2023/06/04 20:52:47 - mmengine - INFO - Epoch(train) [24][2040/2569] lr: 4.0000e-02 eta: 1 day, 0:04:05 time: 0.2643 data_time: 0.0077 memory: 5828 grad_norm: 2.8759 loss: 2.5565 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5565 2023/06/04 20:52:52 - mmengine - INFO - Epoch(train) [24][2060/2569] lr: 4.0000e-02 eta: 1 day, 0:04:00 time: 0.2676 data_time: 0.0085 memory: 5828 grad_norm: 2.9173 loss: 2.6232 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6232 2023/06/04 20:52:57 - mmengine - INFO - Epoch(train) [24][2080/2569] lr: 4.0000e-02 eta: 1 day, 0:03:54 time: 0.2628 data_time: 0.0077 memory: 5828 grad_norm: 2.9348 loss: 2.5010 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5010 2023/06/04 20:53:02 - mmengine - INFO - Epoch(train) [24][2100/2569] lr: 4.0000e-02 eta: 1 day, 0:03:48 time: 0.2619 data_time: 0.0080 memory: 5828 grad_norm: 2.9213 loss: 2.6248 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6248 2023/06/04 20:53:08 - mmengine - INFO - Epoch(train) [24][2120/2569] lr: 4.0000e-02 eta: 1 day, 0:03:43 time: 0.2678 data_time: 0.0076 memory: 5828 grad_norm: 2.9239 loss: 2.4287 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4287 2023/06/04 20:53:13 - mmengine - INFO - Epoch(train) [24][2140/2569] lr: 4.0000e-02 eta: 1 day, 0:03:38 time: 0.2749 data_time: 0.0078 memory: 5828 grad_norm: 2.8956 loss: 2.5329 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5329 2023/06/04 20:53:19 - mmengine - INFO - Epoch(train) [24][2160/2569] lr: 4.0000e-02 eta: 1 day, 0:03:33 time: 0.2656 data_time: 0.0086 memory: 5828 grad_norm: 2.9623 loss: 2.5860 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5860 2023/06/04 20:53:24 - mmengine - INFO - Epoch(train) [24][2180/2569] lr: 4.0000e-02 eta: 1 day, 0:03:28 time: 0.2767 data_time: 0.0074 memory: 5828 grad_norm: 2.9164 loss: 2.6061 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6061 2023/06/04 20:53:29 - mmengine - INFO - Epoch(train) [24][2200/2569] lr: 4.0000e-02 eta: 1 day, 0:03:23 time: 0.2652 data_time: 0.0082 memory: 5828 grad_norm: 2.9060 loss: 2.7462 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7462 2023/06/04 20:53:35 - mmengine - INFO - Epoch(train) [24][2220/2569] lr: 4.0000e-02 eta: 1 day, 0:03:18 time: 0.2711 data_time: 0.0081 memory: 5828 grad_norm: 2.8903 loss: 2.6138 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6138 2023/06/04 20:53:40 - mmengine - INFO - Epoch(train) [24][2240/2569] lr: 4.0000e-02 eta: 1 day, 0:03:13 time: 0.2679 data_time: 0.0080 memory: 5828 grad_norm: 2.8993 loss: 2.6058 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6058 2023/06/04 20:53:45 - mmengine - INFO - Epoch(train) [24][2260/2569] lr: 4.0000e-02 eta: 1 day, 0:03:07 time: 0.2605 data_time: 0.0087 memory: 5828 grad_norm: 2.9566 loss: 2.5259 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5259 2023/06/04 20:53:51 - mmengine - INFO - Epoch(train) [24][2280/2569] lr: 4.0000e-02 eta: 1 day, 0:03:01 time: 0.2612 data_time: 0.0083 memory: 5828 grad_norm: 2.8669 loss: 2.4262 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4262 2023/06/04 20:53:56 - mmengine - INFO - Epoch(train) [24][2300/2569] lr: 4.0000e-02 eta: 1 day, 0:02:55 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 2.9250 loss: 2.6503 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6503 2023/06/04 20:54:01 - mmengine - INFO - Epoch(train) [24][2320/2569] lr: 4.0000e-02 eta: 1 day, 0:02:49 time: 0.2662 data_time: 0.0078 memory: 5828 grad_norm: 2.9298 loss: 2.5528 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5528 2023/06/04 20:54:07 - mmengine - INFO - Epoch(train) [24][2340/2569] lr: 4.0000e-02 eta: 1 day, 0:02:44 time: 0.2659 data_time: 0.0076 memory: 5828 grad_norm: 2.9927 loss: 2.5544 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5544 2023/06/04 20:54:12 - mmengine - INFO - Epoch(train) [24][2360/2569] lr: 4.0000e-02 eta: 1 day, 0:02:38 time: 0.2641 data_time: 0.0077 memory: 5828 grad_norm: 2.8723 loss: 2.6542 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6542 2023/06/04 20:54:17 - mmengine - INFO - Epoch(train) [24][2380/2569] lr: 4.0000e-02 eta: 1 day, 0:02:33 time: 0.2714 data_time: 0.0075 memory: 5828 grad_norm: 2.9976 loss: 2.3023 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3023 2023/06/04 20:54:23 - mmengine - INFO - Epoch(train) [24][2400/2569] lr: 4.0000e-02 eta: 1 day, 0:02:28 time: 0.2626 data_time: 0.0077 memory: 5828 grad_norm: 2.9521 loss: 2.4060 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4060 2023/06/04 20:54:28 - mmengine - INFO - Epoch(train) [24][2420/2569] lr: 4.0000e-02 eta: 1 day, 0:02:23 time: 0.2722 data_time: 0.0075 memory: 5828 grad_norm: 2.8874 loss: 2.7474 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7474 2023/06/04 20:54:34 - mmengine - INFO - Epoch(train) [24][2440/2569] lr: 4.0000e-02 eta: 1 day, 0:02:18 time: 0.2758 data_time: 0.0081 memory: 5828 grad_norm: 2.9330 loss: 2.5760 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5760 2023/06/04 20:54:39 - mmengine - INFO - Epoch(train) [24][2460/2569] lr: 4.0000e-02 eta: 1 day, 0:02:13 time: 0.2655 data_time: 0.0079 memory: 5828 grad_norm: 2.8578 loss: 2.7950 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7950 2023/06/04 20:54:44 - mmengine - INFO - Epoch(train) [24][2480/2569] lr: 4.0000e-02 eta: 1 day, 0:02:07 time: 0.2675 data_time: 0.0078 memory: 5828 grad_norm: 2.9757 loss: 2.5141 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5141 2023/06/04 20:54:50 - mmengine - INFO - Epoch(train) [24][2500/2569] lr: 4.0000e-02 eta: 1 day, 0:02:02 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 2.9310 loss: 2.6913 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6913 2023/06/04 20:54:55 - mmengine - INFO - Epoch(train) [24][2520/2569] lr: 4.0000e-02 eta: 1 day, 0:01:57 time: 0.2684 data_time: 0.0087 memory: 5828 grad_norm: 2.9676 loss: 2.5725 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5725 2023/06/04 20:55:00 - mmengine - INFO - Epoch(train) [24][2540/2569] lr: 4.0000e-02 eta: 1 day, 0:01:51 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 2.9843 loss: 2.1626 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1626 2023/06/04 20:55:05 - mmengine - INFO - Epoch(train) [24][2560/2569] lr: 4.0000e-02 eta: 1 day, 0:01:45 time: 0.2578 data_time: 0.0077 memory: 5828 grad_norm: 2.9313 loss: 2.6449 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6449 2023/06/04 20:55:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:55:08 - mmengine - INFO - Epoch(train) [24][2569/2569] lr: 4.0000e-02 eta: 1 day, 0:01:41 time: 0.2504 data_time: 0.0080 memory: 5828 grad_norm: 2.9261 loss: 2.5634 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5634 2023/06/04 20:55:08 - mmengine - INFO - Saving checkpoint at 24 epochs 2023/06/04 20:55:18 - mmengine - INFO - Epoch(train) [25][ 20/2569] lr: 4.0000e-02 eta: 1 day, 0:01:41 time: 0.3141 data_time: 0.0463 memory: 5828 grad_norm: 2.9562 loss: 2.2919 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2919 2023/06/04 20:55:24 - mmengine - INFO - Epoch(train) [25][ 40/2569] lr: 4.0000e-02 eta: 1 day, 0:01:36 time: 0.2662 data_time: 0.0078 memory: 5828 grad_norm: 2.9036 loss: 2.3652 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3652 2023/06/04 20:55:29 - mmengine - INFO - Epoch(train) [25][ 60/2569] lr: 4.0000e-02 eta: 1 day, 0:01:30 time: 0.2614 data_time: 0.0079 memory: 5828 grad_norm: 2.9293 loss: 2.3816 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3816 2023/06/04 20:55:34 - mmengine - INFO - Epoch(train) [25][ 80/2569] lr: 4.0000e-02 eta: 1 day, 0:01:24 time: 0.2658 data_time: 0.0078 memory: 5828 grad_norm: 2.9247 loss: 2.9042 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9042 2023/06/04 20:55:40 - mmengine - INFO - Epoch(train) [25][ 100/2569] lr: 4.0000e-02 eta: 1 day, 0:01:19 time: 0.2665 data_time: 0.0076 memory: 5828 grad_norm: 2.9762 loss: 3.0785 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0785 2023/06/04 20:55:45 - mmengine - INFO - Epoch(train) [25][ 120/2569] lr: 4.0000e-02 eta: 1 day, 0:01:14 time: 0.2707 data_time: 0.0077 memory: 5828 grad_norm: 2.9585 loss: 2.2138 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2138 2023/06/04 20:55:51 - mmengine - INFO - Epoch(train) [25][ 140/2569] lr: 4.0000e-02 eta: 1 day, 0:01:09 time: 0.2764 data_time: 0.0080 memory: 5828 grad_norm: 2.9640 loss: 2.5942 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.5942 2023/06/04 20:55:56 - mmengine - INFO - Epoch(train) [25][ 160/2569] lr: 4.0000e-02 eta: 1 day, 0:01:04 time: 0.2712 data_time: 0.0078 memory: 5828 grad_norm: 2.9470 loss: 2.7369 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7369 2023/06/04 20:56:01 - mmengine - INFO - Epoch(train) [25][ 180/2569] lr: 4.0000e-02 eta: 1 day, 0:00:58 time: 0.2592 data_time: 0.0080 memory: 5828 grad_norm: 2.9670 loss: 2.8562 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8562 2023/06/04 20:56:07 - mmengine - INFO - Epoch(train) [25][ 200/2569] lr: 4.0000e-02 eta: 1 day, 0:00:54 time: 0.2765 data_time: 0.0080 memory: 5828 grad_norm: 3.0174 loss: 2.5166 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5166 2023/06/04 20:56:12 - mmengine - INFO - Epoch(train) [25][ 220/2569] lr: 4.0000e-02 eta: 1 day, 0:00:48 time: 0.2670 data_time: 0.0075 memory: 5828 grad_norm: 2.9075 loss: 2.6359 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6359 2023/06/04 20:56:17 - mmengine - INFO - Epoch(train) [25][ 240/2569] lr: 4.0000e-02 eta: 1 day, 0:00:43 time: 0.2662 data_time: 0.0091 memory: 5828 grad_norm: 2.9337 loss: 2.8311 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8311 2023/06/04 20:56:23 - mmengine - INFO - Epoch(train) [25][ 260/2569] lr: 4.0000e-02 eta: 1 day, 0:00:38 time: 0.2730 data_time: 0.0085 memory: 5828 grad_norm: 2.9411 loss: 2.4348 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4348 2023/06/04 20:56:28 - mmengine - INFO - Epoch(train) [25][ 280/2569] lr: 4.0000e-02 eta: 1 day, 0:00:33 time: 0.2657 data_time: 0.0078 memory: 5828 grad_norm: 2.9237 loss: 2.6008 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6008 2023/06/04 20:56:34 - mmengine - INFO - Epoch(train) [25][ 300/2569] lr: 4.0000e-02 eta: 1 day, 0:00:27 time: 0.2673 data_time: 0.0076 memory: 5828 grad_norm: 2.8756 loss: 2.4946 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4946 2023/06/04 20:56:39 - mmengine - INFO - Epoch(train) [25][ 320/2569] lr: 4.0000e-02 eta: 1 day, 0:00:23 time: 0.2713 data_time: 0.0080 memory: 5828 grad_norm: 2.9105 loss: 2.9404 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9404 2023/06/04 20:56:44 - mmengine - INFO - Epoch(train) [25][ 340/2569] lr: 4.0000e-02 eta: 1 day, 0:00:17 time: 0.2669 data_time: 0.0080 memory: 5828 grad_norm: 2.9156 loss: 2.7776 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7776 2023/06/04 20:56:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 20:56:50 - mmengine - INFO - Epoch(train) [25][ 360/2569] lr: 4.0000e-02 eta: 1 day, 0:00:13 time: 0.2757 data_time: 0.0078 memory: 5828 grad_norm: 2.9212 loss: 2.8509 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8509 2023/06/04 20:56:55 - mmengine - INFO - Epoch(train) [25][ 380/2569] lr: 4.0000e-02 eta: 1 day, 0:00:07 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 2.9764 loss: 2.5322 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5322 2023/06/04 20:57:00 - mmengine - INFO - Epoch(train) [25][ 400/2569] lr: 4.0000e-02 eta: 1 day, 0:00:01 time: 0.2620 data_time: 0.0077 memory: 5828 grad_norm: 2.9055 loss: 2.6552 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6552 2023/06/04 20:57:06 - mmengine - INFO - Epoch(train) [25][ 420/2569] lr: 4.0000e-02 eta: 23:59:55 time: 0.2621 data_time: 0.0071 memory: 5828 grad_norm: 2.8927 loss: 2.5089 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5089 2023/06/04 20:57:11 - mmengine - INFO - Epoch(train) [25][ 440/2569] lr: 4.0000e-02 eta: 23:59:50 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 2.9137 loss: 2.8703 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8703 2023/06/04 20:57:16 - mmengine - INFO - Epoch(train) [25][ 460/2569] lr: 4.0000e-02 eta: 23:59:44 time: 0.2633 data_time: 0.0076 memory: 5828 grad_norm: 2.9301 loss: 2.5640 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5640 2023/06/04 20:57:22 - mmengine - INFO - Epoch(train) [25][ 480/2569] lr: 4.0000e-02 eta: 23:59:39 time: 0.2651 data_time: 0.0084 memory: 5828 grad_norm: 2.9113 loss: 2.8347 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8347 2023/06/04 20:57:27 - mmengine - INFO - Epoch(train) [25][ 500/2569] lr: 4.0000e-02 eta: 23:59:33 time: 0.2618 data_time: 0.0082 memory: 5828 grad_norm: 2.9298 loss: 2.4162 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4162 2023/06/04 20:57:32 - mmengine - INFO - Epoch(train) [25][ 520/2569] lr: 4.0000e-02 eta: 23:59:28 time: 0.2701 data_time: 0.0086 memory: 5828 grad_norm: 2.9670 loss: 2.5998 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5998 2023/06/04 20:57:38 - mmengine - INFO - Epoch(train) [25][ 540/2569] lr: 4.0000e-02 eta: 23:59:23 time: 0.2703 data_time: 0.0077 memory: 5828 grad_norm: 2.8886 loss: 2.5339 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5339 2023/06/04 20:57:43 - mmengine - INFO - Epoch(train) [25][ 560/2569] lr: 4.0000e-02 eta: 23:59:17 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 2.9144 loss: 2.6847 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6847 2023/06/04 20:57:48 - mmengine - INFO - Epoch(train) [25][ 580/2569] lr: 4.0000e-02 eta: 23:59:12 time: 0.2720 data_time: 0.0073 memory: 5828 grad_norm: 2.9795 loss: 2.6456 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6456 2023/06/04 20:57:54 - mmengine - INFO - Epoch(train) [25][ 600/2569] lr: 4.0000e-02 eta: 23:59:06 time: 0.2622 data_time: 0.0079 memory: 5828 grad_norm: 2.9519 loss: 3.0057 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 3.0057 2023/06/04 20:57:59 - mmengine - INFO - Epoch(train) [25][ 620/2569] lr: 4.0000e-02 eta: 23:59:01 time: 0.2718 data_time: 0.0080 memory: 5828 grad_norm: 2.9041 loss: 2.3913 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3913 2023/06/04 20:58:04 - mmengine - INFO - Epoch(train) [25][ 640/2569] lr: 4.0000e-02 eta: 23:58:56 time: 0.2725 data_time: 0.0080 memory: 5828 grad_norm: 2.8793 loss: 2.4259 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4259 2023/06/04 20:58:10 - mmengine - INFO - Epoch(train) [25][ 660/2569] lr: 4.0000e-02 eta: 23:58:51 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 2.9157 loss: 2.4277 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4277 2023/06/04 20:58:15 - mmengine - INFO - Epoch(train) [25][ 680/2569] lr: 4.0000e-02 eta: 23:58:45 time: 0.2630 data_time: 0.0079 memory: 5828 grad_norm: 2.8630 loss: 2.2226 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2226 2023/06/04 20:58:20 - mmengine - INFO - Epoch(train) [25][ 700/2569] lr: 4.0000e-02 eta: 23:58:40 time: 0.2735 data_time: 0.0083 memory: 5828 grad_norm: 2.9079 loss: 2.7950 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7950 2023/06/04 20:58:26 - mmengine - INFO - Epoch(train) [25][ 720/2569] lr: 4.0000e-02 eta: 23:58:35 time: 0.2668 data_time: 0.0079 memory: 5828 grad_norm: 2.8989 loss: 2.5198 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5198 2023/06/04 20:58:31 - mmengine - INFO - Epoch(train) [25][ 740/2569] lr: 4.0000e-02 eta: 23:58:29 time: 0.2663 data_time: 0.0072 memory: 5828 grad_norm: 2.9460 loss: 2.3637 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3637 2023/06/04 20:58:37 - mmengine - INFO - Epoch(train) [25][ 760/2569] lr: 4.0000e-02 eta: 23:58:25 time: 0.2767 data_time: 0.0081 memory: 5828 grad_norm: 2.9235 loss: 2.7500 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7500 2023/06/04 20:58:42 - mmengine - INFO - Epoch(train) [25][ 780/2569] lr: 4.0000e-02 eta: 23:58:19 time: 0.2601 data_time: 0.0076 memory: 5828 grad_norm: 2.9212 loss: 2.4343 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4343 2023/06/04 20:58:47 - mmengine - INFO - Epoch(train) [25][ 800/2569] lr: 4.0000e-02 eta: 23:58:14 time: 0.2712 data_time: 0.0075 memory: 5828 grad_norm: 2.9344 loss: 2.6470 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6470 2023/06/04 20:58:53 - mmengine - INFO - Epoch(train) [25][ 820/2569] lr: 4.0000e-02 eta: 23:58:08 time: 0.2643 data_time: 0.0081 memory: 5828 grad_norm: 2.9726 loss: 2.4289 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4289 2023/06/04 20:58:58 - mmengine - INFO - Epoch(train) [25][ 840/2569] lr: 4.0000e-02 eta: 23:58:03 time: 0.2674 data_time: 0.0081 memory: 5828 grad_norm: 2.9094 loss: 2.7590 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7590 2023/06/04 20:59:03 - mmengine - INFO - Epoch(train) [25][ 860/2569] lr: 4.0000e-02 eta: 23:57:58 time: 0.2692 data_time: 0.0080 memory: 5828 grad_norm: 2.9076 loss: 2.5019 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5019 2023/06/04 20:59:09 - mmengine - INFO - Epoch(train) [25][ 880/2569] lr: 4.0000e-02 eta: 23:57:53 time: 0.2714 data_time: 0.0078 memory: 5828 grad_norm: 2.9899 loss: 2.5657 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5657 2023/06/04 20:59:14 - mmengine - INFO - Epoch(train) [25][ 900/2569] lr: 4.0000e-02 eta: 23:57:48 time: 0.2713 data_time: 0.0079 memory: 5828 grad_norm: 2.9522 loss: 2.6792 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6792 2023/06/04 20:59:20 - mmengine - INFO - Epoch(train) [25][ 920/2569] lr: 4.0000e-02 eta: 23:57:43 time: 0.2712 data_time: 0.0077 memory: 5828 grad_norm: 2.9960 loss: 2.7840 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7840 2023/06/04 20:59:25 - mmengine - INFO - Epoch(train) [25][ 940/2569] lr: 4.0000e-02 eta: 23:57:38 time: 0.2645 data_time: 0.0075 memory: 5828 grad_norm: 2.9642 loss: 2.7423 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7423 2023/06/04 20:59:30 - mmengine - INFO - Epoch(train) [25][ 960/2569] lr: 4.0000e-02 eta: 23:57:32 time: 0.2652 data_time: 0.0084 memory: 5828 grad_norm: 2.9381 loss: 2.7100 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7100 2023/06/04 20:59:36 - mmengine - INFO - Epoch(train) [25][ 980/2569] lr: 4.0000e-02 eta: 23:57:27 time: 0.2736 data_time: 0.0071 memory: 5828 grad_norm: 2.9845 loss: 2.4627 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4627 2023/06/04 20:59:41 - mmengine - INFO - Epoch(train) [25][1000/2569] lr: 4.0000e-02 eta: 23:57:21 time: 0.2608 data_time: 0.0080 memory: 5828 grad_norm: 2.9410 loss: 2.7530 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7530 2023/06/04 20:59:46 - mmengine - INFO - Epoch(train) [25][1020/2569] lr: 4.0000e-02 eta: 23:57:16 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 2.9666 loss: 2.6804 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6804 2023/06/04 20:59:52 - mmengine - INFO - Epoch(train) [25][1040/2569] lr: 4.0000e-02 eta: 23:57:10 time: 0.2642 data_time: 0.0076 memory: 5828 grad_norm: 2.8802 loss: 2.7997 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7997 2023/06/04 20:59:57 - mmengine - INFO - Epoch(train) [25][1060/2569] lr: 4.0000e-02 eta: 23:57:05 time: 0.2708 data_time: 0.0079 memory: 5828 grad_norm: 2.9889 loss: 3.0252 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0252 2023/06/04 21:00:02 - mmengine - INFO - Epoch(train) [25][1080/2569] lr: 4.0000e-02 eta: 23:57:00 time: 0.2679 data_time: 0.0076 memory: 5828 grad_norm: 2.9483 loss: 2.6911 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6911 2023/06/04 21:00:08 - mmengine - INFO - Epoch(train) [25][1100/2569] lr: 4.0000e-02 eta: 23:56:55 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 2.9531 loss: 2.8502 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8502 2023/06/04 21:00:13 - mmengine - INFO - Epoch(train) [25][1120/2569] lr: 4.0000e-02 eta: 23:56:51 time: 0.2807 data_time: 0.0083 memory: 5828 grad_norm: 2.9455 loss: 2.5300 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5300 2023/06/04 21:00:18 - mmengine - INFO - Epoch(train) [25][1140/2569] lr: 4.0000e-02 eta: 23:56:45 time: 0.2599 data_time: 0.0077 memory: 5828 grad_norm: 2.9337 loss: 2.4530 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4530 2023/06/04 21:00:24 - mmengine - INFO - Epoch(train) [25][1160/2569] lr: 4.0000e-02 eta: 23:56:40 time: 0.2750 data_time: 0.0080 memory: 5828 grad_norm: 2.8657 loss: 2.2502 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2502 2023/06/04 21:00:29 - mmengine - INFO - Epoch(train) [25][1180/2569] lr: 4.0000e-02 eta: 23:56:34 time: 0.2613 data_time: 0.0076 memory: 5828 grad_norm: 2.9178 loss: 2.5105 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5105 2023/06/04 21:00:35 - mmengine - INFO - Epoch(train) [25][1200/2569] lr: 4.0000e-02 eta: 23:56:29 time: 0.2692 data_time: 0.0077 memory: 5828 grad_norm: 2.8821 loss: 2.5560 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5560 2023/06/04 21:00:40 - mmengine - INFO - Epoch(train) [25][1220/2569] lr: 4.0000e-02 eta: 23:56:23 time: 0.2653 data_time: 0.0077 memory: 5828 grad_norm: 2.9329 loss: 2.4420 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4420 2023/06/04 21:00:45 - mmengine - INFO - Epoch(train) [25][1240/2569] lr: 4.0000e-02 eta: 23:56:18 time: 0.2692 data_time: 0.0078 memory: 5828 grad_norm: 2.9090 loss: 2.3470 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3470 2023/06/04 21:00:51 - mmengine - INFO - Epoch(train) [25][1260/2569] lr: 4.0000e-02 eta: 23:56:13 time: 0.2673 data_time: 0.0079 memory: 5828 grad_norm: 2.9772 loss: 2.5057 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5057 2023/06/04 21:00:56 - mmengine - INFO - Epoch(train) [25][1280/2569] lr: 4.0000e-02 eta: 23:56:07 time: 0.2642 data_time: 0.0079 memory: 5828 grad_norm: 2.9729 loss: 2.7415 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7415 2023/06/04 21:01:01 - mmengine - INFO - Epoch(train) [25][1300/2569] lr: 4.0000e-02 eta: 23:56:03 time: 0.2729 data_time: 0.0079 memory: 5828 grad_norm: 2.9287 loss: 2.7079 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7079 2023/06/04 21:01:07 - mmengine - INFO - Epoch(train) [25][1320/2569] lr: 4.0000e-02 eta: 23:55:57 time: 0.2637 data_time: 0.0076 memory: 5828 grad_norm: 2.9785 loss: 2.3675 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3675 2023/06/04 21:01:12 - mmengine - INFO - Epoch(train) [25][1340/2569] lr: 4.0000e-02 eta: 23:55:52 time: 0.2724 data_time: 0.0074 memory: 5828 grad_norm: 2.9625 loss: 2.1956 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.1956 2023/06/04 21:01:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:01:17 - mmengine - INFO - Epoch(train) [25][1360/2569] lr: 4.0000e-02 eta: 23:55:46 time: 0.2643 data_time: 0.0076 memory: 5828 grad_norm: 2.8904 loss: 2.5848 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5848 2023/06/04 21:01:23 - mmengine - INFO - Epoch(train) [25][1380/2569] lr: 4.0000e-02 eta: 23:55:42 time: 0.2791 data_time: 0.0077 memory: 5828 grad_norm: 2.9234 loss: 2.6622 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6622 2023/06/04 21:01:28 - mmengine - INFO - Epoch(train) [25][1400/2569] lr: 4.0000e-02 eta: 23:55:36 time: 0.2598 data_time: 0.0076 memory: 5828 grad_norm: 2.9095 loss: 2.5754 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5754 2023/06/04 21:01:34 - mmengine - INFO - Epoch(train) [25][1420/2569] lr: 4.0000e-02 eta: 23:55:32 time: 0.2758 data_time: 0.0083 memory: 5828 grad_norm: 2.9160 loss: 2.4796 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.4796 2023/06/04 21:01:39 - mmengine - INFO - Epoch(train) [25][1440/2569] lr: 4.0000e-02 eta: 23:55:27 time: 0.2744 data_time: 0.0077 memory: 5828 grad_norm: 2.9234 loss: 2.8452 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8452 2023/06/04 21:01:45 - mmengine - INFO - Epoch(train) [25][1460/2569] lr: 4.0000e-02 eta: 23:55:23 time: 0.2766 data_time: 0.0077 memory: 5828 grad_norm: 2.8796 loss: 2.6696 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6696 2023/06/04 21:01:50 - mmengine - INFO - Epoch(train) [25][1480/2569] lr: 4.0000e-02 eta: 23:55:17 time: 0.2660 data_time: 0.0081 memory: 5828 grad_norm: 2.9644 loss: 2.5518 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5518 2023/06/04 21:01:55 - mmengine - INFO - Epoch(train) [25][1500/2569] lr: 4.0000e-02 eta: 23:55:12 time: 0.2662 data_time: 0.0077 memory: 5828 grad_norm: 2.9250 loss: 2.2256 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2256 2023/06/04 21:02:01 - mmengine - INFO - Epoch(train) [25][1520/2569] lr: 4.0000e-02 eta: 23:55:06 time: 0.2681 data_time: 0.0078 memory: 5828 grad_norm: 2.9085 loss: 2.5516 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5516 2023/06/04 21:02:06 - mmengine - INFO - Epoch(train) [25][1540/2569] lr: 4.0000e-02 eta: 23:55:01 time: 0.2632 data_time: 0.0078 memory: 5828 grad_norm: 2.9136 loss: 2.7655 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7655 2023/06/04 21:02:11 - mmengine - INFO - Epoch(train) [25][1560/2569] lr: 4.0000e-02 eta: 23:54:56 time: 0.2729 data_time: 0.0075 memory: 5828 grad_norm: 2.9436 loss: 2.1280 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1280 2023/06/04 21:02:17 - mmengine - INFO - Epoch(train) [25][1580/2569] lr: 4.0000e-02 eta: 23:54:50 time: 0.2601 data_time: 0.0082 memory: 5828 grad_norm: 2.9334 loss: 2.7055 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7055 2023/06/04 21:02:22 - mmengine - INFO - Epoch(train) [25][1600/2569] lr: 4.0000e-02 eta: 23:54:45 time: 0.2733 data_time: 0.0076 memory: 5828 grad_norm: 2.9699 loss: 2.5329 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5329 2023/06/04 21:02:27 - mmengine - INFO - Epoch(train) [25][1620/2569] lr: 4.0000e-02 eta: 23:54:39 time: 0.2619 data_time: 0.0080 memory: 5828 grad_norm: 2.8967 loss: 2.7962 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7962 2023/06/04 21:02:33 - mmengine - INFO - Epoch(train) [25][1640/2569] lr: 4.0000e-02 eta: 23:54:34 time: 0.2654 data_time: 0.0076 memory: 5828 grad_norm: 2.9136 loss: 2.8049 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8049 2023/06/04 21:02:38 - mmengine - INFO - Epoch(train) [25][1660/2569] lr: 4.0000e-02 eta: 23:54:29 time: 0.2778 data_time: 0.0084 memory: 5828 grad_norm: 2.9023 loss: 2.6038 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6038 2023/06/04 21:02:44 - mmengine - INFO - Epoch(train) [25][1680/2569] lr: 4.0000e-02 eta: 23:54:24 time: 0.2664 data_time: 0.0080 memory: 5828 grad_norm: 2.8883 loss: 2.7283 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7283 2023/06/04 21:02:49 - mmengine - INFO - Epoch(train) [25][1700/2569] lr: 4.0000e-02 eta: 23:54:18 time: 0.2651 data_time: 0.0076 memory: 5828 grad_norm: 2.9600 loss: 2.5295 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5295 2023/06/04 21:02:54 - mmengine - INFO - Epoch(train) [25][1720/2569] lr: 4.0000e-02 eta: 23:54:13 time: 0.2656 data_time: 0.0081 memory: 5828 grad_norm: 2.9542 loss: 2.7502 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7502 2023/06/04 21:03:00 - mmengine - INFO - Epoch(train) [25][1740/2569] lr: 4.0000e-02 eta: 23:54:08 time: 0.2677 data_time: 0.0081 memory: 5828 grad_norm: 2.9925 loss: 2.1248 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1248 2023/06/04 21:03:05 - mmengine - INFO - Epoch(train) [25][1760/2569] lr: 4.0000e-02 eta: 23:54:02 time: 0.2643 data_time: 0.0081 memory: 5828 grad_norm: 2.8982 loss: 2.5243 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5243 2023/06/04 21:03:10 - mmengine - INFO - Epoch(train) [25][1780/2569] lr: 4.0000e-02 eta: 23:53:56 time: 0.2616 data_time: 0.0080 memory: 5828 grad_norm: 2.9225 loss: 2.4309 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4309 2023/06/04 21:03:15 - mmengine - INFO - Epoch(train) [25][1800/2569] lr: 4.0000e-02 eta: 23:53:50 time: 0.2607 data_time: 0.0078 memory: 5828 grad_norm: 2.8917 loss: 2.5032 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5032 2023/06/04 21:03:21 - mmengine - INFO - Epoch(train) [25][1820/2569] lr: 4.0000e-02 eta: 23:53:44 time: 0.2651 data_time: 0.0078 memory: 5828 grad_norm: 2.9007 loss: 2.6774 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6774 2023/06/04 21:03:26 - mmengine - INFO - Epoch(train) [25][1840/2569] lr: 4.0000e-02 eta: 23:53:40 time: 0.2740 data_time: 0.0073 memory: 5828 grad_norm: 2.9561 loss: 2.5698 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5698 2023/06/04 21:03:31 - mmengine - INFO - Epoch(train) [25][1860/2569] lr: 4.0000e-02 eta: 23:53:34 time: 0.2669 data_time: 0.0082 memory: 5828 grad_norm: 2.9739 loss: 2.5406 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5406 2023/06/04 21:03:37 - mmengine - INFO - Epoch(train) [25][1880/2569] lr: 4.0000e-02 eta: 23:53:29 time: 0.2681 data_time: 0.0081 memory: 5828 grad_norm: 2.9072 loss: 2.6777 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6777 2023/06/04 21:03:42 - mmengine - INFO - Epoch(train) [25][1900/2569] lr: 4.0000e-02 eta: 23:53:23 time: 0.2629 data_time: 0.0080 memory: 5828 grad_norm: 2.9065 loss: 2.7721 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7721 2023/06/04 21:03:47 - mmengine - INFO - Epoch(train) [25][1920/2569] lr: 4.0000e-02 eta: 23:53:18 time: 0.2699 data_time: 0.0078 memory: 5828 grad_norm: 2.9181 loss: 2.7312 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7312 2023/06/04 21:03:53 - mmengine - INFO - Epoch(train) [25][1940/2569] lr: 4.0000e-02 eta: 23:53:12 time: 0.2604 data_time: 0.0080 memory: 5828 grad_norm: 2.9621 loss: 3.0137 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 3.0137 2023/06/04 21:03:58 - mmengine - INFO - Epoch(train) [25][1960/2569] lr: 4.0000e-02 eta: 23:53:07 time: 0.2691 data_time: 0.0082 memory: 5828 grad_norm: 2.9519 loss: 2.2422 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2422 2023/06/04 21:04:03 - mmengine - INFO - Epoch(train) [25][1980/2569] lr: 4.0000e-02 eta: 23:53:01 time: 0.2605 data_time: 0.0073 memory: 5828 grad_norm: 2.9412 loss: 2.5546 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5546 2023/06/04 21:04:09 - mmengine - INFO - Epoch(train) [25][2000/2569] lr: 4.0000e-02 eta: 23:52:56 time: 0.2701 data_time: 0.0080 memory: 5828 grad_norm: 2.8766 loss: 2.6882 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6882 2023/06/04 21:04:14 - mmengine - INFO - Epoch(train) [25][2020/2569] lr: 4.0000e-02 eta: 23:52:50 time: 0.2645 data_time: 0.0079 memory: 5828 grad_norm: 2.8589 loss: 2.4115 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4115 2023/06/04 21:04:19 - mmengine - INFO - Epoch(train) [25][2040/2569] lr: 4.0000e-02 eta: 23:52:45 time: 0.2716 data_time: 0.0078 memory: 5828 grad_norm: 2.9448 loss: 2.4774 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4774 2023/06/04 21:04:25 - mmengine - INFO - Epoch(train) [25][2060/2569] lr: 4.0000e-02 eta: 23:52:40 time: 0.2657 data_time: 0.0078 memory: 5828 grad_norm: 2.9226 loss: 2.7231 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7231 2023/06/04 21:04:30 - mmengine - INFO - Epoch(train) [25][2080/2569] lr: 4.0000e-02 eta: 23:52:36 time: 0.2776 data_time: 0.0080 memory: 5828 grad_norm: 2.9270 loss: 2.4024 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4024 2023/06/04 21:04:36 - mmengine - INFO - Epoch(train) [25][2100/2569] lr: 4.0000e-02 eta: 23:52:30 time: 0.2679 data_time: 0.0079 memory: 5828 grad_norm: 2.9050 loss: 2.5581 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5581 2023/06/04 21:04:41 - mmengine - INFO - Epoch(train) [25][2120/2569] lr: 4.0000e-02 eta: 23:52:25 time: 0.2680 data_time: 0.0082 memory: 5828 grad_norm: 2.8484 loss: 2.3601 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3601 2023/06/04 21:04:46 - mmengine - INFO - Epoch(train) [25][2140/2569] lr: 4.0000e-02 eta: 23:52:20 time: 0.2737 data_time: 0.0081 memory: 5828 grad_norm: 2.9583 loss: 2.0951 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0951 2023/06/04 21:04:52 - mmengine - INFO - Epoch(train) [25][2160/2569] lr: 4.0000e-02 eta: 23:52:14 time: 0.2616 data_time: 0.0081 memory: 5828 grad_norm: 2.9244 loss: 2.6494 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6494 2023/06/04 21:04:57 - mmengine - INFO - Epoch(train) [25][2180/2569] lr: 4.0000e-02 eta: 23:52:10 time: 0.2730 data_time: 0.0078 memory: 5828 grad_norm: 2.8657 loss: 2.4278 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4278 2023/06/04 21:05:02 - mmengine - INFO - Epoch(train) [25][2200/2569] lr: 4.0000e-02 eta: 23:52:04 time: 0.2603 data_time: 0.0078 memory: 5828 grad_norm: 3.0020 loss: 2.3545 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3545 2023/06/04 21:05:08 - mmengine - INFO - Epoch(train) [25][2220/2569] lr: 4.0000e-02 eta: 23:51:58 time: 0.2672 data_time: 0.0079 memory: 5828 grad_norm: 2.8972 loss: 2.6916 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.6916 2023/06/04 21:05:13 - mmengine - INFO - Epoch(train) [25][2240/2569] lr: 4.0000e-02 eta: 23:51:52 time: 0.2621 data_time: 0.0079 memory: 5828 grad_norm: 2.9278 loss: 2.8260 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8260 2023/06/04 21:05:18 - mmengine - INFO - Epoch(train) [25][2260/2569] lr: 4.0000e-02 eta: 23:51:48 time: 0.2733 data_time: 0.0077 memory: 5828 grad_norm: 2.9507 loss: 2.8521 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8521 2023/06/04 21:05:24 - mmengine - INFO - Epoch(train) [25][2280/2569] lr: 4.0000e-02 eta: 23:51:42 time: 0.2606 data_time: 0.0081 memory: 5828 grad_norm: 2.8808 loss: 2.6257 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6257 2023/06/04 21:05:29 - mmengine - INFO - Epoch(train) [25][2300/2569] lr: 4.0000e-02 eta: 23:51:37 time: 0.2775 data_time: 0.0081 memory: 5828 grad_norm: 2.9149 loss: 2.4161 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4161 2023/06/04 21:05:34 - mmengine - INFO - Epoch(train) [25][2320/2569] lr: 4.0000e-02 eta: 23:51:31 time: 0.2613 data_time: 0.0077 memory: 5828 grad_norm: 2.9303 loss: 2.3945 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3945 2023/06/04 21:05:40 - mmengine - INFO - Epoch(train) [25][2340/2569] lr: 4.0000e-02 eta: 23:51:27 time: 0.2738 data_time: 0.0077 memory: 5828 grad_norm: 2.9690 loss: 2.7189 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7189 2023/06/04 21:05:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:05:45 - mmengine - INFO - Epoch(train) [25][2360/2569] lr: 4.0000e-02 eta: 23:51:22 time: 0.2696 data_time: 0.0077 memory: 5828 grad_norm: 2.9322 loss: 2.6598 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6598 2023/06/04 21:05:51 - mmengine - INFO - Epoch(train) [25][2380/2569] lr: 4.0000e-02 eta: 23:51:16 time: 0.2662 data_time: 0.0075 memory: 5828 grad_norm: 2.9312 loss: 2.5844 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5844 2023/06/04 21:05:56 - mmengine - INFO - Epoch(train) [25][2400/2569] lr: 4.0000e-02 eta: 23:51:10 time: 0.2627 data_time: 0.0077 memory: 5828 grad_norm: 2.9359 loss: 2.6641 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6641 2023/06/04 21:06:01 - mmengine - INFO - Epoch(train) [25][2420/2569] lr: 4.0000e-02 eta: 23:51:06 time: 0.2719 data_time: 0.0078 memory: 5828 grad_norm: 2.9750 loss: 2.8254 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8254 2023/06/04 21:06:07 - mmengine - INFO - Epoch(train) [25][2440/2569] lr: 4.0000e-02 eta: 23:51:00 time: 0.2699 data_time: 0.0079 memory: 5828 grad_norm: 2.9447 loss: 2.5551 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5551 2023/06/04 21:06:12 - mmengine - INFO - Epoch(train) [25][2460/2569] lr: 4.0000e-02 eta: 23:50:55 time: 0.2701 data_time: 0.0076 memory: 5828 grad_norm: 2.9792 loss: 2.5771 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5771 2023/06/04 21:06:18 - mmengine - INFO - Epoch(train) [25][2480/2569] lr: 4.0000e-02 eta: 23:50:50 time: 0.2711 data_time: 0.0080 memory: 5828 grad_norm: 2.9808 loss: 2.4713 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4713 2023/06/04 21:06:23 - mmengine - INFO - Epoch(train) [25][2500/2569] lr: 4.0000e-02 eta: 23:50:45 time: 0.2616 data_time: 0.0076 memory: 5828 grad_norm: 2.9483 loss: 2.3622 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3622 2023/06/04 21:06:28 - mmengine - INFO - Epoch(train) [25][2520/2569] lr: 4.0000e-02 eta: 23:50:40 time: 0.2740 data_time: 0.0080 memory: 5828 grad_norm: 2.8853 loss: 2.8567 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8567 2023/06/04 21:06:34 - mmengine - INFO - Epoch(train) [25][2540/2569] lr: 4.0000e-02 eta: 23:50:35 time: 0.2677 data_time: 0.0079 memory: 5828 grad_norm: 2.9011 loss: 2.9763 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9763 2023/06/04 21:06:39 - mmengine - INFO - Epoch(train) [25][2560/2569] lr: 4.0000e-02 eta: 23:50:29 time: 0.2703 data_time: 0.0079 memory: 5828 grad_norm: 2.9271 loss: 2.7853 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7853 2023/06/04 21:06:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:06:41 - mmengine - INFO - Epoch(train) [25][2569/2569] lr: 4.0000e-02 eta: 23:50:27 time: 0.2663 data_time: 0.0079 memory: 5828 grad_norm: 2.9871 loss: 2.7124 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.7124 2023/06/04 21:06:45 - mmengine - INFO - Epoch(val) [25][ 20/260] eta: 0:00:44 time: 0.1866 data_time: 0.1278 memory: 1238 2023/06/04 21:06:48 - mmengine - INFO - Epoch(val) [25][ 40/260] eta: 0:00:37 time: 0.1539 data_time: 0.0955 memory: 1238 2023/06/04 21:06:51 - mmengine - INFO - Epoch(val) [25][ 60/260] eta: 0:00:33 time: 0.1552 data_time: 0.0968 memory: 1238 2023/06/04 21:06:54 - mmengine - INFO - Epoch(val) [25][ 80/260] eta: 0:00:27 time: 0.1106 data_time: 0.0522 memory: 1238 2023/06/04 21:06:57 - mmengine - INFO - Epoch(val) [25][100/260] eta: 0:00:24 time: 0.1565 data_time: 0.0981 memory: 1238 2023/06/04 21:06:59 - mmengine - INFO - Epoch(val) [25][120/260] eta: 0:00:20 time: 0.1290 data_time: 0.0705 memory: 1238 2023/06/04 21:07:02 - mmengine - INFO - Epoch(val) [25][140/260] eta: 0:00:17 time: 0.1374 data_time: 0.0786 memory: 1238 2023/06/04 21:07:05 - mmengine - INFO - Epoch(val) [25][160/260] eta: 0:00:14 time: 0.1483 data_time: 0.0902 memory: 1238 2023/06/04 21:07:08 - mmengine - INFO - Epoch(val) [25][180/260] eta: 0:00:11 time: 0.1493 data_time: 0.0909 memory: 1238 2023/06/04 21:07:11 - mmengine - INFO - Epoch(val) [25][200/260] eta: 0:00:08 time: 0.1369 data_time: 0.0786 memory: 1238 2023/06/04 21:07:13 - mmengine - INFO - Epoch(val) [25][220/260] eta: 0:00:05 time: 0.1316 data_time: 0.0730 memory: 1238 2023/06/04 21:07:16 - mmengine - INFO - Epoch(val) [25][240/260] eta: 0:00:02 time: 0.1214 data_time: 0.0630 memory: 1238 2023/06/04 21:07:18 - mmengine - INFO - Epoch(val) [25][260/260] eta: 0:00:00 time: 0.1367 data_time: 0.0794 memory: 1238 2023/06/04 21:07:26 - mmengine - INFO - Epoch(val) [25][260/260] acc/top1: 0.4907 acc/top5: 0.7371 acc/mean1: 0.4819 data_time: 0.0839 time: 0.1422 2023/06/04 21:07:26 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_15.pth is removed 2023/06/04 21:07:29 - mmengine - INFO - The best checkpoint with 0.4907 acc/top1 at 25 epoch is saved to best_acc_top1_epoch_25.pth. 2023/06/04 21:07:34 - mmengine - INFO - Epoch(train) [26][ 20/2569] lr: 4.0000e-02 eta: 23:50:24 time: 0.2904 data_time: 0.0422 memory: 5828 grad_norm: 2.9409 loss: 2.4583 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4583 2023/06/04 21:07:40 - mmengine - INFO - Epoch(train) [26][ 40/2569] lr: 4.0000e-02 eta: 23:50:18 time: 0.2678 data_time: 0.0074 memory: 5828 grad_norm: 2.9327 loss: 2.4971 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4971 2023/06/04 21:07:45 - mmengine - INFO - Epoch(train) [26][ 60/2569] lr: 4.0000e-02 eta: 23:50:13 time: 0.2716 data_time: 0.0078 memory: 5828 grad_norm: 2.9237 loss: 2.6224 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6224 2023/06/04 21:07:50 - mmengine - INFO - Epoch(train) [26][ 80/2569] lr: 4.0000e-02 eta: 23:50:08 time: 0.2637 data_time: 0.0079 memory: 5828 grad_norm: 2.9287 loss: 2.2633 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2633 2023/06/04 21:07:56 - mmengine - INFO - Epoch(train) [26][ 100/2569] lr: 4.0000e-02 eta: 23:50:03 time: 0.2723 data_time: 0.0079 memory: 5828 grad_norm: 2.9255 loss: 2.6825 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6825 2023/06/04 21:08:01 - mmengine - INFO - Epoch(train) [26][ 120/2569] lr: 4.0000e-02 eta: 23:49:58 time: 0.2739 data_time: 0.0077 memory: 5828 grad_norm: 2.9392 loss: 2.6119 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6119 2023/06/04 21:08:07 - mmengine - INFO - Epoch(train) [26][ 140/2569] lr: 4.0000e-02 eta: 23:49:52 time: 0.2606 data_time: 0.0078 memory: 5828 grad_norm: 2.9819 loss: 2.5478 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5478 2023/06/04 21:08:12 - mmengine - INFO - Epoch(train) [26][ 160/2569] lr: 4.0000e-02 eta: 23:49:46 time: 0.2603 data_time: 0.0079 memory: 5828 grad_norm: 2.9595 loss: 2.9525 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9525 2023/06/04 21:08:17 - mmengine - INFO - Epoch(train) [26][ 180/2569] lr: 4.0000e-02 eta: 23:49:40 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 2.9167 loss: 2.5552 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5552 2023/06/04 21:08:23 - mmengine - INFO - Epoch(train) [26][ 200/2569] lr: 4.0000e-02 eta: 23:49:36 time: 0.2762 data_time: 0.0080 memory: 5828 grad_norm: 2.9606 loss: 2.3931 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3931 2023/06/04 21:08:28 - mmengine - INFO - Epoch(train) [26][ 220/2569] lr: 4.0000e-02 eta: 23:49:31 time: 0.2700 data_time: 0.0082 memory: 5828 grad_norm: 2.9231 loss: 2.6644 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6644 2023/06/04 21:08:33 - mmengine - INFO - Epoch(train) [26][ 240/2569] lr: 4.0000e-02 eta: 23:49:25 time: 0.2624 data_time: 0.0080 memory: 5828 grad_norm: 2.9346 loss: 2.5380 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5380 2023/06/04 21:08:39 - mmengine - INFO - Epoch(train) [26][ 260/2569] lr: 4.0000e-02 eta: 23:49:20 time: 0.2720 data_time: 0.0078 memory: 5828 grad_norm: 2.9894 loss: 2.4150 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4150 2023/06/04 21:08:44 - mmengine - INFO - Epoch(train) [26][ 280/2569] lr: 4.0000e-02 eta: 23:49:15 time: 0.2715 data_time: 0.0078 memory: 5828 grad_norm: 2.8984 loss: 2.8146 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8146 2023/06/04 21:08:51 - mmengine - INFO - Epoch(train) [26][ 300/2569] lr: 4.0000e-02 eta: 23:49:17 time: 0.3405 data_time: 0.0075 memory: 5828 grad_norm: 2.9144 loss: 2.5681 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5681 2023/06/04 21:08:56 - mmengine - INFO - Epoch(train) [26][ 320/2569] lr: 4.0000e-02 eta: 23:49:11 time: 0.2640 data_time: 0.0078 memory: 5828 grad_norm: 2.9374 loss: 2.7775 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7775 2023/06/04 21:09:01 - mmengine - INFO - Epoch(train) [26][ 340/2569] lr: 4.0000e-02 eta: 23:49:05 time: 0.2630 data_time: 0.0077 memory: 5828 grad_norm: 2.9033 loss: 2.6776 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6776 2023/06/04 21:09:07 - mmengine - INFO - Epoch(train) [26][ 360/2569] lr: 4.0000e-02 eta: 23:49:00 time: 0.2629 data_time: 0.0080 memory: 5828 grad_norm: 2.8880 loss: 2.4796 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4796 2023/06/04 21:09:12 - mmengine - INFO - Epoch(train) [26][ 380/2569] lr: 4.0000e-02 eta: 23:48:54 time: 0.2650 data_time: 0.0080 memory: 5828 grad_norm: 2.9543 loss: 2.7030 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7030 2023/06/04 21:09:17 - mmengine - INFO - Epoch(train) [26][ 400/2569] lr: 4.0000e-02 eta: 23:48:48 time: 0.2601 data_time: 0.0075 memory: 5828 grad_norm: 2.9805 loss: 2.6624 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6624 2023/06/04 21:09:23 - mmengine - INFO - Epoch(train) [26][ 420/2569] lr: 4.0000e-02 eta: 23:48:43 time: 0.2674 data_time: 0.0076 memory: 5828 grad_norm: 2.9538 loss: 2.3705 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3705 2023/06/04 21:09:28 - mmengine - INFO - Epoch(train) [26][ 440/2569] lr: 4.0000e-02 eta: 23:48:37 time: 0.2615 data_time: 0.0077 memory: 5828 grad_norm: 2.9387 loss: 2.3910 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3910 2023/06/04 21:09:33 - mmengine - INFO - Epoch(train) [26][ 460/2569] lr: 4.0000e-02 eta: 23:48:31 time: 0.2651 data_time: 0.0076 memory: 5828 grad_norm: 2.9004 loss: 2.3272 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3272 2023/06/04 21:09:38 - mmengine - INFO - Epoch(train) [26][ 480/2569] lr: 4.0000e-02 eta: 23:48:25 time: 0.2625 data_time: 0.0080 memory: 5828 grad_norm: 3.0177 loss: 2.4348 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4348 2023/06/04 21:09:44 - mmengine - INFO - Epoch(train) [26][ 500/2569] lr: 4.0000e-02 eta: 23:48:20 time: 0.2696 data_time: 0.0074 memory: 5828 grad_norm: 2.9377 loss: 2.8915 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8915 2023/06/04 21:09:49 - mmengine - INFO - Epoch(train) [26][ 520/2569] lr: 4.0000e-02 eta: 23:48:15 time: 0.2724 data_time: 0.0079 memory: 5828 grad_norm: 2.8223 loss: 2.8046 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8046 2023/06/04 21:09:55 - mmengine - INFO - Epoch(train) [26][ 540/2569] lr: 4.0000e-02 eta: 23:48:10 time: 0.2688 data_time: 0.0079 memory: 5828 grad_norm: 2.9663 loss: 2.2514 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2514 2023/06/04 21:10:00 - mmengine - INFO - Epoch(train) [26][ 560/2569] lr: 4.0000e-02 eta: 23:48:06 time: 0.2777 data_time: 0.0081 memory: 5828 grad_norm: 2.9346 loss: 2.5961 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5961 2023/06/04 21:10:06 - mmengine - INFO - Epoch(train) [26][ 580/2569] lr: 4.0000e-02 eta: 23:48:02 time: 0.2781 data_time: 0.0080 memory: 5828 grad_norm: 3.0033 loss: 2.7768 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7768 2023/06/04 21:10:11 - mmengine - INFO - Epoch(train) [26][ 600/2569] lr: 4.0000e-02 eta: 23:47:57 time: 0.2765 data_time: 0.0073 memory: 5828 grad_norm: 2.9951 loss: 2.4768 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4768 2023/06/04 21:10:16 - mmengine - INFO - Epoch(train) [26][ 620/2569] lr: 4.0000e-02 eta: 23:47:51 time: 0.2618 data_time: 0.0080 memory: 5828 grad_norm: 2.9327 loss: 2.6284 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6284 2023/06/04 21:10:22 - mmengine - INFO - Epoch(train) [26][ 640/2569] lr: 4.0000e-02 eta: 23:47:46 time: 0.2699 data_time: 0.0074 memory: 5828 grad_norm: 2.9514 loss: 2.5635 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5635 2023/06/04 21:10:27 - mmengine - INFO - Epoch(train) [26][ 660/2569] lr: 4.0000e-02 eta: 23:47:41 time: 0.2669 data_time: 0.0082 memory: 5828 grad_norm: 2.9437 loss: 2.6000 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6000 2023/06/04 21:10:33 - mmengine - INFO - Epoch(train) [26][ 680/2569] lr: 4.0000e-02 eta: 23:47:35 time: 0.2665 data_time: 0.0077 memory: 5828 grad_norm: 2.9395 loss: 2.6450 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6450 2023/06/04 21:10:38 - mmengine - INFO - Epoch(train) [26][ 700/2569] lr: 4.0000e-02 eta: 23:47:30 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 2.9113 loss: 2.2848 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2848 2023/06/04 21:10:43 - mmengine - INFO - Epoch(train) [26][ 720/2569] lr: 4.0000e-02 eta: 23:47:25 time: 0.2666 data_time: 0.0079 memory: 5828 grad_norm: 2.9125 loss: 2.5044 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5044 2023/06/04 21:10:49 - mmengine - INFO - Epoch(train) [26][ 740/2569] lr: 4.0000e-02 eta: 23:47:20 time: 0.2724 data_time: 0.0074 memory: 5828 grad_norm: 2.8637 loss: 2.3939 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3939 2023/06/04 21:10:54 - mmengine - INFO - Epoch(train) [26][ 760/2569] lr: 4.0000e-02 eta: 23:47:14 time: 0.2613 data_time: 0.0085 memory: 5828 grad_norm: 2.9435 loss: 2.3803 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3803 2023/06/04 21:10:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:10:59 - mmengine - INFO - Epoch(train) [26][ 780/2569] lr: 4.0000e-02 eta: 23:47:09 time: 0.2731 data_time: 0.0077 memory: 5828 grad_norm: 2.9115 loss: 2.4581 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4581 2023/06/04 21:11:05 - mmengine - INFO - Epoch(train) [26][ 800/2569] lr: 4.0000e-02 eta: 23:47:03 time: 0.2613 data_time: 0.0082 memory: 5828 grad_norm: 2.9668 loss: 2.5542 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5542 2023/06/04 21:11:10 - mmengine - INFO - Epoch(train) [26][ 820/2569] lr: 4.0000e-02 eta: 23:46:58 time: 0.2686 data_time: 0.0101 memory: 5828 grad_norm: 2.9085 loss: 2.6289 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6289 2023/06/04 21:11:15 - mmengine - INFO - Epoch(train) [26][ 840/2569] lr: 4.0000e-02 eta: 23:46:53 time: 0.2667 data_time: 0.0079 memory: 5828 grad_norm: 3.0158 loss: 2.7874 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.7874 2023/06/04 21:11:21 - mmengine - INFO - Epoch(train) [26][ 860/2569] lr: 4.0000e-02 eta: 23:46:47 time: 0.2641 data_time: 0.0076 memory: 5828 grad_norm: 2.9917 loss: 2.5255 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5255 2023/06/04 21:11:26 - mmengine - INFO - Epoch(train) [26][ 880/2569] lr: 4.0000e-02 eta: 23:46:42 time: 0.2693 data_time: 0.0084 memory: 5828 grad_norm: 2.9447 loss: 2.6406 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6406 2023/06/04 21:11:31 - mmengine - INFO - Epoch(train) [26][ 900/2569] lr: 4.0000e-02 eta: 23:46:36 time: 0.2632 data_time: 0.0081 memory: 5828 grad_norm: 2.9122 loss: 2.5972 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5972 2023/06/04 21:11:37 - mmengine - INFO - Epoch(train) [26][ 920/2569] lr: 4.0000e-02 eta: 23:46:30 time: 0.2624 data_time: 0.0080 memory: 5828 grad_norm: 2.9823 loss: 2.5454 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5454 2023/06/04 21:11:42 - mmengine - INFO - Epoch(train) [26][ 940/2569] lr: 4.0000e-02 eta: 23:46:25 time: 0.2672 data_time: 0.0076 memory: 5828 grad_norm: 2.9251 loss: 2.5339 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5339 2023/06/04 21:11:47 - mmengine - INFO - Epoch(train) [26][ 960/2569] lr: 4.0000e-02 eta: 23:46:20 time: 0.2672 data_time: 0.0081 memory: 5828 grad_norm: 2.9179 loss: 2.3607 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3607 2023/06/04 21:11:53 - mmengine - INFO - Epoch(train) [26][ 980/2569] lr: 4.0000e-02 eta: 23:46:14 time: 0.2667 data_time: 0.0082 memory: 5828 grad_norm: 3.0528 loss: 2.5035 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5035 2023/06/04 21:11:58 - mmengine - INFO - Epoch(train) [26][1000/2569] lr: 4.0000e-02 eta: 23:46:09 time: 0.2656 data_time: 0.0080 memory: 5828 grad_norm: 2.9026 loss: 2.6225 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6225 2023/06/04 21:12:03 - mmengine - INFO - Epoch(train) [26][1020/2569] lr: 4.0000e-02 eta: 23:46:03 time: 0.2685 data_time: 0.0079 memory: 5828 grad_norm: 2.9256 loss: 2.6357 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6357 2023/06/04 21:12:08 - mmengine - INFO - Epoch(train) [26][1040/2569] lr: 4.0000e-02 eta: 23:45:58 time: 0.2619 data_time: 0.0081 memory: 5828 grad_norm: 2.9110 loss: 2.6655 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6655 2023/06/04 21:12:14 - mmengine - INFO - Epoch(train) [26][1060/2569] lr: 4.0000e-02 eta: 23:45:52 time: 0.2619 data_time: 0.0079 memory: 5828 grad_norm: 2.9144 loss: 2.7520 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7520 2023/06/04 21:12:19 - mmengine - INFO - Epoch(train) [26][1080/2569] lr: 4.0000e-02 eta: 23:45:47 time: 0.2706 data_time: 0.0075 memory: 5828 grad_norm: 2.8719 loss: 2.5152 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5152 2023/06/04 21:12:24 - mmengine - INFO - Epoch(train) [26][1100/2569] lr: 4.0000e-02 eta: 23:45:41 time: 0.2606 data_time: 0.0080 memory: 5828 grad_norm: 2.8913 loss: 2.4728 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4728 2023/06/04 21:12:30 - mmengine - INFO - Epoch(train) [26][1120/2569] lr: 4.0000e-02 eta: 23:45:35 time: 0.2615 data_time: 0.0085 memory: 5828 grad_norm: 2.8536 loss: 2.3308 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3308 2023/06/04 21:12:35 - mmengine - INFO - Epoch(train) [26][1140/2569] lr: 4.0000e-02 eta: 23:45:29 time: 0.2625 data_time: 0.0081 memory: 5828 grad_norm: 2.9691 loss: 2.5576 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5576 2023/06/04 21:12:40 - mmengine - INFO - Epoch(train) [26][1160/2569] lr: 4.0000e-02 eta: 23:45:24 time: 0.2674 data_time: 0.0078 memory: 5828 grad_norm: 2.9551 loss: 2.4511 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4511 2023/06/04 21:12:46 - mmengine - INFO - Epoch(train) [26][1180/2569] lr: 4.0000e-02 eta: 23:45:18 time: 0.2694 data_time: 0.0075 memory: 5828 grad_norm: 2.9537 loss: 2.5154 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5154 2023/06/04 21:12:51 - mmengine - INFO - Epoch(train) [26][1200/2569] lr: 4.0000e-02 eta: 23:45:13 time: 0.2664 data_time: 0.0081 memory: 5828 grad_norm: 2.9982 loss: 2.9345 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9345 2023/06/04 21:12:56 - mmengine - INFO - Epoch(train) [26][1220/2569] lr: 4.0000e-02 eta: 23:45:08 time: 0.2718 data_time: 0.0079 memory: 5828 grad_norm: 2.9291 loss: 2.8865 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8865 2023/06/04 21:13:02 - mmengine - INFO - Epoch(train) [26][1240/2569] lr: 4.0000e-02 eta: 23:45:03 time: 0.2664 data_time: 0.0078 memory: 5828 grad_norm: 3.0214 loss: 2.5163 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5163 2023/06/04 21:13:07 - mmengine - INFO - Epoch(train) [26][1260/2569] lr: 4.0000e-02 eta: 23:44:58 time: 0.2712 data_time: 0.0080 memory: 5828 grad_norm: 2.9770 loss: 2.4003 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4003 2023/06/04 21:13:12 - mmengine - INFO - Epoch(train) [26][1280/2569] lr: 4.0000e-02 eta: 23:44:52 time: 0.2678 data_time: 0.0078 memory: 5828 grad_norm: 2.9210 loss: 2.7132 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.7132 2023/06/04 21:13:18 - mmengine - INFO - Epoch(train) [26][1300/2569] lr: 4.0000e-02 eta: 23:44:49 time: 0.2825 data_time: 0.0081 memory: 5828 grad_norm: 2.9676 loss: 2.3454 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3454 2023/06/04 21:13:24 - mmengine - INFO - Epoch(train) [26][1320/2569] lr: 4.0000e-02 eta: 23:44:45 time: 0.2837 data_time: 0.0076 memory: 5828 grad_norm: 2.9518 loss: 2.3508 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3508 2023/06/04 21:13:29 - mmengine - INFO - Epoch(train) [26][1340/2569] lr: 4.0000e-02 eta: 23:44:40 time: 0.2734 data_time: 0.0077 memory: 5828 grad_norm: 3.0007 loss: 2.8222 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8222 2023/06/04 21:13:35 - mmengine - INFO - Epoch(train) [26][1360/2569] lr: 4.0000e-02 eta: 23:44:36 time: 0.2762 data_time: 0.0080 memory: 5828 grad_norm: 2.9301 loss: 2.6372 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6372 2023/06/04 21:13:40 - mmengine - INFO - Epoch(train) [26][1380/2569] lr: 4.0000e-02 eta: 23:44:31 time: 0.2722 data_time: 0.0075 memory: 5828 grad_norm: 2.9413 loss: 2.8593 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8593 2023/06/04 21:13:45 - mmengine - INFO - Epoch(train) [26][1400/2569] lr: 4.0000e-02 eta: 23:44:25 time: 0.2610 data_time: 0.0076 memory: 5828 grad_norm: 2.9689 loss: 2.2987 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2987 2023/06/04 21:13:51 - mmengine - INFO - Epoch(train) [26][1420/2569] lr: 4.0000e-02 eta: 23:44:19 time: 0.2664 data_time: 0.0075 memory: 5828 grad_norm: 2.9787 loss: 2.7836 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7836 2023/06/04 21:13:56 - mmengine - INFO - Epoch(train) [26][1440/2569] lr: 4.0000e-02 eta: 23:44:14 time: 0.2665 data_time: 0.0082 memory: 5828 grad_norm: 2.9634 loss: 2.4383 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4383 2023/06/04 21:14:02 - mmengine - INFO - Epoch(train) [26][1460/2569] lr: 4.0000e-02 eta: 23:44:11 time: 0.2919 data_time: 0.0079 memory: 5828 grad_norm: 2.9984 loss: 2.8462 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.8462 2023/06/04 21:14:07 - mmengine - INFO - Epoch(train) [26][1480/2569] lr: 4.0000e-02 eta: 23:44:05 time: 0.2652 data_time: 0.0078 memory: 5828 grad_norm: 2.9712 loss: 2.7094 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7094 2023/06/04 21:14:13 - mmengine - INFO - Epoch(train) [26][1500/2569] lr: 4.0000e-02 eta: 23:44:01 time: 0.2824 data_time: 0.0078 memory: 5828 grad_norm: 2.9095 loss: 2.3538 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3538 2023/06/04 21:14:18 - mmengine - INFO - Epoch(train) [26][1520/2569] lr: 4.0000e-02 eta: 23:43:56 time: 0.2644 data_time: 0.0082 memory: 5828 grad_norm: 2.9448 loss: 2.5939 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5939 2023/06/04 21:14:24 - mmengine - INFO - Epoch(train) [26][1540/2569] lr: 4.0000e-02 eta: 23:43:51 time: 0.2697 data_time: 0.0078 memory: 5828 grad_norm: 2.9473 loss: 2.3728 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3728 2023/06/04 21:14:29 - mmengine - INFO - Epoch(train) [26][1560/2569] lr: 4.0000e-02 eta: 23:43:46 time: 0.2684 data_time: 0.0078 memory: 5828 grad_norm: 2.9438 loss: 2.8806 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8806 2023/06/04 21:14:34 - mmengine - INFO - Epoch(train) [26][1580/2569] lr: 4.0000e-02 eta: 23:43:39 time: 0.2597 data_time: 0.0076 memory: 5828 grad_norm: 2.9764 loss: 2.8259 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8259 2023/06/04 21:14:40 - mmengine - INFO - Epoch(train) [26][1600/2569] lr: 4.0000e-02 eta: 23:43:34 time: 0.2673 data_time: 0.0081 memory: 5828 grad_norm: 2.8659 loss: 2.3388 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3388 2023/06/04 21:14:45 - mmengine - INFO - Epoch(train) [26][1620/2569] lr: 4.0000e-02 eta: 23:43:29 time: 0.2670 data_time: 0.0077 memory: 5828 grad_norm: 2.9454 loss: 2.7476 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7476 2023/06/04 21:14:50 - mmengine - INFO - Epoch(train) [26][1640/2569] lr: 4.0000e-02 eta: 23:43:23 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 2.9213 loss: 2.7204 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7204 2023/06/04 21:14:56 - mmengine - INFO - Epoch(train) [26][1660/2569] lr: 4.0000e-02 eta: 23:43:19 time: 0.2720 data_time: 0.0081 memory: 5828 grad_norm: 2.9549 loss: 2.9034 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9034 2023/06/04 21:15:01 - mmengine - INFO - Epoch(train) [26][1680/2569] lr: 4.0000e-02 eta: 23:43:13 time: 0.2677 data_time: 0.0078 memory: 5828 grad_norm: 3.0159 loss: 2.7789 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7789 2023/06/04 21:15:06 - mmengine - INFO - Epoch(train) [26][1700/2569] lr: 4.0000e-02 eta: 23:43:08 time: 0.2659 data_time: 0.0078 memory: 5828 grad_norm: 2.9171 loss: 2.6710 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6710 2023/06/04 21:15:12 - mmengine - INFO - Epoch(train) [26][1720/2569] lr: 4.0000e-02 eta: 23:43:03 time: 0.2721 data_time: 0.0078 memory: 5828 grad_norm: 2.9047 loss: 2.5881 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5881 2023/06/04 21:15:17 - mmengine - INFO - Epoch(train) [26][1740/2569] lr: 4.0000e-02 eta: 23:42:57 time: 0.2618 data_time: 0.0077 memory: 5828 grad_norm: 2.9351 loss: 2.7279 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7279 2023/06/04 21:15:23 - mmengine - INFO - Epoch(train) [26][1760/2569] lr: 4.0000e-02 eta: 23:42:52 time: 0.2747 data_time: 0.0080 memory: 5828 grad_norm: 2.9648 loss: 2.3996 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3996 2023/06/04 21:15:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:15:28 - mmengine - INFO - Epoch(train) [26][1780/2569] lr: 4.0000e-02 eta: 23:42:47 time: 0.2662 data_time: 0.0079 memory: 5828 grad_norm: 2.9330 loss: 2.8757 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.8757 2023/06/04 21:15:33 - mmengine - INFO - Epoch(train) [26][1800/2569] lr: 4.0000e-02 eta: 23:42:42 time: 0.2682 data_time: 0.0072 memory: 5828 grad_norm: 2.9348 loss: 2.4781 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4781 2023/06/04 21:15:39 - mmengine - INFO - Epoch(train) [26][1820/2569] lr: 4.0000e-02 eta: 23:42:36 time: 0.2652 data_time: 0.0079 memory: 5828 grad_norm: 3.0102 loss: 2.6117 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6117 2023/06/04 21:15:44 - mmengine - INFO - Epoch(train) [26][1840/2569] lr: 4.0000e-02 eta: 23:42:31 time: 0.2713 data_time: 0.0084 memory: 5828 grad_norm: 2.9172 loss: 2.6998 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6998 2023/06/04 21:15:49 - mmengine - INFO - Epoch(train) [26][1860/2569] lr: 4.0000e-02 eta: 23:42:25 time: 0.2632 data_time: 0.0079 memory: 5828 grad_norm: 2.9584 loss: 2.6597 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6597 2023/06/04 21:15:55 - mmengine - INFO - Epoch(train) [26][1880/2569] lr: 4.0000e-02 eta: 23:42:20 time: 0.2718 data_time: 0.0082 memory: 5828 grad_norm: 2.9135 loss: 2.3222 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3222 2023/06/04 21:16:00 - mmengine - INFO - Epoch(train) [26][1900/2569] lr: 4.0000e-02 eta: 23:42:16 time: 0.2749 data_time: 0.0076 memory: 5828 grad_norm: 2.9286 loss: 2.4353 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4353 2023/06/04 21:16:05 - mmengine - INFO - Epoch(train) [26][1920/2569] lr: 4.0000e-02 eta: 23:42:10 time: 0.2608 data_time: 0.0081 memory: 5828 grad_norm: 2.9075 loss: 2.6157 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6157 2023/06/04 21:16:11 - mmengine - INFO - Epoch(train) [26][1940/2569] lr: 4.0000e-02 eta: 23:42:05 time: 0.2765 data_time: 0.0079 memory: 5828 grad_norm: 2.9686 loss: 2.6455 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6455 2023/06/04 21:16:16 - mmengine - INFO - Epoch(train) [26][1960/2569] lr: 4.0000e-02 eta: 23:42:00 time: 0.2631 data_time: 0.0080 memory: 5828 grad_norm: 2.9426 loss: 2.4866 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4866 2023/06/04 21:16:22 - mmengine - INFO - Epoch(train) [26][1980/2569] lr: 4.0000e-02 eta: 23:41:55 time: 0.2704 data_time: 0.0076 memory: 5828 grad_norm: 2.9377 loss: 2.6923 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6923 2023/06/04 21:16:27 - mmengine - INFO - Epoch(train) [26][2000/2569] lr: 4.0000e-02 eta: 23:41:49 time: 0.2608 data_time: 0.0083 memory: 5828 grad_norm: 2.8943 loss: 2.6663 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6663 2023/06/04 21:16:32 - mmengine - INFO - Epoch(train) [26][2020/2569] lr: 4.0000e-02 eta: 23:41:43 time: 0.2638 data_time: 0.0079 memory: 5828 grad_norm: 2.9607 loss: 2.8181 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8181 2023/06/04 21:16:37 - mmengine - INFO - Epoch(train) [26][2040/2569] lr: 4.0000e-02 eta: 23:41:37 time: 0.2639 data_time: 0.0078 memory: 5828 grad_norm: 2.8782 loss: 2.3554 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3554 2023/06/04 21:16:43 - mmengine - INFO - Epoch(train) [26][2060/2569] lr: 4.0000e-02 eta: 23:41:32 time: 0.2700 data_time: 0.0080 memory: 5828 grad_norm: 2.8914 loss: 2.3667 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3667 2023/06/04 21:16:48 - mmengine - INFO - Epoch(train) [26][2080/2569] lr: 4.0000e-02 eta: 23:41:27 time: 0.2692 data_time: 0.0081 memory: 5828 grad_norm: 2.9143 loss: 2.3948 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3948 2023/06/04 21:16:53 - mmengine - INFO - Epoch(train) [26][2100/2569] lr: 4.0000e-02 eta: 23:41:21 time: 0.2619 data_time: 0.0081 memory: 5828 grad_norm: 2.9122 loss: 2.8346 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8346 2023/06/04 21:16:59 - mmengine - INFO - Epoch(train) [26][2120/2569] lr: 4.0000e-02 eta: 23:41:16 time: 0.2716 data_time: 0.0079 memory: 5828 grad_norm: 2.9138 loss: 2.9070 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9070 2023/06/04 21:17:04 - mmengine - INFO - Epoch(train) [26][2140/2569] lr: 4.0000e-02 eta: 23:41:10 time: 0.2618 data_time: 0.0080 memory: 5828 grad_norm: 2.9353 loss: 2.5917 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5917 2023/06/04 21:17:09 - mmengine - INFO - Epoch(train) [26][2160/2569] lr: 4.0000e-02 eta: 23:41:05 time: 0.2678 data_time: 0.0078 memory: 5828 grad_norm: 2.9819 loss: 2.3643 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3643 2023/06/04 21:17:15 - mmengine - INFO - Epoch(train) [26][2180/2569] lr: 4.0000e-02 eta: 23:40:59 time: 0.2621 data_time: 0.0079 memory: 5828 grad_norm: 2.9461 loss: 2.4258 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4258 2023/06/04 21:17:20 - mmengine - INFO - Epoch(train) [26][2200/2569] lr: 4.0000e-02 eta: 23:40:54 time: 0.2669 data_time: 0.0078 memory: 5828 grad_norm: 2.9395 loss: 2.7083 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7083 2023/06/04 21:17:25 - mmengine - INFO - Epoch(train) [26][2220/2569] lr: 4.0000e-02 eta: 23:40:48 time: 0.2622 data_time: 0.0081 memory: 5828 grad_norm: 2.9637 loss: 2.6899 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6899 2023/06/04 21:17:30 - mmengine - INFO - Epoch(train) [26][2240/2569] lr: 4.0000e-02 eta: 23:40:42 time: 0.2613 data_time: 0.0078 memory: 5828 grad_norm: 2.9799 loss: 2.6266 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6266 2023/06/04 21:17:36 - mmengine - INFO - Epoch(train) [26][2260/2569] lr: 4.0000e-02 eta: 23:40:36 time: 0.2615 data_time: 0.0078 memory: 5828 grad_norm: 2.9325 loss: 2.1886 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1886 2023/06/04 21:17:41 - mmengine - INFO - Epoch(train) [26][2280/2569] lr: 4.0000e-02 eta: 23:40:31 time: 0.2686 data_time: 0.0078 memory: 5828 grad_norm: 2.8999 loss: 2.7488 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7488 2023/06/04 21:17:46 - mmengine - INFO - Epoch(train) [26][2300/2569] lr: 4.0000e-02 eta: 23:40:25 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 3.0195 loss: 2.5110 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5110 2023/06/04 21:17:52 - mmengine - INFO - Epoch(train) [26][2320/2569] lr: 4.0000e-02 eta: 23:40:19 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 2.9615 loss: 2.8532 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8532 2023/06/04 21:17:57 - mmengine - INFO - Epoch(train) [26][2340/2569] lr: 4.0000e-02 eta: 23:40:14 time: 0.2673 data_time: 0.0083 memory: 5828 grad_norm: 2.9189 loss: 2.2978 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2978 2023/06/04 21:18:02 - mmengine - INFO - Epoch(train) [26][2360/2569] lr: 4.0000e-02 eta: 23:40:08 time: 0.2615 data_time: 0.0079 memory: 5828 grad_norm: 2.8917 loss: 2.8421 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8421 2023/06/04 21:18:08 - mmengine - INFO - Epoch(train) [26][2380/2569] lr: 4.0000e-02 eta: 23:40:03 time: 0.2747 data_time: 0.0073 memory: 5828 grad_norm: 2.9357 loss: 2.3440 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3440 2023/06/04 21:18:13 - mmengine - INFO - Epoch(train) [26][2400/2569] lr: 4.0000e-02 eta: 23:39:57 time: 0.2626 data_time: 0.0075 memory: 5828 grad_norm: 2.9988 loss: 2.7283 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7283 2023/06/04 21:18:18 - mmengine - INFO - Epoch(train) [26][2420/2569] lr: 4.0000e-02 eta: 23:39:52 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 2.9427 loss: 2.4619 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4619 2023/06/04 21:18:24 - mmengine - INFO - Epoch(train) [26][2440/2569] lr: 4.0000e-02 eta: 23:39:47 time: 0.2731 data_time: 0.0075 memory: 5828 grad_norm: 2.9214 loss: 2.7505 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7505 2023/06/04 21:18:29 - mmengine - INFO - Epoch(train) [26][2460/2569] lr: 4.0000e-02 eta: 23:39:42 time: 0.2699 data_time: 0.0076 memory: 5828 grad_norm: 2.9146 loss: 2.6499 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6499 2023/06/04 21:18:34 - mmengine - INFO - Epoch(train) [26][2480/2569] lr: 4.0000e-02 eta: 23:39:37 time: 0.2653 data_time: 0.0083 memory: 5828 grad_norm: 2.9228 loss: 2.6815 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6815 2023/06/04 21:18:40 - mmengine - INFO - Epoch(train) [26][2500/2569] lr: 4.0000e-02 eta: 23:39:32 time: 0.2727 data_time: 0.0078 memory: 5828 grad_norm: 2.9631 loss: 2.4453 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4453 2023/06/04 21:18:45 - mmengine - INFO - Epoch(train) [26][2520/2569] lr: 4.0000e-02 eta: 23:39:26 time: 0.2620 data_time: 0.0084 memory: 5828 grad_norm: 2.9209 loss: 2.6570 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6570 2023/06/04 21:18:51 - mmengine - INFO - Epoch(train) [26][2540/2569] lr: 4.0000e-02 eta: 23:39:23 time: 0.2886 data_time: 0.0074 memory: 5828 grad_norm: 2.9739 loss: 2.5438 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5438 2023/06/04 21:18:56 - mmengine - INFO - Epoch(train) [26][2560/2569] lr: 4.0000e-02 eta: 23:39:17 time: 0.2597 data_time: 0.0080 memory: 5828 grad_norm: 3.0207 loss: 2.9692 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9692 2023/06/04 21:18:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:18:58 - mmengine - INFO - Epoch(train) [26][2569/2569] lr: 4.0000e-02 eta: 23:39:13 time: 0.2542 data_time: 0.0078 memory: 5828 grad_norm: 3.0087 loss: 2.7617 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.7617 2023/06/04 21:19:05 - mmengine - INFO - Epoch(train) [27][ 20/2569] lr: 4.0000e-02 eta: 23:39:15 time: 0.3369 data_time: 0.0560 memory: 5828 grad_norm: 2.9272 loss: 2.5148 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5148 2023/06/04 21:19:11 - mmengine - INFO - Epoch(train) [27][ 40/2569] lr: 4.0000e-02 eta: 23:39:10 time: 0.2725 data_time: 0.0081 memory: 5828 grad_norm: 2.8951 loss: 2.7564 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7564 2023/06/04 21:19:16 - mmengine - INFO - Epoch(train) [27][ 60/2569] lr: 4.0000e-02 eta: 23:39:04 time: 0.2621 data_time: 0.0078 memory: 5828 grad_norm: 2.9473 loss: 2.8046 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8046 2023/06/04 21:19:21 - mmengine - INFO - Epoch(train) [27][ 80/2569] lr: 4.0000e-02 eta: 23:38:58 time: 0.2668 data_time: 0.0084 memory: 5828 grad_norm: 2.9700 loss: 2.7210 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7210 2023/06/04 21:19:26 - mmengine - INFO - Epoch(train) [27][ 100/2569] lr: 4.0000e-02 eta: 23:38:53 time: 0.2663 data_time: 0.0080 memory: 5828 grad_norm: 2.9771 loss: 2.6943 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6943 2023/06/04 21:19:32 - mmengine - INFO - Epoch(train) [27][ 120/2569] lr: 4.0000e-02 eta: 23:38:47 time: 0.2602 data_time: 0.0080 memory: 5828 grad_norm: 2.9781 loss: 2.7304 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7304 2023/06/04 21:19:37 - mmengine - INFO - Epoch(train) [27][ 140/2569] lr: 4.0000e-02 eta: 23:38:41 time: 0.2614 data_time: 0.0083 memory: 5828 grad_norm: 2.9131 loss: 2.8876 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8876 2023/06/04 21:19:42 - mmengine - INFO - Epoch(train) [27][ 160/2569] lr: 4.0000e-02 eta: 23:38:35 time: 0.2617 data_time: 0.0077 memory: 5828 grad_norm: 2.9764 loss: 2.6196 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6196 2023/06/04 21:19:47 - mmengine - INFO - Epoch(train) [27][ 180/2569] lr: 4.0000e-02 eta: 23:38:30 time: 0.2682 data_time: 0.0082 memory: 5828 grad_norm: 2.9311 loss: 2.6884 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6884 2023/06/04 21:19:53 - mmengine - INFO - Epoch(train) [27][ 200/2569] lr: 4.0000e-02 eta: 23:38:25 time: 0.2716 data_time: 0.0075 memory: 5828 grad_norm: 3.0161 loss: 3.0508 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0508 2023/06/04 21:19:54 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:19:58 - mmengine - INFO - Epoch(train) [27][ 220/2569] lr: 4.0000e-02 eta: 23:38:20 time: 0.2693 data_time: 0.0077 memory: 5828 grad_norm: 2.8699 loss: 2.5503 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5503 2023/06/04 21:20:04 - mmengine - INFO - Epoch(train) [27][ 240/2569] lr: 4.0000e-02 eta: 23:38:14 time: 0.2651 data_time: 0.0077 memory: 5828 grad_norm: 2.9899 loss: 2.7330 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7330 2023/06/04 21:20:09 - mmengine - INFO - Epoch(train) [27][ 260/2569] lr: 4.0000e-02 eta: 23:38:09 time: 0.2664 data_time: 0.0080 memory: 5828 grad_norm: 2.9442 loss: 2.4453 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4453 2023/06/04 21:20:14 - mmengine - INFO - Epoch(train) [27][ 280/2569] lr: 4.0000e-02 eta: 23:38:04 time: 0.2688 data_time: 0.0077 memory: 5828 grad_norm: 2.9708 loss: 2.4376 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4376 2023/06/04 21:20:20 - mmengine - INFO - Epoch(train) [27][ 300/2569] lr: 4.0000e-02 eta: 23:37:59 time: 0.2755 data_time: 0.0084 memory: 5828 grad_norm: 2.9318 loss: 2.7297 top1_acc: 0.1250 top5_acc: 1.0000 loss_cls: 2.7297 2023/06/04 21:20:25 - mmengine - INFO - Epoch(train) [27][ 320/2569] lr: 4.0000e-02 eta: 23:37:54 time: 0.2743 data_time: 0.0082 memory: 5828 grad_norm: 2.9533 loss: 2.5400 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5400 2023/06/04 21:20:31 - mmengine - INFO - Epoch(train) [27][ 340/2569] lr: 4.0000e-02 eta: 23:37:50 time: 0.2786 data_time: 0.0076 memory: 5828 grad_norm: 2.9151 loss: 2.7499 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7499 2023/06/04 21:20:36 - mmengine - INFO - Epoch(train) [27][ 360/2569] lr: 4.0000e-02 eta: 23:37:44 time: 0.2621 data_time: 0.0079 memory: 5828 grad_norm: 2.9619 loss: 2.7807 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7807 2023/06/04 21:20:42 - mmengine - INFO - Epoch(train) [27][ 380/2569] lr: 4.0000e-02 eta: 23:37:39 time: 0.2694 data_time: 0.0081 memory: 5828 grad_norm: 2.9870 loss: 2.6694 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6694 2023/06/04 21:20:47 - mmengine - INFO - Epoch(train) [27][ 400/2569] lr: 4.0000e-02 eta: 23:37:34 time: 0.2658 data_time: 0.0080 memory: 5828 grad_norm: 2.9949 loss: 2.5431 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5431 2023/06/04 21:20:52 - mmengine - INFO - Epoch(train) [27][ 420/2569] lr: 4.0000e-02 eta: 23:37:29 time: 0.2723 data_time: 0.0078 memory: 5828 grad_norm: 2.9350 loss: 2.3507 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3507 2023/06/04 21:20:58 - mmengine - INFO - Epoch(train) [27][ 440/2569] lr: 4.0000e-02 eta: 23:37:23 time: 0.2667 data_time: 0.0079 memory: 5828 grad_norm: 2.9013 loss: 2.4944 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4944 2023/06/04 21:21:03 - mmengine - INFO - Epoch(train) [27][ 460/2569] lr: 4.0000e-02 eta: 23:37:18 time: 0.2705 data_time: 0.0078 memory: 5828 grad_norm: 2.9579 loss: 2.7549 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7549 2023/06/04 21:21:08 - mmengine - INFO - Epoch(train) [27][ 480/2569] lr: 4.0000e-02 eta: 23:37:12 time: 0.2620 data_time: 0.0076 memory: 5828 grad_norm: 2.9104 loss: 2.5302 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5302 2023/06/04 21:21:14 - mmengine - INFO - Epoch(train) [27][ 500/2569] lr: 4.0000e-02 eta: 23:37:07 time: 0.2663 data_time: 0.0078 memory: 5828 grad_norm: 2.9806 loss: 2.7600 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7600 2023/06/04 21:21:19 - mmengine - INFO - Epoch(train) [27][ 520/2569] lr: 4.0000e-02 eta: 23:37:01 time: 0.2633 data_time: 0.0082 memory: 5828 grad_norm: 2.9872 loss: 2.7270 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7270 2023/06/04 21:21:24 - mmengine - INFO - Epoch(train) [27][ 540/2569] lr: 4.0000e-02 eta: 23:36:56 time: 0.2713 data_time: 0.0076 memory: 5828 grad_norm: 2.9985 loss: 2.7330 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7330 2023/06/04 21:21:30 - mmengine - INFO - Epoch(train) [27][ 560/2569] lr: 4.0000e-02 eta: 23:36:52 time: 0.2780 data_time: 0.0077 memory: 5828 grad_norm: 3.0008 loss: 2.9128 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9128 2023/06/04 21:21:35 - mmengine - INFO - Epoch(train) [27][ 580/2569] lr: 4.0000e-02 eta: 23:36:46 time: 0.2659 data_time: 0.0077 memory: 5828 grad_norm: 2.9493 loss: 2.6239 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6239 2023/06/04 21:21:41 - mmengine - INFO - Epoch(train) [27][ 600/2569] lr: 4.0000e-02 eta: 23:36:42 time: 0.2814 data_time: 0.0079 memory: 5828 grad_norm: 2.9716 loss: 2.8618 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8618 2023/06/04 21:21:46 - mmengine - INFO - Epoch(train) [27][ 620/2569] lr: 4.0000e-02 eta: 23:36:37 time: 0.2658 data_time: 0.0086 memory: 5828 grad_norm: 2.9982 loss: 2.8000 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8000 2023/06/04 21:21:51 - mmengine - INFO - Epoch(train) [27][ 640/2569] lr: 4.0000e-02 eta: 23:36:32 time: 0.2665 data_time: 0.0079 memory: 5828 grad_norm: 2.9409 loss: 2.6174 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6174 2023/06/04 21:21:57 - mmengine - INFO - Epoch(train) [27][ 660/2569] lr: 4.0000e-02 eta: 23:36:27 time: 0.2706 data_time: 0.0077 memory: 5828 grad_norm: 2.9421 loss: 2.5574 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5574 2023/06/04 21:22:02 - mmengine - INFO - Epoch(train) [27][ 680/2569] lr: 4.0000e-02 eta: 23:36:21 time: 0.2626 data_time: 0.0078 memory: 5828 grad_norm: 3.0007 loss: 2.6425 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6425 2023/06/04 21:22:07 - mmengine - INFO - Epoch(train) [27][ 700/2569] lr: 4.0000e-02 eta: 23:36:15 time: 0.2608 data_time: 0.0077 memory: 5828 grad_norm: 3.0379 loss: 2.6458 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6458 2023/06/04 21:22:13 - mmengine - INFO - Epoch(train) [27][ 720/2569] lr: 4.0000e-02 eta: 23:36:09 time: 0.2619 data_time: 0.0077 memory: 5828 grad_norm: 2.9302 loss: 2.5094 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5094 2023/06/04 21:22:18 - mmengine - INFO - Epoch(train) [27][ 740/2569] lr: 4.0000e-02 eta: 23:36:04 time: 0.2713 data_time: 0.0085 memory: 5828 grad_norm: 2.8847 loss: 2.6059 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6059 2023/06/04 21:22:23 - mmengine - INFO - Epoch(train) [27][ 760/2569] lr: 4.0000e-02 eta: 23:35:58 time: 0.2638 data_time: 0.0083 memory: 5828 grad_norm: 2.9709 loss: 2.4010 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4010 2023/06/04 21:22:29 - mmengine - INFO - Epoch(train) [27][ 780/2569] lr: 4.0000e-02 eta: 23:35:53 time: 0.2662 data_time: 0.0077 memory: 5828 grad_norm: 2.9789 loss: 2.3127 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3127 2023/06/04 21:22:34 - mmengine - INFO - Epoch(train) [27][ 800/2569] lr: 4.0000e-02 eta: 23:35:48 time: 0.2728 data_time: 0.0081 memory: 5828 grad_norm: 3.0100 loss: 2.7909 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7909 2023/06/04 21:22:39 - mmengine - INFO - Epoch(train) [27][ 820/2569] lr: 4.0000e-02 eta: 23:35:42 time: 0.2608 data_time: 0.0080 memory: 5828 grad_norm: 2.9931 loss: 2.5108 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5108 2023/06/04 21:22:45 - mmengine - INFO - Epoch(train) [27][ 840/2569] lr: 4.0000e-02 eta: 23:35:36 time: 0.2632 data_time: 0.0079 memory: 5828 grad_norm: 2.9722 loss: 2.5738 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5738 2023/06/04 21:22:50 - mmengine - INFO - Epoch(train) [27][ 860/2569] lr: 4.0000e-02 eta: 23:35:31 time: 0.2658 data_time: 0.0079 memory: 5828 grad_norm: 2.9898 loss: 2.5043 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5043 2023/06/04 21:22:55 - mmengine - INFO - Epoch(train) [27][ 880/2569] lr: 4.0000e-02 eta: 23:35:25 time: 0.2669 data_time: 0.0082 memory: 5828 grad_norm: 2.9616 loss: 2.3539 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3539 2023/06/04 21:23:01 - mmengine - INFO - Epoch(train) [27][ 900/2569] lr: 4.0000e-02 eta: 23:35:20 time: 0.2723 data_time: 0.0074 memory: 5828 grad_norm: 2.9628 loss: 2.9775 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9775 2023/06/04 21:23:06 - mmengine - INFO - Epoch(train) [27][ 920/2569] lr: 4.0000e-02 eta: 23:35:15 time: 0.2682 data_time: 0.0077 memory: 5828 grad_norm: 2.9231 loss: 2.7751 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7751 2023/06/04 21:23:11 - mmengine - INFO - Epoch(train) [27][ 940/2569] lr: 4.0000e-02 eta: 23:35:10 time: 0.2670 data_time: 0.0077 memory: 5828 grad_norm: 2.9455 loss: 2.3698 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3698 2023/06/04 21:23:17 - mmengine - INFO - Epoch(train) [27][ 960/2569] lr: 4.0000e-02 eta: 23:35:05 time: 0.2684 data_time: 0.0077 memory: 5828 grad_norm: 3.0133 loss: 2.6538 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6538 2023/06/04 21:23:22 - mmengine - INFO - Epoch(train) [27][ 980/2569] lr: 4.0000e-02 eta: 23:34:59 time: 0.2667 data_time: 0.0078 memory: 5828 grad_norm: 2.9503 loss: 2.4566 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4566 2023/06/04 21:23:28 - mmengine - INFO - Epoch(train) [27][1000/2569] lr: 4.0000e-02 eta: 23:34:54 time: 0.2723 data_time: 0.0081 memory: 5828 grad_norm: 2.9123 loss: 2.3978 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3978 2023/06/04 21:23:33 - mmengine - INFO - Epoch(train) [27][1020/2569] lr: 4.0000e-02 eta: 23:34:48 time: 0.2619 data_time: 0.0082 memory: 5828 grad_norm: 2.9488 loss: 2.9011 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9011 2023/06/04 21:23:38 - mmengine - INFO - Epoch(train) [27][1040/2569] lr: 4.0000e-02 eta: 23:34:44 time: 0.2730 data_time: 0.0084 memory: 5828 grad_norm: 2.8815 loss: 2.7288 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7288 2023/06/04 21:23:44 - mmengine - INFO - Epoch(train) [27][1060/2569] lr: 4.0000e-02 eta: 23:34:38 time: 0.2647 data_time: 0.0075 memory: 5828 grad_norm: 2.9746 loss: 2.4694 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4694 2023/06/04 21:23:49 - mmengine - INFO - Epoch(train) [27][1080/2569] lr: 4.0000e-02 eta: 23:34:32 time: 0.2610 data_time: 0.0079 memory: 5828 grad_norm: 3.0055 loss: 2.6111 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6111 2023/06/04 21:23:54 - mmengine - INFO - Epoch(train) [27][1100/2569] lr: 4.0000e-02 eta: 23:34:28 time: 0.2764 data_time: 0.0075 memory: 5828 grad_norm: 2.9649 loss: 2.8896 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8896 2023/06/04 21:24:00 - mmengine - INFO - Epoch(train) [27][1120/2569] lr: 4.0000e-02 eta: 23:34:22 time: 0.2658 data_time: 0.0077 memory: 5828 grad_norm: 2.9537 loss: 2.5792 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5792 2023/06/04 21:24:05 - mmengine - INFO - Epoch(train) [27][1140/2569] lr: 4.0000e-02 eta: 23:34:17 time: 0.2703 data_time: 0.0083 memory: 5828 grad_norm: 2.9450 loss: 2.6723 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6723 2023/06/04 21:24:11 - mmengine - INFO - Epoch(train) [27][1160/2569] lr: 4.0000e-02 eta: 23:34:12 time: 0.2723 data_time: 0.0084 memory: 5828 grad_norm: 3.0438 loss: 2.6972 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6972 2023/06/04 21:24:16 - mmengine - INFO - Epoch(train) [27][1180/2569] lr: 4.0000e-02 eta: 23:34:07 time: 0.2656 data_time: 0.0084 memory: 5828 grad_norm: 3.0076 loss: 2.8698 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8698 2023/06/04 21:24:21 - mmengine - INFO - Epoch(train) [27][1200/2569] lr: 4.0000e-02 eta: 23:34:01 time: 0.2644 data_time: 0.0082 memory: 5828 grad_norm: 2.9333 loss: 2.7935 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7935 2023/06/04 21:24:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:24:26 - mmengine - INFO - Epoch(train) [27][1220/2569] lr: 4.0000e-02 eta: 23:33:55 time: 0.2593 data_time: 0.0075 memory: 5828 grad_norm: 2.8914 loss: 2.4826 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4826 2023/06/04 21:24:32 - mmengine - INFO - Epoch(train) [27][1240/2569] lr: 4.0000e-02 eta: 23:33:50 time: 0.2678 data_time: 0.0068 memory: 5828 grad_norm: 2.9894 loss: 2.2577 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2577 2023/06/04 21:24:37 - mmengine - INFO - Epoch(train) [27][1260/2569] lr: 4.0000e-02 eta: 23:33:44 time: 0.2611 data_time: 0.0080 memory: 5828 grad_norm: 3.0251 loss: 2.5714 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5714 2023/06/04 21:24:42 - mmengine - INFO - Epoch(train) [27][1280/2569] lr: 4.0000e-02 eta: 23:33:38 time: 0.2672 data_time: 0.0072 memory: 5828 grad_norm: 2.9599 loss: 2.3546 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3546 2023/06/04 21:24:48 - mmengine - INFO - Epoch(train) [27][1300/2569] lr: 4.0000e-02 eta: 23:33:33 time: 0.2659 data_time: 0.0076 memory: 5828 grad_norm: 2.9462 loss: 2.8233 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8233 2023/06/04 21:24:53 - mmengine - INFO - Epoch(train) [27][1320/2569] lr: 4.0000e-02 eta: 23:33:27 time: 0.2665 data_time: 0.0080 memory: 5828 grad_norm: 2.9859 loss: 2.7167 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7167 2023/06/04 21:24:58 - mmengine - INFO - Epoch(train) [27][1340/2569] lr: 4.0000e-02 eta: 23:33:22 time: 0.2702 data_time: 0.0074 memory: 5828 grad_norm: 2.9780 loss: 2.8255 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8255 2023/06/04 21:25:04 - mmengine - INFO - Epoch(train) [27][1360/2569] lr: 4.0000e-02 eta: 23:33:17 time: 0.2671 data_time: 0.0082 memory: 5828 grad_norm: 2.9378 loss: 2.6018 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6018 2023/06/04 21:25:09 - mmengine - INFO - Epoch(train) [27][1380/2569] lr: 4.0000e-02 eta: 23:33:12 time: 0.2673 data_time: 0.0087 memory: 5828 grad_norm: 2.9271 loss: 2.4923 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4923 2023/06/04 21:25:14 - mmengine - INFO - Epoch(train) [27][1400/2569] lr: 4.0000e-02 eta: 23:33:06 time: 0.2658 data_time: 0.0083 memory: 5828 grad_norm: 2.9342 loss: 2.7371 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7371 2023/06/04 21:25:20 - mmengine - INFO - Epoch(train) [27][1420/2569] lr: 4.0000e-02 eta: 23:33:01 time: 0.2665 data_time: 0.0075 memory: 5828 grad_norm: 2.9014 loss: 2.6444 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6444 2023/06/04 21:25:25 - mmengine - INFO - Epoch(train) [27][1440/2569] lr: 4.0000e-02 eta: 23:32:56 time: 0.2730 data_time: 0.0078 memory: 5828 grad_norm: 2.9045 loss: 2.5910 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5910 2023/06/04 21:25:30 - mmengine - INFO - Epoch(train) [27][1460/2569] lr: 4.0000e-02 eta: 23:32:50 time: 0.2611 data_time: 0.0079 memory: 5828 grad_norm: 2.9647 loss: 2.6874 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6874 2023/06/04 21:25:36 - mmengine - INFO - Epoch(train) [27][1480/2569] lr: 4.0000e-02 eta: 23:32:44 time: 0.2623 data_time: 0.0079 memory: 5828 grad_norm: 2.9055 loss: 2.5820 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5820 2023/06/04 21:25:41 - mmengine - INFO - Epoch(train) [27][1500/2569] lr: 4.0000e-02 eta: 23:32:38 time: 0.2607 data_time: 0.0084 memory: 5828 grad_norm: 2.9618 loss: 2.3420 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3420 2023/06/04 21:25:46 - mmengine - INFO - Epoch(train) [27][1520/2569] lr: 4.0000e-02 eta: 23:32:33 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 2.9870 loss: 2.5779 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5779 2023/06/04 21:25:51 - mmengine - INFO - Epoch(train) [27][1540/2569] lr: 4.0000e-02 eta: 23:32:27 time: 0.2680 data_time: 0.0076 memory: 5828 grad_norm: 2.8655 loss: 2.5912 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5912 2023/06/04 21:25:57 - mmengine - INFO - Epoch(train) [27][1560/2569] lr: 4.0000e-02 eta: 23:32:22 time: 0.2664 data_time: 0.0076 memory: 5828 grad_norm: 2.9647 loss: 2.4742 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4742 2023/06/04 21:26:02 - mmengine - INFO - Epoch(train) [27][1580/2569] lr: 4.0000e-02 eta: 23:32:17 time: 0.2673 data_time: 0.0079 memory: 5828 grad_norm: 2.9588 loss: 2.4535 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4535 2023/06/04 21:26:07 - mmengine - INFO - Epoch(train) [27][1600/2569] lr: 4.0000e-02 eta: 23:32:11 time: 0.2619 data_time: 0.0080 memory: 5828 grad_norm: 2.9542 loss: 2.6539 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6539 2023/06/04 21:26:13 - mmengine - INFO - Epoch(train) [27][1620/2569] lr: 4.0000e-02 eta: 23:32:05 time: 0.2607 data_time: 0.0077 memory: 5828 grad_norm: 2.9543 loss: 2.7850 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7850 2023/06/04 21:26:18 - mmengine - INFO - Epoch(train) [27][1640/2569] lr: 4.0000e-02 eta: 23:31:59 time: 0.2638 data_time: 0.0078 memory: 5828 grad_norm: 3.0037 loss: 2.7056 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7056 2023/06/04 21:26:23 - mmengine - INFO - Epoch(train) [27][1660/2569] lr: 4.0000e-02 eta: 23:31:54 time: 0.2661 data_time: 0.0073 memory: 5828 grad_norm: 2.9341 loss: 2.5143 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5143 2023/06/04 21:26:29 - mmengine - INFO - Epoch(train) [27][1680/2569] lr: 4.0000e-02 eta: 23:31:49 time: 0.2750 data_time: 0.0078 memory: 5828 grad_norm: 2.9382 loss: 2.6369 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.6369 2023/06/04 21:26:34 - mmengine - INFO - Epoch(train) [27][1700/2569] lr: 4.0000e-02 eta: 23:31:44 time: 0.2691 data_time: 0.0080 memory: 5828 grad_norm: 2.9117 loss: 2.6368 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6368 2023/06/04 21:26:40 - mmengine - INFO - Epoch(train) [27][1720/2569] lr: 4.0000e-02 eta: 23:31:39 time: 0.2725 data_time: 0.0080 memory: 5828 grad_norm: 2.9249 loss: 2.7348 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7348 2023/06/04 21:26:45 - mmengine - INFO - Epoch(train) [27][1740/2569] lr: 4.0000e-02 eta: 23:31:33 time: 0.2628 data_time: 0.0074 memory: 5828 grad_norm: 2.9711 loss: 2.8032 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8032 2023/06/04 21:26:50 - mmengine - INFO - Epoch(train) [27][1760/2569] lr: 4.0000e-02 eta: 23:31:28 time: 0.2728 data_time: 0.0077 memory: 5828 grad_norm: 2.9673 loss: 2.7035 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7035 2023/06/04 21:26:56 - mmengine - INFO - Epoch(train) [27][1780/2569] lr: 4.0000e-02 eta: 23:31:23 time: 0.2721 data_time: 0.0074 memory: 5828 grad_norm: 2.9070 loss: 2.2872 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2872 2023/06/04 21:27:01 - mmengine - INFO - Epoch(train) [27][1800/2569] lr: 4.0000e-02 eta: 23:31:18 time: 0.2633 data_time: 0.0084 memory: 5828 grad_norm: 2.9493 loss: 2.8667 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8667 2023/06/04 21:27:06 - mmengine - INFO - Epoch(train) [27][1820/2569] lr: 4.0000e-02 eta: 23:31:13 time: 0.2747 data_time: 0.0082 memory: 5828 grad_norm: 2.9793 loss: 2.5487 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5487 2023/06/04 21:27:12 - mmengine - INFO - Epoch(train) [27][1840/2569] lr: 4.0000e-02 eta: 23:31:09 time: 0.2779 data_time: 0.0079 memory: 5828 grad_norm: 2.9580 loss: 2.3757 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3757 2023/06/04 21:27:17 - mmengine - INFO - Epoch(train) [27][1860/2569] lr: 4.0000e-02 eta: 23:31:03 time: 0.2609 data_time: 0.0106 memory: 5828 grad_norm: 2.9837 loss: 2.8880 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8880 2023/06/04 21:27:23 - mmengine - INFO - Epoch(train) [27][1880/2569] lr: 4.0000e-02 eta: 23:30:57 time: 0.2667 data_time: 0.0079 memory: 5828 grad_norm: 2.9081 loss: 2.7148 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7148 2023/06/04 21:27:28 - mmengine - INFO - Epoch(train) [27][1900/2569] lr: 4.0000e-02 eta: 23:30:52 time: 0.2657 data_time: 0.0077 memory: 5828 grad_norm: 2.9763 loss: 3.1077 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.1077 2023/06/04 21:27:33 - mmengine - INFO - Epoch(train) [27][1920/2569] lr: 4.0000e-02 eta: 23:30:46 time: 0.2642 data_time: 0.0076 memory: 5828 grad_norm: 2.9057 loss: 2.4872 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4872 2023/06/04 21:27:38 - mmengine - INFO - Epoch(train) [27][1940/2569] lr: 4.0000e-02 eta: 23:30:41 time: 0.2643 data_time: 0.0078 memory: 5828 grad_norm: 2.9530 loss: 2.5349 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5349 2023/06/04 21:27:44 - mmengine - INFO - Epoch(train) [27][1960/2569] lr: 4.0000e-02 eta: 23:30:35 time: 0.2625 data_time: 0.0079 memory: 5828 grad_norm: 2.9408 loss: 2.5522 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5522 2023/06/04 21:27:49 - mmengine - INFO - Epoch(train) [27][1980/2569] lr: 4.0000e-02 eta: 23:30:29 time: 0.2662 data_time: 0.0079 memory: 5828 grad_norm: 3.0128 loss: 2.8421 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8421 2023/06/04 21:27:54 - mmengine - INFO - Epoch(train) [27][2000/2569] lr: 4.0000e-02 eta: 23:30:24 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 2.9710 loss: 2.3927 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3927 2023/06/04 21:28:00 - mmengine - INFO - Epoch(train) [27][2020/2569] lr: 4.0000e-02 eta: 23:30:18 time: 0.2626 data_time: 0.0076 memory: 5828 grad_norm: 2.9228 loss: 2.5623 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5623 2023/06/04 21:28:05 - mmengine - INFO - Epoch(train) [27][2040/2569] lr: 4.0000e-02 eta: 23:30:12 time: 0.2633 data_time: 0.0078 memory: 5828 grad_norm: 2.9757 loss: 2.6487 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6487 2023/06/04 21:28:10 - mmengine - INFO - Epoch(train) [27][2060/2569] lr: 4.0000e-02 eta: 23:30:07 time: 0.2675 data_time: 0.0081 memory: 5828 grad_norm: 2.9053 loss: 2.5777 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5777 2023/06/04 21:28:16 - mmengine - INFO - Epoch(train) [27][2080/2569] lr: 4.0000e-02 eta: 23:30:02 time: 0.2733 data_time: 0.0081 memory: 5828 grad_norm: 2.9163 loss: 2.6611 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6611 2023/06/04 21:28:21 - mmengine - INFO - Epoch(train) [27][2100/2569] lr: 4.0000e-02 eta: 23:29:57 time: 0.2732 data_time: 0.0076 memory: 5828 grad_norm: 2.9339 loss: 2.3718 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3718 2023/06/04 21:28:27 - mmengine - INFO - Epoch(train) [27][2120/2569] lr: 4.0000e-02 eta: 23:29:52 time: 0.2691 data_time: 0.0076 memory: 5828 grad_norm: 2.9339 loss: 2.5829 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5829 2023/06/04 21:28:32 - mmengine - INFO - Epoch(train) [27][2140/2569] lr: 4.0000e-02 eta: 23:29:46 time: 0.2609 data_time: 0.0078 memory: 5828 grad_norm: 2.9585 loss: 2.5267 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5267 2023/06/04 21:28:37 - mmengine - INFO - Epoch(train) [27][2160/2569] lr: 4.0000e-02 eta: 23:29:41 time: 0.2685 data_time: 0.0074 memory: 5828 grad_norm: 2.9120 loss: 2.4548 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4548 2023/06/04 21:28:42 - mmengine - INFO - Epoch(train) [27][2180/2569] lr: 4.0000e-02 eta: 23:29:36 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 2.9560 loss: 2.5036 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5036 2023/06/04 21:28:48 - mmengine - INFO - Epoch(train) [27][2200/2569] lr: 4.0000e-02 eta: 23:29:30 time: 0.2620 data_time: 0.0080 memory: 5828 grad_norm: 2.9343 loss: 2.5806 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5806 2023/06/04 21:28:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:28:53 - mmengine - INFO - Epoch(train) [27][2220/2569] lr: 4.0000e-02 eta: 23:29:24 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 3.0108 loss: 2.2481 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2481 2023/06/04 21:28:58 - mmengine - INFO - Epoch(train) [27][2240/2569] lr: 4.0000e-02 eta: 23:29:18 time: 0.2633 data_time: 0.0082 memory: 5828 grad_norm: 2.9864 loss: 2.6786 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6786 2023/06/04 21:29:04 - mmengine - INFO - Epoch(train) [27][2260/2569] lr: 4.0000e-02 eta: 23:29:13 time: 0.2663 data_time: 0.0085 memory: 5828 grad_norm: 3.0232 loss: 2.4864 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4864 2023/06/04 21:29:09 - mmengine - INFO - Epoch(train) [27][2280/2569] lr: 4.0000e-02 eta: 23:29:07 time: 0.2614 data_time: 0.0078 memory: 5828 grad_norm: 2.9338 loss: 2.7215 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7215 2023/06/04 21:29:14 - mmengine - INFO - Epoch(train) [27][2300/2569] lr: 4.0000e-02 eta: 23:29:02 time: 0.2726 data_time: 0.0077 memory: 5828 grad_norm: 2.9141 loss: 2.4041 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4041 2023/06/04 21:29:20 - mmengine - INFO - Epoch(train) [27][2320/2569] lr: 4.0000e-02 eta: 23:28:56 time: 0.2631 data_time: 0.0082 memory: 5828 grad_norm: 2.9286 loss: 2.6689 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6689 2023/06/04 21:29:25 - mmengine - INFO - Epoch(train) [27][2340/2569] lr: 4.0000e-02 eta: 23:28:51 time: 0.2694 data_time: 0.0077 memory: 5828 grad_norm: 2.9860 loss: 2.6098 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6098 2023/06/04 21:29:30 - mmengine - INFO - Epoch(train) [27][2360/2569] lr: 4.0000e-02 eta: 23:28:46 time: 0.2684 data_time: 0.0078 memory: 5828 grad_norm: 2.9185 loss: 2.6421 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6421 2023/06/04 21:29:36 - mmengine - INFO - Epoch(train) [27][2380/2569] lr: 4.0000e-02 eta: 23:28:40 time: 0.2669 data_time: 0.0080 memory: 5828 grad_norm: 2.9201 loss: 2.6007 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6007 2023/06/04 21:29:41 - mmengine - INFO - Epoch(train) [27][2400/2569] lr: 4.0000e-02 eta: 23:28:35 time: 0.2718 data_time: 0.0081 memory: 5828 grad_norm: 2.9142 loss: 2.5167 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5167 2023/06/04 21:29:46 - mmengine - INFO - Epoch(train) [27][2420/2569] lr: 4.0000e-02 eta: 23:28:30 time: 0.2615 data_time: 0.0078 memory: 5828 grad_norm: 2.9405 loss: 2.6160 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6160 2023/06/04 21:29:52 - mmengine - INFO - Epoch(train) [27][2440/2569] lr: 4.0000e-02 eta: 23:28:24 time: 0.2658 data_time: 0.0078 memory: 5828 grad_norm: 2.8800 loss: 2.6246 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6246 2023/06/04 21:29:57 - mmengine - INFO - Epoch(train) [27][2460/2569] lr: 4.0000e-02 eta: 23:28:18 time: 0.2612 data_time: 0.0092 memory: 5828 grad_norm: 2.9589 loss: 2.5890 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5890 2023/06/04 21:30:02 - mmengine - INFO - Epoch(train) [27][2480/2569] lr: 4.0000e-02 eta: 23:28:14 time: 0.2745 data_time: 0.0078 memory: 5828 grad_norm: 2.9943 loss: 2.6448 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6448 2023/06/04 21:30:08 - mmengine - INFO - Epoch(train) [27][2500/2569] lr: 4.0000e-02 eta: 23:28:08 time: 0.2667 data_time: 0.0075 memory: 5828 grad_norm: 3.0245 loss: 2.4516 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.4516 2023/06/04 21:30:13 - mmengine - INFO - Epoch(train) [27][2520/2569] lr: 4.0000e-02 eta: 23:28:03 time: 0.2690 data_time: 0.0079 memory: 5828 grad_norm: 2.8865 loss: 2.6246 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6246 2023/06/04 21:30:18 - mmengine - INFO - Epoch(train) [27][2540/2569] lr: 4.0000e-02 eta: 23:27:58 time: 0.2669 data_time: 0.0079 memory: 5828 grad_norm: 2.9493 loss: 2.9064 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9064 2023/06/04 21:30:24 - mmengine - INFO - Epoch(train) [27][2560/2569] lr: 4.0000e-02 eta: 23:27:52 time: 0.2657 data_time: 0.0081 memory: 5828 grad_norm: 2.9803 loss: 2.6111 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6111 2023/06/04 21:30:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:30:26 - mmengine - INFO - Epoch(train) [27][2569/2569] lr: 4.0000e-02 eta: 23:27:49 time: 0.2639 data_time: 0.0078 memory: 5828 grad_norm: 2.9795 loss: 2.5110 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5110 2023/06/04 21:30:33 - mmengine - INFO - Epoch(train) [28][ 20/2569] lr: 4.0000e-02 eta: 23:27:52 time: 0.3585 data_time: 0.0686 memory: 5828 grad_norm: 2.9114 loss: 2.7365 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7365 2023/06/04 21:30:39 - mmengine - INFO - Epoch(train) [28][ 40/2569] lr: 4.0000e-02 eta: 23:27:47 time: 0.2728 data_time: 0.0082 memory: 5828 grad_norm: 2.9576 loss: 2.7876 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7876 2023/06/04 21:30:44 - mmengine - INFO - Epoch(train) [28][ 60/2569] lr: 4.0000e-02 eta: 23:27:42 time: 0.2637 data_time: 0.0080 memory: 5828 grad_norm: 2.9870 loss: 2.6927 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6927 2023/06/04 21:30:50 - mmengine - INFO - Epoch(train) [28][ 80/2569] lr: 4.0000e-02 eta: 23:27:38 time: 0.2819 data_time: 0.0079 memory: 5828 grad_norm: 2.9734 loss: 2.7054 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7054 2023/06/04 21:30:55 - mmengine - INFO - Epoch(train) [28][ 100/2569] lr: 4.0000e-02 eta: 23:27:32 time: 0.2620 data_time: 0.0077 memory: 5828 grad_norm: 2.9203 loss: 2.8295 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8295 2023/06/04 21:31:00 - mmengine - INFO - Epoch(train) [28][ 120/2569] lr: 4.0000e-02 eta: 23:27:27 time: 0.2701 data_time: 0.0076 memory: 5828 grad_norm: 2.9291 loss: 2.8809 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8809 2023/06/04 21:31:06 - mmengine - INFO - Epoch(train) [28][ 140/2569] lr: 4.0000e-02 eta: 23:27:21 time: 0.2670 data_time: 0.0076 memory: 5828 grad_norm: 2.9947 loss: 2.5368 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5368 2023/06/04 21:31:11 - mmengine - INFO - Epoch(train) [28][ 160/2569] lr: 4.0000e-02 eta: 23:27:16 time: 0.2654 data_time: 0.0074 memory: 5828 grad_norm: 3.0061 loss: 2.6622 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6622 2023/06/04 21:31:16 - mmengine - INFO - Epoch(train) [28][ 180/2569] lr: 4.0000e-02 eta: 23:27:10 time: 0.2668 data_time: 0.0084 memory: 5828 grad_norm: 2.9672 loss: 2.6681 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6681 2023/06/04 21:31:22 - mmengine - INFO - Epoch(train) [28][ 200/2569] lr: 4.0000e-02 eta: 23:27:05 time: 0.2635 data_time: 0.0078 memory: 5828 grad_norm: 2.9734 loss: 2.7278 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7278 2023/06/04 21:31:27 - mmengine - INFO - Epoch(train) [28][ 220/2569] lr: 4.0000e-02 eta: 23:26:59 time: 0.2652 data_time: 0.0081 memory: 5828 grad_norm: 2.9794 loss: 2.7259 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7259 2023/06/04 21:31:32 - mmengine - INFO - Epoch(train) [28][ 240/2569] lr: 4.0000e-02 eta: 23:26:54 time: 0.2723 data_time: 0.0081 memory: 5828 grad_norm: 2.9378 loss: 2.7314 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7314 2023/06/04 21:31:38 - mmengine - INFO - Epoch(train) [28][ 260/2569] lr: 4.0000e-02 eta: 23:26:49 time: 0.2689 data_time: 0.0075 memory: 5828 grad_norm: 2.9362 loss: 2.7664 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7664 2023/06/04 21:31:43 - mmengine - INFO - Epoch(train) [28][ 280/2569] lr: 4.0000e-02 eta: 23:26:44 time: 0.2691 data_time: 0.0079 memory: 5828 grad_norm: 2.9409 loss: 2.7562 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7562 2023/06/04 21:31:48 - mmengine - INFO - Epoch(train) [28][ 300/2569] lr: 4.0000e-02 eta: 23:26:39 time: 0.2684 data_time: 0.0080 memory: 5828 grad_norm: 2.9328 loss: 2.6045 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6045 2023/06/04 21:31:54 - mmengine - INFO - Epoch(train) [28][ 320/2569] lr: 4.0000e-02 eta: 23:26:33 time: 0.2604 data_time: 0.0077 memory: 5828 grad_norm: 2.9004 loss: 2.6160 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6160 2023/06/04 21:31:59 - mmengine - INFO - Epoch(train) [28][ 340/2569] lr: 4.0000e-02 eta: 23:26:28 time: 0.2746 data_time: 0.0078 memory: 5828 grad_norm: 2.9828 loss: 2.5654 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5654 2023/06/04 21:32:04 - mmengine - INFO - Epoch(train) [28][ 360/2569] lr: 4.0000e-02 eta: 23:26:22 time: 0.2617 data_time: 0.0079 memory: 5828 grad_norm: 2.9328 loss: 2.5707 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5707 2023/06/04 21:32:10 - mmengine - INFO - Epoch(train) [28][ 380/2569] lr: 4.0000e-02 eta: 23:26:16 time: 0.2617 data_time: 0.0084 memory: 5828 grad_norm: 2.9879 loss: 2.3780 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3780 2023/06/04 21:32:15 - mmengine - INFO - Epoch(train) [28][ 400/2569] lr: 4.0000e-02 eta: 23:26:11 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 2.9364 loss: 2.7458 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7458 2023/06/04 21:32:20 - mmengine - INFO - Epoch(train) [28][ 420/2569] lr: 4.0000e-02 eta: 23:26:05 time: 0.2674 data_time: 0.0077 memory: 5828 grad_norm: 2.9477 loss: 2.2774 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2774 2023/06/04 21:32:26 - mmengine - INFO - Epoch(train) [28][ 440/2569] lr: 4.0000e-02 eta: 23:26:00 time: 0.2628 data_time: 0.0078 memory: 5828 grad_norm: 2.9542 loss: 2.7064 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7064 2023/06/04 21:32:31 - mmengine - INFO - Epoch(train) [28][ 460/2569] lr: 4.0000e-02 eta: 23:25:54 time: 0.2628 data_time: 0.0081 memory: 5828 grad_norm: 2.9759 loss: 2.6405 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6405 2023/06/04 21:32:36 - mmengine - INFO - Epoch(train) [28][ 480/2569] lr: 4.0000e-02 eta: 23:25:49 time: 0.2707 data_time: 0.0079 memory: 5828 grad_norm: 2.9653 loss: 2.7472 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7472 2023/06/04 21:32:41 - mmengine - INFO - Epoch(train) [28][ 500/2569] lr: 4.0000e-02 eta: 23:25:43 time: 0.2631 data_time: 0.0079 memory: 5828 grad_norm: 2.9338 loss: 2.5740 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5740 2023/06/04 21:32:47 - mmengine - INFO - Epoch(train) [28][ 520/2569] lr: 4.0000e-02 eta: 23:25:38 time: 0.2700 data_time: 0.0075 memory: 5828 grad_norm: 2.9914 loss: 2.1608 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1608 2023/06/04 21:32:52 - mmengine - INFO - Epoch(train) [28][ 540/2569] lr: 4.0000e-02 eta: 23:25:32 time: 0.2607 data_time: 0.0085 memory: 5828 grad_norm: 2.9163 loss: 2.4463 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4463 2023/06/04 21:32:58 - mmengine - INFO - Epoch(train) [28][ 560/2569] lr: 4.0000e-02 eta: 23:25:27 time: 0.2716 data_time: 0.0077 memory: 5828 grad_norm: 2.9292 loss: 2.6531 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6531 2023/06/04 21:33:03 - mmengine - INFO - Epoch(train) [28][ 580/2569] lr: 4.0000e-02 eta: 23:25:22 time: 0.2740 data_time: 0.0079 memory: 5828 grad_norm: 2.9901 loss: 2.8089 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8089 2023/06/04 21:33:08 - mmengine - INFO - Epoch(train) [28][ 600/2569] lr: 4.0000e-02 eta: 23:25:17 time: 0.2655 data_time: 0.0081 memory: 5828 grad_norm: 2.8636 loss: 2.7449 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7449 2023/06/04 21:33:14 - mmengine - INFO - Epoch(train) [28][ 620/2569] lr: 4.0000e-02 eta: 23:25:11 time: 0.2670 data_time: 0.0078 memory: 5828 grad_norm: 2.9219 loss: 2.7478 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7478 2023/06/04 21:33:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:33:19 - mmengine - INFO - Epoch(train) [28][ 640/2569] lr: 4.0000e-02 eta: 23:25:07 time: 0.2780 data_time: 0.0073 memory: 5828 grad_norm: 2.8859 loss: 2.4190 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4190 2023/06/04 21:33:24 - mmengine - INFO - Epoch(train) [28][ 660/2569] lr: 4.0000e-02 eta: 23:25:01 time: 0.2614 data_time: 0.0083 memory: 5828 grad_norm: 2.9420 loss: 2.5651 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5651 2023/06/04 21:33:30 - mmengine - INFO - Epoch(train) [28][ 680/2569] lr: 4.0000e-02 eta: 23:24:55 time: 0.2636 data_time: 0.0082 memory: 5828 grad_norm: 2.9385 loss: 2.5247 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5247 2023/06/04 21:33:35 - mmengine - INFO - Epoch(train) [28][ 700/2569] lr: 4.0000e-02 eta: 23:24:50 time: 0.2663 data_time: 0.0077 memory: 5828 grad_norm: 2.9531 loss: 2.3536 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3536 2023/06/04 21:33:40 - mmengine - INFO - Epoch(train) [28][ 720/2569] lr: 4.0000e-02 eta: 23:24:45 time: 0.2674 data_time: 0.0076 memory: 5828 grad_norm: 2.9353 loss: 2.5815 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5815 2023/06/04 21:33:46 - mmengine - INFO - Epoch(train) [28][ 740/2569] lr: 4.0000e-02 eta: 23:24:39 time: 0.2610 data_time: 0.0079 memory: 5828 grad_norm: 2.9922 loss: 2.4760 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4760 2023/06/04 21:33:51 - mmengine - INFO - Epoch(train) [28][ 760/2569] lr: 4.0000e-02 eta: 23:24:34 time: 0.2695 data_time: 0.0080 memory: 5828 grad_norm: 2.9596 loss: 2.3839 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3839 2023/06/04 21:33:56 - mmengine - INFO - Epoch(train) [28][ 780/2569] lr: 4.0000e-02 eta: 23:24:28 time: 0.2650 data_time: 0.0082 memory: 5828 grad_norm: 2.8738 loss: 2.5848 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5848 2023/06/04 21:34:02 - mmengine - INFO - Epoch(train) [28][ 800/2569] lr: 4.0000e-02 eta: 23:24:23 time: 0.2669 data_time: 0.0081 memory: 5828 grad_norm: 2.9617 loss: 2.7183 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7183 2023/06/04 21:34:07 - mmengine - INFO - Epoch(train) [28][ 820/2569] lr: 4.0000e-02 eta: 23:24:17 time: 0.2618 data_time: 0.0083 memory: 5828 grad_norm: 2.9305 loss: 2.5689 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5689 2023/06/04 21:34:12 - mmengine - INFO - Epoch(train) [28][ 840/2569] lr: 4.0000e-02 eta: 23:24:11 time: 0.2628 data_time: 0.0081 memory: 5828 grad_norm: 2.9009 loss: 2.5263 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5263 2023/06/04 21:34:18 - mmengine - INFO - Epoch(train) [28][ 860/2569] lr: 4.0000e-02 eta: 23:24:06 time: 0.2692 data_time: 0.0078 memory: 5828 grad_norm: 2.9523 loss: 2.6253 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6253 2023/06/04 21:34:23 - mmengine - INFO - Epoch(train) [28][ 880/2569] lr: 4.0000e-02 eta: 23:24:01 time: 0.2699 data_time: 0.0076 memory: 5828 grad_norm: 2.9681 loss: 2.5259 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5259 2023/06/04 21:34:28 - mmengine - INFO - Epoch(train) [28][ 900/2569] lr: 4.0000e-02 eta: 23:23:56 time: 0.2737 data_time: 0.0078 memory: 5828 grad_norm: 2.9546 loss: 2.8474 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8474 2023/06/04 21:34:34 - mmengine - INFO - Epoch(train) [28][ 920/2569] lr: 4.0000e-02 eta: 23:23:50 time: 0.2601 data_time: 0.0081 memory: 5828 grad_norm: 2.9617 loss: 2.6675 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6675 2023/06/04 21:34:39 - mmengine - INFO - Epoch(train) [28][ 940/2569] lr: 4.0000e-02 eta: 23:23:45 time: 0.2689 data_time: 0.0078 memory: 5828 grad_norm: 2.9591 loss: 2.1864 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1864 2023/06/04 21:34:44 - mmengine - INFO - Epoch(train) [28][ 960/2569] lr: 4.0000e-02 eta: 23:23:40 time: 0.2685 data_time: 0.0076 memory: 5828 grad_norm: 2.9869 loss: 2.3589 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3589 2023/06/04 21:34:50 - mmengine - INFO - Epoch(train) [28][ 980/2569] lr: 4.0000e-02 eta: 23:23:34 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 3.0066 loss: 2.8740 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8740 2023/06/04 21:34:55 - mmengine - INFO - Epoch(train) [28][1000/2569] lr: 4.0000e-02 eta: 23:23:28 time: 0.2632 data_time: 0.0079 memory: 5828 grad_norm: 2.9424 loss: 2.5851 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5851 2023/06/04 21:35:00 - mmengine - INFO - Epoch(train) [28][1020/2569] lr: 4.0000e-02 eta: 23:23:23 time: 0.2691 data_time: 0.0076 memory: 5828 grad_norm: 2.9402 loss: 2.6304 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6304 2023/06/04 21:35:06 - mmengine - INFO - Epoch(train) [28][1040/2569] lr: 4.0000e-02 eta: 23:23:18 time: 0.2707 data_time: 0.0077 memory: 5828 grad_norm: 2.9944 loss: 2.3241 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3241 2023/06/04 21:35:11 - mmengine - INFO - Epoch(train) [28][1060/2569] lr: 4.0000e-02 eta: 23:23:13 time: 0.2683 data_time: 0.0081 memory: 5828 grad_norm: 2.9174 loss: 2.7012 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7012 2023/06/04 21:35:17 - mmengine - INFO - Epoch(train) [28][1080/2569] lr: 4.0000e-02 eta: 23:23:08 time: 0.2746 data_time: 0.0077 memory: 5828 grad_norm: 2.9134 loss: 2.2129 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2129 2023/06/04 21:35:22 - mmengine - INFO - Epoch(train) [28][1100/2569] lr: 4.0000e-02 eta: 23:23:02 time: 0.2619 data_time: 0.0079 memory: 5828 grad_norm: 2.9864 loss: 2.6355 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6355 2023/06/04 21:35:27 - mmengine - INFO - Epoch(train) [28][1120/2569] lr: 4.0000e-02 eta: 23:22:57 time: 0.2738 data_time: 0.0080 memory: 5828 grad_norm: 2.9529 loss: 2.3977 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3977 2023/06/04 21:35:33 - mmengine - INFO - Epoch(train) [28][1140/2569] lr: 4.0000e-02 eta: 23:22:52 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 2.9744 loss: 2.5559 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5559 2023/06/04 21:35:38 - mmengine - INFO - Epoch(train) [28][1160/2569] lr: 4.0000e-02 eta: 23:22:46 time: 0.2672 data_time: 0.0081 memory: 5828 grad_norm: 2.9218 loss: 2.6412 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6412 2023/06/04 21:35:43 - mmengine - INFO - Epoch(train) [28][1180/2569] lr: 4.0000e-02 eta: 23:22:41 time: 0.2640 data_time: 0.0082 memory: 5828 grad_norm: 2.9416 loss: 2.3725 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3725 2023/06/04 21:35:49 - mmengine - INFO - Epoch(train) [28][1200/2569] lr: 4.0000e-02 eta: 23:22:36 time: 0.2731 data_time: 0.0080 memory: 5828 grad_norm: 2.9947 loss: 2.6511 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6511 2023/06/04 21:35:54 - mmengine - INFO - Epoch(train) [28][1220/2569] lr: 4.0000e-02 eta: 23:22:30 time: 0.2605 data_time: 0.0079 memory: 5828 grad_norm: 2.9861 loss: 2.6530 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6530 2023/06/04 21:35:59 - mmengine - INFO - Epoch(train) [28][1240/2569] lr: 4.0000e-02 eta: 23:22:25 time: 0.2756 data_time: 0.0077 memory: 5828 grad_norm: 2.9581 loss: 2.6758 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6758 2023/06/04 21:36:05 - mmengine - INFO - Epoch(train) [28][1260/2569] lr: 4.0000e-02 eta: 23:22:19 time: 0.2616 data_time: 0.0076 memory: 5828 grad_norm: 2.9757 loss: 2.6119 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6119 2023/06/04 21:36:10 - mmengine - INFO - Epoch(train) [28][1280/2569] lr: 4.0000e-02 eta: 23:22:14 time: 0.2677 data_time: 0.0078 memory: 5828 grad_norm: 2.9532 loss: 2.9037 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9037 2023/06/04 21:36:15 - mmengine - INFO - Epoch(train) [28][1300/2569] lr: 4.0000e-02 eta: 23:22:09 time: 0.2683 data_time: 0.0077 memory: 5828 grad_norm: 2.9158 loss: 2.6237 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6237 2023/06/04 21:36:21 - mmengine - INFO - Epoch(train) [28][1320/2569] lr: 4.0000e-02 eta: 23:22:04 time: 0.2715 data_time: 0.0080 memory: 5828 grad_norm: 3.0155 loss: 2.7430 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7430 2023/06/04 21:36:26 - mmengine - INFO - Epoch(train) [28][1340/2569] lr: 4.0000e-02 eta: 23:21:58 time: 0.2625 data_time: 0.0084 memory: 5828 grad_norm: 2.9929 loss: 2.7787 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7787 2023/06/04 21:36:31 - mmengine - INFO - Epoch(train) [28][1360/2569] lr: 4.0000e-02 eta: 23:21:53 time: 0.2737 data_time: 0.0078 memory: 5828 grad_norm: 2.9992 loss: 2.6239 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6239 2023/06/04 21:36:37 - mmengine - INFO - Epoch(train) [28][1380/2569] lr: 4.0000e-02 eta: 23:21:48 time: 0.2660 data_time: 0.0082 memory: 5828 grad_norm: 2.9841 loss: 2.5298 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5298 2023/06/04 21:36:42 - mmengine - INFO - Epoch(train) [28][1400/2569] lr: 4.0000e-02 eta: 23:21:43 time: 0.2769 data_time: 0.0077 memory: 5828 grad_norm: 2.9638 loss: 2.7675 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.7675 2023/06/04 21:36:48 - mmengine - INFO - Epoch(train) [28][1420/2569] lr: 4.0000e-02 eta: 23:21:38 time: 0.2704 data_time: 0.0075 memory: 5828 grad_norm: 3.0231 loss: 2.8437 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8437 2023/06/04 21:36:53 - mmengine - INFO - Epoch(train) [28][1440/2569] lr: 4.0000e-02 eta: 23:21:33 time: 0.2714 data_time: 0.0078 memory: 5828 grad_norm: 2.9580 loss: 2.6018 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6018 2023/06/04 21:36:58 - mmengine - INFO - Epoch(train) [28][1460/2569] lr: 4.0000e-02 eta: 23:21:27 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 2.9452 loss: 2.7096 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.7096 2023/06/04 21:37:04 - mmengine - INFO - Epoch(train) [28][1480/2569] lr: 4.0000e-02 eta: 23:21:22 time: 0.2704 data_time: 0.0086 memory: 5828 grad_norm: 2.9959 loss: 2.6635 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6635 2023/06/04 21:37:09 - mmengine - INFO - Epoch(train) [28][1500/2569] lr: 4.0000e-02 eta: 23:21:17 time: 0.2668 data_time: 0.0085 memory: 5828 grad_norm: 2.9870 loss: 2.6427 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6427 2023/06/04 21:37:15 - mmengine - INFO - Epoch(train) [28][1520/2569] lr: 4.0000e-02 eta: 23:21:12 time: 0.2717 data_time: 0.0079 memory: 5828 grad_norm: 2.9191 loss: 2.4661 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4661 2023/06/04 21:37:20 - mmengine - INFO - Epoch(train) [28][1540/2569] lr: 4.0000e-02 eta: 23:21:07 time: 0.2677 data_time: 0.0085 memory: 5828 grad_norm: 2.9756 loss: 2.1878 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1878 2023/06/04 21:37:25 - mmengine - INFO - Epoch(train) [28][1560/2569] lr: 4.0000e-02 eta: 23:21:01 time: 0.2659 data_time: 0.0079 memory: 5828 grad_norm: 2.9452 loss: 2.5202 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5202 2023/06/04 21:37:31 - mmengine - INFO - Epoch(train) [28][1580/2569] lr: 4.0000e-02 eta: 23:20:56 time: 0.2651 data_time: 0.0080 memory: 5828 grad_norm: 2.9169 loss: 2.2805 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2805 2023/06/04 21:37:36 - mmengine - INFO - Epoch(train) [28][1600/2569] lr: 4.0000e-02 eta: 23:20:51 time: 0.2719 data_time: 0.0079 memory: 5828 grad_norm: 3.0003 loss: 2.6899 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6899 2023/06/04 21:37:41 - mmengine - INFO - Epoch(train) [28][1620/2569] lr: 4.0000e-02 eta: 23:20:45 time: 0.2693 data_time: 0.0076 memory: 5828 grad_norm: 2.9864 loss: 2.5451 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5451 2023/06/04 21:37:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:37:47 - mmengine - INFO - Epoch(train) [28][1640/2569] lr: 4.0000e-02 eta: 23:20:40 time: 0.2720 data_time: 0.0080 memory: 5828 grad_norm: 2.9352 loss: 2.4956 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4956 2023/06/04 21:37:52 - mmengine - INFO - Epoch(train) [28][1660/2569] lr: 4.0000e-02 eta: 23:20:35 time: 0.2673 data_time: 0.0077 memory: 5828 grad_norm: 2.9646 loss: 2.3706 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3706 2023/06/04 21:37:58 - mmengine - INFO - Epoch(train) [28][1680/2569] lr: 4.0000e-02 eta: 23:20:31 time: 0.2815 data_time: 0.0078 memory: 5828 grad_norm: 2.9437 loss: 2.7171 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7171 2023/06/04 21:38:03 - mmengine - INFO - Epoch(train) [28][1700/2569] lr: 4.0000e-02 eta: 23:20:26 time: 0.2709 data_time: 0.0079 memory: 5828 grad_norm: 3.0499 loss: 2.7105 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7105 2023/06/04 21:38:09 - mmengine - INFO - Epoch(train) [28][1720/2569] lr: 4.0000e-02 eta: 23:20:21 time: 0.2740 data_time: 0.0079 memory: 5828 grad_norm: 2.9848 loss: 2.5750 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5750 2023/06/04 21:38:14 - mmengine - INFO - Epoch(train) [28][1740/2569] lr: 4.0000e-02 eta: 23:20:16 time: 0.2709 data_time: 0.0075 memory: 5828 grad_norm: 3.0063 loss: 2.5361 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5361 2023/06/04 21:38:19 - mmengine - INFO - Epoch(train) [28][1760/2569] lr: 4.0000e-02 eta: 23:20:10 time: 0.2616 data_time: 0.0077 memory: 5828 grad_norm: 2.9880 loss: 2.8053 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8053 2023/06/04 21:38:25 - mmengine - INFO - Epoch(train) [28][1780/2569] lr: 4.0000e-02 eta: 23:20:06 time: 0.2756 data_time: 0.0077 memory: 5828 grad_norm: 2.9586 loss: 2.8311 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8311 2023/06/04 21:38:30 - mmengine - INFO - Epoch(train) [28][1800/2569] lr: 4.0000e-02 eta: 23:20:00 time: 0.2625 data_time: 0.0080 memory: 5828 grad_norm: 2.9938 loss: 2.4964 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4964 2023/06/04 21:38:36 - mmengine - INFO - Epoch(train) [28][1820/2569] lr: 4.0000e-02 eta: 23:19:55 time: 0.2734 data_time: 0.0079 memory: 5828 grad_norm: 3.0000 loss: 2.7261 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7261 2023/06/04 21:38:41 - mmengine - INFO - Epoch(train) [28][1840/2569] lr: 4.0000e-02 eta: 23:19:49 time: 0.2604 data_time: 0.0078 memory: 5828 grad_norm: 2.9728 loss: 2.9197 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.9197 2023/06/04 21:38:46 - mmengine - INFO - Epoch(train) [28][1860/2569] lr: 4.0000e-02 eta: 23:19:44 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 2.9264 loss: 2.4538 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4538 2023/06/04 21:38:52 - mmengine - INFO - Epoch(train) [28][1880/2569] lr: 4.0000e-02 eta: 23:19:39 time: 0.2719 data_time: 0.0086 memory: 5828 grad_norm: 2.9149 loss: 2.6846 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6846 2023/06/04 21:38:57 - mmengine - INFO - Epoch(train) [28][1900/2569] lr: 4.0000e-02 eta: 23:19:34 time: 0.2732 data_time: 0.0073 memory: 5828 grad_norm: 3.0445 loss: 2.9835 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.9835 2023/06/04 21:39:02 - mmengine - INFO - Epoch(train) [28][1920/2569] lr: 4.0000e-02 eta: 23:19:28 time: 0.2623 data_time: 0.0087 memory: 5828 grad_norm: 2.9518 loss: 2.3524 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.3524 2023/06/04 21:39:08 - mmengine - INFO - Epoch(train) [28][1940/2569] lr: 4.0000e-02 eta: 23:19:22 time: 0.2649 data_time: 0.0079 memory: 5828 grad_norm: 2.9524 loss: 2.5599 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5599 2023/06/04 21:39:13 - mmengine - INFO - Epoch(train) [28][1960/2569] lr: 4.0000e-02 eta: 23:19:17 time: 0.2624 data_time: 0.0078 memory: 5828 grad_norm: 2.9392 loss: 2.7269 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7269 2023/06/04 21:39:18 - mmengine - INFO - Epoch(train) [28][1980/2569] lr: 4.0000e-02 eta: 23:19:12 time: 0.2795 data_time: 0.0075 memory: 5828 grad_norm: 3.0070 loss: 2.8777 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.8777 2023/06/04 21:39:24 - mmengine - INFO - Epoch(train) [28][2000/2569] lr: 4.0000e-02 eta: 23:19:06 time: 0.2611 data_time: 0.0082 memory: 5828 grad_norm: 2.9674 loss: 2.5243 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5243 2023/06/04 21:39:29 - mmengine - INFO - Epoch(train) [28][2020/2569] lr: 4.0000e-02 eta: 23:19:01 time: 0.2710 data_time: 0.0077 memory: 5828 grad_norm: 2.9619 loss: 2.4273 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4273 2023/06/04 21:39:35 - mmengine - INFO - Epoch(train) [28][2040/2569] lr: 4.0000e-02 eta: 23:18:57 time: 0.2760 data_time: 0.0073 memory: 5828 grad_norm: 2.9548 loss: 2.5657 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5657 2023/06/04 21:39:40 - mmengine - INFO - Epoch(train) [28][2060/2569] lr: 4.0000e-02 eta: 23:18:51 time: 0.2649 data_time: 0.0080 memory: 5828 grad_norm: 2.9874 loss: 2.8284 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8284 2023/06/04 21:39:45 - mmengine - INFO - Epoch(train) [28][2080/2569] lr: 4.0000e-02 eta: 23:18:46 time: 0.2703 data_time: 0.0078 memory: 5828 grad_norm: 2.9736 loss: 2.2153 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2153 2023/06/04 21:39:51 - mmengine - INFO - Epoch(train) [28][2100/2569] lr: 4.0000e-02 eta: 23:18:41 time: 0.2712 data_time: 0.0074 memory: 5828 grad_norm: 2.9848 loss: 2.6656 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6656 2023/06/04 21:39:56 - mmengine - INFO - Epoch(train) [28][2120/2569] lr: 4.0000e-02 eta: 23:18:36 time: 0.2675 data_time: 0.0078 memory: 5828 grad_norm: 2.9312 loss: 2.6343 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6343 2023/06/04 21:40:01 - mmengine - INFO - Epoch(train) [28][2140/2569] lr: 4.0000e-02 eta: 23:18:30 time: 0.2627 data_time: 0.0079 memory: 5828 grad_norm: 2.9636 loss: 2.6767 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6767 2023/06/04 21:40:07 - mmengine - INFO - Epoch(train) [28][2160/2569] lr: 4.0000e-02 eta: 23:18:26 time: 0.2796 data_time: 0.0079 memory: 5828 grad_norm: 3.0078 loss: 2.7927 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7927 2023/06/04 21:40:12 - mmengine - INFO - Epoch(train) [28][2180/2569] lr: 4.0000e-02 eta: 23:18:20 time: 0.2616 data_time: 0.0078 memory: 5828 grad_norm: 2.9657 loss: 2.5006 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5006 2023/06/04 21:40:18 - mmengine - INFO - Epoch(train) [28][2200/2569] lr: 4.0000e-02 eta: 23:18:14 time: 0.2656 data_time: 0.0075 memory: 5828 grad_norm: 2.9783 loss: 2.4356 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4356 2023/06/04 21:40:23 - mmengine - INFO - Epoch(train) [28][2220/2569] lr: 4.0000e-02 eta: 23:18:09 time: 0.2661 data_time: 0.0073 memory: 5828 grad_norm: 2.9759 loss: 2.6082 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6082 2023/06/04 21:40:28 - mmengine - INFO - Epoch(train) [28][2240/2569] lr: 4.0000e-02 eta: 23:18:04 time: 0.2693 data_time: 0.0079 memory: 5828 grad_norm: 2.9568 loss: 2.5470 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5470 2023/06/04 21:40:34 - mmengine - INFO - Epoch(train) [28][2260/2569] lr: 4.0000e-02 eta: 23:17:58 time: 0.2637 data_time: 0.0082 memory: 5828 grad_norm: 2.9289 loss: 2.6478 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6478 2023/06/04 21:40:39 - mmengine - INFO - Epoch(train) [28][2280/2569] lr: 4.0000e-02 eta: 23:17:53 time: 0.2661 data_time: 0.0075 memory: 5828 grad_norm: 2.9994 loss: 2.3301 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3301 2023/06/04 21:40:44 - mmengine - INFO - Epoch(train) [28][2300/2569] lr: 4.0000e-02 eta: 23:17:47 time: 0.2627 data_time: 0.0081 memory: 5828 grad_norm: 2.9669 loss: 2.9692 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9692 2023/06/04 21:40:49 - mmengine - INFO - Epoch(train) [28][2320/2569] lr: 4.0000e-02 eta: 23:17:42 time: 0.2664 data_time: 0.0076 memory: 5828 grad_norm: 2.9239 loss: 2.8352 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8352 2023/06/04 21:40:55 - mmengine - INFO - Epoch(train) [28][2340/2569] lr: 4.0000e-02 eta: 23:17:36 time: 0.2613 data_time: 0.0079 memory: 5828 grad_norm: 3.0029 loss: 2.5768 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5768 2023/06/04 21:41:00 - mmengine - INFO - Epoch(train) [28][2360/2569] lr: 4.0000e-02 eta: 23:17:30 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 2.9730 loss: 2.7687 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7687 2023/06/04 21:41:05 - mmengine - INFO - Epoch(train) [28][2380/2569] lr: 4.0000e-02 eta: 23:17:24 time: 0.2667 data_time: 0.0081 memory: 5828 grad_norm: 2.9118 loss: 2.7000 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7000 2023/06/04 21:41:11 - mmengine - INFO - Epoch(train) [28][2400/2569] lr: 4.0000e-02 eta: 23:17:19 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 3.0129 loss: 2.4506 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4506 2023/06/04 21:41:16 - mmengine - INFO - Epoch(train) [28][2420/2569] lr: 4.0000e-02 eta: 23:17:14 time: 0.2645 data_time: 0.0077 memory: 5828 grad_norm: 2.9341 loss: 2.7905 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.7905 2023/06/04 21:41:21 - mmengine - INFO - Epoch(train) [28][2440/2569] lr: 4.0000e-02 eta: 23:17:08 time: 0.2631 data_time: 0.0080 memory: 5828 grad_norm: 2.9314 loss: 2.5052 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5052 2023/06/04 21:41:27 - mmengine - INFO - Epoch(train) [28][2460/2569] lr: 4.0000e-02 eta: 23:17:03 time: 0.2722 data_time: 0.0078 memory: 5828 grad_norm: 2.9562 loss: 2.2704 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2704 2023/06/04 21:41:32 - mmengine - INFO - Epoch(train) [28][2480/2569] lr: 4.0000e-02 eta: 23:16:58 time: 0.2673 data_time: 0.0081 memory: 5828 grad_norm: 2.9492 loss: 2.6729 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6729 2023/06/04 21:41:37 - mmengine - INFO - Epoch(train) [28][2500/2569] lr: 4.0000e-02 eta: 23:16:52 time: 0.2696 data_time: 0.0077 memory: 5828 grad_norm: 2.9801 loss: 2.6446 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6446 2023/06/04 21:41:43 - mmengine - INFO - Epoch(train) [28][2520/2569] lr: 4.0000e-02 eta: 23:16:47 time: 0.2617 data_time: 0.0078 memory: 5828 grad_norm: 2.9550 loss: 2.2948 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2948 2023/06/04 21:41:48 - mmengine - INFO - Epoch(train) [28][2540/2569] lr: 4.0000e-02 eta: 23:16:41 time: 0.2664 data_time: 0.0072 memory: 5828 grad_norm: 2.9612 loss: 2.6346 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6346 2023/06/04 21:41:53 - mmengine - INFO - Epoch(train) [28][2560/2569] lr: 4.0000e-02 eta: 23:16:35 time: 0.2581 data_time: 0.0086 memory: 5828 grad_norm: 3.0125 loss: 2.8933 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8933 2023/06/04 21:41:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:41:55 - mmengine - INFO - Epoch(train) [28][2569/2569] lr: 4.0000e-02 eta: 23:16:32 time: 0.2508 data_time: 0.0076 memory: 5828 grad_norm: 3.0409 loss: 2.5798 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.5798 2023/06/04 21:41:55 - mmengine - INFO - Saving checkpoint at 28 epochs 2023/06/04 21:42:03 - mmengine - INFO - Epoch(train) [29][ 20/2569] lr: 4.0000e-02 eta: 23:16:29 time: 0.2979 data_time: 0.0448 memory: 5828 grad_norm: 3.0216 loss: 2.6124 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6124 2023/06/04 21:42:09 - mmengine - INFO - Epoch(train) [29][ 40/2569] lr: 4.0000e-02 eta: 23:16:23 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 2.9959 loss: 2.3438 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.3438 2023/06/04 21:42:14 - mmengine - INFO - Epoch(train) [29][ 60/2569] lr: 4.0000e-02 eta: 23:16:18 time: 0.2713 data_time: 0.0078 memory: 5828 grad_norm: 2.9497 loss: 2.6604 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6604 2023/06/04 21:42:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:42:19 - mmengine - INFO - Epoch(train) [29][ 80/2569] lr: 4.0000e-02 eta: 23:16:13 time: 0.2619 data_time: 0.0082 memory: 5828 grad_norm: 2.9306 loss: 2.8502 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8502 2023/06/04 21:42:25 - mmengine - INFO - Epoch(train) [29][ 100/2569] lr: 4.0000e-02 eta: 23:16:07 time: 0.2648 data_time: 0.0080 memory: 5828 grad_norm: 2.9732 loss: 2.4355 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4355 2023/06/04 21:42:30 - mmengine - INFO - Epoch(train) [29][ 120/2569] lr: 4.0000e-02 eta: 23:16:01 time: 0.2630 data_time: 0.0077 memory: 5828 grad_norm: 2.9498 loss: 2.8238 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8238 2023/06/04 21:42:35 - mmengine - INFO - Epoch(train) [29][ 140/2569] lr: 4.0000e-02 eta: 23:15:56 time: 0.2637 data_time: 0.0078 memory: 5828 grad_norm: 2.9919 loss: 2.8251 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8251 2023/06/04 21:42:41 - mmengine - INFO - Epoch(train) [29][ 160/2569] lr: 4.0000e-02 eta: 23:15:51 time: 0.2730 data_time: 0.0077 memory: 5828 grad_norm: 2.9934 loss: 2.7675 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7675 2023/06/04 21:42:46 - mmengine - INFO - Epoch(train) [29][ 180/2569] lr: 4.0000e-02 eta: 23:15:46 time: 0.2703 data_time: 0.0078 memory: 5828 grad_norm: 2.9416 loss: 2.4081 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4081 2023/06/04 21:42:51 - mmengine - INFO - Epoch(train) [29][ 200/2569] lr: 4.0000e-02 eta: 23:15:40 time: 0.2625 data_time: 0.0078 memory: 5828 grad_norm: 2.9991 loss: 2.5304 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5304 2023/06/04 21:42:57 - mmengine - INFO - Epoch(train) [29][ 220/2569] lr: 4.0000e-02 eta: 23:15:35 time: 0.2762 data_time: 0.0076 memory: 5828 grad_norm: 2.9638 loss: 2.5156 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5156 2023/06/04 21:43:03 - mmengine - INFO - Epoch(train) [29][ 240/2569] lr: 4.0000e-02 eta: 23:15:31 time: 0.2818 data_time: 0.0080 memory: 5828 grad_norm: 2.9262 loss: 2.7008 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7008 2023/06/04 21:43:08 - mmengine - INFO - Epoch(train) [29][ 260/2569] lr: 4.0000e-02 eta: 23:15:26 time: 0.2642 data_time: 0.0088 memory: 5828 grad_norm: 2.9671 loss: 2.4315 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4315 2023/06/04 21:43:13 - mmengine - INFO - Epoch(train) [29][ 280/2569] lr: 4.0000e-02 eta: 23:15:20 time: 0.2672 data_time: 0.0080 memory: 5828 grad_norm: 2.9636 loss: 2.5593 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5593 2023/06/04 21:43:18 - mmengine - INFO - Epoch(train) [29][ 300/2569] lr: 4.0000e-02 eta: 23:15:14 time: 0.2617 data_time: 0.0080 memory: 5828 grad_norm: 2.9784 loss: 2.6732 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6732 2023/06/04 21:43:24 - mmengine - INFO - Epoch(train) [29][ 320/2569] lr: 4.0000e-02 eta: 23:15:09 time: 0.2699 data_time: 0.0085 memory: 5828 grad_norm: 2.9882 loss: 2.5115 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5115 2023/06/04 21:43:29 - mmengine - INFO - Epoch(train) [29][ 340/2569] lr: 4.0000e-02 eta: 23:15:03 time: 0.2615 data_time: 0.0080 memory: 5828 grad_norm: 2.9649 loss: 2.5012 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5012 2023/06/04 21:43:34 - mmengine - INFO - Epoch(train) [29][ 360/2569] lr: 4.0000e-02 eta: 23:14:58 time: 0.2626 data_time: 0.0085 memory: 5828 grad_norm: 2.9938 loss: 2.4800 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4800 2023/06/04 21:43:40 - mmengine - INFO - Epoch(train) [29][ 380/2569] lr: 4.0000e-02 eta: 23:14:53 time: 0.2698 data_time: 0.0078 memory: 5828 grad_norm: 2.9666 loss: 2.3948 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3948 2023/06/04 21:43:45 - mmengine - INFO - Epoch(train) [29][ 400/2569] lr: 4.0000e-02 eta: 23:14:47 time: 0.2659 data_time: 0.0076 memory: 5828 grad_norm: 3.0062 loss: 2.5881 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5881 2023/06/04 21:43:51 - mmengine - INFO - Epoch(train) [29][ 420/2569] lr: 4.0000e-02 eta: 23:14:43 time: 0.2777 data_time: 0.0074 memory: 5828 grad_norm: 3.0194 loss: 2.9780 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9780 2023/06/04 21:43:56 - mmengine - INFO - Epoch(train) [29][ 440/2569] lr: 4.0000e-02 eta: 23:14:37 time: 0.2611 data_time: 0.0078 memory: 5828 grad_norm: 2.9943 loss: 2.6392 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6392 2023/06/04 21:44:01 - mmengine - INFO - Epoch(train) [29][ 460/2569] lr: 4.0000e-02 eta: 23:14:32 time: 0.2766 data_time: 0.0078 memory: 5828 grad_norm: 2.9878 loss: 2.6023 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6023 2023/06/04 21:44:07 - mmengine - INFO - Epoch(train) [29][ 480/2569] lr: 4.0000e-02 eta: 23:14:27 time: 0.2666 data_time: 0.0079 memory: 5828 grad_norm: 2.9094 loss: 2.6564 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6564 2023/06/04 21:44:12 - mmengine - INFO - Epoch(train) [29][ 500/2569] lr: 4.0000e-02 eta: 23:14:22 time: 0.2683 data_time: 0.0077 memory: 5828 grad_norm: 2.9650 loss: 2.4365 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4365 2023/06/04 21:44:17 - mmengine - INFO - Epoch(train) [29][ 520/2569] lr: 4.0000e-02 eta: 23:14:16 time: 0.2688 data_time: 0.0082 memory: 5828 grad_norm: 3.0058 loss: 2.1952 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1952 2023/06/04 21:44:23 - mmengine - INFO - Epoch(train) [29][ 540/2569] lr: 4.0000e-02 eta: 23:14:11 time: 0.2628 data_time: 0.0080 memory: 5828 grad_norm: 2.9270 loss: 2.6074 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6074 2023/06/04 21:44:28 - mmengine - INFO - Epoch(train) [29][ 560/2569] lr: 4.0000e-02 eta: 23:14:05 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 2.9728 loss: 2.6981 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6981 2023/06/04 21:44:33 - mmengine - INFO - Epoch(train) [29][ 580/2569] lr: 4.0000e-02 eta: 23:13:59 time: 0.2612 data_time: 0.0078 memory: 5828 grad_norm: 3.0312 loss: 2.8413 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8413 2023/06/04 21:44:38 - mmengine - INFO - Epoch(train) [29][ 600/2569] lr: 4.0000e-02 eta: 23:13:54 time: 0.2636 data_time: 0.0077 memory: 5828 grad_norm: 2.9852 loss: 2.5592 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5592 2023/06/04 21:44:44 - mmengine - INFO - Epoch(train) [29][ 620/2569] lr: 4.0000e-02 eta: 23:13:48 time: 0.2636 data_time: 0.0082 memory: 5828 grad_norm: 3.0001 loss: 2.5628 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5628 2023/06/04 21:44:49 - mmengine - INFO - Epoch(train) [29][ 640/2569] lr: 4.0000e-02 eta: 23:13:42 time: 0.2648 data_time: 0.0079 memory: 5828 grad_norm: 2.9047 loss: 2.4613 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4613 2023/06/04 21:44:54 - mmengine - INFO - Epoch(train) [29][ 660/2569] lr: 4.0000e-02 eta: 23:13:37 time: 0.2624 data_time: 0.0081 memory: 5828 grad_norm: 3.0532 loss: 2.7295 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7295 2023/06/04 21:45:00 - mmengine - INFO - Epoch(train) [29][ 680/2569] lr: 4.0000e-02 eta: 23:13:32 time: 0.2702 data_time: 0.0082 memory: 5828 grad_norm: 2.9985 loss: 2.8830 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8830 2023/06/04 21:45:05 - mmengine - INFO - Epoch(train) [29][ 700/2569] lr: 4.0000e-02 eta: 23:13:26 time: 0.2613 data_time: 0.0083 memory: 5828 grad_norm: 2.9214 loss: 2.3854 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3854 2023/06/04 21:45:10 - mmengine - INFO - Epoch(train) [29][ 720/2569] lr: 4.0000e-02 eta: 23:13:20 time: 0.2673 data_time: 0.0078 memory: 5828 grad_norm: 2.9950 loss: 2.5583 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5583 2023/06/04 21:45:16 - mmengine - INFO - Epoch(train) [29][ 740/2569] lr: 4.0000e-02 eta: 23:13:15 time: 0.2657 data_time: 0.0078 memory: 5828 grad_norm: 2.9857 loss: 2.6699 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6699 2023/06/04 21:45:21 - mmengine - INFO - Epoch(train) [29][ 760/2569] lr: 4.0000e-02 eta: 23:13:11 time: 0.2811 data_time: 0.0078 memory: 5828 grad_norm: 2.9786 loss: 2.8319 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8319 2023/06/04 21:45:27 - mmengine - INFO - Epoch(train) [29][ 780/2569] lr: 4.0000e-02 eta: 23:13:05 time: 0.2639 data_time: 0.0079 memory: 5828 grad_norm: 2.9277 loss: 2.3513 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3513 2023/06/04 21:45:32 - mmengine - INFO - Epoch(train) [29][ 800/2569] lr: 4.0000e-02 eta: 23:13:00 time: 0.2708 data_time: 0.0077 memory: 5828 grad_norm: 2.9987 loss: 2.6983 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6983 2023/06/04 21:45:37 - mmengine - INFO - Epoch(train) [29][ 820/2569] lr: 4.0000e-02 eta: 23:12:54 time: 0.2620 data_time: 0.0079 memory: 5828 grad_norm: 2.9732 loss: 2.7153 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7153 2023/06/04 21:45:42 - mmengine - INFO - Epoch(train) [29][ 840/2569] lr: 4.0000e-02 eta: 23:12:49 time: 0.2641 data_time: 0.0084 memory: 5828 grad_norm: 2.8779 loss: 2.6555 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6555 2023/06/04 21:45:48 - mmengine - INFO - Epoch(train) [29][ 860/2569] lr: 4.0000e-02 eta: 23:12:43 time: 0.2682 data_time: 0.0082 memory: 5828 grad_norm: 2.9683 loss: 2.8305 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8305 2023/06/04 21:45:53 - mmengine - INFO - Epoch(train) [29][ 880/2569] lr: 4.0000e-02 eta: 23:12:38 time: 0.2647 data_time: 0.0079 memory: 5828 grad_norm: 2.9296 loss: 2.3752 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3752 2023/06/04 21:45:58 - mmengine - INFO - Epoch(train) [29][ 900/2569] lr: 4.0000e-02 eta: 23:12:32 time: 0.2671 data_time: 0.0080 memory: 5828 grad_norm: 2.9009 loss: 2.5309 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5309 2023/06/04 21:46:04 - mmengine - INFO - Epoch(train) [29][ 920/2569] lr: 4.0000e-02 eta: 23:12:27 time: 0.2670 data_time: 0.0079 memory: 5828 grad_norm: 3.0206 loss: 2.8409 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8409 2023/06/04 21:46:09 - mmengine - INFO - Epoch(train) [29][ 940/2569] lr: 4.0000e-02 eta: 23:12:22 time: 0.2694 data_time: 0.0080 memory: 5828 grad_norm: 2.9538 loss: 2.7929 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7929 2023/06/04 21:46:14 - mmengine - INFO - Epoch(train) [29][ 960/2569] lr: 4.0000e-02 eta: 23:12:16 time: 0.2629 data_time: 0.0078 memory: 5828 grad_norm: 3.0162 loss: 2.7017 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7017 2023/06/04 21:46:20 - mmengine - INFO - Epoch(train) [29][ 980/2569] lr: 4.0000e-02 eta: 23:12:12 time: 0.2780 data_time: 0.0075 memory: 5828 grad_norm: 2.9518 loss: 2.2038 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2038 2023/06/04 21:46:25 - mmengine - INFO - Epoch(train) [29][1000/2569] lr: 4.0000e-02 eta: 23:12:06 time: 0.2643 data_time: 0.0075 memory: 5828 grad_norm: 3.0152 loss: 2.7982 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7982 2023/06/04 21:46:31 - mmengine - INFO - Epoch(train) [29][1020/2569] lr: 4.0000e-02 eta: 23:12:01 time: 0.2701 data_time: 0.0079 memory: 5828 grad_norm: 2.8917 loss: 2.5330 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5330 2023/06/04 21:46:36 - mmengine - INFO - Epoch(train) [29][1040/2569] lr: 4.0000e-02 eta: 23:11:56 time: 0.2689 data_time: 0.0083 memory: 5828 grad_norm: 2.9801 loss: 2.4983 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4983 2023/06/04 21:46:41 - mmengine - INFO - Epoch(train) [29][1060/2569] lr: 4.0000e-02 eta: 23:11:50 time: 0.2634 data_time: 0.0081 memory: 5828 grad_norm: 3.0231 loss: 2.6848 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6848 2023/06/04 21:46:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:46:47 - mmengine - INFO - Epoch(train) [29][1080/2569] lr: 4.0000e-02 eta: 23:11:45 time: 0.2718 data_time: 0.0075 memory: 5828 grad_norm: 2.9449 loss: 2.7635 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7635 2023/06/04 21:46:52 - mmengine - INFO - Epoch(train) [29][1100/2569] lr: 4.0000e-02 eta: 23:11:39 time: 0.2629 data_time: 0.0079 memory: 5828 grad_norm: 3.0274 loss: 2.2947 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2947 2023/06/04 21:46:57 - mmengine - INFO - Epoch(train) [29][1120/2569] lr: 4.0000e-02 eta: 23:11:34 time: 0.2675 data_time: 0.0081 memory: 5828 grad_norm: 2.9697 loss: 2.5693 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5693 2023/06/04 21:47:03 - mmengine - INFO - Epoch(train) [29][1140/2569] lr: 4.0000e-02 eta: 23:11:28 time: 0.2619 data_time: 0.0077 memory: 5828 grad_norm: 2.9918 loss: 2.7333 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7333 2023/06/04 21:47:08 - mmengine - INFO - Epoch(train) [29][1160/2569] lr: 4.0000e-02 eta: 23:11:23 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 2.9726 loss: 2.6552 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6552 2023/06/04 21:47:13 - mmengine - INFO - Epoch(train) [29][1180/2569] lr: 4.0000e-02 eta: 23:11:17 time: 0.2666 data_time: 0.0078 memory: 5828 grad_norm: 2.9599 loss: 2.6571 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6571 2023/06/04 21:47:19 - mmengine - INFO - Epoch(train) [29][1200/2569] lr: 4.0000e-02 eta: 23:11:12 time: 0.2646 data_time: 0.0079 memory: 5828 grad_norm: 2.9315 loss: 2.2275 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2275 2023/06/04 21:47:24 - mmengine - INFO - Epoch(train) [29][1220/2569] lr: 4.0000e-02 eta: 23:11:08 time: 0.2838 data_time: 0.0079 memory: 5828 grad_norm: 2.9986 loss: 2.5484 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5484 2023/06/04 21:47:30 - mmengine - INFO - Epoch(train) [29][1240/2569] lr: 4.0000e-02 eta: 23:11:02 time: 0.2660 data_time: 0.0083 memory: 5828 grad_norm: 3.0244 loss: 2.8192 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8192 2023/06/04 21:47:35 - mmengine - INFO - Epoch(train) [29][1260/2569] lr: 4.0000e-02 eta: 23:10:57 time: 0.2721 data_time: 0.0078 memory: 5828 grad_norm: 2.9679 loss: 2.4795 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4795 2023/06/04 21:47:40 - mmengine - INFO - Epoch(train) [29][1280/2569] lr: 4.0000e-02 eta: 23:10:52 time: 0.2624 data_time: 0.0081 memory: 5828 grad_norm: 2.9740 loss: 2.4728 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4728 2023/06/04 21:47:46 - mmengine - INFO - Epoch(train) [29][1300/2569] lr: 4.0000e-02 eta: 23:10:47 time: 0.2714 data_time: 0.0078 memory: 5828 grad_norm: 2.9976 loss: 2.5477 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5477 2023/06/04 21:47:51 - mmengine - INFO - Epoch(train) [29][1320/2569] lr: 4.0000e-02 eta: 23:10:41 time: 0.2671 data_time: 0.0079 memory: 5828 grad_norm: 2.9380 loss: 2.4118 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4118 2023/06/04 21:47:57 - mmengine - INFO - Epoch(train) [29][1340/2569] lr: 4.0000e-02 eta: 23:10:36 time: 0.2740 data_time: 0.0078 memory: 5828 grad_norm: 2.9742 loss: 2.6991 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6991 2023/06/04 21:48:02 - mmengine - INFO - Epoch(train) [29][1360/2569] lr: 4.0000e-02 eta: 23:10:31 time: 0.2634 data_time: 0.0082 memory: 5828 grad_norm: 2.9427 loss: 2.6276 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6276 2023/06/04 21:48:07 - mmengine - INFO - Epoch(train) [29][1380/2569] lr: 4.0000e-02 eta: 23:10:26 time: 0.2725 data_time: 0.0075 memory: 5828 grad_norm: 2.9687 loss: 2.5561 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5561 2023/06/04 21:48:13 - mmengine - INFO - Epoch(train) [29][1400/2569] lr: 4.0000e-02 eta: 23:10:20 time: 0.2623 data_time: 0.0077 memory: 5828 grad_norm: 2.9671 loss: 2.7526 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7526 2023/06/04 21:48:18 - mmengine - INFO - Epoch(train) [29][1420/2569] lr: 4.0000e-02 eta: 23:10:14 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 2.9439 loss: 2.3830 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3830 2023/06/04 21:48:23 - mmengine - INFO - Epoch(train) [29][1440/2569] lr: 4.0000e-02 eta: 23:10:09 time: 0.2674 data_time: 0.0080 memory: 5828 grad_norm: 3.0529 loss: 2.5894 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5894 2023/06/04 21:48:29 - mmengine - INFO - Epoch(train) [29][1460/2569] lr: 4.0000e-02 eta: 23:10:04 time: 0.2677 data_time: 0.0081 memory: 5828 grad_norm: 2.9433 loss: 2.7389 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7389 2023/06/04 21:48:34 - mmengine - INFO - Epoch(train) [29][1480/2569] lr: 4.0000e-02 eta: 23:09:59 time: 0.2702 data_time: 0.0078 memory: 5828 grad_norm: 3.0178 loss: 2.7415 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7415 2023/06/04 21:48:39 - mmengine - INFO - Epoch(train) [29][1500/2569] lr: 4.0000e-02 eta: 23:09:53 time: 0.2663 data_time: 0.0083 memory: 5828 grad_norm: 2.9539 loss: 2.5134 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5134 2023/06/04 21:48:45 - mmengine - INFO - Epoch(train) [29][1520/2569] lr: 4.0000e-02 eta: 23:09:48 time: 0.2669 data_time: 0.0083 memory: 5828 grad_norm: 2.9616 loss: 2.3299 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3299 2023/06/04 21:48:50 - mmengine - INFO - Epoch(train) [29][1540/2569] lr: 4.0000e-02 eta: 23:09:43 time: 0.2718 data_time: 0.0071 memory: 5828 grad_norm: 3.0243 loss: 2.6669 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6669 2023/06/04 21:48:55 - mmengine - INFO - Epoch(train) [29][1560/2569] lr: 4.0000e-02 eta: 23:09:38 time: 0.2707 data_time: 0.0080 memory: 5828 grad_norm: 3.0020 loss: 2.7129 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7129 2023/06/04 21:49:01 - mmengine - INFO - Epoch(train) [29][1580/2569] lr: 4.0000e-02 eta: 23:09:32 time: 0.2662 data_time: 0.0080 memory: 5828 grad_norm: 2.9770 loss: 2.6794 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6794 2023/06/04 21:49:06 - mmengine - INFO - Epoch(train) [29][1600/2569] lr: 4.0000e-02 eta: 23:09:26 time: 0.2616 data_time: 0.0072 memory: 5828 grad_norm: 3.0342 loss: 2.7388 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7388 2023/06/04 21:49:11 - mmengine - INFO - Epoch(train) [29][1620/2569] lr: 4.0000e-02 eta: 23:09:21 time: 0.2618 data_time: 0.0079 memory: 5828 grad_norm: 2.9510 loss: 2.7079 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7079 2023/06/04 21:49:17 - mmengine - INFO - Epoch(train) [29][1640/2569] lr: 4.0000e-02 eta: 23:09:15 time: 0.2666 data_time: 0.0081 memory: 5828 grad_norm: 2.9647 loss: 2.6580 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6580 2023/06/04 21:49:22 - mmengine - INFO - Epoch(train) [29][1660/2569] lr: 4.0000e-02 eta: 23:09:11 time: 0.2751 data_time: 0.0075 memory: 5828 grad_norm: 2.9639 loss: 2.4591 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4591 2023/06/04 21:49:27 - mmengine - INFO - Epoch(train) [29][1680/2569] lr: 4.0000e-02 eta: 23:09:05 time: 0.2631 data_time: 0.0082 memory: 5828 grad_norm: 2.9370 loss: 2.6528 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6528 2023/06/04 21:49:33 - mmengine - INFO - Epoch(train) [29][1700/2569] lr: 4.0000e-02 eta: 23:09:00 time: 0.2788 data_time: 0.0072 memory: 5828 grad_norm: 3.0256 loss: 2.6464 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6464 2023/06/04 21:49:38 - mmengine - INFO - Epoch(train) [29][1720/2569] lr: 4.0000e-02 eta: 23:08:55 time: 0.2720 data_time: 0.0081 memory: 5828 grad_norm: 2.9427 loss: 2.4400 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4400 2023/06/04 21:49:44 - mmengine - INFO - Epoch(train) [29][1740/2569] lr: 4.0000e-02 eta: 23:08:51 time: 0.2736 data_time: 0.0081 memory: 5828 grad_norm: 3.0042 loss: 2.8864 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8864 2023/06/04 21:49:49 - mmengine - INFO - Epoch(train) [29][1760/2569] lr: 4.0000e-02 eta: 23:08:45 time: 0.2688 data_time: 0.0079 memory: 5828 grad_norm: 2.9926 loss: 2.8244 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8244 2023/06/04 21:49:55 - mmengine - INFO - Epoch(train) [29][1780/2569] lr: 4.0000e-02 eta: 23:08:40 time: 0.2689 data_time: 0.0080 memory: 5828 grad_norm: 2.9969 loss: 2.6591 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6591 2023/06/04 21:50:00 - mmengine - INFO - Epoch(train) [29][1800/2569] lr: 4.0000e-02 eta: 23:08:35 time: 0.2730 data_time: 0.0077 memory: 5828 grad_norm: 3.0578 loss: 2.2233 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2233 2023/06/04 21:50:05 - mmengine - INFO - Epoch(train) [29][1820/2569] lr: 4.0000e-02 eta: 23:08:30 time: 0.2633 data_time: 0.0077 memory: 5828 grad_norm: 2.9374 loss: 2.8495 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8495 2023/06/04 21:50:11 - mmengine - INFO - Epoch(train) [29][1840/2569] lr: 4.0000e-02 eta: 23:08:24 time: 0.2694 data_time: 0.0078 memory: 5828 grad_norm: 3.0039 loss: 2.4521 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4521 2023/06/04 21:50:16 - mmengine - INFO - Epoch(train) [29][1860/2569] lr: 4.0000e-02 eta: 23:08:19 time: 0.2604 data_time: 0.0076 memory: 5828 grad_norm: 2.9710 loss: 2.5753 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5753 2023/06/04 21:50:21 - mmengine - INFO - Epoch(train) [29][1880/2569] lr: 4.0000e-02 eta: 23:08:13 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 2.9805 loss: 2.3759 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3759 2023/06/04 21:50:27 - mmengine - INFO - Epoch(train) [29][1900/2569] lr: 4.0000e-02 eta: 23:08:07 time: 0.2648 data_time: 0.0081 memory: 5828 grad_norm: 2.9610 loss: 2.6722 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6722 2023/06/04 21:50:32 - mmengine - INFO - Epoch(train) [29][1920/2569] lr: 4.0000e-02 eta: 23:08:02 time: 0.2702 data_time: 0.0074 memory: 5828 grad_norm: 2.9842 loss: 2.6505 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6505 2023/06/04 21:50:37 - mmengine - INFO - Epoch(train) [29][1940/2569] lr: 4.0000e-02 eta: 23:07:56 time: 0.2639 data_time: 0.0078 memory: 5828 grad_norm: 2.9910 loss: 2.2941 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2941 2023/06/04 21:50:43 - mmengine - INFO - Epoch(train) [29][1960/2569] lr: 4.0000e-02 eta: 23:07:51 time: 0.2668 data_time: 0.0077 memory: 5828 grad_norm: 2.9417 loss: 2.4489 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4489 2023/06/04 21:50:48 - mmengine - INFO - Epoch(train) [29][1980/2569] lr: 4.0000e-02 eta: 23:07:45 time: 0.2615 data_time: 0.0078 memory: 5828 grad_norm: 2.9437 loss: 2.7696 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7696 2023/06/04 21:50:53 - mmengine - INFO - Epoch(train) [29][2000/2569] lr: 4.0000e-02 eta: 23:07:41 time: 0.2767 data_time: 0.0079 memory: 5828 grad_norm: 2.9501 loss: 2.3397 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3397 2023/06/04 21:50:59 - mmengine - INFO - Epoch(train) [29][2020/2569] lr: 4.0000e-02 eta: 23:07:35 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 2.9539 loss: 2.3798 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3798 2023/06/04 21:51:04 - mmengine - INFO - Epoch(train) [29][2040/2569] lr: 4.0000e-02 eta: 23:07:30 time: 0.2675 data_time: 0.0081 memory: 5828 grad_norm: 2.9823 loss: 2.5241 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5241 2023/06/04 21:51:09 - mmengine - INFO - Epoch(train) [29][2060/2569] lr: 4.0000e-02 eta: 23:07:25 time: 0.2678 data_time: 0.0078 memory: 5828 grad_norm: 2.9656 loss: 2.7605 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7605 2023/06/04 21:51:11 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:51:15 - mmengine - INFO - Epoch(train) [29][2080/2569] lr: 4.0000e-02 eta: 23:07:19 time: 0.2648 data_time: 0.0080 memory: 5828 grad_norm: 3.0151 loss: 2.4221 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4221 2023/06/04 21:51:20 - mmengine - INFO - Epoch(train) [29][2100/2569] lr: 4.0000e-02 eta: 23:07:14 time: 0.2673 data_time: 0.0078 memory: 5828 grad_norm: 3.0297 loss: 2.5227 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5227 2023/06/04 21:51:25 - mmengine - INFO - Epoch(train) [29][2120/2569] lr: 4.0000e-02 eta: 23:07:08 time: 0.2587 data_time: 0.0081 memory: 5828 grad_norm: 2.9917 loss: 2.6963 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6963 2023/06/04 21:51:31 - mmengine - INFO - Epoch(train) [29][2140/2569] lr: 4.0000e-02 eta: 23:07:02 time: 0.2691 data_time: 0.0077 memory: 5828 grad_norm: 2.9972 loss: 2.8251 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8251 2023/06/04 21:51:36 - mmengine - INFO - Epoch(train) [29][2160/2569] lr: 4.0000e-02 eta: 23:06:56 time: 0.2604 data_time: 0.0085 memory: 5828 grad_norm: 2.9666 loss: 2.3895 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3895 2023/06/04 21:51:41 - mmengine - INFO - Epoch(train) [29][2180/2569] lr: 4.0000e-02 eta: 23:06:51 time: 0.2694 data_time: 0.0089 memory: 5828 grad_norm: 2.9443 loss: 2.8829 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8829 2023/06/04 21:51:46 - mmengine - INFO - Epoch(train) [29][2200/2569] lr: 4.0000e-02 eta: 23:06:45 time: 0.2604 data_time: 0.0085 memory: 5828 grad_norm: 2.9608 loss: 2.6229 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6229 2023/06/04 21:51:52 - mmengine - INFO - Epoch(train) [29][2220/2569] lr: 4.0000e-02 eta: 23:06:40 time: 0.2611 data_time: 0.0079 memory: 5828 grad_norm: 3.0088 loss: 2.4990 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4990 2023/06/04 21:51:57 - mmengine - INFO - Epoch(train) [29][2240/2569] lr: 4.0000e-02 eta: 23:06:34 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 2.9987 loss: 2.2202 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2202 2023/06/04 21:52:02 - mmengine - INFO - Epoch(train) [29][2260/2569] lr: 4.0000e-02 eta: 23:06:29 time: 0.2679 data_time: 0.0076 memory: 5828 grad_norm: 3.0277 loss: 2.8905 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.8905 2023/06/04 21:52:08 - mmengine - INFO - Epoch(train) [29][2280/2569] lr: 4.0000e-02 eta: 23:06:23 time: 0.2680 data_time: 0.0076 memory: 5828 grad_norm: 2.9251 loss: 2.1668 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1668 2023/06/04 21:52:13 - mmengine - INFO - Epoch(train) [29][2300/2569] lr: 4.0000e-02 eta: 23:06:18 time: 0.2713 data_time: 0.0079 memory: 5828 grad_norm: 2.9368 loss: 2.5229 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5229 2023/06/04 21:52:18 - mmengine - INFO - Epoch(train) [29][2320/2569] lr: 4.0000e-02 eta: 23:06:13 time: 0.2632 data_time: 0.0079 memory: 5828 grad_norm: 2.9665 loss: 2.6364 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6364 2023/06/04 21:52:24 - mmengine - INFO - Epoch(train) [29][2340/2569] lr: 4.0000e-02 eta: 23:06:07 time: 0.2670 data_time: 0.0079 memory: 5828 grad_norm: 2.9583 loss: 2.8138 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8138 2023/06/04 21:52:29 - mmengine - INFO - Epoch(train) [29][2360/2569] lr: 4.0000e-02 eta: 23:06:02 time: 0.2630 data_time: 0.0086 memory: 5828 grad_norm: 2.9741 loss: 2.6048 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6048 2023/06/04 21:52:34 - mmengine - INFO - Epoch(train) [29][2380/2569] lr: 4.0000e-02 eta: 23:05:56 time: 0.2674 data_time: 0.0074 memory: 5828 grad_norm: 3.0034 loss: 2.2704 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2704 2023/06/04 21:52:40 - mmengine - INFO - Epoch(train) [29][2400/2569] lr: 4.0000e-02 eta: 23:05:51 time: 0.2654 data_time: 0.0080 memory: 5828 grad_norm: 2.9626 loss: 2.5171 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5171 2023/06/04 21:52:45 - mmengine - INFO - Epoch(train) [29][2420/2569] lr: 4.0000e-02 eta: 23:05:46 time: 0.2732 data_time: 0.0073 memory: 5828 grad_norm: 2.9504 loss: 2.5732 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5732 2023/06/04 21:52:50 - mmengine - INFO - Epoch(train) [29][2440/2569] lr: 4.0000e-02 eta: 23:05:40 time: 0.2658 data_time: 0.0082 memory: 5828 grad_norm: 2.9571 loss: 2.4957 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4957 2023/06/04 21:52:56 - mmengine - INFO - Epoch(train) [29][2460/2569] lr: 4.0000e-02 eta: 23:05:34 time: 0.2604 data_time: 0.0081 memory: 5828 grad_norm: 2.9983 loss: 2.5976 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5976 2023/06/04 21:53:01 - mmengine - INFO - Epoch(train) [29][2480/2569] lr: 4.0000e-02 eta: 23:05:29 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 3.0174 loss: 2.5507 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5507 2023/06/04 21:53:06 - mmengine - INFO - Epoch(train) [29][2500/2569] lr: 4.0000e-02 eta: 23:05:23 time: 0.2605 data_time: 0.0074 memory: 5828 grad_norm: 2.9500 loss: 2.3341 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3341 2023/06/04 21:53:11 - mmengine - INFO - Epoch(train) [29][2520/2569] lr: 4.0000e-02 eta: 23:05:17 time: 0.2646 data_time: 0.0082 memory: 5828 grad_norm: 2.9851 loss: 2.6641 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6641 2023/06/04 21:53:17 - mmengine - INFO - Epoch(train) [29][2540/2569] lr: 4.0000e-02 eta: 23:05:12 time: 0.2619 data_time: 0.0079 memory: 5828 grad_norm: 3.0540 loss: 2.3827 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3827 2023/06/04 21:53:22 - mmengine - INFO - Epoch(train) [29][2560/2569] lr: 4.0000e-02 eta: 23:05:07 time: 0.2707 data_time: 0.0080 memory: 5828 grad_norm: 2.9747 loss: 2.4013 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4013 2023/06/04 21:53:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:53:24 - mmengine - INFO - Epoch(train) [29][2569/2569] lr: 4.0000e-02 eta: 23:05:03 time: 0.2493 data_time: 0.0084 memory: 5828 grad_norm: 2.9727 loss: 2.5826 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.5826 2023/06/04 21:53:31 - mmengine - INFO - Epoch(train) [30][ 20/2569] lr: 4.0000e-02 eta: 23:05:04 time: 0.3446 data_time: 0.0643 memory: 5828 grad_norm: 2.9359 loss: 2.6354 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6354 2023/06/04 21:53:37 - mmengine - INFO - Epoch(train) [30][ 40/2569] lr: 4.0000e-02 eta: 23:05:00 time: 0.2745 data_time: 0.0078 memory: 5828 grad_norm: 3.0237 loss: 2.4784 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4784 2023/06/04 21:53:42 - mmengine - INFO - Epoch(train) [30][ 60/2569] lr: 4.0000e-02 eta: 23:04:54 time: 0.2661 data_time: 0.0082 memory: 5828 grad_norm: 2.9899 loss: 2.6504 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6504 2023/06/04 21:53:47 - mmengine - INFO - Epoch(train) [30][ 80/2569] lr: 4.0000e-02 eta: 23:04:48 time: 0.2626 data_time: 0.0077 memory: 5828 grad_norm: 2.9058 loss: 2.4288 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4288 2023/06/04 21:53:53 - mmengine - INFO - Epoch(train) [30][ 100/2569] lr: 4.0000e-02 eta: 23:04:43 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 2.9532 loss: 2.4280 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4280 2023/06/04 21:53:58 - mmengine - INFO - Epoch(train) [30][ 120/2569] lr: 4.0000e-02 eta: 23:04:37 time: 0.2670 data_time: 0.0082 memory: 5828 grad_norm: 2.9609 loss: 2.4560 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4560 2023/06/04 21:54:03 - mmengine - INFO - Epoch(train) [30][ 140/2569] lr: 4.0000e-02 eta: 23:04:32 time: 0.2646 data_time: 0.0076 memory: 5828 grad_norm: 2.9573 loss: 2.5927 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5927 2023/06/04 21:54:08 - mmengine - INFO - Epoch(train) [30][ 160/2569] lr: 4.0000e-02 eta: 23:04:26 time: 0.2636 data_time: 0.0081 memory: 5828 grad_norm: 2.9669 loss: 2.5346 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5346 2023/06/04 21:54:14 - mmengine - INFO - Epoch(train) [30][ 180/2569] lr: 4.0000e-02 eta: 23:04:21 time: 0.2676 data_time: 0.0076 memory: 5828 grad_norm: 3.0365 loss: 2.5377 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5377 2023/06/04 21:54:19 - mmengine - INFO - Epoch(train) [30][ 200/2569] lr: 4.0000e-02 eta: 23:04:15 time: 0.2626 data_time: 0.0079 memory: 5828 grad_norm: 2.9630 loss: 2.7263 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7263 2023/06/04 21:54:25 - mmengine - INFO - Epoch(train) [30][ 220/2569] lr: 4.0000e-02 eta: 23:04:10 time: 0.2748 data_time: 0.0076 memory: 5828 grad_norm: 2.9759 loss: 2.6092 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6092 2023/06/04 21:54:30 - mmengine - INFO - Epoch(train) [30][ 240/2569] lr: 4.0000e-02 eta: 23:04:05 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 2.9350 loss: 2.3625 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.3625 2023/06/04 21:54:35 - mmengine - INFO - Epoch(train) [30][ 260/2569] lr: 4.0000e-02 eta: 23:04:00 time: 0.2702 data_time: 0.0074 memory: 5828 grad_norm: 2.9717 loss: 2.4155 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4155 2023/06/04 21:54:41 - mmengine - INFO - Epoch(train) [30][ 280/2569] lr: 4.0000e-02 eta: 23:03:54 time: 0.2670 data_time: 0.0081 memory: 5828 grad_norm: 2.9704 loss: 2.3735 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3735 2023/06/04 21:54:46 - mmengine - INFO - Epoch(train) [30][ 300/2569] lr: 4.0000e-02 eta: 23:03:49 time: 0.2709 data_time: 0.0080 memory: 5828 grad_norm: 2.9884 loss: 2.8208 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8208 2023/06/04 21:54:51 - mmengine - INFO - Epoch(train) [30][ 320/2569] lr: 4.0000e-02 eta: 23:03:44 time: 0.2660 data_time: 0.0080 memory: 5828 grad_norm: 2.9625 loss: 2.3599 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3599 2023/06/04 21:54:57 - mmengine - INFO - Epoch(train) [30][ 340/2569] lr: 4.0000e-02 eta: 23:03:39 time: 0.2744 data_time: 0.0079 memory: 5828 grad_norm: 2.9894 loss: 2.5048 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5048 2023/06/04 21:55:02 - mmengine - INFO - Epoch(train) [30][ 360/2569] lr: 4.0000e-02 eta: 23:03:33 time: 0.2635 data_time: 0.0080 memory: 5828 grad_norm: 2.9933 loss: 2.6073 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6073 2023/06/04 21:55:07 - mmengine - INFO - Epoch(train) [30][ 380/2569] lr: 4.0000e-02 eta: 23:03:27 time: 0.2599 data_time: 0.0078 memory: 5828 grad_norm: 2.9816 loss: 2.7098 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7098 2023/06/04 21:55:13 - mmengine - INFO - Epoch(train) [30][ 400/2569] lr: 4.0000e-02 eta: 23:03:22 time: 0.2698 data_time: 0.0080 memory: 5828 grad_norm: 2.9253 loss: 2.7027 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7027 2023/06/04 21:55:18 - mmengine - INFO - Epoch(train) [30][ 420/2569] lr: 4.0000e-02 eta: 23:03:17 time: 0.2676 data_time: 0.0075 memory: 5828 grad_norm: 2.9855 loss: 2.6692 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6692 2023/06/04 21:55:24 - mmengine - INFO - Epoch(train) [30][ 440/2569] lr: 4.0000e-02 eta: 23:03:12 time: 0.2721 data_time: 0.0076 memory: 5828 grad_norm: 2.9262 loss: 2.7262 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7262 2023/06/04 21:55:29 - mmengine - INFO - Epoch(train) [30][ 460/2569] lr: 4.0000e-02 eta: 23:03:06 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 3.0312 loss: 2.7567 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.7567 2023/06/04 21:55:34 - mmengine - INFO - Epoch(train) [30][ 480/2569] lr: 4.0000e-02 eta: 23:03:01 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 2.9854 loss: 2.6478 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6478 2023/06/04 21:55:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 21:55:39 - mmengine - INFO - Epoch(train) [30][ 500/2569] lr: 4.0000e-02 eta: 23:02:55 time: 0.2645 data_time: 0.0080 memory: 5828 grad_norm: 2.9630 loss: 2.8824 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8824 2023/06/04 21:55:45 - mmengine - INFO - Epoch(train) [30][ 520/2569] lr: 4.0000e-02 eta: 23:02:50 time: 0.2676 data_time: 0.0077 memory: 5828 grad_norm: 2.9835 loss: 2.6252 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6252 2023/06/04 21:55:50 - mmengine - INFO - Epoch(train) [30][ 540/2569] lr: 4.0000e-02 eta: 23:02:45 time: 0.2710 data_time: 0.0079 memory: 5828 grad_norm: 2.9192 loss: 2.3180 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3180 2023/06/04 21:55:56 - mmengine - INFO - Epoch(train) [30][ 560/2569] lr: 4.0000e-02 eta: 23:02:39 time: 0.2672 data_time: 0.0081 memory: 5828 grad_norm: 3.1285 loss: 2.6688 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6688 2023/06/04 21:56:01 - mmengine - INFO - Epoch(train) [30][ 580/2569] lr: 4.0000e-02 eta: 23:02:34 time: 0.2674 data_time: 0.0077 memory: 5828 grad_norm: 3.0979 loss: 2.6651 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6651 2023/06/04 21:56:06 - mmengine - INFO - Epoch(train) [30][ 600/2569] lr: 4.0000e-02 eta: 23:02:29 time: 0.2695 data_time: 0.0077 memory: 5828 grad_norm: 2.9769 loss: 2.6069 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6069 2023/06/04 21:56:12 - mmengine - INFO - Epoch(train) [30][ 620/2569] lr: 4.0000e-02 eta: 23:02:23 time: 0.2659 data_time: 0.0067 memory: 5828 grad_norm: 2.9554 loss: 2.4923 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4923 2023/06/04 21:56:17 - mmengine - INFO - Epoch(train) [30][ 640/2569] lr: 4.0000e-02 eta: 23:02:18 time: 0.2707 data_time: 0.0077 memory: 5828 grad_norm: 2.8902 loss: 2.3989 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3989 2023/06/04 21:56:22 - mmengine - INFO - Epoch(train) [30][ 660/2569] lr: 4.0000e-02 eta: 23:02:13 time: 0.2706 data_time: 0.0077 memory: 5828 grad_norm: 3.0299 loss: 2.7546 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7546 2023/06/04 21:56:28 - mmengine - INFO - Epoch(train) [30][ 680/2569] lr: 4.0000e-02 eta: 23:02:07 time: 0.2603 data_time: 0.0080 memory: 5828 grad_norm: 2.9834 loss: 2.3778 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3778 2023/06/04 21:56:33 - mmengine - INFO - Epoch(train) [30][ 700/2569] lr: 4.0000e-02 eta: 23:02:02 time: 0.2665 data_time: 0.0078 memory: 5828 grad_norm: 2.9667 loss: 2.7991 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7991 2023/06/04 21:56:38 - mmengine - INFO - Epoch(train) [30][ 720/2569] lr: 4.0000e-02 eta: 23:01:56 time: 0.2629 data_time: 0.0077 memory: 5828 grad_norm: 3.0708 loss: 2.7932 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7932 2023/06/04 21:56:43 - mmengine - INFO - Epoch(train) [30][ 740/2569] lr: 4.0000e-02 eta: 23:01:50 time: 0.2625 data_time: 0.0076 memory: 5828 grad_norm: 3.0273 loss: 2.6833 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6833 2023/06/04 21:56:49 - mmengine - INFO - Epoch(train) [30][ 760/2569] lr: 4.0000e-02 eta: 23:01:45 time: 0.2657 data_time: 0.0075 memory: 5828 grad_norm: 2.9864 loss: 2.6142 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6142 2023/06/04 21:56:54 - mmengine - INFO - Epoch(train) [30][ 780/2569] lr: 4.0000e-02 eta: 23:01:39 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 3.0206 loss: 2.4521 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4521 2023/06/04 21:56:59 - mmengine - INFO - Epoch(train) [30][ 800/2569] lr: 4.0000e-02 eta: 23:01:34 time: 0.2668 data_time: 0.0079 memory: 5828 grad_norm: 2.9107 loss: 2.6352 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6352 2023/06/04 21:57:05 - mmengine - INFO - Epoch(train) [30][ 820/2569] lr: 4.0000e-02 eta: 23:01:28 time: 0.2622 data_time: 0.0078 memory: 5828 grad_norm: 3.0424 loss: 2.6200 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6200 2023/06/04 21:57:10 - mmengine - INFO - Epoch(train) [30][ 840/2569] lr: 4.0000e-02 eta: 23:01:23 time: 0.2658 data_time: 0.0080 memory: 5828 grad_norm: 2.9491 loss: 2.4714 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4714 2023/06/04 21:57:15 - mmengine - INFO - Epoch(train) [30][ 860/2569] lr: 4.0000e-02 eta: 23:01:17 time: 0.2610 data_time: 0.0078 memory: 5828 grad_norm: 2.9842 loss: 2.5893 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5893 2023/06/04 21:57:20 - mmengine - INFO - Epoch(train) [30][ 880/2569] lr: 4.0000e-02 eta: 23:01:11 time: 0.2630 data_time: 0.0078 memory: 5828 grad_norm: 2.9636 loss: 2.4934 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4934 2023/06/04 21:57:26 - mmengine - INFO - Epoch(train) [30][ 900/2569] lr: 4.0000e-02 eta: 23:01:06 time: 0.2690 data_time: 0.0074 memory: 5828 grad_norm: 2.9940 loss: 2.5016 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5016 2023/06/04 21:57:31 - mmengine - INFO - Epoch(train) [30][ 920/2569] lr: 4.0000e-02 eta: 23:01:00 time: 0.2638 data_time: 0.0079 memory: 5828 grad_norm: 3.0571 loss: 2.7703 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7703 2023/06/04 21:57:36 - mmengine - INFO - Epoch(train) [30][ 940/2569] lr: 4.0000e-02 eta: 23:00:55 time: 0.2690 data_time: 0.0076 memory: 5828 grad_norm: 3.0011 loss: 2.5068 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5068 2023/06/04 21:57:42 - mmengine - INFO - Epoch(train) [30][ 960/2569] lr: 4.0000e-02 eta: 23:00:49 time: 0.2660 data_time: 0.0079 memory: 5828 grad_norm: 2.9453 loss: 2.6309 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6309 2023/06/04 21:57:47 - mmengine - INFO - Epoch(train) [30][ 980/2569] lr: 4.0000e-02 eta: 23:00:44 time: 0.2709 data_time: 0.0075 memory: 5828 grad_norm: 3.0561 loss: 2.6030 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6030 2023/06/04 21:57:53 - mmengine - INFO - Epoch(train) [30][1000/2569] lr: 4.0000e-02 eta: 23:00:39 time: 0.2722 data_time: 0.0080 memory: 5828 grad_norm: 2.9429 loss: 2.6173 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6173 2023/06/04 21:57:58 - mmengine - INFO - Epoch(train) [30][1020/2569] lr: 4.0000e-02 eta: 23:00:34 time: 0.2611 data_time: 0.0078 memory: 5828 grad_norm: 2.9467 loss: 2.9099 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.9099 2023/06/04 21:58:04 - mmengine - INFO - Epoch(train) [30][1040/2569] lr: 4.0000e-02 eta: 23:00:30 time: 0.2835 data_time: 0.0078 memory: 5828 grad_norm: 2.9662 loss: 2.5157 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5157 2023/06/04 21:58:09 - mmengine - INFO - Epoch(train) [30][1060/2569] lr: 4.0000e-02 eta: 23:00:24 time: 0.2621 data_time: 0.0076 memory: 5828 grad_norm: 2.9147 loss: 2.3817 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3817 2023/06/04 21:58:14 - mmengine - INFO - Epoch(train) [30][1080/2569] lr: 4.0000e-02 eta: 23:00:18 time: 0.2649 data_time: 0.0080 memory: 5828 grad_norm: 3.0205 loss: 2.8499 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8499 2023/06/04 21:58:19 - mmengine - INFO - Epoch(train) [30][1100/2569] lr: 4.0000e-02 eta: 23:00:13 time: 0.2679 data_time: 0.0077 memory: 5828 grad_norm: 3.0411 loss: 2.8709 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8709 2023/06/04 21:58:25 - mmengine - INFO - Epoch(train) [30][1120/2569] lr: 4.0000e-02 eta: 23:00:08 time: 0.2686 data_time: 0.0086 memory: 5828 grad_norm: 2.9463 loss: 2.4315 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4315 2023/06/04 21:58:30 - mmengine - INFO - Epoch(train) [30][1140/2569] lr: 4.0000e-02 eta: 23:00:02 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 2.9693 loss: 2.9090 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9090 2023/06/04 21:58:35 - mmengine - INFO - Epoch(train) [30][1160/2569] lr: 4.0000e-02 eta: 22:59:56 time: 0.2623 data_time: 0.0081 memory: 5828 grad_norm: 3.0456 loss: 2.7930 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7930 2023/06/04 21:58:41 - mmengine - INFO - Epoch(train) [30][1180/2569] lr: 4.0000e-02 eta: 22:59:50 time: 0.2643 data_time: 0.0078 memory: 5828 grad_norm: 2.9620 loss: 2.5624 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5624 2023/06/04 21:58:46 - mmengine - INFO - Epoch(train) [30][1200/2569] lr: 4.0000e-02 eta: 22:59:45 time: 0.2717 data_time: 0.0084 memory: 5828 grad_norm: 2.9599 loss: 2.3676 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3676 2023/06/04 21:58:51 - mmengine - INFO - Epoch(train) [30][1220/2569] lr: 4.0000e-02 eta: 22:59:40 time: 0.2719 data_time: 0.0075 memory: 5828 grad_norm: 2.9626 loss: 2.5628 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5628 2023/06/04 21:58:57 - mmengine - INFO - Epoch(train) [30][1240/2569] lr: 4.0000e-02 eta: 22:59:35 time: 0.2614 data_time: 0.0084 memory: 5828 grad_norm: 3.0140 loss: 2.4588 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4588 2023/06/04 21:59:02 - mmengine - INFO - Epoch(train) [30][1260/2569] lr: 4.0000e-02 eta: 22:59:30 time: 0.2715 data_time: 0.0078 memory: 5828 grad_norm: 2.9974 loss: 2.6320 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6320 2023/06/04 21:59:07 - mmengine - INFO - Epoch(train) [30][1280/2569] lr: 4.0000e-02 eta: 22:59:24 time: 0.2610 data_time: 0.0079 memory: 5828 grad_norm: 2.9677 loss: 2.4448 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4448 2023/06/04 21:59:13 - mmengine - INFO - Epoch(train) [30][1300/2569] lr: 4.0000e-02 eta: 22:59:19 time: 0.2726 data_time: 0.0074 memory: 5828 grad_norm: 3.0421 loss: 2.9377 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9377 2023/06/04 21:59:18 - mmengine - INFO - Epoch(train) [30][1320/2569] lr: 4.0000e-02 eta: 22:59:14 time: 0.2692 data_time: 0.0081 memory: 5828 grad_norm: 3.0055 loss: 2.6189 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6189 2023/06/04 21:59:23 - mmengine - INFO - Epoch(train) [30][1340/2569] lr: 4.0000e-02 eta: 22:59:08 time: 0.2617 data_time: 0.0079 memory: 5828 grad_norm: 2.9902 loss: 2.3243 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3243 2023/06/04 21:59:29 - mmengine - INFO - Epoch(train) [30][1360/2569] lr: 4.0000e-02 eta: 22:59:02 time: 0.2664 data_time: 0.0078 memory: 5828 grad_norm: 2.9699 loss: 2.4222 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4222 2023/06/04 21:59:34 - mmengine - INFO - Epoch(train) [30][1380/2569] lr: 4.0000e-02 eta: 22:58:57 time: 0.2669 data_time: 0.0083 memory: 5828 grad_norm: 2.9669 loss: 2.5525 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.5525 2023/06/04 21:59:39 - mmengine - INFO - Epoch(train) [30][1400/2569] lr: 4.0000e-02 eta: 22:58:52 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 2.9461 loss: 2.4202 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4202 2023/06/04 21:59:45 - mmengine - INFO - Epoch(train) [30][1420/2569] lr: 4.0000e-02 eta: 22:58:47 time: 0.2774 data_time: 0.0082 memory: 5828 grad_norm: 3.0058 loss: 2.5083 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5083 2023/06/04 21:59:50 - mmengine - INFO - Epoch(train) [30][1440/2569] lr: 4.0000e-02 eta: 22:58:41 time: 0.2607 data_time: 0.0082 memory: 5828 grad_norm: 2.9805 loss: 2.6382 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6382 2023/06/04 21:59:56 - mmengine - INFO - Epoch(train) [30][1460/2569] lr: 4.0000e-02 eta: 22:58:37 time: 0.2779 data_time: 0.0086 memory: 5828 grad_norm: 3.0302 loss: 2.4619 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4619 2023/06/04 22:00:01 - mmengine - INFO - Epoch(train) [30][1480/2569] lr: 4.0000e-02 eta: 22:58:31 time: 0.2624 data_time: 0.0077 memory: 5828 grad_norm: 2.9696 loss: 2.4164 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4164 2023/06/04 22:00:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:00:07 - mmengine - INFO - Epoch(train) [30][1500/2569] lr: 4.0000e-02 eta: 22:58:26 time: 0.2738 data_time: 0.0076 memory: 5828 grad_norm: 3.0177 loss: 2.3685 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3685 2023/06/04 22:00:12 - mmengine - INFO - Epoch(train) [30][1520/2569] lr: 4.0000e-02 eta: 22:58:20 time: 0.2616 data_time: 0.0078 memory: 5828 grad_norm: 2.9691 loss: 2.9653 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9653 2023/06/04 22:00:17 - mmengine - INFO - Epoch(train) [30][1540/2569] lr: 4.0000e-02 eta: 22:58:16 time: 0.2726 data_time: 0.0080 memory: 5828 grad_norm: 2.9626 loss: 2.6150 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6150 2023/06/04 22:00:22 - mmengine - INFO - Epoch(train) [30][1560/2569] lr: 4.0000e-02 eta: 22:58:10 time: 0.2623 data_time: 0.0077 memory: 5828 grad_norm: 3.0679 loss: 2.3182 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.3182 2023/06/04 22:00:28 - mmengine - INFO - Epoch(train) [30][1580/2569] lr: 4.0000e-02 eta: 22:58:04 time: 0.2670 data_time: 0.0079 memory: 5828 grad_norm: 3.0308 loss: 2.8721 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8721 2023/06/04 22:00:33 - mmengine - INFO - Epoch(train) [30][1600/2569] lr: 4.0000e-02 eta: 22:57:59 time: 0.2703 data_time: 0.0077 memory: 5828 grad_norm: 2.9689 loss: 2.3607 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3607 2023/06/04 22:00:39 - mmengine - INFO - Epoch(train) [30][1620/2569] lr: 4.0000e-02 eta: 22:57:54 time: 0.2655 data_time: 0.0085 memory: 5828 grad_norm: 2.9851 loss: 2.5808 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5808 2023/06/04 22:00:44 - mmengine - INFO - Epoch(train) [30][1640/2569] lr: 4.0000e-02 eta: 22:57:49 time: 0.2678 data_time: 0.0083 memory: 5828 grad_norm: 3.0363 loss: 2.6354 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6354 2023/06/04 22:00:49 - mmengine - INFO - Epoch(train) [30][1660/2569] lr: 4.0000e-02 eta: 22:57:43 time: 0.2615 data_time: 0.0078 memory: 5828 grad_norm: 2.9172 loss: 2.7154 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7154 2023/06/04 22:00:54 - mmengine - INFO - Epoch(train) [30][1680/2569] lr: 4.0000e-02 eta: 22:57:37 time: 0.2587 data_time: 0.0083 memory: 5828 grad_norm: 3.0106 loss: 2.4035 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4035 2023/06/04 22:01:00 - mmengine - INFO - Epoch(train) [30][1700/2569] lr: 4.0000e-02 eta: 22:57:31 time: 0.2620 data_time: 0.0080 memory: 5828 grad_norm: 3.0049 loss: 2.7566 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7566 2023/06/04 22:01:05 - mmengine - INFO - Epoch(train) [30][1720/2569] lr: 4.0000e-02 eta: 22:57:25 time: 0.2673 data_time: 0.0077 memory: 5828 grad_norm: 2.9729 loss: 2.3107 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3107 2023/06/04 22:01:10 - mmengine - INFO - Epoch(train) [30][1740/2569] lr: 4.0000e-02 eta: 22:57:20 time: 0.2607 data_time: 0.0080 memory: 5828 grad_norm: 3.0339 loss: 2.6059 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6059 2023/06/04 22:01:15 - mmengine - INFO - Epoch(train) [30][1760/2569] lr: 4.0000e-02 eta: 22:57:14 time: 0.2630 data_time: 0.0082 memory: 5828 grad_norm: 2.9810 loss: 2.7222 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.7222 2023/06/04 22:01:21 - mmengine - INFO - Epoch(train) [30][1780/2569] lr: 4.0000e-02 eta: 22:57:08 time: 0.2656 data_time: 0.0079 memory: 5828 grad_norm: 2.9764 loss: 2.7149 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7149 2023/06/04 22:01:26 - mmengine - INFO - Epoch(train) [30][1800/2569] lr: 4.0000e-02 eta: 22:57:04 time: 0.2778 data_time: 0.0076 memory: 5828 grad_norm: 3.0201 loss: 2.6314 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6314 2023/06/04 22:01:32 - mmengine - INFO - Epoch(train) [30][1820/2569] lr: 4.0000e-02 eta: 22:56:59 time: 0.2714 data_time: 0.0076 memory: 5828 grad_norm: 2.9693 loss: 2.1872 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1872 2023/06/04 22:01:37 - mmengine - INFO - Epoch(train) [30][1840/2569] lr: 4.0000e-02 eta: 22:56:54 time: 0.2687 data_time: 0.0080 memory: 5828 grad_norm: 3.0133 loss: 2.6597 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6597 2023/06/04 22:01:42 - mmengine - INFO - Epoch(train) [30][1860/2569] lr: 4.0000e-02 eta: 22:56:48 time: 0.2635 data_time: 0.0074 memory: 5828 grad_norm: 2.9860 loss: 2.4310 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4310 2023/06/04 22:01:48 - mmengine - INFO - Epoch(train) [30][1880/2569] lr: 4.0000e-02 eta: 22:56:43 time: 0.2658 data_time: 0.0079 memory: 5828 grad_norm: 3.0024 loss: 2.8898 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8898 2023/06/04 22:01:53 - mmengine - INFO - Epoch(train) [30][1900/2569] lr: 4.0000e-02 eta: 22:56:37 time: 0.2658 data_time: 0.0076 memory: 5828 grad_norm: 2.9807 loss: 2.6015 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6015 2023/06/04 22:01:58 - mmengine - INFO - Epoch(train) [30][1920/2569] lr: 4.0000e-02 eta: 22:56:31 time: 0.2630 data_time: 0.0083 memory: 5828 grad_norm: 2.9639 loss: 2.4780 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4780 2023/06/04 22:02:04 - mmengine - INFO - Epoch(train) [30][1940/2569] lr: 4.0000e-02 eta: 22:56:26 time: 0.2668 data_time: 0.0079 memory: 5828 grad_norm: 2.9953 loss: 2.5679 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5679 2023/06/04 22:02:09 - mmengine - INFO - Epoch(train) [30][1960/2569] lr: 4.0000e-02 eta: 22:56:21 time: 0.2664 data_time: 0.0078 memory: 5828 grad_norm: 2.9095 loss: 2.4020 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4020 2023/06/04 22:02:14 - mmengine - INFO - Epoch(train) [30][1980/2569] lr: 4.0000e-02 eta: 22:56:15 time: 0.2641 data_time: 0.0079 memory: 5828 grad_norm: 2.9782 loss: 2.7401 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7401 2023/06/04 22:02:20 - mmengine - INFO - Epoch(train) [30][2000/2569] lr: 4.0000e-02 eta: 22:56:10 time: 0.2721 data_time: 0.0083 memory: 5828 grad_norm: 2.9864 loss: 2.5149 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5149 2023/06/04 22:02:25 - mmengine - INFO - Epoch(train) [30][2020/2569] lr: 4.0000e-02 eta: 22:56:04 time: 0.2638 data_time: 0.0086 memory: 5828 grad_norm: 2.9823 loss: 2.5051 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5051 2023/06/04 22:02:30 - mmengine - INFO - Epoch(train) [30][2040/2569] lr: 4.0000e-02 eta: 22:55:59 time: 0.2698 data_time: 0.0077 memory: 5828 grad_norm: 2.9422 loss: 2.5158 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5158 2023/06/04 22:02:36 - mmengine - INFO - Epoch(train) [30][2060/2569] lr: 4.0000e-02 eta: 22:55:53 time: 0.2620 data_time: 0.0076 memory: 5828 grad_norm: 2.9859 loss: 2.6396 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6396 2023/06/04 22:02:41 - mmengine - INFO - Epoch(train) [30][2080/2569] lr: 4.0000e-02 eta: 22:55:48 time: 0.2670 data_time: 0.0077 memory: 5828 grad_norm: 2.9637 loss: 2.3280 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3280 2023/06/04 22:02:46 - mmengine - INFO - Epoch(train) [30][2100/2569] lr: 4.0000e-02 eta: 22:55:42 time: 0.2607 data_time: 0.0081 memory: 5828 grad_norm: 2.9815 loss: 2.4323 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4323 2023/06/04 22:02:52 - mmengine - INFO - Epoch(train) [30][2120/2569] lr: 4.0000e-02 eta: 22:55:37 time: 0.2670 data_time: 0.0084 memory: 5828 grad_norm: 2.9879 loss: 2.3002 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3002 2023/06/04 22:02:57 - mmengine - INFO - Epoch(train) [30][2140/2569] lr: 4.0000e-02 eta: 22:55:31 time: 0.2620 data_time: 0.0076 memory: 5828 grad_norm: 3.0198 loss: 2.4144 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4144 2023/06/04 22:03:02 - mmengine - INFO - Epoch(train) [30][2160/2569] lr: 4.0000e-02 eta: 22:55:25 time: 0.2604 data_time: 0.0087 memory: 5828 grad_norm: 2.9117 loss: 2.5188 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5188 2023/06/04 22:03:07 - mmengine - INFO - Epoch(train) [30][2180/2569] lr: 4.0000e-02 eta: 22:55:19 time: 0.2631 data_time: 0.0079 memory: 5828 grad_norm: 2.9940 loss: 2.6514 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6514 2023/06/04 22:03:13 - mmengine - INFO - Epoch(train) [30][2200/2569] lr: 4.0000e-02 eta: 22:55:14 time: 0.2659 data_time: 0.0081 memory: 5828 grad_norm: 3.0005 loss: 2.4557 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4557 2023/06/04 22:03:18 - mmengine - INFO - Epoch(train) [30][2220/2569] lr: 4.0000e-02 eta: 22:55:09 time: 0.2673 data_time: 0.0078 memory: 5828 grad_norm: 2.9928 loss: 2.3271 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3271 2023/06/04 22:03:23 - mmengine - INFO - Epoch(train) [30][2240/2569] lr: 4.0000e-02 eta: 22:55:04 time: 0.2741 data_time: 0.0081 memory: 5828 grad_norm: 3.0458 loss: 2.4373 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4373 2023/06/04 22:03:29 - mmengine - INFO - Epoch(train) [30][2260/2569] lr: 4.0000e-02 eta: 22:54:58 time: 0.2625 data_time: 0.0080 memory: 5828 grad_norm: 3.0293 loss: 2.6709 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6709 2023/06/04 22:03:34 - mmengine - INFO - Epoch(train) [30][2280/2569] lr: 4.0000e-02 eta: 22:54:53 time: 0.2748 data_time: 0.0083 memory: 5828 grad_norm: 2.9238 loss: 2.8268 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8268 2023/06/04 22:03:39 - mmengine - INFO - Epoch(train) [30][2300/2569] lr: 4.0000e-02 eta: 22:54:48 time: 0.2629 data_time: 0.0081 memory: 5828 grad_norm: 2.9238 loss: 2.7289 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7289 2023/06/04 22:03:45 - mmengine - INFO - Epoch(train) [30][2320/2569] lr: 4.0000e-02 eta: 22:54:42 time: 0.2618 data_time: 0.0077 memory: 5828 grad_norm: 2.9933 loss: 2.5723 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5723 2023/06/04 22:03:50 - mmengine - INFO - Epoch(train) [30][2340/2569] lr: 4.0000e-02 eta: 22:54:37 time: 0.2734 data_time: 0.0078 memory: 5828 grad_norm: 3.0552 loss: 2.6548 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6548 2023/06/04 22:03:55 - mmengine - INFO - Epoch(train) [30][2360/2569] lr: 4.0000e-02 eta: 22:54:31 time: 0.2605 data_time: 0.0080 memory: 5828 grad_norm: 2.9973 loss: 2.4605 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4605 2023/06/04 22:04:01 - mmengine - INFO - Epoch(train) [30][2380/2569] lr: 4.0000e-02 eta: 22:54:26 time: 0.2673 data_time: 0.0074 memory: 5828 grad_norm: 2.9422 loss: 2.7140 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7140 2023/06/04 22:04:06 - mmengine - INFO - Epoch(train) [30][2400/2569] lr: 4.0000e-02 eta: 22:54:20 time: 0.2667 data_time: 0.0079 memory: 5828 grad_norm: 3.0194 loss: 2.4970 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4970 2023/06/04 22:04:11 - mmengine - INFO - Epoch(train) [30][2420/2569] lr: 4.0000e-02 eta: 22:54:15 time: 0.2655 data_time: 0.0074 memory: 5828 grad_norm: 2.8852 loss: 2.7161 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7161 2023/06/04 22:04:17 - mmengine - INFO - Epoch(train) [30][2440/2569] lr: 4.0000e-02 eta: 22:54:10 time: 0.2686 data_time: 0.0080 memory: 5828 grad_norm: 2.9873 loss: 2.4073 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4073 2023/06/04 22:04:22 - mmengine - INFO - Epoch(train) [30][2460/2569] lr: 4.0000e-02 eta: 22:54:04 time: 0.2690 data_time: 0.0080 memory: 5828 grad_norm: 2.9259 loss: 2.7244 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7244 2023/06/04 22:04:28 - mmengine - INFO - Epoch(train) [30][2480/2569] lr: 4.0000e-02 eta: 22:53:59 time: 0.2724 data_time: 0.0078 memory: 5828 grad_norm: 2.9976 loss: 2.7598 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7598 2023/06/04 22:04:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:04:33 - mmengine - INFO - Epoch(train) [30][2500/2569] lr: 4.0000e-02 eta: 22:53:54 time: 0.2609 data_time: 0.0076 memory: 5828 grad_norm: 2.9703 loss: 2.2467 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2467 2023/06/04 22:04:38 - mmengine - INFO - Epoch(train) [30][2520/2569] lr: 4.0000e-02 eta: 22:53:48 time: 0.2631 data_time: 0.0075 memory: 5828 grad_norm: 2.9976 loss: 2.6900 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6900 2023/06/04 22:04:43 - mmengine - INFO - Epoch(train) [30][2540/2569] lr: 4.0000e-02 eta: 22:53:43 time: 0.2680 data_time: 0.0078 memory: 5828 grad_norm: 2.9667 loss: 2.8330 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8330 2023/06/04 22:04:49 - mmengine - INFO - Epoch(train) [30][2560/2569] lr: 4.0000e-02 eta: 22:53:37 time: 0.2643 data_time: 0.0077 memory: 5828 grad_norm: 2.9595 loss: 2.4743 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4743 2023/06/04 22:04:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:04:51 - mmengine - INFO - Epoch(train) [30][2569/2569] lr: 4.0000e-02 eta: 22:53:34 time: 0.2543 data_time: 0.0072 memory: 5828 grad_norm: 2.9938 loss: 2.5237 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.5237 2023/06/04 22:04:54 - mmengine - INFO - Epoch(val) [30][ 20/260] eta: 0:00:41 time: 0.1746 data_time: 0.1154 memory: 1238 2023/06/04 22:04:57 - mmengine - INFO - Epoch(val) [30][ 40/260] eta: 0:00:35 time: 0.1483 data_time: 0.0897 memory: 1238 2023/06/04 22:05:01 - mmengine - INFO - Epoch(val) [30][ 60/260] eta: 0:00:32 time: 0.1642 data_time: 0.1058 memory: 1238 2023/06/04 22:05:03 - mmengine - INFO - Epoch(val) [30][ 80/260] eta: 0:00:27 time: 0.1139 data_time: 0.0552 memory: 1238 2023/06/04 22:05:06 - mmengine - INFO - Epoch(val) [30][100/260] eta: 0:00:23 time: 0.1460 data_time: 0.0874 memory: 1238 2023/06/04 22:05:08 - mmengine - INFO - Epoch(val) [30][120/260] eta: 0:00:20 time: 0.1220 data_time: 0.0631 memory: 1238 2023/06/04 22:05:11 - mmengine - INFO - Epoch(val) [30][140/260] eta: 0:00:17 time: 0.1427 data_time: 0.0844 memory: 1238 2023/06/04 22:05:14 - mmengine - INFO - Epoch(val) [30][160/260] eta: 0:00:14 time: 0.1295 data_time: 0.0705 memory: 1238 2023/06/04 22:05:17 - mmengine - INFO - Epoch(val) [30][180/260] eta: 0:00:11 time: 0.1730 data_time: 0.1145 memory: 1238 2023/06/04 22:05:20 - mmengine - INFO - Epoch(val) [30][200/260] eta: 0:00:08 time: 0.1360 data_time: 0.0774 memory: 1238 2023/06/04 22:05:23 - mmengine - INFO - Epoch(val) [30][220/260] eta: 0:00:05 time: 0.1535 data_time: 0.0952 memory: 1238 2023/06/04 22:05:26 - mmengine - INFO - Epoch(val) [30][240/260] eta: 0:00:02 time: 0.1420 data_time: 0.0838 memory: 1238 2023/06/04 22:05:28 - mmengine - INFO - Epoch(val) [30][260/260] eta: 0:00:00 time: 0.1280 data_time: 0.0716 memory: 1238 2023/06/04 22:05:36 - mmengine - INFO - Epoch(val) [30][260/260] acc/top1: 0.4891 acc/top5: 0.7398 acc/mean1: 0.4812 data_time: 0.0854 time: 0.1438 2023/06/04 22:05:43 - mmengine - INFO - Epoch(train) [31][ 20/2569] lr: 4.0000e-02 eta: 22:53:35 time: 0.3479 data_time: 0.0605 memory: 5828 grad_norm: 3.0045 loss: 2.4693 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4693 2023/06/04 22:05:48 - mmengine - INFO - Epoch(train) [31][ 40/2569] lr: 4.0000e-02 eta: 22:53:29 time: 0.2624 data_time: 0.0083 memory: 5828 grad_norm: 2.9993 loss: 3.0055 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0055 2023/06/04 22:05:54 - mmengine - INFO - Epoch(train) [31][ 60/2569] lr: 4.0000e-02 eta: 22:53:24 time: 0.2656 data_time: 0.0083 memory: 5828 grad_norm: 2.9191 loss: 2.5009 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5009 2023/06/04 22:05:59 - mmengine - INFO - Epoch(train) [31][ 80/2569] lr: 4.0000e-02 eta: 22:53:19 time: 0.2759 data_time: 0.0073 memory: 5828 grad_norm: 2.9733 loss: 2.4506 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4506 2023/06/04 22:06:05 - mmengine - INFO - Epoch(train) [31][ 100/2569] lr: 4.0000e-02 eta: 22:53:13 time: 0.2618 data_time: 0.0080 memory: 5828 grad_norm: 2.9863 loss: 2.2438 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2438 2023/06/04 22:06:10 - mmengine - INFO - Epoch(train) [31][ 120/2569] lr: 4.0000e-02 eta: 22:53:07 time: 0.2629 data_time: 0.0077 memory: 5828 grad_norm: 2.9906 loss: 2.7300 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7300 2023/06/04 22:06:15 - mmengine - INFO - Epoch(train) [31][ 140/2569] lr: 4.0000e-02 eta: 22:53:02 time: 0.2629 data_time: 0.0078 memory: 5828 grad_norm: 2.9751 loss: 2.4002 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4002 2023/06/04 22:06:20 - mmengine - INFO - Epoch(train) [31][ 160/2569] lr: 4.0000e-02 eta: 22:52:57 time: 0.2719 data_time: 0.0079 memory: 5828 grad_norm: 3.0365 loss: 2.6697 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6697 2023/06/04 22:06:26 - mmengine - INFO - Epoch(train) [31][ 180/2569] lr: 4.0000e-02 eta: 22:52:51 time: 0.2612 data_time: 0.0084 memory: 5828 grad_norm: 2.9604 loss: 2.1624 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1624 2023/06/04 22:06:31 - mmengine - INFO - Epoch(train) [31][ 200/2569] lr: 4.0000e-02 eta: 22:52:46 time: 0.2684 data_time: 0.0082 memory: 5828 grad_norm: 2.9571 loss: 2.8505 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8505 2023/06/04 22:06:37 - mmengine - INFO - Epoch(train) [31][ 220/2569] lr: 4.0000e-02 eta: 22:52:41 time: 0.2755 data_time: 0.0076 memory: 5828 grad_norm: 2.9966 loss: 2.7548 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7548 2023/06/04 22:06:42 - mmengine - INFO - Epoch(train) [31][ 240/2569] lr: 4.0000e-02 eta: 22:52:36 time: 0.2671 data_time: 0.0077 memory: 5828 grad_norm: 2.9624 loss: 2.5649 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5649 2023/06/04 22:06:47 - mmengine - INFO - Epoch(train) [31][ 260/2569] lr: 4.0000e-02 eta: 22:52:30 time: 0.2613 data_time: 0.0081 memory: 5828 grad_norm: 3.0066 loss: 2.4512 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4512 2023/06/04 22:06:53 - mmengine - INFO - Epoch(train) [31][ 280/2569] lr: 4.0000e-02 eta: 22:52:25 time: 0.2732 data_time: 0.0075 memory: 5828 grad_norm: 2.9332 loss: 2.3047 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3047 2023/06/04 22:06:58 - mmengine - INFO - Epoch(train) [31][ 300/2569] lr: 4.0000e-02 eta: 22:52:20 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 3.0412 loss: 2.5073 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5073 2023/06/04 22:07:03 - mmengine - INFO - Epoch(train) [31][ 320/2569] lr: 4.0000e-02 eta: 22:52:14 time: 0.2653 data_time: 0.0076 memory: 5828 grad_norm: 2.9877 loss: 2.5291 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5291 2023/06/04 22:07:09 - mmengine - INFO - Epoch(train) [31][ 340/2569] lr: 4.0000e-02 eta: 22:52:09 time: 0.2698 data_time: 0.0077 memory: 5828 grad_norm: 2.9958 loss: 2.8498 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8498 2023/06/04 22:07:14 - mmengine - INFO - Epoch(train) [31][ 360/2569] lr: 4.0000e-02 eta: 22:52:04 time: 0.2717 data_time: 0.0082 memory: 5828 grad_norm: 2.9554 loss: 2.7406 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7406 2023/06/04 22:07:19 - mmengine - INFO - Epoch(train) [31][ 380/2569] lr: 4.0000e-02 eta: 22:51:58 time: 0.2626 data_time: 0.0075 memory: 5828 grad_norm: 3.0817 loss: 2.5312 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5312 2023/06/04 22:07:25 - mmengine - INFO - Epoch(train) [31][ 400/2569] lr: 4.0000e-02 eta: 22:51:54 time: 0.2783 data_time: 0.0075 memory: 5828 grad_norm: 2.9383 loss: 2.4084 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4084 2023/06/04 22:07:30 - mmengine - INFO - Epoch(train) [31][ 420/2569] lr: 4.0000e-02 eta: 22:51:48 time: 0.2646 data_time: 0.0078 memory: 5828 grad_norm: 2.9805 loss: 2.4797 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4797 2023/06/04 22:07:36 - mmengine - INFO - Epoch(train) [31][ 440/2569] lr: 4.0000e-02 eta: 22:51:43 time: 0.2685 data_time: 0.0076 memory: 5828 grad_norm: 3.0197 loss: 2.9452 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9452 2023/06/04 22:07:41 - mmengine - INFO - Epoch(train) [31][ 460/2569] lr: 4.0000e-02 eta: 22:51:37 time: 0.2604 data_time: 0.0078 memory: 5828 grad_norm: 2.9964 loss: 2.3983 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3983 2023/06/04 22:07:46 - mmengine - INFO - Epoch(train) [31][ 480/2569] lr: 4.0000e-02 eta: 22:51:32 time: 0.2674 data_time: 0.0079 memory: 5828 grad_norm: 2.9477 loss: 2.7714 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7714 2023/06/04 22:07:52 - mmengine - INFO - Epoch(train) [31][ 500/2569] lr: 4.0000e-02 eta: 22:51:27 time: 0.2717 data_time: 0.0076 memory: 5828 grad_norm: 2.9463 loss: 2.5281 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5281 2023/06/04 22:07:57 - mmengine - INFO - Epoch(train) [31][ 520/2569] lr: 4.0000e-02 eta: 22:51:21 time: 0.2610 data_time: 0.0079 memory: 5828 grad_norm: 3.0448 loss: 2.6335 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6335 2023/06/04 22:08:02 - mmengine - INFO - Epoch(train) [31][ 540/2569] lr: 4.0000e-02 eta: 22:51:15 time: 0.2623 data_time: 0.0078 memory: 5828 grad_norm: 2.9592 loss: 2.4119 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4119 2023/06/04 22:08:07 - mmengine - INFO - Epoch(train) [31][ 560/2569] lr: 4.0000e-02 eta: 22:51:10 time: 0.2655 data_time: 0.0076 memory: 5828 grad_norm: 2.9905 loss: 2.4226 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4226 2023/06/04 22:08:13 - mmengine - INFO - Epoch(train) [31][ 580/2569] lr: 4.0000e-02 eta: 22:51:04 time: 0.2665 data_time: 0.0078 memory: 5828 grad_norm: 3.0188 loss: 2.5871 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5871 2023/06/04 22:08:18 - mmengine - INFO - Epoch(train) [31][ 600/2569] lr: 4.0000e-02 eta: 22:50:58 time: 0.2617 data_time: 0.0083 memory: 5828 grad_norm: 2.9374 loss: 2.5426 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5426 2023/06/04 22:08:23 - mmengine - INFO - Epoch(train) [31][ 620/2569] lr: 4.0000e-02 eta: 22:50:53 time: 0.2676 data_time: 0.0075 memory: 5828 grad_norm: 3.0530 loss: 2.3677 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3677 2023/06/04 22:08:29 - mmengine - INFO - Epoch(train) [31][ 640/2569] lr: 4.0000e-02 eta: 22:50:47 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 2.9985 loss: 2.8948 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.8948 2023/06/04 22:08:34 - mmengine - INFO - Epoch(train) [31][ 660/2569] lr: 4.0000e-02 eta: 22:50:42 time: 0.2709 data_time: 0.0078 memory: 5828 grad_norm: 2.9762 loss: 2.3606 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3606 2023/06/04 22:08:39 - mmengine - INFO - Epoch(train) [31][ 680/2569] lr: 4.0000e-02 eta: 22:50:37 time: 0.2670 data_time: 0.0077 memory: 5828 grad_norm: 3.0010 loss: 2.8629 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8629 2023/06/04 22:08:45 - mmengine - INFO - Epoch(train) [31][ 700/2569] lr: 4.0000e-02 eta: 22:50:32 time: 0.2733 data_time: 0.0076 memory: 5828 grad_norm: 2.9764 loss: 2.3843 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3843 2023/06/04 22:08:50 - mmengine - INFO - Epoch(train) [31][ 720/2569] lr: 4.0000e-02 eta: 22:50:27 time: 0.2655 data_time: 0.0080 memory: 5828 grad_norm: 2.9880 loss: 2.6255 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6255 2023/06/04 22:08:55 - mmengine - INFO - Epoch(train) [31][ 740/2569] lr: 4.0000e-02 eta: 22:50:21 time: 0.2610 data_time: 0.0079 memory: 5828 grad_norm: 3.0189 loss: 2.8648 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8648 2023/06/04 22:09:01 - mmengine - INFO - Epoch(train) [31][ 760/2569] lr: 4.0000e-02 eta: 22:50:15 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 2.9797 loss: 2.8376 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8376 2023/06/04 22:09:06 - mmengine - INFO - Epoch(train) [31][ 780/2569] lr: 4.0000e-02 eta: 22:50:10 time: 0.2633 data_time: 0.0076 memory: 5828 grad_norm: 2.9960 loss: 2.5644 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5644 2023/06/04 22:09:11 - mmengine - INFO - Epoch(train) [31][ 800/2569] lr: 4.0000e-02 eta: 22:50:04 time: 0.2652 data_time: 0.0073 memory: 5828 grad_norm: 2.9685 loss: 2.5194 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5194 2023/06/04 22:09:17 - mmengine - INFO - Epoch(train) [31][ 820/2569] lr: 4.0000e-02 eta: 22:49:59 time: 0.2672 data_time: 0.0080 memory: 5828 grad_norm: 3.0598 loss: 2.7912 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7912 2023/06/04 22:09:22 - mmengine - INFO - Epoch(train) [31][ 840/2569] lr: 4.0000e-02 eta: 22:49:54 time: 0.2709 data_time: 0.0081 memory: 5828 grad_norm: 3.0526 loss: 2.7251 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7251 2023/06/04 22:09:28 - mmengine - INFO - Epoch(train) [31][ 860/2569] lr: 4.0000e-02 eta: 22:49:49 time: 0.2783 data_time: 0.0077 memory: 5828 grad_norm: 2.9223 loss: 2.6911 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6911 2023/06/04 22:09:33 - mmengine - INFO - Epoch(train) [31][ 880/2569] lr: 4.0000e-02 eta: 22:49:44 time: 0.2644 data_time: 0.0075 memory: 5828 grad_norm: 3.0029 loss: 2.8496 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8496 2023/06/04 22:09:38 - mmengine - INFO - Epoch(train) [31][ 900/2569] lr: 4.0000e-02 eta: 22:49:38 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 3.0122 loss: 2.8059 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8059 2023/06/04 22:09:44 - mmengine - INFO - Epoch(train) [31][ 920/2569] lr: 4.0000e-02 eta: 22:49:32 time: 0.2594 data_time: 0.0083 memory: 5828 grad_norm: 2.9839 loss: 2.5784 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5784 2023/06/04 22:09:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:09:49 - mmengine - INFO - Epoch(train) [31][ 940/2569] lr: 4.0000e-02 eta: 22:49:27 time: 0.2637 data_time: 0.0074 memory: 5828 grad_norm: 2.9615 loss: 2.6601 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6601 2023/06/04 22:09:54 - mmengine - INFO - Epoch(train) [31][ 960/2569] lr: 4.0000e-02 eta: 22:49:21 time: 0.2638 data_time: 0.0078 memory: 5828 grad_norm: 2.9715 loss: 2.6004 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6004 2023/06/04 22:09:59 - mmengine - INFO - Epoch(train) [31][ 980/2569] lr: 4.0000e-02 eta: 22:49:16 time: 0.2651 data_time: 0.0079 memory: 5828 grad_norm: 3.0914 loss: 2.8105 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8105 2023/06/04 22:10:05 - mmengine - INFO - Epoch(train) [31][1000/2569] lr: 4.0000e-02 eta: 22:49:10 time: 0.2673 data_time: 0.0076 memory: 5828 grad_norm: 3.0462 loss: 3.0039 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0039 2023/06/04 22:10:10 - mmengine - INFO - Epoch(train) [31][1020/2569] lr: 4.0000e-02 eta: 22:49:05 time: 0.2658 data_time: 0.0075 memory: 5828 grad_norm: 2.9986 loss: 2.7746 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7746 2023/06/04 22:10:15 - mmengine - INFO - Epoch(train) [31][1040/2569] lr: 4.0000e-02 eta: 22:48:59 time: 0.2663 data_time: 0.0078 memory: 5828 grad_norm: 3.0275 loss: 2.6027 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6027 2023/06/04 22:10:21 - mmengine - INFO - Epoch(train) [31][1060/2569] lr: 4.0000e-02 eta: 22:48:54 time: 0.2639 data_time: 0.0084 memory: 5828 grad_norm: 3.0013 loss: 2.5353 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5353 2023/06/04 22:10:26 - mmengine - INFO - Epoch(train) [31][1080/2569] lr: 4.0000e-02 eta: 22:48:48 time: 0.2682 data_time: 0.0083 memory: 5828 grad_norm: 3.0030 loss: 2.7252 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7252 2023/06/04 22:10:31 - mmengine - INFO - Epoch(train) [31][1100/2569] lr: 4.0000e-02 eta: 22:48:44 time: 0.2720 data_time: 0.0077 memory: 5828 grad_norm: 3.0420 loss: 2.5720 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5720 2023/06/04 22:10:37 - mmengine - INFO - Epoch(train) [31][1120/2569] lr: 4.0000e-02 eta: 22:48:38 time: 0.2628 data_time: 0.0079 memory: 5828 grad_norm: 2.9359 loss: 2.7192 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7192 2023/06/04 22:10:42 - mmengine - INFO - Epoch(train) [31][1140/2569] lr: 4.0000e-02 eta: 22:48:32 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 3.0144 loss: 2.8452 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8452 2023/06/04 22:10:47 - mmengine - INFO - Epoch(train) [31][1160/2569] lr: 4.0000e-02 eta: 22:48:27 time: 0.2696 data_time: 0.0079 memory: 5828 grad_norm: 2.9646 loss: 2.4970 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4970 2023/06/04 22:10:53 - mmengine - INFO - Epoch(train) [31][1180/2569] lr: 4.0000e-02 eta: 22:48:21 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 3.0105 loss: 2.1664 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1664 2023/06/04 22:10:58 - mmengine - INFO - Epoch(train) [31][1200/2569] lr: 4.0000e-02 eta: 22:48:16 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 3.1068 loss: 2.4408 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4408 2023/06/04 22:11:03 - mmengine - INFO - Epoch(train) [31][1220/2569] lr: 4.0000e-02 eta: 22:48:11 time: 0.2690 data_time: 0.0081 memory: 5828 grad_norm: 2.9539 loss: 2.7226 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7226 2023/06/04 22:11:09 - mmengine - INFO - Epoch(train) [31][1240/2569] lr: 4.0000e-02 eta: 22:48:05 time: 0.2624 data_time: 0.0080 memory: 5828 grad_norm: 2.9116 loss: 2.7901 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7901 2023/06/04 22:11:14 - mmengine - INFO - Epoch(train) [31][1260/2569] lr: 4.0000e-02 eta: 22:48:00 time: 0.2706 data_time: 0.0078 memory: 5828 grad_norm: 3.0679 loss: 2.3565 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3565 2023/06/04 22:11:19 - mmengine - INFO - Epoch(train) [31][1280/2569] lr: 4.0000e-02 eta: 22:47:54 time: 0.2629 data_time: 0.0079 memory: 5828 grad_norm: 3.0421 loss: 2.7287 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7287 2023/06/04 22:11:25 - mmengine - INFO - Epoch(train) [31][1300/2569] lr: 4.0000e-02 eta: 22:47:50 time: 0.2749 data_time: 0.0084 memory: 5828 grad_norm: 2.9854 loss: 2.9553 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9553 2023/06/04 22:11:30 - mmengine - INFO - Epoch(train) [31][1320/2569] lr: 4.0000e-02 eta: 22:47:44 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 3.0052 loss: 2.2532 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2532 2023/06/04 22:11:36 - mmengine - INFO - Epoch(train) [31][1340/2569] lr: 4.0000e-02 eta: 22:47:39 time: 0.2746 data_time: 0.0078 memory: 5828 grad_norm: 2.9563 loss: 2.8666 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8666 2023/06/04 22:11:41 - mmengine - INFO - Epoch(train) [31][1360/2569] lr: 4.0000e-02 eta: 22:47:34 time: 0.2706 data_time: 0.0081 memory: 5828 grad_norm: 3.0825 loss: 2.6872 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6872 2023/06/04 22:11:46 - mmengine - INFO - Epoch(train) [31][1380/2569] lr: 4.0000e-02 eta: 22:47:28 time: 0.2645 data_time: 0.0078 memory: 5828 grad_norm: 3.0050 loss: 2.3050 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3050 2023/06/04 22:11:52 - mmengine - INFO - Epoch(train) [31][1400/2569] lr: 4.0000e-02 eta: 22:47:23 time: 0.2666 data_time: 0.0083 memory: 5828 grad_norm: 2.9448 loss: 2.5605 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5605 2023/06/04 22:11:57 - mmengine - INFO - Epoch(train) [31][1420/2569] lr: 4.0000e-02 eta: 22:47:18 time: 0.2762 data_time: 0.0073 memory: 5828 grad_norm: 2.9500 loss: 2.5312 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5312 2023/06/04 22:12:02 - mmengine - INFO - Epoch(train) [31][1440/2569] lr: 4.0000e-02 eta: 22:47:13 time: 0.2645 data_time: 0.0082 memory: 5828 grad_norm: 3.0400 loss: 2.8255 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8255 2023/06/04 22:12:08 - mmengine - INFO - Epoch(train) [31][1460/2569] lr: 4.0000e-02 eta: 22:47:07 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 2.9435 loss: 2.3030 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3030 2023/06/04 22:12:13 - mmengine - INFO - Epoch(train) [31][1480/2569] lr: 4.0000e-02 eta: 22:47:02 time: 0.2691 data_time: 0.0078 memory: 5828 grad_norm: 3.0588 loss: 2.5623 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5623 2023/06/04 22:12:18 - mmengine - INFO - Epoch(train) [31][1500/2569] lr: 4.0000e-02 eta: 22:46:56 time: 0.2668 data_time: 0.0077 memory: 5828 grad_norm: 2.9968 loss: 2.5055 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5055 2023/06/04 22:12:24 - mmengine - INFO - Epoch(train) [31][1520/2569] lr: 4.0000e-02 eta: 22:46:51 time: 0.2620 data_time: 0.0083 memory: 5828 grad_norm: 2.9818 loss: 2.7352 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7352 2023/06/04 22:12:29 - mmengine - INFO - Epoch(train) [31][1540/2569] lr: 4.0000e-02 eta: 22:46:46 time: 0.2757 data_time: 0.0076 memory: 5828 grad_norm: 2.9845 loss: 2.7519 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7519 2023/06/04 22:12:35 - mmengine - INFO - Epoch(train) [31][1560/2569] lr: 4.0000e-02 eta: 22:46:40 time: 0.2652 data_time: 0.0076 memory: 5828 grad_norm: 2.9733 loss: 2.7293 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7293 2023/06/04 22:12:40 - mmengine - INFO - Epoch(train) [31][1580/2569] lr: 4.0000e-02 eta: 22:46:35 time: 0.2707 data_time: 0.0080 memory: 5828 grad_norm: 3.0326 loss: 2.7845 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7845 2023/06/04 22:12:45 - mmengine - INFO - Epoch(train) [31][1600/2569] lr: 4.0000e-02 eta: 22:46:29 time: 0.2590 data_time: 0.0075 memory: 5828 grad_norm: 3.0233 loss: 2.7388 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.7388 2023/06/04 22:12:50 - mmengine - INFO - Epoch(train) [31][1620/2569] lr: 4.0000e-02 eta: 22:46:24 time: 0.2636 data_time: 0.0079 memory: 5828 grad_norm: 3.0073 loss: 2.8047 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8047 2023/06/04 22:12:56 - mmengine - INFO - Epoch(train) [31][1640/2569] lr: 4.0000e-02 eta: 22:46:18 time: 0.2604 data_time: 0.0077 memory: 5828 grad_norm: 2.9748 loss: 2.9473 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9473 2023/06/04 22:13:01 - mmengine - INFO - Epoch(train) [31][1660/2569] lr: 4.0000e-02 eta: 22:46:13 time: 0.2713 data_time: 0.0079 memory: 5828 grad_norm: 2.9548 loss: 2.5528 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5528 2023/06/04 22:13:06 - mmengine - INFO - Epoch(train) [31][1680/2569] lr: 4.0000e-02 eta: 22:46:07 time: 0.2650 data_time: 0.0078 memory: 5828 grad_norm: 2.9724 loss: 2.3420 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3420 2023/06/04 22:13:12 - mmengine - INFO - Epoch(train) [31][1700/2569] lr: 4.0000e-02 eta: 22:46:02 time: 0.2702 data_time: 0.0082 memory: 5828 grad_norm: 2.9628 loss: 2.9079 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9079 2023/06/04 22:13:17 - mmengine - INFO - Epoch(train) [31][1720/2569] lr: 4.0000e-02 eta: 22:45:57 time: 0.2646 data_time: 0.0080 memory: 5828 grad_norm: 2.9649 loss: 2.2847 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2847 2023/06/04 22:13:22 - mmengine - INFO - Epoch(train) [31][1740/2569] lr: 4.0000e-02 eta: 22:45:51 time: 0.2636 data_time: 0.0081 memory: 5828 grad_norm: 2.9405 loss: 2.5756 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5756 2023/06/04 22:13:28 - mmengine - INFO - Epoch(train) [31][1760/2569] lr: 4.0000e-02 eta: 22:45:46 time: 0.2737 data_time: 0.0081 memory: 5828 grad_norm: 2.9770 loss: 2.5709 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5709 2023/06/04 22:13:33 - mmengine - INFO - Epoch(train) [31][1780/2569] lr: 4.0000e-02 eta: 22:45:40 time: 0.2628 data_time: 0.0080 memory: 5828 grad_norm: 2.9383 loss: 2.7938 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7938 2023/06/04 22:13:38 - mmengine - INFO - Epoch(train) [31][1800/2569] lr: 4.0000e-02 eta: 22:45:35 time: 0.2651 data_time: 0.0079 memory: 5828 grad_norm: 2.9081 loss: 2.4532 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4532 2023/06/04 22:13:44 - mmengine - INFO - Epoch(train) [31][1820/2569] lr: 4.0000e-02 eta: 22:45:29 time: 0.2647 data_time: 0.0079 memory: 5828 grad_norm: 3.0089 loss: 2.1074 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1074 2023/06/04 22:13:49 - mmengine - INFO - Epoch(train) [31][1840/2569] lr: 4.0000e-02 eta: 22:45:24 time: 0.2640 data_time: 0.0081 memory: 5828 grad_norm: 2.9705 loss: 2.6615 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6615 2023/06/04 22:13:54 - mmengine - INFO - Epoch(train) [31][1860/2569] lr: 4.0000e-02 eta: 22:45:18 time: 0.2622 data_time: 0.0091 memory: 5828 grad_norm: 2.9837 loss: 2.5668 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5668 2023/06/04 22:13:59 - mmengine - INFO - Epoch(train) [31][1880/2569] lr: 4.0000e-02 eta: 22:45:12 time: 0.2594 data_time: 0.0077 memory: 5828 grad_norm: 2.9436 loss: 2.3601 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3601 2023/06/04 22:14:05 - mmengine - INFO - Epoch(train) [31][1900/2569] lr: 4.0000e-02 eta: 22:45:06 time: 0.2633 data_time: 0.0077 memory: 5828 grad_norm: 2.9832 loss: 2.5230 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5230 2023/06/04 22:14:10 - mmengine - INFO - Epoch(train) [31][1920/2569] lr: 4.0000e-02 eta: 22:45:01 time: 0.2684 data_time: 0.0077 memory: 5828 grad_norm: 2.9547 loss: 2.5249 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5249 2023/06/04 22:14:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:14:15 - mmengine - INFO - Epoch(train) [31][1940/2569] lr: 4.0000e-02 eta: 22:44:55 time: 0.2630 data_time: 0.0078 memory: 5828 grad_norm: 3.0300 loss: 2.6856 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6856 2023/06/04 22:14:21 - mmengine - INFO - Epoch(train) [31][1960/2569] lr: 4.0000e-02 eta: 22:44:50 time: 0.2661 data_time: 0.0073 memory: 5828 grad_norm: 3.0251 loss: 2.7691 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7691 2023/06/04 22:14:26 - mmengine - INFO - Epoch(train) [31][1980/2569] lr: 4.0000e-02 eta: 22:44:44 time: 0.2640 data_time: 0.0083 memory: 5828 grad_norm: 3.0705 loss: 2.4550 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4550 2023/06/04 22:14:31 - mmengine - INFO - Epoch(train) [31][2000/2569] lr: 4.0000e-02 eta: 22:44:39 time: 0.2664 data_time: 0.0078 memory: 5828 grad_norm: 3.0501 loss: 2.6462 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6462 2023/06/04 22:14:37 - mmengine - INFO - Epoch(train) [31][2020/2569] lr: 4.0000e-02 eta: 22:44:34 time: 0.2701 data_time: 0.0077 memory: 5828 grad_norm: 3.0034 loss: 2.8149 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8149 2023/06/04 22:14:42 - mmengine - INFO - Epoch(train) [31][2040/2569] lr: 4.0000e-02 eta: 22:44:29 time: 0.2711 data_time: 0.0086 memory: 5828 grad_norm: 3.0011 loss: 2.5960 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5960 2023/06/04 22:14:47 - mmengine - INFO - Epoch(train) [31][2060/2569] lr: 4.0000e-02 eta: 22:44:23 time: 0.2651 data_time: 0.0082 memory: 5828 grad_norm: 2.9498 loss: 2.5079 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5079 2023/06/04 22:14:53 - mmengine - INFO - Epoch(train) [31][2080/2569] lr: 4.0000e-02 eta: 22:44:18 time: 0.2710 data_time: 0.0086 memory: 5828 grad_norm: 3.0573 loss: 2.3954 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3954 2023/06/04 22:14:58 - mmengine - INFO - Epoch(train) [31][2100/2569] lr: 4.0000e-02 eta: 22:44:12 time: 0.2609 data_time: 0.0078 memory: 5828 grad_norm: 3.0079 loss: 2.3518 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3518 2023/06/04 22:15:03 - mmengine - INFO - Epoch(train) [31][2120/2569] lr: 4.0000e-02 eta: 22:44:07 time: 0.2708 data_time: 0.0078 memory: 5828 grad_norm: 3.0385 loss: 2.7291 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7291 2023/06/04 22:15:09 - mmengine - INFO - Epoch(train) [31][2140/2569] lr: 4.0000e-02 eta: 22:44:03 time: 0.2772 data_time: 0.0081 memory: 5828 grad_norm: 3.0161 loss: 2.9806 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9806 2023/06/04 22:15:14 - mmengine - INFO - Epoch(train) [31][2160/2569] lr: 4.0000e-02 eta: 22:43:57 time: 0.2688 data_time: 0.0081 memory: 5828 grad_norm: 2.9797 loss: 2.6878 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6878 2023/06/04 22:15:20 - mmengine - INFO - Epoch(train) [31][2180/2569] lr: 4.0000e-02 eta: 22:43:52 time: 0.2705 data_time: 0.0079 memory: 5828 grad_norm: 2.9590 loss: 2.4274 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4274 2023/06/04 22:15:25 - mmengine - INFO - Epoch(train) [31][2200/2569] lr: 4.0000e-02 eta: 22:43:47 time: 0.2637 data_time: 0.0082 memory: 5828 grad_norm: 3.0384 loss: 2.7584 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7584 2023/06/04 22:15:30 - mmengine - INFO - Epoch(train) [31][2220/2569] lr: 4.0000e-02 eta: 22:43:42 time: 0.2691 data_time: 0.0076 memory: 5828 grad_norm: 3.0065 loss: 2.7703 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7703 2023/06/04 22:15:36 - mmengine - INFO - Epoch(train) [31][2240/2569] lr: 4.0000e-02 eta: 22:43:36 time: 0.2642 data_time: 0.0081 memory: 5828 grad_norm: 2.9527 loss: 2.6756 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6756 2023/06/04 22:15:41 - mmengine - INFO - Epoch(train) [31][2260/2569] lr: 4.0000e-02 eta: 22:43:31 time: 0.2669 data_time: 0.0078 memory: 5828 grad_norm: 3.0225 loss: 2.8732 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8732 2023/06/04 22:15:46 - mmengine - INFO - Epoch(train) [31][2280/2569] lr: 4.0000e-02 eta: 22:43:25 time: 0.2654 data_time: 0.0076 memory: 5828 grad_norm: 2.9924 loss: 2.6496 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6496 2023/06/04 22:15:52 - mmengine - INFO - Epoch(train) [31][2300/2569] lr: 4.0000e-02 eta: 22:43:20 time: 0.2711 data_time: 0.0079 memory: 5828 grad_norm: 3.0641 loss: 2.8521 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8521 2023/06/04 22:15:57 - mmengine - INFO - Epoch(train) [31][2320/2569] lr: 4.0000e-02 eta: 22:43:15 time: 0.2708 data_time: 0.0080 memory: 5828 grad_norm: 3.0391 loss: 2.5012 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5012 2023/06/04 22:16:03 - mmengine - INFO - Epoch(train) [31][2340/2569] lr: 4.0000e-02 eta: 22:43:10 time: 0.2688 data_time: 0.0075 memory: 5828 grad_norm: 2.9274 loss: 2.7883 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7883 2023/06/04 22:16:08 - mmengine - INFO - Epoch(train) [31][2360/2569] lr: 4.0000e-02 eta: 22:43:04 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 3.0561 loss: 2.4149 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4149 2023/06/04 22:16:13 - mmengine - INFO - Epoch(train) [31][2380/2569] lr: 4.0000e-02 eta: 22:42:59 time: 0.2698 data_time: 0.0081 memory: 5828 grad_norm: 2.9996 loss: 2.5546 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5546 2023/06/04 22:16:18 - mmengine - INFO - Epoch(train) [31][2400/2569] lr: 4.0000e-02 eta: 22:42:53 time: 0.2634 data_time: 0.0080 memory: 5828 grad_norm: 2.9923 loss: 2.4199 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4199 2023/06/04 22:16:24 - mmengine - INFO - Epoch(train) [31][2420/2569] lr: 4.0000e-02 eta: 22:42:47 time: 0.2617 data_time: 0.0081 memory: 5828 grad_norm: 2.9783 loss: 2.5782 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5782 2023/06/04 22:16:29 - mmengine - INFO - Epoch(train) [31][2440/2569] lr: 4.0000e-02 eta: 22:42:42 time: 0.2745 data_time: 0.0078 memory: 5828 grad_norm: 2.9943 loss: 2.4126 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4126 2023/06/04 22:16:34 - mmengine - INFO - Epoch(train) [31][2460/2569] lr: 4.0000e-02 eta: 22:42:36 time: 0.2574 data_time: 0.0081 memory: 5828 grad_norm: 3.0668 loss: 2.5091 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5091 2023/06/04 22:16:40 - mmengine - INFO - Epoch(train) [31][2480/2569] lr: 4.0000e-02 eta: 22:42:32 time: 0.2766 data_time: 0.0078 memory: 5828 grad_norm: 2.9793 loss: 2.5877 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5877 2023/06/04 22:16:45 - mmengine - INFO - Epoch(train) [31][2500/2569] lr: 4.0000e-02 eta: 22:42:26 time: 0.2647 data_time: 0.0079 memory: 5828 grad_norm: 2.9778 loss: 2.7961 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7961 2023/06/04 22:16:51 - mmengine - INFO - Epoch(train) [31][2520/2569] lr: 4.0000e-02 eta: 22:42:21 time: 0.2699 data_time: 0.0077 memory: 5828 grad_norm: 3.0049 loss: 2.5671 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5671 2023/06/04 22:16:56 - mmengine - INFO - Epoch(train) [31][2540/2569] lr: 4.0000e-02 eta: 22:42:15 time: 0.2611 data_time: 0.0076 memory: 5828 grad_norm: 2.9753 loss: 2.4788 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4788 2023/06/04 22:17:01 - mmengine - INFO - Epoch(train) [31][2560/2569] lr: 4.0000e-02 eta: 22:42:10 time: 0.2668 data_time: 0.0079 memory: 5828 grad_norm: 2.9555 loss: 2.7589 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7589 2023/06/04 22:17:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:17:03 - mmengine - INFO - Epoch(train) [31][2569/2569] lr: 4.0000e-02 eta: 22:42:07 time: 0.2654 data_time: 0.0068 memory: 5828 grad_norm: 2.9660 loss: 2.7160 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.7160 2023/06/04 22:17:10 - mmengine - INFO - Epoch(train) [32][ 20/2569] lr: 4.0000e-02 eta: 22:42:08 time: 0.3468 data_time: 0.0593 memory: 5828 grad_norm: 3.0352 loss: 2.4093 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4093 2023/06/04 22:17:16 - mmengine - INFO - Epoch(train) [32][ 40/2569] lr: 4.0000e-02 eta: 22:42:03 time: 0.2735 data_time: 0.0076 memory: 5828 grad_norm: 3.0421 loss: 2.7694 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7694 2023/06/04 22:17:21 - mmengine - INFO - Epoch(train) [32][ 60/2569] lr: 4.0000e-02 eta: 22:41:58 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 3.0076 loss: 2.7314 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7314 2023/06/04 22:17:27 - mmengine - INFO - Epoch(train) [32][ 80/2569] lr: 4.0000e-02 eta: 22:41:52 time: 0.2673 data_time: 0.0097 memory: 5828 grad_norm: 2.9390 loss: 2.9352 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9352 2023/06/04 22:17:32 - mmengine - INFO - Epoch(train) [32][ 100/2569] lr: 4.0000e-02 eta: 22:41:46 time: 0.2602 data_time: 0.0078 memory: 5828 grad_norm: 2.9840 loss: 2.4300 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4300 2023/06/04 22:17:37 - mmengine - INFO - Epoch(train) [32][ 120/2569] lr: 4.0000e-02 eta: 22:41:41 time: 0.2621 data_time: 0.0080 memory: 5828 grad_norm: 3.0318 loss: 2.6082 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6082 2023/06/04 22:17:42 - mmengine - INFO - Epoch(train) [32][ 140/2569] lr: 4.0000e-02 eta: 22:41:35 time: 0.2602 data_time: 0.0080 memory: 5828 grad_norm: 2.9903 loss: 2.4239 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4239 2023/06/04 22:17:48 - mmengine - INFO - Epoch(train) [32][ 160/2569] lr: 4.0000e-02 eta: 22:41:29 time: 0.2641 data_time: 0.0080 memory: 5828 grad_norm: 3.0036 loss: 2.3070 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3070 2023/06/04 22:17:53 - mmengine - INFO - Epoch(train) [32][ 180/2569] lr: 4.0000e-02 eta: 22:41:23 time: 0.2595 data_time: 0.0080 memory: 5828 grad_norm: 2.9643 loss: 2.4827 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4827 2023/06/04 22:17:58 - mmengine - INFO - Epoch(train) [32][ 200/2569] lr: 4.0000e-02 eta: 22:41:18 time: 0.2641 data_time: 0.0079 memory: 5828 grad_norm: 3.0230 loss: 2.7059 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7059 2023/06/04 22:18:03 - mmengine - INFO - Epoch(train) [32][ 220/2569] lr: 4.0000e-02 eta: 22:41:12 time: 0.2636 data_time: 0.0083 memory: 5828 grad_norm: 3.0077 loss: 2.4670 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4670 2023/06/04 22:18:09 - mmengine - INFO - Epoch(train) [32][ 240/2569] lr: 4.0000e-02 eta: 22:41:06 time: 0.2596 data_time: 0.0079 memory: 5828 grad_norm: 2.9821 loss: 2.7081 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7081 2023/06/04 22:18:14 - mmengine - INFO - Epoch(train) [32][ 260/2569] lr: 4.0000e-02 eta: 22:41:00 time: 0.2622 data_time: 0.0083 memory: 5828 grad_norm: 3.0104 loss: 2.5165 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5165 2023/06/04 22:18:19 - mmengine - INFO - Epoch(train) [32][ 280/2569] lr: 4.0000e-02 eta: 22:40:55 time: 0.2646 data_time: 0.0077 memory: 5828 grad_norm: 2.9970 loss: 2.7214 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7214 2023/06/04 22:18:24 - mmengine - INFO - Epoch(train) [32][ 300/2569] lr: 4.0000e-02 eta: 22:40:49 time: 0.2628 data_time: 0.0079 memory: 5828 grad_norm: 2.9767 loss: 2.3379 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3379 2023/06/04 22:18:30 - mmengine - INFO - Epoch(train) [32][ 320/2569] lr: 4.0000e-02 eta: 22:40:43 time: 0.2611 data_time: 0.0080 memory: 5828 grad_norm: 3.0766 loss: 2.5192 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5192 2023/06/04 22:18:35 - mmengine - INFO - Epoch(train) [32][ 340/2569] lr: 4.0000e-02 eta: 22:40:37 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 3.0367 loss: 2.5791 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.5791 2023/06/04 22:18:40 - mmengine - INFO - Epoch(train) [32][ 360/2569] lr: 4.0000e-02 eta: 22:40:32 time: 0.2658 data_time: 0.0087 memory: 5828 grad_norm: 3.0240 loss: 2.7048 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7048 2023/06/04 22:18:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:18:46 - mmengine - INFO - Epoch(train) [32][ 380/2569] lr: 4.0000e-02 eta: 22:40:27 time: 0.2705 data_time: 0.0072 memory: 5828 grad_norm: 2.9481 loss: 2.5788 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5788 2023/06/04 22:18:51 - mmengine - INFO - Epoch(train) [32][ 400/2569] lr: 4.0000e-02 eta: 22:40:22 time: 0.2679 data_time: 0.0081 memory: 5828 grad_norm: 2.9890 loss: 2.4294 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4294 2023/06/04 22:18:56 - mmengine - INFO - Epoch(train) [32][ 420/2569] lr: 4.0000e-02 eta: 22:40:16 time: 0.2696 data_time: 0.0080 memory: 5828 grad_norm: 2.9476 loss: 2.5931 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5931 2023/06/04 22:19:02 - mmengine - INFO - Epoch(train) [32][ 440/2569] lr: 4.0000e-02 eta: 22:40:11 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 2.9240 loss: 2.6891 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6891 2023/06/04 22:19:07 - mmengine - INFO - Epoch(train) [32][ 460/2569] lr: 4.0000e-02 eta: 22:40:05 time: 0.2599 data_time: 0.0078 memory: 5828 grad_norm: 2.9723 loss: 2.4526 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4526 2023/06/04 22:19:12 - mmengine - INFO - Epoch(train) [32][ 480/2569] lr: 4.0000e-02 eta: 22:39:59 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 3.0244 loss: 2.6276 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6276 2023/06/04 22:19:17 - mmengine - INFO - Epoch(train) [32][ 500/2569] lr: 4.0000e-02 eta: 22:39:53 time: 0.2613 data_time: 0.0081 memory: 5828 grad_norm: 3.0584 loss: 2.3871 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3871 2023/06/04 22:19:23 - mmengine - INFO - Epoch(train) [32][ 520/2569] lr: 4.0000e-02 eta: 22:39:48 time: 0.2686 data_time: 0.0074 memory: 5828 grad_norm: 3.0816 loss: 2.5666 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5666 2023/06/04 22:19:28 - mmengine - INFO - Epoch(train) [32][ 540/2569] lr: 4.0000e-02 eta: 22:39:43 time: 0.2740 data_time: 0.0074 memory: 5828 grad_norm: 3.1527 loss: 2.9235 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9235 2023/06/04 22:19:34 - mmengine - INFO - Epoch(train) [32][ 560/2569] lr: 4.0000e-02 eta: 22:39:39 time: 0.2779 data_time: 0.0077 memory: 5828 grad_norm: 2.9647 loss: 2.9413 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.9413 2023/06/04 22:19:39 - mmengine - INFO - Epoch(train) [32][ 580/2569] lr: 4.0000e-02 eta: 22:39:33 time: 0.2655 data_time: 0.0079 memory: 5828 grad_norm: 3.0530 loss: 2.5150 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5150 2023/06/04 22:19:44 - mmengine - INFO - Epoch(train) [32][ 600/2569] lr: 4.0000e-02 eta: 22:39:28 time: 0.2697 data_time: 0.0078 memory: 5828 grad_norm: 2.9837 loss: 2.8282 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8282 2023/06/04 22:19:50 - mmengine - INFO - Epoch(train) [32][ 620/2569] lr: 4.0000e-02 eta: 22:39:22 time: 0.2654 data_time: 0.0078 memory: 5828 grad_norm: 2.9723 loss: 2.6110 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6110 2023/06/04 22:19:55 - mmengine - INFO - Epoch(train) [32][ 640/2569] lr: 4.0000e-02 eta: 22:39:17 time: 0.2667 data_time: 0.0078 memory: 5828 grad_norm: 2.9655 loss: 2.5205 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5205 2023/06/04 22:20:00 - mmengine - INFO - Epoch(train) [32][ 660/2569] lr: 4.0000e-02 eta: 22:39:12 time: 0.2702 data_time: 0.0080 memory: 5828 grad_norm: 2.9648 loss: 2.3869 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3869 2023/06/04 22:20:06 - mmengine - INFO - Epoch(train) [32][ 680/2569] lr: 4.0000e-02 eta: 22:39:07 time: 0.2671 data_time: 0.0093 memory: 5828 grad_norm: 3.0114 loss: 2.4791 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4791 2023/06/04 22:20:11 - mmengine - INFO - Epoch(train) [32][ 700/2569] lr: 4.0000e-02 eta: 22:39:01 time: 0.2668 data_time: 0.0077 memory: 5828 grad_norm: 3.0066 loss: 2.4661 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4661 2023/06/04 22:20:16 - mmengine - INFO - Epoch(train) [32][ 720/2569] lr: 4.0000e-02 eta: 22:38:56 time: 0.2660 data_time: 0.0081 memory: 5828 grad_norm: 2.9534 loss: 2.8507 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8507 2023/06/04 22:20:22 - mmengine - INFO - Epoch(train) [32][ 740/2569] lr: 4.0000e-02 eta: 22:38:50 time: 0.2607 data_time: 0.0080 memory: 5828 grad_norm: 3.0194 loss: 2.7695 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7695 2023/06/04 22:20:27 - mmengine - INFO - Epoch(train) [32][ 760/2569] lr: 4.0000e-02 eta: 22:38:45 time: 0.2749 data_time: 0.0074 memory: 5828 grad_norm: 2.9598 loss: 2.4916 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4916 2023/06/04 22:20:32 - mmengine - INFO - Epoch(train) [32][ 780/2569] lr: 4.0000e-02 eta: 22:38:40 time: 0.2680 data_time: 0.0080 memory: 5828 grad_norm: 2.9108 loss: 2.6900 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6900 2023/06/04 22:20:38 - mmengine - INFO - Epoch(train) [32][ 800/2569] lr: 4.0000e-02 eta: 22:38:34 time: 0.2618 data_time: 0.0080 memory: 5828 grad_norm: 2.9925 loss: 2.7365 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7365 2023/06/04 22:20:43 - mmengine - INFO - Epoch(train) [32][ 820/2569] lr: 4.0000e-02 eta: 22:38:28 time: 0.2615 data_time: 0.0087 memory: 5828 grad_norm: 3.0210 loss: 2.6636 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6636 2023/06/04 22:20:48 - mmengine - INFO - Epoch(train) [32][ 840/2569] lr: 4.0000e-02 eta: 22:38:22 time: 0.2620 data_time: 0.0076 memory: 5828 grad_norm: 2.9407 loss: 2.7360 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7360 2023/06/04 22:20:53 - mmengine - INFO - Epoch(train) [32][ 860/2569] lr: 4.0000e-02 eta: 22:38:17 time: 0.2606 data_time: 0.0084 memory: 5828 grad_norm: 3.0215 loss: 2.6161 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6161 2023/06/04 22:20:59 - mmengine - INFO - Epoch(train) [32][ 880/2569] lr: 4.0000e-02 eta: 22:38:12 time: 0.2714 data_time: 0.0085 memory: 5828 grad_norm: 2.9969 loss: 2.4958 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4958 2023/06/04 22:21:04 - mmengine - INFO - Epoch(train) [32][ 900/2569] lr: 4.0000e-02 eta: 22:38:06 time: 0.2641 data_time: 0.0077 memory: 5828 grad_norm: 2.9859 loss: 2.6574 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6574 2023/06/04 22:21:10 - mmengine - INFO - Epoch(train) [32][ 920/2569] lr: 4.0000e-02 eta: 22:38:01 time: 0.2708 data_time: 0.0077 memory: 5828 grad_norm: 3.0238 loss: 2.6206 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6206 2023/06/04 22:21:15 - mmengine - INFO - Epoch(train) [32][ 940/2569] lr: 4.0000e-02 eta: 22:37:55 time: 0.2658 data_time: 0.0081 memory: 5828 grad_norm: 2.9620 loss: 2.5043 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5043 2023/06/04 22:21:20 - mmengine - INFO - Epoch(train) [32][ 960/2569] lr: 4.0000e-02 eta: 22:37:50 time: 0.2661 data_time: 0.0081 memory: 5828 grad_norm: 2.9812 loss: 2.2515 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2515 2023/06/04 22:21:25 - mmengine - INFO - Epoch(train) [32][ 980/2569] lr: 4.0000e-02 eta: 22:37:44 time: 0.2604 data_time: 0.0081 memory: 5828 grad_norm: 3.0480 loss: 2.5399 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5399 2023/06/04 22:21:31 - mmengine - INFO - Epoch(train) [32][1000/2569] lr: 4.0000e-02 eta: 22:37:39 time: 0.2680 data_time: 0.0078 memory: 5828 grad_norm: 2.9878 loss: 2.4304 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4304 2023/06/04 22:21:36 - mmengine - INFO - Epoch(train) [32][1020/2569] lr: 4.0000e-02 eta: 22:37:33 time: 0.2603 data_time: 0.0096 memory: 5828 grad_norm: 2.9830 loss: 2.5594 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5594 2023/06/04 22:21:41 - mmengine - INFO - Epoch(train) [32][1040/2569] lr: 4.0000e-02 eta: 22:37:28 time: 0.2663 data_time: 0.0081 memory: 5828 grad_norm: 2.9644 loss: 2.7467 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7467 2023/06/04 22:21:47 - mmengine - INFO - Epoch(train) [32][1060/2569] lr: 4.0000e-02 eta: 22:37:22 time: 0.2630 data_time: 0.0083 memory: 5828 grad_norm: 2.9440 loss: 2.4715 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4715 2023/06/04 22:21:52 - mmengine - INFO - Epoch(train) [32][1080/2569] lr: 4.0000e-02 eta: 22:37:17 time: 0.2743 data_time: 0.0084 memory: 5828 grad_norm: 3.0268 loss: 2.5052 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5052 2023/06/04 22:21:57 - mmengine - INFO - Epoch(train) [32][1100/2569] lr: 4.0000e-02 eta: 22:37:12 time: 0.2711 data_time: 0.0086 memory: 5828 grad_norm: 3.0188 loss: 2.3180 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3180 2023/06/04 22:22:03 - mmengine - INFO - Epoch(train) [32][1120/2569] lr: 4.0000e-02 eta: 22:37:07 time: 0.2685 data_time: 0.0082 memory: 5828 grad_norm: 2.9573 loss: 2.6401 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6401 2023/06/04 22:22:08 - mmengine - INFO - Epoch(train) [32][1140/2569] lr: 4.0000e-02 eta: 22:37:01 time: 0.2647 data_time: 0.0085 memory: 5828 grad_norm: 3.1185 loss: 2.5714 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5714 2023/06/04 22:22:13 - mmengine - INFO - Epoch(train) [32][1160/2569] lr: 4.0000e-02 eta: 22:36:55 time: 0.2586 data_time: 0.0085 memory: 5828 grad_norm: 3.0904 loss: 2.4378 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4378 2023/06/04 22:22:19 - mmengine - INFO - Epoch(train) [32][1180/2569] lr: 4.0000e-02 eta: 22:36:50 time: 0.2708 data_time: 0.0081 memory: 5828 grad_norm: 3.0335 loss: 2.8471 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8471 2023/06/04 22:22:24 - mmengine - INFO - Epoch(train) [32][1200/2569] lr: 4.0000e-02 eta: 22:36:44 time: 0.2618 data_time: 0.0079 memory: 5828 grad_norm: 3.0161 loss: 2.6562 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6562 2023/06/04 22:22:29 - mmengine - INFO - Epoch(train) [32][1220/2569] lr: 4.0000e-02 eta: 22:36:39 time: 0.2714 data_time: 0.0077 memory: 5828 grad_norm: 3.0249 loss: 2.5321 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5321 2023/06/04 22:22:35 - mmengine - INFO - Epoch(train) [32][1240/2569] lr: 4.0000e-02 eta: 22:36:34 time: 0.2747 data_time: 0.0089 memory: 5828 grad_norm: 2.9451 loss: 2.7525 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7525 2023/06/04 22:22:40 - mmengine - INFO - Epoch(train) [32][1260/2569] lr: 4.0000e-02 eta: 22:36:29 time: 0.2639 data_time: 0.0080 memory: 5828 grad_norm: 3.0664 loss: 2.6894 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6894 2023/06/04 22:22:46 - mmengine - INFO - Epoch(train) [32][1280/2569] lr: 4.0000e-02 eta: 22:36:23 time: 0.2660 data_time: 0.0081 memory: 5828 grad_norm: 2.9958 loss: 2.5854 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5854 2023/06/04 22:22:51 - mmengine - INFO - Epoch(train) [32][1300/2569] lr: 4.0000e-02 eta: 22:36:18 time: 0.2640 data_time: 0.0078 memory: 5828 grad_norm: 3.0218 loss: 2.7575 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7575 2023/06/04 22:22:56 - mmengine - INFO - Epoch(train) [32][1320/2569] lr: 4.0000e-02 eta: 22:36:12 time: 0.2662 data_time: 0.0083 memory: 5828 grad_norm: 3.0341 loss: 2.5307 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5307 2023/06/04 22:23:01 - mmengine - INFO - Epoch(train) [32][1340/2569] lr: 4.0000e-02 eta: 22:36:07 time: 0.2631 data_time: 0.0082 memory: 5828 grad_norm: 3.0380 loss: 2.5365 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5365 2023/06/04 22:23:07 - mmengine - INFO - Epoch(train) [32][1360/2569] lr: 4.0000e-02 eta: 22:36:01 time: 0.2597 data_time: 0.0085 memory: 5828 grad_norm: 3.0179 loss: 2.6498 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6498 2023/06/04 22:23:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:23:12 - mmengine - INFO - Epoch(train) [32][1380/2569] lr: 4.0000e-02 eta: 22:35:55 time: 0.2598 data_time: 0.0078 memory: 5828 grad_norm: 3.0182 loss: 2.3624 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3624 2023/06/04 22:23:17 - mmengine - INFO - Epoch(train) [32][1400/2569] lr: 4.0000e-02 eta: 22:35:50 time: 0.2676 data_time: 0.0081 memory: 5828 grad_norm: 3.0573 loss: 2.7283 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7283 2023/06/04 22:23:22 - mmengine - INFO - Epoch(train) [32][1420/2569] lr: 4.0000e-02 eta: 22:35:44 time: 0.2642 data_time: 0.0079 memory: 5828 grad_norm: 3.0235 loss: 2.6999 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6999 2023/06/04 22:23:28 - mmengine - INFO - Epoch(train) [32][1440/2569] lr: 4.0000e-02 eta: 22:35:39 time: 0.2693 data_time: 0.0081 memory: 5828 grad_norm: 3.0030 loss: 2.7027 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7027 2023/06/04 22:23:33 - mmengine - INFO - Epoch(train) [32][1460/2569] lr: 4.0000e-02 eta: 22:35:33 time: 0.2593 data_time: 0.0084 memory: 5828 grad_norm: 2.9306 loss: 2.7051 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7051 2023/06/04 22:23:38 - mmengine - INFO - Epoch(train) [32][1480/2569] lr: 4.0000e-02 eta: 22:35:28 time: 0.2695 data_time: 0.0083 memory: 5828 grad_norm: 3.0264 loss: 2.6390 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6390 2023/06/04 22:23:44 - mmengine - INFO - Epoch(train) [32][1500/2569] lr: 4.0000e-02 eta: 22:35:23 time: 0.2732 data_time: 0.0088 memory: 5828 grad_norm: 3.0237 loss: 2.7835 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7835 2023/06/04 22:23:49 - mmengine - INFO - Epoch(train) [32][1520/2569] lr: 4.0000e-02 eta: 22:35:17 time: 0.2650 data_time: 0.0083 memory: 5828 grad_norm: 3.0318 loss: 2.2670 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.2670 2023/06/04 22:23:54 - mmengine - INFO - Epoch(train) [32][1540/2569] lr: 4.0000e-02 eta: 22:35:11 time: 0.2576 data_time: 0.0082 memory: 5828 grad_norm: 3.0005 loss: 2.4920 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4920 2023/06/04 22:24:00 - mmengine - INFO - Epoch(train) [32][1560/2569] lr: 4.0000e-02 eta: 22:35:06 time: 0.2711 data_time: 0.0090 memory: 5828 grad_norm: 3.0391 loss: 2.8379 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8379 2023/06/04 22:24:05 - mmengine - INFO - Epoch(train) [32][1580/2569] lr: 4.0000e-02 eta: 22:35:01 time: 0.2680 data_time: 0.0081 memory: 5828 grad_norm: 2.9828 loss: 2.4842 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4842 2023/06/04 22:24:11 - mmengine - INFO - Epoch(train) [32][1600/2569] lr: 4.0000e-02 eta: 22:34:56 time: 0.2806 data_time: 0.0084 memory: 5828 grad_norm: 3.0262 loss: 2.6141 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6141 2023/06/04 22:24:16 - mmengine - INFO - Epoch(train) [32][1620/2569] lr: 4.0000e-02 eta: 22:34:51 time: 0.2653 data_time: 0.0082 memory: 5828 grad_norm: 3.0073 loss: 2.3990 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3990 2023/06/04 22:24:21 - mmengine - INFO - Epoch(train) [32][1640/2569] lr: 4.0000e-02 eta: 22:34:46 time: 0.2675 data_time: 0.0078 memory: 5828 grad_norm: 3.0187 loss: 2.5709 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5709 2023/06/04 22:24:27 - mmengine - INFO - Epoch(train) [32][1660/2569] lr: 4.0000e-02 eta: 22:34:40 time: 0.2644 data_time: 0.0090 memory: 5828 grad_norm: 2.9853 loss: 2.5246 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5246 2023/06/04 22:24:32 - mmengine - INFO - Epoch(train) [32][1680/2569] lr: 4.0000e-02 eta: 22:34:34 time: 0.2618 data_time: 0.0076 memory: 5828 grad_norm: 2.9480 loss: 2.7816 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7816 2023/06/04 22:24:37 - mmengine - INFO - Epoch(train) [32][1700/2569] lr: 4.0000e-02 eta: 22:34:29 time: 0.2616 data_time: 0.0092 memory: 5828 grad_norm: 3.0086 loss: 2.2501 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2501 2023/06/04 22:24:42 - mmengine - INFO - Epoch(train) [32][1720/2569] lr: 4.0000e-02 eta: 22:34:23 time: 0.2656 data_time: 0.0084 memory: 5828 grad_norm: 3.0364 loss: 2.4282 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4282 2023/06/04 22:24:48 - mmengine - INFO - Epoch(train) [32][1740/2569] lr: 4.0000e-02 eta: 22:34:18 time: 0.2701 data_time: 0.0081 memory: 5828 grad_norm: 3.0253 loss: 2.5601 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5601 2023/06/04 22:24:53 - mmengine - INFO - Epoch(train) [32][1760/2569] lr: 4.0000e-02 eta: 22:34:12 time: 0.2655 data_time: 0.0090 memory: 5828 grad_norm: 3.0133 loss: 2.6531 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6531 2023/06/04 22:24:59 - mmengine - INFO - Epoch(train) [32][1780/2569] lr: 4.0000e-02 eta: 22:34:07 time: 0.2698 data_time: 0.0080 memory: 5828 grad_norm: 3.0255 loss: 2.6337 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6337 2023/06/04 22:25:04 - mmengine - INFO - Epoch(train) [32][1800/2569] lr: 4.0000e-02 eta: 22:34:02 time: 0.2657 data_time: 0.0084 memory: 5828 grad_norm: 3.0184 loss: 2.4625 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4625 2023/06/04 22:25:09 - mmengine - INFO - Epoch(train) [32][1820/2569] lr: 4.0000e-02 eta: 22:33:56 time: 0.2605 data_time: 0.0078 memory: 5828 grad_norm: 3.0271 loss: 2.6539 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6539 2023/06/04 22:25:14 - mmengine - INFO - Epoch(train) [32][1840/2569] lr: 4.0000e-02 eta: 22:33:50 time: 0.2605 data_time: 0.0085 memory: 5828 grad_norm: 3.0163 loss: 2.2224 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2224 2023/06/04 22:25:20 - mmengine - INFO - Epoch(train) [32][1860/2569] lr: 4.0000e-02 eta: 22:33:44 time: 0.2608 data_time: 0.0084 memory: 5828 grad_norm: 2.9820 loss: 2.6397 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6397 2023/06/04 22:25:25 - mmengine - INFO - Epoch(train) [32][1880/2569] lr: 4.0000e-02 eta: 22:33:39 time: 0.2636 data_time: 0.0082 memory: 5828 grad_norm: 3.0370 loss: 2.8150 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8150 2023/06/04 22:25:30 - mmengine - INFO - Epoch(train) [32][1900/2569] lr: 4.0000e-02 eta: 22:33:33 time: 0.2615 data_time: 0.0085 memory: 5828 grad_norm: 3.2550 loss: 2.7218 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7218 2023/06/04 22:25:35 - mmengine - INFO - Epoch(train) [32][1920/2569] lr: 4.0000e-02 eta: 22:33:27 time: 0.2664 data_time: 0.0080 memory: 5828 grad_norm: 2.9635 loss: 2.4380 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4380 2023/06/04 22:25:41 - mmengine - INFO - Epoch(train) [32][1940/2569] lr: 4.0000e-02 eta: 22:33:22 time: 0.2666 data_time: 0.0080 memory: 5828 grad_norm: 2.9874 loss: 2.6185 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6185 2023/06/04 22:25:46 - mmengine - INFO - Epoch(train) [32][1960/2569] lr: 4.0000e-02 eta: 22:33:17 time: 0.2712 data_time: 0.0075 memory: 5828 grad_norm: 3.0445 loss: 2.6942 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6942 2023/06/04 22:25:52 - mmengine - INFO - Epoch(train) [32][1980/2569] lr: 4.0000e-02 eta: 22:33:12 time: 0.2699 data_time: 0.0079 memory: 5828 grad_norm: 3.0190 loss: 2.8112 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8112 2023/06/04 22:25:57 - mmengine - INFO - Epoch(train) [32][2000/2569] lr: 4.0000e-02 eta: 22:33:07 time: 0.2681 data_time: 0.0076 memory: 5828 grad_norm: 3.0046 loss: 3.0326 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0326 2023/06/04 22:26:02 - mmengine - INFO - Epoch(train) [32][2020/2569] lr: 4.0000e-02 eta: 22:33:01 time: 0.2669 data_time: 0.0075 memory: 5828 grad_norm: 3.0230 loss: 2.7450 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7450 2023/06/04 22:26:08 - mmengine - INFO - Epoch(train) [32][2040/2569] lr: 4.0000e-02 eta: 22:32:56 time: 0.2669 data_time: 0.0078 memory: 5828 grad_norm: 2.9689 loss: 2.8043 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8043 2023/06/04 22:26:13 - mmengine - INFO - Epoch(train) [32][2060/2569] lr: 4.0000e-02 eta: 22:32:50 time: 0.2651 data_time: 0.0078 memory: 5828 grad_norm: 3.0172 loss: 2.4492 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4492 2023/06/04 22:26:18 - mmengine - INFO - Epoch(train) [32][2080/2569] lr: 4.0000e-02 eta: 22:32:45 time: 0.2635 data_time: 0.0082 memory: 5828 grad_norm: 2.9527 loss: 2.7978 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7978 2023/06/04 22:26:24 - mmengine - INFO - Epoch(train) [32][2100/2569] lr: 4.0000e-02 eta: 22:32:39 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 3.0078 loss: 2.6692 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6692 2023/06/04 22:26:29 - mmengine - INFO - Epoch(train) [32][2120/2569] lr: 4.0000e-02 eta: 22:32:34 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 2.9704 loss: 2.6041 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6041 2023/06/04 22:26:34 - mmengine - INFO - Epoch(train) [32][2140/2569] lr: 4.0000e-02 eta: 22:32:28 time: 0.2655 data_time: 0.0078 memory: 5828 grad_norm: 3.0427 loss: 2.6524 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6524 2023/06/04 22:26:39 - mmengine - INFO - Epoch(train) [32][2160/2569] lr: 4.0000e-02 eta: 22:32:22 time: 0.2590 data_time: 0.0073 memory: 5828 grad_norm: 2.9384 loss: 2.8982 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8982 2023/06/04 22:26:45 - mmengine - INFO - Epoch(train) [32][2180/2569] lr: 4.0000e-02 eta: 22:32:17 time: 0.2709 data_time: 0.0081 memory: 5828 grad_norm: 3.0278 loss: 2.7047 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7047 2023/06/04 22:26:50 - mmengine - INFO - Epoch(train) [32][2200/2569] lr: 4.0000e-02 eta: 22:32:12 time: 0.2643 data_time: 0.0079 memory: 5828 grad_norm: 3.0078 loss: 2.4443 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4443 2023/06/04 22:26:55 - mmengine - INFO - Epoch(train) [32][2220/2569] lr: 4.0000e-02 eta: 22:32:06 time: 0.2645 data_time: 0.0082 memory: 5828 grad_norm: 2.9847 loss: 2.5200 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5200 2023/06/04 22:27:01 - mmengine - INFO - Epoch(train) [32][2240/2569] lr: 4.0000e-02 eta: 22:32:01 time: 0.2702 data_time: 0.0078 memory: 5828 grad_norm: 3.0183 loss: 2.4780 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4780 2023/06/04 22:27:06 - mmengine - INFO - Epoch(train) [32][2260/2569] lr: 4.0000e-02 eta: 22:31:56 time: 0.2662 data_time: 0.0076 memory: 5828 grad_norm: 3.0526 loss: 2.4044 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4044 2023/06/04 22:27:12 - mmengine - INFO - Epoch(train) [32][2280/2569] lr: 4.0000e-02 eta: 22:31:51 time: 0.2767 data_time: 0.0084 memory: 5828 grad_norm: 3.0409 loss: 2.7605 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7605 2023/06/04 22:27:17 - mmengine - INFO - Epoch(train) [32][2300/2569] lr: 4.0000e-02 eta: 22:31:46 time: 0.2692 data_time: 0.0078 memory: 5828 grad_norm: 2.9434 loss: 2.7314 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7314 2023/06/04 22:27:22 - mmengine - INFO - Epoch(train) [32][2320/2569] lr: 4.0000e-02 eta: 22:31:40 time: 0.2682 data_time: 0.0078 memory: 5828 grad_norm: 2.9447 loss: 2.4608 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4608 2023/06/04 22:27:28 - mmengine - INFO - Epoch(train) [32][2340/2569] lr: 4.0000e-02 eta: 22:31:35 time: 0.2651 data_time: 0.0075 memory: 5828 grad_norm: 3.0175 loss: 2.8087 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8087 2023/06/04 22:27:33 - mmengine - INFO - Epoch(train) [32][2360/2569] lr: 4.0000e-02 eta: 22:31:30 time: 0.2695 data_time: 0.0080 memory: 5828 grad_norm: 2.9834 loss: 2.7241 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7241 2023/06/04 22:27:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:27:39 - mmengine - INFO - Epoch(train) [32][2380/2569] lr: 4.0000e-02 eta: 22:31:25 time: 0.2725 data_time: 0.0077 memory: 5828 grad_norm: 3.0016 loss: 2.9534 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9534 2023/06/04 22:27:44 - mmengine - INFO - Epoch(train) [32][2400/2569] lr: 4.0000e-02 eta: 22:31:19 time: 0.2604 data_time: 0.0082 memory: 5828 grad_norm: 3.0293 loss: 2.3979 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3979 2023/06/04 22:27:49 - mmengine - INFO - Epoch(train) [32][2420/2569] lr: 4.0000e-02 eta: 22:31:13 time: 0.2604 data_time: 0.0076 memory: 5828 grad_norm: 3.0263 loss: 2.6830 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6830 2023/06/04 22:27:54 - mmengine - INFO - Epoch(train) [32][2440/2569] lr: 4.0000e-02 eta: 22:31:07 time: 0.2625 data_time: 0.0080 memory: 5828 grad_norm: 2.9365 loss: 2.4887 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4887 2023/06/04 22:27:59 - mmengine - INFO - Epoch(train) [32][2460/2569] lr: 4.0000e-02 eta: 22:31:02 time: 0.2626 data_time: 0.0077 memory: 5828 grad_norm: 2.9990 loss: 2.4377 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4377 2023/06/04 22:28:05 - mmengine - INFO - Epoch(train) [32][2480/2569] lr: 4.0000e-02 eta: 22:30:56 time: 0.2668 data_time: 0.0076 memory: 5828 grad_norm: 3.0281 loss: 2.5740 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5740 2023/06/04 22:28:10 - mmengine - INFO - Epoch(train) [32][2500/2569] lr: 4.0000e-02 eta: 22:30:50 time: 0.2609 data_time: 0.0084 memory: 5828 grad_norm: 3.0563 loss: 2.7481 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7481 2023/06/04 22:28:15 - mmengine - INFO - Epoch(train) [32][2520/2569] lr: 4.0000e-02 eta: 22:30:45 time: 0.2724 data_time: 0.0080 memory: 5828 grad_norm: 3.0749 loss: 2.5388 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5388 2023/06/04 22:28:21 - mmengine - INFO - Epoch(train) [32][2540/2569] lr: 4.0000e-02 eta: 22:30:40 time: 0.2612 data_time: 0.0081 memory: 5828 grad_norm: 2.9683 loss: 2.9555 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9555 2023/06/04 22:28:26 - mmengine - INFO - Epoch(train) [32][2560/2569] lr: 4.0000e-02 eta: 22:30:35 time: 0.2801 data_time: 0.0082 memory: 5828 grad_norm: 3.0284 loss: 2.4704 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4704 2023/06/04 22:28:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:28:29 - mmengine - INFO - Epoch(train) [32][2569/2569] lr: 4.0000e-02 eta: 22:30:32 time: 0.2746 data_time: 0.0077 memory: 5828 grad_norm: 3.0162 loss: 2.5686 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5686 2023/06/04 22:28:29 - mmengine - INFO - Saving checkpoint at 32 epochs 2023/06/04 22:28:37 - mmengine - INFO - Epoch(train) [33][ 20/2569] lr: 4.0000e-02 eta: 22:30:31 time: 0.3294 data_time: 0.0585 memory: 5828 grad_norm: 2.9937 loss: 2.3778 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3778 2023/06/04 22:28:43 - mmengine - INFO - Epoch(train) [33][ 40/2569] lr: 4.0000e-02 eta: 22:30:26 time: 0.2699 data_time: 0.0077 memory: 5828 grad_norm: 2.9865 loss: 2.3082 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3082 2023/06/04 22:28:48 - mmengine - INFO - Epoch(train) [33][ 60/2569] lr: 4.0000e-02 eta: 22:30:21 time: 0.2649 data_time: 0.0077 memory: 5828 grad_norm: 3.0453 loss: 2.9308 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9308 2023/06/04 22:28:54 - mmengine - INFO - Epoch(train) [33][ 80/2569] lr: 4.0000e-02 eta: 22:30:16 time: 0.2764 data_time: 0.0086 memory: 5828 grad_norm: 2.9959 loss: 2.5361 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5361 2023/06/04 22:28:59 - mmengine - INFO - Epoch(train) [33][ 100/2569] lr: 4.0000e-02 eta: 22:30:10 time: 0.2630 data_time: 0.0087 memory: 5828 grad_norm: 2.9870 loss: 2.6805 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6805 2023/06/04 22:29:04 - mmengine - INFO - Epoch(train) [33][ 120/2569] lr: 4.0000e-02 eta: 22:30:05 time: 0.2685 data_time: 0.0083 memory: 5828 grad_norm: 3.0031 loss: 2.4788 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4788 2023/06/04 22:29:10 - mmengine - INFO - Epoch(train) [33][ 140/2569] lr: 4.0000e-02 eta: 22:30:00 time: 0.2702 data_time: 0.0081 memory: 5828 grad_norm: 3.0027 loss: 2.2927 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2927 2023/06/04 22:29:15 - mmengine - INFO - Epoch(train) [33][ 160/2569] lr: 4.0000e-02 eta: 22:29:55 time: 0.2697 data_time: 0.0077 memory: 5828 grad_norm: 2.9708 loss: 2.4917 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4917 2023/06/04 22:29:20 - mmengine - INFO - Epoch(train) [33][ 180/2569] lr: 4.0000e-02 eta: 22:29:50 time: 0.2693 data_time: 0.0078 memory: 5828 grad_norm: 3.0532 loss: 2.6416 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6416 2023/06/04 22:29:26 - mmengine - INFO - Epoch(train) [33][ 200/2569] lr: 4.0000e-02 eta: 22:29:44 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 2.9502 loss: 2.7089 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7089 2023/06/04 22:29:31 - mmengine - INFO - Epoch(train) [33][ 220/2569] lr: 4.0000e-02 eta: 22:29:39 time: 0.2729 data_time: 0.0075 memory: 5828 grad_norm: 2.9940 loss: 2.7684 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7684 2023/06/04 22:29:36 - mmengine - INFO - Epoch(train) [33][ 240/2569] lr: 4.0000e-02 eta: 22:29:33 time: 0.2619 data_time: 0.0079 memory: 5828 grad_norm: 3.0234 loss: 2.6339 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6339 2023/06/04 22:29:42 - mmengine - INFO - Epoch(train) [33][ 260/2569] lr: 4.0000e-02 eta: 22:29:28 time: 0.2714 data_time: 0.0081 memory: 5828 grad_norm: 3.0221 loss: 2.4222 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4222 2023/06/04 22:29:47 - mmengine - INFO - Epoch(train) [33][ 280/2569] lr: 4.0000e-02 eta: 22:29:22 time: 0.2598 data_time: 0.0077 memory: 5828 grad_norm: 3.0317 loss: 2.4181 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4181 2023/06/04 22:29:52 - mmengine - INFO - Epoch(train) [33][ 300/2569] lr: 4.0000e-02 eta: 22:29:17 time: 0.2651 data_time: 0.0082 memory: 5828 grad_norm: 3.0178 loss: 2.4297 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4297 2023/06/04 22:29:57 - mmengine - INFO - Epoch(train) [33][ 320/2569] lr: 4.0000e-02 eta: 22:29:11 time: 0.2592 data_time: 0.0080 memory: 5828 grad_norm: 3.0097 loss: 2.2762 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2762 2023/06/04 22:30:03 - mmengine - INFO - Epoch(train) [33][ 340/2569] lr: 4.0000e-02 eta: 22:29:05 time: 0.2607 data_time: 0.0080 memory: 5828 grad_norm: 3.0740 loss: 2.2727 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2727 2023/06/04 22:30:08 - mmengine - INFO - Epoch(train) [33][ 360/2569] lr: 4.0000e-02 eta: 22:28:59 time: 0.2593 data_time: 0.0086 memory: 5828 grad_norm: 3.0337 loss: 2.8010 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.8010 2023/06/04 22:30:13 - mmengine - INFO - Epoch(train) [33][ 380/2569] lr: 4.0000e-02 eta: 22:28:54 time: 0.2653 data_time: 0.0077 memory: 5828 grad_norm: 3.0007 loss: 2.5534 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5534 2023/06/04 22:30:19 - mmengine - INFO - Epoch(train) [33][ 400/2569] lr: 4.0000e-02 eta: 22:28:49 time: 0.2706 data_time: 0.0081 memory: 5828 grad_norm: 3.0175 loss: 2.3817 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3817 2023/06/04 22:30:24 - mmengine - INFO - Epoch(train) [33][ 420/2569] lr: 4.0000e-02 eta: 22:28:43 time: 0.2716 data_time: 0.0079 memory: 5828 grad_norm: 3.0000 loss: 2.6529 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6529 2023/06/04 22:30:29 - mmengine - INFO - Epoch(train) [33][ 440/2569] lr: 4.0000e-02 eta: 22:28:38 time: 0.2690 data_time: 0.0084 memory: 5828 grad_norm: 3.0102 loss: 2.6388 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6388 2023/06/04 22:30:35 - mmengine - INFO - Epoch(train) [33][ 460/2569] lr: 4.0000e-02 eta: 22:28:33 time: 0.2659 data_time: 0.0076 memory: 5828 grad_norm: 3.0720 loss: 2.7845 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7845 2023/06/04 22:30:40 - mmengine - INFO - Epoch(train) [33][ 480/2569] lr: 4.0000e-02 eta: 22:28:27 time: 0.2629 data_time: 0.0077 memory: 5828 grad_norm: 2.9870 loss: 2.6028 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6028 2023/06/04 22:30:45 - mmengine - INFO - Epoch(train) [33][ 500/2569] lr: 4.0000e-02 eta: 22:28:22 time: 0.2644 data_time: 0.0078 memory: 5828 grad_norm: 2.9480 loss: 2.5090 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5090 2023/06/04 22:30:50 - mmengine - INFO - Epoch(train) [33][ 520/2569] lr: 4.0000e-02 eta: 22:28:16 time: 0.2590 data_time: 0.0075 memory: 5828 grad_norm: 2.9629 loss: 2.5480 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5480 2023/06/04 22:30:56 - mmengine - INFO - Epoch(train) [33][ 540/2569] lr: 4.0000e-02 eta: 22:28:10 time: 0.2666 data_time: 0.0078 memory: 5828 grad_norm: 2.9944 loss: 2.5431 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5431 2023/06/04 22:31:01 - mmengine - INFO - Epoch(train) [33][ 560/2569] lr: 4.0000e-02 eta: 22:28:04 time: 0.2610 data_time: 0.0080 memory: 5828 grad_norm: 3.0110 loss: 2.3934 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3934 2023/06/04 22:31:06 - mmengine - INFO - Epoch(train) [33][ 580/2569] lr: 4.0000e-02 eta: 22:27:59 time: 0.2681 data_time: 0.0076 memory: 5828 grad_norm: 2.9903 loss: 2.3677 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3677 2023/06/04 22:31:12 - mmengine - INFO - Epoch(train) [33][ 600/2569] lr: 4.0000e-02 eta: 22:27:54 time: 0.2662 data_time: 0.0077 memory: 5828 grad_norm: 2.9829 loss: 2.8433 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8433 2023/06/04 22:31:17 - mmengine - INFO - Epoch(train) [33][ 620/2569] lr: 4.0000e-02 eta: 22:27:48 time: 0.2689 data_time: 0.0078 memory: 5828 grad_norm: 3.0478 loss: 2.4821 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4821 2023/06/04 22:31:22 - mmengine - INFO - Epoch(train) [33][ 640/2569] lr: 4.0000e-02 eta: 22:27:43 time: 0.2641 data_time: 0.0086 memory: 5828 grad_norm: 3.0262 loss: 2.5811 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5811 2023/06/04 22:31:28 - mmengine - INFO - Epoch(train) [33][ 660/2569] lr: 4.0000e-02 eta: 22:27:37 time: 0.2615 data_time: 0.0079 memory: 5828 grad_norm: 3.0511 loss: 2.5322 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5322 2023/06/04 22:31:33 - mmengine - INFO - Epoch(train) [33][ 680/2569] lr: 4.0000e-02 eta: 22:27:31 time: 0.2591 data_time: 0.0081 memory: 5828 grad_norm: 2.9853 loss: 2.3582 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3582 2023/06/04 22:31:38 - mmengine - INFO - Epoch(train) [33][ 700/2569] lr: 4.0000e-02 eta: 22:27:26 time: 0.2704 data_time: 0.0073 memory: 5828 grad_norm: 3.0324 loss: 2.4982 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4982 2023/06/04 22:31:43 - mmengine - INFO - Epoch(train) [33][ 720/2569] lr: 4.0000e-02 eta: 22:27:20 time: 0.2627 data_time: 0.0081 memory: 5828 grad_norm: 3.0171 loss: 2.5991 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5991 2023/06/04 22:31:49 - mmengine - INFO - Epoch(train) [33][ 740/2569] lr: 4.0000e-02 eta: 22:27:15 time: 0.2707 data_time: 0.0080 memory: 5828 grad_norm: 3.0258 loss: 2.8227 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8227 2023/06/04 22:31:54 - mmengine - INFO - Epoch(train) [33][ 760/2569] lr: 4.0000e-02 eta: 22:27:10 time: 0.2704 data_time: 0.0078 memory: 5828 grad_norm: 3.0038 loss: 2.6613 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6613 2023/06/04 22:32:00 - mmengine - INFO - Epoch(train) [33][ 780/2569] lr: 4.0000e-02 eta: 22:27:05 time: 0.2654 data_time: 0.0079 memory: 5828 grad_norm: 3.0168 loss: 2.3199 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3199 2023/06/04 22:32:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:32:05 - mmengine - INFO - Epoch(train) [33][ 800/2569] lr: 4.0000e-02 eta: 22:26:59 time: 0.2691 data_time: 0.0080 memory: 5828 grad_norm: 3.0184 loss: 2.2937 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2937 2023/06/04 22:32:10 - mmengine - INFO - Epoch(train) [33][ 820/2569] lr: 4.0000e-02 eta: 22:26:54 time: 0.2642 data_time: 0.0082 memory: 5828 grad_norm: 2.9711 loss: 2.6340 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6340 2023/06/04 22:32:16 - mmengine - INFO - Epoch(train) [33][ 840/2569] lr: 4.0000e-02 eta: 22:26:49 time: 0.2730 data_time: 0.0080 memory: 5828 grad_norm: 3.0550 loss: 2.3759 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3759 2023/06/04 22:32:21 - mmengine - INFO - Epoch(train) [33][ 860/2569] lr: 4.0000e-02 eta: 22:26:44 time: 0.2674 data_time: 0.0075 memory: 5828 grad_norm: 3.0723 loss: 2.7313 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7313 2023/06/04 22:32:26 - mmengine - INFO - Epoch(train) [33][ 880/2569] lr: 4.0000e-02 eta: 22:26:38 time: 0.2646 data_time: 0.0080 memory: 5828 grad_norm: 3.0276 loss: 2.6939 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6939 2023/06/04 22:32:32 - mmengine - INFO - Epoch(train) [33][ 900/2569] lr: 4.0000e-02 eta: 22:26:32 time: 0.2601 data_time: 0.0080 memory: 5828 grad_norm: 3.0018 loss: 2.8223 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8223 2023/06/04 22:32:37 - mmengine - INFO - Epoch(train) [33][ 920/2569] lr: 4.0000e-02 eta: 22:26:27 time: 0.2635 data_time: 0.0080 memory: 5828 grad_norm: 2.9691 loss: 2.4635 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4635 2023/06/04 22:32:42 - mmengine - INFO - Epoch(train) [33][ 940/2569] lr: 4.0000e-02 eta: 22:26:21 time: 0.2699 data_time: 0.0085 memory: 5828 grad_norm: 3.0187 loss: 2.5608 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5608 2023/06/04 22:32:48 - mmengine - INFO - Epoch(train) [33][ 960/2569] lr: 4.0000e-02 eta: 22:26:16 time: 0.2647 data_time: 0.0078 memory: 5828 grad_norm: 3.0322 loss: 2.6195 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6195 2023/06/04 22:32:53 - mmengine - INFO - Epoch(train) [33][ 980/2569] lr: 4.0000e-02 eta: 22:26:10 time: 0.2663 data_time: 0.0083 memory: 5828 grad_norm: 3.0545 loss: 2.8376 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8376 2023/06/04 22:32:58 - mmengine - INFO - Epoch(train) [33][1000/2569] lr: 4.0000e-02 eta: 22:26:05 time: 0.2670 data_time: 0.0078 memory: 5828 grad_norm: 3.0164 loss: 2.5871 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5871 2023/06/04 22:33:04 - mmengine - INFO - Epoch(train) [33][1020/2569] lr: 4.0000e-02 eta: 22:26:00 time: 0.2700 data_time: 0.0078 memory: 5828 grad_norm: 3.0457 loss: 2.3770 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3770 2023/06/04 22:33:09 - mmengine - INFO - Epoch(train) [33][1040/2569] lr: 4.0000e-02 eta: 22:25:55 time: 0.2694 data_time: 0.0078 memory: 5828 grad_norm: 3.0033 loss: 2.6519 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6519 2023/06/04 22:33:14 - mmengine - INFO - Epoch(train) [33][1060/2569] lr: 4.0000e-02 eta: 22:25:49 time: 0.2681 data_time: 0.0080 memory: 5828 grad_norm: 3.0344 loss: 2.6163 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6163 2023/06/04 22:33:20 - mmengine - INFO - Epoch(train) [33][1080/2569] lr: 4.0000e-02 eta: 22:25:45 time: 0.2739 data_time: 0.0083 memory: 5828 grad_norm: 2.9861 loss: 2.4525 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4525 2023/06/04 22:33:25 - mmengine - INFO - Epoch(train) [33][1100/2569] lr: 4.0000e-02 eta: 22:25:39 time: 0.2658 data_time: 0.0079 memory: 5828 grad_norm: 2.9836 loss: 2.2928 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2928 2023/06/04 22:33:31 - mmengine - INFO - Epoch(train) [33][1120/2569] lr: 4.0000e-02 eta: 22:25:34 time: 0.2661 data_time: 0.0083 memory: 5828 grad_norm: 3.0329 loss: 2.6471 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6471 2023/06/04 22:33:36 - mmengine - INFO - Epoch(train) [33][1140/2569] lr: 4.0000e-02 eta: 22:25:28 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 2.9985 loss: 2.4628 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4628 2023/06/04 22:33:41 - mmengine - INFO - Epoch(train) [33][1160/2569] lr: 4.0000e-02 eta: 22:25:22 time: 0.2604 data_time: 0.0079 memory: 5828 grad_norm: 3.0002 loss: 2.6319 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6319 2023/06/04 22:33:46 - mmengine - INFO - Epoch(train) [33][1180/2569] lr: 4.0000e-02 eta: 22:25:16 time: 0.2631 data_time: 0.0079 memory: 5828 grad_norm: 3.0408 loss: 2.1445 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1445 2023/06/04 22:33:51 - mmengine - INFO - Epoch(train) [33][1200/2569] lr: 4.0000e-02 eta: 22:25:11 time: 0.2626 data_time: 0.0082 memory: 5828 grad_norm: 3.0330 loss: 2.7531 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7531 2023/06/04 22:33:57 - mmengine - INFO - Epoch(train) [33][1220/2569] lr: 4.0000e-02 eta: 22:25:05 time: 0.2592 data_time: 0.0080 memory: 5828 grad_norm: 3.0408 loss: 2.5613 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5613 2023/06/04 22:34:02 - mmengine - INFO - Epoch(train) [33][1240/2569] lr: 4.0000e-02 eta: 22:24:59 time: 0.2667 data_time: 0.0076 memory: 5828 grad_norm: 3.0738 loss: 2.6209 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6209 2023/06/04 22:34:07 - mmengine - INFO - Epoch(train) [33][1260/2569] lr: 4.0000e-02 eta: 22:24:54 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 3.0340 loss: 2.7956 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7956 2023/06/04 22:34:13 - mmengine - INFO - Epoch(train) [33][1280/2569] lr: 4.0000e-02 eta: 22:24:48 time: 0.2654 data_time: 0.0080 memory: 5828 grad_norm: 2.9787 loss: 2.4387 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4387 2023/06/04 22:34:18 - mmengine - INFO - Epoch(train) [33][1300/2569] lr: 4.0000e-02 eta: 22:24:43 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 3.0037 loss: 2.5416 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5416 2023/06/04 22:34:23 - mmengine - INFO - Epoch(train) [33][1320/2569] lr: 4.0000e-02 eta: 22:24:38 time: 0.2655 data_time: 0.0078 memory: 5828 grad_norm: 2.9987 loss: 2.7365 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7365 2023/06/04 22:34:29 - mmengine - INFO - Epoch(train) [33][1340/2569] lr: 4.0000e-02 eta: 22:24:32 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 2.9961 loss: 2.9074 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9074 2023/06/04 22:34:34 - mmengine - INFO - Epoch(train) [33][1360/2569] lr: 4.0000e-02 eta: 22:24:27 time: 0.2707 data_time: 0.0079 memory: 5828 grad_norm: 3.0018 loss: 2.6614 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6614 2023/06/04 22:34:40 - mmengine - INFO - Epoch(train) [33][1380/2569] lr: 4.0000e-02 eta: 22:24:22 time: 0.2759 data_time: 0.0077 memory: 5828 grad_norm: 2.9471 loss: 2.3549 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3549 2023/06/04 22:34:45 - mmengine - INFO - Epoch(train) [33][1400/2569] lr: 4.0000e-02 eta: 22:24:17 time: 0.2703 data_time: 0.0087 memory: 5828 grad_norm: 3.0295 loss: 2.7108 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7108 2023/06/04 22:34:50 - mmengine - INFO - Epoch(train) [33][1420/2569] lr: 4.0000e-02 eta: 22:24:12 time: 0.2646 data_time: 0.0078 memory: 5828 grad_norm: 2.9773 loss: 2.6824 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6824 2023/06/04 22:34:56 - mmengine - INFO - Epoch(train) [33][1440/2569] lr: 4.0000e-02 eta: 22:24:07 time: 0.2752 data_time: 0.0077 memory: 5828 grad_norm: 2.9987 loss: 2.6452 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6452 2023/06/04 22:35:01 - mmengine - INFO - Epoch(train) [33][1460/2569] lr: 4.0000e-02 eta: 22:24:02 time: 0.2731 data_time: 0.0080 memory: 5828 grad_norm: 3.0333 loss: 2.7918 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7918 2023/06/04 22:35:07 - mmengine - INFO - Epoch(train) [33][1480/2569] lr: 4.0000e-02 eta: 22:23:57 time: 0.2752 data_time: 0.0081 memory: 5828 grad_norm: 2.9758 loss: 2.6595 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6595 2023/06/04 22:35:12 - mmengine - INFO - Epoch(train) [33][1500/2569] lr: 4.0000e-02 eta: 22:23:52 time: 0.2752 data_time: 0.0078 memory: 5828 grad_norm: 3.0569 loss: 2.3458 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3458 2023/06/04 22:35:18 - mmengine - INFO - Epoch(train) [33][1520/2569] lr: 4.0000e-02 eta: 22:23:48 time: 0.2747 data_time: 0.0077 memory: 5828 grad_norm: 3.0690 loss: 2.6010 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6010 2023/06/04 22:35:23 - mmengine - INFO - Epoch(train) [33][1540/2569] lr: 4.0000e-02 eta: 22:23:42 time: 0.2611 data_time: 0.0076 memory: 5828 grad_norm: 2.9990 loss: 2.8028 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.8028 2023/06/04 22:35:28 - mmengine - INFO - Epoch(train) [33][1560/2569] lr: 4.0000e-02 eta: 22:23:37 time: 0.2744 data_time: 0.0082 memory: 5828 grad_norm: 2.9968 loss: 2.5573 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5573 2023/06/04 22:35:34 - mmengine - INFO - Epoch(train) [33][1580/2569] lr: 4.0000e-02 eta: 22:23:31 time: 0.2645 data_time: 0.0084 memory: 5828 grad_norm: 2.9546 loss: 2.4300 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4300 2023/06/04 22:35:39 - mmengine - INFO - Epoch(train) [33][1600/2569] lr: 4.0000e-02 eta: 22:23:26 time: 0.2733 data_time: 0.0077 memory: 5828 grad_norm: 3.0284 loss: 2.7761 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7761 2023/06/04 22:35:44 - mmengine - INFO - Epoch(train) [33][1620/2569] lr: 4.0000e-02 eta: 22:23:21 time: 0.2610 data_time: 0.0082 memory: 5828 grad_norm: 2.9846 loss: 2.3726 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3726 2023/06/04 22:35:50 - mmengine - INFO - Epoch(train) [33][1640/2569] lr: 4.0000e-02 eta: 22:23:15 time: 0.2694 data_time: 0.0079 memory: 5828 grad_norm: 3.0197 loss: 2.1981 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1981 2023/06/04 22:35:55 - mmengine - INFO - Epoch(train) [33][1660/2569] lr: 4.0000e-02 eta: 22:23:10 time: 0.2605 data_time: 0.0083 memory: 5828 grad_norm: 3.0286 loss: 2.3598 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3598 2023/06/04 22:36:00 - mmengine - INFO - Epoch(train) [33][1680/2569] lr: 4.0000e-02 eta: 22:23:04 time: 0.2600 data_time: 0.0078 memory: 5828 grad_norm: 3.0481 loss: 2.6649 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6649 2023/06/04 22:36:06 - mmengine - INFO - Epoch(train) [33][1700/2569] lr: 4.0000e-02 eta: 22:22:59 time: 0.2701 data_time: 0.0082 memory: 5828 grad_norm: 3.0194 loss: 3.0292 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0292 2023/06/04 22:36:11 - mmengine - INFO - Epoch(train) [33][1720/2569] lr: 4.0000e-02 eta: 22:22:53 time: 0.2590 data_time: 0.0079 memory: 5828 grad_norm: 2.9579 loss: 2.5287 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5287 2023/06/04 22:36:16 - mmengine - INFO - Epoch(train) [33][1740/2569] lr: 4.0000e-02 eta: 22:22:47 time: 0.2690 data_time: 0.0082 memory: 5828 grad_norm: 3.0378 loss: 2.7946 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7946 2023/06/04 22:36:21 - mmengine - INFO - Epoch(train) [33][1760/2569] lr: 4.0000e-02 eta: 22:22:41 time: 0.2581 data_time: 0.0080 memory: 5828 grad_norm: 3.0664 loss: 2.1864 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1864 2023/06/04 22:36:27 - mmengine - INFO - Epoch(train) [33][1780/2569] lr: 4.0000e-02 eta: 22:22:36 time: 0.2625 data_time: 0.0082 memory: 5828 grad_norm: 3.0369 loss: 2.9149 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9149 2023/06/04 22:36:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:36:32 - mmengine - INFO - Epoch(train) [33][1800/2569] lr: 4.0000e-02 eta: 22:22:30 time: 0.2589 data_time: 0.0101 memory: 5828 grad_norm: 3.0212 loss: 2.8595 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8595 2023/06/04 22:36:37 - mmengine - INFO - Epoch(train) [33][1820/2569] lr: 4.0000e-02 eta: 22:22:24 time: 0.2614 data_time: 0.0077 memory: 5828 grad_norm: 2.9473 loss: 2.4932 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4932 2023/06/04 22:36:42 - mmengine - INFO - Epoch(train) [33][1840/2569] lr: 4.0000e-02 eta: 22:22:19 time: 0.2657 data_time: 0.0083 memory: 5828 grad_norm: 3.0606 loss: 2.7554 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7554 2023/06/04 22:36:48 - mmengine - INFO - Epoch(train) [33][1860/2569] lr: 4.0000e-02 eta: 22:22:13 time: 0.2655 data_time: 0.0079 memory: 5828 grad_norm: 3.0079 loss: 2.8247 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8247 2023/06/04 22:36:53 - mmengine - INFO - Epoch(train) [33][1880/2569] lr: 4.0000e-02 eta: 22:22:08 time: 0.2666 data_time: 0.0077 memory: 5828 grad_norm: 3.0171 loss: 2.8252 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8252 2023/06/04 22:36:58 - mmengine - INFO - Epoch(train) [33][1900/2569] lr: 4.0000e-02 eta: 22:22:02 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 2.9936 loss: 2.3198 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3198 2023/06/04 22:37:04 - mmengine - INFO - Epoch(train) [33][1920/2569] lr: 4.0000e-02 eta: 22:21:57 time: 0.2636 data_time: 0.0081 memory: 5828 grad_norm: 2.9906 loss: 2.8603 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8603 2023/06/04 22:37:09 - mmengine - INFO - Epoch(train) [33][1940/2569] lr: 4.0000e-02 eta: 22:21:51 time: 0.2582 data_time: 0.0076 memory: 5828 grad_norm: 3.0609 loss: 2.8123 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8123 2023/06/04 22:37:14 - mmengine - INFO - Epoch(train) [33][1960/2569] lr: 4.0000e-02 eta: 22:21:45 time: 0.2688 data_time: 0.0093 memory: 5828 grad_norm: 3.0345 loss: 2.4800 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4800 2023/06/04 22:37:19 - mmengine - INFO - Epoch(train) [33][1980/2569] lr: 4.0000e-02 eta: 22:21:40 time: 0.2645 data_time: 0.0081 memory: 5828 grad_norm: 3.1047 loss: 2.4536 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4536 2023/06/04 22:37:25 - mmengine - INFO - Epoch(train) [33][2000/2569] lr: 4.0000e-02 eta: 22:21:34 time: 0.2587 data_time: 0.0081 memory: 5828 grad_norm: 2.9876 loss: 2.3544 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3544 2023/06/04 22:37:30 - mmengine - INFO - Epoch(train) [33][2020/2569] lr: 4.0000e-02 eta: 22:21:28 time: 0.2632 data_time: 0.0080 memory: 5828 grad_norm: 3.0164 loss: 2.6690 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6690 2023/06/04 22:37:35 - mmengine - INFO - Epoch(train) [33][2040/2569] lr: 4.0000e-02 eta: 22:21:22 time: 0.2595 data_time: 0.0081 memory: 5828 grad_norm: 3.0189 loss: 2.6007 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6007 2023/06/04 22:37:40 - mmengine - INFO - Epoch(train) [33][2060/2569] lr: 4.0000e-02 eta: 22:21:17 time: 0.2659 data_time: 0.0078 memory: 5828 grad_norm: 2.9784 loss: 2.4627 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4627 2023/06/04 22:37:46 - mmengine - INFO - Epoch(train) [33][2080/2569] lr: 4.0000e-02 eta: 22:21:11 time: 0.2592 data_time: 0.0077 memory: 5828 grad_norm: 3.0235 loss: 2.4535 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4535 2023/06/04 22:37:51 - mmengine - INFO - Epoch(train) [33][2100/2569] lr: 4.0000e-02 eta: 22:21:05 time: 0.2627 data_time: 0.0076 memory: 5828 grad_norm: 3.0195 loss: 2.6772 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6772 2023/06/04 22:37:56 - mmengine - INFO - Epoch(train) [33][2120/2569] lr: 4.0000e-02 eta: 22:21:00 time: 0.2648 data_time: 0.0081 memory: 5828 grad_norm: 3.0485 loss: 2.5573 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5573 2023/06/04 22:38:02 - mmengine - INFO - Epoch(train) [33][2140/2569] lr: 4.0000e-02 eta: 22:20:54 time: 0.2655 data_time: 0.0079 memory: 5828 grad_norm: 3.0145 loss: 2.5203 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5203 2023/06/04 22:38:07 - mmengine - INFO - Epoch(train) [33][2160/2569] lr: 4.0000e-02 eta: 22:20:49 time: 0.2655 data_time: 0.0082 memory: 5828 grad_norm: 3.0624 loss: 2.6761 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6761 2023/06/04 22:38:12 - mmengine - INFO - Epoch(train) [33][2180/2569] lr: 4.0000e-02 eta: 22:20:43 time: 0.2587 data_time: 0.0079 memory: 5828 grad_norm: 2.9447 loss: 2.3917 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3917 2023/06/04 22:38:17 - mmengine - INFO - Epoch(train) [33][2200/2569] lr: 4.0000e-02 eta: 22:20:37 time: 0.2621 data_time: 0.0077 memory: 5828 grad_norm: 2.9987 loss: 2.8435 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8435 2023/06/04 22:38:23 - mmengine - INFO - Epoch(train) [33][2220/2569] lr: 4.0000e-02 eta: 22:20:32 time: 0.2632 data_time: 0.0079 memory: 5828 grad_norm: 3.0644 loss: 2.5342 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5342 2023/06/04 22:38:28 - mmengine - INFO - Epoch(train) [33][2240/2569] lr: 4.0000e-02 eta: 22:20:26 time: 0.2620 data_time: 0.0082 memory: 5828 grad_norm: 3.0263 loss: 2.6008 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6008 2023/06/04 22:38:33 - mmengine - INFO - Epoch(train) [33][2260/2569] lr: 4.0000e-02 eta: 22:20:20 time: 0.2603 data_time: 0.0077 memory: 5828 grad_norm: 2.9815 loss: 2.5296 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.5296 2023/06/04 22:38:38 - mmengine - INFO - Epoch(train) [33][2280/2569] lr: 4.0000e-02 eta: 22:20:14 time: 0.2599 data_time: 0.0077 memory: 5828 grad_norm: 3.0318 loss: 2.6233 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6233 2023/06/04 22:38:44 - mmengine - INFO - Epoch(train) [33][2300/2569] lr: 4.0000e-02 eta: 22:20:09 time: 0.2682 data_time: 0.0079 memory: 5828 grad_norm: 2.9893 loss: 2.5867 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5867 2023/06/04 22:38:49 - mmengine - INFO - Epoch(train) [33][2320/2569] lr: 4.0000e-02 eta: 22:20:04 time: 0.2719 data_time: 0.0077 memory: 5828 grad_norm: 3.0362 loss: 2.5504 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5504 2023/06/04 22:38:54 - mmengine - INFO - Epoch(train) [33][2340/2569] lr: 4.0000e-02 eta: 22:19:58 time: 0.2613 data_time: 0.0078 memory: 5828 grad_norm: 2.9745 loss: 2.4969 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4969 2023/06/04 22:39:00 - mmengine - INFO - Epoch(train) [33][2360/2569] lr: 4.0000e-02 eta: 22:19:53 time: 0.2726 data_time: 0.0082 memory: 5828 grad_norm: 2.9707 loss: 2.4895 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4895 2023/06/04 22:39:05 - mmengine - INFO - Epoch(train) [33][2380/2569] lr: 4.0000e-02 eta: 22:19:47 time: 0.2600 data_time: 0.0083 memory: 5828 grad_norm: 3.0105 loss: 2.4678 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4678 2023/06/04 22:39:10 - mmengine - INFO - Epoch(train) [33][2400/2569] lr: 4.0000e-02 eta: 22:19:42 time: 0.2641 data_time: 0.0082 memory: 5828 grad_norm: 3.0698 loss: 2.5723 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5723 2023/06/04 22:39:15 - mmengine - INFO - Epoch(train) [33][2420/2569] lr: 4.0000e-02 eta: 22:19:36 time: 0.2651 data_time: 0.0077 memory: 5828 grad_norm: 3.0478 loss: 2.8019 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8019 2023/06/04 22:39:21 - mmengine - INFO - Epoch(train) [33][2440/2569] lr: 4.0000e-02 eta: 22:19:31 time: 0.2644 data_time: 0.0080 memory: 5828 grad_norm: 2.9859 loss: 2.9021 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9021 2023/06/04 22:39:26 - mmengine - INFO - Epoch(train) [33][2460/2569] lr: 4.0000e-02 eta: 22:19:25 time: 0.2597 data_time: 0.0079 memory: 5828 grad_norm: 3.0008 loss: 2.7387 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7387 2023/06/04 22:39:31 - mmengine - INFO - Epoch(train) [33][2480/2569] lr: 4.0000e-02 eta: 22:19:19 time: 0.2597 data_time: 0.0079 memory: 5828 grad_norm: 3.0277 loss: 2.7399 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7399 2023/06/04 22:39:36 - mmengine - INFO - Epoch(train) [33][2500/2569] lr: 4.0000e-02 eta: 22:19:13 time: 0.2651 data_time: 0.0079 memory: 5828 grad_norm: 3.0350 loss: 2.7276 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7276 2023/06/04 22:39:42 - mmengine - INFO - Epoch(train) [33][2520/2569] lr: 4.0000e-02 eta: 22:19:08 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 2.9921 loss: 2.4798 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4798 2023/06/04 22:39:47 - mmengine - INFO - Epoch(train) [33][2540/2569] lr: 4.0000e-02 eta: 22:19:03 time: 0.2711 data_time: 0.0079 memory: 5828 grad_norm: 3.0007 loss: 2.1706 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1706 2023/06/04 22:39:52 - mmengine - INFO - Epoch(train) [33][2560/2569] lr: 4.0000e-02 eta: 22:18:57 time: 0.2605 data_time: 0.0081 memory: 5828 grad_norm: 2.9897 loss: 2.5886 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5886 2023/06/04 22:39:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:39:55 - mmengine - INFO - Epoch(train) [33][2569/2569] lr: 4.0000e-02 eta: 22:18:54 time: 0.2589 data_time: 0.0076 memory: 5828 grad_norm: 3.0127 loss: 2.4347 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.4347 2023/06/04 22:40:02 - mmengine - INFO - Epoch(train) [34][ 20/2569] lr: 4.0000e-02 eta: 22:18:55 time: 0.3500 data_time: 0.0609 memory: 5828 grad_norm: 2.9827 loss: 2.4686 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4686 2023/06/04 22:40:07 - mmengine - INFO - Epoch(train) [34][ 40/2569] lr: 4.0000e-02 eta: 22:18:49 time: 0.2658 data_time: 0.0079 memory: 5828 grad_norm: 3.0522 loss: 2.4581 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4581 2023/06/04 22:40:12 - mmengine - INFO - Epoch(train) [34][ 60/2569] lr: 4.0000e-02 eta: 22:18:44 time: 0.2686 data_time: 0.0075 memory: 5828 grad_norm: 2.9839 loss: 2.6435 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6435 2023/06/04 22:40:18 - mmengine - INFO - Epoch(train) [34][ 80/2569] lr: 4.0000e-02 eta: 22:18:38 time: 0.2599 data_time: 0.0084 memory: 5828 grad_norm: 3.0393 loss: 2.6968 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6968 2023/06/04 22:40:23 - mmengine - INFO - Epoch(train) [34][ 100/2569] lr: 4.0000e-02 eta: 22:18:33 time: 0.2643 data_time: 0.0081 memory: 5828 grad_norm: 3.0036 loss: 2.6927 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6927 2023/06/04 22:40:28 - mmengine - INFO - Epoch(train) [34][ 120/2569] lr: 4.0000e-02 eta: 22:18:27 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 3.0228 loss: 2.4832 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4832 2023/06/04 22:40:33 - mmengine - INFO - Epoch(train) [34][ 140/2569] lr: 4.0000e-02 eta: 22:18:21 time: 0.2589 data_time: 0.0074 memory: 5828 grad_norm: 2.9778 loss: 2.7951 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7951 2023/06/04 22:40:39 - mmengine - INFO - Epoch(train) [34][ 160/2569] lr: 4.0000e-02 eta: 22:18:16 time: 0.2700 data_time: 0.0078 memory: 5828 grad_norm: 3.0097 loss: 2.3586 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3586 2023/06/04 22:40:44 - mmengine - INFO - Epoch(train) [34][ 180/2569] lr: 4.0000e-02 eta: 22:18:10 time: 0.2634 data_time: 0.0083 memory: 5828 grad_norm: 3.0363 loss: 2.5014 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5014 2023/06/04 22:40:49 - mmengine - INFO - Epoch(train) [34][ 200/2569] lr: 4.0000e-02 eta: 22:18:04 time: 0.2575 data_time: 0.0080 memory: 5828 grad_norm: 3.0310 loss: 2.5220 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5220 2023/06/04 22:40:55 - mmengine - INFO - Epoch(train) [34][ 220/2569] lr: 4.0000e-02 eta: 22:17:59 time: 0.2728 data_time: 0.0078 memory: 5828 grad_norm: 3.0098 loss: 2.5949 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5949 2023/06/04 22:40:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:41:00 - mmengine - INFO - Epoch(train) [34][ 240/2569] lr: 4.0000e-02 eta: 22:17:54 time: 0.2673 data_time: 0.0074 memory: 5828 grad_norm: 2.9547 loss: 3.1788 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1788 2023/06/04 22:41:05 - mmengine - INFO - Epoch(train) [34][ 260/2569] lr: 4.0000e-02 eta: 22:17:49 time: 0.2700 data_time: 0.0078 memory: 5828 grad_norm: 3.0151 loss: 2.5185 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5185 2023/06/04 22:41:11 - mmengine - INFO - Epoch(train) [34][ 280/2569] lr: 4.0000e-02 eta: 22:17:44 time: 0.2690 data_time: 0.0080 memory: 5828 grad_norm: 2.9722 loss: 2.6197 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6197 2023/06/04 22:41:16 - mmengine - INFO - Epoch(train) [34][ 300/2569] lr: 4.0000e-02 eta: 22:17:38 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 3.0051 loss: 2.6317 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6317 2023/06/04 22:41:21 - mmengine - INFO - Epoch(train) [34][ 320/2569] lr: 4.0000e-02 eta: 22:17:32 time: 0.2630 data_time: 0.0077 memory: 5828 grad_norm: 3.0406 loss: 2.4769 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4769 2023/06/04 22:41:27 - mmengine - INFO - Epoch(train) [34][ 340/2569] lr: 4.0000e-02 eta: 22:17:28 time: 0.2753 data_time: 0.0081 memory: 5828 grad_norm: 2.9877 loss: 2.4328 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4328 2023/06/04 22:41:32 - mmengine - INFO - Epoch(train) [34][ 360/2569] lr: 4.0000e-02 eta: 22:17:22 time: 0.2579 data_time: 0.0077 memory: 5828 grad_norm: 2.9609 loss: 2.8250 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8250 2023/06/04 22:41:37 - mmengine - INFO - Epoch(train) [34][ 380/2569] lr: 4.0000e-02 eta: 22:17:16 time: 0.2623 data_time: 0.0084 memory: 5828 grad_norm: 3.0453 loss: 2.7105 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7105 2023/06/04 22:41:43 - mmengine - INFO - Epoch(train) [34][ 400/2569] lr: 4.0000e-02 eta: 22:17:10 time: 0.2654 data_time: 0.0076 memory: 5828 grad_norm: 3.0708 loss: 2.6981 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6981 2023/06/04 22:41:48 - mmengine - INFO - Epoch(train) [34][ 420/2569] lr: 4.0000e-02 eta: 22:17:05 time: 0.2648 data_time: 0.0078 memory: 5828 grad_norm: 3.0477 loss: 2.4736 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4736 2023/06/04 22:41:53 - mmengine - INFO - Epoch(train) [34][ 440/2569] lr: 4.0000e-02 eta: 22:16:59 time: 0.2614 data_time: 0.0078 memory: 5828 grad_norm: 3.0206 loss: 2.6248 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6248 2023/06/04 22:41:58 - mmengine - INFO - Epoch(train) [34][ 460/2569] lr: 4.0000e-02 eta: 22:16:54 time: 0.2653 data_time: 0.0078 memory: 5828 grad_norm: 2.9894 loss: 2.9020 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.9020 2023/06/04 22:42:04 - mmengine - INFO - Epoch(train) [34][ 480/2569] lr: 4.0000e-02 eta: 22:16:48 time: 0.2647 data_time: 0.0078 memory: 5828 grad_norm: 2.9949 loss: 2.5989 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5989 2023/06/04 22:42:09 - mmengine - INFO - Epoch(train) [34][ 500/2569] lr: 4.0000e-02 eta: 22:16:42 time: 0.2626 data_time: 0.0081 memory: 5828 grad_norm: 3.0345 loss: 2.6114 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6114 2023/06/04 22:42:14 - mmengine - INFO - Epoch(train) [34][ 520/2569] lr: 4.0000e-02 eta: 22:16:37 time: 0.2611 data_time: 0.0078 memory: 5828 grad_norm: 3.1085 loss: 2.4419 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4419 2023/06/04 22:42:20 - mmengine - INFO - Epoch(train) [34][ 540/2569] lr: 4.0000e-02 eta: 22:16:31 time: 0.2693 data_time: 0.0078 memory: 5828 grad_norm: 3.0192 loss: 2.7574 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7574 2023/06/04 22:42:25 - mmengine - INFO - Epoch(train) [34][ 560/2569] lr: 4.0000e-02 eta: 22:16:26 time: 0.2656 data_time: 0.0080 memory: 5828 grad_norm: 3.0513 loss: 2.6011 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6011 2023/06/04 22:42:30 - mmengine - INFO - Epoch(train) [34][ 580/2569] lr: 4.0000e-02 eta: 22:16:20 time: 0.2651 data_time: 0.0092 memory: 5828 grad_norm: 3.0306 loss: 2.3993 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3993 2023/06/04 22:42:36 - mmengine - INFO - Epoch(train) [34][ 600/2569] lr: 4.0000e-02 eta: 22:16:15 time: 0.2652 data_time: 0.0081 memory: 5828 grad_norm: 3.0448 loss: 2.5667 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5667 2023/06/04 22:42:41 - mmengine - INFO - Epoch(train) [34][ 620/2569] lr: 4.0000e-02 eta: 22:16:09 time: 0.2636 data_time: 0.0083 memory: 5828 grad_norm: 3.0020 loss: 2.7757 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7757 2023/06/04 22:42:46 - mmengine - INFO - Epoch(train) [34][ 640/2569] lr: 4.0000e-02 eta: 22:16:04 time: 0.2647 data_time: 0.0078 memory: 5828 grad_norm: 2.9591 loss: 2.5664 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5664 2023/06/04 22:42:51 - mmengine - INFO - Epoch(train) [34][ 660/2569] lr: 4.0000e-02 eta: 22:15:59 time: 0.2681 data_time: 0.0079 memory: 5828 grad_norm: 3.0321 loss: 2.5404 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5404 2023/06/04 22:42:57 - mmengine - INFO - Epoch(train) [34][ 680/2569] lr: 4.0000e-02 eta: 22:15:53 time: 0.2663 data_time: 0.0082 memory: 5828 grad_norm: 3.0487 loss: 2.7271 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7271 2023/06/04 22:43:02 - mmengine - INFO - Epoch(train) [34][ 700/2569] lr: 4.0000e-02 eta: 22:15:47 time: 0.2583 data_time: 0.0076 memory: 5828 grad_norm: 2.9787 loss: 2.4018 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4018 2023/06/04 22:43:07 - mmengine - INFO - Epoch(train) [34][ 720/2569] lr: 4.0000e-02 eta: 22:15:42 time: 0.2646 data_time: 0.0081 memory: 5828 grad_norm: 3.0547 loss: 2.6082 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6082 2023/06/04 22:43:13 - mmengine - INFO - Epoch(train) [34][ 740/2569] lr: 4.0000e-02 eta: 22:15:37 time: 0.2749 data_time: 0.0076 memory: 5828 grad_norm: 3.0501 loss: 2.8379 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8379 2023/06/04 22:43:18 - mmengine - INFO - Epoch(train) [34][ 760/2569] lr: 4.0000e-02 eta: 22:15:32 time: 0.2746 data_time: 0.0080 memory: 5828 grad_norm: 2.9672 loss: 2.3986 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3986 2023/06/04 22:43:24 - mmengine - INFO - Epoch(train) [34][ 780/2569] lr: 4.0000e-02 eta: 22:15:26 time: 0.2634 data_time: 0.0083 memory: 5828 grad_norm: 3.1127 loss: 2.4994 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4994 2023/06/04 22:43:29 - mmengine - INFO - Epoch(train) [34][ 800/2569] lr: 4.0000e-02 eta: 22:15:21 time: 0.2673 data_time: 0.0083 memory: 5828 grad_norm: 3.0810 loss: 2.8462 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8462 2023/06/04 22:43:34 - mmengine - INFO - Epoch(train) [34][ 820/2569] lr: 4.0000e-02 eta: 22:15:15 time: 0.2621 data_time: 0.0083 memory: 5828 grad_norm: 3.0822 loss: 2.7879 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7879 2023/06/04 22:43:40 - mmengine - INFO - Epoch(train) [34][ 840/2569] lr: 4.0000e-02 eta: 22:15:10 time: 0.2742 data_time: 0.0078 memory: 5828 grad_norm: 3.0681 loss: 2.6425 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6425 2023/06/04 22:43:45 - mmengine - INFO - Epoch(train) [34][ 860/2569] lr: 4.0000e-02 eta: 22:15:05 time: 0.2589 data_time: 0.0087 memory: 5828 grad_norm: 3.0501 loss: 2.6515 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6515 2023/06/04 22:43:50 - mmengine - INFO - Epoch(train) [34][ 880/2569] lr: 4.0000e-02 eta: 22:14:59 time: 0.2649 data_time: 0.0076 memory: 5828 grad_norm: 3.0058 loss: 2.8169 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8169 2023/06/04 22:43:55 - mmengine - INFO - Epoch(train) [34][ 900/2569] lr: 4.0000e-02 eta: 22:14:53 time: 0.2633 data_time: 0.0081 memory: 5828 grad_norm: 3.0339 loss: 2.4963 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4963 2023/06/04 22:44:01 - mmengine - INFO - Epoch(train) [34][ 920/2569] lr: 4.0000e-02 eta: 22:14:48 time: 0.2734 data_time: 0.0083 memory: 5828 grad_norm: 2.9976 loss: 2.4927 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4927 2023/06/04 22:44:06 - mmengine - INFO - Epoch(train) [34][ 940/2569] lr: 4.0000e-02 eta: 22:14:43 time: 0.2651 data_time: 0.0076 memory: 5828 grad_norm: 3.0327 loss: 2.7322 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7322 2023/06/04 22:44:11 - mmengine - INFO - Epoch(train) [34][ 960/2569] lr: 4.0000e-02 eta: 22:14:37 time: 0.2637 data_time: 0.0075 memory: 5828 grad_norm: 3.0242 loss: 2.7987 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7987 2023/06/04 22:44:17 - mmengine - INFO - Epoch(train) [34][ 980/2569] lr: 4.0000e-02 eta: 22:14:32 time: 0.2680 data_time: 0.0078 memory: 5828 grad_norm: 3.0547 loss: 2.4343 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4343 2023/06/04 22:44:22 - mmengine - INFO - Epoch(train) [34][1000/2569] lr: 4.0000e-02 eta: 22:14:26 time: 0.2627 data_time: 0.0079 memory: 5828 grad_norm: 3.0790 loss: 2.2774 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2774 2023/06/04 22:44:27 - mmengine - INFO - Epoch(train) [34][1020/2569] lr: 4.0000e-02 eta: 22:14:20 time: 0.2591 data_time: 0.0078 memory: 5828 grad_norm: 3.0293 loss: 2.8891 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8891 2023/06/04 22:44:32 - mmengine - INFO - Epoch(train) [34][1040/2569] lr: 4.0000e-02 eta: 22:14:15 time: 0.2610 data_time: 0.0081 memory: 5828 grad_norm: 2.9803 loss: 2.6536 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6536 2023/06/04 22:44:38 - mmengine - INFO - Epoch(train) [34][1060/2569] lr: 4.0000e-02 eta: 22:14:09 time: 0.2594 data_time: 0.0080 memory: 5828 grad_norm: 3.0318 loss: 2.3554 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3554 2023/06/04 22:44:43 - mmengine - INFO - Epoch(train) [34][1080/2569] lr: 4.0000e-02 eta: 22:14:03 time: 0.2639 data_time: 0.0083 memory: 5828 grad_norm: 3.0236 loss: 2.6699 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6699 2023/06/04 22:44:48 - mmengine - INFO - Epoch(train) [34][1100/2569] lr: 4.0000e-02 eta: 22:13:58 time: 0.2660 data_time: 0.0080 memory: 5828 grad_norm: 3.0567 loss: 2.6881 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6881 2023/06/04 22:44:54 - mmengine - INFO - Epoch(train) [34][1120/2569] lr: 4.0000e-02 eta: 22:13:53 time: 0.2694 data_time: 0.0089 memory: 5828 grad_norm: 3.0699 loss: 2.8093 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8093 2023/06/04 22:44:59 - mmengine - INFO - Epoch(train) [34][1140/2569] lr: 4.0000e-02 eta: 22:13:47 time: 0.2640 data_time: 0.0084 memory: 5828 grad_norm: 3.0307 loss: 2.5187 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5187 2023/06/04 22:45:04 - mmengine - INFO - Epoch(train) [34][1160/2569] lr: 4.0000e-02 eta: 22:13:41 time: 0.2624 data_time: 0.0083 memory: 5828 grad_norm: 3.0543 loss: 2.5895 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5895 2023/06/04 22:45:09 - mmengine - INFO - Epoch(train) [34][1180/2569] lr: 4.0000e-02 eta: 22:13:35 time: 0.2600 data_time: 0.0080 memory: 5828 grad_norm: 2.9925 loss: 2.5966 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5966 2023/06/04 22:45:15 - mmengine - INFO - Epoch(train) [34][1200/2569] lr: 4.0000e-02 eta: 22:13:30 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 3.0057 loss: 2.4797 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4797 2023/06/04 22:45:20 - mmengine - INFO - Epoch(train) [34][1220/2569] lr: 4.0000e-02 eta: 22:13:24 time: 0.2612 data_time: 0.0077 memory: 5828 grad_norm: 3.1132 loss: 2.4048 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4048 2023/06/04 22:45:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:45:25 - mmengine - INFO - Epoch(train) [34][1240/2569] lr: 4.0000e-02 eta: 22:13:19 time: 0.2729 data_time: 0.0080 memory: 5828 grad_norm: 3.0243 loss: 2.7533 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7533 2023/06/04 22:45:31 - mmengine - INFO - Epoch(train) [34][1260/2569] lr: 4.0000e-02 eta: 22:13:13 time: 0.2655 data_time: 0.0076 memory: 5828 grad_norm: 3.0042 loss: 2.3794 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3794 2023/06/04 22:45:36 - mmengine - INFO - Epoch(train) [34][1280/2569] lr: 4.0000e-02 eta: 22:13:08 time: 0.2707 data_time: 0.0081 memory: 5828 grad_norm: 3.0774 loss: 2.8785 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8785 2023/06/04 22:45:41 - mmengine - INFO - Epoch(train) [34][1300/2569] lr: 4.0000e-02 eta: 22:13:03 time: 0.2657 data_time: 0.0080 memory: 5828 grad_norm: 3.0066 loss: 2.5870 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5870 2023/06/04 22:45:47 - mmengine - INFO - Epoch(train) [34][1320/2569] lr: 4.0000e-02 eta: 22:12:57 time: 0.2631 data_time: 0.0080 memory: 5828 grad_norm: 3.0267 loss: 2.6357 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6357 2023/06/04 22:45:52 - mmengine - INFO - Epoch(train) [34][1340/2569] lr: 4.0000e-02 eta: 22:12:52 time: 0.2737 data_time: 0.0078 memory: 5828 grad_norm: 2.9969 loss: 2.6123 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6123 2023/06/04 22:45:57 - mmengine - INFO - Epoch(train) [34][1360/2569] lr: 4.0000e-02 eta: 22:12:47 time: 0.2635 data_time: 0.0078 memory: 5828 grad_norm: 3.0218 loss: 2.4197 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4197 2023/06/04 22:46:03 - mmengine - INFO - Epoch(train) [34][1380/2569] lr: 4.0000e-02 eta: 22:12:42 time: 0.2761 data_time: 0.0079 memory: 5828 grad_norm: 2.9949 loss: 2.9814 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9814 2023/06/04 22:46:08 - mmengine - INFO - Epoch(train) [34][1400/2569] lr: 4.0000e-02 eta: 22:12:37 time: 0.2682 data_time: 0.0087 memory: 5828 grad_norm: 3.0433 loss: 2.5471 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5471 2023/06/04 22:46:14 - mmengine - INFO - Epoch(train) [34][1420/2569] lr: 4.0000e-02 eta: 22:12:31 time: 0.2682 data_time: 0.0079 memory: 5828 grad_norm: 3.0204 loss: 2.5946 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5946 2023/06/04 22:46:19 - mmengine - INFO - Epoch(train) [34][1440/2569] lr: 4.0000e-02 eta: 22:12:26 time: 0.2649 data_time: 0.0076 memory: 5828 grad_norm: 3.0140 loss: 2.7335 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7335 2023/06/04 22:46:24 - mmengine - INFO - Epoch(train) [34][1460/2569] lr: 4.0000e-02 eta: 22:12:20 time: 0.2643 data_time: 0.0083 memory: 5828 grad_norm: 3.0132 loss: 2.5996 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5996 2023/06/04 22:46:30 - mmengine - INFO - Epoch(train) [34][1480/2569] lr: 4.0000e-02 eta: 22:12:15 time: 0.2697 data_time: 0.0085 memory: 5828 grad_norm: 3.0680 loss: 2.5113 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5113 2023/06/04 22:46:35 - mmengine - INFO - Epoch(train) [34][1500/2569] lr: 4.0000e-02 eta: 22:12:10 time: 0.2685 data_time: 0.0080 memory: 5828 grad_norm: 3.0145 loss: 2.5552 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5552 2023/06/04 22:46:40 - mmengine - INFO - Epoch(train) [34][1520/2569] lr: 4.0000e-02 eta: 22:12:05 time: 0.2753 data_time: 0.0078 memory: 5828 grad_norm: 2.9804 loss: 2.5592 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5592 2023/06/04 22:46:46 - mmengine - INFO - Epoch(train) [34][1540/2569] lr: 4.0000e-02 eta: 22:11:59 time: 0.2629 data_time: 0.0079 memory: 5828 grad_norm: 3.0765 loss: 2.9839 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9839 2023/06/04 22:46:51 - mmengine - INFO - Epoch(train) [34][1560/2569] lr: 4.0000e-02 eta: 22:11:54 time: 0.2592 data_time: 0.0076 memory: 5828 grad_norm: 3.0444 loss: 2.7124 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7124 2023/06/04 22:46:56 - mmengine - INFO - Epoch(train) [34][1580/2569] lr: 4.0000e-02 eta: 22:11:48 time: 0.2635 data_time: 0.0081 memory: 5828 grad_norm: 3.0538 loss: 2.7379 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7379 2023/06/04 22:47:01 - mmengine - INFO - Epoch(train) [34][1600/2569] lr: 4.0000e-02 eta: 22:11:42 time: 0.2638 data_time: 0.0084 memory: 5828 grad_norm: 2.9959 loss: 2.7145 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7145 2023/06/04 22:47:07 - mmengine - INFO - Epoch(train) [34][1620/2569] lr: 4.0000e-02 eta: 22:11:37 time: 0.2702 data_time: 0.0080 memory: 5828 grad_norm: 3.0709 loss: 2.6245 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6245 2023/06/04 22:47:12 - mmengine - INFO - Epoch(train) [34][1640/2569] lr: 4.0000e-02 eta: 22:11:32 time: 0.2716 data_time: 0.0081 memory: 5828 grad_norm: 3.0706 loss: 2.6163 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6163 2023/06/04 22:47:18 - mmengine - INFO - Epoch(train) [34][1660/2569] lr: 4.0000e-02 eta: 22:11:27 time: 0.2693 data_time: 0.0079 memory: 5828 grad_norm: 2.9917 loss: 2.3224 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3224 2023/06/04 22:47:23 - mmengine - INFO - Epoch(train) [34][1680/2569] lr: 4.0000e-02 eta: 22:11:21 time: 0.2601 data_time: 0.0083 memory: 5828 grad_norm: 2.9779 loss: 2.6899 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6899 2023/06/04 22:47:28 - mmengine - INFO - Epoch(train) [34][1700/2569] lr: 4.0000e-02 eta: 22:11:15 time: 0.2627 data_time: 0.0079 memory: 5828 grad_norm: 3.0956 loss: 2.7652 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7652 2023/06/04 22:47:33 - mmengine - INFO - Epoch(train) [34][1720/2569] lr: 4.0000e-02 eta: 22:11:10 time: 0.2652 data_time: 0.0081 memory: 5828 grad_norm: 3.0282 loss: 2.6055 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6055 2023/06/04 22:47:39 - mmengine - INFO - Epoch(train) [34][1740/2569] lr: 4.0000e-02 eta: 22:11:05 time: 0.2669 data_time: 0.0077 memory: 5828 grad_norm: 3.0614 loss: 2.4411 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4411 2023/06/04 22:47:44 - mmengine - INFO - Epoch(train) [34][1760/2569] lr: 4.0000e-02 eta: 22:10:59 time: 0.2674 data_time: 0.0081 memory: 5828 grad_norm: 3.0671 loss: 2.7498 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7498 2023/06/04 22:47:50 - mmengine - INFO - Epoch(train) [34][1780/2569] lr: 4.0000e-02 eta: 22:10:54 time: 0.2734 data_time: 0.0078 memory: 5828 grad_norm: 3.0206 loss: 2.8576 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8576 2023/06/04 22:47:55 - mmengine - INFO - Epoch(train) [34][1800/2569] lr: 4.0000e-02 eta: 22:10:49 time: 0.2648 data_time: 0.0078 memory: 5828 grad_norm: 3.0154 loss: 2.7142 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7142 2023/06/04 22:48:00 - mmengine - INFO - Epoch(train) [34][1820/2569] lr: 4.0000e-02 eta: 22:10:44 time: 0.2700 data_time: 0.0077 memory: 5828 grad_norm: 3.0088 loss: 2.6975 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6975 2023/06/04 22:48:06 - mmengine - INFO - Epoch(train) [34][1840/2569] lr: 4.0000e-02 eta: 22:10:39 time: 0.2714 data_time: 0.0084 memory: 5828 grad_norm: 2.9659 loss: 2.6834 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6834 2023/06/04 22:48:11 - mmengine - INFO - Epoch(train) [34][1860/2569] lr: 4.0000e-02 eta: 22:10:33 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 3.0906 loss: 2.6692 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6692 2023/06/04 22:48:16 - mmengine - INFO - Epoch(train) [34][1880/2569] lr: 4.0000e-02 eta: 22:10:28 time: 0.2698 data_time: 0.0082 memory: 5828 grad_norm: 3.0140 loss: 2.4186 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4186 2023/06/04 22:48:22 - mmengine - INFO - Epoch(train) [34][1900/2569] lr: 4.0000e-02 eta: 22:10:22 time: 0.2626 data_time: 0.0082 memory: 5828 grad_norm: 2.9847 loss: 2.4766 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4766 2023/06/04 22:48:27 - mmengine - INFO - Epoch(train) [34][1920/2569] lr: 4.0000e-02 eta: 22:10:17 time: 0.2707 data_time: 0.0082 memory: 5828 grad_norm: 2.9871 loss: 2.6491 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6491 2023/06/04 22:48:32 - mmengine - INFO - Epoch(train) [34][1940/2569] lr: 4.0000e-02 eta: 22:10:11 time: 0.2627 data_time: 0.0078 memory: 5828 grad_norm: 3.0061 loss: 2.5892 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5892 2023/06/04 22:48:38 - mmengine - INFO - Epoch(train) [34][1960/2569] lr: 4.0000e-02 eta: 22:10:06 time: 0.2747 data_time: 0.0088 memory: 5828 grad_norm: 3.0667 loss: 2.4551 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4551 2023/06/04 22:48:43 - mmengine - INFO - Epoch(train) [34][1980/2569] lr: 4.0000e-02 eta: 22:10:00 time: 0.2594 data_time: 0.0077 memory: 5828 grad_norm: 2.9878 loss: 2.6017 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6017 2023/06/04 22:48:48 - mmengine - INFO - Epoch(train) [34][2000/2569] lr: 4.0000e-02 eta: 22:09:55 time: 0.2673 data_time: 0.0074 memory: 5828 grad_norm: 3.0541 loss: 2.8963 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8963 2023/06/04 22:48:54 - mmengine - INFO - Epoch(train) [34][2020/2569] lr: 4.0000e-02 eta: 22:09:50 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 2.9664 loss: 2.3945 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3945 2023/06/04 22:48:59 - mmengine - INFO - Epoch(train) [34][2040/2569] lr: 4.0000e-02 eta: 22:09:44 time: 0.2621 data_time: 0.0079 memory: 5828 grad_norm: 3.0680 loss: 2.3363 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3363 2023/06/04 22:49:04 - mmengine - INFO - Epoch(train) [34][2060/2569] lr: 4.0000e-02 eta: 22:09:38 time: 0.2596 data_time: 0.0080 memory: 5828 grad_norm: 3.0154 loss: 2.6007 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6007 2023/06/04 22:49:10 - mmengine - INFO - Epoch(train) [34][2080/2569] lr: 4.0000e-02 eta: 22:09:33 time: 0.2741 data_time: 0.0076 memory: 5828 grad_norm: 3.0966 loss: 2.7228 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7228 2023/06/04 22:49:15 - mmengine - INFO - Epoch(train) [34][2100/2569] lr: 4.0000e-02 eta: 22:09:28 time: 0.2644 data_time: 0.0077 memory: 5828 grad_norm: 3.0712 loss: 2.7755 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7755 2023/06/04 22:49:20 - mmengine - INFO - Epoch(train) [34][2120/2569] lr: 4.0000e-02 eta: 22:09:22 time: 0.2638 data_time: 0.0082 memory: 5828 grad_norm: 3.0623 loss: 2.7092 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7092 2023/06/04 22:49:26 - mmengine - INFO - Epoch(train) [34][2140/2569] lr: 4.0000e-02 eta: 22:09:17 time: 0.2665 data_time: 0.0077 memory: 5828 grad_norm: 3.0064 loss: 2.6998 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6998 2023/06/04 22:49:31 - mmengine - INFO - Epoch(train) [34][2160/2569] lr: 4.0000e-02 eta: 22:09:11 time: 0.2603 data_time: 0.0079 memory: 5828 grad_norm: 3.0408 loss: 2.4589 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4589 2023/06/04 22:49:36 - mmengine - INFO - Epoch(train) [34][2180/2569] lr: 4.0000e-02 eta: 22:09:05 time: 0.2614 data_time: 0.0080 memory: 5828 grad_norm: 3.0272 loss: 2.5851 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5851 2023/06/04 22:49:41 - mmengine - INFO - Epoch(train) [34][2200/2569] lr: 4.0000e-02 eta: 22:09:00 time: 0.2697 data_time: 0.0080 memory: 5828 grad_norm: 3.0389 loss: 2.5561 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5561 2023/06/04 22:49:47 - mmengine - INFO - Epoch(train) [34][2220/2569] lr: 4.0000e-02 eta: 22:08:54 time: 0.2597 data_time: 0.0080 memory: 5828 grad_norm: 3.0557 loss: 2.4898 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4898 2023/06/04 22:49:47 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:49:52 - mmengine - INFO - Epoch(train) [34][2240/2569] lr: 4.0000e-02 eta: 22:08:49 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 3.0002 loss: 2.7260 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7260 2023/06/04 22:49:57 - mmengine - INFO - Epoch(train) [34][2260/2569] lr: 4.0000e-02 eta: 22:08:43 time: 0.2606 data_time: 0.0082 memory: 5828 grad_norm: 2.9871 loss: 2.6982 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6982 2023/06/04 22:50:03 - mmengine - INFO - Epoch(train) [34][2280/2569] lr: 4.0000e-02 eta: 22:08:38 time: 0.2719 data_time: 0.0077 memory: 5828 grad_norm: 3.0231 loss: 2.4417 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4417 2023/06/04 22:50:08 - mmengine - INFO - Epoch(train) [34][2300/2569] lr: 4.0000e-02 eta: 22:08:33 time: 0.2711 data_time: 0.0079 memory: 5828 grad_norm: 3.0463 loss: 2.5999 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5999 2023/06/04 22:50:13 - mmengine - INFO - Epoch(train) [34][2320/2569] lr: 4.0000e-02 eta: 22:08:27 time: 0.2662 data_time: 0.0081 memory: 5828 grad_norm: 3.0529 loss: 2.7748 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7748 2023/06/04 22:50:19 - mmengine - INFO - Epoch(train) [34][2340/2569] lr: 4.0000e-02 eta: 22:08:22 time: 0.2705 data_time: 0.0080 memory: 5828 grad_norm: 3.0328 loss: 2.7225 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7225 2023/06/04 22:50:24 - mmengine - INFO - Epoch(train) [34][2360/2569] lr: 4.0000e-02 eta: 22:08:16 time: 0.2603 data_time: 0.0082 memory: 5828 grad_norm: 2.9510 loss: 2.7748 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7748 2023/06/04 22:50:29 - mmengine - INFO - Epoch(train) [34][2380/2569] lr: 4.0000e-02 eta: 22:08:11 time: 0.2600 data_time: 0.0080 memory: 5828 grad_norm: 3.1025 loss: 2.4134 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4134 2023/06/04 22:50:34 - mmengine - INFO - Epoch(train) [34][2400/2569] lr: 4.0000e-02 eta: 22:08:05 time: 0.2648 data_time: 0.0084 memory: 5828 grad_norm: 3.0233 loss: 2.6887 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6887 2023/06/04 22:50:40 - mmengine - INFO - Epoch(train) [34][2420/2569] lr: 4.0000e-02 eta: 22:08:00 time: 0.2717 data_time: 0.0081 memory: 5828 grad_norm: 3.0057 loss: 2.5118 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5118 2023/06/04 22:50:45 - mmengine - INFO - Epoch(train) [34][2440/2569] lr: 4.0000e-02 eta: 22:07:55 time: 0.2653 data_time: 0.0079 memory: 5828 grad_norm: 3.0527 loss: 2.7322 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7322 2023/06/04 22:50:50 - mmengine - INFO - Epoch(train) [34][2460/2569] lr: 4.0000e-02 eta: 22:07:49 time: 0.2648 data_time: 0.0079 memory: 5828 grad_norm: 3.0176 loss: 2.4349 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4349 2023/06/04 22:50:56 - mmengine - INFO - Epoch(train) [34][2480/2569] lr: 4.0000e-02 eta: 22:07:44 time: 0.2714 data_time: 0.0078 memory: 5828 grad_norm: 3.0783 loss: 2.4062 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4062 2023/06/04 22:51:01 - mmengine - INFO - Epoch(train) [34][2500/2569] lr: 4.0000e-02 eta: 22:07:39 time: 0.2680 data_time: 0.0079 memory: 5828 grad_norm: 3.0154 loss: 2.5556 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5556 2023/06/04 22:51:07 - mmengine - INFO - Epoch(train) [34][2520/2569] lr: 4.0000e-02 eta: 22:07:33 time: 0.2639 data_time: 0.0079 memory: 5828 grad_norm: 2.9850 loss: 2.5688 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5688 2023/06/04 22:51:12 - mmengine - INFO - Epoch(train) [34][2540/2569] lr: 4.0000e-02 eta: 22:07:27 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 3.0420 loss: 2.7174 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7174 2023/06/04 22:51:17 - mmengine - INFO - Epoch(train) [34][2560/2569] lr: 4.0000e-02 eta: 22:07:21 time: 0.2575 data_time: 0.0082 memory: 5828 grad_norm: 2.9880 loss: 2.7205 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7205 2023/06/04 22:51:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:51:19 - mmengine - INFO - Epoch(train) [34][2569/2569] lr: 4.0000e-02 eta: 22:07:18 time: 0.2517 data_time: 0.0078 memory: 5828 grad_norm: 3.0186 loss: 2.9096 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.9096 2023/06/04 22:51:26 - mmengine - INFO - Epoch(train) [35][ 20/2569] lr: 4.0000e-02 eta: 22:07:18 time: 0.3418 data_time: 0.0526 memory: 5828 grad_norm: 3.0363 loss: 2.6975 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6975 2023/06/04 22:51:31 - mmengine - INFO - Epoch(train) [35][ 40/2569] lr: 4.0000e-02 eta: 22:07:13 time: 0.2675 data_time: 0.0081 memory: 5828 grad_norm: 3.0008 loss: 2.4804 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4804 2023/06/04 22:51:37 - mmengine - INFO - Epoch(train) [35][ 60/2569] lr: 4.0000e-02 eta: 22:07:08 time: 0.2707 data_time: 0.0073 memory: 5828 grad_norm: 3.0588 loss: 2.4397 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4397 2023/06/04 22:51:42 - mmengine - INFO - Epoch(train) [35][ 80/2569] lr: 4.0000e-02 eta: 22:07:02 time: 0.2673 data_time: 0.0080 memory: 5828 grad_norm: 3.0355 loss: 2.6225 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6225 2023/06/04 22:51:47 - mmengine - INFO - Epoch(train) [35][ 100/2569] lr: 4.0000e-02 eta: 22:06:57 time: 0.2630 data_time: 0.0077 memory: 5828 grad_norm: 3.0865 loss: 2.7570 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7570 2023/06/04 22:51:53 - mmengine - INFO - Epoch(train) [35][ 120/2569] lr: 4.0000e-02 eta: 22:06:52 time: 0.2799 data_time: 0.0084 memory: 5828 grad_norm: 3.0985 loss: 2.4954 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4954 2023/06/04 22:51:58 - mmengine - INFO - Epoch(train) [35][ 140/2569] lr: 4.0000e-02 eta: 22:06:46 time: 0.2577 data_time: 0.0080 memory: 5828 grad_norm: 3.0953 loss: 2.6774 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6774 2023/06/04 22:52:03 - mmengine - INFO - Epoch(train) [35][ 160/2569] lr: 4.0000e-02 eta: 22:06:41 time: 0.2689 data_time: 0.0079 memory: 5828 grad_norm: 3.0402 loss: 2.7210 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7210 2023/06/04 22:52:09 - mmengine - INFO - Epoch(train) [35][ 180/2569] lr: 4.0000e-02 eta: 22:06:36 time: 0.2728 data_time: 0.0077 memory: 5828 grad_norm: 3.0484 loss: 2.5183 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5183 2023/06/04 22:52:14 - mmengine - INFO - Epoch(train) [35][ 200/2569] lr: 4.0000e-02 eta: 22:06:30 time: 0.2606 data_time: 0.0089 memory: 5828 grad_norm: 3.0098 loss: 2.5165 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5165 2023/06/04 22:52:20 - mmengine - INFO - Epoch(train) [35][ 220/2569] lr: 4.0000e-02 eta: 22:06:25 time: 0.2719 data_time: 0.0075 memory: 5828 grad_norm: 3.0609 loss: 2.7031 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7031 2023/06/04 22:52:25 - mmengine - INFO - Epoch(train) [35][ 240/2569] lr: 4.0000e-02 eta: 22:06:19 time: 0.2594 data_time: 0.0077 memory: 5828 grad_norm: 3.0181 loss: 2.5054 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5054 2023/06/04 22:52:30 - mmengine - INFO - Epoch(train) [35][ 260/2569] lr: 4.0000e-02 eta: 22:06:14 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 3.0505 loss: 2.0439 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0439 2023/06/04 22:52:35 - mmengine - INFO - Epoch(train) [35][ 280/2569] lr: 4.0000e-02 eta: 22:06:08 time: 0.2591 data_time: 0.0080 memory: 5828 grad_norm: 3.0577 loss: 2.6341 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6341 2023/06/04 22:52:41 - mmengine - INFO - Epoch(train) [35][ 300/2569] lr: 4.0000e-02 eta: 22:06:02 time: 0.2640 data_time: 0.0080 memory: 5828 grad_norm: 3.0029 loss: 2.4232 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4232 2023/06/04 22:52:46 - mmengine - INFO - Epoch(train) [35][ 320/2569] lr: 4.0000e-02 eta: 22:05:57 time: 0.2643 data_time: 0.0091 memory: 5828 grad_norm: 3.0062 loss: 3.1052 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.1052 2023/06/04 22:52:51 - mmengine - INFO - Epoch(train) [35][ 340/2569] lr: 4.0000e-02 eta: 22:05:52 time: 0.2695 data_time: 0.0081 memory: 5828 grad_norm: 3.0436 loss: 2.5866 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5866 2023/06/04 22:52:56 - mmengine - INFO - Epoch(train) [35][ 360/2569] lr: 4.0000e-02 eta: 22:05:46 time: 0.2596 data_time: 0.0081 memory: 5828 grad_norm: 3.0697 loss: 2.5516 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5516 2023/06/04 22:53:02 - mmengine - INFO - Epoch(train) [35][ 380/2569] lr: 4.0000e-02 eta: 22:05:40 time: 0.2590 data_time: 0.0078 memory: 5828 grad_norm: 3.0210 loss: 2.9821 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9821 2023/06/04 22:53:07 - mmengine - INFO - Epoch(train) [35][ 400/2569] lr: 4.0000e-02 eta: 22:05:35 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 3.0304 loss: 2.9367 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9367 2023/06/04 22:53:12 - mmengine - INFO - Epoch(train) [35][ 420/2569] lr: 4.0000e-02 eta: 22:05:29 time: 0.2709 data_time: 0.0078 memory: 5828 grad_norm: 3.0445 loss: 2.6067 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6067 2023/06/04 22:53:18 - mmengine - INFO - Epoch(train) [35][ 440/2569] lr: 4.0000e-02 eta: 22:05:24 time: 0.2581 data_time: 0.0078 memory: 5828 grad_norm: 3.0066 loss: 2.7288 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7288 2023/06/04 22:53:23 - mmengine - INFO - Epoch(train) [35][ 460/2569] lr: 4.0000e-02 eta: 22:05:18 time: 0.2603 data_time: 0.0078 memory: 5828 grad_norm: 3.0279 loss: 2.4575 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4575 2023/06/04 22:53:28 - mmengine - INFO - Epoch(train) [35][ 480/2569] lr: 4.0000e-02 eta: 22:05:12 time: 0.2613 data_time: 0.0080 memory: 5828 grad_norm: 3.0466 loss: 2.7914 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7914 2023/06/04 22:53:33 - mmengine - INFO - Epoch(train) [35][ 500/2569] lr: 4.0000e-02 eta: 22:05:06 time: 0.2601 data_time: 0.0076 memory: 5828 grad_norm: 3.0120 loss: 2.6385 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6385 2023/06/04 22:53:39 - mmengine - INFO - Epoch(train) [35][ 520/2569] lr: 4.0000e-02 eta: 22:05:01 time: 0.2637 data_time: 0.0082 memory: 5828 grad_norm: 2.9739 loss: 2.6190 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6190 2023/06/04 22:53:44 - mmengine - INFO - Epoch(train) [35][ 540/2569] lr: 4.0000e-02 eta: 22:04:55 time: 0.2643 data_time: 0.0075 memory: 5828 grad_norm: 3.0143 loss: 2.4446 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4446 2023/06/04 22:53:49 - mmengine - INFO - Epoch(train) [35][ 560/2569] lr: 4.0000e-02 eta: 22:04:49 time: 0.2585 data_time: 0.0084 memory: 5828 grad_norm: 3.0292 loss: 2.9069 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.9069 2023/06/04 22:53:54 - mmengine - INFO - Epoch(train) [35][ 580/2569] lr: 4.0000e-02 eta: 22:04:44 time: 0.2686 data_time: 0.0080 memory: 5828 grad_norm: 3.1108 loss: 2.6289 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6289 2023/06/04 22:54:00 - mmengine - INFO - Epoch(train) [35][ 600/2569] lr: 4.0000e-02 eta: 22:04:38 time: 0.2656 data_time: 0.0075 memory: 5828 grad_norm: 3.0654 loss: 2.5060 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5060 2023/06/04 22:54:05 - mmengine - INFO - Epoch(train) [35][ 620/2569] lr: 4.0000e-02 eta: 22:04:32 time: 0.2593 data_time: 0.0080 memory: 5828 grad_norm: 2.9779 loss: 3.0010 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0010 2023/06/04 22:54:10 - mmengine - INFO - Epoch(train) [35][ 640/2569] lr: 4.0000e-02 eta: 22:04:27 time: 0.2642 data_time: 0.0079 memory: 5828 grad_norm: 3.0557 loss: 2.7200 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7200 2023/06/04 22:54:14 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:54:15 - mmengine - INFO - Epoch(train) [35][ 660/2569] lr: 4.0000e-02 eta: 22:04:21 time: 0.2609 data_time: 0.0078 memory: 5828 grad_norm: 3.0266 loss: 2.5890 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5890 2023/06/04 22:54:21 - mmengine - INFO - Epoch(train) [35][ 680/2569] lr: 4.0000e-02 eta: 22:04:16 time: 0.2651 data_time: 0.0078 memory: 5828 grad_norm: 3.0894 loss: 2.8571 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8571 2023/06/04 22:54:26 - mmengine - INFO - Epoch(train) [35][ 700/2569] lr: 4.0000e-02 eta: 22:04:10 time: 0.2600 data_time: 0.0079 memory: 5828 grad_norm: 3.0373 loss: 2.7266 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7266 2023/06/04 22:54:31 - mmengine - INFO - Epoch(train) [35][ 720/2569] lr: 4.0000e-02 eta: 22:04:04 time: 0.2654 data_time: 0.0084 memory: 5828 grad_norm: 3.0463 loss: 2.5267 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5267 2023/06/04 22:54:37 - mmengine - INFO - Epoch(train) [35][ 740/2569] lr: 4.0000e-02 eta: 22:03:59 time: 0.2725 data_time: 0.0076 memory: 5828 grad_norm: 2.9737 loss: 2.4584 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4584 2023/06/04 22:54:42 - mmengine - INFO - Epoch(train) [35][ 760/2569] lr: 4.0000e-02 eta: 22:03:54 time: 0.2602 data_time: 0.0080 memory: 5828 grad_norm: 2.9775 loss: 2.9091 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9091 2023/06/04 22:54:48 - mmengine - INFO - Epoch(train) [35][ 780/2569] lr: 4.0000e-02 eta: 22:03:49 time: 0.2839 data_time: 0.0075 memory: 5828 grad_norm: 2.9979 loss: 3.0189 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0189 2023/06/04 22:54:53 - mmengine - INFO - Epoch(train) [35][ 800/2569] lr: 4.0000e-02 eta: 22:03:44 time: 0.2621 data_time: 0.0082 memory: 5828 grad_norm: 3.0782 loss: 2.1967 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1967 2023/06/04 22:54:58 - mmengine - INFO - Epoch(train) [35][ 820/2569] lr: 4.0000e-02 eta: 22:03:38 time: 0.2670 data_time: 0.0076 memory: 5828 grad_norm: 2.9863 loss: 2.5112 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5112 2023/06/04 22:55:03 - mmengine - INFO - Epoch(train) [35][ 840/2569] lr: 4.0000e-02 eta: 22:03:33 time: 0.2650 data_time: 0.0079 memory: 5828 grad_norm: 3.0779 loss: 2.5923 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5923 2023/06/04 22:55:09 - mmengine - INFO - Epoch(train) [35][ 860/2569] lr: 4.0000e-02 eta: 22:03:27 time: 0.2595 data_time: 0.0075 memory: 5828 grad_norm: 3.0405 loss: 2.1087 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1087 2023/06/04 22:55:14 - mmengine - INFO - Epoch(train) [35][ 880/2569] lr: 4.0000e-02 eta: 22:03:22 time: 0.2708 data_time: 0.0078 memory: 5828 grad_norm: 3.0039 loss: 2.0790 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.0790 2023/06/04 22:55:19 - mmengine - INFO - Epoch(train) [35][ 900/2569] lr: 4.0000e-02 eta: 22:03:16 time: 0.2591 data_time: 0.0081 memory: 5828 grad_norm: 3.0524 loss: 2.7116 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7116 2023/06/04 22:55:25 - mmengine - INFO - Epoch(train) [35][ 920/2569] lr: 4.0000e-02 eta: 22:03:10 time: 0.2661 data_time: 0.0078 memory: 5828 grad_norm: 3.0023 loss: 2.5300 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5300 2023/06/04 22:55:30 - mmengine - INFO - Epoch(train) [35][ 940/2569] lr: 4.0000e-02 eta: 22:03:05 time: 0.2622 data_time: 0.0077 memory: 5828 grad_norm: 3.0767 loss: 2.7033 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7033 2023/06/04 22:55:35 - mmengine - INFO - Epoch(train) [35][ 960/2569] lr: 4.0000e-02 eta: 22:02:59 time: 0.2650 data_time: 0.0080 memory: 5828 grad_norm: 2.9316 loss: 2.5857 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5857 2023/06/04 22:55:40 - mmengine - INFO - Epoch(train) [35][ 980/2569] lr: 4.0000e-02 eta: 22:02:54 time: 0.2622 data_time: 0.0079 memory: 5828 grad_norm: 3.0619 loss: 2.6512 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6512 2023/06/04 22:55:46 - mmengine - INFO - Epoch(train) [35][1000/2569] lr: 4.0000e-02 eta: 22:02:48 time: 0.2639 data_time: 0.0080 memory: 5828 grad_norm: 3.0813 loss: 2.5695 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5695 2023/06/04 22:55:51 - mmengine - INFO - Epoch(train) [35][1020/2569] lr: 4.0000e-02 eta: 22:02:42 time: 0.2601 data_time: 0.0076 memory: 5828 grad_norm: 3.0391 loss: 2.6840 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6840 2023/06/04 22:55:56 - mmengine - INFO - Epoch(train) [35][1040/2569] lr: 4.0000e-02 eta: 22:02:37 time: 0.2645 data_time: 0.0080 memory: 5828 grad_norm: 3.0482 loss: 2.4790 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4790 2023/06/04 22:56:02 - mmengine - INFO - Epoch(train) [35][1060/2569] lr: 4.0000e-02 eta: 22:02:32 time: 0.2724 data_time: 0.0081 memory: 5828 grad_norm: 3.1079 loss: 2.6983 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6983 2023/06/04 22:56:07 - mmengine - INFO - Epoch(train) [35][1080/2569] lr: 4.0000e-02 eta: 22:02:26 time: 0.2587 data_time: 0.0081 memory: 5828 grad_norm: 3.0118 loss: 2.4146 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4146 2023/06/04 22:56:12 - mmengine - INFO - Epoch(train) [35][1100/2569] lr: 4.0000e-02 eta: 22:02:20 time: 0.2622 data_time: 0.0079 memory: 5828 grad_norm: 3.0112 loss: 2.4839 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4839 2023/06/04 22:56:17 - mmengine - INFO - Epoch(train) [35][1120/2569] lr: 4.0000e-02 eta: 22:02:14 time: 0.2595 data_time: 0.0080 memory: 5828 grad_norm: 3.1078 loss: 2.5282 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5282 2023/06/04 22:56:22 - mmengine - INFO - Epoch(train) [35][1140/2569] lr: 4.0000e-02 eta: 22:02:09 time: 0.2614 data_time: 0.0081 memory: 5828 grad_norm: 3.0830 loss: 2.6372 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6372 2023/06/04 22:56:28 - mmengine - INFO - Epoch(train) [35][1160/2569] lr: 4.0000e-02 eta: 22:02:03 time: 0.2698 data_time: 0.0074 memory: 5828 grad_norm: 3.0430 loss: 2.5976 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5976 2023/06/04 22:56:33 - mmengine - INFO - Epoch(train) [35][1180/2569] lr: 4.0000e-02 eta: 22:01:58 time: 0.2701 data_time: 0.0077 memory: 5828 grad_norm: 3.0329 loss: 2.5802 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5802 2023/06/04 22:56:39 - mmengine - INFO - Epoch(train) [35][1200/2569] lr: 4.0000e-02 eta: 22:01:53 time: 0.2725 data_time: 0.0082 memory: 5828 grad_norm: 3.0013 loss: 3.0182 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.0182 2023/06/04 22:56:44 - mmengine - INFO - Epoch(train) [35][1220/2569] lr: 4.0000e-02 eta: 22:01:48 time: 0.2650 data_time: 0.0081 memory: 5828 grad_norm: 2.9962 loss: 2.2963 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2963 2023/06/04 22:56:49 - mmengine - INFO - Epoch(train) [35][1240/2569] lr: 4.0000e-02 eta: 22:01:42 time: 0.2680 data_time: 0.0078 memory: 5828 grad_norm: 3.0071 loss: 2.2787 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2787 2023/06/04 22:56:55 - mmengine - INFO - Epoch(train) [35][1260/2569] lr: 4.0000e-02 eta: 22:01:37 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 3.0081 loss: 2.7583 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7583 2023/06/04 22:57:00 - mmengine - INFO - Epoch(train) [35][1280/2569] lr: 4.0000e-02 eta: 22:01:32 time: 0.2697 data_time: 0.0076 memory: 5828 grad_norm: 3.0493 loss: 2.2316 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.2316 2023/06/04 22:57:05 - mmengine - INFO - Epoch(train) [35][1300/2569] lr: 4.0000e-02 eta: 22:01:26 time: 0.2573 data_time: 0.0071 memory: 5828 grad_norm: 3.0037 loss: 2.4706 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4706 2023/06/04 22:57:11 - mmengine - INFO - Epoch(train) [35][1320/2569] lr: 4.0000e-02 eta: 22:01:21 time: 0.2745 data_time: 0.0078 memory: 5828 grad_norm: 3.0606 loss: 2.4266 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4266 2023/06/04 22:57:16 - mmengine - INFO - Epoch(train) [35][1340/2569] lr: 4.0000e-02 eta: 22:01:15 time: 0.2658 data_time: 0.0078 memory: 5828 grad_norm: 3.0484 loss: 2.3385 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3385 2023/06/04 22:57:21 - mmengine - INFO - Epoch(train) [35][1360/2569] lr: 4.0000e-02 eta: 22:01:10 time: 0.2697 data_time: 0.0083 memory: 5828 grad_norm: 3.0789 loss: 2.5626 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5626 2023/06/04 22:57:27 - mmengine - INFO - Epoch(train) [35][1380/2569] lr: 4.0000e-02 eta: 22:01:05 time: 0.2731 data_time: 0.0077 memory: 5828 grad_norm: 3.0312 loss: 2.8357 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8357 2023/06/04 22:57:33 - mmengine - INFO - Epoch(train) [35][1400/2569] lr: 4.0000e-02 eta: 22:01:01 time: 0.2789 data_time: 0.0080 memory: 5828 grad_norm: 3.0268 loss: 2.2501 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2501 2023/06/04 22:57:38 - mmengine - INFO - Epoch(train) [35][1420/2569] lr: 4.0000e-02 eta: 22:00:56 time: 0.2709 data_time: 0.0077 memory: 5828 grad_norm: 3.0553 loss: 2.9324 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9324 2023/06/04 22:57:43 - mmengine - INFO - Epoch(train) [35][1440/2569] lr: 4.0000e-02 eta: 22:00:50 time: 0.2663 data_time: 0.0081 memory: 5828 grad_norm: 3.0680 loss: 2.6634 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6634 2023/06/04 22:57:49 - mmengine - INFO - Epoch(train) [35][1460/2569] lr: 4.0000e-02 eta: 22:00:45 time: 0.2644 data_time: 0.0078 memory: 5828 grad_norm: 3.0349 loss: 2.7775 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7775 2023/06/04 22:57:54 - mmengine - INFO - Epoch(train) [35][1480/2569] lr: 4.0000e-02 eta: 22:00:39 time: 0.2657 data_time: 0.0078 memory: 5828 grad_norm: 3.0437 loss: 2.5586 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5586 2023/06/04 22:57:59 - mmengine - INFO - Epoch(train) [35][1500/2569] lr: 4.0000e-02 eta: 22:00:34 time: 0.2656 data_time: 0.0076 memory: 5828 grad_norm: 2.9863 loss: 2.4906 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4906 2023/06/04 22:58:05 - mmengine - INFO - Epoch(train) [35][1520/2569] lr: 4.0000e-02 eta: 22:00:29 time: 0.2691 data_time: 0.0077 memory: 5828 grad_norm: 2.9967 loss: 2.7685 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7685 2023/06/04 22:58:10 - mmengine - INFO - Epoch(train) [35][1540/2569] lr: 4.0000e-02 eta: 22:00:23 time: 0.2620 data_time: 0.0078 memory: 5828 grad_norm: 3.0399 loss: 2.5911 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5911 2023/06/04 22:58:15 - mmengine - INFO - Epoch(train) [35][1560/2569] lr: 4.0000e-02 eta: 22:00:17 time: 0.2655 data_time: 0.0083 memory: 5828 grad_norm: 3.0725 loss: 2.6500 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6500 2023/06/04 22:58:20 - mmengine - INFO - Epoch(train) [35][1580/2569] lr: 4.0000e-02 eta: 22:00:12 time: 0.2639 data_time: 0.0078 memory: 5828 grad_norm: 3.0430 loss: 2.5654 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5654 2023/06/04 22:58:26 - mmengine - INFO - Epoch(train) [35][1600/2569] lr: 4.0000e-02 eta: 22:00:07 time: 0.2677 data_time: 0.0079 memory: 5828 grad_norm: 3.0405 loss: 2.5243 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5243 2023/06/04 22:58:31 - mmengine - INFO - Epoch(train) [35][1620/2569] lr: 4.0000e-02 eta: 22:00:01 time: 0.2579 data_time: 0.0079 memory: 5828 grad_norm: 3.0687 loss: 2.6638 top1_acc: 0.1250 top5_acc: 1.0000 loss_cls: 2.6638 2023/06/04 22:58:36 - mmengine - INFO - Epoch(train) [35][1640/2569] lr: 4.0000e-02 eta: 21:59:56 time: 0.2721 data_time: 0.0079 memory: 5828 grad_norm: 2.9886 loss: 2.8156 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8156 2023/06/04 22:58:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 22:58:42 - mmengine - INFO - Epoch(train) [35][1660/2569] lr: 4.0000e-02 eta: 21:59:50 time: 0.2643 data_time: 0.0082 memory: 5828 grad_norm: 3.0398 loss: 2.8776 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8776 2023/06/04 22:58:47 - mmengine - INFO - Epoch(train) [35][1680/2569] lr: 4.0000e-02 eta: 21:59:45 time: 0.2684 data_time: 0.0079 memory: 5828 grad_norm: 3.0566 loss: 2.3222 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3222 2023/06/04 22:58:52 - mmengine - INFO - Epoch(train) [35][1700/2569] lr: 4.0000e-02 eta: 21:59:39 time: 0.2620 data_time: 0.0077 memory: 5828 grad_norm: 2.9851 loss: 2.5776 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5776 2023/06/04 22:58:57 - mmengine - INFO - Epoch(train) [35][1720/2569] lr: 4.0000e-02 eta: 21:59:33 time: 0.2604 data_time: 0.0078 memory: 5828 grad_norm: 3.0647 loss: 2.3715 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3715 2023/06/04 22:59:03 - mmengine - INFO - Epoch(train) [35][1740/2569] lr: 4.0000e-02 eta: 21:59:28 time: 0.2634 data_time: 0.0085 memory: 5828 grad_norm: 3.0470 loss: 2.6941 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6941 2023/06/04 22:59:08 - mmengine - INFO - Epoch(train) [35][1760/2569] lr: 4.0000e-02 eta: 21:59:22 time: 0.2645 data_time: 0.0081 memory: 5828 grad_norm: 3.0357 loss: 2.3007 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3007 2023/06/04 22:59:13 - mmengine - INFO - Epoch(train) [35][1780/2569] lr: 4.0000e-02 eta: 21:59:17 time: 0.2710 data_time: 0.0076 memory: 5828 grad_norm: 3.1049 loss: 2.5863 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5863 2023/06/04 22:59:19 - mmengine - INFO - Epoch(train) [35][1800/2569] lr: 4.0000e-02 eta: 21:59:13 time: 0.2797 data_time: 0.0083 memory: 5828 grad_norm: 3.0361 loss: 2.8486 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8486 2023/06/04 22:59:25 - mmengine - INFO - Epoch(train) [35][1820/2569] lr: 4.0000e-02 eta: 21:59:08 time: 0.2731 data_time: 0.0081 memory: 5828 grad_norm: 3.0281 loss: 2.9003 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9003 2023/06/04 22:59:30 - mmengine - INFO - Epoch(train) [35][1840/2569] lr: 4.0000e-02 eta: 21:59:03 time: 0.2737 data_time: 0.0090 memory: 5828 grad_norm: 3.0150 loss: 2.5015 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5015 2023/06/04 22:59:35 - mmengine - INFO - Epoch(train) [35][1860/2569] lr: 4.0000e-02 eta: 21:58:57 time: 0.2653 data_time: 0.0084 memory: 5828 grad_norm: 3.0829 loss: 2.8972 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8972 2023/06/04 22:59:41 - mmengine - INFO - Epoch(train) [35][1880/2569] lr: 4.0000e-02 eta: 21:58:51 time: 0.2618 data_time: 0.0081 memory: 5828 grad_norm: 3.0584 loss: 2.6309 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6309 2023/06/04 22:59:46 - mmengine - INFO - Epoch(train) [35][1900/2569] lr: 4.0000e-02 eta: 21:58:46 time: 0.2598 data_time: 0.0080 memory: 5828 grad_norm: 3.0917 loss: 2.7152 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7152 2023/06/04 22:59:51 - mmengine - INFO - Epoch(train) [35][1920/2569] lr: 4.0000e-02 eta: 21:58:40 time: 0.2597 data_time: 0.0082 memory: 5828 grad_norm: 3.0287 loss: 2.7267 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7267 2023/06/04 22:59:56 - mmengine - INFO - Epoch(train) [35][1940/2569] lr: 4.0000e-02 eta: 21:58:35 time: 0.2700 data_time: 0.0080 memory: 5828 grad_norm: 2.9793 loss: 2.7944 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7944 2023/06/04 23:00:02 - mmengine - INFO - Epoch(train) [35][1960/2569] lr: 4.0000e-02 eta: 21:58:29 time: 0.2657 data_time: 0.0081 memory: 5828 grad_norm: 3.0163 loss: 2.7655 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7655 2023/06/04 23:00:07 - mmengine - INFO - Epoch(train) [35][1980/2569] lr: 4.0000e-02 eta: 21:58:24 time: 0.2739 data_time: 0.0073 memory: 5828 grad_norm: 3.0721 loss: 2.6581 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6581 2023/06/04 23:00:12 - mmengine - INFO - Epoch(train) [35][2000/2569] lr: 4.0000e-02 eta: 21:58:18 time: 0.2599 data_time: 0.0077 memory: 5828 grad_norm: 3.0172 loss: 2.5304 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5304 2023/06/04 23:00:18 - mmengine - INFO - Epoch(train) [35][2020/2569] lr: 4.0000e-02 eta: 21:58:13 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 3.0616 loss: 2.6226 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6226 2023/06/04 23:00:23 - mmengine - INFO - Epoch(train) [35][2040/2569] lr: 4.0000e-02 eta: 21:58:07 time: 0.2683 data_time: 0.0076 memory: 5828 grad_norm: 3.0272 loss: 2.6484 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6484 2023/06/04 23:00:28 - mmengine - INFO - Epoch(train) [35][2060/2569] lr: 4.0000e-02 eta: 21:58:02 time: 0.2660 data_time: 0.0079 memory: 5828 grad_norm: 2.9841 loss: 2.5836 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5836 2023/06/04 23:00:34 - mmengine - INFO - Epoch(train) [35][2080/2569] lr: 4.0000e-02 eta: 21:57:57 time: 0.2668 data_time: 0.0079 memory: 5828 grad_norm: 3.0407 loss: 2.4144 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4144 2023/06/04 23:00:39 - mmengine - INFO - Epoch(train) [35][2100/2569] lr: 4.0000e-02 eta: 21:57:51 time: 0.2665 data_time: 0.0078 memory: 5828 grad_norm: 3.0681 loss: 2.6335 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.6335 2023/06/04 23:00:44 - mmengine - INFO - Epoch(train) [35][2120/2569] lr: 4.0000e-02 eta: 21:57:46 time: 0.2672 data_time: 0.0080 memory: 5828 grad_norm: 2.9864 loss: 2.6151 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6151 2023/06/04 23:00:50 - mmengine - INFO - Epoch(train) [35][2140/2569] lr: 4.0000e-02 eta: 21:57:40 time: 0.2660 data_time: 0.0083 memory: 5828 grad_norm: 3.0155 loss: 2.6781 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6781 2023/06/04 23:00:55 - mmengine - INFO - Epoch(train) [35][2160/2569] lr: 4.0000e-02 eta: 21:57:35 time: 0.2700 data_time: 0.0076 memory: 5828 grad_norm: 3.0478 loss: 2.4837 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4837 2023/06/04 23:01:00 - mmengine - INFO - Epoch(train) [35][2180/2569] lr: 4.0000e-02 eta: 21:57:30 time: 0.2634 data_time: 0.0077 memory: 5828 grad_norm: 3.0758 loss: 2.6408 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6408 2023/06/04 23:01:05 - mmengine - INFO - Epoch(train) [35][2200/2569] lr: 4.0000e-02 eta: 21:57:24 time: 0.2604 data_time: 0.0084 memory: 5828 grad_norm: 3.0463 loss: 2.6528 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6528 2023/06/04 23:01:11 - mmengine - INFO - Epoch(train) [35][2220/2569] lr: 4.0000e-02 eta: 21:57:19 time: 0.2734 data_time: 0.0076 memory: 5828 grad_norm: 2.9953 loss: 2.8168 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8168 2023/06/04 23:01:16 - mmengine - INFO - Epoch(train) [35][2240/2569] lr: 4.0000e-02 eta: 21:57:13 time: 0.2608 data_time: 0.0081 memory: 5828 grad_norm: 2.9759 loss: 2.5833 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5833 2023/06/04 23:01:22 - mmengine - INFO - Epoch(train) [35][2260/2569] lr: 4.0000e-02 eta: 21:57:08 time: 0.2664 data_time: 0.0080 memory: 5828 grad_norm: 3.0797 loss: 2.7108 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7108 2023/06/04 23:01:27 - mmengine - INFO - Epoch(train) [35][2280/2569] lr: 4.0000e-02 eta: 21:57:02 time: 0.2607 data_time: 0.0081 memory: 5828 grad_norm: 3.0567 loss: 2.3958 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3958 2023/06/04 23:01:32 - mmengine - INFO - Epoch(train) [35][2300/2569] lr: 4.0000e-02 eta: 21:56:56 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 3.0541 loss: 2.7940 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7940 2023/06/04 23:01:37 - mmengine - INFO - Epoch(train) [35][2320/2569] lr: 4.0000e-02 eta: 21:56:51 time: 0.2583 data_time: 0.0080 memory: 5828 grad_norm: 3.0086 loss: 2.2637 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2637 2023/06/04 23:01:43 - mmengine - INFO - Epoch(train) [35][2340/2569] lr: 4.0000e-02 eta: 21:56:46 time: 0.2740 data_time: 0.0076 memory: 5828 grad_norm: 3.0782 loss: 2.5688 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5688 2023/06/04 23:01:48 - mmengine - INFO - Epoch(train) [35][2360/2569] lr: 4.0000e-02 eta: 21:56:40 time: 0.2601 data_time: 0.0083 memory: 5828 grad_norm: 3.0260 loss: 2.6273 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6273 2023/06/04 23:01:53 - mmengine - INFO - Epoch(train) [35][2380/2569] lr: 4.0000e-02 eta: 21:56:34 time: 0.2671 data_time: 0.0079 memory: 5828 grad_norm: 3.0513 loss: 2.5044 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5044 2023/06/04 23:01:59 - mmengine - INFO - Epoch(train) [35][2400/2569] lr: 4.0000e-02 eta: 21:56:29 time: 0.2660 data_time: 0.0080 memory: 5828 grad_norm: 3.0415 loss: 2.6949 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6949 2023/06/04 23:02:04 - mmengine - INFO - Epoch(train) [35][2420/2569] lr: 4.0000e-02 eta: 21:56:24 time: 0.2696 data_time: 0.0078 memory: 5828 grad_norm: 3.0206 loss: 2.6950 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6950 2023/06/04 23:02:09 - mmengine - INFO - Epoch(train) [35][2440/2569] lr: 4.0000e-02 eta: 21:56:18 time: 0.2583 data_time: 0.0078 memory: 5828 grad_norm: 3.0332 loss: 2.5589 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5589 2023/06/04 23:02:15 - mmengine - INFO - Epoch(train) [35][2460/2569] lr: 4.0000e-02 eta: 21:56:13 time: 0.2681 data_time: 0.0076 memory: 5828 grad_norm: 3.0784 loss: 2.3977 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3977 2023/06/04 23:02:20 - mmengine - INFO - Epoch(train) [35][2480/2569] lr: 4.0000e-02 eta: 21:56:07 time: 0.2636 data_time: 0.0082 memory: 5828 grad_norm: 3.0587 loss: 2.4681 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4681 2023/06/04 23:02:25 - mmengine - INFO - Epoch(train) [35][2500/2569] lr: 4.0000e-02 eta: 21:56:02 time: 0.2727 data_time: 0.0083 memory: 5828 grad_norm: 3.0361 loss: 2.5818 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5818 2023/06/04 23:02:31 - mmengine - INFO - Epoch(train) [35][2520/2569] lr: 4.0000e-02 eta: 21:55:56 time: 0.2631 data_time: 0.0079 memory: 5828 grad_norm: 3.0424 loss: 2.5596 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5596 2023/06/04 23:02:36 - mmengine - INFO - Epoch(train) [35][2540/2569] lr: 4.0000e-02 eta: 21:55:51 time: 0.2695 data_time: 0.0083 memory: 5828 grad_norm: 3.0385 loss: 2.9914 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9914 2023/06/04 23:02:41 - mmengine - INFO - Epoch(train) [35][2560/2569] lr: 4.0000e-02 eta: 21:55:45 time: 0.2584 data_time: 0.0078 memory: 5828 grad_norm: 3.0260 loss: 2.5776 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5776 2023/06/04 23:02:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:02:44 - mmengine - INFO - Epoch(train) [35][2569/2569] lr: 4.0000e-02 eta: 21:55:43 time: 0.2639 data_time: 0.0077 memory: 5828 grad_norm: 3.0342 loss: 2.4480 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.4480 2023/06/04 23:02:47 - mmengine - INFO - Epoch(val) [35][ 20/260] eta: 0:00:44 time: 0.1859 data_time: 0.1268 memory: 1238 2023/06/04 23:02:50 - mmengine - INFO - Epoch(val) [35][ 40/260] eta: 0:00:35 time: 0.1377 data_time: 0.0791 memory: 1238 2023/06/04 23:02:53 - mmengine - INFO - Epoch(val) [35][ 60/260] eta: 0:00:31 time: 0.1441 data_time: 0.0851 memory: 1238 2023/06/04 23:02:55 - mmengine - INFO - Epoch(val) [35][ 80/260] eta: 0:00:26 time: 0.1222 data_time: 0.0634 memory: 1238 2023/06/04 23:02:59 - mmengine - INFO - Epoch(val) [35][100/260] eta: 0:00:24 time: 0.1628 data_time: 0.1043 memory: 1238 2023/06/04 23:03:01 - mmengine - INFO - Epoch(val) [35][120/260] eta: 0:00:20 time: 0.1161 data_time: 0.0576 memory: 1238 2023/06/04 23:03:04 - mmengine - INFO - Epoch(val) [35][140/260] eta: 0:00:17 time: 0.1539 data_time: 0.0952 memory: 1238 2023/06/04 23:03:06 - mmengine - INFO - Epoch(val) [35][160/260] eta: 0:00:14 time: 0.1165 data_time: 0.0578 memory: 1238 2023/06/04 23:03:09 - mmengine - INFO - Epoch(val) [35][180/260] eta: 0:00:11 time: 0.1538 data_time: 0.0954 memory: 1238 2023/06/04 23:03:12 - mmengine - INFO - Epoch(val) [35][200/260] eta: 0:00:08 time: 0.1345 data_time: 0.0763 memory: 1238 2023/06/04 23:03:15 - mmengine - INFO - Epoch(val) [35][220/260] eta: 0:00:05 time: 0.1547 data_time: 0.0963 memory: 1238 2023/06/04 23:03:18 - mmengine - INFO - Epoch(val) [35][240/260] eta: 0:00:02 time: 0.1353 data_time: 0.0770 memory: 1238 2023/06/04 23:03:21 - mmengine - INFO - Epoch(val) [35][260/260] eta: 0:00:00 time: 0.1390 data_time: 0.0819 memory: 1238 2023/06/04 23:03:30 - mmengine - INFO - Epoch(val) [35][260/260] acc/top1: 0.4953 acc/top5: 0.7397 acc/mean1: 0.4875 data_time: 0.0840 time: 0.1424 2023/06/04 23:03:30 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_25.pth is removed 2023/06/04 23:03:31 - mmengine - INFO - The best checkpoint with 0.4953 acc/top1 at 35 epoch is saved to best_acc_top1_epoch_35.pth. 2023/06/04 23:03:37 - mmengine - INFO - Epoch(train) [36][ 20/2569] lr: 4.0000e-02 eta: 21:55:40 time: 0.2974 data_time: 0.0477 memory: 5828 grad_norm: 3.0076 loss: 2.5778 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5778 2023/06/04 23:03:42 - mmengine - INFO - Epoch(train) [36][ 40/2569] lr: 4.0000e-02 eta: 21:55:34 time: 0.2595 data_time: 0.0077 memory: 5828 grad_norm: 3.0163 loss: 2.6607 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6607 2023/06/04 23:03:48 - mmengine - INFO - Epoch(train) [36][ 60/2569] lr: 4.0000e-02 eta: 21:55:29 time: 0.2730 data_time: 0.0071 memory: 5828 grad_norm: 3.0488 loss: 2.7320 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7320 2023/06/04 23:03:53 - mmengine - INFO - Epoch(train) [36][ 80/2569] lr: 4.0000e-02 eta: 21:55:23 time: 0.2647 data_time: 0.0075 memory: 5828 grad_norm: 2.9987 loss: 2.4453 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4453 2023/06/04 23:03:54 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:03:58 - mmengine - INFO - Epoch(train) [36][ 100/2569] lr: 4.0000e-02 eta: 21:55:17 time: 0.2593 data_time: 0.0076 memory: 5828 grad_norm: 3.0487 loss: 2.5445 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5445 2023/06/04 23:04:04 - mmengine - INFO - Epoch(train) [36][ 120/2569] lr: 4.0000e-02 eta: 21:55:12 time: 0.2596 data_time: 0.0080 memory: 5828 grad_norm: 3.0405 loss: 2.6249 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6249 2023/06/04 23:04:09 - mmengine - INFO - Epoch(train) [36][ 140/2569] lr: 4.0000e-02 eta: 21:55:06 time: 0.2695 data_time: 0.0077 memory: 5828 grad_norm: 3.0439 loss: 2.4628 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4628 2023/06/04 23:04:14 - mmengine - INFO - Epoch(train) [36][ 160/2569] lr: 4.0000e-02 eta: 21:55:01 time: 0.2634 data_time: 0.0082 memory: 5828 grad_norm: 2.9901 loss: 2.4743 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4743 2023/06/04 23:04:19 - mmengine - INFO - Epoch(train) [36][ 180/2569] lr: 4.0000e-02 eta: 21:54:55 time: 0.2645 data_time: 0.0077 memory: 5828 grad_norm: 3.0623 loss: 2.7043 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7043 2023/06/04 23:04:25 - mmengine - INFO - Epoch(train) [36][ 200/2569] lr: 4.0000e-02 eta: 21:54:50 time: 0.2639 data_time: 0.0076 memory: 5828 grad_norm: 3.0590 loss: 2.3162 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3162 2023/06/04 23:04:30 - mmengine - INFO - Epoch(train) [36][ 220/2569] lr: 4.0000e-02 eta: 21:54:44 time: 0.2597 data_time: 0.0079 memory: 5828 grad_norm: 3.0515 loss: 2.4672 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4672 2023/06/04 23:04:35 - mmengine - INFO - Epoch(train) [36][ 240/2569] lr: 4.0000e-02 eta: 21:54:39 time: 0.2737 data_time: 0.0076 memory: 5828 grad_norm: 3.0857 loss: 2.2330 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2330 2023/06/04 23:04:41 - mmengine - INFO - Epoch(train) [36][ 260/2569] lr: 4.0000e-02 eta: 21:54:33 time: 0.2608 data_time: 0.0077 memory: 5828 grad_norm: 3.0968 loss: 2.4033 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4033 2023/06/04 23:04:46 - mmengine - INFO - Epoch(train) [36][ 280/2569] lr: 4.0000e-02 eta: 21:54:28 time: 0.2749 data_time: 0.0076 memory: 5828 grad_norm: 3.0508 loss: 3.1790 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1790 2023/06/04 23:04:51 - mmengine - INFO - Epoch(train) [36][ 300/2569] lr: 4.0000e-02 eta: 21:54:23 time: 0.2601 data_time: 0.0093 memory: 5828 grad_norm: 2.9961 loss: 2.3373 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3373 2023/06/04 23:04:57 - mmengine - INFO - Epoch(train) [36][ 320/2569] lr: 4.0000e-02 eta: 21:54:17 time: 0.2615 data_time: 0.0079 memory: 5828 grad_norm: 3.0501 loss: 2.6025 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6025 2023/06/04 23:05:02 - mmengine - INFO - Epoch(train) [36][ 340/2569] lr: 4.0000e-02 eta: 21:54:11 time: 0.2619 data_time: 0.0077 memory: 5828 grad_norm: 3.0235 loss: 2.5820 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5820 2023/06/04 23:05:07 - mmengine - INFO - Epoch(train) [36][ 360/2569] lr: 4.0000e-02 eta: 21:54:06 time: 0.2688 data_time: 0.0078 memory: 5828 grad_norm: 3.0782 loss: 2.5349 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5349 2023/06/04 23:05:12 - mmengine - INFO - Epoch(train) [36][ 380/2569] lr: 4.0000e-02 eta: 21:54:00 time: 0.2602 data_time: 0.0079 memory: 5828 grad_norm: 3.0588 loss: 2.4545 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4545 2023/06/04 23:05:18 - mmengine - INFO - Epoch(train) [36][ 400/2569] lr: 4.0000e-02 eta: 21:53:55 time: 0.2687 data_time: 0.0077 memory: 5828 grad_norm: 3.0452 loss: 2.5172 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5172 2023/06/04 23:05:23 - mmengine - INFO - Epoch(train) [36][ 420/2569] lr: 4.0000e-02 eta: 21:53:49 time: 0.2592 data_time: 0.0082 memory: 5828 grad_norm: 3.0549 loss: 2.6879 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6879 2023/06/04 23:05:28 - mmengine - INFO - Epoch(train) [36][ 440/2569] lr: 4.0000e-02 eta: 21:53:44 time: 0.2691 data_time: 0.0081 memory: 5828 grad_norm: 3.0507 loss: 2.5164 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5164 2023/06/04 23:05:34 - mmengine - INFO - Epoch(train) [36][ 460/2569] lr: 4.0000e-02 eta: 21:53:38 time: 0.2594 data_time: 0.0076 memory: 5828 grad_norm: 3.0535 loss: 2.4182 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4182 2023/06/04 23:05:39 - mmengine - INFO - Epoch(train) [36][ 480/2569] lr: 4.0000e-02 eta: 21:53:32 time: 0.2639 data_time: 0.0085 memory: 5828 grad_norm: 3.0372 loss: 2.3676 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3676 2023/06/04 23:05:44 - mmengine - INFO - Epoch(train) [36][ 500/2569] lr: 4.0000e-02 eta: 21:53:27 time: 0.2612 data_time: 0.0080 memory: 5828 grad_norm: 3.0391 loss: 2.7036 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7036 2023/06/04 23:05:49 - mmengine - INFO - Epoch(train) [36][ 520/2569] lr: 4.0000e-02 eta: 21:53:21 time: 0.2632 data_time: 0.0081 memory: 5828 grad_norm: 3.0134 loss: 2.8039 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8039 2023/06/04 23:05:55 - mmengine - INFO - Epoch(train) [36][ 540/2569] lr: 4.0000e-02 eta: 21:53:15 time: 0.2639 data_time: 0.0083 memory: 5828 grad_norm: 3.0419 loss: 2.2794 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2794 2023/06/04 23:06:00 - mmengine - INFO - Epoch(train) [36][ 560/2569] lr: 4.0000e-02 eta: 21:53:10 time: 0.2687 data_time: 0.0081 memory: 5828 grad_norm: 3.0980 loss: 2.6977 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6977 2023/06/04 23:06:06 - mmengine - INFO - Epoch(train) [36][ 580/2569] lr: 4.0000e-02 eta: 21:53:06 time: 0.2788 data_time: 0.0075 memory: 5828 grad_norm: 3.0845 loss: 2.3940 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3940 2023/06/04 23:06:11 - mmengine - INFO - Epoch(train) [36][ 600/2569] lr: 4.0000e-02 eta: 21:53:00 time: 0.2651 data_time: 0.0082 memory: 5828 grad_norm: 3.0099 loss: 2.5894 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5894 2023/06/04 23:06:16 - mmengine - INFO - Epoch(train) [36][ 620/2569] lr: 4.0000e-02 eta: 21:52:55 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.0596 loss: 2.5235 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5235 2023/06/04 23:06:21 - mmengine - INFO - Epoch(train) [36][ 640/2569] lr: 4.0000e-02 eta: 21:52:49 time: 0.2644 data_time: 0.0080 memory: 5828 grad_norm: 3.0707 loss: 2.7593 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7593 2023/06/04 23:06:27 - mmengine - INFO - Epoch(train) [36][ 660/2569] lr: 4.0000e-02 eta: 21:52:43 time: 0.2600 data_time: 0.0082 memory: 5828 grad_norm: 3.0034 loss: 2.5633 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5633 2023/06/04 23:06:32 - mmengine - INFO - Epoch(train) [36][ 680/2569] lr: 4.0000e-02 eta: 21:52:38 time: 0.2695 data_time: 0.0077 memory: 5828 grad_norm: 3.0676 loss: 2.7865 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7865 2023/06/04 23:06:37 - mmengine - INFO - Epoch(train) [36][ 700/2569] lr: 4.0000e-02 eta: 21:52:33 time: 0.2678 data_time: 0.0079 memory: 5828 grad_norm: 3.0413 loss: 2.6438 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6438 2023/06/04 23:06:43 - mmengine - INFO - Epoch(train) [36][ 720/2569] lr: 4.0000e-02 eta: 21:52:27 time: 0.2630 data_time: 0.0076 memory: 5828 grad_norm: 3.0728 loss: 2.6682 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6682 2023/06/04 23:06:48 - mmengine - INFO - Epoch(train) [36][ 740/2569] lr: 4.0000e-02 eta: 21:52:22 time: 0.2646 data_time: 0.0081 memory: 5828 grad_norm: 3.0585 loss: 2.1806 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1806 2023/06/04 23:06:53 - mmengine - INFO - Epoch(train) [36][ 760/2569] lr: 4.0000e-02 eta: 21:52:16 time: 0.2622 data_time: 0.0079 memory: 5828 grad_norm: 3.0388 loss: 2.6028 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6028 2023/06/04 23:06:59 - mmengine - INFO - Epoch(train) [36][ 780/2569] lr: 4.0000e-02 eta: 21:52:11 time: 0.2646 data_time: 0.0079 memory: 5828 grad_norm: 3.0093 loss: 2.3937 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3937 2023/06/04 23:07:04 - mmengine - INFO - Epoch(train) [36][ 800/2569] lr: 4.0000e-02 eta: 21:52:05 time: 0.2607 data_time: 0.0077 memory: 5828 grad_norm: 3.0538 loss: 2.7253 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7253 2023/06/04 23:07:09 - mmengine - INFO - Epoch(train) [36][ 820/2569] lr: 4.0000e-02 eta: 21:51:59 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 3.0922 loss: 2.5828 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5828 2023/06/04 23:07:14 - mmengine - INFO - Epoch(train) [36][ 840/2569] lr: 4.0000e-02 eta: 21:51:53 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 3.0644 loss: 2.2986 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2986 2023/06/04 23:07:20 - mmengine - INFO - Epoch(train) [36][ 860/2569] lr: 4.0000e-02 eta: 21:51:48 time: 0.2706 data_time: 0.0083 memory: 5828 grad_norm: 3.0539 loss: 2.8373 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8373 2023/06/04 23:07:25 - mmengine - INFO - Epoch(train) [36][ 880/2569] lr: 4.0000e-02 eta: 21:51:42 time: 0.2592 data_time: 0.0084 memory: 5828 grad_norm: 3.0793 loss: 2.8667 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8667 2023/06/04 23:07:30 - mmengine - INFO - Epoch(train) [36][ 900/2569] lr: 4.0000e-02 eta: 21:51:37 time: 0.2641 data_time: 0.0082 memory: 5828 grad_norm: 3.0592 loss: 2.3419 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3419 2023/06/04 23:07:35 - mmengine - INFO - Epoch(train) [36][ 920/2569] lr: 4.0000e-02 eta: 21:51:31 time: 0.2596 data_time: 0.0078 memory: 5828 grad_norm: 2.9897 loss: 2.8522 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8522 2023/06/04 23:07:41 - mmengine - INFO - Epoch(train) [36][ 940/2569] lr: 4.0000e-02 eta: 21:51:25 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 3.0829 loss: 2.7124 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7124 2023/06/04 23:07:46 - mmengine - INFO - Epoch(train) [36][ 960/2569] lr: 4.0000e-02 eta: 21:51:20 time: 0.2680 data_time: 0.0079 memory: 5828 grad_norm: 3.0648 loss: 2.3819 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3819 2023/06/04 23:07:51 - mmengine - INFO - Epoch(train) [36][ 980/2569] lr: 4.0000e-02 eta: 21:51:15 time: 0.2650 data_time: 0.0080 memory: 5828 grad_norm: 3.0622 loss: 2.5527 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5527 2023/06/04 23:07:57 - mmengine - INFO - Epoch(train) [36][1000/2569] lr: 4.0000e-02 eta: 21:51:09 time: 0.2652 data_time: 0.0083 memory: 5828 grad_norm: 3.0702 loss: 2.9292 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9292 2023/06/04 23:08:02 - mmengine - INFO - Epoch(train) [36][1020/2569] lr: 4.0000e-02 eta: 21:51:04 time: 0.2659 data_time: 0.0078 memory: 5828 grad_norm: 3.0591 loss: 2.1339 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1339 2023/06/04 23:08:07 - mmengine - INFO - Epoch(train) [36][1040/2569] lr: 4.0000e-02 eta: 21:50:58 time: 0.2608 data_time: 0.0081 memory: 5828 grad_norm: 3.0608 loss: 2.6359 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6359 2023/06/04 23:08:12 - mmengine - INFO - Epoch(train) [36][1060/2569] lr: 4.0000e-02 eta: 21:50:52 time: 0.2623 data_time: 0.0078 memory: 5828 grad_norm: 3.0883 loss: 2.6208 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6208 2023/06/04 23:08:18 - mmengine - INFO - Epoch(train) [36][1080/2569] lr: 4.0000e-02 eta: 21:50:47 time: 0.2655 data_time: 0.0080 memory: 5828 grad_norm: 3.0328 loss: 2.3789 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3789 2023/06/04 23:08:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:08:23 - mmengine - INFO - Epoch(train) [36][1100/2569] lr: 4.0000e-02 eta: 21:50:41 time: 0.2642 data_time: 0.0087 memory: 5828 grad_norm: 3.0416 loss: 2.6177 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6177 2023/06/04 23:08:28 - mmengine - INFO - Epoch(train) [36][1120/2569] lr: 4.0000e-02 eta: 21:50:36 time: 0.2749 data_time: 0.0079 memory: 5828 grad_norm: 3.0392 loss: 2.3804 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3804 2023/06/04 23:08:34 - mmengine - INFO - Epoch(train) [36][1140/2569] lr: 4.0000e-02 eta: 21:50:31 time: 0.2615 data_time: 0.0077 memory: 5828 grad_norm: 3.0270 loss: 2.9578 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.9578 2023/06/04 23:08:39 - mmengine - INFO - Epoch(train) [36][1160/2569] lr: 4.0000e-02 eta: 21:50:25 time: 0.2658 data_time: 0.0083 memory: 5828 grad_norm: 3.0828 loss: 2.7802 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7802 2023/06/04 23:08:44 - mmengine - INFO - Epoch(train) [36][1180/2569] lr: 4.0000e-02 eta: 21:50:19 time: 0.2588 data_time: 0.0080 memory: 5828 grad_norm: 3.0199 loss: 2.8158 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8158 2023/06/04 23:08:49 - mmengine - INFO - Epoch(train) [36][1200/2569] lr: 4.0000e-02 eta: 21:50:14 time: 0.2593 data_time: 0.0082 memory: 5828 grad_norm: 3.0391 loss: 2.5623 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5623 2023/06/04 23:08:55 - mmengine - INFO - Epoch(train) [36][1220/2569] lr: 4.0000e-02 eta: 21:50:08 time: 0.2695 data_time: 0.0076 memory: 5828 grad_norm: 3.0611 loss: 2.7278 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7278 2023/06/04 23:09:00 - mmengine - INFO - Epoch(train) [36][1240/2569] lr: 4.0000e-02 eta: 21:50:03 time: 0.2642 data_time: 0.0080 memory: 5828 grad_norm: 3.0295 loss: 2.9110 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.9110 2023/06/04 23:09:05 - mmengine - INFO - Epoch(train) [36][1260/2569] lr: 4.0000e-02 eta: 21:49:57 time: 0.2651 data_time: 0.0081 memory: 5828 grad_norm: 3.0839 loss: 2.4079 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4079 2023/06/04 23:09:11 - mmengine - INFO - Epoch(train) [36][1280/2569] lr: 4.0000e-02 eta: 21:49:52 time: 0.2701 data_time: 0.0081 memory: 5828 grad_norm: 3.0354 loss: 2.4853 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4853 2023/06/04 23:09:16 - mmengine - INFO - Epoch(train) [36][1300/2569] lr: 4.0000e-02 eta: 21:49:47 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 3.0639 loss: 2.7357 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7357 2023/06/04 23:09:21 - mmengine - INFO - Epoch(train) [36][1320/2569] lr: 4.0000e-02 eta: 21:49:42 time: 0.2718 data_time: 0.0078 memory: 5828 grad_norm: 3.0116 loss: 2.8074 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8074 2023/06/04 23:09:27 - mmengine - INFO - Epoch(train) [36][1340/2569] lr: 4.0000e-02 eta: 21:49:37 time: 0.2755 data_time: 0.0080 memory: 5828 grad_norm: 3.0912 loss: 2.5059 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5059 2023/06/04 23:09:32 - mmengine - INFO - Epoch(train) [36][1360/2569] lr: 4.0000e-02 eta: 21:49:31 time: 0.2630 data_time: 0.0079 memory: 5828 grad_norm: 3.0329 loss: 2.3790 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3790 2023/06/04 23:09:37 - mmengine - INFO - Epoch(train) [36][1380/2569] lr: 4.0000e-02 eta: 21:49:25 time: 0.2580 data_time: 0.0076 memory: 5828 grad_norm: 3.0747 loss: 2.4528 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4528 2023/06/04 23:09:43 - mmengine - INFO - Epoch(train) [36][1400/2569] lr: 4.0000e-02 eta: 21:49:19 time: 0.2591 data_time: 0.0079 memory: 5828 grad_norm: 3.1765 loss: 2.5558 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5558 2023/06/04 23:09:48 - mmengine - INFO - Epoch(train) [36][1420/2569] lr: 4.0000e-02 eta: 21:49:14 time: 0.2647 data_time: 0.0079 memory: 5828 grad_norm: 3.0562 loss: 2.7092 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7092 2023/06/04 23:09:53 - mmengine - INFO - Epoch(train) [36][1440/2569] lr: 4.0000e-02 eta: 21:49:08 time: 0.2651 data_time: 0.0079 memory: 5828 grad_norm: 3.0057 loss: 2.8005 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8005 2023/06/04 23:09:59 - mmengine - INFO - Epoch(train) [36][1460/2569] lr: 4.0000e-02 eta: 21:49:03 time: 0.2680 data_time: 0.0080 memory: 5828 grad_norm: 3.0617 loss: 2.3829 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3829 2023/06/04 23:10:04 - mmengine - INFO - Epoch(train) [36][1480/2569] lr: 4.0000e-02 eta: 21:48:58 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 3.0093 loss: 2.7709 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7709 2023/06/04 23:10:09 - mmengine - INFO - Epoch(train) [36][1500/2569] lr: 4.0000e-02 eta: 21:48:52 time: 0.2655 data_time: 0.0076 memory: 5828 grad_norm: 3.0343 loss: 2.6341 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6341 2023/06/04 23:10:15 - mmengine - INFO - Epoch(train) [36][1520/2569] lr: 4.0000e-02 eta: 21:48:47 time: 0.2744 data_time: 0.0079 memory: 5828 grad_norm: 3.0504 loss: 2.5894 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5894 2023/06/04 23:10:20 - mmengine - INFO - Epoch(train) [36][1540/2569] lr: 4.0000e-02 eta: 21:48:42 time: 0.2651 data_time: 0.0079 memory: 5828 grad_norm: 3.0272 loss: 2.8539 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8539 2023/06/04 23:10:25 - mmengine - INFO - Epoch(train) [36][1560/2569] lr: 4.0000e-02 eta: 21:48:36 time: 0.2640 data_time: 0.0079 memory: 5828 grad_norm: 3.0232 loss: 2.9213 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9213 2023/06/04 23:10:31 - mmengine - INFO - Epoch(train) [36][1580/2569] lr: 4.0000e-02 eta: 21:48:31 time: 0.2649 data_time: 0.0078 memory: 5828 grad_norm: 3.0468 loss: 2.7582 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7582 2023/06/04 23:10:36 - mmengine - INFO - Epoch(train) [36][1600/2569] lr: 4.0000e-02 eta: 21:48:25 time: 0.2643 data_time: 0.0087 memory: 5828 grad_norm: 3.0111 loss: 2.1466 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.1466 2023/06/04 23:10:41 - mmengine - INFO - Epoch(train) [36][1620/2569] lr: 4.0000e-02 eta: 21:48:20 time: 0.2737 data_time: 0.0077 memory: 5828 grad_norm: 3.0833 loss: 2.6086 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6086 2023/06/04 23:10:47 - mmengine - INFO - Epoch(train) [36][1640/2569] lr: 4.0000e-02 eta: 21:48:15 time: 0.2644 data_time: 0.0082 memory: 5828 grad_norm: 3.0631 loss: 2.7312 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7312 2023/06/04 23:10:52 - mmengine - INFO - Epoch(train) [36][1660/2569] lr: 4.0000e-02 eta: 21:48:09 time: 0.2632 data_time: 0.0079 memory: 5828 grad_norm: 3.0696 loss: 2.8145 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8145 2023/06/04 23:10:57 - mmengine - INFO - Epoch(train) [36][1680/2569] lr: 4.0000e-02 eta: 21:48:03 time: 0.2590 data_time: 0.0080 memory: 5828 grad_norm: 2.9627 loss: 2.6711 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6711 2023/06/04 23:11:02 - mmengine - INFO - Epoch(train) [36][1700/2569] lr: 4.0000e-02 eta: 21:47:58 time: 0.2682 data_time: 0.0079 memory: 5828 grad_norm: 3.0769 loss: 2.5651 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5651 2023/06/04 23:11:08 - mmengine - INFO - Epoch(train) [36][1720/2569] lr: 4.0000e-02 eta: 21:47:52 time: 0.2593 data_time: 0.0079 memory: 5828 grad_norm: 3.0493 loss: 2.4333 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4333 2023/06/04 23:11:13 - mmengine - INFO - Epoch(train) [36][1740/2569] lr: 4.0000e-02 eta: 21:47:47 time: 0.2684 data_time: 0.0075 memory: 5828 grad_norm: 3.0520 loss: 2.7994 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7994 2023/06/04 23:11:18 - mmengine - INFO - Epoch(train) [36][1760/2569] lr: 4.0000e-02 eta: 21:47:41 time: 0.2596 data_time: 0.0082 memory: 5828 grad_norm: 3.0823 loss: 2.6921 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6921 2023/06/04 23:11:24 - mmengine - INFO - Epoch(train) [36][1780/2569] lr: 4.0000e-02 eta: 21:47:36 time: 0.2684 data_time: 0.0081 memory: 5828 grad_norm: 3.0107 loss: 2.7627 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7627 2023/06/04 23:11:29 - mmengine - INFO - Epoch(train) [36][1800/2569] lr: 4.0000e-02 eta: 21:47:30 time: 0.2596 data_time: 0.0079 memory: 5828 grad_norm: 2.9495 loss: 2.4037 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4037 2023/06/04 23:11:34 - mmengine - INFO - Epoch(train) [36][1820/2569] lr: 4.0000e-02 eta: 21:47:25 time: 0.2694 data_time: 0.0082 memory: 5828 grad_norm: 3.0999 loss: 2.5281 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5281 2023/06/04 23:11:39 - mmengine - INFO - Epoch(train) [36][1840/2569] lr: 4.0000e-02 eta: 21:47:19 time: 0.2639 data_time: 0.0079 memory: 5828 grad_norm: 3.0631 loss: 2.8824 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8824 2023/06/04 23:11:45 - mmengine - INFO - Epoch(train) [36][1860/2569] lr: 4.0000e-02 eta: 21:47:14 time: 0.2687 data_time: 0.0077 memory: 5828 grad_norm: 3.0806 loss: 2.6789 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6789 2023/06/04 23:11:50 - mmengine - INFO - Epoch(train) [36][1880/2569] lr: 4.0000e-02 eta: 21:47:09 time: 0.2718 data_time: 0.0081 memory: 5828 grad_norm: 3.0805 loss: 2.6540 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6540 2023/06/04 23:11:56 - mmengine - INFO - Epoch(train) [36][1900/2569] lr: 4.0000e-02 eta: 21:47:03 time: 0.2598 data_time: 0.0077 memory: 5828 grad_norm: 3.0938 loss: 2.6447 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6447 2023/06/04 23:12:01 - mmengine - INFO - Epoch(train) [36][1920/2569] lr: 4.0000e-02 eta: 21:46:58 time: 0.2662 data_time: 0.0078 memory: 5828 grad_norm: 3.0103 loss: 2.6044 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6044 2023/06/04 23:12:06 - mmengine - INFO - Epoch(train) [36][1940/2569] lr: 4.0000e-02 eta: 21:46:53 time: 0.2707 data_time: 0.0081 memory: 5828 grad_norm: 3.0344 loss: 2.5224 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5224 2023/06/04 23:12:11 - mmengine - INFO - Epoch(train) [36][1960/2569] lr: 4.0000e-02 eta: 21:46:47 time: 0.2604 data_time: 0.0082 memory: 5828 grad_norm: 3.0813 loss: 2.7261 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7261 2023/06/04 23:12:17 - mmengine - INFO - Epoch(train) [36][1980/2569] lr: 4.0000e-02 eta: 21:46:41 time: 0.2613 data_time: 0.0081 memory: 5828 grad_norm: 3.0745 loss: 2.3997 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3997 2023/06/04 23:12:22 - mmengine - INFO - Epoch(train) [36][2000/2569] lr: 4.0000e-02 eta: 21:46:36 time: 0.2690 data_time: 0.0078 memory: 5828 grad_norm: 3.0419 loss: 2.7472 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7472 2023/06/04 23:12:27 - mmengine - INFO - Epoch(train) [36][2020/2569] lr: 4.0000e-02 eta: 21:46:31 time: 0.2669 data_time: 0.0082 memory: 5828 grad_norm: 2.9956 loss: 2.5753 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5753 2023/06/04 23:12:33 - mmengine - INFO - Epoch(train) [36][2040/2569] lr: 4.0000e-02 eta: 21:46:26 time: 0.2781 data_time: 0.0080 memory: 5828 grad_norm: 2.9906 loss: 2.6014 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6014 2023/06/04 23:12:38 - mmengine - INFO - Epoch(train) [36][2060/2569] lr: 4.0000e-02 eta: 21:46:21 time: 0.2683 data_time: 0.0076 memory: 5828 grad_norm: 3.0759 loss: 2.3680 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.3680 2023/06/04 23:12:44 - mmengine - INFO - Epoch(train) [36][2080/2569] lr: 4.0000e-02 eta: 21:46:16 time: 0.2694 data_time: 0.0082 memory: 5828 grad_norm: 3.0606 loss: 2.4253 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4253 2023/06/04 23:12:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:12:49 - mmengine - INFO - Epoch(train) [36][2100/2569] lr: 4.0000e-02 eta: 21:46:10 time: 0.2615 data_time: 0.0081 memory: 5828 grad_norm: 3.0521 loss: 2.5300 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5300 2023/06/04 23:12:54 - mmengine - INFO - Epoch(train) [36][2120/2569] lr: 4.0000e-02 eta: 21:46:04 time: 0.2638 data_time: 0.0076 memory: 5828 grad_norm: 3.0546 loss: 2.5836 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5836 2023/06/04 23:13:00 - mmengine - INFO - Epoch(train) [36][2140/2569] lr: 4.0000e-02 eta: 21:45:59 time: 0.2671 data_time: 0.0080 memory: 5828 grad_norm: 3.0524 loss: 2.8174 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8174 2023/06/04 23:13:05 - mmengine - INFO - Epoch(train) [36][2160/2569] lr: 4.0000e-02 eta: 21:45:53 time: 0.2603 data_time: 0.0081 memory: 5828 grad_norm: 3.1157 loss: 2.7122 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7122 2023/06/04 23:13:10 - mmengine - INFO - Epoch(train) [36][2180/2569] lr: 4.0000e-02 eta: 21:45:48 time: 0.2636 data_time: 0.0083 memory: 5828 grad_norm: 3.1063 loss: 2.5101 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5101 2023/06/04 23:13:15 - mmengine - INFO - Epoch(train) [36][2200/2569] lr: 4.0000e-02 eta: 21:45:42 time: 0.2614 data_time: 0.0080 memory: 5828 grad_norm: 3.0522 loss: 2.7006 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7006 2023/06/04 23:13:21 - mmengine - INFO - Epoch(train) [36][2220/2569] lr: 4.0000e-02 eta: 21:45:37 time: 0.2735 data_time: 0.0082 memory: 5828 grad_norm: 3.0284 loss: 2.5918 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5918 2023/06/04 23:13:26 - mmengine - INFO - Epoch(train) [36][2240/2569] lr: 4.0000e-02 eta: 21:45:32 time: 0.2687 data_time: 0.0079 memory: 5828 grad_norm: 3.0083 loss: 2.7495 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7495 2023/06/04 23:13:32 - mmengine - INFO - Epoch(train) [36][2260/2569] lr: 4.0000e-02 eta: 21:45:27 time: 0.2760 data_time: 0.0077 memory: 5828 grad_norm: 3.0417 loss: 2.7004 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7004 2023/06/04 23:13:37 - mmengine - INFO - Epoch(train) [36][2280/2569] lr: 4.0000e-02 eta: 21:45:21 time: 0.2649 data_time: 0.0081 memory: 5828 grad_norm: 3.1089 loss: 2.7259 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7259 2023/06/04 23:13:42 - mmengine - INFO - Epoch(train) [36][2300/2569] lr: 4.0000e-02 eta: 21:45:16 time: 0.2714 data_time: 0.0071 memory: 5828 grad_norm: 3.0272 loss: 2.4897 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4897 2023/06/04 23:13:48 - mmengine - INFO - Epoch(train) [36][2320/2569] lr: 4.0000e-02 eta: 21:45:11 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 3.0365 loss: 2.8672 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8672 2023/06/04 23:13:53 - mmengine - INFO - Epoch(train) [36][2340/2569] lr: 4.0000e-02 eta: 21:45:05 time: 0.2638 data_time: 0.0079 memory: 5828 grad_norm: 3.0470 loss: 2.7360 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7360 2023/06/04 23:13:58 - mmengine - INFO - Epoch(train) [36][2360/2569] lr: 4.0000e-02 eta: 21:45:00 time: 0.2702 data_time: 0.0074 memory: 5828 grad_norm: 2.9794 loss: 2.6000 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6000 2023/06/04 23:14:04 - mmengine - INFO - Epoch(train) [36][2380/2569] lr: 4.0000e-02 eta: 21:44:55 time: 0.2628 data_time: 0.0082 memory: 5828 grad_norm: 3.1509 loss: 2.6555 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6555 2023/06/04 23:14:09 - mmengine - INFO - Epoch(train) [36][2400/2569] lr: 4.0000e-02 eta: 21:44:49 time: 0.2648 data_time: 0.0076 memory: 5828 grad_norm: 3.0049 loss: 2.8795 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8795 2023/06/04 23:14:14 - mmengine - INFO - Epoch(train) [36][2420/2569] lr: 4.0000e-02 eta: 21:44:43 time: 0.2599 data_time: 0.0078 memory: 5828 grad_norm: 3.0384 loss: 2.5478 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5478 2023/06/04 23:14:19 - mmengine - INFO - Epoch(train) [36][2440/2569] lr: 4.0000e-02 eta: 21:44:37 time: 0.2586 data_time: 0.0078 memory: 5828 grad_norm: 3.0898 loss: 2.7301 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7301 2023/06/04 23:14:25 - mmengine - INFO - Epoch(train) [36][2460/2569] lr: 4.0000e-02 eta: 21:44:32 time: 0.2628 data_time: 0.0079 memory: 5828 grad_norm: 2.9931 loss: 2.5006 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5006 2023/06/04 23:14:30 - mmengine - INFO - Epoch(train) [36][2480/2569] lr: 4.0000e-02 eta: 21:44:26 time: 0.2587 data_time: 0.0078 memory: 5828 grad_norm: 3.0312 loss: 2.5838 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5838 2023/06/04 23:14:35 - mmengine - INFO - Epoch(train) [36][2500/2569] lr: 4.0000e-02 eta: 21:44:21 time: 0.2686 data_time: 0.0081 memory: 5828 grad_norm: 3.0302 loss: 2.4892 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4892 2023/06/04 23:14:40 - mmengine - INFO - Epoch(train) [36][2520/2569] lr: 4.0000e-02 eta: 21:44:15 time: 0.2580 data_time: 0.0085 memory: 5828 grad_norm: 3.0417 loss: 2.5515 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5515 2023/06/04 23:14:46 - mmengine - INFO - Epoch(train) [36][2540/2569] lr: 4.0000e-02 eta: 21:44:09 time: 0.2631 data_time: 0.0076 memory: 5828 grad_norm: 3.0530 loss: 2.7541 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7541 2023/06/04 23:14:51 - mmengine - INFO - Epoch(train) [36][2560/2569] lr: 4.0000e-02 eta: 21:44:03 time: 0.2583 data_time: 0.0079 memory: 5828 grad_norm: 3.1044 loss: 2.6385 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6385 2023/06/04 23:14:53 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:14:53 - mmengine - INFO - Epoch(train) [36][2569/2569] lr: 4.0000e-02 eta: 21:44:00 time: 0.2524 data_time: 0.0077 memory: 5828 grad_norm: 3.1092 loss: 2.5346 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.5346 2023/06/04 23:14:53 - mmengine - INFO - Saving checkpoint at 36 epochs 2023/06/04 23:15:01 - mmengine - INFO - Epoch(train) [37][ 20/2569] lr: 4.0000e-02 eta: 21:43:57 time: 0.2943 data_time: 0.0423 memory: 5828 grad_norm: 3.0548 loss: 2.3855 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.3855 2023/06/04 23:15:06 - mmengine - INFO - Epoch(train) [37][ 40/2569] lr: 4.0000e-02 eta: 21:43:51 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 3.1642 loss: 2.4854 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4854 2023/06/04 23:15:12 - mmengine - INFO - Epoch(train) [37][ 60/2569] lr: 4.0000e-02 eta: 21:43:46 time: 0.2691 data_time: 0.0081 memory: 5828 grad_norm: 3.0005 loss: 2.4696 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4696 2023/06/04 23:15:17 - mmengine - INFO - Epoch(train) [37][ 80/2569] lr: 4.0000e-02 eta: 21:43:40 time: 0.2685 data_time: 0.0084 memory: 5828 grad_norm: 3.1616 loss: 3.0336 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 3.0336 2023/06/04 23:15:22 - mmengine - INFO - Epoch(train) [37][ 100/2569] lr: 4.0000e-02 eta: 21:43:35 time: 0.2599 data_time: 0.0079 memory: 5828 grad_norm: 3.1468 loss: 2.5950 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5950 2023/06/04 23:15:28 - mmengine - INFO - Epoch(train) [37][ 120/2569] lr: 4.0000e-02 eta: 21:43:29 time: 0.2704 data_time: 0.0080 memory: 5828 grad_norm: 3.0218 loss: 2.6823 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6823 2023/06/04 23:15:33 - mmengine - INFO - Epoch(train) [37][ 140/2569] lr: 4.0000e-02 eta: 21:43:24 time: 0.2606 data_time: 0.0077 memory: 5828 grad_norm: 3.0932 loss: 2.4878 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4878 2023/06/04 23:15:38 - mmengine - INFO - Epoch(train) [37][ 160/2569] lr: 4.0000e-02 eta: 21:43:18 time: 0.2597 data_time: 0.0080 memory: 5828 grad_norm: 3.0469 loss: 2.4735 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4735 2023/06/04 23:15:43 - mmengine - INFO - Epoch(train) [37][ 180/2569] lr: 4.0000e-02 eta: 21:43:13 time: 0.2712 data_time: 0.0081 memory: 5828 grad_norm: 3.1229 loss: 2.7417 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7417 2023/06/04 23:15:49 - mmengine - INFO - Epoch(train) [37][ 200/2569] lr: 4.0000e-02 eta: 21:43:07 time: 0.2586 data_time: 0.0079 memory: 5828 grad_norm: 3.0524 loss: 2.5884 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5884 2023/06/04 23:15:54 - mmengine - INFO - Epoch(train) [37][ 220/2569] lr: 4.0000e-02 eta: 21:43:02 time: 0.2730 data_time: 0.0075 memory: 5828 grad_norm: 3.0308 loss: 2.5532 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5532 2023/06/04 23:15:59 - mmengine - INFO - Epoch(train) [37][ 240/2569] lr: 4.0000e-02 eta: 21:42:56 time: 0.2594 data_time: 0.0081 memory: 5828 grad_norm: 3.0657 loss: 2.6374 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6374 2023/06/04 23:16:05 - mmengine - INFO - Epoch(train) [37][ 260/2569] lr: 4.0000e-02 eta: 21:42:51 time: 0.2651 data_time: 0.0080 memory: 5828 grad_norm: 3.0584 loss: 2.6252 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6252 2023/06/04 23:16:10 - mmengine - INFO - Epoch(train) [37][ 280/2569] lr: 4.0000e-02 eta: 21:42:45 time: 0.2619 data_time: 0.0078 memory: 5828 grad_norm: 3.0187 loss: 2.7593 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.7593 2023/06/04 23:16:15 - mmengine - INFO - Epoch(train) [37][ 300/2569] lr: 4.0000e-02 eta: 21:42:40 time: 0.2677 data_time: 0.0076 memory: 5828 grad_norm: 3.0487 loss: 2.5884 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5884 2023/06/04 23:16:20 - mmengine - INFO - Epoch(train) [37][ 320/2569] lr: 4.0000e-02 eta: 21:42:34 time: 0.2651 data_time: 0.0077 memory: 5828 grad_norm: 2.9866 loss: 2.7531 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7531 2023/06/04 23:16:26 - mmengine - INFO - Epoch(train) [37][ 340/2569] lr: 4.0000e-02 eta: 21:42:29 time: 0.2722 data_time: 0.0079 memory: 5828 grad_norm: 3.0464 loss: 2.4001 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4001 2023/06/04 23:16:31 - mmengine - INFO - Epoch(train) [37][ 360/2569] lr: 4.0000e-02 eta: 21:42:24 time: 0.2710 data_time: 0.0079 memory: 5828 grad_norm: 3.1093 loss: 2.4632 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4632 2023/06/04 23:16:37 - mmengine - INFO - Epoch(train) [37][ 380/2569] lr: 4.0000e-02 eta: 21:42:19 time: 0.2701 data_time: 0.0079 memory: 5828 grad_norm: 3.0459 loss: 2.5637 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5637 2023/06/04 23:16:42 - mmengine - INFO - Epoch(train) [37][ 400/2569] lr: 4.0000e-02 eta: 21:42:14 time: 0.2762 data_time: 0.0076 memory: 5828 grad_norm: 3.0322 loss: 2.7369 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7369 2023/06/04 23:16:48 - mmengine - INFO - Epoch(train) [37][ 420/2569] lr: 4.0000e-02 eta: 21:42:09 time: 0.2704 data_time: 0.0080 memory: 5828 grad_norm: 3.0569 loss: 2.8963 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8963 2023/06/04 23:16:53 - mmengine - INFO - Epoch(train) [37][ 440/2569] lr: 4.0000e-02 eta: 21:42:03 time: 0.2609 data_time: 0.0085 memory: 5828 grad_norm: 3.0971 loss: 2.5472 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5472 2023/06/04 23:16:58 - mmengine - INFO - Epoch(train) [37][ 460/2569] lr: 4.0000e-02 eta: 21:41:58 time: 0.2747 data_time: 0.0080 memory: 5828 grad_norm: 3.0443 loss: 2.8394 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8394 2023/06/04 23:17:04 - mmengine - INFO - Epoch(train) [37][ 480/2569] lr: 4.0000e-02 eta: 21:41:53 time: 0.2691 data_time: 0.0080 memory: 5828 grad_norm: 3.0945 loss: 2.6761 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6761 2023/06/04 23:17:09 - mmengine - INFO - Epoch(train) [37][ 500/2569] lr: 4.0000e-02 eta: 21:41:47 time: 0.2602 data_time: 0.0077 memory: 5828 grad_norm: 3.0621 loss: 2.5641 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5641 2023/06/04 23:17:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:17:14 - mmengine - INFO - Epoch(train) [37][ 520/2569] lr: 4.0000e-02 eta: 21:41:42 time: 0.2735 data_time: 0.0075 memory: 5828 grad_norm: 3.1024 loss: 2.8500 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8500 2023/06/04 23:17:20 - mmengine - INFO - Epoch(train) [37][ 540/2569] lr: 4.0000e-02 eta: 21:41:37 time: 0.2605 data_time: 0.0078 memory: 5828 grad_norm: 3.0330 loss: 2.7001 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7001 2023/06/04 23:17:25 - mmengine - INFO - Epoch(train) [37][ 560/2569] lr: 4.0000e-02 eta: 21:41:32 time: 0.2736 data_time: 0.0080 memory: 5828 grad_norm: 3.0501 loss: 2.7751 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7751 2023/06/04 23:17:30 - mmengine - INFO - Epoch(train) [37][ 580/2569] lr: 4.0000e-02 eta: 21:41:26 time: 0.2604 data_time: 0.0078 memory: 5828 grad_norm: 3.0562 loss: 2.8209 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8209 2023/06/04 23:17:36 - mmengine - INFO - Epoch(train) [37][ 600/2569] lr: 4.0000e-02 eta: 21:41:21 time: 0.2676 data_time: 0.0078 memory: 5828 grad_norm: 3.0580 loss: 2.5104 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5104 2023/06/04 23:17:41 - mmengine - INFO - Epoch(train) [37][ 620/2569] lr: 4.0000e-02 eta: 21:41:15 time: 0.2588 data_time: 0.0078 memory: 5828 grad_norm: 3.0945 loss: 2.8790 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8790 2023/06/04 23:17:46 - mmengine - INFO - Epoch(train) [37][ 640/2569] lr: 4.0000e-02 eta: 21:41:10 time: 0.2697 data_time: 0.0079 memory: 5828 grad_norm: 3.0542 loss: 2.5840 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5840 2023/06/04 23:17:52 - mmengine - INFO - Epoch(train) [37][ 660/2569] lr: 4.0000e-02 eta: 21:41:04 time: 0.2678 data_time: 0.0076 memory: 5828 grad_norm: 3.1257 loss: 2.6514 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6514 2023/06/04 23:17:57 - mmengine - INFO - Epoch(train) [37][ 680/2569] lr: 4.0000e-02 eta: 21:40:59 time: 0.2700 data_time: 0.0084 memory: 5828 grad_norm: 3.0441 loss: 2.6708 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6708 2023/06/04 23:18:02 - mmengine - INFO - Epoch(train) [37][ 700/2569] lr: 4.0000e-02 eta: 21:40:54 time: 0.2653 data_time: 0.0073 memory: 5828 grad_norm: 3.0943 loss: 2.8574 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8574 2023/06/04 23:18:08 - mmengine - INFO - Epoch(train) [37][ 720/2569] lr: 4.0000e-02 eta: 21:40:48 time: 0.2649 data_time: 0.0087 memory: 5828 grad_norm: 3.0346 loss: 2.4330 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4330 2023/06/04 23:18:13 - mmengine - INFO - Epoch(train) [37][ 740/2569] lr: 4.0000e-02 eta: 21:40:43 time: 0.2713 data_time: 0.0080 memory: 5828 grad_norm: 3.0890 loss: 2.6984 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6984 2023/06/04 23:18:18 - mmengine - INFO - Epoch(train) [37][ 760/2569] lr: 4.0000e-02 eta: 21:40:38 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 3.1214 loss: 2.6794 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6794 2023/06/04 23:18:24 - mmengine - INFO - Epoch(train) [37][ 780/2569] lr: 4.0000e-02 eta: 21:40:32 time: 0.2692 data_time: 0.0082 memory: 5828 grad_norm: 3.0649 loss: 2.3950 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3950 2023/06/04 23:18:29 - mmengine - INFO - Epoch(train) [37][ 800/2569] lr: 4.0000e-02 eta: 21:40:27 time: 0.2709 data_time: 0.0079 memory: 5828 grad_norm: 3.1773 loss: 2.5751 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5751 2023/06/04 23:18:35 - mmengine - INFO - Epoch(train) [37][ 820/2569] lr: 4.0000e-02 eta: 21:40:22 time: 0.2694 data_time: 0.0077 memory: 5828 grad_norm: 3.0483 loss: 2.6805 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6805 2023/06/04 23:18:40 - mmengine - INFO - Epoch(train) [37][ 840/2569] lr: 4.0000e-02 eta: 21:40:17 time: 0.2694 data_time: 0.0082 memory: 5828 grad_norm: 3.0757 loss: 2.3476 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3476 2023/06/04 23:18:45 - mmengine - INFO - Epoch(train) [37][ 860/2569] lr: 4.0000e-02 eta: 21:40:11 time: 0.2645 data_time: 0.0077 memory: 5828 grad_norm: 3.0715 loss: 2.5767 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5767 2023/06/04 23:18:51 - mmengine - INFO - Epoch(train) [37][ 880/2569] lr: 4.0000e-02 eta: 21:40:06 time: 0.2718 data_time: 0.0082 memory: 5828 grad_norm: 3.0103 loss: 2.2786 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2786 2023/06/04 23:18:56 - mmengine - INFO - Epoch(train) [37][ 900/2569] lr: 4.0000e-02 eta: 21:40:01 time: 0.2719 data_time: 0.0081 memory: 5828 grad_norm: 3.0521 loss: 2.7980 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7980 2023/06/04 23:19:01 - mmengine - INFO - Epoch(train) [37][ 920/2569] lr: 4.0000e-02 eta: 21:39:55 time: 0.2606 data_time: 0.0082 memory: 5828 grad_norm: 3.0237 loss: 2.5618 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5618 2023/06/04 23:19:07 - mmengine - INFO - Epoch(train) [37][ 940/2569] lr: 4.0000e-02 eta: 21:39:50 time: 0.2595 data_time: 0.0081 memory: 5828 grad_norm: 3.0752 loss: 2.7062 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7062 2023/06/04 23:19:12 - mmengine - INFO - Epoch(train) [37][ 960/2569] lr: 4.0000e-02 eta: 21:39:44 time: 0.2593 data_time: 0.0080 memory: 5828 grad_norm: 3.0694 loss: 2.3755 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3755 2023/06/04 23:19:17 - mmengine - INFO - Epoch(train) [37][ 980/2569] lr: 4.0000e-02 eta: 21:39:38 time: 0.2670 data_time: 0.0077 memory: 5828 grad_norm: 3.1219 loss: 2.5592 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5592 2023/06/04 23:19:23 - mmengine - INFO - Epoch(train) [37][1000/2569] lr: 4.0000e-02 eta: 21:39:33 time: 0.2701 data_time: 0.0077 memory: 5828 grad_norm: 3.0439 loss: 2.1161 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1161 2023/06/04 23:19:28 - mmengine - INFO - Epoch(train) [37][1020/2569] lr: 4.0000e-02 eta: 21:39:28 time: 0.2697 data_time: 0.0080 memory: 5828 grad_norm: 3.1111 loss: 2.7445 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7445 2023/06/04 23:19:33 - mmengine - INFO - Epoch(train) [37][1040/2569] lr: 4.0000e-02 eta: 21:39:22 time: 0.2620 data_time: 0.0081 memory: 5828 grad_norm: 3.0410 loss: 2.7606 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7606 2023/06/04 23:19:38 - mmengine - INFO - Epoch(train) [37][1060/2569] lr: 4.0000e-02 eta: 21:39:17 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 3.0575 loss: 2.7867 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7867 2023/06/04 23:19:44 - mmengine - INFO - Epoch(train) [37][1080/2569] lr: 4.0000e-02 eta: 21:39:11 time: 0.2616 data_time: 0.0079 memory: 5828 grad_norm: 3.0647 loss: 2.7392 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7392 2023/06/04 23:19:49 - mmengine - INFO - Epoch(train) [37][1100/2569] lr: 4.0000e-02 eta: 21:39:05 time: 0.2593 data_time: 0.0080 memory: 5828 grad_norm: 3.0108 loss: 2.6760 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6760 2023/06/04 23:19:54 - mmengine - INFO - Epoch(train) [37][1120/2569] lr: 4.0000e-02 eta: 21:39:00 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.0211 loss: 2.7315 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7315 2023/06/04 23:19:59 - mmengine - INFO - Epoch(train) [37][1140/2569] lr: 4.0000e-02 eta: 21:38:54 time: 0.2598 data_time: 0.0078 memory: 5828 grad_norm: 3.0150 loss: 2.7443 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7443 2023/06/04 23:20:05 - mmengine - INFO - Epoch(train) [37][1160/2569] lr: 4.0000e-02 eta: 21:38:49 time: 0.2688 data_time: 0.0077 memory: 5828 grad_norm: 3.0725 loss: 2.5385 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5385 2023/06/04 23:20:10 - mmengine - INFO - Epoch(train) [37][1180/2569] lr: 4.0000e-02 eta: 21:38:44 time: 0.2677 data_time: 0.0075 memory: 5828 grad_norm: 3.0954 loss: 2.1945 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1945 2023/06/04 23:20:16 - mmengine - INFO - Epoch(train) [37][1200/2569] lr: 4.0000e-02 eta: 21:38:38 time: 0.2691 data_time: 0.0078 memory: 5828 grad_norm: 3.1069 loss: 2.4885 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4885 2023/06/04 23:20:21 - mmengine - INFO - Epoch(train) [37][1220/2569] lr: 4.0000e-02 eta: 21:38:33 time: 0.2670 data_time: 0.0078 memory: 5828 grad_norm: 3.0376 loss: 2.7697 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7697 2023/06/04 23:20:26 - mmengine - INFO - Epoch(train) [37][1240/2569] lr: 4.0000e-02 eta: 21:38:27 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.0462 loss: 2.6870 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6870 2023/06/04 23:20:31 - mmengine - INFO - Epoch(train) [37][1260/2569] lr: 4.0000e-02 eta: 21:38:22 time: 0.2649 data_time: 0.0081 memory: 5828 grad_norm: 3.1063 loss: 2.6429 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6429 2023/06/04 23:20:37 - mmengine - INFO - Epoch(train) [37][1280/2569] lr: 4.0000e-02 eta: 21:38:17 time: 0.2718 data_time: 0.0082 memory: 5828 grad_norm: 3.0721 loss: 2.8693 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8693 2023/06/04 23:20:42 - mmengine - INFO - Epoch(train) [37][1300/2569] lr: 4.0000e-02 eta: 21:38:11 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.0997 loss: 2.3385 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3385 2023/06/04 23:20:47 - mmengine - INFO - Epoch(train) [37][1320/2569] lr: 4.0000e-02 eta: 21:38:06 time: 0.2632 data_time: 0.0085 memory: 5828 grad_norm: 3.0568 loss: 2.2859 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2859 2023/06/04 23:20:53 - mmengine - INFO - Epoch(train) [37][1340/2569] lr: 4.0000e-02 eta: 21:38:00 time: 0.2650 data_time: 0.0079 memory: 5828 grad_norm: 3.0429 loss: 2.5025 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5025 2023/06/04 23:20:58 - mmengine - INFO - Epoch(train) [37][1360/2569] lr: 4.0000e-02 eta: 21:37:55 time: 0.2596 data_time: 0.0082 memory: 5828 grad_norm: 3.0157 loss: 2.3875 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3875 2023/06/04 23:21:03 - mmengine - INFO - Epoch(train) [37][1380/2569] lr: 4.0000e-02 eta: 21:37:49 time: 0.2698 data_time: 0.0078 memory: 5828 grad_norm: 3.1148 loss: 2.4272 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4272 2023/06/04 23:21:09 - mmengine - INFO - Epoch(train) [37][1400/2569] lr: 4.0000e-02 eta: 21:37:44 time: 0.2686 data_time: 0.0082 memory: 5828 grad_norm: 3.0170 loss: 2.5283 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5283 2023/06/04 23:21:14 - mmengine - INFO - Epoch(train) [37][1420/2569] lr: 4.0000e-02 eta: 21:37:38 time: 0.2622 data_time: 0.0080 memory: 5828 grad_norm: 2.9813 loss: 2.9592 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9592 2023/06/04 23:21:19 - mmengine - INFO - Epoch(train) [37][1440/2569] lr: 4.0000e-02 eta: 21:37:33 time: 0.2667 data_time: 0.0083 memory: 5828 grad_norm: 3.0403 loss: 2.6371 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6371 2023/06/04 23:21:25 - mmengine - INFO - Epoch(train) [37][1460/2569] lr: 4.0000e-02 eta: 21:37:27 time: 0.2622 data_time: 0.0078 memory: 5828 grad_norm: 3.0890 loss: 2.6565 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6565 2023/06/04 23:21:30 - mmengine - INFO - Epoch(train) [37][1480/2569] lr: 4.0000e-02 eta: 21:37:22 time: 0.2673 data_time: 0.0081 memory: 5828 grad_norm: 3.0026 loss: 2.5721 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5721 2023/06/04 23:21:35 - mmengine - INFO - Epoch(train) [37][1500/2569] lr: 4.0000e-02 eta: 21:37:17 time: 0.2665 data_time: 0.0078 memory: 5828 grad_norm: 3.0778 loss: 2.3667 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3667 2023/06/04 23:21:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:21:41 - mmengine - INFO - Epoch(train) [37][1520/2569] lr: 4.0000e-02 eta: 21:37:12 time: 0.2809 data_time: 0.0081 memory: 5828 grad_norm: 3.0000 loss: 2.3841 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3841 2023/06/04 23:21:46 - mmengine - INFO - Epoch(train) [37][1540/2569] lr: 4.0000e-02 eta: 21:37:07 time: 0.2704 data_time: 0.0080 memory: 5828 grad_norm: 3.0659 loss: 2.5702 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5702 2023/06/04 23:21:51 - mmengine - INFO - Epoch(train) [37][1560/2569] lr: 4.0000e-02 eta: 21:37:01 time: 0.2608 data_time: 0.0075 memory: 5828 grad_norm: 3.0843 loss: 2.6604 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6604 2023/06/04 23:21:57 - mmengine - INFO - Epoch(train) [37][1580/2569] lr: 4.0000e-02 eta: 21:36:56 time: 0.2659 data_time: 0.0079 memory: 5828 grad_norm: 3.0688 loss: 2.3746 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3746 2023/06/04 23:22:02 - mmengine - INFO - Epoch(train) [37][1600/2569] lr: 4.0000e-02 eta: 21:36:50 time: 0.2648 data_time: 0.0077 memory: 5828 grad_norm: 2.9734 loss: 2.2716 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2716 2023/06/04 23:22:07 - mmengine - INFO - Epoch(train) [37][1620/2569] lr: 4.0000e-02 eta: 21:36:45 time: 0.2654 data_time: 0.0077 memory: 5828 grad_norm: 3.0704 loss: 2.7393 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7393 2023/06/04 23:22:13 - mmengine - INFO - Epoch(train) [37][1640/2569] lr: 4.0000e-02 eta: 21:36:40 time: 0.2659 data_time: 0.0080 memory: 5828 grad_norm: 3.0251 loss: 2.5829 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5829 2023/06/04 23:22:18 - mmengine - INFO - Epoch(train) [37][1660/2569] lr: 4.0000e-02 eta: 21:36:34 time: 0.2583 data_time: 0.0079 memory: 5828 grad_norm: 3.0783 loss: 2.4555 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4555 2023/06/04 23:22:23 - mmengine - INFO - Epoch(train) [37][1680/2569] lr: 4.0000e-02 eta: 21:36:29 time: 0.2701 data_time: 0.0080 memory: 5828 grad_norm: 3.0622 loss: 2.6590 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6590 2023/06/04 23:22:28 - mmengine - INFO - Epoch(train) [37][1700/2569] lr: 4.0000e-02 eta: 21:36:23 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 3.0514 loss: 2.8619 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8619 2023/06/04 23:22:34 - mmengine - INFO - Epoch(train) [37][1720/2569] lr: 4.0000e-02 eta: 21:36:17 time: 0.2638 data_time: 0.0082 memory: 5828 grad_norm: 3.0446 loss: 2.6631 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6631 2023/06/04 23:22:39 - mmengine - INFO - Epoch(train) [37][1740/2569] lr: 4.0000e-02 eta: 21:36:11 time: 0.2590 data_time: 0.0081 memory: 5828 grad_norm: 3.0669 loss: 2.6012 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6012 2023/06/04 23:22:44 - mmengine - INFO - Epoch(train) [37][1760/2569] lr: 4.0000e-02 eta: 21:36:06 time: 0.2611 data_time: 0.0082 memory: 5828 grad_norm: 3.1012 loss: 2.6243 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6243 2023/06/04 23:22:49 - mmengine - INFO - Epoch(train) [37][1780/2569] lr: 4.0000e-02 eta: 21:36:00 time: 0.2636 data_time: 0.0080 memory: 5828 grad_norm: 3.1035 loss: 2.6316 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6316 2023/06/04 23:22:55 - mmengine - INFO - Epoch(train) [37][1800/2569] lr: 4.0000e-02 eta: 21:35:54 time: 0.2584 data_time: 0.0080 memory: 5828 grad_norm: 3.0621 loss: 2.5850 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5850 2023/06/04 23:23:00 - mmengine - INFO - Epoch(train) [37][1820/2569] lr: 4.0000e-02 eta: 21:35:49 time: 0.2640 data_time: 0.0080 memory: 5828 grad_norm: 3.0432 loss: 2.3472 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3472 2023/06/04 23:23:05 - mmengine - INFO - Epoch(train) [37][1840/2569] lr: 4.0000e-02 eta: 21:35:43 time: 0.2679 data_time: 0.0075 memory: 5828 grad_norm: 3.0114 loss: 2.6158 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6158 2023/06/04 23:23:11 - mmengine - INFO - Epoch(train) [37][1860/2569] lr: 4.0000e-02 eta: 21:35:38 time: 0.2621 data_time: 0.0077 memory: 5828 grad_norm: 3.0049 loss: 2.6275 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6275 2023/06/04 23:23:16 - mmengine - INFO - Epoch(train) [37][1880/2569] lr: 4.0000e-02 eta: 21:35:32 time: 0.2640 data_time: 0.0081 memory: 5828 grad_norm: 2.9877 loss: 2.4878 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4878 2023/06/04 23:23:21 - mmengine - INFO - Epoch(train) [37][1900/2569] lr: 4.0000e-02 eta: 21:35:26 time: 0.2606 data_time: 0.0078 memory: 5828 grad_norm: 3.0814 loss: 2.5543 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5543 2023/06/04 23:23:27 - mmengine - INFO - Epoch(train) [37][1920/2569] lr: 4.0000e-02 eta: 21:35:21 time: 0.2747 data_time: 0.0090 memory: 5828 grad_norm: 3.0396 loss: 2.4440 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4440 2023/06/04 23:23:32 - mmengine - INFO - Epoch(train) [37][1940/2569] lr: 4.0000e-02 eta: 21:35:16 time: 0.2591 data_time: 0.0080 memory: 5828 grad_norm: 3.0706 loss: 2.4926 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4926 2023/06/04 23:23:37 - mmengine - INFO - Epoch(train) [37][1960/2569] lr: 4.0000e-02 eta: 21:35:10 time: 0.2656 data_time: 0.0080 memory: 5828 grad_norm: 3.0566 loss: 2.4858 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4858 2023/06/04 23:23:42 - mmengine - INFO - Epoch(train) [37][1980/2569] lr: 4.0000e-02 eta: 21:35:04 time: 0.2592 data_time: 0.0081 memory: 5828 grad_norm: 3.0548 loss: 2.9441 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.9441 2023/06/04 23:23:48 - mmengine - INFO - Epoch(train) [37][2000/2569] lr: 4.0000e-02 eta: 21:34:59 time: 0.2646 data_time: 0.0077 memory: 5828 grad_norm: 3.0806 loss: 2.4613 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4613 2023/06/04 23:23:53 - mmengine - INFO - Epoch(train) [37][2020/2569] lr: 4.0000e-02 eta: 21:34:53 time: 0.2622 data_time: 0.0078 memory: 5828 grad_norm: 3.0485 loss: 2.3187 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3187 2023/06/04 23:23:58 - mmengine - INFO - Epoch(train) [37][2040/2569] lr: 4.0000e-02 eta: 21:34:48 time: 0.2639 data_time: 0.0080 memory: 5828 grad_norm: 3.0808 loss: 2.3591 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3591 2023/06/04 23:24:03 - mmengine - INFO - Epoch(train) [37][2060/2569] lr: 4.0000e-02 eta: 21:34:42 time: 0.2634 data_time: 0.0078 memory: 5828 grad_norm: 3.0732 loss: 2.4988 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4988 2023/06/04 23:24:08 - mmengine - INFO - Epoch(train) [37][2080/2569] lr: 4.0000e-02 eta: 21:34:36 time: 0.2587 data_time: 0.0082 memory: 5828 grad_norm: 3.1285 loss: 2.7889 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7889 2023/06/04 23:24:14 - mmengine - INFO - Epoch(train) [37][2100/2569] lr: 4.0000e-02 eta: 21:34:31 time: 0.2648 data_time: 0.0082 memory: 5828 grad_norm: 3.0500 loss: 2.6111 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6111 2023/06/04 23:24:19 - mmengine - INFO - Epoch(train) [37][2120/2569] lr: 4.0000e-02 eta: 21:34:25 time: 0.2626 data_time: 0.0080 memory: 5828 grad_norm: 3.0907 loss: 2.3993 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3993 2023/06/04 23:24:24 - mmengine - INFO - Epoch(train) [37][2140/2569] lr: 4.0000e-02 eta: 21:34:20 time: 0.2646 data_time: 0.0078 memory: 5828 grad_norm: 3.0810 loss: 2.7776 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7776 2023/06/04 23:24:30 - mmengine - INFO - Epoch(train) [37][2160/2569] lr: 4.0000e-02 eta: 21:34:15 time: 0.2792 data_time: 0.0076 memory: 5828 grad_norm: 3.0657 loss: 2.3801 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3801 2023/06/04 23:24:35 - mmengine - INFO - Epoch(train) [37][2180/2569] lr: 4.0000e-02 eta: 21:34:10 time: 0.2643 data_time: 0.0085 memory: 5828 grad_norm: 3.0292 loss: 2.7546 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7546 2023/06/04 23:24:41 - mmengine - INFO - Epoch(train) [37][2200/2569] lr: 4.0000e-02 eta: 21:34:04 time: 0.2676 data_time: 0.0079 memory: 5828 grad_norm: 3.0529 loss: 2.5650 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5650 2023/06/04 23:24:46 - mmengine - INFO - Epoch(train) [37][2220/2569] lr: 4.0000e-02 eta: 21:33:59 time: 0.2655 data_time: 0.0077 memory: 5828 grad_norm: 2.9888 loss: 2.6542 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6542 2023/06/04 23:24:51 - mmengine - INFO - Epoch(train) [37][2240/2569] lr: 4.0000e-02 eta: 21:33:53 time: 0.2632 data_time: 0.0078 memory: 5828 grad_norm: 2.9876 loss: 2.3557 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3557 2023/06/04 23:24:56 - mmengine - INFO - Epoch(train) [37][2260/2569] lr: 4.0000e-02 eta: 21:33:47 time: 0.2594 data_time: 0.0083 memory: 5828 grad_norm: 2.9946 loss: 2.8057 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8057 2023/06/04 23:25:02 - mmengine - INFO - Epoch(train) [37][2280/2569] lr: 4.0000e-02 eta: 21:33:42 time: 0.2594 data_time: 0.0081 memory: 5828 grad_norm: 3.0189 loss: 2.5093 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5093 2023/06/04 23:25:07 - mmengine - INFO - Epoch(train) [37][2300/2569] lr: 4.0000e-02 eta: 21:33:36 time: 0.2606 data_time: 0.0076 memory: 5828 grad_norm: 3.0582 loss: 2.2442 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2442 2023/06/04 23:25:12 - mmengine - INFO - Epoch(train) [37][2320/2569] lr: 4.0000e-02 eta: 21:33:30 time: 0.2604 data_time: 0.0080 memory: 5828 grad_norm: 3.0581 loss: 2.3892 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3892 2023/06/04 23:25:17 - mmengine - INFO - Epoch(train) [37][2340/2569] lr: 4.0000e-02 eta: 21:33:25 time: 0.2648 data_time: 0.0079 memory: 5828 grad_norm: 3.0840 loss: 2.7600 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7600 2023/06/04 23:25:23 - mmengine - INFO - Epoch(train) [37][2360/2569] lr: 4.0000e-02 eta: 21:33:19 time: 0.2625 data_time: 0.0077 memory: 5828 grad_norm: 3.0553 loss: 2.4198 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4198 2023/06/04 23:25:28 - mmengine - INFO - Epoch(train) [37][2380/2569] lr: 4.0000e-02 eta: 21:33:13 time: 0.2649 data_time: 0.0078 memory: 5828 grad_norm: 3.0830 loss: 2.6945 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6945 2023/06/04 23:25:33 - mmengine - INFO - Epoch(train) [37][2400/2569] lr: 4.0000e-02 eta: 21:33:08 time: 0.2700 data_time: 0.0082 memory: 5828 grad_norm: 3.0709 loss: 2.3327 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3327 2023/06/04 23:25:39 - mmengine - INFO - Epoch(train) [37][2420/2569] lr: 4.0000e-02 eta: 21:33:03 time: 0.2653 data_time: 0.0077 memory: 5828 grad_norm: 3.0976 loss: 2.1614 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1614 2023/06/04 23:25:44 - mmengine - INFO - Epoch(train) [37][2440/2569] lr: 4.0000e-02 eta: 21:32:58 time: 0.2685 data_time: 0.0081 memory: 5828 grad_norm: 3.0402 loss: 2.7207 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7207 2023/06/04 23:25:49 - mmengine - INFO - Epoch(train) [37][2460/2569] lr: 4.0000e-02 eta: 21:32:52 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 3.0225 loss: 2.6476 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.6476 2023/06/04 23:25:54 - mmengine - INFO - Epoch(train) [37][2480/2569] lr: 4.0000e-02 eta: 21:32:46 time: 0.2629 data_time: 0.0078 memory: 5828 grad_norm: 2.9857 loss: 2.6173 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6173 2023/06/04 23:26:00 - mmengine - INFO - Epoch(train) [37][2500/2569] lr: 4.0000e-02 eta: 21:32:41 time: 0.2604 data_time: 0.0077 memory: 5828 grad_norm: 3.0707 loss: 2.6631 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6631 2023/06/04 23:26:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:26:05 - mmengine - INFO - Epoch(train) [37][2520/2569] lr: 4.0000e-02 eta: 21:32:35 time: 0.2667 data_time: 0.0080 memory: 5828 grad_norm: 3.0652 loss: 2.6037 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6037 2023/06/04 23:26:10 - mmengine - INFO - Epoch(train) [37][2540/2569] lr: 4.0000e-02 eta: 21:32:30 time: 0.2597 data_time: 0.0075 memory: 5828 grad_norm: 3.0721 loss: 2.4015 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4015 2023/06/04 23:26:15 - mmengine - INFO - Epoch(train) [37][2560/2569] lr: 4.0000e-02 eta: 21:32:24 time: 0.2600 data_time: 0.0076 memory: 5828 grad_norm: 3.0495 loss: 2.4557 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4557 2023/06/04 23:26:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:26:18 - mmengine - INFO - Epoch(train) [37][2569/2569] lr: 4.0000e-02 eta: 21:32:21 time: 0.2501 data_time: 0.0074 memory: 5828 grad_norm: 3.0682 loss: 2.5417 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.5417 2023/06/04 23:26:24 - mmengine - INFO - Epoch(train) [38][ 20/2569] lr: 4.0000e-02 eta: 21:32:20 time: 0.3417 data_time: 0.0768 memory: 5828 grad_norm: 3.0768 loss: 2.6686 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6686 2023/06/04 23:26:30 - mmengine - INFO - Epoch(train) [38][ 40/2569] lr: 4.0000e-02 eta: 21:32:14 time: 0.2618 data_time: 0.0082 memory: 5828 grad_norm: 3.1447 loss: 2.5169 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5169 2023/06/04 23:26:35 - mmengine - INFO - Epoch(train) [38][ 60/2569] lr: 4.0000e-02 eta: 21:32:09 time: 0.2652 data_time: 0.0080 memory: 5828 grad_norm: 3.0162 loss: 2.3661 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3661 2023/06/04 23:26:40 - mmengine - INFO - Epoch(train) [38][ 80/2569] lr: 4.0000e-02 eta: 21:32:03 time: 0.2647 data_time: 0.0080 memory: 5828 grad_norm: 3.0265 loss: 2.4757 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4757 2023/06/04 23:26:46 - mmengine - INFO - Epoch(train) [38][ 100/2569] lr: 4.0000e-02 eta: 21:31:58 time: 0.2690 data_time: 0.0079 memory: 5828 grad_norm: 3.0128 loss: 2.4139 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4139 2023/06/04 23:26:51 - mmengine - INFO - Epoch(train) [38][ 120/2569] lr: 4.0000e-02 eta: 21:31:53 time: 0.2663 data_time: 0.0084 memory: 5828 grad_norm: 3.0943 loss: 2.7768 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7768 2023/06/04 23:26:56 - mmengine - INFO - Epoch(train) [38][ 140/2569] lr: 4.0000e-02 eta: 21:31:48 time: 0.2704 data_time: 0.0082 memory: 5828 grad_norm: 3.0799 loss: 2.6611 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6611 2023/06/04 23:27:02 - mmengine - INFO - Epoch(train) [38][ 160/2569] lr: 4.0000e-02 eta: 21:31:42 time: 0.2658 data_time: 0.0082 memory: 5828 grad_norm: 3.0352 loss: 2.3755 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3755 2023/06/04 23:27:07 - mmengine - INFO - Epoch(train) [38][ 180/2569] lr: 4.0000e-02 eta: 21:31:37 time: 0.2626 data_time: 0.0078 memory: 5828 grad_norm: 3.0420 loss: 2.8230 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8230 2023/06/04 23:27:12 - mmengine - INFO - Epoch(train) [38][ 200/2569] lr: 4.0000e-02 eta: 21:31:31 time: 0.2662 data_time: 0.0080 memory: 5828 grad_norm: 3.0408 loss: 2.4119 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4119 2023/06/04 23:27:18 - mmengine - INFO - Epoch(train) [38][ 220/2569] lr: 4.0000e-02 eta: 21:31:26 time: 0.2695 data_time: 0.0078 memory: 5828 grad_norm: 3.0610 loss: 2.4937 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4937 2023/06/04 23:27:23 - mmengine - INFO - Epoch(train) [38][ 240/2569] lr: 4.0000e-02 eta: 21:31:20 time: 0.2569 data_time: 0.0076 memory: 5828 grad_norm: 3.0537 loss: 2.7715 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7715 2023/06/04 23:27:28 - mmengine - INFO - Epoch(train) [38][ 260/2569] lr: 4.0000e-02 eta: 21:31:15 time: 0.2681 data_time: 0.0083 memory: 5828 grad_norm: 3.0960 loss: 2.9046 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9046 2023/06/04 23:27:33 - mmengine - INFO - Epoch(train) [38][ 280/2569] lr: 4.0000e-02 eta: 21:31:09 time: 0.2610 data_time: 0.0078 memory: 5828 grad_norm: 3.0189 loss: 2.5792 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5792 2023/06/04 23:27:39 - mmengine - INFO - Epoch(train) [38][ 300/2569] lr: 4.0000e-02 eta: 21:31:04 time: 0.2659 data_time: 0.0077 memory: 5828 grad_norm: 3.0600 loss: 2.4255 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4255 2023/06/04 23:27:44 - mmengine - INFO - Epoch(train) [38][ 320/2569] lr: 4.0000e-02 eta: 21:30:58 time: 0.2673 data_time: 0.0095 memory: 5828 grad_norm: 3.0595 loss: 2.5879 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5879 2023/06/04 23:27:50 - mmengine - INFO - Epoch(train) [38][ 340/2569] lr: 4.0000e-02 eta: 21:30:53 time: 0.2753 data_time: 0.0086 memory: 5828 grad_norm: 3.1126 loss: 2.6744 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6744 2023/06/04 23:27:55 - mmengine - INFO - Epoch(train) [38][ 360/2569] lr: 4.0000e-02 eta: 21:30:48 time: 0.2597 data_time: 0.0085 memory: 5828 grad_norm: 3.0633 loss: 2.4015 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4015 2023/06/04 23:28:00 - mmengine - INFO - Epoch(train) [38][ 380/2569] lr: 4.0000e-02 eta: 21:30:42 time: 0.2680 data_time: 0.0080 memory: 5828 grad_norm: 3.0343 loss: 2.5895 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5895 2023/06/04 23:28:06 - mmengine - INFO - Epoch(train) [38][ 400/2569] lr: 4.0000e-02 eta: 21:30:37 time: 0.2708 data_time: 0.0085 memory: 5828 grad_norm: 3.0914 loss: 2.1775 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1775 2023/06/04 23:28:11 - mmengine - INFO - Epoch(train) [38][ 420/2569] lr: 4.0000e-02 eta: 21:30:31 time: 0.2584 data_time: 0.0082 memory: 5828 grad_norm: 3.0748 loss: 2.3433 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3433 2023/06/04 23:28:16 - mmengine - INFO - Epoch(train) [38][ 440/2569] lr: 4.0000e-02 eta: 21:30:26 time: 0.2633 data_time: 0.0083 memory: 5828 grad_norm: 3.0316 loss: 2.7532 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7532 2023/06/04 23:28:21 - mmengine - INFO - Epoch(train) [38][ 460/2569] lr: 4.0000e-02 eta: 21:30:20 time: 0.2614 data_time: 0.0080 memory: 5828 grad_norm: 3.0989 loss: 2.3609 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3609 2023/06/04 23:28:27 - mmengine - INFO - Epoch(train) [38][ 480/2569] lr: 4.0000e-02 eta: 21:30:14 time: 0.2581 data_time: 0.0076 memory: 5828 grad_norm: 3.1160 loss: 2.5117 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5117 2023/06/04 23:28:32 - mmengine - INFO - Epoch(train) [38][ 500/2569] lr: 4.0000e-02 eta: 21:30:09 time: 0.2631 data_time: 0.0077 memory: 5828 grad_norm: 3.0951 loss: 2.2888 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2888 2023/06/04 23:28:37 - mmengine - INFO - Epoch(train) [38][ 520/2569] lr: 4.0000e-02 eta: 21:30:04 time: 0.2730 data_time: 0.0079 memory: 5828 grad_norm: 3.1004 loss: 2.3309 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3309 2023/06/04 23:28:43 - mmengine - INFO - Epoch(train) [38][ 540/2569] lr: 4.0000e-02 eta: 21:29:59 time: 0.2708 data_time: 0.0079 memory: 5828 grad_norm: 3.0620 loss: 2.7076 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7076 2023/06/04 23:28:48 - mmengine - INFO - Epoch(train) [38][ 560/2569] lr: 4.0000e-02 eta: 21:29:54 time: 0.2727 data_time: 0.0076 memory: 5828 grad_norm: 3.0198 loss: 2.7699 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7699 2023/06/04 23:28:53 - mmengine - INFO - Epoch(train) [38][ 580/2569] lr: 4.0000e-02 eta: 21:29:48 time: 0.2686 data_time: 0.0079 memory: 5828 grad_norm: 3.1506 loss: 2.6082 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6082 2023/06/04 23:28:59 - mmengine - INFO - Epoch(train) [38][ 600/2569] lr: 4.0000e-02 eta: 21:29:43 time: 0.2644 data_time: 0.0080 memory: 5828 grad_norm: 3.0736 loss: 2.8600 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8600 2023/06/04 23:29:04 - mmengine - INFO - Epoch(train) [38][ 620/2569] lr: 4.0000e-02 eta: 21:29:38 time: 0.2757 data_time: 0.0080 memory: 5828 grad_norm: 3.1041 loss: 2.6481 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6481 2023/06/04 23:29:10 - mmengine - INFO - Epoch(train) [38][ 640/2569] lr: 4.0000e-02 eta: 21:29:33 time: 0.2657 data_time: 0.0083 memory: 5828 grad_norm: 3.0691 loss: 2.4966 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4966 2023/06/04 23:29:15 - mmengine - INFO - Epoch(train) [38][ 660/2569] lr: 4.0000e-02 eta: 21:29:27 time: 0.2700 data_time: 0.0085 memory: 5828 grad_norm: 3.0460 loss: 2.6971 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.6971 2023/06/04 23:29:20 - mmengine - INFO - Epoch(train) [38][ 680/2569] lr: 4.0000e-02 eta: 21:29:22 time: 0.2709 data_time: 0.0083 memory: 5828 grad_norm: 3.1662 loss: 2.4948 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4948 2023/06/04 23:29:26 - mmengine - INFO - Epoch(train) [38][ 700/2569] lr: 4.0000e-02 eta: 21:29:17 time: 0.2623 data_time: 0.0081 memory: 5828 grad_norm: 3.0302 loss: 2.8655 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8655 2023/06/04 23:29:31 - mmengine - INFO - Epoch(train) [38][ 720/2569] lr: 4.0000e-02 eta: 21:29:12 time: 0.2718 data_time: 0.0084 memory: 5828 grad_norm: 3.0661 loss: 2.5478 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5478 2023/06/04 23:29:36 - mmengine - INFO - Epoch(train) [38][ 740/2569] lr: 4.0000e-02 eta: 21:29:06 time: 0.2599 data_time: 0.0078 memory: 5828 grad_norm: 3.1199 loss: 2.5280 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5280 2023/06/04 23:29:42 - mmengine - INFO - Epoch(train) [38][ 760/2569] lr: 4.0000e-02 eta: 21:29:00 time: 0.2619 data_time: 0.0078 memory: 5828 grad_norm: 3.1827 loss: 2.6284 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6284 2023/06/04 23:29:47 - mmengine - INFO - Epoch(train) [38][ 780/2569] lr: 4.0000e-02 eta: 21:28:54 time: 0.2594 data_time: 0.0080 memory: 5828 grad_norm: 3.0354 loss: 2.6021 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6021 2023/06/04 23:29:52 - mmengine - INFO - Epoch(train) [38][ 800/2569] lr: 4.0000e-02 eta: 21:28:49 time: 0.2625 data_time: 0.0076 memory: 5828 grad_norm: 3.0920 loss: 2.4878 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4878 2023/06/04 23:29:57 - mmengine - INFO - Epoch(train) [38][ 820/2569] lr: 4.0000e-02 eta: 21:28:43 time: 0.2601 data_time: 0.0081 memory: 5828 grad_norm: 3.0929 loss: 2.9843 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9843 2023/06/04 23:30:03 - mmengine - INFO - Epoch(train) [38][ 840/2569] lr: 4.0000e-02 eta: 21:28:37 time: 0.2632 data_time: 0.0082 memory: 5828 grad_norm: 3.0319 loss: 2.2024 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2024 2023/06/04 23:30:08 - mmengine - INFO - Epoch(train) [38][ 860/2569] lr: 4.0000e-02 eta: 21:28:32 time: 0.2604 data_time: 0.0081 memory: 5828 grad_norm: 2.9571 loss: 2.4374 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4374 2023/06/04 23:30:13 - mmengine - INFO - Epoch(train) [38][ 880/2569] lr: 4.0000e-02 eta: 21:28:26 time: 0.2624 data_time: 0.0080 memory: 5828 grad_norm: 3.0002 loss: 2.6561 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6561 2023/06/04 23:30:18 - mmengine - INFO - Epoch(train) [38][ 900/2569] lr: 4.0000e-02 eta: 21:28:20 time: 0.2598 data_time: 0.0079 memory: 5828 grad_norm: 3.1009 loss: 2.5606 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5606 2023/06/04 23:30:23 - mmengine - INFO - Epoch(train) [38][ 920/2569] lr: 4.0000e-02 eta: 21:28:14 time: 0.2599 data_time: 0.0079 memory: 5828 grad_norm: 3.0395 loss: 2.5755 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5755 2023/06/04 23:30:29 - mmengine - INFO - Epoch(train) [38][ 940/2569] lr: 4.0000e-02 eta: 21:28:09 time: 0.2743 data_time: 0.0080 memory: 5828 grad_norm: 3.0765 loss: 2.7406 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7406 2023/06/04 23:30:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:30:34 - mmengine - INFO - Epoch(train) [38][ 960/2569] lr: 4.0000e-02 eta: 21:28:04 time: 0.2607 data_time: 0.0083 memory: 5828 grad_norm: 3.0892 loss: 2.5252 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5252 2023/06/04 23:30:39 - mmengine - INFO - Epoch(train) [38][ 980/2569] lr: 4.0000e-02 eta: 21:27:58 time: 0.2627 data_time: 0.0084 memory: 5828 grad_norm: 3.0414 loss: 2.4596 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4596 2023/06/04 23:30:45 - mmengine - INFO - Epoch(train) [38][1000/2569] lr: 4.0000e-02 eta: 21:27:53 time: 0.2716 data_time: 0.0085 memory: 5828 grad_norm: 3.1631 loss: 2.6826 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6826 2023/06/04 23:30:50 - mmengine - INFO - Epoch(train) [38][1020/2569] lr: 4.0000e-02 eta: 21:27:48 time: 0.2700 data_time: 0.0078 memory: 5828 grad_norm: 3.0399 loss: 2.2799 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2799 2023/06/04 23:30:56 - mmengine - INFO - Epoch(train) [38][1040/2569] lr: 4.0000e-02 eta: 21:27:43 time: 0.2786 data_time: 0.0083 memory: 5828 grad_norm: 3.0744 loss: 2.7107 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7107 2023/06/04 23:31:01 - mmengine - INFO - Epoch(train) [38][1060/2569] lr: 4.0000e-02 eta: 21:27:38 time: 0.2644 data_time: 0.0084 memory: 5828 grad_norm: 2.9962 loss: 2.8374 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8374 2023/06/04 23:31:06 - mmengine - INFO - Epoch(train) [38][1080/2569] lr: 4.0000e-02 eta: 21:27:32 time: 0.2631 data_time: 0.0076 memory: 5828 grad_norm: 3.0848 loss: 2.5320 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5320 2023/06/04 23:31:11 - mmengine - INFO - Epoch(train) [38][1100/2569] lr: 4.0000e-02 eta: 21:27:26 time: 0.2583 data_time: 0.0081 memory: 5828 grad_norm: 3.0850 loss: 2.5221 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5221 2023/06/04 23:31:17 - mmengine - INFO - Epoch(train) [38][1120/2569] lr: 4.0000e-02 eta: 21:27:20 time: 0.2580 data_time: 0.0084 memory: 5828 grad_norm: 3.1227 loss: 2.6493 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6493 2023/06/04 23:31:22 - mmengine - INFO - Epoch(train) [38][1140/2569] lr: 4.0000e-02 eta: 21:27:15 time: 0.2621 data_time: 0.0080 memory: 5828 grad_norm: 3.0571 loss: 2.6148 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6148 2023/06/04 23:31:27 - mmengine - INFO - Epoch(train) [38][1160/2569] lr: 4.0000e-02 eta: 21:27:09 time: 0.2567 data_time: 0.0080 memory: 5828 grad_norm: 3.1075 loss: 2.3798 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.3798 2023/06/04 23:31:32 - mmengine - INFO - Epoch(train) [38][1180/2569] lr: 4.0000e-02 eta: 21:27:03 time: 0.2626 data_time: 0.0078 memory: 5828 grad_norm: 3.0571 loss: 2.7291 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7291 2023/06/04 23:31:38 - mmengine - INFO - Epoch(train) [38][1200/2569] lr: 4.0000e-02 eta: 21:26:58 time: 0.2658 data_time: 0.0081 memory: 5828 grad_norm: 3.0932 loss: 2.9630 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9630 2023/06/04 23:31:43 - mmengine - INFO - Epoch(train) [38][1220/2569] lr: 4.0000e-02 eta: 21:26:52 time: 0.2680 data_time: 0.0079 memory: 5828 grad_norm: 3.0174 loss: 2.2855 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2855 2023/06/04 23:31:48 - mmengine - INFO - Epoch(train) [38][1240/2569] lr: 4.0000e-02 eta: 21:26:47 time: 0.2620 data_time: 0.0080 memory: 5828 grad_norm: 3.0828 loss: 2.7392 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7392 2023/06/04 23:31:53 - mmengine - INFO - Epoch(train) [38][1260/2569] lr: 4.0000e-02 eta: 21:26:41 time: 0.2601 data_time: 0.0081 memory: 5828 grad_norm: 3.0923 loss: 2.3006 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3006 2023/06/04 23:31:59 - mmengine - INFO - Epoch(train) [38][1280/2569] lr: 4.0000e-02 eta: 21:26:35 time: 0.2587 data_time: 0.0081 memory: 5828 grad_norm: 3.1031 loss: 2.6034 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6034 2023/06/04 23:32:04 - mmengine - INFO - Epoch(train) [38][1300/2569] lr: 4.0000e-02 eta: 21:26:29 time: 0.2596 data_time: 0.0079 memory: 5828 grad_norm: 3.0856 loss: 2.4191 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4191 2023/06/04 23:32:09 - mmengine - INFO - Epoch(train) [38][1320/2569] lr: 4.0000e-02 eta: 21:26:24 time: 0.2577 data_time: 0.0073 memory: 5828 grad_norm: 3.1037 loss: 2.7340 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7340 2023/06/04 23:32:14 - mmengine - INFO - Epoch(train) [38][1340/2569] lr: 4.0000e-02 eta: 21:26:18 time: 0.2696 data_time: 0.0082 memory: 5828 grad_norm: 3.0831 loss: 2.5514 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5514 2023/06/04 23:32:20 - mmengine - INFO - Epoch(train) [38][1360/2569] lr: 4.0000e-02 eta: 21:26:12 time: 0.2588 data_time: 0.0080 memory: 5828 grad_norm: 3.0588 loss: 2.5529 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5529 2023/06/04 23:32:25 - mmengine - INFO - Epoch(train) [38][1380/2569] lr: 4.0000e-02 eta: 21:26:07 time: 0.2626 data_time: 0.0077 memory: 5828 grad_norm: 3.0288 loss: 2.3017 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3017 2023/06/04 23:32:30 - mmengine - INFO - Epoch(train) [38][1400/2569] lr: 4.0000e-02 eta: 21:26:01 time: 0.2625 data_time: 0.0084 memory: 5828 grad_norm: 3.0345 loss: 2.6528 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6528 2023/06/04 23:32:35 - mmengine - INFO - Epoch(train) [38][1420/2569] lr: 4.0000e-02 eta: 21:25:56 time: 0.2619 data_time: 0.0082 memory: 5828 grad_norm: 3.1111 loss: 2.3093 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3093 2023/06/04 23:32:41 - mmengine - INFO - Epoch(train) [38][1440/2569] lr: 4.0000e-02 eta: 21:25:50 time: 0.2611 data_time: 0.0078 memory: 5828 grad_norm: 3.0973 loss: 2.7759 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7759 2023/06/04 23:32:46 - mmengine - INFO - Epoch(train) [38][1460/2569] lr: 4.0000e-02 eta: 21:25:44 time: 0.2599 data_time: 0.0081 memory: 5828 grad_norm: 3.0181 loss: 2.4085 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4085 2023/06/04 23:32:51 - mmengine - INFO - Epoch(train) [38][1480/2569] lr: 4.0000e-02 eta: 21:25:38 time: 0.2566 data_time: 0.0081 memory: 5828 grad_norm: 3.1080 loss: 2.6209 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6209 2023/06/04 23:32:56 - mmengine - INFO - Epoch(train) [38][1500/2569] lr: 4.0000e-02 eta: 21:25:33 time: 0.2650 data_time: 0.0079 memory: 5828 grad_norm: 3.0114 loss: 2.8269 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8269 2023/06/04 23:33:01 - mmengine - INFO - Epoch(train) [38][1520/2569] lr: 4.0000e-02 eta: 21:25:27 time: 0.2627 data_time: 0.0079 memory: 5828 grad_norm: 3.0880 loss: 2.4669 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4669 2023/06/04 23:33:07 - mmengine - INFO - Epoch(train) [38][1540/2569] lr: 4.0000e-02 eta: 21:25:21 time: 0.2621 data_time: 0.0079 memory: 5828 grad_norm: 3.0333 loss: 2.3215 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3215 2023/06/04 23:33:12 - mmengine - INFO - Epoch(train) [38][1560/2569] lr: 4.0000e-02 eta: 21:25:16 time: 0.2637 data_time: 0.0078 memory: 5828 grad_norm: 3.1017 loss: 2.5089 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5089 2023/06/04 23:33:17 - mmengine - INFO - Epoch(train) [38][1580/2569] lr: 4.0000e-02 eta: 21:25:10 time: 0.2567 data_time: 0.0080 memory: 5828 grad_norm: 3.0686 loss: 2.5248 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5248 2023/06/04 23:33:23 - mmengine - INFO - Epoch(train) [38][1600/2569] lr: 4.0000e-02 eta: 21:25:05 time: 0.2802 data_time: 0.0074 memory: 5828 grad_norm: 3.0046 loss: 2.4385 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4385 2023/06/04 23:33:28 - mmengine - INFO - Epoch(train) [38][1620/2569] lr: 4.0000e-02 eta: 21:24:59 time: 0.2572 data_time: 0.0083 memory: 5828 grad_norm: 3.0234 loss: 2.4116 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4116 2023/06/04 23:33:33 - mmengine - INFO - Epoch(train) [38][1640/2569] lr: 4.0000e-02 eta: 21:24:54 time: 0.2634 data_time: 0.0082 memory: 5828 grad_norm: 2.9994 loss: 2.4835 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4835 2023/06/04 23:33:38 - mmengine - INFO - Epoch(train) [38][1660/2569] lr: 4.0000e-02 eta: 21:24:48 time: 0.2591 data_time: 0.0078 memory: 5828 grad_norm: 3.0853 loss: 2.4741 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4741 2023/06/04 23:33:44 - mmengine - INFO - Epoch(train) [38][1680/2569] lr: 4.0000e-02 eta: 21:24:42 time: 0.2629 data_time: 0.0081 memory: 5828 grad_norm: 3.0313 loss: 2.6822 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6822 2023/06/04 23:33:49 - mmengine - INFO - Epoch(train) [38][1700/2569] lr: 4.0000e-02 eta: 21:24:37 time: 0.2627 data_time: 0.0081 memory: 5828 grad_norm: 3.0814 loss: 2.7773 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7773 2023/06/04 23:33:54 - mmengine - INFO - Epoch(train) [38][1720/2569] lr: 4.0000e-02 eta: 21:24:31 time: 0.2648 data_time: 0.0080 memory: 5828 grad_norm: 2.9572 loss: 2.5062 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5062 2023/06/04 23:33:59 - mmengine - INFO - Epoch(train) [38][1740/2569] lr: 4.0000e-02 eta: 21:24:26 time: 0.2620 data_time: 0.0080 memory: 5828 grad_norm: 3.1149 loss: 2.5618 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5618 2023/06/04 23:34:05 - mmengine - INFO - Epoch(train) [38][1760/2569] lr: 4.0000e-02 eta: 21:24:20 time: 0.2635 data_time: 0.0080 memory: 5828 grad_norm: 2.9913 loss: 2.6539 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6539 2023/06/04 23:34:10 - mmengine - INFO - Epoch(train) [38][1780/2569] lr: 4.0000e-02 eta: 21:24:15 time: 0.2740 data_time: 0.0078 memory: 5828 grad_norm: 3.0107 loss: 2.5352 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5352 2023/06/04 23:34:16 - mmengine - INFO - Epoch(train) [38][1800/2569] lr: 4.0000e-02 eta: 21:24:10 time: 0.2689 data_time: 0.0079 memory: 5828 grad_norm: 3.0540 loss: 2.6114 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6114 2023/06/04 23:34:21 - mmengine - INFO - Epoch(train) [38][1820/2569] lr: 4.0000e-02 eta: 21:24:04 time: 0.2577 data_time: 0.0079 memory: 5828 grad_norm: 3.0911 loss: 2.6457 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6457 2023/06/04 23:34:26 - mmengine - INFO - Epoch(train) [38][1840/2569] lr: 4.0000e-02 eta: 21:23:59 time: 0.2627 data_time: 0.0085 memory: 5828 grad_norm: 3.0404 loss: 2.6044 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6044 2023/06/04 23:34:31 - mmengine - INFO - Epoch(train) [38][1860/2569] lr: 4.0000e-02 eta: 21:23:53 time: 0.2627 data_time: 0.0080 memory: 5828 grad_norm: 3.0668 loss: 2.5416 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5416 2023/06/04 23:34:36 - mmengine - INFO - Epoch(train) [38][1880/2569] lr: 4.0000e-02 eta: 21:23:47 time: 0.2580 data_time: 0.0078 memory: 5828 grad_norm: 3.0751 loss: 2.4204 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4204 2023/06/04 23:34:42 - mmengine - INFO - Epoch(train) [38][1900/2569] lr: 4.0000e-02 eta: 21:23:41 time: 0.2592 data_time: 0.0079 memory: 5828 grad_norm: 3.0079 loss: 2.5472 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5472 2023/06/04 23:34:47 - mmengine - INFO - Epoch(train) [38][1920/2569] lr: 4.0000e-02 eta: 21:23:36 time: 0.2623 data_time: 0.0079 memory: 5828 grad_norm: 3.0515 loss: 2.5985 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5985 2023/06/04 23:34:52 - mmengine - INFO - Epoch(train) [38][1940/2569] lr: 4.0000e-02 eta: 21:23:30 time: 0.2709 data_time: 0.0082 memory: 5828 grad_norm: 2.9999 loss: 2.9450 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9450 2023/06/04 23:34:54 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:34:57 - mmengine - INFO - Epoch(train) [38][1960/2569] lr: 4.0000e-02 eta: 21:23:25 time: 0.2609 data_time: 0.0084 memory: 5828 grad_norm: 3.0844 loss: 3.0316 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.0316 2023/06/04 23:35:03 - mmengine - INFO - Epoch(train) [38][1980/2569] lr: 4.0000e-02 eta: 21:23:20 time: 0.2765 data_time: 0.0076 memory: 5828 grad_norm: 3.0338 loss: 2.6534 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6534 2023/06/04 23:35:08 - mmengine - INFO - Epoch(train) [38][2000/2569] lr: 4.0000e-02 eta: 21:23:14 time: 0.2590 data_time: 0.0083 memory: 5828 grad_norm: 3.1440 loss: 2.3449 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3449 2023/06/04 23:35:14 - mmengine - INFO - Epoch(train) [38][2020/2569] lr: 4.0000e-02 eta: 21:23:09 time: 0.2750 data_time: 0.0080 memory: 5828 grad_norm: 3.0823 loss: 2.5391 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5391 2023/06/04 23:35:19 - mmengine - INFO - Epoch(train) [38][2040/2569] lr: 4.0000e-02 eta: 21:23:04 time: 0.2595 data_time: 0.0081 memory: 5828 grad_norm: 3.1078 loss: 2.3362 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3362 2023/06/04 23:35:24 - mmengine - INFO - Epoch(train) [38][2060/2569] lr: 4.0000e-02 eta: 21:22:59 time: 0.2746 data_time: 0.0079 memory: 5828 grad_norm: 3.0497 loss: 2.7831 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7831 2023/06/04 23:35:30 - mmengine - INFO - Epoch(train) [38][2080/2569] lr: 4.0000e-02 eta: 21:22:53 time: 0.2694 data_time: 0.0075 memory: 5828 grad_norm: 3.0695 loss: 2.7027 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7027 2023/06/04 23:35:35 - mmengine - INFO - Epoch(train) [38][2100/2569] lr: 4.0000e-02 eta: 21:22:48 time: 0.2698 data_time: 0.0080 memory: 5828 grad_norm: 3.0607 loss: 2.5596 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5596 2023/06/04 23:35:40 - mmengine - INFO - Epoch(train) [38][2120/2569] lr: 4.0000e-02 eta: 21:22:42 time: 0.2587 data_time: 0.0076 memory: 5828 grad_norm: 3.0938 loss: 2.6488 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6488 2023/06/04 23:35:46 - mmengine - INFO - Epoch(train) [38][2140/2569] lr: 4.0000e-02 eta: 21:22:37 time: 0.2594 data_time: 0.0077 memory: 5828 grad_norm: 3.0828 loss: 2.7364 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7364 2023/06/04 23:35:51 - mmengine - INFO - Epoch(train) [38][2160/2569] lr: 4.0000e-02 eta: 21:22:31 time: 0.2648 data_time: 0.0080 memory: 5828 grad_norm: 3.0353 loss: 2.5847 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5847 2023/06/04 23:35:56 - mmengine - INFO - Epoch(train) [38][2180/2569] lr: 4.0000e-02 eta: 21:22:26 time: 0.2709 data_time: 0.0076 memory: 5828 grad_norm: 3.0274 loss: 2.3977 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3977 2023/06/04 23:36:01 - mmengine - INFO - Epoch(train) [38][2200/2569] lr: 4.0000e-02 eta: 21:22:20 time: 0.2613 data_time: 0.0083 memory: 5828 grad_norm: 3.0971 loss: 2.4650 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4650 2023/06/04 23:36:07 - mmengine - INFO - Epoch(train) [38][2220/2569] lr: 4.0000e-02 eta: 21:22:15 time: 0.2706 data_time: 0.0084 memory: 5828 grad_norm: 3.1062 loss: 2.7954 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7954 2023/06/04 23:36:12 - mmengine - INFO - Epoch(train) [38][2240/2569] lr: 4.0000e-02 eta: 21:22:10 time: 0.2621 data_time: 0.0080 memory: 5828 grad_norm: 3.1182 loss: 2.5824 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5824 2023/06/04 23:36:18 - mmengine - INFO - Epoch(train) [38][2260/2569] lr: 4.0000e-02 eta: 21:22:05 time: 0.2718 data_time: 0.0079 memory: 5828 grad_norm: 3.0235 loss: 2.7973 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7973 2023/06/04 23:36:23 - mmengine - INFO - Epoch(train) [38][2280/2569] lr: 4.0000e-02 eta: 21:21:59 time: 0.2573 data_time: 0.0082 memory: 5828 grad_norm: 3.0688 loss: 3.0518 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0518 2023/06/04 23:36:28 - mmengine - INFO - Epoch(train) [38][2300/2569] lr: 4.0000e-02 eta: 21:21:53 time: 0.2650 data_time: 0.0082 memory: 5828 grad_norm: 3.0296 loss: 2.4606 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.4606 2023/06/04 23:36:33 - mmengine - INFO - Epoch(train) [38][2320/2569] lr: 4.0000e-02 eta: 21:21:47 time: 0.2614 data_time: 0.0078 memory: 5828 grad_norm: 3.0870 loss: 2.7568 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7568 2023/06/04 23:36:39 - mmengine - INFO - Epoch(train) [38][2340/2569] lr: 4.0000e-02 eta: 21:21:42 time: 0.2647 data_time: 0.0079 memory: 5828 grad_norm: 3.0918 loss: 2.6791 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6791 2023/06/04 23:36:44 - mmengine - INFO - Epoch(train) [38][2360/2569] lr: 4.0000e-02 eta: 21:21:36 time: 0.2628 data_time: 0.0079 memory: 5828 grad_norm: 3.0666 loss: 2.7204 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7204 2023/06/04 23:36:49 - mmengine - INFO - Epoch(train) [38][2380/2569] lr: 4.0000e-02 eta: 21:21:31 time: 0.2587 data_time: 0.0077 memory: 5828 grad_norm: 3.0996 loss: 2.5933 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5933 2023/06/04 23:36:54 - mmengine - INFO - Epoch(train) [38][2400/2569] lr: 4.0000e-02 eta: 21:21:25 time: 0.2647 data_time: 0.0079 memory: 5828 grad_norm: 3.0035 loss: 2.2949 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2949 2023/06/04 23:37:00 - mmengine - INFO - Epoch(train) [38][2420/2569] lr: 4.0000e-02 eta: 21:21:19 time: 0.2611 data_time: 0.0081 memory: 5828 grad_norm: 3.0615 loss: 2.6635 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6635 2023/06/04 23:37:05 - mmengine - INFO - Epoch(train) [38][2440/2569] lr: 4.0000e-02 eta: 21:21:14 time: 0.2592 data_time: 0.0079 memory: 5828 grad_norm: 3.0546 loss: 2.6888 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6888 2023/06/04 23:37:10 - mmengine - INFO - Epoch(train) [38][2460/2569] lr: 4.0000e-02 eta: 21:21:08 time: 0.2644 data_time: 0.0082 memory: 5828 grad_norm: 3.0532 loss: 2.5578 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5578 2023/06/04 23:37:15 - mmengine - INFO - Epoch(train) [38][2480/2569] lr: 4.0000e-02 eta: 21:21:03 time: 0.2657 data_time: 0.0086 memory: 5828 grad_norm: 3.0166 loss: 2.4525 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4525 2023/06/04 23:37:21 - mmengine - INFO - Epoch(train) [38][2500/2569] lr: 4.0000e-02 eta: 21:20:57 time: 0.2705 data_time: 0.0083 memory: 5828 grad_norm: 3.0586 loss: 2.6539 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6539 2023/06/04 23:37:26 - mmengine - INFO - Epoch(train) [38][2520/2569] lr: 4.0000e-02 eta: 21:20:52 time: 0.2580 data_time: 0.0087 memory: 5828 grad_norm: 3.0436 loss: 2.7361 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7361 2023/06/04 23:37:31 - mmengine - INFO - Epoch(train) [38][2540/2569] lr: 4.0000e-02 eta: 21:20:46 time: 0.2660 data_time: 0.0079 memory: 5828 grad_norm: 3.0167 loss: 2.7815 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7815 2023/06/04 23:37:36 - mmengine - INFO - Epoch(train) [38][2560/2569] lr: 4.0000e-02 eta: 21:20:40 time: 0.2559 data_time: 0.0077 memory: 5828 grad_norm: 3.0650 loss: 2.3832 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3832 2023/06/04 23:37:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:37:39 - mmengine - INFO - Epoch(train) [38][2569/2569] lr: 4.0000e-02 eta: 21:20:37 time: 0.2493 data_time: 0.0077 memory: 5828 grad_norm: 3.0866 loss: 2.5860 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5860 2023/06/04 23:37:45 - mmengine - INFO - Epoch(train) [39][ 20/2569] lr: 4.0000e-02 eta: 21:20:36 time: 0.3379 data_time: 0.0590 memory: 5828 grad_norm: 3.0687 loss: 2.8422 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8422 2023/06/04 23:37:51 - mmengine - INFO - Epoch(train) [39][ 40/2569] lr: 4.0000e-02 eta: 21:20:31 time: 0.2640 data_time: 0.0082 memory: 5828 grad_norm: 2.9925 loss: 2.9048 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.9048 2023/06/04 23:37:56 - mmengine - INFO - Epoch(train) [39][ 60/2569] lr: 4.0000e-02 eta: 21:20:25 time: 0.2584 data_time: 0.0075 memory: 5828 grad_norm: 3.0391 loss: 2.3892 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3892 2023/06/04 23:38:01 - mmengine - INFO - Epoch(train) [39][ 80/2569] lr: 4.0000e-02 eta: 21:20:19 time: 0.2663 data_time: 0.0080 memory: 5828 grad_norm: 3.1134 loss: 2.6482 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6482 2023/06/04 23:38:06 - mmengine - INFO - Epoch(train) [39][ 100/2569] lr: 4.0000e-02 eta: 21:20:14 time: 0.2652 data_time: 0.0080 memory: 5828 grad_norm: 3.0737 loss: 2.5543 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5543 2023/06/04 23:38:12 - mmengine - INFO - Epoch(train) [39][ 120/2569] lr: 4.0000e-02 eta: 21:20:08 time: 0.2624 data_time: 0.0079 memory: 5828 grad_norm: 3.1052 loss: 2.8472 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8472 2023/06/04 23:38:17 - mmengine - INFO - Epoch(train) [39][ 140/2569] lr: 4.0000e-02 eta: 21:20:03 time: 0.2677 data_time: 0.0084 memory: 5828 grad_norm: 3.0585 loss: 2.5275 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5275 2023/06/04 23:38:22 - mmengine - INFO - Epoch(train) [39][ 160/2569] lr: 4.0000e-02 eta: 21:19:57 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 3.0284 loss: 2.6023 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6023 2023/06/04 23:38:28 - mmengine - INFO - Epoch(train) [39][ 180/2569] lr: 4.0000e-02 eta: 21:19:52 time: 0.2682 data_time: 0.0081 memory: 5828 grad_norm: 3.0724 loss: 2.7831 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7831 2023/06/04 23:38:33 - mmengine - INFO - Epoch(train) [39][ 200/2569] lr: 4.0000e-02 eta: 21:19:47 time: 0.2645 data_time: 0.0083 memory: 5828 grad_norm: 3.0909 loss: 2.4221 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4221 2023/06/04 23:38:38 - mmengine - INFO - Epoch(train) [39][ 220/2569] lr: 4.0000e-02 eta: 21:19:41 time: 0.2572 data_time: 0.0076 memory: 5828 grad_norm: 3.1154 loss: 2.6524 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6524 2023/06/04 23:38:43 - mmengine - INFO - Epoch(train) [39][ 240/2569] lr: 4.0000e-02 eta: 21:19:35 time: 0.2640 data_time: 0.0080 memory: 5828 grad_norm: 3.0888 loss: 2.6720 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6720 2023/06/04 23:38:49 - mmengine - INFO - Epoch(train) [39][ 260/2569] lr: 4.0000e-02 eta: 21:19:30 time: 0.2622 data_time: 0.0077 memory: 5828 grad_norm: 3.0606 loss: 2.6197 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6197 2023/06/04 23:38:54 - mmengine - INFO - Epoch(train) [39][ 280/2569] lr: 4.0000e-02 eta: 21:19:24 time: 0.2640 data_time: 0.0081 memory: 5828 grad_norm: 3.0073 loss: 2.8039 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8039 2023/06/04 23:38:59 - mmengine - INFO - Epoch(train) [39][ 300/2569] lr: 4.0000e-02 eta: 21:19:18 time: 0.2578 data_time: 0.0078 memory: 5828 grad_norm: 3.0577 loss: 2.7272 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7272 2023/06/04 23:39:04 - mmengine - INFO - Epoch(train) [39][ 320/2569] lr: 4.0000e-02 eta: 21:19:13 time: 0.2623 data_time: 0.0080 memory: 5828 grad_norm: 3.0815 loss: 2.4227 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.4227 2023/06/04 23:39:10 - mmengine - INFO - Epoch(train) [39][ 340/2569] lr: 4.0000e-02 eta: 21:19:07 time: 0.2572 data_time: 0.0078 memory: 5828 grad_norm: 3.0864 loss: 2.3647 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3647 2023/06/04 23:39:15 - mmengine - INFO - Epoch(train) [39][ 360/2569] lr: 4.0000e-02 eta: 21:19:01 time: 0.2617 data_time: 0.0077 memory: 5828 grad_norm: 3.0659 loss: 2.4687 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4687 2023/06/04 23:39:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:39:20 - mmengine - INFO - Epoch(train) [39][ 380/2569] lr: 4.0000e-02 eta: 21:18:56 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 3.0866 loss: 2.4774 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4774 2023/06/04 23:39:25 - mmengine - INFO - Epoch(train) [39][ 400/2569] lr: 4.0000e-02 eta: 21:18:50 time: 0.2625 data_time: 0.0079 memory: 5828 grad_norm: 3.0835 loss: 2.6160 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6160 2023/06/04 23:39:31 - mmengine - INFO - Epoch(train) [39][ 420/2569] lr: 4.0000e-02 eta: 21:18:45 time: 0.2663 data_time: 0.0080 memory: 5828 grad_norm: 3.0790 loss: 2.8778 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8778 2023/06/04 23:39:36 - mmengine - INFO - Epoch(train) [39][ 440/2569] lr: 4.0000e-02 eta: 21:18:39 time: 0.2577 data_time: 0.0083 memory: 5828 grad_norm: 3.0484 loss: 2.3249 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3249 2023/06/04 23:39:41 - mmengine - INFO - Epoch(train) [39][ 460/2569] lr: 4.0000e-02 eta: 21:18:33 time: 0.2616 data_time: 0.0078 memory: 5828 grad_norm: 3.0248 loss: 2.9051 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9051 2023/06/04 23:39:46 - mmengine - INFO - Epoch(train) [39][ 480/2569] lr: 4.0000e-02 eta: 21:18:27 time: 0.2649 data_time: 0.0077 memory: 5828 grad_norm: 3.0005 loss: 2.3709 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3709 2023/06/04 23:39:52 - mmengine - INFO - Epoch(train) [39][ 500/2569] lr: 4.0000e-02 eta: 21:18:22 time: 0.2610 data_time: 0.0080 memory: 5828 grad_norm: 3.1221 loss: 2.6215 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6215 2023/06/04 23:39:57 - mmengine - INFO - Epoch(train) [39][ 520/2569] lr: 4.0000e-02 eta: 21:18:16 time: 0.2615 data_time: 0.0080 memory: 5828 grad_norm: 3.0136 loss: 2.2752 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2752 2023/06/04 23:40:02 - mmengine - INFO - Epoch(train) [39][ 540/2569] lr: 4.0000e-02 eta: 21:18:11 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 3.0308 loss: 2.7326 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7326 2023/06/04 23:40:07 - mmengine - INFO - Epoch(train) [39][ 560/2569] lr: 4.0000e-02 eta: 21:18:05 time: 0.2676 data_time: 0.0082 memory: 5828 grad_norm: 3.0753 loss: 2.5189 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5189 2023/06/04 23:40:13 - mmengine - INFO - Epoch(train) [39][ 580/2569] lr: 4.0000e-02 eta: 21:18:00 time: 0.2633 data_time: 0.0078 memory: 5828 grad_norm: 3.0648 loss: 2.2517 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2517 2023/06/04 23:40:18 - mmengine - INFO - Epoch(train) [39][ 600/2569] lr: 4.0000e-02 eta: 21:17:54 time: 0.2576 data_time: 0.0077 memory: 5828 grad_norm: 3.0772 loss: 2.7288 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7288 2023/06/04 23:40:23 - mmengine - INFO - Epoch(train) [39][ 620/2569] lr: 4.0000e-02 eta: 21:17:48 time: 0.2587 data_time: 0.0079 memory: 5828 grad_norm: 3.0894 loss: 2.1803 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1803 2023/06/04 23:40:28 - mmengine - INFO - Epoch(train) [39][ 640/2569] lr: 4.0000e-02 eta: 21:17:43 time: 0.2726 data_time: 0.0083 memory: 5828 grad_norm: 3.0199 loss: 2.3754 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3754 2023/06/04 23:40:34 - mmengine - INFO - Epoch(train) [39][ 660/2569] lr: 4.0000e-02 eta: 21:17:37 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 3.0898 loss: 2.6082 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6082 2023/06/04 23:40:39 - mmengine - INFO - Epoch(train) [39][ 680/2569] lr: 4.0000e-02 eta: 21:17:32 time: 0.2716 data_time: 0.0079 memory: 5828 grad_norm: 3.1277 loss: 2.6796 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6796 2023/06/04 23:40:45 - mmengine - INFO - Epoch(train) [39][ 700/2569] lr: 4.0000e-02 eta: 21:17:27 time: 0.2676 data_time: 0.0076 memory: 5828 grad_norm: 3.0637 loss: 2.7366 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.7366 2023/06/04 23:40:50 - mmengine - INFO - Epoch(train) [39][ 720/2569] lr: 4.0000e-02 eta: 21:17:21 time: 0.2621 data_time: 0.0080 memory: 5828 grad_norm: 3.0450 loss: 2.4497 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4497 2023/06/04 23:40:55 - mmengine - INFO - Epoch(train) [39][ 740/2569] lr: 4.0000e-02 eta: 21:17:16 time: 0.2673 data_time: 0.0076 memory: 5828 grad_norm: 3.0835 loss: 2.6413 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6413 2023/06/04 23:41:00 - mmengine - INFO - Epoch(train) [39][ 760/2569] lr: 4.0000e-02 eta: 21:17:10 time: 0.2571 data_time: 0.0082 memory: 5828 grad_norm: 3.0809 loss: 2.4233 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4233 2023/06/04 23:41:05 - mmengine - INFO - Epoch(train) [39][ 780/2569] lr: 4.0000e-02 eta: 21:17:04 time: 0.2576 data_time: 0.0077 memory: 5828 grad_norm: 3.1416 loss: 2.6184 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6184 2023/06/04 23:41:11 - mmengine - INFO - Epoch(train) [39][ 800/2569] lr: 4.0000e-02 eta: 21:16:59 time: 0.2618 data_time: 0.0080 memory: 5828 grad_norm: 3.0883 loss: 2.5875 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5875 2023/06/04 23:41:16 - mmengine - INFO - Epoch(train) [39][ 820/2569] lr: 4.0000e-02 eta: 21:16:53 time: 0.2571 data_time: 0.0076 memory: 5828 grad_norm: 3.0246 loss: 2.3450 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3450 2023/06/04 23:41:21 - mmengine - INFO - Epoch(train) [39][ 840/2569] lr: 4.0000e-02 eta: 21:16:48 time: 0.2771 data_time: 0.0075 memory: 5828 grad_norm: 3.0444 loss: 2.8634 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8634 2023/06/04 23:41:27 - mmengine - INFO - Epoch(train) [39][ 860/2569] lr: 4.0000e-02 eta: 21:16:42 time: 0.2628 data_time: 0.0077 memory: 5828 grad_norm: 3.1200 loss: 2.8379 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8379 2023/06/04 23:41:32 - mmengine - INFO - Epoch(train) [39][ 880/2569] lr: 4.0000e-02 eta: 21:16:37 time: 0.2721 data_time: 0.0075 memory: 5828 grad_norm: 3.0626 loss: 2.9575 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9575 2023/06/04 23:41:37 - mmengine - INFO - Epoch(train) [39][ 900/2569] lr: 4.0000e-02 eta: 21:16:32 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 3.1160 loss: 2.5344 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5344 2023/06/04 23:41:43 - mmengine - INFO - Epoch(train) [39][ 920/2569] lr: 4.0000e-02 eta: 21:16:26 time: 0.2675 data_time: 0.0077 memory: 5828 grad_norm: 3.0311 loss: 2.7086 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7086 2023/06/04 23:41:48 - mmengine - INFO - Epoch(train) [39][ 940/2569] lr: 4.0000e-02 eta: 21:16:21 time: 0.2642 data_time: 0.0079 memory: 5828 grad_norm: 3.0723 loss: 2.9814 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9814 2023/06/04 23:41:53 - mmengine - INFO - Epoch(train) [39][ 960/2569] lr: 4.0000e-02 eta: 21:16:15 time: 0.2645 data_time: 0.0083 memory: 5828 grad_norm: 3.0328 loss: 2.6469 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6469 2023/06/04 23:41:58 - mmengine - INFO - Epoch(train) [39][ 980/2569] lr: 4.0000e-02 eta: 21:16:10 time: 0.2621 data_time: 0.0083 memory: 5828 grad_norm: 3.0566 loss: 2.7387 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.7387 2023/06/04 23:42:04 - mmengine - INFO - Epoch(train) [39][1000/2569] lr: 4.0000e-02 eta: 21:16:04 time: 0.2655 data_time: 0.0076 memory: 5828 grad_norm: 3.0939 loss: 2.6556 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6556 2023/06/04 23:42:09 - mmengine - INFO - Epoch(train) [39][1020/2569] lr: 4.0000e-02 eta: 21:15:58 time: 0.2553 data_time: 0.0078 memory: 5828 grad_norm: 3.0731 loss: 2.7918 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7918 2023/06/04 23:42:14 - mmengine - INFO - Epoch(train) [39][1040/2569] lr: 4.0000e-02 eta: 21:15:53 time: 0.2629 data_time: 0.0079 memory: 5828 grad_norm: 3.1075 loss: 2.7528 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7528 2023/06/04 23:42:19 - mmengine - INFO - Epoch(train) [39][1060/2569] lr: 4.0000e-02 eta: 21:15:47 time: 0.2557 data_time: 0.0083 memory: 5828 grad_norm: 3.0369 loss: 2.4140 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4140 2023/06/04 23:42:24 - mmengine - INFO - Epoch(train) [39][1080/2569] lr: 4.0000e-02 eta: 21:15:41 time: 0.2571 data_time: 0.0081 memory: 5828 grad_norm: 3.0361 loss: 2.4990 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4990 2023/06/04 23:42:30 - mmengine - INFO - Epoch(train) [39][1100/2569] lr: 4.0000e-02 eta: 21:15:35 time: 0.2574 data_time: 0.0082 memory: 5828 grad_norm: 3.0932 loss: 2.3636 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3636 2023/06/04 23:42:35 - mmengine - INFO - Epoch(train) [39][1120/2569] lr: 4.0000e-02 eta: 21:15:30 time: 0.2677 data_time: 0.0079 memory: 5828 grad_norm: 3.0660 loss: 2.6942 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6942 2023/06/04 23:42:40 - mmengine - INFO - Epoch(train) [39][1140/2569] lr: 4.0000e-02 eta: 21:15:25 time: 0.2738 data_time: 0.0077 memory: 5828 grad_norm: 3.0968 loss: 2.5222 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5222 2023/06/04 23:42:46 - mmengine - INFO - Epoch(train) [39][1160/2569] lr: 4.0000e-02 eta: 21:15:19 time: 0.2633 data_time: 0.0083 memory: 5828 grad_norm: 3.0596 loss: 2.4488 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4488 2023/06/04 23:42:51 - mmengine - INFO - Epoch(train) [39][1180/2569] lr: 4.0000e-02 eta: 21:15:14 time: 0.2631 data_time: 0.0082 memory: 5828 grad_norm: 3.1491 loss: 2.6733 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6733 2023/06/04 23:42:56 - mmengine - INFO - Epoch(train) [39][1200/2569] lr: 4.0000e-02 eta: 21:15:08 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 3.0483 loss: 2.6787 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6787 2023/06/04 23:43:01 - mmengine - INFO - Epoch(train) [39][1220/2569] lr: 4.0000e-02 eta: 21:15:02 time: 0.2621 data_time: 0.0082 memory: 5828 grad_norm: 3.0943 loss: 2.8105 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 2.8105 2023/06/04 23:43:07 - mmengine - INFO - Epoch(train) [39][1240/2569] lr: 4.0000e-02 eta: 21:14:57 time: 0.2638 data_time: 0.0084 memory: 5828 grad_norm: 3.0397 loss: 2.5776 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5776 2023/06/04 23:43:12 - mmengine - INFO - Epoch(train) [39][1260/2569] lr: 4.0000e-02 eta: 21:14:52 time: 0.2683 data_time: 0.0083 memory: 5828 grad_norm: 3.0439 loss: 2.4163 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4163 2023/06/04 23:43:17 - mmengine - INFO - Epoch(train) [39][1280/2569] lr: 4.0000e-02 eta: 21:14:46 time: 0.2585 data_time: 0.0086 memory: 5828 grad_norm: 3.1035 loss: 2.5034 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5034 2023/06/04 23:43:23 - mmengine - INFO - Epoch(train) [39][1300/2569] lr: 4.0000e-02 eta: 21:14:40 time: 0.2639 data_time: 0.0080 memory: 5828 grad_norm: 3.0197 loss: 2.4748 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4748 2023/06/04 23:43:28 - mmengine - INFO - Epoch(train) [39][1320/2569] lr: 4.0000e-02 eta: 21:14:34 time: 0.2583 data_time: 0.0083 memory: 5828 grad_norm: 3.4080 loss: 2.7512 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7512 2023/06/04 23:43:33 - mmengine - INFO - Epoch(train) [39][1340/2569] lr: 4.0000e-02 eta: 21:14:29 time: 0.2602 data_time: 0.0080 memory: 5828 grad_norm: 3.1748 loss: 2.3989 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3989 2023/06/04 23:43:38 - mmengine - INFO - Epoch(train) [39][1360/2569] lr: 4.0000e-02 eta: 21:14:23 time: 0.2690 data_time: 0.0077 memory: 5828 grad_norm: 3.1455 loss: 2.8372 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8372 2023/06/04 23:43:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:43:44 - mmengine - INFO - Epoch(train) [39][1380/2569] lr: 4.0000e-02 eta: 21:14:18 time: 0.2593 data_time: 0.0078 memory: 5828 grad_norm: 3.0465 loss: 2.3274 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3274 2023/06/04 23:43:49 - mmengine - INFO - Epoch(train) [39][1400/2569] lr: 4.0000e-02 eta: 21:14:12 time: 0.2586 data_time: 0.0082 memory: 5828 grad_norm: 3.1363 loss: 2.7370 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.7370 2023/06/04 23:43:54 - mmengine - INFO - Epoch(train) [39][1420/2569] lr: 4.0000e-02 eta: 21:14:06 time: 0.2631 data_time: 0.0077 memory: 5828 grad_norm: 3.0273 loss: 2.3636 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3636 2023/06/04 23:43:59 - mmengine - INFO - Epoch(train) [39][1440/2569] lr: 4.0000e-02 eta: 21:14:01 time: 0.2660 data_time: 0.0078 memory: 5828 grad_norm: 3.1274 loss: 2.5760 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5760 2023/06/04 23:44:04 - mmengine - INFO - Epoch(train) [39][1460/2569] lr: 4.0000e-02 eta: 21:13:55 time: 0.2561 data_time: 0.0080 memory: 5828 grad_norm: 3.0790 loss: 2.5361 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5361 2023/06/04 23:44:10 - mmengine - INFO - Epoch(train) [39][1480/2569] lr: 4.0000e-02 eta: 21:13:49 time: 0.2624 data_time: 0.0081 memory: 5828 grad_norm: 3.0727 loss: 2.3991 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3991 2023/06/04 23:44:15 - mmengine - INFO - Epoch(train) [39][1500/2569] lr: 4.0000e-02 eta: 21:13:45 time: 0.2785 data_time: 0.0076 memory: 5828 grad_norm: 3.0506 loss: 2.4482 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4482 2023/06/04 23:44:20 - mmengine - INFO - Epoch(train) [39][1520/2569] lr: 4.0000e-02 eta: 21:13:39 time: 0.2601 data_time: 0.0078 memory: 5828 grad_norm: 3.0685 loss: 2.6150 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6150 2023/06/04 23:44:26 - mmengine - INFO - Epoch(train) [39][1540/2569] lr: 4.0000e-02 eta: 21:13:33 time: 0.2633 data_time: 0.0079 memory: 5828 grad_norm: 3.1128 loss: 2.6105 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6105 2023/06/04 23:44:31 - mmengine - INFO - Epoch(train) [39][1560/2569] lr: 4.0000e-02 eta: 21:13:28 time: 0.2655 data_time: 0.0077 memory: 5828 grad_norm: 3.0725 loss: 2.5262 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5262 2023/06/04 23:44:37 - mmengine - INFO - Epoch(train) [39][1580/2569] lr: 4.0000e-02 eta: 21:13:23 time: 0.2726 data_time: 0.0076 memory: 5828 grad_norm: 3.0667 loss: 2.4826 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4826 2023/06/04 23:44:42 - mmengine - INFO - Epoch(train) [39][1600/2569] lr: 4.0000e-02 eta: 21:13:17 time: 0.2605 data_time: 0.0078 memory: 5828 grad_norm: 3.1628 loss: 2.3888 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3888 2023/06/04 23:44:47 - mmengine - INFO - Epoch(train) [39][1620/2569] lr: 4.0000e-02 eta: 21:13:11 time: 0.2570 data_time: 0.0080 memory: 5828 grad_norm: 3.0911 loss: 2.5506 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5506 2023/06/04 23:44:52 - mmengine - INFO - Epoch(train) [39][1640/2569] lr: 4.0000e-02 eta: 21:13:06 time: 0.2646 data_time: 0.0083 memory: 5828 grad_norm: 3.1299 loss: 2.8330 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8330 2023/06/04 23:44:57 - mmengine - INFO - Epoch(train) [39][1660/2569] lr: 4.0000e-02 eta: 21:13:00 time: 0.2604 data_time: 0.0081 memory: 5828 grad_norm: 3.1293 loss: 2.6371 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6371 2023/06/04 23:45:03 - mmengine - INFO - Epoch(train) [39][1680/2569] lr: 4.0000e-02 eta: 21:12:54 time: 0.2610 data_time: 0.0076 memory: 5828 grad_norm: 3.0689 loss: 2.7459 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7459 2023/06/04 23:45:08 - mmengine - INFO - Epoch(train) [39][1700/2569] lr: 4.0000e-02 eta: 21:12:49 time: 0.2701 data_time: 0.0082 memory: 5828 grad_norm: 3.0741 loss: 2.6527 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6527 2023/06/04 23:45:13 - mmengine - INFO - Epoch(train) [39][1720/2569] lr: 4.0000e-02 eta: 21:12:44 time: 0.2637 data_time: 0.0083 memory: 5828 grad_norm: 3.1102 loss: 2.6330 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6330 2023/06/04 23:45:18 - mmengine - INFO - Epoch(train) [39][1740/2569] lr: 4.0000e-02 eta: 21:12:38 time: 0.2576 data_time: 0.0083 memory: 5828 grad_norm: 3.0858 loss: 2.7657 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7657 2023/06/04 23:45:24 - mmengine - INFO - Epoch(train) [39][1760/2569] lr: 4.0000e-02 eta: 21:12:32 time: 0.2619 data_time: 0.0082 memory: 5828 grad_norm: 3.0957 loss: 2.6805 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6805 2023/06/04 23:45:29 - mmengine - INFO - Epoch(train) [39][1780/2569] lr: 4.0000e-02 eta: 21:12:26 time: 0.2561 data_time: 0.0082 memory: 5828 grad_norm: 3.0640 loss: 2.4584 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4584 2023/06/04 23:45:34 - mmengine - INFO - Epoch(train) [39][1800/2569] lr: 4.0000e-02 eta: 21:12:20 time: 0.2583 data_time: 0.0081 memory: 5828 grad_norm: 3.0459 loss: 2.5719 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5719 2023/06/04 23:45:39 - mmengine - INFO - Epoch(train) [39][1820/2569] lr: 4.0000e-02 eta: 21:12:14 time: 0.2588 data_time: 0.0078 memory: 5828 grad_norm: 3.0458 loss: 2.2755 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2755 2023/06/04 23:45:44 - mmengine - INFO - Epoch(train) [39][1840/2569] lr: 4.0000e-02 eta: 21:12:09 time: 0.2628 data_time: 0.0080 memory: 5828 grad_norm: 3.0948 loss: 2.9024 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9024 2023/06/04 23:45:50 - mmengine - INFO - Epoch(train) [39][1860/2569] lr: 4.0000e-02 eta: 21:12:04 time: 0.2674 data_time: 0.0080 memory: 5828 grad_norm: 3.1424 loss: 2.5623 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5623 2023/06/04 23:45:55 - mmengine - INFO - Epoch(train) [39][1880/2569] lr: 4.0000e-02 eta: 21:11:58 time: 0.2689 data_time: 0.0080 memory: 5828 grad_norm: 3.0642 loss: 2.3899 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3899 2023/06/04 23:46:01 - mmengine - INFO - Epoch(train) [39][1900/2569] lr: 4.0000e-02 eta: 21:11:53 time: 0.2680 data_time: 0.0084 memory: 5828 grad_norm: 3.0784 loss: 2.6539 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6539 2023/06/04 23:46:06 - mmengine - INFO - Epoch(train) [39][1920/2569] lr: 4.0000e-02 eta: 21:11:47 time: 0.2581 data_time: 0.0081 memory: 5828 grad_norm: 3.1279 loss: 2.5853 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5853 2023/06/04 23:46:11 - mmengine - INFO - Epoch(train) [39][1940/2569] lr: 4.0000e-02 eta: 21:11:42 time: 0.2639 data_time: 0.0080 memory: 5828 grad_norm: 3.0953 loss: 2.5921 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5921 2023/06/04 23:46:16 - mmengine - INFO - Epoch(train) [39][1960/2569] lr: 4.0000e-02 eta: 21:11:36 time: 0.2651 data_time: 0.0082 memory: 5828 grad_norm: 3.0001 loss: 2.7271 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7271 2023/06/04 23:46:21 - mmengine - INFO - Epoch(train) [39][1980/2569] lr: 4.0000e-02 eta: 21:11:30 time: 0.2580 data_time: 0.0077 memory: 5828 grad_norm: 3.0211 loss: 2.2442 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2442 2023/06/04 23:46:27 - mmengine - INFO - Epoch(train) [39][2000/2569] lr: 4.0000e-02 eta: 21:11:25 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 3.0900 loss: 2.3825 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3825 2023/06/04 23:46:32 - mmengine - INFO - Epoch(train) [39][2020/2569] lr: 4.0000e-02 eta: 21:11:19 time: 0.2573 data_time: 0.0074 memory: 5828 grad_norm: 3.0727 loss: 2.8087 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8087 2023/06/04 23:46:37 - mmengine - INFO - Epoch(train) [39][2040/2569] lr: 4.0000e-02 eta: 21:11:14 time: 0.2734 data_time: 0.0077 memory: 5828 grad_norm: 3.0604 loss: 2.3354 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3354 2023/06/04 23:46:43 - mmengine - INFO - Epoch(train) [39][2060/2569] lr: 4.0000e-02 eta: 21:11:09 time: 0.2667 data_time: 0.0075 memory: 5828 grad_norm: 3.1038 loss: 2.3540 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3540 2023/06/04 23:46:48 - mmengine - INFO - Epoch(train) [39][2080/2569] lr: 4.0000e-02 eta: 21:11:03 time: 0.2666 data_time: 0.0081 memory: 5828 grad_norm: 3.0089 loss: 2.7228 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7228 2023/06/04 23:46:53 - mmengine - INFO - Epoch(train) [39][2100/2569] lr: 4.0000e-02 eta: 21:10:57 time: 0.2590 data_time: 0.0080 memory: 5828 grad_norm: 3.0684 loss: 2.9609 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9609 2023/06/04 23:46:58 - mmengine - INFO - Epoch(train) [39][2120/2569] lr: 4.0000e-02 eta: 21:10:52 time: 0.2620 data_time: 0.0075 memory: 5828 grad_norm: 3.0796 loss: 2.5165 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5165 2023/06/04 23:47:04 - mmengine - INFO - Epoch(train) [39][2140/2569] lr: 4.0000e-02 eta: 21:10:47 time: 0.2668 data_time: 0.0076 memory: 5828 grad_norm: 3.0647 loss: 3.1583 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1583 2023/06/04 23:47:09 - mmengine - INFO - Epoch(train) [39][2160/2569] lr: 4.0000e-02 eta: 21:10:41 time: 0.2583 data_time: 0.0075 memory: 5828 grad_norm: 3.1234 loss: 2.5968 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5968 2023/06/04 23:47:14 - mmengine - INFO - Epoch(train) [39][2180/2569] lr: 4.0000e-02 eta: 21:10:35 time: 0.2676 data_time: 0.0077 memory: 5828 grad_norm: 3.0433 loss: 2.3854 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3854 2023/06/04 23:47:20 - mmengine - INFO - Epoch(train) [39][2200/2569] lr: 4.0000e-02 eta: 21:10:30 time: 0.2630 data_time: 0.0082 memory: 5828 grad_norm: 3.1501 loss: 2.3942 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3942 2023/06/04 23:47:25 - mmengine - INFO - Epoch(train) [39][2220/2569] lr: 4.0000e-02 eta: 21:10:24 time: 0.2605 data_time: 0.0082 memory: 5828 grad_norm: 3.0639 loss: 2.7929 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7929 2023/06/04 23:47:30 - mmengine - INFO - Epoch(train) [39][2240/2569] lr: 4.0000e-02 eta: 21:10:19 time: 0.2640 data_time: 0.0080 memory: 5828 grad_norm: 3.0372 loss: 2.7179 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7179 2023/06/04 23:47:35 - mmengine - INFO - Epoch(train) [39][2260/2569] lr: 4.0000e-02 eta: 21:10:13 time: 0.2563 data_time: 0.0078 memory: 5828 grad_norm: 3.0521 loss: 2.8309 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.8309 2023/06/04 23:47:40 - mmengine - INFO - Epoch(train) [39][2280/2569] lr: 4.0000e-02 eta: 21:10:07 time: 0.2629 data_time: 0.0082 memory: 5828 grad_norm: 3.0036 loss: 2.6409 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6409 2023/06/04 23:47:46 - mmengine - INFO - Epoch(train) [39][2300/2569] lr: 4.0000e-02 eta: 21:10:01 time: 0.2585 data_time: 0.0079 memory: 5828 grad_norm: 3.0403 loss: 2.9984 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9984 2023/06/04 23:47:51 - mmengine - INFO - Epoch(train) [39][2320/2569] lr: 4.0000e-02 eta: 21:09:55 time: 0.2594 data_time: 0.0081 memory: 5828 grad_norm: 3.0618 loss: 2.5100 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5100 2023/06/04 23:47:56 - mmengine - INFO - Epoch(train) [39][2340/2569] lr: 4.0000e-02 eta: 21:09:50 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 3.1631 loss: 2.4319 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4319 2023/06/04 23:48:01 - mmengine - INFO - Epoch(train) [39][2360/2569] lr: 4.0000e-02 eta: 21:09:44 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 3.1221 loss: 2.7219 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7219 2023/06/04 23:48:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:48:07 - mmengine - INFO - Epoch(train) [39][2380/2569] lr: 4.0000e-02 eta: 21:09:39 time: 0.2662 data_time: 0.0082 memory: 5828 grad_norm: 3.0219 loss: 2.5799 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5799 2023/06/04 23:48:12 - mmengine - INFO - Epoch(train) [39][2400/2569] lr: 4.0000e-02 eta: 21:09:34 time: 0.2666 data_time: 0.0080 memory: 5828 grad_norm: 3.1756 loss: 2.4104 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4104 2023/06/04 23:48:17 - mmengine - INFO - Epoch(train) [39][2420/2569] lr: 4.0000e-02 eta: 21:09:28 time: 0.2677 data_time: 0.0079 memory: 5828 grad_norm: 3.0921 loss: 2.5141 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5141 2023/06/04 23:48:23 - mmengine - INFO - Epoch(train) [39][2440/2569] lr: 4.0000e-02 eta: 21:09:23 time: 0.2621 data_time: 0.0078 memory: 5828 grad_norm: 3.0488 loss: 2.6926 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6926 2023/06/04 23:48:28 - mmengine - INFO - Epoch(train) [39][2460/2569] lr: 4.0000e-02 eta: 21:09:17 time: 0.2678 data_time: 0.0076 memory: 5828 grad_norm: 3.0972 loss: 2.5506 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.5506 2023/06/04 23:48:33 - mmengine - INFO - Epoch(train) [39][2480/2569] lr: 4.0000e-02 eta: 21:09:12 time: 0.2626 data_time: 0.0080 memory: 5828 grad_norm: 3.0754 loss: 2.4583 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4583 2023/06/04 23:48:39 - mmengine - INFO - Epoch(train) [39][2500/2569] lr: 4.0000e-02 eta: 21:09:07 time: 0.2749 data_time: 0.0076 memory: 5828 grad_norm: 3.0371 loss: 2.5050 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5050 2023/06/04 23:48:44 - mmengine - INFO - Epoch(train) [39][2520/2569] lr: 4.0000e-02 eta: 21:09:01 time: 0.2575 data_time: 0.0082 memory: 5828 grad_norm: 3.1133 loss: 2.5669 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5669 2023/06/04 23:48:49 - mmengine - INFO - Epoch(train) [39][2540/2569] lr: 4.0000e-02 eta: 21:08:55 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 3.0910 loss: 2.3046 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3046 2023/06/04 23:48:54 - mmengine - INFO - Epoch(train) [39][2560/2569] lr: 4.0000e-02 eta: 21:08:49 time: 0.2558 data_time: 0.0090 memory: 5828 grad_norm: 3.0400 loss: 2.6509 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6509 2023/06/04 23:48:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:48:57 - mmengine - INFO - Epoch(train) [39][2569/2569] lr: 4.0000e-02 eta: 21:08:46 time: 0.2501 data_time: 0.0088 memory: 5828 grad_norm: 3.0561 loss: 2.9317 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.9317 2023/06/04 23:49:03 - mmengine - INFO - Epoch(train) [40][ 20/2569] lr: 4.0000e-02 eta: 21:08:45 time: 0.3398 data_time: 0.0689 memory: 5828 grad_norm: 3.0726 loss: 2.2839 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2839 2023/06/04 23:49:09 - mmengine - INFO - Epoch(train) [40][ 40/2569] lr: 4.0000e-02 eta: 21:08:40 time: 0.2746 data_time: 0.0083 memory: 5828 grad_norm: 3.0697 loss: 2.5854 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5854 2023/06/04 23:49:14 - mmengine - INFO - Epoch(train) [40][ 60/2569] lr: 4.0000e-02 eta: 21:08:35 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 3.0112 loss: 2.3925 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3925 2023/06/04 23:49:19 - mmengine - INFO - Epoch(train) [40][ 80/2569] lr: 4.0000e-02 eta: 21:08:29 time: 0.2626 data_time: 0.0081 memory: 5828 grad_norm: 3.0675 loss: 2.5693 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5693 2023/06/04 23:49:25 - mmengine - INFO - Epoch(train) [40][ 100/2569] lr: 4.0000e-02 eta: 21:08:24 time: 0.2636 data_time: 0.0078 memory: 5828 grad_norm: 3.0181 loss: 2.5203 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5203 2023/06/04 23:49:30 - mmengine - INFO - Epoch(train) [40][ 120/2569] lr: 4.0000e-02 eta: 21:08:18 time: 0.2584 data_time: 0.0080 memory: 5828 grad_norm: 3.0897 loss: 2.5764 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5764 2023/06/04 23:49:35 - mmengine - INFO - Epoch(train) [40][ 140/2569] lr: 4.0000e-02 eta: 21:08:13 time: 0.2717 data_time: 0.0077 memory: 5828 grad_norm: 3.0139 loss: 2.3611 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3611 2023/06/04 23:49:41 - mmengine - INFO - Epoch(train) [40][ 160/2569] lr: 4.0000e-02 eta: 21:08:07 time: 0.2627 data_time: 0.0079 memory: 5828 grad_norm: 3.0733 loss: 2.5410 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5410 2023/06/04 23:49:46 - mmengine - INFO - Epoch(train) [40][ 180/2569] lr: 4.0000e-02 eta: 21:08:02 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 3.0353 loss: 2.6174 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6174 2023/06/04 23:49:51 - mmengine - INFO - Epoch(train) [40][ 200/2569] lr: 4.0000e-02 eta: 21:07:56 time: 0.2627 data_time: 0.0077 memory: 5828 grad_norm: 3.1156 loss: 2.7301 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7301 2023/06/04 23:49:57 - mmengine - INFO - Epoch(train) [40][ 220/2569] lr: 4.0000e-02 eta: 21:07:51 time: 0.2722 data_time: 0.0084 memory: 5828 grad_norm: 3.1107 loss: 2.3558 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3558 2023/06/04 23:50:02 - mmengine - INFO - Epoch(train) [40][ 240/2569] lr: 4.0000e-02 eta: 21:07:46 time: 0.2690 data_time: 0.0083 memory: 5828 grad_norm: 3.0160 loss: 2.4016 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4016 2023/06/04 23:50:07 - mmengine - INFO - Epoch(train) [40][ 260/2569] lr: 4.0000e-02 eta: 21:07:40 time: 0.2588 data_time: 0.0080 memory: 5828 grad_norm: 3.0638 loss: 2.6906 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6906 2023/06/04 23:50:12 - mmengine - INFO - Epoch(train) [40][ 280/2569] lr: 4.0000e-02 eta: 21:07:35 time: 0.2589 data_time: 0.0078 memory: 5828 grad_norm: 3.1039 loss: 2.2448 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2448 2023/06/04 23:50:18 - mmengine - INFO - Epoch(train) [40][ 300/2569] lr: 4.0000e-02 eta: 21:07:29 time: 0.2654 data_time: 0.0079 memory: 5828 grad_norm: 3.1086 loss: 2.6361 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6361 2023/06/04 23:50:23 - mmengine - INFO - Epoch(train) [40][ 320/2569] lr: 4.0000e-02 eta: 21:07:24 time: 0.2618 data_time: 0.0082 memory: 5828 grad_norm: 3.1074 loss: 2.3748 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3748 2023/06/04 23:50:28 - mmengine - INFO - Epoch(train) [40][ 340/2569] lr: 4.0000e-02 eta: 21:07:18 time: 0.2661 data_time: 0.0088 memory: 5828 grad_norm: 3.0719 loss: 2.4340 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4340 2023/06/04 23:50:33 - mmengine - INFO - Epoch(train) [40][ 360/2569] lr: 4.0000e-02 eta: 21:07:12 time: 0.2616 data_time: 0.0082 memory: 5828 grad_norm: 3.1621 loss: 2.4950 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4950 2023/06/04 23:50:39 - mmengine - INFO - Epoch(train) [40][ 380/2569] lr: 4.0000e-02 eta: 21:07:07 time: 0.2641 data_time: 0.0079 memory: 5828 grad_norm: 3.0752 loss: 2.4410 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4410 2023/06/04 23:50:44 - mmengine - INFO - Epoch(train) [40][ 400/2569] lr: 4.0000e-02 eta: 21:07:01 time: 0.2628 data_time: 0.0077 memory: 5828 grad_norm: 3.0899 loss: 2.2908 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2908 2023/06/04 23:50:49 - mmengine - INFO - Epoch(train) [40][ 420/2569] lr: 4.0000e-02 eta: 21:06:56 time: 0.2582 data_time: 0.0078 memory: 5828 grad_norm: 3.0540 loss: 2.5855 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5855 2023/06/04 23:50:54 - mmengine - INFO - Epoch(train) [40][ 440/2569] lr: 4.0000e-02 eta: 21:06:50 time: 0.2605 data_time: 0.0082 memory: 5828 grad_norm: 3.0316 loss: 2.4738 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4738 2023/06/04 23:51:00 - mmengine - INFO - Epoch(train) [40][ 460/2569] lr: 4.0000e-02 eta: 21:06:44 time: 0.2588 data_time: 0.0080 memory: 5828 grad_norm: 3.0810 loss: 2.4209 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4209 2023/06/04 23:51:05 - mmengine - INFO - Epoch(train) [40][ 480/2569] lr: 4.0000e-02 eta: 21:06:38 time: 0.2623 data_time: 0.0078 memory: 5828 grad_norm: 3.0821 loss: 2.5610 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5610 2023/06/04 23:51:10 - mmengine - INFO - Epoch(train) [40][ 500/2569] lr: 4.0000e-02 eta: 21:06:33 time: 0.2576 data_time: 0.0080 memory: 5828 grad_norm: 3.0615 loss: 2.4209 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4209 2023/06/04 23:51:15 - mmengine - INFO - Epoch(train) [40][ 520/2569] lr: 4.0000e-02 eta: 21:06:27 time: 0.2662 data_time: 0.0076 memory: 5828 grad_norm: 3.0661 loss: 2.4411 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4411 2023/06/04 23:51:20 - mmengine - INFO - Epoch(train) [40][ 540/2569] lr: 4.0000e-02 eta: 21:06:21 time: 0.2574 data_time: 0.0088 memory: 5828 grad_norm: 3.0204 loss: 2.9322 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9322 2023/06/04 23:51:26 - mmengine - INFO - Epoch(train) [40][ 560/2569] lr: 4.0000e-02 eta: 21:06:16 time: 0.2636 data_time: 0.0080 memory: 5828 grad_norm: 3.1381 loss: 2.5495 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5495 2023/06/04 23:51:31 - mmengine - INFO - Epoch(train) [40][ 580/2569] lr: 4.0000e-02 eta: 21:06:10 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 3.0365 loss: 2.2811 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2811 2023/06/04 23:51:36 - mmengine - INFO - Epoch(train) [40][ 600/2569] lr: 4.0000e-02 eta: 21:06:04 time: 0.2576 data_time: 0.0077 memory: 5828 grad_norm: 3.1340 loss: 3.2506 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.2506 2023/06/04 23:51:41 - mmengine - INFO - Epoch(train) [40][ 620/2569] lr: 4.0000e-02 eta: 21:05:59 time: 0.2629 data_time: 0.0089 memory: 5828 grad_norm: 3.1211 loss: 2.6282 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6282 2023/06/04 23:51:47 - mmengine - INFO - Epoch(train) [40][ 640/2569] lr: 4.0000e-02 eta: 21:05:53 time: 0.2682 data_time: 0.0082 memory: 5828 grad_norm: 3.0289 loss: 2.6959 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6959 2023/06/04 23:51:52 - mmengine - INFO - Epoch(train) [40][ 660/2569] lr: 4.0000e-02 eta: 21:05:48 time: 0.2572 data_time: 0.0081 memory: 5828 grad_norm: 3.0612 loss: 2.5050 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5050 2023/06/04 23:51:57 - mmengine - INFO - Epoch(train) [40][ 680/2569] lr: 4.0000e-02 eta: 21:05:42 time: 0.2603 data_time: 0.0083 memory: 5828 grad_norm: 3.0612 loss: 2.7385 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7385 2023/06/04 23:52:02 - mmengine - INFO - Epoch(train) [40][ 700/2569] lr: 4.0000e-02 eta: 21:05:36 time: 0.2613 data_time: 0.0077 memory: 5828 grad_norm: 3.1099 loss: 2.9925 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9925 2023/06/04 23:52:08 - mmengine - INFO - Epoch(train) [40][ 720/2569] lr: 4.0000e-02 eta: 21:05:31 time: 0.2772 data_time: 0.0078 memory: 5828 grad_norm: 3.1146 loss: 2.6323 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6323 2023/06/04 23:52:13 - mmengine - INFO - Epoch(train) [40][ 740/2569] lr: 4.0000e-02 eta: 21:05:26 time: 0.2569 data_time: 0.0075 memory: 5828 grad_norm: 3.0708 loss: 2.8501 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.8501 2023/06/04 23:52:18 - mmengine - INFO - Epoch(train) [40][ 760/2569] lr: 4.0000e-02 eta: 21:05:20 time: 0.2643 data_time: 0.0084 memory: 5828 grad_norm: 3.1152 loss: 2.8639 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8639 2023/06/04 23:52:24 - mmengine - INFO - Epoch(train) [40][ 780/2569] lr: 4.0000e-02 eta: 21:05:14 time: 0.2591 data_time: 0.0081 memory: 5828 grad_norm: 3.1009 loss: 2.6615 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6615 2023/06/04 23:52:29 - mmengine - INFO - Epoch(train) [40][ 800/2569] lr: 4.0000e-02 eta: 21:05:09 time: 0.2628 data_time: 0.0082 memory: 5828 grad_norm: 3.0776 loss: 2.4457 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4457 2023/06/04 23:52:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:52:34 - mmengine - INFO - Epoch(train) [40][ 820/2569] lr: 4.0000e-02 eta: 21:05:03 time: 0.2590 data_time: 0.0080 memory: 5828 grad_norm: 3.0985 loss: 2.8392 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8392 2023/06/04 23:52:40 - mmengine - INFO - Epoch(train) [40][ 840/2569] lr: 4.0000e-02 eta: 21:04:58 time: 0.2772 data_time: 0.0080 memory: 5828 grad_norm: 3.1431 loss: 2.6468 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6468 2023/06/04 23:52:45 - mmengine - INFO - Epoch(train) [40][ 860/2569] lr: 4.0000e-02 eta: 21:04:53 time: 0.2671 data_time: 0.0080 memory: 5828 grad_norm: 3.0505 loss: 2.4753 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4753 2023/06/04 23:52:50 - mmengine - INFO - Epoch(train) [40][ 880/2569] lr: 4.0000e-02 eta: 21:04:47 time: 0.2620 data_time: 0.0086 memory: 5828 grad_norm: 3.0477 loss: 2.7949 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7949 2023/06/04 23:52:55 - mmengine - INFO - Epoch(train) [40][ 900/2569] lr: 4.0000e-02 eta: 21:04:42 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 3.1444 loss: 2.7301 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.7301 2023/06/04 23:53:01 - mmengine - INFO - Epoch(train) [40][ 920/2569] lr: 4.0000e-02 eta: 21:04:36 time: 0.2590 data_time: 0.0081 memory: 5828 grad_norm: 3.0329 loss: 2.4158 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4158 2023/06/04 23:53:06 - mmengine - INFO - Epoch(train) [40][ 940/2569] lr: 4.0000e-02 eta: 21:04:30 time: 0.2630 data_time: 0.0071 memory: 5828 grad_norm: 3.0569 loss: 2.4115 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4115 2023/06/04 23:53:11 - mmengine - INFO - Epoch(train) [40][ 960/2569] lr: 4.0000e-02 eta: 21:04:24 time: 0.2576 data_time: 0.0077 memory: 5828 grad_norm: 3.0894 loss: 2.3685 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3685 2023/06/04 23:53:16 - mmengine - INFO - Epoch(train) [40][ 980/2569] lr: 4.0000e-02 eta: 21:04:19 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 3.0823 loss: 2.6601 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6601 2023/06/04 23:53:22 - mmengine - INFO - Epoch(train) [40][1000/2569] lr: 4.0000e-02 eta: 21:04:14 time: 0.2674 data_time: 0.0077 memory: 5828 grad_norm: 3.0638 loss: 2.4478 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4478 2023/06/04 23:53:27 - mmengine - INFO - Epoch(train) [40][1020/2569] lr: 4.0000e-02 eta: 21:04:08 time: 0.2630 data_time: 0.0082 memory: 5828 grad_norm: 3.0898 loss: 2.2024 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2024 2023/06/04 23:53:32 - mmengine - INFO - Epoch(train) [40][1040/2569] lr: 4.0000e-02 eta: 21:04:02 time: 0.2584 data_time: 0.0072 memory: 5828 grad_norm: 3.1083 loss: 2.3347 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3347 2023/06/04 23:53:37 - mmengine - INFO - Epoch(train) [40][1060/2569] lr: 4.0000e-02 eta: 21:03:57 time: 0.2624 data_time: 0.0079 memory: 5828 grad_norm: 3.0473 loss: 2.6790 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6790 2023/06/04 23:53:42 - mmengine - INFO - Epoch(train) [40][1080/2569] lr: 4.0000e-02 eta: 21:03:51 time: 0.2583 data_time: 0.0082 memory: 5828 grad_norm: 3.0550 loss: 2.6795 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6795 2023/06/04 23:53:48 - mmengine - INFO - Epoch(train) [40][1100/2569] lr: 4.0000e-02 eta: 21:03:46 time: 0.2699 data_time: 0.0087 memory: 5828 grad_norm: 3.1114 loss: 2.4601 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4601 2023/06/04 23:53:53 - mmengine - INFO - Epoch(train) [40][1120/2569] lr: 4.0000e-02 eta: 21:03:40 time: 0.2583 data_time: 0.0079 memory: 5828 grad_norm: 3.0968 loss: 2.5590 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5590 2023/06/04 23:53:58 - mmengine - INFO - Epoch(train) [40][1140/2569] lr: 4.0000e-02 eta: 21:03:35 time: 0.2730 data_time: 0.0074 memory: 5828 grad_norm: 3.0932 loss: 2.6976 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.6976 2023/06/04 23:54:04 - mmengine - INFO - Epoch(train) [40][1160/2569] lr: 4.0000e-02 eta: 21:03:29 time: 0.2664 data_time: 0.0086 memory: 5828 grad_norm: 3.0951 loss: 2.4932 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4932 2023/06/04 23:54:09 - mmengine - INFO - Epoch(train) [40][1180/2569] lr: 4.0000e-02 eta: 21:03:24 time: 0.2682 data_time: 0.0077 memory: 5828 grad_norm: 3.0037 loss: 2.7963 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7963 2023/06/04 23:54:14 - mmengine - INFO - Epoch(train) [40][1200/2569] lr: 4.0000e-02 eta: 21:03:19 time: 0.2650 data_time: 0.0082 memory: 5828 grad_norm: 3.1018 loss: 2.7146 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7146 2023/06/04 23:54:20 - mmengine - INFO - Epoch(train) [40][1220/2569] lr: 4.0000e-02 eta: 21:03:13 time: 0.2575 data_time: 0.0080 memory: 5828 grad_norm: 3.0735 loss: 2.6250 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6250 2023/06/04 23:54:25 - mmengine - INFO - Epoch(train) [40][1240/2569] lr: 4.0000e-02 eta: 21:03:07 time: 0.2635 data_time: 0.0075 memory: 5828 grad_norm: 3.1427 loss: 2.4021 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4021 2023/06/04 23:54:30 - mmengine - INFO - Epoch(train) [40][1260/2569] lr: 4.0000e-02 eta: 21:03:02 time: 0.2685 data_time: 0.0079 memory: 5828 grad_norm: 2.9832 loss: 2.8357 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8357 2023/06/04 23:54:35 - mmengine - INFO - Epoch(train) [40][1280/2569] lr: 4.0000e-02 eta: 21:02:56 time: 0.2585 data_time: 0.0084 memory: 5828 grad_norm: 3.1112 loss: 2.6127 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6127 2023/06/04 23:54:41 - mmengine - INFO - Epoch(train) [40][1300/2569] lr: 4.0000e-02 eta: 21:02:51 time: 0.2622 data_time: 0.0082 memory: 5828 grad_norm: 3.0766 loss: 2.5497 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5497 2023/06/04 23:54:46 - mmengine - INFO - Epoch(train) [40][1320/2569] lr: 4.0000e-02 eta: 21:02:45 time: 0.2617 data_time: 0.0084 memory: 5828 grad_norm: 3.1376 loss: 2.5091 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5091 2023/06/04 23:54:51 - mmengine - INFO - Epoch(train) [40][1340/2569] lr: 4.0000e-02 eta: 21:02:39 time: 0.2574 data_time: 0.0078 memory: 5828 grad_norm: 3.0677 loss: 2.6703 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6703 2023/06/04 23:54:56 - mmengine - INFO - Epoch(train) [40][1360/2569] lr: 4.0000e-02 eta: 21:02:34 time: 0.2687 data_time: 0.0079 memory: 5828 grad_norm: 3.0655 loss: 2.4984 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4984 2023/06/04 23:55:02 - mmengine - INFO - Epoch(train) [40][1380/2569] lr: 4.0000e-02 eta: 21:02:28 time: 0.2572 data_time: 0.0077 memory: 5828 grad_norm: 3.0961 loss: 2.7230 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7230 2023/06/04 23:55:07 - mmengine - INFO - Epoch(train) [40][1400/2569] lr: 4.0000e-02 eta: 21:02:23 time: 0.2651 data_time: 0.0081 memory: 5828 grad_norm: 3.0825 loss: 2.2120 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2120 2023/06/04 23:55:12 - mmengine - INFO - Epoch(train) [40][1420/2569] lr: 4.0000e-02 eta: 21:02:17 time: 0.2590 data_time: 0.0078 memory: 5828 grad_norm: 3.0851 loss: 2.7656 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7656 2023/06/04 23:55:17 - mmengine - INFO - Epoch(train) [40][1440/2569] lr: 4.0000e-02 eta: 21:02:11 time: 0.2582 data_time: 0.0081 memory: 5828 grad_norm: 3.0820 loss: 2.5660 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5660 2023/06/04 23:55:23 - mmengine - INFO - Epoch(train) [40][1460/2569] lr: 4.0000e-02 eta: 21:02:05 time: 0.2620 data_time: 0.0078 memory: 5828 grad_norm: 3.0867 loss: 2.5152 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5152 2023/06/04 23:55:28 - mmengine - INFO - Epoch(train) [40][1480/2569] lr: 4.0000e-02 eta: 21:02:00 time: 0.2741 data_time: 0.0080 memory: 5828 grad_norm: 3.0576 loss: 2.5434 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5434 2023/06/04 23:55:33 - mmengine - INFO - Epoch(train) [40][1500/2569] lr: 4.0000e-02 eta: 21:01:55 time: 0.2625 data_time: 0.0079 memory: 5828 grad_norm: 3.0906 loss: 2.2421 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2421 2023/06/04 23:55:39 - mmengine - INFO - Epoch(train) [40][1520/2569] lr: 4.0000e-02 eta: 21:01:50 time: 0.2724 data_time: 0.0085 memory: 5828 grad_norm: 3.0259 loss: 2.6351 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6351 2023/06/04 23:55:44 - mmengine - INFO - Epoch(train) [40][1540/2569] lr: 4.0000e-02 eta: 21:01:44 time: 0.2626 data_time: 0.0079 memory: 5828 grad_norm: 3.0668 loss: 2.3693 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3693 2023/06/04 23:55:49 - mmengine - INFO - Epoch(train) [40][1560/2569] lr: 4.0000e-02 eta: 21:01:38 time: 0.2600 data_time: 0.0077 memory: 5828 grad_norm: 3.1190 loss: 2.6775 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6775 2023/06/04 23:55:54 - mmengine - INFO - Epoch(train) [40][1580/2569] lr: 4.0000e-02 eta: 21:01:33 time: 0.2608 data_time: 0.0077 memory: 5828 grad_norm: 3.0441 loss: 2.1821 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1821 2023/06/04 23:56:00 - mmengine - INFO - Epoch(train) [40][1600/2569] lr: 4.0000e-02 eta: 21:01:27 time: 0.2596 data_time: 0.0083 memory: 5828 grad_norm: 3.1740 loss: 2.7642 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7642 2023/06/04 23:56:05 - mmengine - INFO - Epoch(train) [40][1620/2569] lr: 4.0000e-02 eta: 21:01:21 time: 0.2628 data_time: 0.0084 memory: 5828 grad_norm: 3.0343 loss: 2.7804 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7804 2023/06/04 23:56:10 - mmengine - INFO - Epoch(train) [40][1640/2569] lr: 4.0000e-02 eta: 21:01:16 time: 0.2704 data_time: 0.0080 memory: 5828 grad_norm: 3.0609 loss: 2.6267 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6267 2023/06/04 23:56:16 - mmengine - INFO - Epoch(train) [40][1660/2569] lr: 4.0000e-02 eta: 21:01:11 time: 0.2628 data_time: 0.0085 memory: 5828 grad_norm: 3.0467 loss: 2.5503 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5503 2023/06/04 23:56:21 - mmengine - INFO - Epoch(train) [40][1680/2569] lr: 4.0000e-02 eta: 21:01:05 time: 0.2596 data_time: 0.0079 memory: 5828 grad_norm: 3.0766 loss: 2.5477 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5477 2023/06/04 23:56:26 - mmengine - INFO - Epoch(train) [40][1700/2569] lr: 4.0000e-02 eta: 21:00:59 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 3.0261 loss: 2.3879 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3879 2023/06/04 23:56:31 - mmengine - INFO - Epoch(train) [40][1720/2569] lr: 4.0000e-02 eta: 21:00:54 time: 0.2574 data_time: 0.0081 memory: 5828 grad_norm: 3.0569 loss: 2.6179 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6179 2023/06/04 23:56:36 - mmengine - INFO - Epoch(train) [40][1740/2569] lr: 4.0000e-02 eta: 21:00:48 time: 0.2651 data_time: 0.0075 memory: 5828 grad_norm: 3.1140 loss: 2.3964 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3964 2023/06/04 23:56:42 - mmengine - INFO - Epoch(train) [40][1760/2569] lr: 4.0000e-02 eta: 21:00:43 time: 0.2680 data_time: 0.0078 memory: 5828 grad_norm: 3.1095 loss: 2.6980 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6980 2023/06/04 23:56:47 - mmengine - INFO - Epoch(train) [40][1780/2569] lr: 4.0000e-02 eta: 21:00:38 time: 0.2682 data_time: 0.0076 memory: 5828 grad_norm: 3.1449 loss: 2.5163 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5163 2023/06/04 23:56:52 - mmengine - INFO - Epoch(train) [40][1800/2569] lr: 4.0000e-02 eta: 21:00:32 time: 0.2578 data_time: 0.0076 memory: 5828 grad_norm: 3.0722 loss: 2.6754 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6754 2023/06/04 23:56:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/04 23:56:58 - mmengine - INFO - Epoch(train) [40][1820/2569] lr: 4.0000e-02 eta: 21:00:26 time: 0.2623 data_time: 0.0077 memory: 5828 grad_norm: 3.0941 loss: 2.5778 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5778 2023/06/04 23:57:03 - mmengine - INFO - Epoch(train) [40][1840/2569] lr: 4.0000e-02 eta: 21:00:20 time: 0.2591 data_time: 0.0083 memory: 5828 grad_norm: 3.0727 loss: 2.5482 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5482 2023/06/04 23:57:08 - mmengine - INFO - Epoch(train) [40][1860/2569] lr: 4.0000e-02 eta: 21:00:15 time: 0.2643 data_time: 0.0075 memory: 5828 grad_norm: 3.0899 loss: 2.7544 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7544 2023/06/04 23:57:13 - mmengine - INFO - Epoch(train) [40][1880/2569] lr: 4.0000e-02 eta: 21:00:09 time: 0.2586 data_time: 0.0077 memory: 5828 grad_norm: 3.0386 loss: 2.7575 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7575 2023/06/04 23:57:19 - mmengine - INFO - Epoch(train) [40][1900/2569] lr: 4.0000e-02 eta: 21:00:04 time: 0.2630 data_time: 0.0076 memory: 5828 grad_norm: 3.0569 loss: 2.8162 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.8162 2023/06/04 23:57:24 - mmengine - INFO - Epoch(train) [40][1920/2569] lr: 4.0000e-02 eta: 20:59:58 time: 0.2570 data_time: 0.0074 memory: 5828 grad_norm: 3.0961 loss: 2.5680 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5680 2023/06/04 23:57:29 - mmengine - INFO - Epoch(train) [40][1940/2569] lr: 4.0000e-02 eta: 20:59:52 time: 0.2609 data_time: 0.0082 memory: 5828 grad_norm: 3.1187 loss: 2.1571 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1571 2023/06/04 23:57:34 - mmengine - INFO - Epoch(train) [40][1960/2569] lr: 4.0000e-02 eta: 20:59:47 time: 0.2664 data_time: 0.0079 memory: 5828 grad_norm: 3.0357 loss: 2.1371 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.1371 2023/06/04 23:57:39 - mmengine - INFO - Epoch(train) [40][1980/2569] lr: 4.0000e-02 eta: 20:59:41 time: 0.2564 data_time: 0.0080 memory: 5828 grad_norm: 3.0295 loss: 2.3827 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3827 2023/06/04 23:57:45 - mmengine - INFO - Epoch(train) [40][2000/2569] lr: 4.0000e-02 eta: 20:59:35 time: 0.2645 data_time: 0.0081 memory: 5828 grad_norm: 3.1114 loss: 2.6976 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.6976 2023/06/04 23:57:50 - mmengine - INFO - Epoch(train) [40][2020/2569] lr: 4.0000e-02 eta: 20:59:29 time: 0.2573 data_time: 0.0085 memory: 5828 grad_norm: 3.0905 loss: 3.0077 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0077 2023/06/04 23:57:55 - mmengine - INFO - Epoch(train) [40][2040/2569] lr: 4.0000e-02 eta: 20:59:24 time: 0.2638 data_time: 0.0082 memory: 5828 grad_norm: 3.0635 loss: 2.6271 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6271 2023/06/04 23:58:00 - mmengine - INFO - Epoch(train) [40][2060/2569] lr: 4.0000e-02 eta: 20:59:18 time: 0.2592 data_time: 0.0084 memory: 5828 grad_norm: 3.0298 loss: 2.5531 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5531 2023/06/04 23:58:06 - mmengine - INFO - Epoch(train) [40][2080/2569] lr: 4.0000e-02 eta: 20:59:12 time: 0.2615 data_time: 0.0080 memory: 5828 grad_norm: 3.1631 loss: 2.3322 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3322 2023/06/04 23:58:11 - mmengine - INFO - Epoch(train) [40][2100/2569] lr: 4.0000e-02 eta: 20:59:07 time: 0.2596 data_time: 0.0080 memory: 5828 grad_norm: 3.0911 loss: 2.5319 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5319 2023/06/04 23:58:16 - mmengine - INFO - Epoch(train) [40][2120/2569] lr: 4.0000e-02 eta: 20:59:01 time: 0.2628 data_time: 0.0080 memory: 5828 grad_norm: 3.0358 loss: 2.7131 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7131 2023/06/04 23:58:21 - mmengine - INFO - Epoch(train) [40][2140/2569] lr: 4.0000e-02 eta: 20:58:55 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 3.0272 loss: 2.8080 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8080 2023/06/04 23:58:26 - mmengine - INFO - Epoch(train) [40][2160/2569] lr: 4.0000e-02 eta: 20:58:50 time: 0.2580 data_time: 0.0083 memory: 5828 grad_norm: 3.0790 loss: 2.8705 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8705 2023/06/04 23:58:32 - mmengine - INFO - Epoch(train) [40][2180/2569] lr: 4.0000e-02 eta: 20:58:44 time: 0.2661 data_time: 0.0077 memory: 5828 grad_norm: 3.0820 loss: 2.6260 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6260 2023/06/04 23:58:37 - mmengine - INFO - Epoch(train) [40][2200/2569] lr: 4.0000e-02 eta: 20:58:39 time: 0.2614 data_time: 0.0090 memory: 5828 grad_norm: 3.0136 loss: 2.6821 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6821 2023/06/04 23:58:42 - mmengine - INFO - Epoch(train) [40][2220/2569] lr: 4.0000e-02 eta: 20:58:33 time: 0.2573 data_time: 0.0078 memory: 5828 grad_norm: 3.1400 loss: 2.6233 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6233 2023/06/04 23:58:47 - mmengine - INFO - Epoch(train) [40][2240/2569] lr: 4.0000e-02 eta: 20:58:27 time: 0.2571 data_time: 0.0094 memory: 5828 grad_norm: 3.0255 loss: 2.3494 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3494 2023/06/04 23:58:52 - mmengine - INFO - Epoch(train) [40][2260/2569] lr: 4.0000e-02 eta: 20:58:21 time: 0.2571 data_time: 0.0077 memory: 5828 grad_norm: 3.0651 loss: 2.5170 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5170 2023/06/04 23:58:58 - mmengine - INFO - Epoch(train) [40][2280/2569] lr: 4.0000e-02 eta: 20:58:16 time: 0.2746 data_time: 0.0083 memory: 5828 grad_norm: 3.0985 loss: 2.4553 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4553 2023/06/04 23:59:03 - mmengine - INFO - Epoch(train) [40][2300/2569] lr: 4.0000e-02 eta: 20:58:10 time: 0.2593 data_time: 0.0075 memory: 5828 grad_norm: 3.0373 loss: 2.8236 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8236 2023/06/04 23:59:08 - mmengine - INFO - Epoch(train) [40][2320/2569] lr: 4.0000e-02 eta: 20:58:05 time: 0.2712 data_time: 0.0078 memory: 5828 grad_norm: 3.1190 loss: 2.3870 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3870 2023/06/04 23:59:14 - mmengine - INFO - Epoch(train) [40][2340/2569] lr: 4.0000e-02 eta: 20:58:00 time: 0.2658 data_time: 0.0081 memory: 5828 grad_norm: 3.0572 loss: 2.6760 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6760 2023/06/04 23:59:19 - mmengine - INFO - Epoch(train) [40][2360/2569] lr: 4.0000e-02 eta: 20:57:54 time: 0.2571 data_time: 0.0080 memory: 5828 grad_norm: 3.1143 loss: 2.6081 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6081 2023/06/04 23:59:24 - mmengine - INFO - Epoch(train) [40][2380/2569] lr: 4.0000e-02 eta: 20:57:48 time: 0.2656 data_time: 0.0077 memory: 5828 grad_norm: 3.0756 loss: 2.7130 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7130 2023/06/04 23:59:29 - mmengine - INFO - Epoch(train) [40][2400/2569] lr: 4.0000e-02 eta: 20:57:43 time: 0.2616 data_time: 0.0081 memory: 5828 grad_norm: 3.0998 loss: 2.5944 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5944 2023/06/04 23:59:35 - mmengine - INFO - Epoch(train) [40][2420/2569] lr: 4.0000e-02 eta: 20:57:37 time: 0.2573 data_time: 0.0076 memory: 5828 grad_norm: 3.0536 loss: 2.4436 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4436 2023/06/04 23:59:40 - mmengine - INFO - Epoch(train) [40][2440/2569] lr: 4.0000e-02 eta: 20:57:31 time: 0.2576 data_time: 0.0077 memory: 5828 grad_norm: 3.1030 loss: 2.6090 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.6090 2023/06/04 23:59:45 - mmengine - INFO - Epoch(train) [40][2460/2569] lr: 4.0000e-02 eta: 20:57:25 time: 0.2580 data_time: 0.0079 memory: 5828 grad_norm: 3.0588 loss: 2.3174 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3174 2023/06/04 23:59:50 - mmengine - INFO - Epoch(train) [40][2480/2569] lr: 4.0000e-02 eta: 20:57:19 time: 0.2583 data_time: 0.0079 memory: 5828 grad_norm: 3.0274 loss: 2.5418 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5418 2023/06/04 23:59:55 - mmengine - INFO - Epoch(train) [40][2500/2569] lr: 4.0000e-02 eta: 20:57:14 time: 0.2629 data_time: 0.0077 memory: 5828 grad_norm: 2.9690 loss: 2.4165 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4165 2023/06/05 00:00:01 - mmengine - INFO - Epoch(train) [40][2520/2569] lr: 4.0000e-02 eta: 20:57:08 time: 0.2634 data_time: 0.0082 memory: 5828 grad_norm: 3.0878 loss: 2.4025 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4025 2023/06/05 00:00:06 - mmengine - INFO - Epoch(train) [40][2540/2569] lr: 4.0000e-02 eta: 20:57:03 time: 0.2576 data_time: 0.0077 memory: 5828 grad_norm: 3.1092 loss: 2.4878 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4878 2023/06/05 00:00:11 - mmengine - INFO - Epoch(train) [40][2560/2569] lr: 4.0000e-02 eta: 20:56:58 time: 0.2747 data_time: 0.0086 memory: 5828 grad_norm: 3.0600 loss: 2.9638 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9638 2023/06/05 00:00:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:00:13 - mmengine - INFO - Epoch(train) [40][2569/2569] lr: 4.0000e-02 eta: 20:56:55 time: 0.2612 data_time: 0.0079 memory: 5828 grad_norm: 3.1204 loss: 2.7412 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.7412 2023/06/05 00:00:14 - mmengine - INFO - Saving checkpoint at 40 epochs 2023/06/05 00:00:19 - mmengine - INFO - Epoch(val) [40][ 20/260] eta: 0:00:43 time: 0.1801 data_time: 0.1212 memory: 1238 2023/06/05 00:00:22 - mmengine - INFO - Epoch(val) [40][ 40/260] eta: 0:00:35 time: 0.1389 data_time: 0.0803 memory: 1238 2023/06/05 00:00:25 - mmengine - INFO - Epoch(val) [40][ 60/260] eta: 0:00:30 time: 0.1410 data_time: 0.0821 memory: 1238 2023/06/05 00:00:28 - mmengine - INFO - Epoch(val) [40][ 80/260] eta: 0:00:27 time: 0.1409 data_time: 0.0826 memory: 1238 2023/06/05 00:00:30 - mmengine - INFO - Epoch(val) [40][100/260] eta: 0:00:23 time: 0.1306 data_time: 0.0720 memory: 1238 2023/06/05 00:00:33 - mmengine - INFO - Epoch(val) [40][120/260] eta: 0:00:20 time: 0.1417 data_time: 0.0834 memory: 1238 2023/06/05 00:00:36 - mmengine - INFO - Epoch(val) [40][140/260] eta: 0:00:16 time: 0.1158 data_time: 0.0575 memory: 1238 2023/06/05 00:00:39 - mmengine - INFO - Epoch(val) [40][160/260] eta: 0:00:14 time: 0.1629 data_time: 0.1046 memory: 1238 2023/06/05 00:00:41 - mmengine - INFO - Epoch(val) [40][180/260] eta: 0:00:11 time: 0.1176 data_time: 0.0586 memory: 1238 2023/06/05 00:00:44 - mmengine - INFO - Epoch(val) [40][200/260] eta: 0:00:08 time: 0.1467 data_time: 0.0883 memory: 1238 2023/06/05 00:00:47 - mmengine - INFO - Epoch(val) [40][220/260] eta: 0:00:05 time: 0.1264 data_time: 0.0675 memory: 1238 2023/06/05 00:00:49 - mmengine - INFO - Epoch(val) [40][240/260] eta: 0:00:02 time: 0.1343 data_time: 0.0765 memory: 1238 2023/06/05 00:00:52 - mmengine - INFO - Epoch(val) [40][260/260] eta: 0:00:00 time: 0.1150 data_time: 0.0593 memory: 1238 2023/06/05 00:00:59 - mmengine - INFO - Epoch(val) [40][260/260] acc/top1: 0.4999 acc/top5: 0.7427 acc/mean1: 0.4913 data_time: 0.0792 time: 0.1375 2023/06/05 00:00:59 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_35.pth is removed 2023/06/05 00:01:00 - mmengine - INFO - The best checkpoint with 0.4999 acc/top1 at 40 epoch is saved to best_acc_top1_epoch_40.pth. 2023/06/05 00:01:06 - mmengine - INFO - Epoch(train) [41][ 20/2569] lr: 4.0000e-02 eta: 20:56:51 time: 0.3027 data_time: 0.0536 memory: 5828 grad_norm: 3.0254 loss: 2.6477 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6477 2023/06/05 00:01:11 - mmengine - INFO - Epoch(train) [41][ 40/2569] lr: 4.0000e-02 eta: 20:56:46 time: 0.2603 data_time: 0.0078 memory: 5828 grad_norm: 3.0951 loss: 2.4453 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4453 2023/06/05 00:01:17 - mmengine - INFO - Epoch(train) [41][ 60/2569] lr: 4.0000e-02 eta: 20:56:40 time: 0.2645 data_time: 0.0075 memory: 5828 grad_norm: 3.0601 loss: 2.8920 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8920 2023/06/05 00:01:22 - mmengine - INFO - Epoch(train) [41][ 80/2569] lr: 4.0000e-02 eta: 20:56:35 time: 0.2660 data_time: 0.0079 memory: 5828 grad_norm: 3.0660 loss: 2.7660 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7660 2023/06/05 00:01:27 - mmengine - INFO - Epoch(train) [41][ 100/2569] lr: 4.0000e-02 eta: 20:56:29 time: 0.2633 data_time: 0.0080 memory: 5828 grad_norm: 3.0791 loss: 2.7239 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7239 2023/06/05 00:01:32 - mmengine - INFO - Epoch(train) [41][ 120/2569] lr: 4.0000e-02 eta: 20:56:23 time: 0.2574 data_time: 0.0089 memory: 5828 grad_norm: 3.1611 loss: 2.3038 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3038 2023/06/05 00:01:38 - mmengine - INFO - Epoch(train) [41][ 140/2569] lr: 4.0000e-02 eta: 20:56:18 time: 0.2609 data_time: 0.0073 memory: 5828 grad_norm: 3.0384 loss: 2.4260 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4260 2023/06/05 00:01:43 - mmengine - INFO - Epoch(train) [41][ 160/2569] lr: 4.0000e-02 eta: 20:56:12 time: 0.2630 data_time: 0.0074 memory: 5828 grad_norm: 3.1792 loss: 2.3563 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3563 2023/06/05 00:01:48 - mmengine - INFO - Epoch(train) [41][ 180/2569] lr: 4.0000e-02 eta: 20:56:07 time: 0.2630 data_time: 0.0094 memory: 5828 grad_norm: 3.0510 loss: 2.4574 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4574 2023/06/05 00:01:53 - mmengine - INFO - Epoch(train) [41][ 200/2569] lr: 4.0000e-02 eta: 20:56:01 time: 0.2586 data_time: 0.0077 memory: 5828 grad_norm: 3.0982 loss: 2.7172 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7172 2023/06/05 00:01:59 - mmengine - INFO - Epoch(train) [41][ 220/2569] lr: 4.0000e-02 eta: 20:55:56 time: 0.2678 data_time: 0.0078 memory: 5828 grad_norm: 3.0823 loss: 2.3672 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3672 2023/06/05 00:02:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:02:04 - mmengine - INFO - Epoch(train) [41][ 240/2569] lr: 4.0000e-02 eta: 20:55:50 time: 0.2623 data_time: 0.0077 memory: 5828 grad_norm: 3.0782 loss: 2.5906 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5906 2023/06/05 00:02:09 - mmengine - INFO - Epoch(train) [41][ 260/2569] lr: 4.0000e-02 eta: 20:55:45 time: 0.2667 data_time: 0.0083 memory: 5828 grad_norm: 3.1045 loss: 2.8005 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8005 2023/06/05 00:02:14 - mmengine - INFO - Epoch(train) [41][ 280/2569] lr: 4.0000e-02 eta: 20:55:39 time: 0.2565 data_time: 0.0084 memory: 5828 grad_norm: 3.1679 loss: 2.6090 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6090 2023/06/05 00:02:20 - mmengine - INFO - Epoch(train) [41][ 300/2569] lr: 4.0000e-02 eta: 20:55:34 time: 0.2702 data_time: 0.0077 memory: 5828 grad_norm: 3.1481 loss: 2.6019 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6019 2023/06/05 00:02:25 - mmengine - INFO - Epoch(train) [41][ 320/2569] lr: 4.0000e-02 eta: 20:55:28 time: 0.2590 data_time: 0.0081 memory: 5828 grad_norm: 3.1395 loss: 2.6334 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6334 2023/06/05 00:02:30 - mmengine - INFO - Epoch(train) [41][ 340/2569] lr: 4.0000e-02 eta: 20:55:23 time: 0.2738 data_time: 0.0075 memory: 5828 grad_norm: 3.0230 loss: 2.7509 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7509 2023/06/05 00:02:36 - mmengine - INFO - Epoch(train) [41][ 360/2569] lr: 4.0000e-02 eta: 20:55:18 time: 0.2691 data_time: 0.0081 memory: 5828 grad_norm: 3.1283 loss: 2.7742 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7742 2023/06/05 00:02:41 - mmengine - INFO - Epoch(train) [41][ 380/2569] lr: 4.0000e-02 eta: 20:55:12 time: 0.2678 data_time: 0.0080 memory: 5828 grad_norm: 3.0565 loss: 2.6112 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6112 2023/06/05 00:02:46 - mmengine - INFO - Epoch(train) [41][ 400/2569] lr: 4.0000e-02 eta: 20:55:07 time: 0.2623 data_time: 0.0078 memory: 5828 grad_norm: 3.0707 loss: 2.7267 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7267 2023/06/05 00:02:52 - mmengine - INFO - Epoch(train) [41][ 420/2569] lr: 4.0000e-02 eta: 20:55:01 time: 0.2589 data_time: 0.0075 memory: 5828 grad_norm: 3.0729 loss: 2.7286 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7286 2023/06/05 00:02:57 - mmengine - INFO - Epoch(train) [41][ 440/2569] lr: 4.0000e-02 eta: 20:54:55 time: 0.2636 data_time: 0.0078 memory: 5828 grad_norm: 3.0270 loss: 2.4806 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4806 2023/06/05 00:03:02 - mmengine - INFO - Epoch(train) [41][ 460/2569] lr: 4.0000e-02 eta: 20:54:50 time: 0.2726 data_time: 0.0076 memory: 5828 grad_norm: 3.0635 loss: 2.3035 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3035 2023/06/05 00:03:08 - mmengine - INFO - Epoch(train) [41][ 480/2569] lr: 4.0000e-02 eta: 20:54:45 time: 0.2631 data_time: 0.0079 memory: 5828 grad_norm: 3.1356 loss: 2.5385 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5385 2023/06/05 00:03:13 - mmengine - INFO - Epoch(train) [41][ 500/2569] lr: 4.0000e-02 eta: 20:54:40 time: 0.2677 data_time: 0.0076 memory: 5828 grad_norm: 3.0618 loss: 2.5807 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5807 2023/06/05 00:03:18 - mmengine - INFO - Epoch(train) [41][ 520/2569] lr: 4.0000e-02 eta: 20:54:34 time: 0.2618 data_time: 0.0079 memory: 5828 grad_norm: 2.9751 loss: 2.6440 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6440 2023/06/05 00:03:24 - mmengine - INFO - Epoch(train) [41][ 540/2569] lr: 4.0000e-02 eta: 20:54:29 time: 0.2680 data_time: 0.0077 memory: 5828 grad_norm: 3.0963 loss: 2.4226 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4226 2023/06/05 00:03:29 - mmengine - INFO - Epoch(train) [41][ 560/2569] lr: 4.0000e-02 eta: 20:54:23 time: 0.2610 data_time: 0.0082 memory: 5828 grad_norm: 3.0820 loss: 2.6414 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6414 2023/06/05 00:03:34 - mmengine - INFO - Epoch(train) [41][ 580/2569] lr: 4.0000e-02 eta: 20:54:17 time: 0.2559 data_time: 0.0075 memory: 5828 grad_norm: 3.1435 loss: 2.4435 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4435 2023/06/05 00:03:39 - mmengine - INFO - Epoch(train) [41][ 600/2569] lr: 4.0000e-02 eta: 20:54:11 time: 0.2572 data_time: 0.0077 memory: 5828 grad_norm: 3.1048 loss: 2.3754 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3754 2023/06/05 00:03:44 - mmengine - INFO - Epoch(train) [41][ 620/2569] lr: 4.0000e-02 eta: 20:54:06 time: 0.2616 data_time: 0.0077 memory: 5828 grad_norm: 3.1102 loss: 2.3513 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 2.3513 2023/06/05 00:03:50 - mmengine - INFO - Epoch(train) [41][ 640/2569] lr: 4.0000e-02 eta: 20:54:00 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 3.1809 loss: 2.5171 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5171 2023/06/05 00:03:55 - mmengine - INFO - Epoch(train) [41][ 660/2569] lr: 4.0000e-02 eta: 20:53:54 time: 0.2574 data_time: 0.0080 memory: 5828 grad_norm: 3.0955 loss: 2.6252 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6252 2023/06/05 00:04:00 - mmengine - INFO - Epoch(train) [41][ 680/2569] lr: 4.0000e-02 eta: 20:53:49 time: 0.2637 data_time: 0.0079 memory: 5828 grad_norm: 3.0203 loss: 2.8167 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8167 2023/06/05 00:04:05 - mmengine - INFO - Epoch(train) [41][ 700/2569] lr: 4.0000e-02 eta: 20:53:43 time: 0.2578 data_time: 0.0081 memory: 5828 grad_norm: 3.0769 loss: 2.7186 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7186 2023/06/05 00:04:11 - mmengine - INFO - Epoch(train) [41][ 720/2569] lr: 4.0000e-02 eta: 20:53:38 time: 0.2685 data_time: 0.0077 memory: 5828 grad_norm: 3.1772 loss: 2.7689 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7689 2023/06/05 00:04:16 - mmengine - INFO - Epoch(train) [41][ 740/2569] lr: 4.0000e-02 eta: 20:53:32 time: 0.2559 data_time: 0.0078 memory: 5828 grad_norm: 3.0106 loss: 2.4555 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4555 2023/06/05 00:04:21 - mmengine - INFO - Epoch(train) [41][ 760/2569] lr: 4.0000e-02 eta: 20:53:27 time: 0.2748 data_time: 0.0078 memory: 5828 grad_norm: 3.0804 loss: 2.2154 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2154 2023/06/05 00:04:27 - mmengine - INFO - Epoch(train) [41][ 780/2569] lr: 4.0000e-02 eta: 20:53:21 time: 0.2635 data_time: 0.0084 memory: 5828 grad_norm: 3.0655 loss: 2.5662 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5662 2023/06/05 00:04:32 - mmengine - INFO - Epoch(train) [41][ 800/2569] lr: 4.0000e-02 eta: 20:53:16 time: 0.2613 data_time: 0.0076 memory: 5828 grad_norm: 3.1167 loss: 2.4842 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4842 2023/06/05 00:04:37 - mmengine - INFO - Epoch(train) [41][ 820/2569] lr: 4.0000e-02 eta: 20:53:11 time: 0.2678 data_time: 0.0080 memory: 5828 grad_norm: 3.0382 loss: 2.4912 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4912 2023/06/05 00:04:42 - mmengine - INFO - Epoch(train) [41][ 840/2569] lr: 4.0000e-02 eta: 20:53:05 time: 0.2564 data_time: 0.0076 memory: 5828 grad_norm: 3.1084 loss: 2.8961 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8961 2023/06/05 00:04:47 - mmengine - INFO - Epoch(train) [41][ 860/2569] lr: 4.0000e-02 eta: 20:52:59 time: 0.2599 data_time: 0.0073 memory: 5828 grad_norm: 3.0986 loss: 2.2225 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.2225 2023/06/05 00:04:53 - mmengine - INFO - Epoch(train) [41][ 880/2569] lr: 4.0000e-02 eta: 20:52:53 time: 0.2620 data_time: 0.0077 memory: 5828 grad_norm: 3.1336 loss: 2.8048 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.8048 2023/06/05 00:04:58 - mmengine - INFO - Epoch(train) [41][ 900/2569] lr: 4.0000e-02 eta: 20:52:48 time: 0.2639 data_time: 0.0079 memory: 5828 grad_norm: 3.1110 loss: 2.3952 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3952 2023/06/05 00:05:03 - mmengine - INFO - Epoch(train) [41][ 920/2569] lr: 4.0000e-02 eta: 20:52:42 time: 0.2602 data_time: 0.0077 memory: 5828 grad_norm: 3.1289 loss: 2.6341 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6341 2023/06/05 00:05:08 - mmengine - INFO - Epoch(train) [41][ 940/2569] lr: 4.0000e-02 eta: 20:52:37 time: 0.2635 data_time: 0.0084 memory: 5828 grad_norm: 3.0817 loss: 2.5748 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5748 2023/06/05 00:05:14 - mmengine - INFO - Epoch(train) [41][ 960/2569] lr: 4.0000e-02 eta: 20:52:31 time: 0.2583 data_time: 0.0088 memory: 5828 grad_norm: 2.9777 loss: 2.3859 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3859 2023/06/05 00:05:19 - mmengine - INFO - Epoch(train) [41][ 980/2569] lr: 4.0000e-02 eta: 20:52:25 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 3.0833 loss: 2.4351 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4351 2023/06/05 00:05:24 - mmengine - INFO - Epoch(train) [41][1000/2569] lr: 4.0000e-02 eta: 20:52:19 time: 0.2583 data_time: 0.0074 memory: 5828 grad_norm: 3.0826 loss: 2.5767 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5767 2023/06/05 00:05:29 - mmengine - INFO - Epoch(train) [41][1020/2569] lr: 4.0000e-02 eta: 20:52:14 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 3.0374 loss: 2.7807 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7807 2023/06/05 00:05:35 - mmengine - INFO - Epoch(train) [41][1040/2569] lr: 4.0000e-02 eta: 20:52:08 time: 0.2602 data_time: 0.0077 memory: 5828 grad_norm: 3.0686 loss: 2.6023 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6023 2023/06/05 00:05:40 - mmengine - INFO - Epoch(train) [41][1060/2569] lr: 4.0000e-02 eta: 20:52:03 time: 0.2651 data_time: 0.0075 memory: 5828 grad_norm: 3.1041 loss: 2.5398 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5398 2023/06/05 00:05:45 - mmengine - INFO - Epoch(train) [41][1080/2569] lr: 4.0000e-02 eta: 20:51:57 time: 0.2574 data_time: 0.0083 memory: 5828 grad_norm: 3.0544 loss: 2.4357 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4357 2023/06/05 00:05:51 - mmengine - INFO - Epoch(train) [41][1100/2569] lr: 4.0000e-02 eta: 20:51:52 time: 0.2793 data_time: 0.0074 memory: 5828 grad_norm: 3.0817 loss: 2.5488 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5488 2023/06/05 00:05:56 - mmengine - INFO - Epoch(train) [41][1120/2569] lr: 4.0000e-02 eta: 20:51:47 time: 0.2570 data_time: 0.0085 memory: 5828 grad_norm: 3.1254 loss: 2.7113 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7113 2023/06/05 00:06:01 - mmengine - INFO - Epoch(train) [41][1140/2569] lr: 4.0000e-02 eta: 20:51:41 time: 0.2651 data_time: 0.0077 memory: 5828 grad_norm: 3.1933 loss: 2.8066 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8066 2023/06/05 00:06:06 - mmengine - INFO - Epoch(train) [41][1160/2569] lr: 4.0000e-02 eta: 20:51:35 time: 0.2574 data_time: 0.0080 memory: 5828 grad_norm: 3.0800 loss: 2.4672 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4672 2023/06/05 00:06:12 - mmengine - INFO - Epoch(train) [41][1180/2569] lr: 4.0000e-02 eta: 20:51:30 time: 0.2641 data_time: 0.0078 memory: 5828 grad_norm: 3.0470 loss: 2.3585 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3585 2023/06/05 00:06:17 - mmengine - INFO - Epoch(train) [41][1200/2569] lr: 4.0000e-02 eta: 20:51:24 time: 0.2608 data_time: 0.0080 memory: 5828 grad_norm: 3.1320 loss: 2.5922 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5922 2023/06/05 00:06:22 - mmengine - INFO - Epoch(train) [41][1220/2569] lr: 4.0000e-02 eta: 20:51:18 time: 0.2595 data_time: 0.0079 memory: 5828 grad_norm: 3.0909 loss: 2.4346 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4346 2023/06/05 00:06:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:06:27 - mmengine - INFO - Epoch(train) [41][1240/2569] lr: 4.0000e-02 eta: 20:51:13 time: 0.2609 data_time: 0.0079 memory: 5828 grad_norm: 3.0091 loss: 2.3979 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3979 2023/06/05 00:06:32 - mmengine - INFO - Epoch(train) [41][1260/2569] lr: 4.0000e-02 eta: 20:51:07 time: 0.2596 data_time: 0.0076 memory: 5828 grad_norm: 3.1224 loss: 2.7237 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7237 2023/06/05 00:06:38 - mmengine - INFO - Epoch(train) [41][1280/2569] lr: 4.0000e-02 eta: 20:51:01 time: 0.2598 data_time: 0.0081 memory: 5828 grad_norm: 3.0902 loss: 2.5165 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5165 2023/06/05 00:06:43 - mmengine - INFO - Epoch(train) [41][1300/2569] lr: 4.0000e-02 eta: 20:50:56 time: 0.2634 data_time: 0.0078 memory: 5828 grad_norm: 3.1006 loss: 2.5071 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.5071 2023/06/05 00:06:48 - mmengine - INFO - Epoch(train) [41][1320/2569] lr: 4.0000e-02 eta: 20:50:50 time: 0.2603 data_time: 0.0079 memory: 5828 grad_norm: 3.0502 loss: 2.7026 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7026 2023/06/05 00:06:53 - mmengine - INFO - Epoch(train) [41][1340/2569] lr: 4.0000e-02 eta: 20:50:44 time: 0.2615 data_time: 0.0078 memory: 5828 grad_norm: 3.1000 loss: 2.5125 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5125 2023/06/05 00:06:58 - mmengine - INFO - Epoch(train) [41][1360/2569] lr: 4.0000e-02 eta: 20:50:39 time: 0.2583 data_time: 0.0082 memory: 5828 grad_norm: 3.0801 loss: 2.2017 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2017 2023/06/05 00:07:04 - mmengine - INFO - Epoch(train) [41][1380/2569] lr: 4.0000e-02 eta: 20:50:33 time: 0.2612 data_time: 0.0078 memory: 5828 grad_norm: 3.0733 loss: 2.4563 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4563 2023/06/05 00:07:09 - mmengine - INFO - Epoch(train) [41][1400/2569] lr: 4.0000e-02 eta: 20:50:27 time: 0.2611 data_time: 0.0086 memory: 5828 grad_norm: 3.0497 loss: 2.6702 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6702 2023/06/05 00:07:14 - mmengine - INFO - Epoch(train) [41][1420/2569] lr: 4.0000e-02 eta: 20:50:22 time: 0.2645 data_time: 0.0078 memory: 5828 grad_norm: 3.0527 loss: 2.6223 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6223 2023/06/05 00:07:19 - mmengine - INFO - Epoch(train) [41][1440/2569] lr: 4.0000e-02 eta: 20:50:16 time: 0.2614 data_time: 0.0083 memory: 5828 grad_norm: 3.1328 loss: 2.5117 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5117 2023/06/05 00:07:25 - mmengine - INFO - Epoch(train) [41][1460/2569] lr: 4.0000e-02 eta: 20:50:11 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 3.0015 loss: 2.4608 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4608 2023/06/05 00:07:30 - mmengine - INFO - Epoch(train) [41][1480/2569] lr: 4.0000e-02 eta: 20:50:05 time: 0.2608 data_time: 0.0079 memory: 5828 grad_norm: 3.0840 loss: 2.4399 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4399 2023/06/05 00:07:35 - mmengine - INFO - Epoch(train) [41][1500/2569] lr: 4.0000e-02 eta: 20:50:00 time: 0.2577 data_time: 0.0084 memory: 5828 grad_norm: 3.2039 loss: 2.6904 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6904 2023/06/05 00:07:40 - mmengine - INFO - Epoch(train) [41][1520/2569] lr: 4.0000e-02 eta: 20:49:54 time: 0.2618 data_time: 0.0084 memory: 5828 grad_norm: 3.0604 loss: 2.7019 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7019 2023/06/05 00:07:46 - mmengine - INFO - Epoch(train) [41][1540/2569] lr: 4.0000e-02 eta: 20:49:48 time: 0.2583 data_time: 0.0081 memory: 5828 grad_norm: 3.0818 loss: 2.5079 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5079 2023/06/05 00:07:51 - mmengine - INFO - Epoch(train) [41][1560/2569] lr: 4.0000e-02 eta: 20:49:43 time: 0.2686 data_time: 0.0078 memory: 5828 grad_norm: 3.0603 loss: 2.6103 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6103 2023/06/05 00:07:56 - mmengine - INFO - Epoch(train) [41][1580/2569] lr: 4.0000e-02 eta: 20:49:37 time: 0.2575 data_time: 0.0077 memory: 5828 grad_norm: 3.0266 loss: 2.4918 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4918 2023/06/05 00:08:01 - mmengine - INFO - Epoch(train) [41][1600/2569] lr: 4.0000e-02 eta: 20:49:31 time: 0.2622 data_time: 0.0082 memory: 5828 grad_norm: 3.1280 loss: 2.7513 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7513 2023/06/05 00:08:07 - mmengine - INFO - Epoch(train) [41][1620/2569] lr: 4.0000e-02 eta: 20:49:26 time: 0.2578 data_time: 0.0075 memory: 5828 grad_norm: 3.1274 loss: 2.7240 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7240 2023/06/05 00:08:12 - mmengine - INFO - Epoch(train) [41][1640/2569] lr: 4.0000e-02 eta: 20:49:20 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 3.0532 loss: 2.8860 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8860 2023/06/05 00:08:17 - mmengine - INFO - Epoch(train) [41][1660/2569] lr: 4.0000e-02 eta: 20:49:14 time: 0.2618 data_time: 0.0079 memory: 5828 grad_norm: 3.0203 loss: 2.7355 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7355 2023/06/05 00:08:22 - mmengine - INFO - Epoch(train) [41][1680/2569] lr: 4.0000e-02 eta: 20:49:09 time: 0.2663 data_time: 0.0077 memory: 5828 grad_norm: 3.1135 loss: 2.5715 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5715 2023/06/05 00:08:28 - mmengine - INFO - Epoch(train) [41][1700/2569] lr: 4.0000e-02 eta: 20:49:04 time: 0.2663 data_time: 0.0072 memory: 5828 grad_norm: 3.0935 loss: 2.3205 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3205 2023/06/05 00:08:33 - mmengine - INFO - Epoch(train) [41][1720/2569] lr: 4.0000e-02 eta: 20:48:58 time: 0.2649 data_time: 0.0080 memory: 5828 grad_norm: 3.0856 loss: 2.4391 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4391 2023/06/05 00:08:38 - mmengine - INFO - Epoch(train) [41][1740/2569] lr: 4.0000e-02 eta: 20:48:53 time: 0.2579 data_time: 0.0081 memory: 5828 grad_norm: 3.0528 loss: 2.4631 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4631 2023/06/05 00:08:43 - mmengine - INFO - Epoch(train) [41][1760/2569] lr: 4.0000e-02 eta: 20:48:47 time: 0.2621 data_time: 0.0082 memory: 5828 grad_norm: 3.0542 loss: 2.4638 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4638 2023/06/05 00:08:49 - mmengine - INFO - Epoch(train) [41][1780/2569] lr: 4.0000e-02 eta: 20:48:41 time: 0.2600 data_time: 0.0083 memory: 5828 grad_norm: 3.0240 loss: 2.6441 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6441 2023/06/05 00:08:54 - mmengine - INFO - Epoch(train) [41][1800/2569] lr: 4.0000e-02 eta: 20:48:36 time: 0.2653 data_time: 0.0084 memory: 5828 grad_norm: 3.0686 loss: 2.5087 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5087 2023/06/05 00:08:59 - mmengine - INFO - Epoch(train) [41][1820/2569] lr: 4.0000e-02 eta: 20:48:30 time: 0.2629 data_time: 0.0081 memory: 5828 grad_norm: 3.0721 loss: 2.5958 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5958 2023/06/05 00:09:04 - mmengine - INFO - Epoch(train) [41][1840/2569] lr: 4.0000e-02 eta: 20:48:25 time: 0.2605 data_time: 0.0078 memory: 5828 grad_norm: 3.0742 loss: 2.3712 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3712 2023/06/05 00:09:10 - mmengine - INFO - Epoch(train) [41][1860/2569] lr: 4.0000e-02 eta: 20:48:19 time: 0.2653 data_time: 0.0078 memory: 5828 grad_norm: 3.0786 loss: 2.7235 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7235 2023/06/05 00:09:15 - mmengine - INFO - Epoch(train) [41][1880/2569] lr: 4.0000e-02 eta: 20:48:14 time: 0.2689 data_time: 0.0078 memory: 5828 grad_norm: 3.0472 loss: 2.5204 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5204 2023/06/05 00:09:20 - mmengine - INFO - Epoch(train) [41][1900/2569] lr: 4.0000e-02 eta: 20:48:08 time: 0.2623 data_time: 0.0079 memory: 5828 grad_norm: 3.0735 loss: 2.4515 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4515 2023/06/05 00:09:26 - mmengine - INFO - Epoch(train) [41][1920/2569] lr: 4.0000e-02 eta: 20:48:03 time: 0.2652 data_time: 0.0084 memory: 5828 grad_norm: 3.0941 loss: 2.4910 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4910 2023/06/05 00:09:31 - mmengine - INFO - Epoch(train) [41][1940/2569] lr: 4.0000e-02 eta: 20:47:57 time: 0.2620 data_time: 0.0079 memory: 5828 grad_norm: 3.0907 loss: 2.6038 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6038 2023/06/05 00:09:36 - mmengine - INFO - Epoch(train) [41][1960/2569] lr: 4.0000e-02 eta: 20:47:51 time: 0.2573 data_time: 0.0080 memory: 5828 grad_norm: 3.0721 loss: 2.5328 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5328 2023/06/05 00:09:41 - mmengine - INFO - Epoch(train) [41][1980/2569] lr: 4.0000e-02 eta: 20:47:46 time: 0.2640 data_time: 0.0076 memory: 5828 grad_norm: 3.1316 loss: 2.5646 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5646 2023/06/05 00:09:46 - mmengine - INFO - Epoch(train) [41][2000/2569] lr: 4.0000e-02 eta: 20:47:40 time: 0.2558 data_time: 0.0078 memory: 5828 grad_norm: 3.0649 loss: 2.4460 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4460 2023/06/05 00:09:52 - mmengine - INFO - Epoch(train) [41][2020/2569] lr: 4.0000e-02 eta: 20:47:35 time: 0.2637 data_time: 0.0077 memory: 5828 grad_norm: 3.1341 loss: 2.4485 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4485 2023/06/05 00:09:57 - mmengine - INFO - Epoch(train) [41][2040/2569] lr: 4.0000e-02 eta: 20:47:29 time: 0.2578 data_time: 0.0081 memory: 5828 grad_norm: 3.0983 loss: 2.6418 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6418 2023/06/05 00:10:02 - mmengine - INFO - Epoch(train) [41][2060/2569] lr: 4.0000e-02 eta: 20:47:23 time: 0.2589 data_time: 0.0072 memory: 5828 grad_norm: 3.0915 loss: 2.6400 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6400 2023/06/05 00:10:07 - mmengine - INFO - Epoch(train) [41][2080/2569] lr: 4.0000e-02 eta: 20:47:17 time: 0.2573 data_time: 0.0077 memory: 5828 grad_norm: 3.0342 loss: 2.8998 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8998 2023/06/05 00:10:12 - mmengine - INFO - Epoch(train) [41][2100/2569] lr: 4.0000e-02 eta: 20:47:12 time: 0.2618 data_time: 0.0080 memory: 5828 grad_norm: 3.1078 loss: 2.5435 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5435 2023/06/05 00:10:18 - mmengine - INFO - Epoch(train) [41][2120/2569] lr: 4.0000e-02 eta: 20:47:06 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 3.0660 loss: 2.4990 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4990 2023/06/05 00:10:23 - mmengine - INFO - Epoch(train) [41][2140/2569] lr: 4.0000e-02 eta: 20:47:01 time: 0.2743 data_time: 0.0078 memory: 5828 grad_norm: 3.1143 loss: 2.2877 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2877 2023/06/05 00:10:29 - mmengine - INFO - Epoch(train) [41][2160/2569] lr: 4.0000e-02 eta: 20:46:56 time: 0.2786 data_time: 0.0078 memory: 5828 grad_norm: 3.0834 loss: 2.3110 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3110 2023/06/05 00:10:34 - mmengine - INFO - Epoch(train) [41][2180/2569] lr: 4.0000e-02 eta: 20:46:51 time: 0.2688 data_time: 0.0079 memory: 5828 grad_norm: 3.1338 loss: 2.8298 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8298 2023/06/05 00:10:40 - mmengine - INFO - Epoch(train) [41][2200/2569] lr: 4.0000e-02 eta: 20:46:46 time: 0.2681 data_time: 0.0077 memory: 5828 grad_norm: 3.0709 loss: 2.4544 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4544 2023/06/05 00:10:45 - mmengine - INFO - Epoch(train) [41][2220/2569] lr: 4.0000e-02 eta: 20:46:40 time: 0.2615 data_time: 0.0078 memory: 5828 grad_norm: 3.1238 loss: 2.2627 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2627 2023/06/05 00:10:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:10:50 - mmengine - INFO - Epoch(train) [41][2240/2569] lr: 4.0000e-02 eta: 20:46:35 time: 0.2659 data_time: 0.0078 memory: 5828 grad_norm: 3.1037 loss: 2.9055 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9055 2023/06/05 00:10:55 - mmengine - INFO - Epoch(train) [41][2260/2569] lr: 4.0000e-02 eta: 20:46:29 time: 0.2632 data_time: 0.0078 memory: 5828 grad_norm: 3.0989 loss: 2.6996 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.6996 2023/06/05 00:11:01 - mmengine - INFO - Epoch(train) [41][2280/2569] lr: 4.0000e-02 eta: 20:46:24 time: 0.2648 data_time: 0.0080 memory: 5828 grad_norm: 3.0883 loss: 2.6410 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6410 2023/06/05 00:11:06 - mmengine - INFO - Epoch(train) [41][2300/2569] lr: 4.0000e-02 eta: 20:46:18 time: 0.2599 data_time: 0.0082 memory: 5828 grad_norm: 3.0802 loss: 2.6517 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6517 2023/06/05 00:11:11 - mmengine - INFO - Epoch(train) [41][2320/2569] lr: 4.0000e-02 eta: 20:46:13 time: 0.2620 data_time: 0.0078 memory: 5828 grad_norm: 3.1617 loss: 2.8326 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8326 2023/06/05 00:11:16 - mmengine - INFO - Epoch(train) [41][2340/2569] lr: 4.0000e-02 eta: 20:46:07 time: 0.2626 data_time: 0.0071 memory: 5828 grad_norm: 3.0689 loss: 2.2204 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2204 2023/06/05 00:11:22 - mmengine - INFO - Epoch(train) [41][2360/2569] lr: 4.0000e-02 eta: 20:46:01 time: 0.2630 data_time: 0.0079 memory: 5828 grad_norm: 3.1157 loss: 2.6619 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6619 2023/06/05 00:11:27 - mmengine - INFO - Epoch(train) [41][2380/2569] lr: 4.0000e-02 eta: 20:45:56 time: 0.2637 data_time: 0.0079 memory: 5828 grad_norm: 3.1227 loss: 2.7085 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7085 2023/06/05 00:11:32 - mmengine - INFO - Epoch(train) [41][2400/2569] lr: 4.0000e-02 eta: 20:45:50 time: 0.2594 data_time: 0.0079 memory: 5828 grad_norm: 3.1805 loss: 2.5696 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5696 2023/06/05 00:11:37 - mmengine - INFO - Epoch(train) [41][2420/2569] lr: 4.0000e-02 eta: 20:45:45 time: 0.2689 data_time: 0.0078 memory: 5828 grad_norm: 3.1447 loss: 2.5736 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5736 2023/06/05 00:11:43 - mmengine - INFO - Epoch(train) [41][2440/2569] lr: 4.0000e-02 eta: 20:45:39 time: 0.2630 data_time: 0.0083 memory: 5828 grad_norm: 3.0951 loss: 2.5479 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5479 2023/06/05 00:11:48 - mmengine - INFO - Epoch(train) [41][2460/2569] lr: 4.0000e-02 eta: 20:45:35 time: 0.2758 data_time: 0.0079 memory: 5828 grad_norm: 3.1265 loss: 2.6500 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6500 2023/06/05 00:11:53 - mmengine - INFO - Epoch(train) [41][2480/2569] lr: 4.0000e-02 eta: 20:45:29 time: 0.2575 data_time: 0.0079 memory: 5828 grad_norm: 3.1081 loss: 2.5953 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5953 2023/06/05 00:11:59 - mmengine - INFO - Epoch(train) [41][2500/2569] lr: 4.0000e-02 eta: 20:45:24 time: 0.2781 data_time: 0.0080 memory: 5828 grad_norm: 3.0006 loss: 2.6695 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6695 2023/06/05 00:12:04 - mmengine - INFO - Epoch(train) [41][2520/2569] lr: 4.0000e-02 eta: 20:45:18 time: 0.2616 data_time: 0.0077 memory: 5828 grad_norm: 3.1357 loss: 2.5137 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5137 2023/06/05 00:12:10 - mmengine - INFO - Epoch(train) [41][2540/2569] lr: 4.0000e-02 eta: 20:45:13 time: 0.2671 data_time: 0.0075 memory: 5828 grad_norm: 3.0087 loss: 2.6776 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6776 2023/06/05 00:12:15 - mmengine - INFO - Epoch(train) [41][2560/2569] lr: 4.0000e-02 eta: 20:45:07 time: 0.2594 data_time: 0.0083 memory: 5828 grad_norm: 3.0787 loss: 2.5269 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5269 2023/06/05 00:12:17 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:12:17 - mmengine - INFO - Epoch(train) [41][2569/2569] lr: 4.0000e-02 eta: 20:45:04 time: 0.2550 data_time: 0.0080 memory: 5828 grad_norm: 3.1171 loss: 2.5103 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.5103 2023/06/05 00:12:24 - mmengine - INFO - Epoch(train) [42][ 20/2569] lr: 4.0000e-02 eta: 20:45:03 time: 0.3316 data_time: 0.0600 memory: 5828 grad_norm: 3.0530 loss: 2.4268 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4268 2023/06/05 00:12:29 - mmengine - INFO - Epoch(train) [42][ 40/2569] lr: 4.0000e-02 eta: 20:44:57 time: 0.2683 data_time: 0.0081 memory: 5828 grad_norm: 3.0704 loss: 2.6931 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6931 2023/06/05 00:12:34 - mmengine - INFO - Epoch(train) [42][ 60/2569] lr: 4.0000e-02 eta: 20:44:52 time: 0.2604 data_time: 0.0078 memory: 5828 grad_norm: 3.1157 loss: 2.4843 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4843 2023/06/05 00:12:40 - mmengine - INFO - Epoch(train) [42][ 80/2569] lr: 4.0000e-02 eta: 20:44:47 time: 0.2715 data_time: 0.0082 memory: 5828 grad_norm: 3.0170 loss: 2.7378 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7378 2023/06/05 00:12:45 - mmengine - INFO - Epoch(train) [42][ 100/2569] lr: 4.0000e-02 eta: 20:44:42 time: 0.2762 data_time: 0.0084 memory: 5828 grad_norm: 3.1253 loss: 2.3165 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3165 2023/06/05 00:12:51 - mmengine - INFO - Epoch(train) [42][ 120/2569] lr: 4.0000e-02 eta: 20:44:37 time: 0.2750 data_time: 0.0077 memory: 5828 grad_norm: 3.0857 loss: 2.6602 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6602 2023/06/05 00:12:56 - mmengine - INFO - Epoch(train) [42][ 140/2569] lr: 4.0000e-02 eta: 20:44:31 time: 0.2601 data_time: 0.0077 memory: 5828 grad_norm: 3.1639 loss: 2.7227 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7227 2023/06/05 00:13:01 - mmengine - INFO - Epoch(train) [42][ 160/2569] lr: 4.0000e-02 eta: 20:44:25 time: 0.2604 data_time: 0.0080 memory: 5828 grad_norm: 3.0655 loss: 2.6781 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6781 2023/06/05 00:13:06 - mmengine - INFO - Epoch(train) [42][ 180/2569] lr: 4.0000e-02 eta: 20:44:20 time: 0.2630 data_time: 0.0080 memory: 5828 grad_norm: 3.1283 loss: 2.2712 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2712 2023/06/05 00:13:12 - mmengine - INFO - Epoch(train) [42][ 200/2569] lr: 4.0000e-02 eta: 20:44:15 time: 0.2661 data_time: 0.0081 memory: 5828 grad_norm: 3.1199 loss: 2.4296 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4296 2023/06/05 00:13:17 - mmengine - INFO - Epoch(train) [42][ 220/2569] lr: 4.0000e-02 eta: 20:44:09 time: 0.2608 data_time: 0.0079 memory: 5828 grad_norm: 3.0733 loss: 2.6110 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6110 2023/06/05 00:13:22 - mmengine - INFO - Epoch(train) [42][ 240/2569] lr: 4.0000e-02 eta: 20:44:03 time: 0.2585 data_time: 0.0081 memory: 5828 grad_norm: 3.1934 loss: 2.4918 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4918 2023/06/05 00:13:27 - mmengine - INFO - Epoch(train) [42][ 260/2569] lr: 4.0000e-02 eta: 20:43:58 time: 0.2692 data_time: 0.0083 memory: 5828 grad_norm: 3.0611 loss: 2.5381 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5381 2023/06/05 00:13:33 - mmengine - INFO - Epoch(train) [42][ 280/2569] lr: 4.0000e-02 eta: 20:43:52 time: 0.2593 data_time: 0.0080 memory: 5828 grad_norm: 3.0567 loss: 2.5836 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5836 2023/06/05 00:13:38 - mmengine - INFO - Epoch(train) [42][ 300/2569] lr: 4.0000e-02 eta: 20:43:46 time: 0.2578 data_time: 0.0085 memory: 5828 grad_norm: 3.0701 loss: 2.4523 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4523 2023/06/05 00:13:43 - mmengine - INFO - Epoch(train) [42][ 320/2569] lr: 4.0000e-02 eta: 20:43:41 time: 0.2598 data_time: 0.0072 memory: 5828 grad_norm: 3.0713 loss: 2.4135 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4135 2023/06/05 00:13:48 - mmengine - INFO - Epoch(train) [42][ 340/2569] lr: 4.0000e-02 eta: 20:43:35 time: 0.2575 data_time: 0.0080 memory: 5828 grad_norm: 3.0341 loss: 3.0036 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.0036 2023/06/05 00:13:54 - mmengine - INFO - Epoch(train) [42][ 360/2569] lr: 4.0000e-02 eta: 20:43:30 time: 0.2683 data_time: 0.0076 memory: 5828 grad_norm: 3.0244 loss: 2.3346 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3346 2023/06/05 00:13:59 - mmengine - INFO - Epoch(train) [42][ 380/2569] lr: 4.0000e-02 eta: 20:43:24 time: 0.2624 data_time: 0.0078 memory: 5828 grad_norm: 3.0667 loss: 2.4424 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4424 2023/06/05 00:14:04 - mmengine - INFO - Epoch(train) [42][ 400/2569] lr: 4.0000e-02 eta: 20:43:18 time: 0.2571 data_time: 0.0077 memory: 5828 grad_norm: 3.0456 loss: 2.6044 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6044 2023/06/05 00:14:09 - mmengine - INFO - Epoch(train) [42][ 420/2569] lr: 4.0000e-02 eta: 20:43:12 time: 0.2563 data_time: 0.0076 memory: 5828 grad_norm: 3.1077 loss: 2.3560 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3560 2023/06/05 00:14:14 - mmengine - INFO - Epoch(train) [42][ 440/2569] lr: 4.0000e-02 eta: 20:43:07 time: 0.2633 data_time: 0.0077 memory: 5828 grad_norm: 3.0420 loss: 2.9231 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9231 2023/06/05 00:14:20 - mmengine - INFO - Epoch(train) [42][ 460/2569] lr: 4.0000e-02 eta: 20:43:01 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 3.1142 loss: 2.4837 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4837 2023/06/05 00:14:25 - mmengine - INFO - Epoch(train) [42][ 480/2569] lr: 4.0000e-02 eta: 20:42:55 time: 0.2574 data_time: 0.0080 memory: 5828 grad_norm: 3.1092 loss: 2.6312 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6312 2023/06/05 00:14:30 - mmengine - INFO - Epoch(train) [42][ 500/2569] lr: 4.0000e-02 eta: 20:42:50 time: 0.2663 data_time: 0.0079 memory: 5828 grad_norm: 3.1755 loss: 2.8781 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8781 2023/06/05 00:14:35 - mmengine - INFO - Epoch(train) [42][ 520/2569] lr: 4.0000e-02 eta: 20:42:45 time: 0.2654 data_time: 0.0085 memory: 5828 grad_norm: 3.0240 loss: 2.5675 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5675 2023/06/05 00:14:41 - mmengine - INFO - Epoch(train) [42][ 540/2569] lr: 4.0000e-02 eta: 20:42:39 time: 0.2663 data_time: 0.0078 memory: 5828 grad_norm: 3.1090 loss: 2.5700 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5700 2023/06/05 00:14:46 - mmengine - INFO - Epoch(train) [42][ 560/2569] lr: 4.0000e-02 eta: 20:42:34 time: 0.2649 data_time: 0.0078 memory: 5828 grad_norm: 3.0619 loss: 2.4213 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4213 2023/06/05 00:14:51 - mmengine - INFO - Epoch(train) [42][ 580/2569] lr: 4.0000e-02 eta: 20:42:28 time: 0.2613 data_time: 0.0078 memory: 5828 grad_norm: 3.1158 loss: 2.1619 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1619 2023/06/05 00:14:57 - mmengine - INFO - Epoch(train) [42][ 600/2569] lr: 4.0000e-02 eta: 20:42:23 time: 0.2614 data_time: 0.0075 memory: 5828 grad_norm: 3.0202 loss: 2.5050 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5050 2023/06/05 00:15:02 - mmengine - INFO - Epoch(train) [42][ 620/2569] lr: 4.0000e-02 eta: 20:42:17 time: 0.2566 data_time: 0.0077 memory: 5828 grad_norm: 3.1245 loss: 2.4090 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4090 2023/06/05 00:15:07 - mmengine - INFO - Epoch(train) [42][ 640/2569] lr: 4.0000e-02 eta: 20:42:12 time: 0.2701 data_time: 0.0083 memory: 5828 grad_norm: 3.1173 loss: 2.4154 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4154 2023/06/05 00:15:12 - mmengine - INFO - Epoch(train) [42][ 660/2569] lr: 4.0000e-02 eta: 20:42:06 time: 0.2584 data_time: 0.0077 memory: 5828 grad_norm: 3.0926 loss: 2.4509 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4509 2023/06/05 00:15:15 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:15:17 - mmengine - INFO - Epoch(train) [42][ 680/2569] lr: 4.0000e-02 eta: 20:42:00 time: 0.2627 data_time: 0.0085 memory: 5828 grad_norm: 3.1073 loss: 2.8016 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.8016 2023/06/05 00:15:23 - mmengine - INFO - Epoch(train) [42][ 700/2569] lr: 4.0000e-02 eta: 20:41:54 time: 0.2593 data_time: 0.0076 memory: 5828 grad_norm: 3.1569 loss: 2.4918 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4918 2023/06/05 00:15:28 - mmengine - INFO - Epoch(train) [42][ 720/2569] lr: 4.0000e-02 eta: 20:41:49 time: 0.2608 data_time: 0.0080 memory: 5828 grad_norm: 3.0658 loss: 2.7205 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7205 2023/06/05 00:15:33 - mmengine - INFO - Epoch(train) [42][ 740/2569] lr: 4.0000e-02 eta: 20:41:43 time: 0.2610 data_time: 0.0076 memory: 5828 grad_norm: 3.0394 loss: 2.7186 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7186 2023/06/05 00:15:39 - mmengine - INFO - Epoch(train) [42][ 760/2569] lr: 4.0000e-02 eta: 20:41:38 time: 0.2687 data_time: 0.0076 memory: 5828 grad_norm: 3.0812 loss: 2.6521 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6521 2023/06/05 00:15:44 - mmengine - INFO - Epoch(train) [42][ 780/2569] lr: 4.0000e-02 eta: 20:41:32 time: 0.2573 data_time: 0.0081 memory: 5828 grad_norm: 3.0623 loss: 2.8213 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8213 2023/06/05 00:15:49 - mmengine - INFO - Epoch(train) [42][ 800/2569] lr: 4.0000e-02 eta: 20:41:26 time: 0.2571 data_time: 0.0077 memory: 5828 grad_norm: 3.0397 loss: 2.2384 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2384 2023/06/05 00:15:54 - mmengine - INFO - Epoch(train) [42][ 820/2569] lr: 4.0000e-02 eta: 20:41:21 time: 0.2586 data_time: 0.0081 memory: 5828 grad_norm: 3.0806 loss: 2.8090 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8090 2023/06/05 00:15:59 - mmengine - INFO - Epoch(train) [42][ 840/2569] lr: 4.0000e-02 eta: 20:41:15 time: 0.2570 data_time: 0.0075 memory: 5828 grad_norm: 3.1157 loss: 2.5192 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5192 2023/06/05 00:16:04 - mmengine - INFO - Epoch(train) [42][ 860/2569] lr: 4.0000e-02 eta: 20:41:09 time: 0.2566 data_time: 0.0077 memory: 5828 grad_norm: 3.0934 loss: 2.5724 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5724 2023/06/05 00:16:09 - mmengine - INFO - Epoch(train) [42][ 880/2569] lr: 4.0000e-02 eta: 20:41:03 time: 0.2571 data_time: 0.0076 memory: 5828 grad_norm: 3.0962 loss: 2.5012 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5012 2023/06/05 00:16:15 - mmengine - INFO - Epoch(train) [42][ 900/2569] lr: 4.0000e-02 eta: 20:40:58 time: 0.2683 data_time: 0.0078 memory: 5828 grad_norm: 3.0730 loss: 2.6840 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6840 2023/06/05 00:16:20 - mmengine - INFO - Epoch(train) [42][ 920/2569] lr: 4.0000e-02 eta: 20:40:52 time: 0.2627 data_time: 0.0078 memory: 5828 grad_norm: 3.1199 loss: 2.7334 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7334 2023/06/05 00:16:25 - mmengine - INFO - Epoch(train) [42][ 940/2569] lr: 4.0000e-02 eta: 20:40:47 time: 0.2680 data_time: 0.0077 memory: 5828 grad_norm: 3.0903 loss: 2.3199 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3199 2023/06/05 00:16:31 - mmengine - INFO - Epoch(train) [42][ 960/2569] lr: 4.0000e-02 eta: 20:40:41 time: 0.2628 data_time: 0.0079 memory: 5828 grad_norm: 3.0972 loss: 2.4320 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4320 2023/06/05 00:16:36 - mmengine - INFO - Epoch(train) [42][ 980/2569] lr: 4.0000e-02 eta: 20:40:36 time: 0.2681 data_time: 0.0073 memory: 5828 grad_norm: 3.0703 loss: 2.6324 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6324 2023/06/05 00:16:41 - mmengine - INFO - Epoch(train) [42][1000/2569] lr: 4.0000e-02 eta: 20:40:30 time: 0.2571 data_time: 0.0081 memory: 5828 grad_norm: 3.1184 loss: 2.2291 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2291 2023/06/05 00:16:46 - mmengine - INFO - Epoch(train) [42][1020/2569] lr: 4.0000e-02 eta: 20:40:24 time: 0.2571 data_time: 0.0083 memory: 5828 grad_norm: 3.1046 loss: 2.6081 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.6081 2023/06/05 00:16:51 - mmengine - INFO - Epoch(train) [42][1040/2569] lr: 4.0000e-02 eta: 20:40:19 time: 0.2578 data_time: 0.0082 memory: 5828 grad_norm: 3.0992 loss: 2.3661 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3661 2023/06/05 00:16:57 - mmengine - INFO - Epoch(train) [42][1060/2569] lr: 4.0000e-02 eta: 20:40:13 time: 0.2641 data_time: 0.0077 memory: 5828 grad_norm: 3.0783 loss: 2.6829 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6829 2023/06/05 00:17:02 - mmengine - INFO - Epoch(train) [42][1080/2569] lr: 4.0000e-02 eta: 20:40:08 time: 0.2676 data_time: 0.0079 memory: 5828 grad_norm: 3.1018 loss: 2.5819 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5819 2023/06/05 00:17:07 - mmengine - INFO - Epoch(train) [42][1100/2569] lr: 4.0000e-02 eta: 20:40:02 time: 0.2648 data_time: 0.0078 memory: 5828 grad_norm: 3.0354 loss: 2.5920 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5920 2023/06/05 00:17:13 - mmengine - INFO - Epoch(train) [42][1120/2569] lr: 4.0000e-02 eta: 20:39:57 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 3.1022 loss: 2.7191 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7191 2023/06/05 00:17:18 - mmengine - INFO - Epoch(train) [42][1140/2569] lr: 4.0000e-02 eta: 20:39:51 time: 0.2629 data_time: 0.0083 memory: 5828 grad_norm: 3.1288 loss: 2.4271 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4271 2023/06/05 00:17:23 - mmengine - INFO - Epoch(train) [42][1160/2569] lr: 4.0000e-02 eta: 20:39:46 time: 0.2588 data_time: 0.0077 memory: 5828 grad_norm: 3.1120 loss: 2.5765 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5765 2023/06/05 00:17:29 - mmengine - INFO - Epoch(train) [42][1180/2569] lr: 4.0000e-02 eta: 20:39:41 time: 0.2739 data_time: 0.0075 memory: 5828 grad_norm: 2.9990 loss: 2.5543 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5543 2023/06/05 00:17:34 - mmengine - INFO - Epoch(train) [42][1200/2569] lr: 4.0000e-02 eta: 20:39:35 time: 0.2626 data_time: 0.0077 memory: 5828 grad_norm: 3.0975 loss: 2.4184 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4184 2023/06/05 00:17:39 - mmengine - INFO - Epoch(train) [42][1220/2569] lr: 4.0000e-02 eta: 20:39:30 time: 0.2694 data_time: 0.0078 memory: 5828 grad_norm: 3.0884 loss: 2.5477 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5477 2023/06/05 00:17:44 - mmengine - INFO - Epoch(train) [42][1240/2569] lr: 4.0000e-02 eta: 20:39:24 time: 0.2576 data_time: 0.0084 memory: 5828 grad_norm: 3.0838 loss: 2.4709 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4709 2023/06/05 00:17:50 - mmengine - INFO - Epoch(train) [42][1260/2569] lr: 4.0000e-02 eta: 20:39:18 time: 0.2617 data_time: 0.0077 memory: 5828 grad_norm: 3.0607 loss: 2.7985 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7985 2023/06/05 00:17:55 - mmengine - INFO - Epoch(train) [42][1280/2569] lr: 4.0000e-02 eta: 20:39:13 time: 0.2697 data_time: 0.0082 memory: 5828 grad_norm: 3.0639 loss: 2.4514 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4514 2023/06/05 00:18:00 - mmengine - INFO - Epoch(train) [42][1300/2569] lr: 4.0000e-02 eta: 20:39:08 time: 0.2593 data_time: 0.0080 memory: 5828 grad_norm: 3.1449 loss: 2.5065 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5065 2023/06/05 00:18:06 - mmengine - INFO - Epoch(train) [42][1320/2569] lr: 4.0000e-02 eta: 20:39:02 time: 0.2648 data_time: 0.0080 memory: 5828 grad_norm: 3.0915 loss: 2.5760 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5760 2023/06/05 00:18:11 - mmengine - INFO - Epoch(train) [42][1340/2569] lr: 4.0000e-02 eta: 20:38:56 time: 0.2584 data_time: 0.0077 memory: 5828 grad_norm: 3.0650 loss: 2.6332 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6332 2023/06/05 00:18:16 - mmengine - INFO - Epoch(train) [42][1360/2569] lr: 4.0000e-02 eta: 20:38:52 time: 0.2793 data_time: 0.0074 memory: 5828 grad_norm: 3.1555 loss: 2.6791 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6791 2023/06/05 00:18:21 - mmengine - INFO - Epoch(train) [42][1380/2569] lr: 4.0000e-02 eta: 20:38:46 time: 0.2584 data_time: 0.0073 memory: 5828 grad_norm: 3.1054 loss: 2.6761 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6761 2023/06/05 00:18:27 - mmengine - INFO - Epoch(train) [42][1400/2569] lr: 4.0000e-02 eta: 20:38:41 time: 0.2750 data_time: 0.0076 memory: 5828 grad_norm: 3.0830 loss: 2.4522 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4522 2023/06/05 00:18:32 - mmengine - INFO - Epoch(train) [42][1420/2569] lr: 4.0000e-02 eta: 20:38:35 time: 0.2629 data_time: 0.0081 memory: 5828 grad_norm: 3.1189 loss: 2.6985 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6985 2023/06/05 00:18:37 - mmengine - INFO - Epoch(train) [42][1440/2569] lr: 4.0000e-02 eta: 20:38:30 time: 0.2569 data_time: 0.0083 memory: 5828 grad_norm: 3.0743 loss: 2.6370 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6370 2023/06/05 00:18:43 - mmengine - INFO - Epoch(train) [42][1460/2569] lr: 4.0000e-02 eta: 20:38:24 time: 0.2676 data_time: 0.0076 memory: 5828 grad_norm: 3.0615 loss: 2.5883 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5883 2023/06/05 00:18:48 - mmengine - INFO - Epoch(train) [42][1480/2569] lr: 4.0000e-02 eta: 20:38:19 time: 0.2672 data_time: 0.0075 memory: 5828 grad_norm: 3.1618 loss: 2.6610 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6610 2023/06/05 00:18:53 - mmengine - INFO - Epoch(train) [42][1500/2569] lr: 4.0000e-02 eta: 20:38:13 time: 0.2593 data_time: 0.0073 memory: 5828 grad_norm: 3.4401 loss: 2.5942 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5942 2023/06/05 00:18:59 - mmengine - INFO - Epoch(train) [42][1520/2569] lr: 4.0000e-02 eta: 20:38:08 time: 0.2640 data_time: 0.0077 memory: 5828 grad_norm: 3.1991 loss: 3.0613 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0613 2023/06/05 00:19:04 - mmengine - INFO - Epoch(train) [42][1540/2569] lr: 4.0000e-02 eta: 20:38:02 time: 0.2573 data_time: 0.0079 memory: 5828 grad_norm: 3.1043 loss: 2.7054 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7054 2023/06/05 00:19:09 - mmengine - INFO - Epoch(train) [42][1560/2569] lr: 4.0000e-02 eta: 20:37:57 time: 0.2725 data_time: 0.0084 memory: 5828 grad_norm: 3.1243 loss: 2.3069 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3069 2023/06/05 00:19:15 - mmengine - INFO - Epoch(train) [42][1580/2569] lr: 4.0000e-02 eta: 20:37:52 time: 0.2673 data_time: 0.0080 memory: 5828 grad_norm: 3.1256 loss: 2.4462 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4462 2023/06/05 00:19:20 - mmengine - INFO - Epoch(train) [42][1600/2569] lr: 4.0000e-02 eta: 20:37:46 time: 0.2607 data_time: 0.0077 memory: 5828 grad_norm: 3.1285 loss: 2.6142 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6142 2023/06/05 00:19:25 - mmengine - INFO - Epoch(train) [42][1620/2569] lr: 4.0000e-02 eta: 20:37:41 time: 0.2701 data_time: 0.0077 memory: 5828 grad_norm: 3.0659 loss: 2.3807 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3807 2023/06/05 00:19:30 - mmengine - INFO - Epoch(train) [42][1640/2569] lr: 4.0000e-02 eta: 20:37:35 time: 0.2570 data_time: 0.0081 memory: 5828 grad_norm: 3.1543 loss: 2.9811 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9811 2023/06/05 00:19:36 - mmengine - INFO - Epoch(train) [42][1660/2569] lr: 4.0000e-02 eta: 20:37:30 time: 0.2795 data_time: 0.0073 memory: 5828 grad_norm: 3.0953 loss: 2.5026 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5026 2023/06/05 00:19:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:19:41 - mmengine - INFO - Epoch(train) [42][1680/2569] lr: 4.0000e-02 eta: 20:37:24 time: 0.2568 data_time: 0.0079 memory: 5828 grad_norm: 3.0887 loss: 2.7667 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7667 2023/06/05 00:19:46 - mmengine - INFO - Epoch(train) [42][1700/2569] lr: 4.0000e-02 eta: 20:37:19 time: 0.2617 data_time: 0.0082 memory: 5828 grad_norm: 3.0818 loss: 2.5416 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5416 2023/06/05 00:19:51 - mmengine - INFO - Epoch(train) [42][1720/2569] lr: 4.0000e-02 eta: 20:37:13 time: 0.2582 data_time: 0.0073 memory: 5828 grad_norm: 3.0724 loss: 2.7186 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7186 2023/06/05 00:19:57 - mmengine - INFO - Epoch(train) [42][1740/2569] lr: 4.0000e-02 eta: 20:37:07 time: 0.2598 data_time: 0.0079 memory: 5828 grad_norm: 3.0831 loss: 2.6651 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6651 2023/06/05 00:20:02 - mmengine - INFO - Epoch(train) [42][1760/2569] lr: 4.0000e-02 eta: 20:37:02 time: 0.2591 data_time: 0.0085 memory: 5828 grad_norm: 3.1136 loss: 2.6262 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6262 2023/06/05 00:20:07 - mmengine - INFO - Epoch(train) [42][1780/2569] lr: 4.0000e-02 eta: 20:36:56 time: 0.2600 data_time: 0.0078 memory: 5828 grad_norm: 3.0994 loss: 2.2294 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2294 2023/06/05 00:20:12 - mmengine - INFO - Epoch(train) [42][1800/2569] lr: 4.0000e-02 eta: 20:36:50 time: 0.2644 data_time: 0.0077 memory: 5828 grad_norm: 3.0831 loss: 2.4350 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4350 2023/06/05 00:20:18 - mmengine - INFO - Epoch(train) [42][1820/2569] lr: 4.0000e-02 eta: 20:36:45 time: 0.2595 data_time: 0.0076 memory: 5828 grad_norm: 3.1663 loss: 2.8821 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8821 2023/06/05 00:20:23 - mmengine - INFO - Epoch(train) [42][1840/2569] lr: 4.0000e-02 eta: 20:36:39 time: 0.2618 data_time: 0.0076 memory: 5828 grad_norm: 3.1198 loss: 2.4649 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4649 2023/06/05 00:20:28 - mmengine - INFO - Epoch(train) [42][1860/2569] lr: 4.0000e-02 eta: 20:36:33 time: 0.2575 data_time: 0.0080 memory: 5828 grad_norm: 3.0807 loss: 2.8492 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8492 2023/06/05 00:20:33 - mmengine - INFO - Epoch(train) [42][1880/2569] lr: 4.0000e-02 eta: 20:36:28 time: 0.2601 data_time: 0.0082 memory: 5828 grad_norm: 3.0961 loss: 2.7772 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7772 2023/06/05 00:20:39 - mmengine - INFO - Epoch(train) [42][1900/2569] lr: 4.0000e-02 eta: 20:36:23 time: 0.2731 data_time: 0.0078 memory: 5828 grad_norm: 3.1433 loss: 2.5932 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5932 2023/06/05 00:20:44 - mmengine - INFO - Epoch(train) [42][1920/2569] lr: 4.0000e-02 eta: 20:36:17 time: 0.2612 data_time: 0.0084 memory: 5828 grad_norm: 3.1144 loss: 2.7224 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7224 2023/06/05 00:20:49 - mmengine - INFO - Epoch(train) [42][1940/2569] lr: 4.0000e-02 eta: 20:36:12 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 3.1296 loss: 2.7197 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7197 2023/06/05 00:20:54 - mmengine - INFO - Epoch(train) [42][1960/2569] lr: 4.0000e-02 eta: 20:36:06 time: 0.2578 data_time: 0.0077 memory: 5828 grad_norm: 3.0707 loss: 2.5813 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5813 2023/06/05 00:21:00 - mmengine - INFO - Epoch(train) [42][1980/2569] lr: 4.0000e-02 eta: 20:36:01 time: 0.2713 data_time: 0.0074 memory: 5828 grad_norm: 2.9979 loss: 2.3336 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3336 2023/06/05 00:21:05 - mmengine - INFO - Epoch(train) [42][2000/2569] lr: 4.0000e-02 eta: 20:35:55 time: 0.2558 data_time: 0.0086 memory: 5828 grad_norm: 3.0646 loss: 2.5395 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5395 2023/06/05 00:21:10 - mmengine - INFO - Epoch(train) [42][2020/2569] lr: 4.0000e-02 eta: 20:35:50 time: 0.2693 data_time: 0.0073 memory: 5828 grad_norm: 3.0940 loss: 2.5291 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5291 2023/06/05 00:21:15 - mmengine - INFO - Epoch(train) [42][2040/2569] lr: 4.0000e-02 eta: 20:35:44 time: 0.2585 data_time: 0.0080 memory: 5828 grad_norm: 3.0860 loss: 2.7180 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7180 2023/06/05 00:21:21 - mmengine - INFO - Epoch(train) [42][2060/2569] lr: 4.0000e-02 eta: 20:35:39 time: 0.2763 data_time: 0.0076 memory: 5828 grad_norm: 3.0972 loss: 2.2261 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2261 2023/06/05 00:21:26 - mmengine - INFO - Epoch(train) [42][2080/2569] lr: 4.0000e-02 eta: 20:35:33 time: 0.2617 data_time: 0.0083 memory: 5828 grad_norm: 3.2106 loss: 2.7463 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7463 2023/06/05 00:21:31 - mmengine - INFO - Epoch(train) [42][2100/2569] lr: 4.0000e-02 eta: 20:35:28 time: 0.2592 data_time: 0.0077 memory: 5828 grad_norm: 3.0666 loss: 2.5380 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5380 2023/06/05 00:21:37 - mmengine - INFO - Epoch(train) [42][2120/2569] lr: 4.0000e-02 eta: 20:35:22 time: 0.2584 data_time: 0.0075 memory: 5828 grad_norm: 3.0996 loss: 2.2857 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.2857 2023/06/05 00:21:42 - mmengine - INFO - Epoch(train) [42][2140/2569] lr: 4.0000e-02 eta: 20:35:17 time: 0.2716 data_time: 0.0075 memory: 5828 grad_norm: 3.1087 loss: 2.6111 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6111 2023/06/05 00:21:47 - mmengine - INFO - Epoch(train) [42][2160/2569] lr: 4.0000e-02 eta: 20:35:11 time: 0.2580 data_time: 0.0076 memory: 5828 grad_norm: 3.0985 loss: 2.4784 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4784 2023/06/05 00:21:53 - mmengine - INFO - Epoch(train) [42][2180/2569] lr: 4.0000e-02 eta: 20:35:06 time: 0.2776 data_time: 0.0083 memory: 5828 grad_norm: 3.1234 loss: 2.3740 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3740 2023/06/05 00:21:58 - mmengine - INFO - Epoch(train) [42][2200/2569] lr: 4.0000e-02 eta: 20:35:01 time: 0.2653 data_time: 0.0081 memory: 5828 grad_norm: 3.1296 loss: 2.3837 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3837 2023/06/05 00:22:03 - mmengine - INFO - Epoch(train) [42][2220/2569] lr: 4.0000e-02 eta: 20:34:56 time: 0.2686 data_time: 0.0079 memory: 5828 grad_norm: 3.0488 loss: 2.4544 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4544 2023/06/05 00:22:09 - mmengine - INFO - Epoch(train) [42][2240/2569] lr: 4.0000e-02 eta: 20:34:50 time: 0.2581 data_time: 0.0078 memory: 5828 grad_norm: 3.0730 loss: 2.5940 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5940 2023/06/05 00:22:14 - mmengine - INFO - Epoch(train) [42][2260/2569] lr: 4.0000e-02 eta: 20:34:45 time: 0.2706 data_time: 0.0077 memory: 5828 grad_norm: 3.1156 loss: 2.5793 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5793 2023/06/05 00:22:19 - mmengine - INFO - Epoch(train) [42][2280/2569] lr: 4.0000e-02 eta: 20:34:39 time: 0.2636 data_time: 0.0078 memory: 5828 grad_norm: 3.1300 loss: 2.7102 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7102 2023/06/05 00:22:25 - mmengine - INFO - Epoch(train) [42][2300/2569] lr: 4.0000e-02 eta: 20:34:34 time: 0.2717 data_time: 0.0078 memory: 5828 grad_norm: 3.0175 loss: 2.6937 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6937 2023/06/05 00:22:30 - mmengine - INFO - Epoch(train) [42][2320/2569] lr: 4.0000e-02 eta: 20:34:29 time: 0.2598 data_time: 0.0083 memory: 5828 grad_norm: 3.0876 loss: 2.5781 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5781 2023/06/05 00:22:35 - mmengine - INFO - Epoch(train) [42][2340/2569] lr: 4.0000e-02 eta: 20:34:23 time: 0.2634 data_time: 0.0080 memory: 5828 grad_norm: 3.1365 loss: 2.4341 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4341 2023/06/05 00:22:41 - mmengine - INFO - Epoch(train) [42][2360/2569] lr: 4.0000e-02 eta: 20:34:18 time: 0.2742 data_time: 0.0086 memory: 5828 grad_norm: 3.1398 loss: 2.5619 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5619 2023/06/05 00:22:46 - mmengine - INFO - Epoch(train) [42][2380/2569] lr: 4.0000e-02 eta: 20:34:12 time: 0.2604 data_time: 0.0073 memory: 5828 grad_norm: 3.0917 loss: 2.3702 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3702 2023/06/05 00:22:51 - mmengine - INFO - Epoch(train) [42][2400/2569] lr: 4.0000e-02 eta: 20:34:07 time: 0.2690 data_time: 0.0080 memory: 5828 grad_norm: 3.1117 loss: 2.3878 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3878 2023/06/05 00:22:56 - mmengine - INFO - Epoch(train) [42][2420/2569] lr: 4.0000e-02 eta: 20:34:01 time: 0.2578 data_time: 0.0082 memory: 5828 grad_norm: 3.1083 loss: 2.7594 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7594 2023/06/05 00:23:02 - mmengine - INFO - Epoch(train) [42][2440/2569] lr: 4.0000e-02 eta: 20:33:56 time: 0.2664 data_time: 0.0078 memory: 5828 grad_norm: 3.1278 loss: 2.7504 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7504 2023/06/05 00:23:07 - mmengine - INFO - Epoch(train) [42][2460/2569] lr: 4.0000e-02 eta: 20:33:50 time: 0.2597 data_time: 0.0079 memory: 5828 grad_norm: 3.0776 loss: 2.8168 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8168 2023/06/05 00:23:12 - mmengine - INFO - Epoch(train) [42][2480/2569] lr: 4.0000e-02 eta: 20:33:45 time: 0.2611 data_time: 0.0081 memory: 5828 grad_norm: 3.0961 loss: 2.5760 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5760 2023/06/05 00:23:18 - mmengine - INFO - Epoch(train) [42][2500/2569] lr: 4.0000e-02 eta: 20:33:39 time: 0.2660 data_time: 0.0077 memory: 5828 grad_norm: 3.0736 loss: 2.4208 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4208 2023/06/05 00:23:23 - mmengine - INFO - Epoch(train) [42][2520/2569] lr: 4.0000e-02 eta: 20:33:34 time: 0.2633 data_time: 0.0080 memory: 5828 grad_norm: 3.0991 loss: 3.0106 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0106 2023/06/05 00:23:28 - mmengine - INFO - Epoch(train) [42][2540/2569] lr: 4.0000e-02 eta: 20:33:28 time: 0.2648 data_time: 0.0080 memory: 5828 grad_norm: 3.1189 loss: 2.7648 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7648 2023/06/05 00:23:33 - mmengine - INFO - Epoch(train) [42][2560/2569] lr: 4.0000e-02 eta: 20:33:23 time: 0.2569 data_time: 0.0083 memory: 5828 grad_norm: 3.0209 loss: 2.2910 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2910 2023/06/05 00:23:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:23:36 - mmengine - INFO - Epoch(train) [42][2569/2569] lr: 4.0000e-02 eta: 20:33:20 time: 0.2619 data_time: 0.0077 memory: 5828 grad_norm: 3.0248 loss: 2.4078 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4078 2023/06/05 00:23:42 - mmengine - INFO - Epoch(train) [43][ 20/2569] lr: 4.0000e-02 eta: 20:33:19 time: 0.3369 data_time: 0.0559 memory: 5828 grad_norm: 3.0405 loss: 2.2399 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.2399 2023/06/05 00:23:48 - mmengine - INFO - Epoch(train) [43][ 40/2569] lr: 4.0000e-02 eta: 20:33:13 time: 0.2638 data_time: 0.0081 memory: 5828 grad_norm: 3.1088 loss: 2.7690 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7690 2023/06/05 00:23:53 - mmengine - INFO - Epoch(train) [43][ 60/2569] lr: 4.0000e-02 eta: 20:33:08 time: 0.2648 data_time: 0.0080 memory: 5828 grad_norm: 3.0399 loss: 2.8332 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8332 2023/06/05 00:23:58 - mmengine - INFO - Epoch(train) [43][ 80/2569] lr: 4.0000e-02 eta: 20:33:02 time: 0.2590 data_time: 0.0081 memory: 5828 grad_norm: 3.1259 loss: 2.7083 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7083 2023/06/05 00:24:03 - mmengine - INFO - Epoch(train) [43][ 100/2569] lr: 4.0000e-02 eta: 20:32:56 time: 0.2650 data_time: 0.0081 memory: 5828 grad_norm: 3.0507 loss: 2.3916 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.3916 2023/06/05 00:24:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:24:09 - mmengine - INFO - Epoch(train) [43][ 120/2569] lr: 4.0000e-02 eta: 20:32:51 time: 0.2596 data_time: 0.0083 memory: 5828 grad_norm: 3.0515 loss: 2.5428 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5428 2023/06/05 00:24:14 - mmengine - INFO - Epoch(train) [43][ 140/2569] lr: 4.0000e-02 eta: 20:32:45 time: 0.2629 data_time: 0.0079 memory: 5828 grad_norm: 3.0915 loss: 2.8285 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8285 2023/06/05 00:24:19 - mmengine - INFO - Epoch(train) [43][ 160/2569] lr: 4.0000e-02 eta: 20:32:40 time: 0.2608 data_time: 0.0074 memory: 5828 grad_norm: 3.1403 loss: 2.4133 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4133 2023/06/05 00:24:25 - mmengine - INFO - Epoch(train) [43][ 180/2569] lr: 4.0000e-02 eta: 20:32:35 time: 0.2732 data_time: 0.0077 memory: 5828 grad_norm: 3.0735 loss: 2.3280 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3280 2023/06/05 00:24:30 - mmengine - INFO - Epoch(train) [43][ 200/2569] lr: 4.0000e-02 eta: 20:32:29 time: 0.2647 data_time: 0.0078 memory: 5828 grad_norm: 3.1093 loss: 2.3682 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3682 2023/06/05 00:24:35 - mmengine - INFO - Epoch(train) [43][ 220/2569] lr: 4.0000e-02 eta: 20:32:24 time: 0.2712 data_time: 0.0076 memory: 5828 grad_norm: 2.9729 loss: 2.5226 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5226 2023/06/05 00:24:41 - mmengine - INFO - Epoch(train) [43][ 240/2569] lr: 4.0000e-02 eta: 20:32:18 time: 0.2597 data_time: 0.0081 memory: 5828 grad_norm: 3.0880 loss: 2.5777 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5777 2023/06/05 00:24:46 - mmengine - INFO - Epoch(train) [43][ 260/2569] lr: 4.0000e-02 eta: 20:32:13 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 3.1686 loss: 2.3195 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3195 2023/06/05 00:24:51 - mmengine - INFO - Epoch(train) [43][ 280/2569] lr: 4.0000e-02 eta: 20:32:07 time: 0.2623 data_time: 0.0074 memory: 5828 grad_norm: 3.0691 loss: 2.6816 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6816 2023/06/05 00:24:56 - mmengine - INFO - Epoch(train) [43][ 300/2569] lr: 4.0000e-02 eta: 20:32:02 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 3.0814 loss: 2.0290 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0290 2023/06/05 00:25:02 - mmengine - INFO - Epoch(train) [43][ 320/2569] lr: 4.0000e-02 eta: 20:31:57 time: 0.2825 data_time: 0.0079 memory: 5828 grad_norm: 3.0670 loss: 2.3928 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3928 2023/06/05 00:25:07 - mmengine - INFO - Epoch(train) [43][ 340/2569] lr: 4.0000e-02 eta: 20:31:52 time: 0.2619 data_time: 0.0078 memory: 5828 grad_norm: 3.0888 loss: 2.5060 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5060 2023/06/05 00:25:13 - mmengine - INFO - Epoch(train) [43][ 360/2569] lr: 4.0000e-02 eta: 20:31:46 time: 0.2646 data_time: 0.0079 memory: 5828 grad_norm: 3.0797 loss: 2.4442 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4442 2023/06/05 00:25:18 - mmengine - INFO - Epoch(train) [43][ 380/2569] lr: 4.0000e-02 eta: 20:31:40 time: 0.2572 data_time: 0.0078 memory: 5828 grad_norm: 3.1570 loss: 2.8093 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8093 2023/06/05 00:25:23 - mmengine - INFO - Epoch(train) [43][ 400/2569] lr: 4.0000e-02 eta: 20:31:35 time: 0.2594 data_time: 0.0081 memory: 5828 grad_norm: 3.0144 loss: 2.6112 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6112 2023/06/05 00:25:28 - mmengine - INFO - Epoch(train) [43][ 420/2569] lr: 4.0000e-02 eta: 20:31:29 time: 0.2618 data_time: 0.0079 memory: 5828 grad_norm: 3.1199 loss: 2.1999 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1999 2023/06/05 00:25:33 - mmengine - INFO - Epoch(train) [43][ 440/2569] lr: 4.0000e-02 eta: 20:31:23 time: 0.2599 data_time: 0.0077 memory: 5828 grad_norm: 3.0354 loss: 2.6607 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6607 2023/06/05 00:25:39 - mmengine - INFO - Epoch(train) [43][ 460/2569] lr: 4.0000e-02 eta: 20:31:18 time: 0.2632 data_time: 0.0076 memory: 5828 grad_norm: 3.0333 loss: 2.3236 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3236 2023/06/05 00:25:44 - mmengine - INFO - Epoch(train) [43][ 480/2569] lr: 4.0000e-02 eta: 20:31:13 time: 0.2697 data_time: 0.0081 memory: 5828 grad_norm: 3.0629 loss: 2.7464 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7464 2023/06/05 00:25:49 - mmengine - INFO - Epoch(train) [43][ 500/2569] lr: 4.0000e-02 eta: 20:31:08 time: 0.2709 data_time: 0.0075 memory: 5828 grad_norm: 3.2532 loss: 2.7404 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7404 2023/06/05 00:25:55 - mmengine - INFO - Epoch(train) [43][ 520/2569] lr: 4.0000e-02 eta: 20:31:02 time: 0.2608 data_time: 0.0081 memory: 5828 grad_norm: 3.1033 loss: 2.4421 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4421 2023/06/05 00:26:00 - mmengine - INFO - Epoch(train) [43][ 540/2569] lr: 4.0000e-02 eta: 20:30:56 time: 0.2637 data_time: 0.0082 memory: 5828 grad_norm: 3.1225 loss: 2.4669 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4669 2023/06/05 00:26:05 - mmengine - INFO - Epoch(train) [43][ 560/2569] lr: 4.0000e-02 eta: 20:30:51 time: 0.2594 data_time: 0.0083 memory: 5828 grad_norm: 3.0154 loss: 2.3533 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3533 2023/06/05 00:26:10 - mmengine - INFO - Epoch(train) [43][ 580/2569] lr: 4.0000e-02 eta: 20:30:45 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.1144 loss: 2.3987 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3987 2023/06/05 00:26:16 - mmengine - INFO - Epoch(train) [43][ 600/2569] lr: 4.0000e-02 eta: 20:30:39 time: 0.2590 data_time: 0.0080 memory: 5828 grad_norm: 3.0671 loss: 2.4897 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4897 2023/06/05 00:26:21 - mmengine - INFO - Epoch(train) [43][ 620/2569] lr: 4.0000e-02 eta: 20:30:34 time: 0.2611 data_time: 0.0081 memory: 5828 grad_norm: 3.1113 loss: 2.5672 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5672 2023/06/05 00:26:26 - mmengine - INFO - Epoch(train) [43][ 640/2569] lr: 4.0000e-02 eta: 20:30:28 time: 0.2629 data_time: 0.0080 memory: 5828 grad_norm: 3.0984 loss: 2.3232 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3232 2023/06/05 00:26:31 - mmengine - INFO - Epoch(train) [43][ 660/2569] lr: 4.0000e-02 eta: 20:30:23 time: 0.2633 data_time: 0.0081 memory: 5828 grad_norm: 3.0689 loss: 2.5444 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5444 2023/06/05 00:26:37 - mmengine - INFO - Epoch(train) [43][ 680/2569] lr: 4.0000e-02 eta: 20:30:17 time: 0.2644 data_time: 0.0080 memory: 5828 grad_norm: 3.0458 loss: 2.1261 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1261 2023/06/05 00:26:42 - mmengine - INFO - Epoch(train) [43][ 700/2569] lr: 4.0000e-02 eta: 20:30:11 time: 0.2560 data_time: 0.0083 memory: 5828 grad_norm: 3.0810 loss: 2.4051 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4051 2023/06/05 00:26:47 - mmengine - INFO - Epoch(train) [43][ 720/2569] lr: 4.0000e-02 eta: 20:30:06 time: 0.2593 data_time: 0.0077 memory: 5828 grad_norm: 3.0869 loss: 2.3965 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3965 2023/06/05 00:26:52 - mmengine - INFO - Epoch(train) [43][ 740/2569] lr: 4.0000e-02 eta: 20:30:00 time: 0.2587 data_time: 0.0078 memory: 5828 grad_norm: 3.0321 loss: 2.7168 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7168 2023/06/05 00:26:57 - mmengine - INFO - Epoch(train) [43][ 760/2569] lr: 4.0000e-02 eta: 20:29:54 time: 0.2583 data_time: 0.0082 memory: 5828 grad_norm: 3.1774 loss: 2.8080 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8080 2023/06/05 00:27:03 - mmengine - INFO - Epoch(train) [43][ 780/2569] lr: 4.0000e-02 eta: 20:29:49 time: 0.2616 data_time: 0.0078 memory: 5828 grad_norm: 3.0569 loss: 2.2985 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2985 2023/06/05 00:27:08 - mmengine - INFO - Epoch(train) [43][ 800/2569] lr: 4.0000e-02 eta: 20:29:43 time: 0.2677 data_time: 0.0083 memory: 5828 grad_norm: 3.1484 loss: 2.4866 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4866 2023/06/05 00:27:13 - mmengine - INFO - Epoch(train) [43][ 820/2569] lr: 4.0000e-02 eta: 20:29:38 time: 0.2645 data_time: 0.0080 memory: 5828 grad_norm: 3.0978 loss: 2.5563 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5563 2023/06/05 00:27:18 - mmengine - INFO - Epoch(train) [43][ 840/2569] lr: 4.0000e-02 eta: 20:29:32 time: 0.2634 data_time: 0.0080 memory: 5828 grad_norm: 3.0622 loss: 2.7203 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7203 2023/06/05 00:27:24 - mmengine - INFO - Epoch(train) [43][ 860/2569] lr: 4.0000e-02 eta: 20:29:27 time: 0.2725 data_time: 0.0079 memory: 5828 grad_norm: 3.1021 loss: 2.4462 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4462 2023/06/05 00:27:29 - mmengine - INFO - Epoch(train) [43][ 880/2569] lr: 4.0000e-02 eta: 20:29:22 time: 0.2622 data_time: 0.0080 memory: 5828 grad_norm: 3.0601 loss: 2.4557 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4557 2023/06/05 00:27:34 - mmengine - INFO - Epoch(train) [43][ 900/2569] lr: 4.0000e-02 eta: 20:29:16 time: 0.2589 data_time: 0.0080 memory: 5828 grad_norm: 3.1024 loss: 2.3163 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.3163 2023/06/05 00:27:40 - mmengine - INFO - Epoch(train) [43][ 920/2569] lr: 4.0000e-02 eta: 20:29:11 time: 0.2684 data_time: 0.0079 memory: 5828 grad_norm: 3.1133 loss: 2.5487 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5487 2023/06/05 00:27:45 - mmengine - INFO - Epoch(train) [43][ 940/2569] lr: 4.0000e-02 eta: 20:29:06 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 3.0577 loss: 2.4217 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4217 2023/06/05 00:27:50 - mmengine - INFO - Epoch(train) [43][ 960/2569] lr: 4.0000e-02 eta: 20:29:00 time: 0.2690 data_time: 0.0077 memory: 5828 grad_norm: 3.1035 loss: 2.6634 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6634 2023/06/05 00:27:56 - mmengine - INFO - Epoch(train) [43][ 980/2569] lr: 4.0000e-02 eta: 20:28:55 time: 0.2667 data_time: 0.0077 memory: 5828 grad_norm: 3.0306 loss: 3.0072 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0072 2023/06/05 00:28:01 - mmengine - INFO - Epoch(train) [43][1000/2569] lr: 4.0000e-02 eta: 20:28:50 time: 0.2735 data_time: 0.0081 memory: 5828 grad_norm: 3.1135 loss: 2.8097 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8097 2023/06/05 00:28:07 - mmengine - INFO - Epoch(train) [43][1020/2569] lr: 4.0000e-02 eta: 20:28:45 time: 0.2725 data_time: 0.0079 memory: 5828 grad_norm: 3.0637 loss: 2.6424 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6424 2023/06/05 00:28:12 - mmengine - INFO - Epoch(train) [43][1040/2569] lr: 4.0000e-02 eta: 20:28:39 time: 0.2617 data_time: 0.0081 memory: 5828 grad_norm: 3.1410 loss: 2.5735 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5735 2023/06/05 00:28:17 - mmengine - INFO - Epoch(train) [43][1060/2569] lr: 4.0000e-02 eta: 20:28:34 time: 0.2734 data_time: 0.0077 memory: 5828 grad_norm: 3.0779 loss: 2.5666 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5666 2023/06/05 00:28:23 - mmengine - INFO - Epoch(train) [43][1080/2569] lr: 4.0000e-02 eta: 20:28:29 time: 0.2590 data_time: 0.0081 memory: 5828 grad_norm: 3.0545 loss: 2.4627 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4627 2023/06/05 00:28:28 - mmengine - INFO - Epoch(train) [43][1100/2569] lr: 4.0000e-02 eta: 20:28:23 time: 0.2623 data_time: 0.0080 memory: 5828 grad_norm: 3.0612 loss: 2.6607 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6607 2023/06/05 00:28:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:28:33 - mmengine - INFO - Epoch(train) [43][1120/2569] lr: 4.0000e-02 eta: 20:28:17 time: 0.2596 data_time: 0.0074 memory: 5828 grad_norm: 3.1336 loss: 2.8349 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8349 2023/06/05 00:28:38 - mmengine - INFO - Epoch(train) [43][1140/2569] lr: 4.0000e-02 eta: 20:28:12 time: 0.2599 data_time: 0.0078 memory: 5828 grad_norm: 3.3215 loss: 2.4670 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4670 2023/06/05 00:28:44 - mmengine - INFO - Epoch(train) [43][1160/2569] lr: 4.0000e-02 eta: 20:28:06 time: 0.2626 data_time: 0.0081 memory: 5828 grad_norm: 3.0872 loss: 2.5460 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5460 2023/06/05 00:28:49 - mmengine - INFO - Epoch(train) [43][1180/2569] lr: 4.0000e-02 eta: 20:28:00 time: 0.2562 data_time: 0.0074 memory: 5828 grad_norm: 3.0714 loss: 2.3733 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3733 2023/06/05 00:28:54 - mmengine - INFO - Epoch(train) [43][1200/2569] lr: 4.0000e-02 eta: 20:27:55 time: 0.2686 data_time: 0.0080 memory: 5828 grad_norm: 3.0235 loss: 2.6778 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6778 2023/06/05 00:29:00 - mmengine - INFO - Epoch(train) [43][1220/2569] lr: 4.0000e-02 eta: 20:27:51 time: 0.2830 data_time: 0.0075 memory: 5828 grad_norm: 3.1058 loss: 2.5702 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5702 2023/06/05 00:29:05 - mmengine - INFO - Epoch(train) [43][1240/2569] lr: 4.0000e-02 eta: 20:27:45 time: 0.2584 data_time: 0.0078 memory: 5828 grad_norm: 3.1444 loss: 2.7358 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7358 2023/06/05 00:29:10 - mmengine - INFO - Epoch(train) [43][1260/2569] lr: 4.0000e-02 eta: 20:27:40 time: 0.2784 data_time: 0.0072 memory: 5828 grad_norm: 3.0934 loss: 2.4401 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4401 2023/06/05 00:29:16 - mmengine - INFO - Epoch(train) [43][1280/2569] lr: 4.0000e-02 eta: 20:27:35 time: 0.2690 data_time: 0.0085 memory: 5828 grad_norm: 3.0525 loss: 2.3845 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3845 2023/06/05 00:29:21 - mmengine - INFO - Epoch(train) [43][1300/2569] lr: 4.0000e-02 eta: 20:27:30 time: 0.2709 data_time: 0.0080 memory: 5828 grad_norm: 3.1006 loss: 2.8534 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.8534 2023/06/05 00:29:27 - mmengine - INFO - Epoch(train) [43][1320/2569] lr: 4.0000e-02 eta: 20:27:25 time: 0.2710 data_time: 0.0080 memory: 5828 grad_norm: 3.0883 loss: 2.6628 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6628 2023/06/05 00:29:32 - mmengine - INFO - Epoch(train) [43][1340/2569] lr: 4.0000e-02 eta: 20:27:19 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 3.1272 loss: 2.7007 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7007 2023/06/05 00:29:37 - mmengine - INFO - Epoch(train) [43][1360/2569] lr: 4.0000e-02 eta: 20:27:14 time: 0.2648 data_time: 0.0084 memory: 5828 grad_norm: 3.0751 loss: 3.0384 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0384 2023/06/05 00:29:42 - mmengine - INFO - Epoch(train) [43][1380/2569] lr: 4.0000e-02 eta: 20:27:08 time: 0.2576 data_time: 0.0079 memory: 5828 grad_norm: 3.1244 loss: 2.5229 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5229 2023/06/05 00:29:48 - mmengine - INFO - Epoch(train) [43][1400/2569] lr: 4.0000e-02 eta: 20:27:03 time: 0.2622 data_time: 0.0081 memory: 5828 grad_norm: 3.1151 loss: 2.6302 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6302 2023/06/05 00:29:53 - mmengine - INFO - Epoch(train) [43][1420/2569] lr: 4.0000e-02 eta: 20:26:57 time: 0.2632 data_time: 0.0080 memory: 5828 grad_norm: 3.1615 loss: 2.2167 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2167 2023/06/05 00:29:58 - mmengine - INFO - Epoch(train) [43][1440/2569] lr: 4.0000e-02 eta: 20:26:51 time: 0.2569 data_time: 0.0078 memory: 5828 grad_norm: 3.1489 loss: 2.7969 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7969 2023/06/05 00:30:03 - mmengine - INFO - Epoch(train) [43][1460/2569] lr: 4.0000e-02 eta: 20:26:46 time: 0.2678 data_time: 0.0078 memory: 5828 grad_norm: 3.0653 loss: 2.4962 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4962 2023/06/05 00:30:09 - mmengine - INFO - Epoch(train) [43][1480/2569] lr: 4.0000e-02 eta: 20:26:41 time: 0.2679 data_time: 0.0085 memory: 5828 grad_norm: 3.0337 loss: 2.5471 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5471 2023/06/05 00:30:14 - mmengine - INFO - Epoch(train) [43][1500/2569] lr: 4.0000e-02 eta: 20:26:35 time: 0.2635 data_time: 0.0077 memory: 5828 grad_norm: 3.0709 loss: 2.4161 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4161 2023/06/05 00:30:19 - mmengine - INFO - Epoch(train) [43][1520/2569] lr: 4.0000e-02 eta: 20:26:30 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 3.1903 loss: 2.6823 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6823 2023/06/05 00:30:25 - mmengine - INFO - Epoch(train) [43][1540/2569] lr: 4.0000e-02 eta: 20:26:25 time: 0.2682 data_time: 0.0079 memory: 5828 grad_norm: 3.0797 loss: 2.5386 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5386 2023/06/05 00:30:30 - mmengine - INFO - Epoch(train) [43][1560/2569] lr: 4.0000e-02 eta: 20:26:19 time: 0.2638 data_time: 0.0083 memory: 5828 grad_norm: 3.0958 loss: 2.7855 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7855 2023/06/05 00:30:36 - mmengine - INFO - Epoch(train) [43][1580/2569] lr: 4.0000e-02 eta: 20:26:14 time: 0.2794 data_time: 0.0077 memory: 5828 grad_norm: 3.0622 loss: 2.3229 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3229 2023/06/05 00:30:41 - mmengine - INFO - Epoch(train) [43][1600/2569] lr: 4.0000e-02 eta: 20:26:09 time: 0.2694 data_time: 0.0077 memory: 5828 grad_norm: 3.0931 loss: 2.6581 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6581 2023/06/05 00:30:46 - mmengine - INFO - Epoch(train) [43][1620/2569] lr: 4.0000e-02 eta: 20:26:04 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.0824 loss: 2.5672 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5672 2023/06/05 00:30:52 - mmengine - INFO - Epoch(train) [43][1640/2569] lr: 4.0000e-02 eta: 20:25:58 time: 0.2590 data_time: 0.0081 memory: 5828 grad_norm: 3.0524 loss: 2.9277 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9277 2023/06/05 00:30:57 - mmengine - INFO - Epoch(train) [43][1660/2569] lr: 4.0000e-02 eta: 20:25:53 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.0674 loss: 2.5233 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5233 2023/06/05 00:31:02 - mmengine - INFO - Epoch(train) [43][1680/2569] lr: 4.0000e-02 eta: 20:25:47 time: 0.2681 data_time: 0.0081 memory: 5828 grad_norm: 3.0688 loss: 2.7073 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.7073 2023/06/05 00:31:08 - mmengine - INFO - Epoch(train) [43][1700/2569] lr: 4.0000e-02 eta: 20:25:42 time: 0.2634 data_time: 0.0080 memory: 5828 grad_norm: 3.0557 loss: 2.7318 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7318 2023/06/05 00:31:13 - mmengine - INFO - Epoch(train) [43][1720/2569] lr: 4.0000e-02 eta: 20:25:36 time: 0.2664 data_time: 0.0090 memory: 5828 grad_norm: 3.0597 loss: 2.7493 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7493 2023/06/05 00:31:18 - mmengine - INFO - Epoch(train) [43][1740/2569] lr: 4.0000e-02 eta: 20:25:31 time: 0.2594 data_time: 0.0079 memory: 5828 grad_norm: 3.0727 loss: 2.2764 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2764 2023/06/05 00:31:23 - mmengine - INFO - Epoch(train) [43][1760/2569] lr: 4.0000e-02 eta: 20:25:25 time: 0.2675 data_time: 0.0077 memory: 5828 grad_norm: 3.0769 loss: 2.5812 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5812 2023/06/05 00:31:29 - mmengine - INFO - Epoch(train) [43][1780/2569] lr: 4.0000e-02 eta: 20:25:20 time: 0.2644 data_time: 0.0079 memory: 5828 grad_norm: 3.0620 loss: 2.7924 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7924 2023/06/05 00:31:34 - mmengine - INFO - Epoch(train) [43][1800/2569] lr: 4.0000e-02 eta: 20:25:15 time: 0.2632 data_time: 0.0077 memory: 5828 grad_norm: 3.0718 loss: 2.7078 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7078 2023/06/05 00:31:39 - mmengine - INFO - Epoch(train) [43][1820/2569] lr: 4.0000e-02 eta: 20:25:09 time: 0.2718 data_time: 0.0081 memory: 5828 grad_norm: 3.0617 loss: 2.7408 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7408 2023/06/05 00:31:45 - mmengine - INFO - Epoch(train) [43][1840/2569] lr: 4.0000e-02 eta: 20:25:04 time: 0.2575 data_time: 0.0081 memory: 5828 grad_norm: 3.0772 loss: 2.6313 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6313 2023/06/05 00:31:50 - mmengine - INFO - Epoch(train) [43][1860/2569] lr: 4.0000e-02 eta: 20:24:58 time: 0.2567 data_time: 0.0073 memory: 5828 grad_norm: 3.1089 loss: 2.7449 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7449 2023/06/05 00:31:55 - mmengine - INFO - Epoch(train) [43][1880/2569] lr: 4.0000e-02 eta: 20:24:52 time: 0.2632 data_time: 0.0083 memory: 5828 grad_norm: 3.1075 loss: 2.6318 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6318 2023/06/05 00:32:00 - mmengine - INFO - Epoch(train) [43][1900/2569] lr: 4.0000e-02 eta: 20:24:47 time: 0.2573 data_time: 0.0076 memory: 5828 grad_norm: 3.0578 loss: 2.7002 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7002 2023/06/05 00:32:06 - mmengine - INFO - Epoch(train) [43][1920/2569] lr: 4.0000e-02 eta: 20:24:41 time: 0.2697 data_time: 0.0082 memory: 5828 grad_norm: 3.1585 loss: 2.5253 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5253 2023/06/05 00:32:11 - mmengine - INFO - Epoch(train) [43][1940/2569] lr: 4.0000e-02 eta: 20:24:36 time: 0.2572 data_time: 0.0081 memory: 5828 grad_norm: 3.1225 loss: 2.4298 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4298 2023/06/05 00:32:16 - mmengine - INFO - Epoch(train) [43][1960/2569] lr: 4.0000e-02 eta: 20:24:30 time: 0.2638 data_time: 0.0079 memory: 5828 grad_norm: 3.0403 loss: 2.4379 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4379 2023/06/05 00:32:21 - mmengine - INFO - Epoch(train) [43][1980/2569] lr: 4.0000e-02 eta: 20:24:24 time: 0.2575 data_time: 0.0075 memory: 5828 grad_norm: 3.1312 loss: 2.2983 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2983 2023/06/05 00:32:26 - mmengine - INFO - Epoch(train) [43][2000/2569] lr: 4.0000e-02 eta: 20:24:19 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 3.0750 loss: 2.8222 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8222 2023/06/05 00:32:32 - mmengine - INFO - Epoch(train) [43][2020/2569] lr: 4.0000e-02 eta: 20:24:13 time: 0.2650 data_time: 0.0077 memory: 5828 grad_norm: 3.0814 loss: 2.8646 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8646 2023/06/05 00:32:37 - mmengine - INFO - Epoch(train) [43][2040/2569] lr: 4.0000e-02 eta: 20:24:08 time: 0.2620 data_time: 0.0078 memory: 5828 grad_norm: 3.0297 loss: 2.5037 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5037 2023/06/05 00:32:42 - mmengine - INFO - Epoch(train) [43][2060/2569] lr: 4.0000e-02 eta: 20:24:02 time: 0.2638 data_time: 0.0080 memory: 5828 grad_norm: 3.1124 loss: 2.5234 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5234 2023/06/05 00:32:47 - mmengine - INFO - Epoch(train) [43][2080/2569] lr: 4.0000e-02 eta: 20:23:57 time: 0.2644 data_time: 0.0084 memory: 5828 grad_norm: 3.1116 loss: 2.5007 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5007 2023/06/05 00:32:53 - mmengine - INFO - Epoch(train) [43][2100/2569] lr: 4.0000e-02 eta: 20:23:52 time: 0.2784 data_time: 0.0077 memory: 5828 grad_norm: 3.0347 loss: 2.4396 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4396 2023/06/05 00:32:54 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:32:58 - mmengine - INFO - Epoch(train) [43][2120/2569] lr: 4.0000e-02 eta: 20:23:47 time: 0.2634 data_time: 0.0082 memory: 5828 grad_norm: 3.0396 loss: 2.6463 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6463 2023/06/05 00:33:04 - mmengine - INFO - Epoch(train) [43][2140/2569] lr: 4.0000e-02 eta: 20:23:41 time: 0.2633 data_time: 0.0079 memory: 5828 grad_norm: 3.0334 loss: 2.5837 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5837 2023/06/05 00:33:09 - mmengine - INFO - Epoch(train) [43][2160/2569] lr: 4.0000e-02 eta: 20:23:36 time: 0.2779 data_time: 0.0082 memory: 5828 grad_norm: 3.0648 loss: 2.8321 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8321 2023/06/05 00:33:14 - mmengine - INFO - Epoch(train) [43][2180/2569] lr: 4.0000e-02 eta: 20:23:31 time: 0.2586 data_time: 0.0077 memory: 5828 grad_norm: 3.0746 loss: 2.6679 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6679 2023/06/05 00:33:20 - mmengine - INFO - Epoch(train) [43][2200/2569] lr: 4.0000e-02 eta: 20:23:25 time: 0.2655 data_time: 0.0080 memory: 5828 grad_norm: 3.0706 loss: 2.6113 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6113 2023/06/05 00:33:25 - mmengine - INFO - Epoch(train) [43][2220/2569] lr: 4.0000e-02 eta: 20:23:19 time: 0.2581 data_time: 0.0080 memory: 5828 grad_norm: 3.0752 loss: 2.4274 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4274 2023/06/05 00:33:30 - mmengine - INFO - Epoch(train) [43][2240/2569] lr: 4.0000e-02 eta: 20:23:14 time: 0.2710 data_time: 0.0088 memory: 5828 grad_norm: 3.0583 loss: 2.6600 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6600 2023/06/05 00:33:36 - mmengine - INFO - Epoch(train) [43][2260/2569] lr: 4.0000e-02 eta: 20:23:09 time: 0.2638 data_time: 0.0077 memory: 5828 grad_norm: 3.1238 loss: 2.5994 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5994 2023/06/05 00:33:41 - mmengine - INFO - Epoch(train) [43][2280/2569] lr: 4.0000e-02 eta: 20:23:03 time: 0.2626 data_time: 0.0082 memory: 5828 grad_norm: 3.0738 loss: 2.4579 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4579 2023/06/05 00:33:46 - mmengine - INFO - Epoch(train) [43][2300/2569] lr: 4.0000e-02 eta: 20:22:57 time: 0.2582 data_time: 0.0081 memory: 5828 grad_norm: 3.1180 loss: 2.7621 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7621 2023/06/05 00:33:51 - mmengine - INFO - Epoch(train) [43][2320/2569] lr: 4.0000e-02 eta: 20:22:52 time: 0.2692 data_time: 0.0079 memory: 5828 grad_norm: 3.1054 loss: 2.3923 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3923 2023/06/05 00:33:57 - mmengine - INFO - Epoch(train) [43][2340/2569] lr: 4.0000e-02 eta: 20:22:47 time: 0.2582 data_time: 0.0077 memory: 5828 grad_norm: 3.0329 loss: 2.4707 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4707 2023/06/05 00:34:02 - mmengine - INFO - Epoch(train) [43][2360/2569] lr: 4.0000e-02 eta: 20:22:41 time: 0.2673 data_time: 0.0079 memory: 5828 grad_norm: 3.1045 loss: 2.5883 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5883 2023/06/05 00:34:07 - mmengine - INFO - Epoch(train) [43][2380/2569] lr: 4.0000e-02 eta: 20:22:36 time: 0.2674 data_time: 0.0075 memory: 5828 grad_norm: 3.0563 loss: 2.6727 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6727 2023/06/05 00:34:12 - mmengine - INFO - Epoch(train) [43][2400/2569] lr: 4.0000e-02 eta: 20:22:30 time: 0.2605 data_time: 0.0080 memory: 5828 grad_norm: 3.0892 loss: 2.4802 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4802 2023/06/05 00:34:18 - mmengine - INFO - Epoch(train) [43][2420/2569] lr: 4.0000e-02 eta: 20:22:25 time: 0.2640 data_time: 0.0077 memory: 5828 grad_norm: 3.0814 loss: 2.5681 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5681 2023/06/05 00:34:23 - mmengine - INFO - Epoch(train) [43][2440/2569] lr: 4.0000e-02 eta: 20:22:19 time: 0.2582 data_time: 0.0080 memory: 5828 grad_norm: 3.0812 loss: 2.4866 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4866 2023/06/05 00:34:28 - mmengine - INFO - Epoch(train) [43][2460/2569] lr: 4.0000e-02 eta: 20:22:14 time: 0.2636 data_time: 0.0081 memory: 5828 grad_norm: 3.0950 loss: 2.7010 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7010 2023/06/05 00:34:34 - mmengine - INFO - Epoch(train) [43][2480/2569] lr: 4.0000e-02 eta: 20:22:09 time: 0.2736 data_time: 0.0079 memory: 5828 grad_norm: 3.0835 loss: 2.8182 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8182 2023/06/05 00:34:39 - mmengine - INFO - Epoch(train) [43][2500/2569] lr: 4.0000e-02 eta: 20:22:03 time: 0.2595 data_time: 0.0076 memory: 5828 grad_norm: 3.1127 loss: 2.7859 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7859 2023/06/05 00:34:44 - mmengine - INFO - Epoch(train) [43][2520/2569] lr: 4.0000e-02 eta: 20:21:58 time: 0.2726 data_time: 0.0081 memory: 5828 grad_norm: 3.1167 loss: 2.6386 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.6386 2023/06/05 00:34:49 - mmengine - INFO - Epoch(train) [43][2540/2569] lr: 4.0000e-02 eta: 20:21:52 time: 0.2593 data_time: 0.0082 memory: 5828 grad_norm: 3.1362 loss: 2.4832 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4832 2023/06/05 00:34:55 - mmengine - INFO - Epoch(train) [43][2560/2569] lr: 4.0000e-02 eta: 20:21:47 time: 0.2711 data_time: 0.0078 memory: 5828 grad_norm: 3.1087 loss: 2.3616 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3616 2023/06/05 00:34:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:34:57 - mmengine - INFO - Epoch(train) [43][2569/2569] lr: 4.0000e-02 eta: 20:21:44 time: 0.2568 data_time: 0.0076 memory: 5828 grad_norm: 3.1508 loss: 2.2797 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.2797 2023/06/05 00:35:04 - mmengine - INFO - Epoch(train) [44][ 20/2569] lr: 4.0000e-02 eta: 20:21:43 time: 0.3532 data_time: 0.0646 memory: 5828 grad_norm: 3.1718 loss: 2.4747 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4747 2023/06/05 00:35:09 - mmengine - INFO - Epoch(train) [44][ 40/2569] lr: 4.0000e-02 eta: 20:21:37 time: 0.2582 data_time: 0.0078 memory: 5828 grad_norm: 3.0916 loss: 2.5550 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5550 2023/06/05 00:35:15 - mmengine - INFO - Epoch(train) [44][ 60/2569] lr: 4.0000e-02 eta: 20:21:32 time: 0.2633 data_time: 0.0079 memory: 5828 grad_norm: 3.0597 loss: 2.5544 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5544 2023/06/05 00:35:20 - mmengine - INFO - Epoch(train) [44][ 80/2569] lr: 4.0000e-02 eta: 20:21:26 time: 0.2604 data_time: 0.0081 memory: 5828 grad_norm: 3.1043 loss: 2.9368 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9368 2023/06/05 00:35:25 - mmengine - INFO - Epoch(train) [44][ 100/2569] lr: 4.0000e-02 eta: 20:21:21 time: 0.2690 data_time: 0.0082 memory: 5828 grad_norm: 3.0556 loss: 2.6811 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6811 2023/06/05 00:35:31 - mmengine - INFO - Epoch(train) [44][ 120/2569] lr: 4.0000e-02 eta: 20:21:16 time: 0.2646 data_time: 0.0078 memory: 5828 grad_norm: 3.0926 loss: 2.5736 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.5736 2023/06/05 00:35:36 - mmengine - INFO - Epoch(train) [44][ 140/2569] lr: 4.0000e-02 eta: 20:21:10 time: 0.2645 data_time: 0.0078 memory: 5828 grad_norm: 3.0901 loss: 2.4086 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4086 2023/06/05 00:35:41 - mmengine - INFO - Epoch(train) [44][ 160/2569] lr: 4.0000e-02 eta: 20:21:05 time: 0.2641 data_time: 0.0077 memory: 5828 grad_norm: 3.1496 loss: 2.6889 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6889 2023/06/05 00:35:47 - mmengine - INFO - Epoch(train) [44][ 180/2569] lr: 4.0000e-02 eta: 20:21:00 time: 0.2701 data_time: 0.0079 memory: 5828 grad_norm: 3.0725 loss: 2.5727 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5727 2023/06/05 00:35:52 - mmengine - INFO - Epoch(train) [44][ 200/2569] lr: 4.0000e-02 eta: 20:20:54 time: 0.2709 data_time: 0.0079 memory: 5828 grad_norm: 3.1365 loss: 2.7292 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7292 2023/06/05 00:35:57 - mmengine - INFO - Epoch(train) [44][ 220/2569] lr: 4.0000e-02 eta: 20:20:49 time: 0.2596 data_time: 0.0079 memory: 5828 grad_norm: 3.1190 loss: 2.6651 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.6651 2023/06/05 00:36:03 - mmengine - INFO - Epoch(train) [44][ 240/2569] lr: 4.0000e-02 eta: 20:20:43 time: 0.2685 data_time: 0.0081 memory: 5828 grad_norm: 3.0364 loss: 2.3851 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3851 2023/06/05 00:36:08 - mmengine - INFO - Epoch(train) [44][ 260/2569] lr: 4.0000e-02 eta: 20:20:38 time: 0.2642 data_time: 0.0076 memory: 5828 grad_norm: 3.0716 loss: 2.7819 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7819 2023/06/05 00:36:13 - mmengine - INFO - Epoch(train) [44][ 280/2569] lr: 4.0000e-02 eta: 20:20:33 time: 0.2683 data_time: 0.0078 memory: 5828 grad_norm: 3.0911 loss: 2.8521 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8521 2023/06/05 00:36:19 - mmengine - INFO - Epoch(train) [44][ 300/2569] lr: 4.0000e-02 eta: 20:20:27 time: 0.2652 data_time: 0.0080 memory: 5828 grad_norm: 3.0616 loss: 2.7322 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7322 2023/06/05 00:36:24 - mmengine - INFO - Epoch(train) [44][ 320/2569] lr: 4.0000e-02 eta: 20:20:22 time: 0.2647 data_time: 0.0078 memory: 5828 grad_norm: 3.1514 loss: 2.3781 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3781 2023/06/05 00:36:29 - mmengine - INFO - Epoch(train) [44][ 340/2569] lr: 4.0000e-02 eta: 20:20:17 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 3.0969 loss: 2.4605 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4605 2023/06/05 00:36:34 - mmengine - INFO - Epoch(train) [44][ 360/2569] lr: 4.0000e-02 eta: 20:20:11 time: 0.2633 data_time: 0.0081 memory: 5828 grad_norm: 3.1347 loss: 2.7097 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7097 2023/06/05 00:36:40 - mmengine - INFO - Epoch(train) [44][ 380/2569] lr: 4.0000e-02 eta: 20:20:06 time: 0.2781 data_time: 0.0083 memory: 5828 grad_norm: 3.0713 loss: 2.4260 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4260 2023/06/05 00:36:45 - mmengine - INFO - Epoch(train) [44][ 400/2569] lr: 4.0000e-02 eta: 20:20:01 time: 0.2622 data_time: 0.0079 memory: 5828 grad_norm: 3.1578 loss: 2.4689 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4689 2023/06/05 00:36:51 - mmengine - INFO - Epoch(train) [44][ 420/2569] lr: 4.0000e-02 eta: 20:19:55 time: 0.2621 data_time: 0.0080 memory: 5828 grad_norm: 3.0421 loss: 2.4619 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4619 2023/06/05 00:36:56 - mmengine - INFO - Epoch(train) [44][ 440/2569] lr: 4.0000e-02 eta: 20:19:50 time: 0.2646 data_time: 0.0081 memory: 5828 grad_norm: 3.0517 loss: 2.5064 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5064 2023/06/05 00:37:01 - mmengine - INFO - Epoch(train) [44][ 460/2569] lr: 4.0000e-02 eta: 20:19:44 time: 0.2646 data_time: 0.0080 memory: 5828 grad_norm: 3.1174 loss: 2.6018 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6018 2023/06/05 00:37:06 - mmengine - INFO - Epoch(train) [44][ 480/2569] lr: 4.0000e-02 eta: 20:19:39 time: 0.2688 data_time: 0.0078 memory: 5828 grad_norm: 3.0507 loss: 2.5166 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5166 2023/06/05 00:37:12 - mmengine - INFO - Epoch(train) [44][ 500/2569] lr: 4.0000e-02 eta: 20:19:34 time: 0.2739 data_time: 0.0079 memory: 5828 grad_norm: 3.1406 loss: 2.7568 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7568 2023/06/05 00:37:17 - mmengine - INFO - Epoch(train) [44][ 520/2569] lr: 4.0000e-02 eta: 20:19:29 time: 0.2677 data_time: 0.0080 memory: 5828 grad_norm: 3.1252 loss: 2.5066 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5066 2023/06/05 00:37:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:37:23 - mmengine - INFO - Epoch(train) [44][ 540/2569] lr: 4.0000e-02 eta: 20:19:24 time: 0.2680 data_time: 0.0077 memory: 5828 grad_norm: 3.1305 loss: 2.5998 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5998 2023/06/05 00:37:28 - mmengine - INFO - Epoch(train) [44][ 560/2569] lr: 4.0000e-02 eta: 20:19:19 time: 0.2728 data_time: 0.0077 memory: 5828 grad_norm: 3.1100 loss: 2.4155 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4155 2023/06/05 00:37:33 - mmengine - INFO - Epoch(train) [44][ 580/2569] lr: 4.0000e-02 eta: 20:19:13 time: 0.2612 data_time: 0.0079 memory: 5828 grad_norm: 3.1027 loss: 2.7319 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7319 2023/06/05 00:37:39 - mmengine - INFO - Epoch(train) [44][ 600/2569] lr: 4.0000e-02 eta: 20:19:08 time: 0.2651 data_time: 0.0083 memory: 5828 grad_norm: 3.1404 loss: 2.7400 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7400 2023/06/05 00:37:44 - mmengine - INFO - Epoch(train) [44][ 620/2569] lr: 4.0000e-02 eta: 20:19:03 time: 0.2785 data_time: 0.0074 memory: 5828 grad_norm: 3.0914 loss: 2.6205 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6205 2023/06/05 00:37:49 - mmengine - INFO - Epoch(train) [44][ 640/2569] lr: 4.0000e-02 eta: 20:18:57 time: 0.2564 data_time: 0.0086 memory: 5828 grad_norm: 3.0830 loss: 2.4801 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4801 2023/06/05 00:37:55 - mmengine - INFO - Epoch(train) [44][ 660/2569] lr: 4.0000e-02 eta: 20:18:52 time: 0.2789 data_time: 0.0079 memory: 5828 grad_norm: 3.0919 loss: 2.5244 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5244 2023/06/05 00:38:00 - mmengine - INFO - Epoch(train) [44][ 680/2569] lr: 4.0000e-02 eta: 20:18:47 time: 0.2628 data_time: 0.0082 memory: 5828 grad_norm: 3.0701 loss: 2.3576 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3576 2023/06/05 00:38:06 - mmengine - INFO - Epoch(train) [44][ 700/2569] lr: 4.0000e-02 eta: 20:18:41 time: 0.2678 data_time: 0.0079 memory: 5828 grad_norm: 3.1014 loss: 2.6109 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6109 2023/06/05 00:38:11 - mmengine - INFO - Epoch(train) [44][ 720/2569] lr: 4.0000e-02 eta: 20:18:36 time: 0.2598 data_time: 0.0077 memory: 5828 grad_norm: 3.0510 loss: 2.5731 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5731 2023/06/05 00:38:16 - mmengine - INFO - Epoch(train) [44][ 740/2569] lr: 4.0000e-02 eta: 20:18:31 time: 0.2726 data_time: 0.0081 memory: 5828 grad_norm: 3.1437 loss: 2.6244 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6244 2023/06/05 00:38:22 - mmengine - INFO - Epoch(train) [44][ 760/2569] lr: 4.0000e-02 eta: 20:18:26 time: 0.2691 data_time: 0.0083 memory: 5828 grad_norm: 3.0116 loss: 2.4600 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4600 2023/06/05 00:38:27 - mmengine - INFO - Epoch(train) [44][ 780/2569] lr: 4.0000e-02 eta: 20:18:20 time: 0.2635 data_time: 0.0077 memory: 5828 grad_norm: 3.0965 loss: 2.9918 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9918 2023/06/05 00:38:32 - mmengine - INFO - Epoch(train) [44][ 800/2569] lr: 4.0000e-02 eta: 20:18:15 time: 0.2645 data_time: 0.0076 memory: 5828 grad_norm: 3.1253 loss: 2.2403 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2403 2023/06/05 00:38:38 - mmengine - INFO - Epoch(train) [44][ 820/2569] lr: 4.0000e-02 eta: 20:18:10 time: 0.2714 data_time: 0.0078 memory: 5828 grad_norm: 3.1210 loss: 2.5887 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5887 2023/06/05 00:38:43 - mmengine - INFO - Epoch(train) [44][ 840/2569] lr: 4.0000e-02 eta: 20:18:04 time: 0.2688 data_time: 0.0076 memory: 5828 grad_norm: 3.1291 loss: 2.3273 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3273 2023/06/05 00:38:48 - mmengine - INFO - Epoch(train) [44][ 860/2569] lr: 4.0000e-02 eta: 20:17:59 time: 0.2629 data_time: 0.0075 memory: 5828 grad_norm: 3.0574 loss: 2.3292 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3292 2023/06/05 00:38:54 - mmengine - INFO - Epoch(train) [44][ 880/2569] lr: 4.0000e-02 eta: 20:17:53 time: 0.2605 data_time: 0.0077 memory: 5828 grad_norm: 3.1501 loss: 2.8311 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8311 2023/06/05 00:38:59 - mmengine - INFO - Epoch(train) [44][ 900/2569] lr: 4.0000e-02 eta: 20:17:48 time: 0.2664 data_time: 0.0081 memory: 5828 grad_norm: 3.0901 loss: 2.5464 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5464 2023/06/05 00:39:04 - mmengine - INFO - Epoch(train) [44][ 920/2569] lr: 4.0000e-02 eta: 20:17:42 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 3.0581 loss: 2.6003 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6003 2023/06/05 00:39:09 - mmengine - INFO - Epoch(train) [44][ 940/2569] lr: 4.0000e-02 eta: 20:17:37 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 3.0899 loss: 2.9455 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9455 2023/06/05 00:39:15 - mmengine - INFO - Epoch(train) [44][ 960/2569] lr: 4.0000e-02 eta: 20:17:31 time: 0.2576 data_time: 0.0080 memory: 5828 grad_norm: 3.0823 loss: 2.3814 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3814 2023/06/05 00:39:20 - mmengine - INFO - Epoch(train) [44][ 980/2569] lr: 4.0000e-02 eta: 20:17:26 time: 0.2713 data_time: 0.0078 memory: 5828 grad_norm: 3.1024 loss: 2.6572 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6572 2023/06/05 00:39:25 - mmengine - INFO - Epoch(train) [44][1000/2569] lr: 4.0000e-02 eta: 20:17:20 time: 0.2617 data_time: 0.0081 memory: 5828 grad_norm: 3.0807 loss: 2.7626 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7626 2023/06/05 00:39:31 - mmengine - INFO - Epoch(train) [44][1020/2569] lr: 4.0000e-02 eta: 20:17:15 time: 0.2636 data_time: 0.0082 memory: 5828 grad_norm: 3.0043 loss: 2.4596 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4596 2023/06/05 00:39:36 - mmengine - INFO - Epoch(train) [44][1040/2569] lr: 4.0000e-02 eta: 20:17:09 time: 0.2578 data_time: 0.0079 memory: 5828 grad_norm: 3.0935 loss: 2.6882 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6882 2023/06/05 00:39:41 - mmengine - INFO - Epoch(train) [44][1060/2569] lr: 4.0000e-02 eta: 20:17:04 time: 0.2612 data_time: 0.0076 memory: 5828 grad_norm: 3.0780 loss: 2.6560 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6560 2023/06/05 00:39:46 - mmengine - INFO - Epoch(train) [44][1080/2569] lr: 4.0000e-02 eta: 20:16:58 time: 0.2623 data_time: 0.0079 memory: 5828 grad_norm: 3.1529 loss: 2.9091 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9091 2023/06/05 00:39:51 - mmengine - INFO - Epoch(train) [44][1100/2569] lr: 4.0000e-02 eta: 20:16:53 time: 0.2647 data_time: 0.0077 memory: 5828 grad_norm: 3.0764 loss: 2.6015 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6015 2023/06/05 00:39:57 - mmengine - INFO - Epoch(train) [44][1120/2569] lr: 4.0000e-02 eta: 20:16:47 time: 0.2695 data_time: 0.0076 memory: 5828 grad_norm: 3.1150 loss: 2.4913 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4913 2023/06/05 00:40:02 - mmengine - INFO - Epoch(train) [44][1140/2569] lr: 4.0000e-02 eta: 20:16:42 time: 0.2680 data_time: 0.0080 memory: 5828 grad_norm: 3.1304 loss: 2.2860 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2860 2023/06/05 00:40:07 - mmengine - INFO - Epoch(train) [44][1160/2569] lr: 4.0000e-02 eta: 20:16:37 time: 0.2610 data_time: 0.0079 memory: 5828 grad_norm: 3.0146 loss: 2.7794 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7794 2023/06/05 00:40:13 - mmengine - INFO - Epoch(train) [44][1180/2569] lr: 4.0000e-02 eta: 20:16:31 time: 0.2578 data_time: 0.0080 memory: 5828 grad_norm: 3.1267 loss: 2.7625 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7625 2023/06/05 00:40:18 - mmengine - INFO - Epoch(train) [44][1200/2569] lr: 4.0000e-02 eta: 20:16:25 time: 0.2589 data_time: 0.0081 memory: 5828 grad_norm: 3.1074 loss: 2.1915 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1915 2023/06/05 00:40:23 - mmengine - INFO - Epoch(train) [44][1220/2569] lr: 4.0000e-02 eta: 20:16:20 time: 0.2689 data_time: 0.0079 memory: 5828 grad_norm: 3.1685 loss: 2.5149 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5149 2023/06/05 00:40:29 - mmengine - INFO - Epoch(train) [44][1240/2569] lr: 4.0000e-02 eta: 20:16:15 time: 0.2679 data_time: 0.0082 memory: 5828 grad_norm: 3.0449 loss: 2.5515 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5515 2023/06/05 00:40:34 - mmengine - INFO - Epoch(train) [44][1260/2569] lr: 4.0000e-02 eta: 20:16:09 time: 0.2616 data_time: 0.0078 memory: 5828 grad_norm: 3.0467 loss: 2.5983 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5983 2023/06/05 00:40:39 - mmengine - INFO - Epoch(train) [44][1280/2569] lr: 4.0000e-02 eta: 20:16:03 time: 0.2587 data_time: 0.0084 memory: 5828 grad_norm: 3.0514 loss: 3.1987 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1987 2023/06/05 00:40:44 - mmengine - INFO - Epoch(train) [44][1300/2569] lr: 4.0000e-02 eta: 20:15:58 time: 0.2648 data_time: 0.0077 memory: 5828 grad_norm: 3.1269 loss: 2.7261 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7261 2023/06/05 00:40:49 - mmengine - INFO - Epoch(train) [44][1320/2569] lr: 4.0000e-02 eta: 20:15:52 time: 0.2576 data_time: 0.0079 memory: 5828 grad_norm: 3.0437 loss: 2.5293 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5293 2023/06/05 00:40:55 - mmengine - INFO - Epoch(train) [44][1340/2569] lr: 4.0000e-02 eta: 20:15:46 time: 0.2628 data_time: 0.0077 memory: 5828 grad_norm: 3.1573 loss: 2.3421 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3421 2023/06/05 00:41:00 - mmengine - INFO - Epoch(train) [44][1360/2569] lr: 4.0000e-02 eta: 20:15:41 time: 0.2600 data_time: 0.0071 memory: 5828 grad_norm: 3.1216 loss: 2.5311 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5311 2023/06/05 00:41:05 - mmengine - INFO - Epoch(train) [44][1380/2569] lr: 4.0000e-02 eta: 20:15:35 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.1076 loss: 2.3223 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3223 2023/06/05 00:41:11 - mmengine - INFO - Epoch(train) [44][1400/2569] lr: 4.0000e-02 eta: 20:15:30 time: 0.2658 data_time: 0.0081 memory: 5828 grad_norm: 3.2003 loss: 2.4992 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4992 2023/06/05 00:41:16 - mmengine - INFO - Epoch(train) [44][1420/2569] lr: 4.0000e-02 eta: 20:15:25 time: 0.2649 data_time: 0.0077 memory: 5828 grad_norm: 3.1430 loss: 2.6971 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6971 2023/06/05 00:41:21 - mmengine - INFO - Epoch(train) [44][1440/2569] lr: 4.0000e-02 eta: 20:15:19 time: 0.2630 data_time: 0.0080 memory: 5828 grad_norm: 3.0918 loss: 2.6619 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6619 2023/06/05 00:41:26 - mmengine - INFO - Epoch(train) [44][1460/2569] lr: 4.0000e-02 eta: 20:15:14 time: 0.2676 data_time: 0.0074 memory: 5828 grad_norm: 3.1250 loss: 2.7451 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7451 2023/06/05 00:41:32 - mmengine - INFO - Epoch(train) [44][1480/2569] lr: 4.0000e-02 eta: 20:15:08 time: 0.2591 data_time: 0.0080 memory: 5828 grad_norm: 3.0744 loss: 2.3436 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3436 2023/06/05 00:41:37 - mmengine - INFO - Epoch(train) [44][1500/2569] lr: 4.0000e-02 eta: 20:15:03 time: 0.2692 data_time: 0.0082 memory: 5828 grad_norm: 3.1421 loss: 2.7620 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7620 2023/06/05 00:41:42 - mmengine - INFO - Epoch(train) [44][1520/2569] lr: 4.0000e-02 eta: 20:14:57 time: 0.2572 data_time: 0.0084 memory: 5828 grad_norm: 3.1106 loss: 2.6191 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6191 2023/06/05 00:41:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:41:47 - mmengine - INFO - Epoch(train) [44][1540/2569] lr: 4.0000e-02 eta: 20:14:51 time: 0.2576 data_time: 0.0077 memory: 5828 grad_norm: 3.0747 loss: 2.8033 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.8033 2023/06/05 00:41:53 - mmengine - INFO - Epoch(train) [44][1560/2569] lr: 4.0000e-02 eta: 20:14:46 time: 0.2590 data_time: 0.0081 memory: 5828 grad_norm: 3.0998 loss: 2.6559 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6559 2023/06/05 00:41:58 - mmengine - INFO - Epoch(train) [44][1580/2569] lr: 4.0000e-02 eta: 20:14:40 time: 0.2576 data_time: 0.0077 memory: 5828 grad_norm: 3.0834 loss: 2.6168 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6168 2023/06/05 00:42:03 - mmengine - INFO - Epoch(train) [44][1600/2569] lr: 4.0000e-02 eta: 20:14:34 time: 0.2627 data_time: 0.0078 memory: 5828 grad_norm: 3.1101 loss: 2.6848 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6848 2023/06/05 00:42:08 - mmengine - INFO - Epoch(train) [44][1620/2569] lr: 4.0000e-02 eta: 20:14:29 time: 0.2606 data_time: 0.0079 memory: 5828 grad_norm: 3.0927 loss: 2.7092 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7092 2023/06/05 00:42:13 - mmengine - INFO - Epoch(train) [44][1640/2569] lr: 4.0000e-02 eta: 20:14:23 time: 0.2641 data_time: 0.0082 memory: 5828 grad_norm: 3.0874 loss: 2.5286 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5286 2023/06/05 00:42:19 - mmengine - INFO - Epoch(train) [44][1660/2569] lr: 4.0000e-02 eta: 20:14:18 time: 0.2636 data_time: 0.0080 memory: 5828 grad_norm: 3.1363 loss: 2.4850 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4850 2023/06/05 00:42:24 - mmengine - INFO - Epoch(train) [44][1680/2569] lr: 4.0000e-02 eta: 20:14:12 time: 0.2684 data_time: 0.0080 memory: 5828 grad_norm: 3.1772 loss: 2.6056 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6056 2023/06/05 00:42:29 - mmengine - INFO - Epoch(train) [44][1700/2569] lr: 4.0000e-02 eta: 20:14:07 time: 0.2639 data_time: 0.0077 memory: 5828 grad_norm: 3.0080 loss: 2.4203 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4203 2023/06/05 00:42:35 - mmengine - INFO - Epoch(train) [44][1720/2569] lr: 4.0000e-02 eta: 20:14:02 time: 0.2712 data_time: 0.0079 memory: 5828 grad_norm: 3.1042 loss: 3.0164 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0164 2023/06/05 00:42:40 - mmengine - INFO - Epoch(train) [44][1740/2569] lr: 4.0000e-02 eta: 20:13:56 time: 0.2638 data_time: 0.0081 memory: 5828 grad_norm: 3.0382 loss: 2.8136 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8136 2023/06/05 00:42:45 - mmengine - INFO - Epoch(train) [44][1760/2569] lr: 4.0000e-02 eta: 20:13:51 time: 0.2602 data_time: 0.0077 memory: 5828 grad_norm: 3.0742 loss: 2.4681 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.4681 2023/06/05 00:42:50 - mmengine - INFO - Epoch(train) [44][1780/2569] lr: 4.0000e-02 eta: 20:13:45 time: 0.2572 data_time: 0.0074 memory: 5828 grad_norm: 3.1031 loss: 2.9227 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9227 2023/06/05 00:42:56 - mmengine - INFO - Epoch(train) [44][1800/2569] lr: 4.0000e-02 eta: 20:13:40 time: 0.2711 data_time: 0.0075 memory: 5828 grad_norm: 3.0940 loss: 2.5108 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5108 2023/06/05 00:43:01 - mmengine - INFO - Epoch(train) [44][1820/2569] lr: 4.0000e-02 eta: 20:13:34 time: 0.2629 data_time: 0.0080 memory: 5828 grad_norm: 3.0829 loss: 2.6479 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6479 2023/06/05 00:43:07 - mmengine - INFO - Epoch(train) [44][1840/2569] lr: 4.0000e-02 eta: 20:13:29 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 3.0647 loss: 2.4438 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4438 2023/06/05 00:43:12 - mmengine - INFO - Epoch(train) [44][1860/2569] lr: 4.0000e-02 eta: 20:13:24 time: 0.2619 data_time: 0.0082 memory: 5828 grad_norm: 3.1008 loss: 2.5956 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5956 2023/06/05 00:43:17 - mmengine - INFO - Epoch(train) [44][1880/2569] lr: 4.0000e-02 eta: 20:13:18 time: 0.2713 data_time: 0.0077 memory: 5828 grad_norm: 3.0639 loss: 2.7805 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7805 2023/06/05 00:43:22 - mmengine - INFO - Epoch(train) [44][1900/2569] lr: 4.0000e-02 eta: 20:13:13 time: 0.2581 data_time: 0.0076 memory: 5828 grad_norm: 3.0226 loss: 2.3950 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3950 2023/06/05 00:43:28 - mmengine - INFO - Epoch(train) [44][1920/2569] lr: 4.0000e-02 eta: 20:13:07 time: 0.2570 data_time: 0.0104 memory: 5828 grad_norm: 3.0509 loss: 2.4324 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4324 2023/06/05 00:43:33 - mmengine - INFO - Epoch(train) [44][1940/2569] lr: 4.0000e-02 eta: 20:13:01 time: 0.2625 data_time: 0.0081 memory: 5828 grad_norm: 3.0407 loss: 2.7371 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7371 2023/06/05 00:43:38 - mmengine - INFO - Epoch(train) [44][1960/2569] lr: 4.0000e-02 eta: 20:12:56 time: 0.2574 data_time: 0.0077 memory: 5828 grad_norm: 3.0257 loss: 2.6394 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6394 2023/06/05 00:43:43 - mmengine - INFO - Epoch(train) [44][1980/2569] lr: 4.0000e-02 eta: 20:12:50 time: 0.2706 data_time: 0.0092 memory: 5828 grad_norm: 3.0992 loss: 2.2005 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2005 2023/06/05 00:43:49 - mmengine - INFO - Epoch(train) [44][2000/2569] lr: 4.0000e-02 eta: 20:12:45 time: 0.2621 data_time: 0.0080 memory: 5828 grad_norm: 3.0520 loss: 2.6693 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6693 2023/06/05 00:43:54 - mmengine - INFO - Epoch(train) [44][2020/2569] lr: 4.0000e-02 eta: 20:12:40 time: 0.2680 data_time: 0.0080 memory: 5828 grad_norm: 3.0810 loss: 2.7924 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7924 2023/06/05 00:43:59 - mmengine - INFO - Epoch(train) [44][2040/2569] lr: 4.0000e-02 eta: 20:12:35 time: 0.2708 data_time: 0.0087 memory: 5828 grad_norm: 3.0944 loss: 2.5304 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5304 2023/06/05 00:44:05 - mmengine - INFO - Epoch(train) [44][2060/2569] lr: 4.0000e-02 eta: 20:12:29 time: 0.2683 data_time: 0.0078 memory: 5828 grad_norm: 3.1247 loss: 2.8463 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8463 2023/06/05 00:44:10 - mmengine - INFO - Epoch(train) [44][2080/2569] lr: 4.0000e-02 eta: 20:12:24 time: 0.2688 data_time: 0.0077 memory: 5828 grad_norm: 3.0728 loss: 2.5369 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5369 2023/06/05 00:44:15 - mmengine - INFO - Epoch(train) [44][2100/2569] lr: 4.0000e-02 eta: 20:12:19 time: 0.2676 data_time: 0.0080 memory: 5828 grad_norm: 3.0393 loss: 2.6626 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6626 2023/06/05 00:44:21 - mmengine - INFO - Epoch(train) [44][2120/2569] lr: 4.0000e-02 eta: 20:12:14 time: 0.2696 data_time: 0.0082 memory: 5828 grad_norm: 3.0606 loss: 2.6695 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6695 2023/06/05 00:44:26 - mmengine - INFO - Epoch(train) [44][2140/2569] lr: 4.0000e-02 eta: 20:12:08 time: 0.2575 data_time: 0.0078 memory: 5828 grad_norm: 3.1448 loss: 2.3210 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3210 2023/06/05 00:44:31 - mmengine - INFO - Epoch(train) [44][2160/2569] lr: 4.0000e-02 eta: 20:12:02 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 3.0923 loss: 2.5057 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5057 2023/06/05 00:44:36 - mmengine - INFO - Epoch(train) [44][2180/2569] lr: 4.0000e-02 eta: 20:11:57 time: 0.2573 data_time: 0.0082 memory: 5828 grad_norm: 3.1259 loss: 2.8071 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8071 2023/06/05 00:44:42 - mmengine - INFO - Epoch(train) [44][2200/2569] lr: 4.0000e-02 eta: 20:11:51 time: 0.2571 data_time: 0.0079 memory: 5828 grad_norm: 3.0688 loss: 2.7342 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7342 2023/06/05 00:44:47 - mmengine - INFO - Epoch(train) [44][2220/2569] lr: 4.0000e-02 eta: 20:11:45 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 3.0291 loss: 2.6296 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6296 2023/06/05 00:44:52 - mmengine - INFO - Epoch(train) [44][2240/2569] lr: 4.0000e-02 eta: 20:11:40 time: 0.2651 data_time: 0.0078 memory: 5828 grad_norm: 3.0693 loss: 2.3321 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3321 2023/06/05 00:44:57 - mmengine - INFO - Epoch(train) [44][2260/2569] lr: 4.0000e-02 eta: 20:11:34 time: 0.2586 data_time: 0.0079 memory: 5828 grad_norm: 3.1737 loss: 2.2510 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2510 2023/06/05 00:45:03 - mmengine - INFO - Epoch(train) [44][2280/2569] lr: 4.0000e-02 eta: 20:11:29 time: 0.2692 data_time: 0.0077 memory: 5828 grad_norm: 3.0943 loss: 2.7621 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7621 2023/06/05 00:45:08 - mmengine - INFO - Epoch(train) [44][2300/2569] lr: 4.0000e-02 eta: 20:11:23 time: 0.2579 data_time: 0.0081 memory: 5828 grad_norm: 3.1041 loss: 2.6902 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6902 2023/06/05 00:45:13 - mmengine - INFO - Epoch(train) [44][2320/2569] lr: 4.0000e-02 eta: 20:11:17 time: 0.2607 data_time: 0.0080 memory: 5828 grad_norm: 2.9872 loss: 3.0849 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0849 2023/06/05 00:45:18 - mmengine - INFO - Epoch(train) [44][2340/2569] lr: 4.0000e-02 eta: 20:11:12 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 3.1128 loss: 2.6957 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6957 2023/06/05 00:45:23 - mmengine - INFO - Epoch(train) [44][2360/2569] lr: 4.0000e-02 eta: 20:11:06 time: 0.2577 data_time: 0.0077 memory: 5828 grad_norm: 3.0716 loss: 2.6311 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6311 2023/06/05 00:45:29 - mmengine - INFO - Epoch(train) [44][2380/2569] lr: 4.0000e-02 eta: 20:11:01 time: 0.2635 data_time: 0.0081 memory: 5828 grad_norm: 3.1258 loss: 2.4662 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4662 2023/06/05 00:45:34 - mmengine - INFO - Epoch(train) [44][2400/2569] lr: 4.0000e-02 eta: 20:10:55 time: 0.2583 data_time: 0.0073 memory: 5828 grad_norm: 3.0287 loss: 2.3308 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3308 2023/06/05 00:45:39 - mmengine - INFO - Epoch(train) [44][2420/2569] lr: 4.0000e-02 eta: 20:10:49 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 3.1126 loss: 2.4158 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4158 2023/06/05 00:45:45 - mmengine - INFO - Epoch(train) [44][2440/2569] lr: 4.0000e-02 eta: 20:10:44 time: 0.2675 data_time: 0.0082 memory: 5828 grad_norm: 3.1141 loss: 2.6322 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6322 2023/06/05 00:45:50 - mmengine - INFO - Epoch(train) [44][2460/2569] lr: 4.0000e-02 eta: 20:10:38 time: 0.2593 data_time: 0.0076 memory: 5828 grad_norm: 3.1254 loss: 2.6271 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6271 2023/06/05 00:45:55 - mmengine - INFO - Epoch(train) [44][2480/2569] lr: 4.0000e-02 eta: 20:10:33 time: 0.2666 data_time: 0.0082 memory: 5828 grad_norm: 3.1428 loss: 2.6144 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6144 2023/06/05 00:46:00 - mmengine - INFO - Epoch(train) [44][2500/2569] lr: 4.0000e-02 eta: 20:10:28 time: 0.2681 data_time: 0.0082 memory: 5828 grad_norm: 3.0171 loss: 3.0225 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0225 2023/06/05 00:46:06 - mmengine - INFO - Epoch(train) [44][2520/2569] lr: 4.0000e-02 eta: 20:10:23 time: 0.2696 data_time: 0.0079 memory: 5828 grad_norm: 3.0989 loss: 2.7538 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7538 2023/06/05 00:46:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:46:11 - mmengine - INFO - Epoch(train) [44][2540/2569] lr: 4.0000e-02 eta: 20:10:17 time: 0.2581 data_time: 0.0076 memory: 5828 grad_norm: 3.1289 loss: 2.5750 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5750 2023/06/05 00:46:16 - mmengine - INFO - Epoch(train) [44][2560/2569] lr: 4.0000e-02 eta: 20:10:11 time: 0.2597 data_time: 0.0078 memory: 5828 grad_norm: 3.0981 loss: 2.6858 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6858 2023/06/05 00:46:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:46:18 - mmengine - INFO - Epoch(train) [44][2569/2569] lr: 4.0000e-02 eta: 20:10:08 time: 0.2541 data_time: 0.0076 memory: 5828 grad_norm: 3.1570 loss: 2.5754 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.5754 2023/06/05 00:46:18 - mmengine - INFO - Saving checkpoint at 44 epochs 2023/06/05 00:46:26 - mmengine - INFO - Epoch(train) [45][ 20/2569] lr: 4.0000e-02 eta: 20:10:04 time: 0.2874 data_time: 0.0393 memory: 5828 grad_norm: 3.0864 loss: 2.6947 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6947 2023/06/05 00:46:31 - mmengine - INFO - Epoch(train) [45][ 40/2569] lr: 4.0000e-02 eta: 20:09:58 time: 0.2575 data_time: 0.0085 memory: 5828 grad_norm: 3.1153 loss: 2.3437 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3437 2023/06/05 00:46:37 - mmengine - INFO - Epoch(train) [45][ 60/2569] lr: 4.0000e-02 eta: 20:09:53 time: 0.2623 data_time: 0.0079 memory: 5828 grad_norm: 3.1057 loss: 2.6242 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6242 2023/06/05 00:46:42 - mmengine - INFO - Epoch(train) [45][ 80/2569] lr: 4.0000e-02 eta: 20:09:47 time: 0.2623 data_time: 0.0083 memory: 5828 grad_norm: 3.0339 loss: 2.5137 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5137 2023/06/05 00:46:47 - mmengine - INFO - Epoch(train) [45][ 100/2569] lr: 4.0000e-02 eta: 20:09:42 time: 0.2623 data_time: 0.0077 memory: 5828 grad_norm: 3.1123 loss: 2.8080 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8080 2023/06/05 00:46:52 - mmengine - INFO - Epoch(train) [45][ 120/2569] lr: 4.0000e-02 eta: 20:09:36 time: 0.2630 data_time: 0.0078 memory: 5828 grad_norm: 3.0932 loss: 2.2948 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2948 2023/06/05 00:46:58 - mmengine - INFO - Epoch(train) [45][ 140/2569] lr: 4.0000e-02 eta: 20:09:31 time: 0.2668 data_time: 0.0083 memory: 5828 grad_norm: 3.1771 loss: 2.2996 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2996 2023/06/05 00:47:03 - mmengine - INFO - Epoch(train) [45][ 160/2569] lr: 4.0000e-02 eta: 20:09:25 time: 0.2588 data_time: 0.0082 memory: 5828 grad_norm: 3.0976 loss: 2.4072 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4072 2023/06/05 00:47:08 - mmengine - INFO - Epoch(train) [45][ 180/2569] lr: 4.0000e-02 eta: 20:09:19 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 3.0959 loss: 2.5943 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5943 2023/06/05 00:47:13 - mmengine - INFO - Epoch(train) [45][ 200/2569] lr: 4.0000e-02 eta: 20:09:14 time: 0.2580 data_time: 0.0078 memory: 5828 grad_norm: 3.0875 loss: 2.6953 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6953 2023/06/05 00:47:18 - mmengine - INFO - Epoch(train) [45][ 220/2569] lr: 4.0000e-02 eta: 20:09:08 time: 0.2637 data_time: 0.0077 memory: 5828 grad_norm: 3.0725 loss: 2.5559 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5559 2023/06/05 00:47:24 - mmengine - INFO - Epoch(train) [45][ 240/2569] lr: 4.0000e-02 eta: 20:09:03 time: 0.2619 data_time: 0.0079 memory: 5828 grad_norm: 3.0869 loss: 2.7714 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7714 2023/06/05 00:47:29 - mmengine - INFO - Epoch(train) [45][ 260/2569] lr: 4.0000e-02 eta: 20:08:57 time: 0.2584 data_time: 0.0078 memory: 5828 grad_norm: 3.0522 loss: 2.4046 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4046 2023/06/05 00:47:34 - mmengine - INFO - Epoch(train) [45][ 280/2569] lr: 4.0000e-02 eta: 20:08:52 time: 0.2651 data_time: 0.0081 memory: 5828 grad_norm: 3.0631 loss: 2.3886 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3886 2023/06/05 00:47:39 - mmengine - INFO - Epoch(train) [45][ 300/2569] lr: 4.0000e-02 eta: 20:08:46 time: 0.2571 data_time: 0.0079 memory: 5828 grad_norm: 3.0928 loss: 2.6787 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6787 2023/06/05 00:47:45 - mmengine - INFO - Epoch(train) [45][ 320/2569] lr: 4.0000e-02 eta: 20:08:40 time: 0.2593 data_time: 0.0079 memory: 5828 grad_norm: 3.0550 loss: 2.7702 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7702 2023/06/05 00:47:50 - mmengine - INFO - Epoch(train) [45][ 340/2569] lr: 4.0000e-02 eta: 20:08:35 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 3.0861 loss: 2.7309 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7309 2023/06/05 00:47:55 - mmengine - INFO - Epoch(train) [45][ 360/2569] lr: 4.0000e-02 eta: 20:08:29 time: 0.2620 data_time: 0.0079 memory: 5828 grad_norm: 3.0474 loss: 2.4630 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4630 2023/06/05 00:48:00 - mmengine - INFO - Epoch(train) [45][ 380/2569] lr: 4.0000e-02 eta: 20:08:23 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 3.1137 loss: 2.2501 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.2501 2023/06/05 00:48:06 - mmengine - INFO - Epoch(train) [45][ 400/2569] lr: 4.0000e-02 eta: 20:08:18 time: 0.2620 data_time: 0.0082 memory: 5828 grad_norm: 3.0814 loss: 2.5796 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5796 2023/06/05 00:48:11 - mmengine - INFO - Epoch(train) [45][ 420/2569] lr: 4.0000e-02 eta: 20:08:12 time: 0.2659 data_time: 0.0077 memory: 5828 grad_norm: 3.0603 loss: 2.7318 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7318 2023/06/05 00:48:16 - mmengine - INFO - Epoch(train) [45][ 440/2569] lr: 4.0000e-02 eta: 20:08:07 time: 0.2648 data_time: 0.0079 memory: 5828 grad_norm: 3.1397 loss: 2.7410 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7410 2023/06/05 00:48:21 - mmengine - INFO - Epoch(train) [45][ 460/2569] lr: 4.0000e-02 eta: 20:08:02 time: 0.2630 data_time: 0.0076 memory: 5828 grad_norm: 3.1056 loss: 2.6459 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6459 2023/06/05 00:48:27 - mmengine - INFO - Epoch(train) [45][ 480/2569] lr: 4.0000e-02 eta: 20:07:56 time: 0.2624 data_time: 0.0091 memory: 5828 grad_norm: 3.1247 loss: 2.8755 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8755 2023/06/05 00:48:32 - mmengine - INFO - Epoch(train) [45][ 500/2569] lr: 4.0000e-02 eta: 20:07:50 time: 0.2602 data_time: 0.0078 memory: 5828 grad_norm: 3.1204 loss: 2.6416 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6416 2023/06/05 00:48:37 - mmengine - INFO - Epoch(train) [45][ 520/2569] lr: 4.0000e-02 eta: 20:07:45 time: 0.2634 data_time: 0.0079 memory: 5828 grad_norm: 3.0546 loss: 2.8561 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8561 2023/06/05 00:48:43 - mmengine - INFO - Epoch(train) [45][ 540/2569] lr: 4.0000e-02 eta: 20:07:40 time: 0.2754 data_time: 0.0075 memory: 5828 grad_norm: 3.0230 loss: 2.7911 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7911 2023/06/05 00:48:48 - mmengine - INFO - Epoch(train) [45][ 560/2569] lr: 4.0000e-02 eta: 20:07:35 time: 0.2665 data_time: 0.0081 memory: 5828 grad_norm: 3.0411 loss: 2.4881 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4881 2023/06/05 00:48:53 - mmengine - INFO - Epoch(train) [45][ 580/2569] lr: 4.0000e-02 eta: 20:07:29 time: 0.2629 data_time: 0.0074 memory: 5828 grad_norm: 3.0523 loss: 2.4927 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4927 2023/06/05 00:48:59 - mmengine - INFO - Epoch(train) [45][ 600/2569] lr: 4.0000e-02 eta: 20:07:24 time: 0.2710 data_time: 0.0082 memory: 5828 grad_norm: 3.0546 loss: 2.6552 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6552 2023/06/05 00:49:04 - mmengine - INFO - Epoch(train) [45][ 620/2569] lr: 4.0000e-02 eta: 20:07:18 time: 0.2624 data_time: 0.0079 memory: 5828 grad_norm: 3.0667 loss: 2.6312 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6312 2023/06/05 00:49:09 - mmengine - INFO - Epoch(train) [45][ 640/2569] lr: 4.0000e-02 eta: 20:07:13 time: 0.2712 data_time: 0.0079 memory: 5828 grad_norm: 3.0424 loss: 2.7441 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7441 2023/06/05 00:49:15 - mmengine - INFO - Epoch(train) [45][ 660/2569] lr: 4.0000e-02 eta: 20:07:08 time: 0.2602 data_time: 0.0078 memory: 5828 grad_norm: 3.0599 loss: 2.5937 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5937 2023/06/05 00:49:20 - mmengine - INFO - Epoch(train) [45][ 680/2569] lr: 4.0000e-02 eta: 20:07:02 time: 0.2630 data_time: 0.0078 memory: 5828 grad_norm: 3.0924 loss: 2.5748 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5748 2023/06/05 00:49:25 - mmengine - INFO - Epoch(train) [45][ 700/2569] lr: 4.0000e-02 eta: 20:06:57 time: 0.2619 data_time: 0.0080 memory: 5828 grad_norm: 3.1038 loss: 2.9322 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9322 2023/06/05 00:49:30 - mmengine - INFO - Epoch(train) [45][ 720/2569] lr: 4.0000e-02 eta: 20:06:51 time: 0.2563 data_time: 0.0083 memory: 5828 grad_norm: 2.9947 loss: 2.6460 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6460 2023/06/05 00:49:35 - mmengine - INFO - Epoch(train) [45][ 740/2569] lr: 4.0000e-02 eta: 20:06:45 time: 0.2579 data_time: 0.0081 memory: 5828 grad_norm: 3.0353 loss: 2.6738 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6738 2023/06/05 00:49:41 - mmengine - INFO - Epoch(train) [45][ 760/2569] lr: 4.0000e-02 eta: 20:06:39 time: 0.2572 data_time: 0.0079 memory: 5828 grad_norm: 3.0688 loss: 2.4527 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4527 2023/06/05 00:49:46 - mmengine - INFO - Epoch(train) [45][ 780/2569] lr: 4.0000e-02 eta: 20:06:34 time: 0.2652 data_time: 0.0078 memory: 5828 grad_norm: 3.1140 loss: 2.7914 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7914 2023/06/05 00:49:51 - mmengine - INFO - Epoch(train) [45][ 800/2569] lr: 4.0000e-02 eta: 20:06:28 time: 0.2644 data_time: 0.0081 memory: 5828 grad_norm: 3.1863 loss: 2.3591 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3591 2023/06/05 00:49:56 - mmengine - INFO - Epoch(train) [45][ 820/2569] lr: 4.0000e-02 eta: 20:06:23 time: 0.2619 data_time: 0.0083 memory: 5828 grad_norm: 3.0886 loss: 2.5888 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5888 2023/06/05 00:50:02 - mmengine - INFO - Epoch(train) [45][ 840/2569] lr: 4.0000e-02 eta: 20:06:17 time: 0.2586 data_time: 0.0082 memory: 5828 grad_norm: 3.0931 loss: 2.2070 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2070 2023/06/05 00:50:07 - mmengine - INFO - Epoch(train) [45][ 860/2569] lr: 4.0000e-02 eta: 20:06:12 time: 0.2619 data_time: 0.0081 memory: 5828 grad_norm: 3.1543 loss: 2.5264 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5264 2023/06/05 00:50:12 - mmengine - INFO - Epoch(train) [45][ 880/2569] lr: 4.0000e-02 eta: 20:06:06 time: 0.2606 data_time: 0.0082 memory: 5828 grad_norm: 3.0897 loss: 2.4512 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4512 2023/06/05 00:50:17 - mmengine - INFO - Epoch(train) [45][ 900/2569] lr: 4.0000e-02 eta: 20:06:00 time: 0.2624 data_time: 0.0074 memory: 5828 grad_norm: 3.1797 loss: 2.5637 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5637 2023/06/05 00:50:22 - mmengine - INFO - Epoch(train) [45][ 920/2569] lr: 4.0000e-02 eta: 20:05:55 time: 0.2614 data_time: 0.0085 memory: 5828 grad_norm: 3.1177 loss: 2.7129 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7129 2023/06/05 00:50:28 - mmengine - INFO - Epoch(train) [45][ 940/2569] lr: 4.0000e-02 eta: 20:05:49 time: 0.2637 data_time: 0.0078 memory: 5828 grad_norm: 3.0514 loss: 2.8907 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8907 2023/06/05 00:50:33 - mmengine - INFO - Epoch(train) [45][ 960/2569] lr: 4.0000e-02 eta: 20:05:44 time: 0.2679 data_time: 0.0080 memory: 5828 grad_norm: 3.1525 loss: 2.7304 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7304 2023/06/05 00:50:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:50:38 - mmengine - INFO - Epoch(train) [45][ 980/2569] lr: 4.0000e-02 eta: 20:05:39 time: 0.2629 data_time: 0.0081 memory: 5828 grad_norm: 3.0585 loss: 2.5821 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5821 2023/06/05 00:50:44 - mmengine - INFO - Epoch(train) [45][1000/2569] lr: 4.0000e-02 eta: 20:05:33 time: 0.2603 data_time: 0.0084 memory: 5828 grad_norm: 3.0526 loss: 2.7978 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7978 2023/06/05 00:50:49 - mmengine - INFO - Epoch(train) [45][1020/2569] lr: 4.0000e-02 eta: 20:05:28 time: 0.2664 data_time: 0.0076 memory: 5828 grad_norm: 3.1456 loss: 2.5498 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5498 2023/06/05 00:50:54 - mmengine - INFO - Epoch(train) [45][1040/2569] lr: 4.0000e-02 eta: 20:05:22 time: 0.2565 data_time: 0.0085 memory: 5828 grad_norm: 3.1327 loss: 2.4443 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4443 2023/06/05 00:50:59 - mmengine - INFO - Epoch(train) [45][1060/2569] lr: 4.0000e-02 eta: 20:05:16 time: 0.2653 data_time: 0.0075 memory: 5828 grad_norm: 3.0708 loss: 2.6707 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6707 2023/06/05 00:51:05 - mmengine - INFO - Epoch(train) [45][1080/2569] lr: 4.0000e-02 eta: 20:05:11 time: 0.2575 data_time: 0.0084 memory: 5828 grad_norm: 3.0569 loss: 2.4715 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4715 2023/06/05 00:51:10 - mmengine - INFO - Epoch(train) [45][1100/2569] lr: 4.0000e-02 eta: 20:05:05 time: 0.2581 data_time: 0.0071 memory: 5828 grad_norm: 3.0329 loss: 2.6402 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6402 2023/06/05 00:51:15 - mmengine - INFO - Epoch(train) [45][1120/2569] lr: 4.0000e-02 eta: 20:05:00 time: 0.2674 data_time: 0.0080 memory: 5828 grad_norm: 3.0342 loss: 2.2746 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2746 2023/06/05 00:51:20 - mmengine - INFO - Epoch(train) [45][1140/2569] lr: 4.0000e-02 eta: 20:04:54 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 3.0451 loss: 2.3783 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3783 2023/06/05 00:51:26 - mmengine - INFO - Epoch(train) [45][1160/2569] lr: 4.0000e-02 eta: 20:04:48 time: 0.2612 data_time: 0.0080 memory: 5828 grad_norm: 3.0733 loss: 2.4701 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4701 2023/06/05 00:51:31 - mmengine - INFO - Epoch(train) [45][1180/2569] lr: 4.0000e-02 eta: 20:04:43 time: 0.2615 data_time: 0.0077 memory: 5828 grad_norm: 3.1068 loss: 2.6247 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6247 2023/06/05 00:51:36 - mmengine - INFO - Epoch(train) [45][1200/2569] lr: 4.0000e-02 eta: 20:04:37 time: 0.2620 data_time: 0.0083 memory: 5828 grad_norm: 3.0907 loss: 2.7273 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7273 2023/06/05 00:51:41 - mmengine - INFO - Epoch(train) [45][1220/2569] lr: 4.0000e-02 eta: 20:04:32 time: 0.2583 data_time: 0.0080 memory: 5828 grad_norm: 3.1177 loss: 2.3889 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3889 2023/06/05 00:51:46 - mmengine - INFO - Epoch(train) [45][1240/2569] lr: 4.0000e-02 eta: 20:04:26 time: 0.2575 data_time: 0.0088 memory: 5828 grad_norm: 3.0823 loss: 2.5105 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5105 2023/06/05 00:51:51 - mmengine - INFO - Epoch(train) [45][1260/2569] lr: 4.0000e-02 eta: 20:04:20 time: 0.2577 data_time: 0.0082 memory: 5828 grad_norm: 3.1072 loss: 2.6720 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6720 2023/06/05 00:51:57 - mmengine - INFO - Epoch(train) [45][1280/2569] lr: 4.0000e-02 eta: 20:04:14 time: 0.2594 data_time: 0.0079 memory: 5828 grad_norm: 3.1142 loss: 2.4521 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4521 2023/06/05 00:52:02 - mmengine - INFO - Epoch(train) [45][1300/2569] lr: 4.0000e-02 eta: 20:04:09 time: 0.2670 data_time: 0.0080 memory: 5828 grad_norm: 3.0735 loss: 2.5861 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5861 2023/06/05 00:52:07 - mmengine - INFO - Epoch(train) [45][1320/2569] lr: 4.0000e-02 eta: 20:04:04 time: 0.2660 data_time: 0.0088 memory: 5828 grad_norm: 3.0771 loss: 2.3645 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3645 2023/06/05 00:52:13 - mmengine - INFO - Epoch(train) [45][1340/2569] lr: 4.0000e-02 eta: 20:03:58 time: 0.2619 data_time: 0.0076 memory: 5828 grad_norm: 3.0019 loss: 2.7898 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7898 2023/06/05 00:52:18 - mmengine - INFO - Epoch(train) [45][1360/2569] lr: 4.0000e-02 eta: 20:03:53 time: 0.2662 data_time: 0.0079 memory: 5828 grad_norm: 3.0422 loss: 2.4802 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4802 2023/06/05 00:52:23 - mmengine - INFO - Epoch(train) [45][1380/2569] lr: 4.0000e-02 eta: 20:03:47 time: 0.2581 data_time: 0.0081 memory: 5828 grad_norm: 3.0578 loss: 2.6837 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6837 2023/06/05 00:52:28 - mmengine - INFO - Epoch(train) [45][1400/2569] lr: 4.0000e-02 eta: 20:03:41 time: 0.2578 data_time: 0.0081 memory: 5828 grad_norm: 3.0662 loss: 2.9122 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9122 2023/06/05 00:52:34 - mmengine - INFO - Epoch(train) [45][1420/2569] lr: 4.0000e-02 eta: 20:03:36 time: 0.2659 data_time: 0.0076 memory: 5828 grad_norm: 3.0477 loss: 2.8715 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8715 2023/06/05 00:52:39 - mmengine - INFO - Epoch(train) [45][1440/2569] lr: 4.0000e-02 eta: 20:03:31 time: 0.2702 data_time: 0.0079 memory: 5828 grad_norm: 3.0891 loss: 2.5924 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5924 2023/06/05 00:52:44 - mmengine - INFO - Epoch(train) [45][1460/2569] lr: 4.0000e-02 eta: 20:03:26 time: 0.2689 data_time: 0.0076 memory: 5828 grad_norm: 3.1557 loss: 2.4830 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.4830 2023/06/05 00:52:50 - mmengine - INFO - Epoch(train) [45][1480/2569] lr: 4.0000e-02 eta: 20:03:20 time: 0.2624 data_time: 0.0083 memory: 5828 grad_norm: 3.1155 loss: 2.6639 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6639 2023/06/05 00:52:55 - mmengine - INFO - Epoch(train) [45][1500/2569] lr: 4.0000e-02 eta: 20:03:15 time: 0.2693 data_time: 0.0081 memory: 5828 grad_norm: 3.0801 loss: 2.5260 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5260 2023/06/05 00:53:00 - mmengine - INFO - Epoch(train) [45][1520/2569] lr: 4.0000e-02 eta: 20:03:09 time: 0.2597 data_time: 0.0077 memory: 5828 grad_norm: 3.0527 loss: 3.0253 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0253 2023/06/05 00:53:06 - mmengine - INFO - Epoch(train) [45][1540/2569] lr: 4.0000e-02 eta: 20:03:04 time: 0.2727 data_time: 0.0081 memory: 5828 grad_norm: 3.0414 loss: 2.5419 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5419 2023/06/05 00:53:11 - mmengine - INFO - Epoch(train) [45][1560/2569] lr: 4.0000e-02 eta: 20:02:59 time: 0.2653 data_time: 0.0080 memory: 5828 grad_norm: 3.1682 loss: 2.4244 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4244 2023/06/05 00:53:16 - mmengine - INFO - Epoch(train) [45][1580/2569] lr: 4.0000e-02 eta: 20:02:53 time: 0.2650 data_time: 0.0080 memory: 5828 grad_norm: 3.0740 loss: 2.5038 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5038 2023/06/05 00:53:22 - mmengine - INFO - Epoch(train) [45][1600/2569] lr: 4.0000e-02 eta: 20:02:48 time: 0.2619 data_time: 0.0081 memory: 5828 grad_norm: 3.0572 loss: 2.7095 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7095 2023/06/05 00:53:27 - mmengine - INFO - Epoch(train) [45][1620/2569] lr: 4.0000e-02 eta: 20:02:42 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 3.0480 loss: 2.6080 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6080 2023/06/05 00:53:32 - mmengine - INFO - Epoch(train) [45][1640/2569] lr: 4.0000e-02 eta: 20:02:37 time: 0.2632 data_time: 0.0081 memory: 5828 grad_norm: 3.0858 loss: 3.0103 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.0103 2023/06/05 00:53:38 - mmengine - INFO - Epoch(train) [45][1660/2569] lr: 4.0000e-02 eta: 20:02:32 time: 0.2732 data_time: 0.0073 memory: 5828 grad_norm: 3.0858 loss: 2.3277 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3277 2023/06/05 00:53:43 - mmengine - INFO - Epoch(train) [45][1680/2569] lr: 4.0000e-02 eta: 20:02:26 time: 0.2554 data_time: 0.0077 memory: 5828 grad_norm: 3.1835 loss: 2.5224 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5224 2023/06/05 00:53:48 - mmengine - INFO - Epoch(train) [45][1700/2569] lr: 4.0000e-02 eta: 20:02:21 time: 0.2708 data_time: 0.0080 memory: 5828 grad_norm: 3.0634 loss: 2.7436 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7436 2023/06/05 00:53:53 - mmengine - INFO - Epoch(train) [45][1720/2569] lr: 4.0000e-02 eta: 20:02:15 time: 0.2580 data_time: 0.0083 memory: 5828 grad_norm: 3.1194 loss: 2.3304 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3304 2023/06/05 00:53:59 - mmengine - INFO - Epoch(train) [45][1740/2569] lr: 4.0000e-02 eta: 20:02:10 time: 0.2677 data_time: 0.0076 memory: 5828 grad_norm: 3.0529 loss: 2.3166 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3166 2023/06/05 00:54:04 - mmengine - INFO - Epoch(train) [45][1760/2569] lr: 4.0000e-02 eta: 20:02:04 time: 0.2567 data_time: 0.0084 memory: 5828 grad_norm: 3.1123 loss: 2.7152 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7152 2023/06/05 00:54:09 - mmengine - INFO - Epoch(train) [45][1780/2569] lr: 4.0000e-02 eta: 20:01:58 time: 0.2601 data_time: 0.0083 memory: 5828 grad_norm: 3.0055 loss: 2.4200 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4200 2023/06/05 00:54:14 - mmengine - INFO - Epoch(train) [45][1800/2569] lr: 4.0000e-02 eta: 20:01:53 time: 0.2625 data_time: 0.0078 memory: 5828 grad_norm: 3.1459 loss: 2.2754 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2754 2023/06/05 00:54:20 - mmengine - INFO - Epoch(train) [45][1820/2569] lr: 4.0000e-02 eta: 20:01:48 time: 0.2703 data_time: 0.0077 memory: 5828 grad_norm: 3.0984 loss: 2.3326 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3326 2023/06/05 00:54:25 - mmengine - INFO - Epoch(train) [45][1840/2569] lr: 4.0000e-02 eta: 20:01:42 time: 0.2678 data_time: 0.0079 memory: 5828 grad_norm: 3.1478 loss: 2.6352 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6352 2023/06/05 00:54:30 - mmengine - INFO - Epoch(train) [45][1860/2569] lr: 4.0000e-02 eta: 20:01:37 time: 0.2682 data_time: 0.0080 memory: 5828 grad_norm: 3.0985 loss: 2.4617 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4617 2023/06/05 00:54:36 - mmengine - INFO - Epoch(train) [45][1880/2569] lr: 4.0000e-02 eta: 20:01:32 time: 0.2604 data_time: 0.0083 memory: 5828 grad_norm: 3.0860 loss: 2.6578 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6578 2023/06/05 00:54:41 - mmengine - INFO - Epoch(train) [45][1900/2569] lr: 4.0000e-02 eta: 20:01:26 time: 0.2691 data_time: 0.0073 memory: 5828 grad_norm: 3.0560 loss: 2.3554 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3554 2023/06/05 00:54:46 - mmengine - INFO - Epoch(train) [45][1920/2569] lr: 4.0000e-02 eta: 20:01:21 time: 0.2566 data_time: 0.0082 memory: 5828 grad_norm: 3.0521 loss: 2.5361 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5361 2023/06/05 00:54:51 - mmengine - INFO - Epoch(train) [45][1940/2569] lr: 4.0000e-02 eta: 20:01:15 time: 0.2607 data_time: 0.0082 memory: 5828 grad_norm: 3.1100 loss: 2.9690 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9690 2023/06/05 00:54:57 - mmengine - INFO - Epoch(train) [45][1960/2569] lr: 4.0000e-02 eta: 20:01:10 time: 0.2677 data_time: 0.0079 memory: 5828 grad_norm: 3.0516 loss: 2.6253 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6253 2023/06/05 00:54:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:55:02 - mmengine - INFO - Epoch(train) [45][1980/2569] lr: 4.0000e-02 eta: 20:01:04 time: 0.2580 data_time: 0.0080 memory: 5828 grad_norm: 3.0864 loss: 2.4828 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4828 2023/06/05 00:55:07 - mmengine - INFO - Epoch(train) [45][2000/2569] lr: 4.0000e-02 eta: 20:00:58 time: 0.2574 data_time: 0.0081 memory: 5828 grad_norm: 3.0586 loss: 2.5939 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5939 2023/06/05 00:55:12 - mmengine - INFO - Epoch(train) [45][2020/2569] lr: 4.0000e-02 eta: 20:00:53 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 3.0240 loss: 2.5909 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5909 2023/06/05 00:55:18 - mmengine - INFO - Epoch(train) [45][2040/2569] lr: 4.0000e-02 eta: 20:00:47 time: 0.2625 data_time: 0.0080 memory: 5828 grad_norm: 3.0497 loss: 2.6190 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6190 2023/06/05 00:55:23 - mmengine - INFO - Epoch(train) [45][2060/2569] lr: 4.0000e-02 eta: 20:00:42 time: 0.2737 data_time: 0.0076 memory: 5828 grad_norm: 3.1176 loss: 2.6397 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6397 2023/06/05 00:55:28 - mmengine - INFO - Epoch(train) [45][2080/2569] lr: 4.0000e-02 eta: 20:00:37 time: 0.2677 data_time: 0.0075 memory: 5828 grad_norm: 3.0353 loss: 2.3667 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3667 2023/06/05 00:55:34 - mmengine - INFO - Epoch(train) [45][2100/2569] lr: 4.0000e-02 eta: 20:00:32 time: 0.2676 data_time: 0.0078 memory: 5828 grad_norm: 3.1066 loss: 2.3690 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3690 2023/06/05 00:55:39 - mmengine - INFO - Epoch(train) [45][2120/2569] lr: 4.0000e-02 eta: 20:00:26 time: 0.2620 data_time: 0.0084 memory: 5828 grad_norm: 3.0750 loss: 2.3887 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3887 2023/06/05 00:55:44 - mmengine - INFO - Epoch(train) [45][2140/2569] lr: 4.0000e-02 eta: 20:00:21 time: 0.2656 data_time: 0.0077 memory: 5828 grad_norm: 3.1300 loss: 2.6477 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6477 2023/06/05 00:55:49 - mmengine - INFO - Epoch(train) [45][2160/2569] lr: 4.0000e-02 eta: 20:00:15 time: 0.2573 data_time: 0.0081 memory: 5828 grad_norm: 3.0941 loss: 2.6633 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6633 2023/06/05 00:55:55 - mmengine - INFO - Epoch(train) [45][2180/2569] lr: 4.0000e-02 eta: 20:00:10 time: 0.2657 data_time: 0.0074 memory: 5828 grad_norm: 3.0801 loss: 2.8486 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8486 2023/06/05 00:56:00 - mmengine - INFO - Epoch(train) [45][2200/2569] lr: 4.0000e-02 eta: 20:00:04 time: 0.2662 data_time: 0.0080 memory: 5828 grad_norm: 3.0389 loss: 2.4013 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4013 2023/06/05 00:56:05 - mmengine - INFO - Epoch(train) [45][2220/2569] lr: 4.0000e-02 eta: 19:59:59 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 3.0249 loss: 2.6425 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6425 2023/06/05 00:56:11 - mmengine - INFO - Epoch(train) [45][2240/2569] lr: 4.0000e-02 eta: 19:59:53 time: 0.2571 data_time: 0.0080 memory: 5828 grad_norm: 3.1465 loss: 2.8382 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8382 2023/06/05 00:56:16 - mmengine - INFO - Epoch(train) [45][2260/2569] lr: 4.0000e-02 eta: 19:59:48 time: 0.2636 data_time: 0.0071 memory: 5828 grad_norm: 3.1069 loss: 2.6234 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6234 2023/06/05 00:56:21 - mmengine - INFO - Epoch(train) [45][2280/2569] lr: 4.0000e-02 eta: 19:59:42 time: 0.2610 data_time: 0.0085 memory: 5828 grad_norm: 3.1006 loss: 2.6710 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6710 2023/06/05 00:56:26 - mmengine - INFO - Epoch(train) [45][2300/2569] lr: 4.0000e-02 eta: 19:59:37 time: 0.2669 data_time: 0.0078 memory: 5828 grad_norm: 3.0704 loss: 2.3485 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3485 2023/06/05 00:56:32 - mmengine - INFO - Epoch(train) [45][2320/2569] lr: 4.0000e-02 eta: 19:59:31 time: 0.2580 data_time: 0.0084 memory: 5828 grad_norm: 3.0751 loss: 2.4970 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4970 2023/06/05 00:56:37 - mmengine - INFO - Epoch(train) [45][2340/2569] lr: 4.0000e-02 eta: 19:59:26 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 3.0027 loss: 2.5936 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5936 2023/06/05 00:56:42 - mmengine - INFO - Epoch(train) [45][2360/2569] lr: 4.0000e-02 eta: 19:59:20 time: 0.2604 data_time: 0.0079 memory: 5828 grad_norm: 3.0858 loss: 2.5322 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5322 2023/06/05 00:56:47 - mmengine - INFO - Epoch(train) [45][2380/2569] lr: 4.0000e-02 eta: 19:59:15 time: 0.2659 data_time: 0.0077 memory: 5828 grad_norm: 3.1826 loss: 2.7066 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7066 2023/06/05 00:56:53 - mmengine - INFO - Epoch(train) [45][2400/2569] lr: 4.0000e-02 eta: 19:59:09 time: 0.2640 data_time: 0.0081 memory: 5828 grad_norm: 3.0738 loss: 2.5543 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5543 2023/06/05 00:56:58 - mmengine - INFO - Epoch(train) [45][2420/2569] lr: 4.0000e-02 eta: 19:59:04 time: 0.2577 data_time: 0.0079 memory: 5828 grad_norm: 3.0784 loss: 2.2445 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2445 2023/06/05 00:57:04 - mmengine - INFO - Epoch(train) [45][2440/2569] lr: 4.0000e-02 eta: 19:58:59 time: 0.2822 data_time: 0.0080 memory: 5828 grad_norm: 2.9910 loss: 2.8642 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8642 2023/06/05 00:57:09 - mmengine - INFO - Epoch(train) [45][2460/2569] lr: 4.0000e-02 eta: 19:58:53 time: 0.2582 data_time: 0.0078 memory: 5828 grad_norm: 3.1093 loss: 2.3264 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3264 2023/06/05 00:57:14 - mmengine - INFO - Epoch(train) [45][2480/2569] lr: 4.0000e-02 eta: 19:58:48 time: 0.2684 data_time: 0.0076 memory: 5828 grad_norm: 3.1071 loss: 2.4148 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4148 2023/06/05 00:57:19 - mmengine - INFO - Epoch(train) [45][2500/2569] lr: 4.0000e-02 eta: 19:58:42 time: 0.2596 data_time: 0.0079 memory: 5828 grad_norm: 3.0364 loss: 2.1973 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1973 2023/06/05 00:57:25 - mmengine - INFO - Epoch(train) [45][2520/2569] lr: 4.0000e-02 eta: 19:58:37 time: 0.2611 data_time: 0.0081 memory: 5828 grad_norm: 3.1662 loss: 2.3735 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3735 2023/06/05 00:57:30 - mmengine - INFO - Epoch(train) [45][2540/2569] lr: 4.0000e-02 eta: 19:58:31 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 3.0529 loss: 2.9269 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9269 2023/06/05 00:57:35 - mmengine - INFO - Epoch(train) [45][2560/2569] lr: 4.0000e-02 eta: 19:58:26 time: 0.2639 data_time: 0.0078 memory: 5828 grad_norm: 3.0243 loss: 2.5431 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5431 2023/06/05 00:57:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 00:57:37 - mmengine - INFO - Epoch(train) [45][2569/2569] lr: 4.0000e-02 eta: 19:58:23 time: 0.2592 data_time: 0.0075 memory: 5828 grad_norm: 3.0651 loss: 2.6132 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.6132 2023/06/05 00:57:41 - mmengine - INFO - Epoch(val) [45][ 20/260] eta: 0:00:44 time: 0.1847 data_time: 0.1257 memory: 1238 2023/06/05 00:57:44 - mmengine - INFO - Epoch(val) [45][ 40/260] eta: 0:00:36 time: 0.1503 data_time: 0.0914 memory: 1238 2023/06/05 00:57:47 - mmengine - INFO - Epoch(val) [45][ 60/260] eta: 0:00:32 time: 0.1582 data_time: 0.0993 memory: 1238 2023/06/05 00:57:50 - mmengine - INFO - Epoch(val) [45][ 80/260] eta: 0:00:27 time: 0.1278 data_time: 0.0694 memory: 1238 2023/06/05 00:57:53 - mmengine - INFO - Epoch(val) [45][100/260] eta: 0:00:24 time: 0.1598 data_time: 0.1015 memory: 1238 2023/06/05 00:57:56 - mmengine - INFO - Epoch(val) [45][120/260] eta: 0:00:21 time: 0.1426 data_time: 0.0837 memory: 1238 2023/06/05 00:57:59 - mmengine - INFO - Epoch(val) [45][140/260] eta: 0:00:18 time: 0.1475 data_time: 0.0887 memory: 1238 2023/06/05 00:58:02 - mmengine - INFO - Epoch(val) [45][160/260] eta: 0:00:15 time: 0.1433 data_time: 0.0841 memory: 1238 2023/06/05 00:58:04 - mmengine - INFO - Epoch(val) [45][180/260] eta: 0:00:11 time: 0.1319 data_time: 0.0736 memory: 1238 2023/06/05 00:58:07 - mmengine - INFO - Epoch(val) [45][200/260] eta: 0:00:08 time: 0.1415 data_time: 0.0825 memory: 1238 2023/06/05 00:58:10 - mmengine - INFO - Epoch(val) [45][220/260] eta: 0:00:05 time: 0.1484 data_time: 0.0903 memory: 1238 2023/06/05 00:58:13 - mmengine - INFO - Epoch(val) [45][240/260] eta: 0:00:02 time: 0.1293 data_time: 0.0705 memory: 1238 2023/06/05 00:58:15 - mmengine - INFO - Epoch(val) [45][260/260] eta: 0:00:00 time: 0.1211 data_time: 0.0649 memory: 1238 2023/06/05 00:58:22 - mmengine - INFO - Epoch(val) [45][260/260] acc/top1: 0.4941 acc/top5: 0.7422 acc/mean1: 0.4870 data_time: 0.0863 time: 0.1447 2023/06/05 00:58:29 - mmengine - INFO - Epoch(train) [46][ 20/2569] lr: 4.0000e-02 eta: 19:58:21 time: 0.3235 data_time: 0.0538 memory: 5828 grad_norm: 3.0055 loss: 2.5485 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5485 2023/06/05 00:58:34 - mmengine - INFO - Epoch(train) [46][ 40/2569] lr: 4.0000e-02 eta: 19:58:15 time: 0.2580 data_time: 0.0077 memory: 5828 grad_norm: 3.0337 loss: 2.7685 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7685 2023/06/05 00:58:39 - mmengine - INFO - Epoch(train) [46][ 60/2569] lr: 4.0000e-02 eta: 19:58:09 time: 0.2616 data_time: 0.0079 memory: 5828 grad_norm: 3.0819 loss: 2.4957 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4957 2023/06/05 00:58:44 - mmengine - INFO - Epoch(train) [46][ 80/2569] lr: 4.0000e-02 eta: 19:58:04 time: 0.2689 data_time: 0.0075 memory: 5828 grad_norm: 3.1152 loss: 2.5760 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5760 2023/06/05 00:58:50 - mmengine - INFO - Epoch(train) [46][ 100/2569] lr: 4.0000e-02 eta: 19:57:59 time: 0.2632 data_time: 0.0080 memory: 5828 grad_norm: 3.1021 loss: 2.4790 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4790 2023/06/05 00:58:55 - mmengine - INFO - Epoch(train) [46][ 120/2569] lr: 4.0000e-02 eta: 19:57:53 time: 0.2686 data_time: 0.0075 memory: 5828 grad_norm: 3.0877 loss: 2.5953 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5953 2023/06/05 00:59:00 - mmengine - INFO - Epoch(train) [46][ 140/2569] lr: 4.0000e-02 eta: 19:57:48 time: 0.2576 data_time: 0.0076 memory: 5828 grad_norm: 3.0555 loss: 2.4680 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4680 2023/06/05 00:59:06 - mmengine - INFO - Epoch(train) [46][ 160/2569] lr: 4.0000e-02 eta: 19:57:42 time: 0.2692 data_time: 0.0078 memory: 5828 grad_norm: 3.0857 loss: 2.4018 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4018 2023/06/05 00:59:11 - mmengine - INFO - Epoch(train) [46][ 180/2569] lr: 4.0000e-02 eta: 19:57:37 time: 0.2630 data_time: 0.0077 memory: 5828 grad_norm: 3.1061 loss: 2.3514 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3514 2023/06/05 00:59:16 - mmengine - INFO - Epoch(train) [46][ 200/2569] lr: 4.0000e-02 eta: 19:57:31 time: 0.2581 data_time: 0.0079 memory: 5828 grad_norm: 3.1125 loss: 2.5024 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5024 2023/06/05 00:59:21 - mmengine - INFO - Epoch(train) [46][ 220/2569] lr: 4.0000e-02 eta: 19:57:25 time: 0.2589 data_time: 0.0078 memory: 5828 grad_norm: 3.0871 loss: 2.4252 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4252 2023/06/05 00:59:27 - mmengine - INFO - Epoch(train) [46][ 240/2569] lr: 4.0000e-02 eta: 19:57:20 time: 0.2647 data_time: 0.0076 memory: 5828 grad_norm: 3.1323 loss: 2.4215 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4215 2023/06/05 00:59:32 - mmengine - INFO - Epoch(train) [46][ 260/2569] lr: 4.0000e-02 eta: 19:57:15 time: 0.2644 data_time: 0.0076 memory: 5828 grad_norm: 2.9953 loss: 2.4974 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4974 2023/06/05 00:59:37 - mmengine - INFO - Epoch(train) [46][ 280/2569] lr: 4.0000e-02 eta: 19:57:09 time: 0.2698 data_time: 0.0079 memory: 5828 grad_norm: 3.1086 loss: 2.5178 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5178 2023/06/05 00:59:43 - mmengine - INFO - Epoch(train) [46][ 300/2569] lr: 4.0000e-02 eta: 19:57:04 time: 0.2665 data_time: 0.0081 memory: 5828 grad_norm: 3.0608 loss: 2.5149 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5149 2023/06/05 00:59:48 - mmengine - INFO - Epoch(train) [46][ 320/2569] lr: 4.0000e-02 eta: 19:56:59 time: 0.2667 data_time: 0.0080 memory: 5828 grad_norm: 3.0235 loss: 2.5551 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5551 2023/06/05 00:59:53 - mmengine - INFO - Epoch(train) [46][ 340/2569] lr: 4.0000e-02 eta: 19:56:53 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 3.0910 loss: 2.6296 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6296 2023/06/05 00:59:58 - mmengine - INFO - Epoch(train) [46][ 360/2569] lr: 4.0000e-02 eta: 19:56:48 time: 0.2590 data_time: 0.0081 memory: 5828 grad_norm: 3.1018 loss: 2.7580 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7580 2023/06/05 01:00:04 - mmengine - INFO - Epoch(train) [46][ 380/2569] lr: 4.0000e-02 eta: 19:56:42 time: 0.2715 data_time: 0.0082 memory: 5828 grad_norm: 3.0841 loss: 2.5495 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.5495 2023/06/05 01:00:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:00:09 - mmengine - INFO - Epoch(train) [46][ 400/2569] lr: 4.0000e-02 eta: 19:56:37 time: 0.2581 data_time: 0.0084 memory: 5828 grad_norm: 3.1447 loss: 2.7337 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7337 2023/06/05 01:00:14 - mmengine - INFO - Epoch(train) [46][ 420/2569] lr: 4.0000e-02 eta: 19:56:32 time: 0.2733 data_time: 0.0084 memory: 5828 grad_norm: 3.1625 loss: 2.5404 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5404 2023/06/05 01:00:20 - mmengine - INFO - Epoch(train) [46][ 440/2569] lr: 4.0000e-02 eta: 19:56:26 time: 0.2585 data_time: 0.0080 memory: 5828 grad_norm: 3.0373 loss: 2.3900 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3900 2023/06/05 01:00:25 - mmengine - INFO - Epoch(train) [46][ 460/2569] lr: 4.0000e-02 eta: 19:56:21 time: 0.2706 data_time: 0.0076 memory: 5828 grad_norm: 3.1499 loss: 2.6324 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6324 2023/06/05 01:00:30 - mmengine - INFO - Epoch(train) [46][ 480/2569] lr: 4.0000e-02 eta: 19:56:15 time: 0.2616 data_time: 0.0079 memory: 5828 grad_norm: 3.1127 loss: 2.6225 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6225 2023/06/05 01:00:36 - mmengine - INFO - Epoch(train) [46][ 500/2569] lr: 4.0000e-02 eta: 19:56:10 time: 0.2647 data_time: 0.0081 memory: 5828 grad_norm: 3.0871 loss: 2.5305 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5305 2023/06/05 01:00:41 - mmengine - INFO - Epoch(train) [46][ 520/2569] lr: 4.0000e-02 eta: 19:56:04 time: 0.2643 data_time: 0.0078 memory: 5828 grad_norm: 3.0412 loss: 2.5739 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5739 2023/06/05 01:00:46 - mmengine - INFO - Epoch(train) [46][ 540/2569] lr: 4.0000e-02 eta: 19:55:59 time: 0.2644 data_time: 0.0081 memory: 5828 grad_norm: 3.0844 loss: 2.5296 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5296 2023/06/05 01:00:51 - mmengine - INFO - Epoch(train) [46][ 560/2569] lr: 4.0000e-02 eta: 19:55:54 time: 0.2649 data_time: 0.0085 memory: 5828 grad_norm: 3.1147 loss: 2.6162 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6162 2023/06/05 01:00:57 - mmengine - INFO - Epoch(train) [46][ 580/2569] lr: 4.0000e-02 eta: 19:55:48 time: 0.2606 data_time: 0.0076 memory: 5828 grad_norm: 3.0566 loss: 2.2041 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2041 2023/06/05 01:01:02 - mmengine - INFO - Epoch(train) [46][ 600/2569] lr: 4.0000e-02 eta: 19:55:43 time: 0.2695 data_time: 0.0078 memory: 5828 grad_norm: 3.1157 loss: 2.7914 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7914 2023/06/05 01:01:07 - mmengine - INFO - Epoch(train) [46][ 620/2569] lr: 4.0000e-02 eta: 19:55:38 time: 0.2688 data_time: 0.0080 memory: 5828 grad_norm: 3.0371 loss: 2.4101 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4101 2023/06/05 01:01:13 - mmengine - INFO - Epoch(train) [46][ 640/2569] lr: 4.0000e-02 eta: 19:55:32 time: 0.2585 data_time: 0.0077 memory: 5828 grad_norm: 3.0909 loss: 2.3310 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3310 2023/06/05 01:01:18 - mmengine - INFO - Epoch(train) [46][ 660/2569] lr: 4.0000e-02 eta: 19:55:26 time: 0.2633 data_time: 0.0076 memory: 5828 grad_norm: 3.0710 loss: 2.5315 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5315 2023/06/05 01:01:23 - mmengine - INFO - Epoch(train) [46][ 680/2569] lr: 4.0000e-02 eta: 19:55:21 time: 0.2572 data_time: 0.0076 memory: 5828 grad_norm: 3.0782 loss: 2.3873 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.3873 2023/06/05 01:01:28 - mmengine - INFO - Epoch(train) [46][ 700/2569] lr: 4.0000e-02 eta: 19:55:15 time: 0.2582 data_time: 0.0079 memory: 5828 grad_norm: 3.1373 loss: 2.7118 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7118 2023/06/05 01:01:33 - mmengine - INFO - Epoch(train) [46][ 720/2569] lr: 4.0000e-02 eta: 19:55:09 time: 0.2577 data_time: 0.0080 memory: 5828 grad_norm: 3.1062 loss: 2.4591 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4591 2023/06/05 01:01:39 - mmengine - INFO - Epoch(train) [46][ 740/2569] lr: 4.0000e-02 eta: 19:55:03 time: 0.2575 data_time: 0.0082 memory: 5828 grad_norm: 3.1186 loss: 2.4964 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4964 2023/06/05 01:01:44 - mmengine - INFO - Epoch(train) [46][ 760/2569] lr: 4.0000e-02 eta: 19:54:58 time: 0.2612 data_time: 0.0074 memory: 5828 grad_norm: 3.0688 loss: 2.6960 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6960 2023/06/05 01:01:49 - mmengine - INFO - Epoch(train) [46][ 780/2569] lr: 4.0000e-02 eta: 19:54:53 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 3.0714 loss: 2.6122 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6122 2023/06/05 01:01:55 - mmengine - INFO - Epoch(train) [46][ 800/2569] lr: 4.0000e-02 eta: 19:54:47 time: 0.2663 data_time: 0.0083 memory: 5828 grad_norm: 3.0814 loss: 2.8455 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8455 2023/06/05 01:02:00 - mmengine - INFO - Epoch(train) [46][ 820/2569] lr: 4.0000e-02 eta: 19:54:42 time: 0.2625 data_time: 0.0078 memory: 5828 grad_norm: 3.0961 loss: 2.3780 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3780 2023/06/05 01:02:05 - mmengine - INFO - Epoch(train) [46][ 840/2569] lr: 4.0000e-02 eta: 19:54:36 time: 0.2639 data_time: 0.0082 memory: 5828 grad_norm: 3.0599 loss: 2.4718 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4718 2023/06/05 01:02:10 - mmengine - INFO - Epoch(train) [46][ 860/2569] lr: 4.0000e-02 eta: 19:54:31 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 3.0356 loss: 2.4986 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4986 2023/06/05 01:02:16 - mmengine - INFO - Epoch(train) [46][ 880/2569] lr: 4.0000e-02 eta: 19:54:26 time: 0.2630 data_time: 0.0080 memory: 5828 grad_norm: 3.0693 loss: 2.6100 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6100 2023/06/05 01:02:21 - mmengine - INFO - Epoch(train) [46][ 900/2569] lr: 4.0000e-02 eta: 19:54:21 time: 0.2794 data_time: 0.0078 memory: 5828 grad_norm: 3.1127 loss: 2.6204 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6204 2023/06/05 01:02:27 - mmengine - INFO - Epoch(train) [46][ 920/2569] lr: 4.0000e-02 eta: 19:54:15 time: 0.2632 data_time: 0.0080 memory: 5828 grad_norm: 3.1226 loss: 2.5828 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5828 2023/06/05 01:02:32 - mmengine - INFO - Epoch(train) [46][ 940/2569] lr: 4.0000e-02 eta: 19:54:10 time: 0.2642 data_time: 0.0077 memory: 5828 grad_norm: 3.1196 loss: 2.7038 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7038 2023/06/05 01:02:37 - mmengine - INFO - Epoch(train) [46][ 960/2569] lr: 4.0000e-02 eta: 19:54:04 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 3.0858 loss: 2.7907 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7907 2023/06/05 01:02:42 - mmengine - INFO - Epoch(train) [46][ 980/2569] lr: 4.0000e-02 eta: 19:53:59 time: 0.2686 data_time: 0.0078 memory: 5828 grad_norm: 3.1579 loss: 2.5834 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5834 2023/06/05 01:02:48 - mmengine - INFO - Epoch(train) [46][1000/2569] lr: 4.0000e-02 eta: 19:53:54 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 3.0040 loss: 2.6283 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6283 2023/06/05 01:02:53 - mmengine - INFO - Epoch(train) [46][1020/2569] lr: 4.0000e-02 eta: 19:53:48 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 3.1170 loss: 2.6865 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6865 2023/06/05 01:02:58 - mmengine - INFO - Epoch(train) [46][1040/2569] lr: 4.0000e-02 eta: 19:53:43 time: 0.2787 data_time: 0.0078 memory: 5828 grad_norm: 3.0457 loss: 2.5934 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5934 2023/06/05 01:03:04 - mmengine - INFO - Epoch(train) [46][1060/2569] lr: 4.0000e-02 eta: 19:53:37 time: 0.2565 data_time: 0.0081 memory: 5828 grad_norm: 3.1168 loss: 2.8763 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8763 2023/06/05 01:03:09 - mmengine - INFO - Epoch(train) [46][1080/2569] lr: 4.0000e-02 eta: 19:53:33 time: 0.2812 data_time: 0.0076 memory: 5828 grad_norm: 3.1455 loss: 2.2918 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2918 2023/06/05 01:03:14 - mmengine - INFO - Epoch(train) [46][1100/2569] lr: 4.0000e-02 eta: 19:53:27 time: 0.2563 data_time: 0.0076 memory: 5828 grad_norm: 3.1064 loss: 2.5847 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5847 2023/06/05 01:03:20 - mmengine - INFO - Epoch(train) [46][1120/2569] lr: 4.0000e-02 eta: 19:53:22 time: 0.2648 data_time: 0.0075 memory: 5828 grad_norm: 3.0358 loss: 2.6902 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6902 2023/06/05 01:03:25 - mmengine - INFO - Epoch(train) [46][1140/2569] lr: 4.0000e-02 eta: 19:53:16 time: 0.2635 data_time: 0.0080 memory: 5828 grad_norm: 3.1238 loss: 2.7679 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7679 2023/06/05 01:03:30 - mmengine - INFO - Epoch(train) [46][1160/2569] lr: 4.0000e-02 eta: 19:53:11 time: 0.2638 data_time: 0.0077 memory: 5828 grad_norm: 3.0776 loss: 2.5319 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5319 2023/06/05 01:03:35 - mmengine - INFO - Epoch(train) [46][1180/2569] lr: 4.0000e-02 eta: 19:53:05 time: 0.2565 data_time: 0.0076 memory: 5828 grad_norm: 3.0164 loss: 2.1386 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.1386 2023/06/05 01:03:41 - mmengine - INFO - Epoch(train) [46][1200/2569] lr: 4.0000e-02 eta: 19:52:59 time: 0.2649 data_time: 0.0076 memory: 5828 grad_norm: 3.1128 loss: 2.7560 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7560 2023/06/05 01:03:46 - mmengine - INFO - Epoch(train) [46][1220/2569] lr: 4.0000e-02 eta: 19:52:54 time: 0.2590 data_time: 0.0079 memory: 5828 grad_norm: 3.1063 loss: 2.5518 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5518 2023/06/05 01:03:51 - mmengine - INFO - Epoch(train) [46][1240/2569] lr: 4.0000e-02 eta: 19:52:48 time: 0.2638 data_time: 0.0084 memory: 5828 grad_norm: 3.0561 loss: 2.5236 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5236 2023/06/05 01:03:56 - mmengine - INFO - Epoch(train) [46][1260/2569] lr: 4.0000e-02 eta: 19:52:43 time: 0.2582 data_time: 0.0085 memory: 5828 grad_norm: 3.1363 loss: 2.4297 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4297 2023/06/05 01:04:02 - mmengine - INFO - Epoch(train) [46][1280/2569] lr: 4.0000e-02 eta: 19:52:37 time: 0.2665 data_time: 0.0080 memory: 5828 grad_norm: 3.1073 loss: 2.3778 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3778 2023/06/05 01:04:07 - mmengine - INFO - Epoch(train) [46][1300/2569] lr: 4.0000e-02 eta: 19:52:32 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 3.0269 loss: 2.7761 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7761 2023/06/05 01:04:12 - mmengine - INFO - Epoch(train) [46][1320/2569] lr: 4.0000e-02 eta: 19:52:26 time: 0.2624 data_time: 0.0082 memory: 5828 grad_norm: 3.0831 loss: 2.4475 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4475 2023/06/05 01:04:17 - mmengine - INFO - Epoch(train) [46][1340/2569] lr: 4.0000e-02 eta: 19:52:21 time: 0.2615 data_time: 0.0083 memory: 5828 grad_norm: 3.0834 loss: 2.4229 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4229 2023/06/05 01:04:23 - mmengine - INFO - Epoch(train) [46][1360/2569] lr: 4.0000e-02 eta: 19:52:15 time: 0.2690 data_time: 0.0078 memory: 5828 grad_norm: 3.0701 loss: 2.3664 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3664 2023/06/05 01:04:28 - mmengine - INFO - Epoch(train) [46][1380/2569] lr: 4.0000e-02 eta: 19:52:10 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 3.1135 loss: 2.6172 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6172 2023/06/05 01:04:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:04:34 - mmengine - INFO - Epoch(train) [46][1400/2569] lr: 4.0000e-02 eta: 19:52:05 time: 0.2738 data_time: 0.0080 memory: 5828 grad_norm: 3.0915 loss: 2.2941 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2941 2023/06/05 01:04:39 - mmengine - INFO - Epoch(train) [46][1420/2569] lr: 4.0000e-02 eta: 19:52:00 time: 0.2608 data_time: 0.0081 memory: 5828 grad_norm: 3.0991 loss: 2.6826 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6826 2023/06/05 01:04:44 - mmengine - INFO - Epoch(train) [46][1440/2569] lr: 4.0000e-02 eta: 19:51:55 time: 0.2769 data_time: 0.0079 memory: 5828 grad_norm: 3.0887 loss: 2.7660 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7660 2023/06/05 01:04:50 - mmengine - INFO - Epoch(train) [46][1460/2569] lr: 4.0000e-02 eta: 19:51:49 time: 0.2668 data_time: 0.0077 memory: 5828 grad_norm: 3.1069 loss: 2.7932 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7932 2023/06/05 01:04:55 - mmengine - INFO - Epoch(train) [46][1480/2569] lr: 4.0000e-02 eta: 19:51:44 time: 0.2627 data_time: 0.0078 memory: 5828 grad_norm: 3.0767 loss: 2.3516 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3516 2023/06/05 01:05:00 - mmengine - INFO - Epoch(train) [46][1500/2569] lr: 4.0000e-02 eta: 19:51:38 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 3.1286 loss: 2.5627 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5627 2023/06/05 01:05:06 - mmengine - INFO - Epoch(train) [46][1520/2569] lr: 4.0000e-02 eta: 19:51:33 time: 0.2680 data_time: 0.0083 memory: 5828 grad_norm: 3.1032 loss: 2.6749 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6749 2023/06/05 01:05:11 - mmengine - INFO - Epoch(train) [46][1540/2569] lr: 4.0000e-02 eta: 19:51:28 time: 0.2624 data_time: 0.0079 memory: 5828 grad_norm: 3.1108 loss: 2.3031 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3031 2023/06/05 01:05:16 - mmengine - INFO - Epoch(train) [46][1560/2569] lr: 4.0000e-02 eta: 19:51:22 time: 0.2630 data_time: 0.0084 memory: 5828 grad_norm: 3.0914 loss: 2.5121 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5121 2023/06/05 01:05:22 - mmengine - INFO - Epoch(train) [46][1580/2569] lr: 4.0000e-02 eta: 19:51:17 time: 0.2676 data_time: 0.0078 memory: 5828 grad_norm: 3.0400 loss: 2.5089 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.5089 2023/06/05 01:05:27 - mmengine - INFO - Epoch(train) [46][1600/2569] lr: 4.0000e-02 eta: 19:51:12 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 3.1200 loss: 2.4966 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4966 2023/06/05 01:05:32 - mmengine - INFO - Epoch(train) [46][1620/2569] lr: 4.0000e-02 eta: 19:51:06 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 3.0919 loss: 2.8800 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8800 2023/06/05 01:05:38 - mmengine - INFO - Epoch(train) [46][1640/2569] lr: 4.0000e-02 eta: 19:51:01 time: 0.2718 data_time: 0.0081 memory: 5828 grad_norm: 3.1323 loss: 2.4652 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4652 2023/06/05 01:05:43 - mmengine - INFO - Epoch(train) [46][1660/2569] lr: 4.0000e-02 eta: 19:50:56 time: 0.2661 data_time: 0.0079 memory: 5828 grad_norm: 3.0733 loss: 2.3611 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3611 2023/06/05 01:05:48 - mmengine - INFO - Epoch(train) [46][1680/2569] lr: 4.0000e-02 eta: 19:50:51 time: 0.2665 data_time: 0.0077 memory: 5828 grad_norm: 3.1082 loss: 2.4669 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4669 2023/06/05 01:05:54 - mmengine - INFO - Epoch(train) [46][1700/2569] lr: 4.0000e-02 eta: 19:50:46 time: 0.2757 data_time: 0.0076 memory: 5828 grad_norm: 3.1635 loss: 2.6321 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6321 2023/06/05 01:05:59 - mmengine - INFO - Epoch(train) [46][1720/2569] lr: 4.0000e-02 eta: 19:50:41 time: 0.2726 data_time: 0.0083 memory: 5828 grad_norm: 3.0652 loss: 2.9478 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9478 2023/06/05 01:06:05 - mmengine - INFO - Epoch(train) [46][1740/2569] lr: 4.0000e-02 eta: 19:50:35 time: 0.2632 data_time: 0.0088 memory: 5828 grad_norm: 3.1712 loss: 2.6613 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6613 2023/06/05 01:06:10 - mmengine - INFO - Epoch(train) [46][1760/2569] lr: 4.0000e-02 eta: 19:50:30 time: 0.2646 data_time: 0.0081 memory: 5828 grad_norm: 3.0988 loss: 2.7766 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7766 2023/06/05 01:06:15 - mmengine - INFO - Epoch(train) [46][1780/2569] lr: 4.0000e-02 eta: 19:50:24 time: 0.2618 data_time: 0.0079 memory: 5828 grad_norm: 3.0327 loss: 2.5498 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5498 2023/06/05 01:06:20 - mmengine - INFO - Epoch(train) [46][1800/2569] lr: 4.0000e-02 eta: 19:50:18 time: 0.2575 data_time: 0.0082 memory: 5828 grad_norm: 3.1102 loss: 2.3320 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3320 2023/06/05 01:06:25 - mmengine - INFO - Epoch(train) [46][1820/2569] lr: 4.0000e-02 eta: 19:50:13 time: 0.2558 data_time: 0.0079 memory: 5828 grad_norm: 3.0854 loss: 2.7013 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7013 2023/06/05 01:06:31 - mmengine - INFO - Epoch(train) [46][1840/2569] lr: 4.0000e-02 eta: 19:50:07 time: 0.2655 data_time: 0.0078 memory: 5828 grad_norm: 3.1398 loss: 2.7917 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7917 2023/06/05 01:06:36 - mmengine - INFO - Epoch(train) [46][1860/2569] lr: 4.0000e-02 eta: 19:50:02 time: 0.2624 data_time: 0.0078 memory: 5828 grad_norm: 3.0717 loss: 2.9349 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9349 2023/06/05 01:06:41 - mmengine - INFO - Epoch(train) [46][1880/2569] lr: 4.0000e-02 eta: 19:49:56 time: 0.2676 data_time: 0.0078 memory: 5828 grad_norm: 3.0348 loss: 2.4989 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4989 2023/06/05 01:06:47 - mmengine - INFO - Epoch(train) [46][1900/2569] lr: 4.0000e-02 eta: 19:49:51 time: 0.2734 data_time: 0.0074 memory: 5828 grad_norm: 3.0709 loss: 2.6036 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6036 2023/06/05 01:06:52 - mmengine - INFO - Epoch(train) [46][1920/2569] lr: 4.0000e-02 eta: 19:49:46 time: 0.2581 data_time: 0.0079 memory: 5828 grad_norm: 3.1216 loss: 2.5984 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5984 2023/06/05 01:06:57 - mmengine - INFO - Epoch(train) [46][1940/2569] lr: 4.0000e-02 eta: 19:49:40 time: 0.2575 data_time: 0.0077 memory: 5828 grad_norm: 3.0793 loss: 2.6493 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6493 2023/06/05 01:07:02 - mmengine - INFO - Epoch(train) [46][1960/2569] lr: 4.0000e-02 eta: 19:49:34 time: 0.2568 data_time: 0.0077 memory: 5828 grad_norm: 3.1088 loss: 2.5970 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5970 2023/06/05 01:07:07 - mmengine - INFO - Epoch(train) [46][1980/2569] lr: 4.0000e-02 eta: 19:49:28 time: 0.2568 data_time: 0.0077 memory: 5828 grad_norm: 3.0910 loss: 2.5166 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5166 2023/06/05 01:07:13 - mmengine - INFO - Epoch(train) [46][2000/2569] lr: 4.0000e-02 eta: 19:49:23 time: 0.2636 data_time: 0.0082 memory: 5828 grad_norm: 3.1213 loss: 2.7177 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7177 2023/06/05 01:07:18 - mmengine - INFO - Epoch(train) [46][2020/2569] lr: 4.0000e-02 eta: 19:49:17 time: 0.2586 data_time: 0.0076 memory: 5828 grad_norm: 3.0636 loss: 2.7875 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7875 2023/06/05 01:07:23 - mmengine - INFO - Epoch(train) [46][2040/2569] lr: 4.0000e-02 eta: 19:49:12 time: 0.2666 data_time: 0.0079 memory: 5828 grad_norm: 3.1568 loss: 2.6441 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6441 2023/06/05 01:07:29 - mmengine - INFO - Epoch(train) [46][2060/2569] lr: 4.0000e-02 eta: 19:49:07 time: 0.2673 data_time: 0.0080 memory: 5828 grad_norm: 3.0849 loss: 2.7708 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7708 2023/06/05 01:07:34 - mmengine - INFO - Epoch(train) [46][2080/2569] lr: 4.0000e-02 eta: 19:49:01 time: 0.2622 data_time: 0.0076 memory: 5828 grad_norm: 3.0860 loss: 2.5033 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5033 2023/06/05 01:07:39 - mmengine - INFO - Epoch(train) [46][2100/2569] lr: 4.0000e-02 eta: 19:48:56 time: 0.2677 data_time: 0.0076 memory: 5828 grad_norm: 3.1333 loss: 2.9206 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9206 2023/06/05 01:07:44 - mmengine - INFO - Epoch(train) [46][2120/2569] lr: 4.0000e-02 eta: 19:48:50 time: 0.2577 data_time: 0.0078 memory: 5828 grad_norm: 3.0933 loss: 2.8332 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8332 2023/06/05 01:07:49 - mmengine - INFO - Epoch(train) [46][2140/2569] lr: 4.0000e-02 eta: 19:48:44 time: 0.2554 data_time: 0.0076 memory: 5828 grad_norm: 3.0124 loss: 2.9402 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9402 2023/06/05 01:07:55 - mmengine - INFO - Epoch(train) [46][2160/2569] lr: 4.0000e-02 eta: 19:48:39 time: 0.2676 data_time: 0.0081 memory: 5828 grad_norm: 3.1705 loss: 2.4650 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4650 2023/06/05 01:08:00 - mmengine - INFO - Epoch(train) [46][2180/2569] lr: 4.0000e-02 eta: 19:48:33 time: 0.2562 data_time: 0.0078 memory: 5828 grad_norm: 3.1243 loss: 2.8166 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8166 2023/06/05 01:08:05 - mmengine - INFO - Epoch(train) [46][2200/2569] lr: 4.0000e-02 eta: 19:48:28 time: 0.2693 data_time: 0.0077 memory: 5828 grad_norm: 3.1825 loss: 2.5646 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5646 2023/06/05 01:08:10 - mmengine - INFO - Epoch(train) [46][2220/2569] lr: 4.0000e-02 eta: 19:48:22 time: 0.2571 data_time: 0.0078 memory: 5828 grad_norm: 3.1070 loss: 2.5961 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5961 2023/06/05 01:08:16 - mmengine - INFO - Epoch(train) [46][2240/2569] lr: 4.0000e-02 eta: 19:48:17 time: 0.2605 data_time: 0.0079 memory: 5828 grad_norm: 3.1344 loss: 2.5585 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.5585 2023/06/05 01:08:21 - mmengine - INFO - Epoch(train) [46][2260/2569] lr: 4.0000e-02 eta: 19:48:11 time: 0.2597 data_time: 0.0075 memory: 5828 grad_norm: 3.0672 loss: 2.1559 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1559 2023/06/05 01:08:26 - mmengine - INFO - Epoch(train) [46][2280/2569] lr: 4.0000e-02 eta: 19:48:05 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 3.0561 loss: 2.6574 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6574 2023/06/05 01:08:31 - mmengine - INFO - Epoch(train) [46][2300/2569] lr: 4.0000e-02 eta: 19:48:00 time: 0.2583 data_time: 0.0077 memory: 5828 grad_norm: 3.0509 loss: 2.3705 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3705 2023/06/05 01:08:37 - mmengine - INFO - Epoch(train) [46][2320/2569] lr: 4.0000e-02 eta: 19:47:54 time: 0.2655 data_time: 0.0077 memory: 5828 grad_norm: 3.1071 loss: 2.4866 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4866 2023/06/05 01:08:42 - mmengine - INFO - Epoch(train) [46][2340/2569] lr: 4.0000e-02 eta: 19:47:49 time: 0.2612 data_time: 0.0079 memory: 5828 grad_norm: 2.9914 loss: 2.6111 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6111 2023/06/05 01:08:47 - mmengine - INFO - Epoch(train) [46][2360/2569] lr: 4.0000e-02 eta: 19:47:43 time: 0.2678 data_time: 0.0078 memory: 5828 grad_norm: 3.1027 loss: 2.6003 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6003 2023/06/05 01:08:53 - mmengine - INFO - Epoch(train) [46][2380/2569] lr: 4.0000e-02 eta: 19:47:38 time: 0.2704 data_time: 0.0077 memory: 5828 grad_norm: 3.1442 loss: 2.7088 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7088 2023/06/05 01:08:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:08:58 - mmengine - INFO - Epoch(train) [46][2400/2569] lr: 4.0000e-02 eta: 19:47:33 time: 0.2644 data_time: 0.0081 memory: 5828 grad_norm: 3.1536 loss: 2.4092 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4092 2023/06/05 01:09:03 - mmengine - INFO - Epoch(train) [46][2420/2569] lr: 4.0000e-02 eta: 19:47:27 time: 0.2598 data_time: 0.0079 memory: 5828 grad_norm: 3.0974 loss: 2.3470 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3470 2023/06/05 01:09:08 - mmengine - INFO - Epoch(train) [46][2440/2569] lr: 4.0000e-02 eta: 19:47:22 time: 0.2617 data_time: 0.0080 memory: 5828 grad_norm: 3.0859 loss: 2.4998 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4998 2023/06/05 01:09:14 - mmengine - INFO - Epoch(train) [46][2460/2569] lr: 4.0000e-02 eta: 19:47:16 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 3.0221 loss: 2.4383 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4383 2023/06/05 01:09:19 - mmengine - INFO - Epoch(train) [46][2480/2569] lr: 4.0000e-02 eta: 19:47:11 time: 0.2652 data_time: 0.0078 memory: 5828 grad_norm: 3.0715 loss: 2.6233 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6233 2023/06/05 01:09:24 - mmengine - INFO - Epoch(train) [46][2500/2569] lr: 4.0000e-02 eta: 19:47:05 time: 0.2621 data_time: 0.0076 memory: 5828 grad_norm: 3.0521 loss: 2.8146 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.8146 2023/06/05 01:09:29 - mmengine - INFO - Epoch(train) [46][2520/2569] lr: 4.0000e-02 eta: 19:47:00 time: 0.2593 data_time: 0.0078 memory: 5828 grad_norm: 3.1500 loss: 2.7099 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7099 2023/06/05 01:09:35 - mmengine - INFO - Epoch(train) [46][2540/2569] lr: 4.0000e-02 eta: 19:46:54 time: 0.2689 data_time: 0.0075 memory: 5828 grad_norm: 3.1467 loss: 2.6129 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6129 2023/06/05 01:09:40 - mmengine - INFO - Epoch(train) [46][2560/2569] lr: 4.0000e-02 eta: 19:46:49 time: 0.2645 data_time: 0.0087 memory: 5828 grad_norm: 3.1137 loss: 2.8197 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8197 2023/06/05 01:09:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:09:42 - mmengine - INFO - Epoch(train) [46][2569/2569] lr: 4.0000e-02 eta: 19:46:46 time: 0.2612 data_time: 0.0086 memory: 5828 grad_norm: 3.1008 loss: 2.8335 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.8335 2023/06/05 01:09:49 - mmengine - INFO - Epoch(train) [47][ 20/2569] lr: 4.0000e-02 eta: 19:46:45 time: 0.3514 data_time: 0.0566 memory: 5828 grad_norm: 3.1533 loss: 2.9003 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.9003 2023/06/05 01:09:55 - mmengine - INFO - Epoch(train) [47][ 40/2569] lr: 4.0000e-02 eta: 19:46:39 time: 0.2653 data_time: 0.0077 memory: 5828 grad_norm: 3.0976 loss: 2.5297 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5297 2023/06/05 01:10:00 - mmengine - INFO - Epoch(train) [47][ 60/2569] lr: 4.0000e-02 eta: 19:46:34 time: 0.2640 data_time: 0.0076 memory: 5828 grad_norm: 3.0520 loss: 2.7982 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7982 2023/06/05 01:10:05 - mmengine - INFO - Epoch(train) [47][ 80/2569] lr: 4.0000e-02 eta: 19:46:29 time: 0.2691 data_time: 0.0079 memory: 5828 grad_norm: 3.1728 loss: 2.8252 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8252 2023/06/05 01:10:11 - mmengine - INFO - Epoch(train) [47][ 100/2569] lr: 4.0000e-02 eta: 19:46:24 time: 0.2682 data_time: 0.0079 memory: 5828 grad_norm: 3.0182 loss: 2.4728 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4728 2023/06/05 01:10:16 - mmengine - INFO - Epoch(train) [47][ 120/2569] lr: 4.0000e-02 eta: 19:46:18 time: 0.2662 data_time: 0.0075 memory: 5828 grad_norm: 3.0952 loss: 2.4167 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4167 2023/06/05 01:10:21 - mmengine - INFO - Epoch(train) [47][ 140/2569] lr: 4.0000e-02 eta: 19:46:13 time: 0.2685 data_time: 0.0077 memory: 5828 grad_norm: 3.1225 loss: 2.6583 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6583 2023/06/05 01:10:27 - mmengine - INFO - Epoch(train) [47][ 160/2569] lr: 4.0000e-02 eta: 19:46:08 time: 0.2669 data_time: 0.0079 memory: 5828 grad_norm: 3.0584 loss: 2.6316 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6316 2023/06/05 01:10:32 - mmengine - INFO - Epoch(train) [47][ 180/2569] lr: 4.0000e-02 eta: 19:46:03 time: 0.2730 data_time: 0.0079 memory: 5828 grad_norm: 3.1596 loss: 2.7629 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7629 2023/06/05 01:10:38 - mmengine - INFO - Epoch(train) [47][ 200/2569] lr: 4.0000e-02 eta: 19:45:57 time: 0.2682 data_time: 0.0076 memory: 5828 grad_norm: 3.0893 loss: 2.3200 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3200 2023/06/05 01:10:43 - mmengine - INFO - Epoch(train) [47][ 220/2569] lr: 4.0000e-02 eta: 19:45:52 time: 0.2692 data_time: 0.0077 memory: 5828 grad_norm: 3.1612 loss: 2.5398 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5398 2023/06/05 01:10:49 - mmengine - INFO - Epoch(train) [47][ 240/2569] lr: 4.0000e-02 eta: 19:45:47 time: 0.2758 data_time: 0.0078 memory: 5828 grad_norm: 3.1507 loss: 2.5736 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5736 2023/06/05 01:10:54 - mmengine - INFO - Epoch(train) [47][ 260/2569] lr: 4.0000e-02 eta: 19:45:42 time: 0.2591 data_time: 0.0084 memory: 5828 grad_norm: 3.0460 loss: 2.4672 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4672 2023/06/05 01:10:59 - mmengine - INFO - Epoch(train) [47][ 280/2569] lr: 4.0000e-02 eta: 19:45:36 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 3.1234 loss: 2.6807 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6807 2023/06/05 01:11:04 - mmengine - INFO - Epoch(train) [47][ 300/2569] lr: 4.0000e-02 eta: 19:45:31 time: 0.2628 data_time: 0.0078 memory: 5828 grad_norm: 3.0842 loss: 2.7011 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7011 2023/06/05 01:11:10 - mmengine - INFO - Epoch(train) [47][ 320/2569] lr: 4.0000e-02 eta: 19:45:25 time: 0.2585 data_time: 0.0081 memory: 5828 grad_norm: 3.1373 loss: 2.5295 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5295 2023/06/05 01:11:15 - mmengine - INFO - Epoch(train) [47][ 340/2569] lr: 4.0000e-02 eta: 19:45:20 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 3.1029 loss: 2.6724 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6724 2023/06/05 01:11:20 - mmengine - INFO - Epoch(train) [47][ 360/2569] lr: 4.0000e-02 eta: 19:45:14 time: 0.2641 data_time: 0.0080 memory: 5828 grad_norm: 3.0461 loss: 2.2757 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2757 2023/06/05 01:11:25 - mmengine - INFO - Epoch(train) [47][ 380/2569] lr: 4.0000e-02 eta: 19:45:09 time: 0.2632 data_time: 0.0080 memory: 5828 grad_norm: 3.0263 loss: 2.6497 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6497 2023/06/05 01:11:31 - mmengine - INFO - Epoch(train) [47][ 400/2569] lr: 4.0000e-02 eta: 19:45:04 time: 0.2718 data_time: 0.0076 memory: 5828 grad_norm: 3.1634 loss: 2.3774 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3774 2023/06/05 01:11:36 - mmengine - INFO - Epoch(train) [47][ 420/2569] lr: 4.0000e-02 eta: 19:44:58 time: 0.2587 data_time: 0.0073 memory: 5828 grad_norm: 3.0982 loss: 2.6957 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6957 2023/06/05 01:11:41 - mmengine - INFO - Epoch(train) [47][ 440/2569] lr: 4.0000e-02 eta: 19:44:52 time: 0.2580 data_time: 0.0082 memory: 5828 grad_norm: 3.1299 loss: 2.5882 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5882 2023/06/05 01:11:47 - mmengine - INFO - Epoch(train) [47][ 460/2569] lr: 4.0000e-02 eta: 19:44:47 time: 0.2694 data_time: 0.0074 memory: 5828 grad_norm: 3.0753 loss: 2.7261 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7261 2023/06/05 01:11:52 - mmengine - INFO - Epoch(train) [47][ 480/2569] lr: 4.0000e-02 eta: 19:44:42 time: 0.2638 data_time: 0.0078 memory: 5828 grad_norm: 3.1138 loss: 2.7224 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7224 2023/06/05 01:11:57 - mmengine - INFO - Epoch(train) [47][ 500/2569] lr: 4.0000e-02 eta: 19:44:37 time: 0.2780 data_time: 0.0079 memory: 5828 grad_norm: 3.0768 loss: 2.7046 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7046 2023/06/05 01:12:03 - mmengine - INFO - Epoch(train) [47][ 520/2569] lr: 4.0000e-02 eta: 19:44:31 time: 0.2578 data_time: 0.0083 memory: 5828 grad_norm: 3.1358 loss: 2.6987 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6987 2023/06/05 01:12:08 - mmengine - INFO - Epoch(train) [47][ 540/2569] lr: 4.0000e-02 eta: 19:44:26 time: 0.2746 data_time: 0.0077 memory: 5828 grad_norm: 3.0571 loss: 2.5535 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5535 2023/06/05 01:12:13 - mmengine - INFO - Epoch(train) [47][ 560/2569] lr: 4.0000e-02 eta: 19:44:21 time: 0.2648 data_time: 0.0080 memory: 5828 grad_norm: 3.1101 loss: 2.3714 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3714 2023/06/05 01:12:19 - mmengine - INFO - Epoch(train) [47][ 580/2569] lr: 4.0000e-02 eta: 19:44:15 time: 0.2592 data_time: 0.0075 memory: 5828 grad_norm: 3.1303 loss: 2.4866 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4866 2023/06/05 01:12:24 - mmengine - INFO - Epoch(train) [47][ 600/2569] lr: 4.0000e-02 eta: 19:44:10 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 3.0583 loss: 2.5516 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5516 2023/06/05 01:12:29 - mmengine - INFO - Epoch(train) [47][ 620/2569] lr: 4.0000e-02 eta: 19:44:04 time: 0.2627 data_time: 0.0079 memory: 5828 grad_norm: 3.0561 loss: 2.6524 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6524 2023/06/05 01:12:34 - mmengine - INFO - Epoch(train) [47][ 640/2569] lr: 4.0000e-02 eta: 19:43:59 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 3.0905 loss: 2.7219 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7219 2023/06/05 01:12:40 - mmengine - INFO - Epoch(train) [47][ 660/2569] lr: 4.0000e-02 eta: 19:43:53 time: 0.2603 data_time: 0.0077 memory: 5828 grad_norm: 3.1629 loss: 2.6293 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6293 2023/06/05 01:12:45 - mmengine - INFO - Epoch(train) [47][ 680/2569] lr: 4.0000e-02 eta: 19:43:48 time: 0.2647 data_time: 0.0080 memory: 5828 grad_norm: 3.0853 loss: 2.7456 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7456 2023/06/05 01:12:50 - mmengine - INFO - Epoch(train) [47][ 700/2569] lr: 4.0000e-02 eta: 19:43:42 time: 0.2589 data_time: 0.0080 memory: 5828 grad_norm: 3.0710 loss: 2.7302 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7302 2023/06/05 01:12:55 - mmengine - INFO - Epoch(train) [47][ 720/2569] lr: 4.0000e-02 eta: 19:43:36 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 3.0813 loss: 2.7859 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7859 2023/06/05 01:13:00 - mmengine - INFO - Epoch(train) [47][ 740/2569] lr: 4.0000e-02 eta: 19:43:31 time: 0.2583 data_time: 0.0071 memory: 5828 grad_norm: 3.1568 loss: 2.3394 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3394 2023/06/05 01:13:06 - mmengine - INFO - Epoch(train) [47][ 760/2569] lr: 4.0000e-02 eta: 19:43:25 time: 0.2621 data_time: 0.0078 memory: 5828 grad_norm: 3.0466 loss: 2.3124 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3124 2023/06/05 01:13:11 - mmengine - INFO - Epoch(train) [47][ 780/2569] lr: 4.0000e-02 eta: 19:43:20 time: 0.2638 data_time: 0.0080 memory: 5828 grad_norm: 3.0901 loss: 2.6210 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6210 2023/06/05 01:13:16 - mmengine - INFO - Epoch(train) [47][ 800/2569] lr: 4.0000e-02 eta: 19:43:14 time: 0.2592 data_time: 0.0084 memory: 5828 grad_norm: 3.0942 loss: 2.2062 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2062 2023/06/05 01:13:22 - mmengine - INFO - Epoch(train) [47][ 820/2569] lr: 4.0000e-02 eta: 19:43:09 time: 0.2704 data_time: 0.0076 memory: 5828 grad_norm: 3.0748 loss: 2.1232 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1232 2023/06/05 01:13:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:13:27 - mmengine - INFO - Epoch(train) [47][ 840/2569] lr: 4.0000e-02 eta: 19:43:04 time: 0.2749 data_time: 0.0078 memory: 5828 grad_norm: 3.0911 loss: 2.4803 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4803 2023/06/05 01:13:32 - mmengine - INFO - Epoch(train) [47][ 860/2569] lr: 4.0000e-02 eta: 19:42:58 time: 0.2601 data_time: 0.0074 memory: 5828 grad_norm: 3.1070 loss: 2.5113 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5113 2023/06/05 01:13:37 - mmengine - INFO - Epoch(train) [47][ 880/2569] lr: 4.0000e-02 eta: 19:42:53 time: 0.2624 data_time: 0.0077 memory: 5828 grad_norm: 3.0951 loss: 2.7077 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7077 2023/06/05 01:13:43 - mmengine - INFO - Epoch(train) [47][ 900/2569] lr: 4.0000e-02 eta: 19:42:47 time: 0.2685 data_time: 0.0080 memory: 5828 grad_norm: 3.1165 loss: 2.9204 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9204 2023/06/05 01:13:48 - mmengine - INFO - Epoch(train) [47][ 920/2569] lr: 4.0000e-02 eta: 19:42:42 time: 0.2571 data_time: 0.0080 memory: 5828 grad_norm: 3.0703 loss: 2.6269 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6269 2023/06/05 01:13:53 - mmengine - INFO - Epoch(train) [47][ 940/2569] lr: 4.0000e-02 eta: 19:42:36 time: 0.2657 data_time: 0.0074 memory: 5828 grad_norm: 3.0898 loss: 2.6784 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6784 2023/06/05 01:13:59 - mmengine - INFO - Epoch(train) [47][ 960/2569] lr: 4.0000e-02 eta: 19:42:31 time: 0.2593 data_time: 0.0079 memory: 5828 grad_norm: 3.0323 loss: 2.8942 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8942 2023/06/05 01:14:04 - mmengine - INFO - Epoch(train) [47][ 980/2569] lr: 4.0000e-02 eta: 19:42:25 time: 0.2635 data_time: 0.0078 memory: 5828 grad_norm: 3.1241 loss: 2.3427 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3427 2023/06/05 01:14:09 - mmengine - INFO - Epoch(train) [47][1000/2569] lr: 4.0000e-02 eta: 19:42:19 time: 0.2573 data_time: 0.0082 memory: 5828 grad_norm: 3.1809 loss: 2.7162 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7162 2023/06/05 01:14:14 - mmengine - INFO - Epoch(train) [47][1020/2569] lr: 4.0000e-02 eta: 19:42:14 time: 0.2653 data_time: 0.0076 memory: 5828 grad_norm: 3.0447 loss: 3.0318 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0318 2023/06/05 01:14:19 - mmengine - INFO - Epoch(train) [47][1040/2569] lr: 4.0000e-02 eta: 19:42:08 time: 0.2596 data_time: 0.0080 memory: 5828 grad_norm: 3.0742 loss: 2.2585 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2585 2023/06/05 01:14:25 - mmengine - INFO - Epoch(train) [47][1060/2569] lr: 4.0000e-02 eta: 19:42:03 time: 0.2636 data_time: 0.0079 memory: 5828 grad_norm: 3.1175 loss: 2.6609 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6609 2023/06/05 01:14:30 - mmengine - INFO - Epoch(train) [47][1080/2569] lr: 4.0000e-02 eta: 19:41:57 time: 0.2595 data_time: 0.0075 memory: 5828 grad_norm: 3.0767 loss: 2.4479 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4479 2023/06/05 01:14:35 - mmengine - INFO - Epoch(train) [47][1100/2569] lr: 4.0000e-02 eta: 19:41:52 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 3.1040 loss: 2.6078 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6078 2023/06/05 01:14:41 - mmengine - INFO - Epoch(train) [47][1120/2569] lr: 4.0000e-02 eta: 19:41:47 time: 0.2684 data_time: 0.0078 memory: 5828 grad_norm: 3.0822 loss: 2.6392 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6392 2023/06/05 01:14:46 - mmengine - INFO - Epoch(train) [47][1140/2569] lr: 4.0000e-02 eta: 19:41:41 time: 0.2579 data_time: 0.0079 memory: 5828 grad_norm: 3.0165 loss: 2.6537 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6537 2023/06/05 01:14:51 - mmengine - INFO - Epoch(train) [47][1160/2569] lr: 4.0000e-02 eta: 19:41:35 time: 0.2585 data_time: 0.0078 memory: 5828 grad_norm: 3.1519 loss: 2.8000 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8000 2023/06/05 01:14:56 - mmengine - INFO - Epoch(train) [47][1180/2569] lr: 4.0000e-02 eta: 19:41:30 time: 0.2593 data_time: 0.0075 memory: 5828 grad_norm: 3.1340 loss: 2.8174 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8174 2023/06/05 01:15:01 - mmengine - INFO - Epoch(train) [47][1200/2569] lr: 4.0000e-02 eta: 19:41:24 time: 0.2583 data_time: 0.0081 memory: 5828 grad_norm: 3.0848 loss: 2.5513 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5513 2023/06/05 01:15:06 - mmengine - INFO - Epoch(train) [47][1220/2569] lr: 4.0000e-02 eta: 19:41:18 time: 0.2602 data_time: 0.0079 memory: 5828 grad_norm: 3.1663 loss: 2.5441 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5441 2023/06/05 01:15:12 - mmengine - INFO - Epoch(train) [47][1240/2569] lr: 4.0000e-02 eta: 19:41:13 time: 0.2650 data_time: 0.0077 memory: 5828 grad_norm: 3.0700 loss: 2.5590 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5590 2023/06/05 01:15:17 - mmengine - INFO - Epoch(train) [47][1260/2569] lr: 4.0000e-02 eta: 19:41:07 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 3.0669 loss: 2.7305 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7305 2023/06/05 01:15:22 - mmengine - INFO - Epoch(train) [47][1280/2569] lr: 4.0000e-02 eta: 19:41:02 time: 0.2583 data_time: 0.0080 memory: 5828 grad_norm: 3.1006 loss: 2.4171 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4171 2023/06/05 01:15:28 - mmengine - INFO - Epoch(train) [47][1300/2569] lr: 4.0000e-02 eta: 19:40:56 time: 0.2645 data_time: 0.0075 memory: 5828 grad_norm: 3.0942 loss: 2.6193 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6193 2023/06/05 01:15:33 - mmengine - INFO - Epoch(train) [47][1320/2569] lr: 4.0000e-02 eta: 19:40:51 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 3.0795 loss: 2.6272 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.6272 2023/06/05 01:15:38 - mmengine - INFO - Epoch(train) [47][1340/2569] lr: 4.0000e-02 eta: 19:40:45 time: 0.2569 data_time: 0.0078 memory: 5828 grad_norm: 3.0150 loss: 2.7932 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7932 2023/06/05 01:15:43 - mmengine - INFO - Epoch(train) [47][1360/2569] lr: 4.0000e-02 eta: 19:40:39 time: 0.2633 data_time: 0.0080 memory: 5828 grad_norm: 3.0084 loss: 2.4829 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4829 2023/06/05 01:15:48 - mmengine - INFO - Epoch(train) [47][1380/2569] lr: 4.0000e-02 eta: 19:40:34 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 3.1278 loss: 2.3296 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3296 2023/06/05 01:15:54 - mmengine - INFO - Epoch(train) [47][1400/2569] lr: 4.0000e-02 eta: 19:40:29 time: 0.2652 data_time: 0.0081 memory: 5828 grad_norm: 3.0825 loss: 2.4002 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4002 2023/06/05 01:15:59 - mmengine - INFO - Epoch(train) [47][1420/2569] lr: 4.0000e-02 eta: 19:40:23 time: 0.2606 data_time: 0.0074 memory: 5828 grad_norm: 3.1234 loss: 2.6860 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6860 2023/06/05 01:16:04 - mmengine - INFO - Epoch(train) [47][1440/2569] lr: 4.0000e-02 eta: 19:40:18 time: 0.2646 data_time: 0.0084 memory: 5828 grad_norm: 3.0466 loss: 2.5347 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5347 2023/06/05 01:16:10 - mmengine - INFO - Epoch(train) [47][1460/2569] lr: 4.0000e-02 eta: 19:40:13 time: 0.2809 data_time: 0.0076 memory: 5828 grad_norm: 3.0942 loss: 2.4794 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4794 2023/06/05 01:16:15 - mmengine - INFO - Epoch(train) [47][1480/2569] lr: 4.0000e-02 eta: 19:40:07 time: 0.2564 data_time: 0.0086 memory: 5828 grad_norm: 3.1292 loss: 2.5314 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5314 2023/06/05 01:16:20 - mmengine - INFO - Epoch(train) [47][1500/2569] lr: 4.0000e-02 eta: 19:40:02 time: 0.2742 data_time: 0.0084 memory: 5828 grad_norm: 3.0710 loss: 2.6409 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6409 2023/06/05 01:16:26 - mmengine - INFO - Epoch(train) [47][1520/2569] lr: 4.0000e-02 eta: 19:39:56 time: 0.2589 data_time: 0.0083 memory: 5828 grad_norm: 3.0858 loss: 2.9276 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.9276 2023/06/05 01:16:31 - mmengine - INFO - Epoch(train) [47][1540/2569] lr: 4.0000e-02 eta: 19:39:51 time: 0.2696 data_time: 0.0073 memory: 5828 grad_norm: 3.1110 loss: 2.6478 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6478 2023/06/05 01:16:36 - mmengine - INFO - Epoch(train) [47][1560/2569] lr: 4.0000e-02 eta: 19:39:46 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 3.1184 loss: 2.8168 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.8168 2023/06/05 01:16:41 - mmengine - INFO - Epoch(train) [47][1580/2569] lr: 4.0000e-02 eta: 19:39:40 time: 0.2587 data_time: 0.0075 memory: 5828 grad_norm: 3.1249 loss: 2.5129 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5129 2023/06/05 01:16:47 - mmengine - INFO - Epoch(train) [47][1600/2569] lr: 4.0000e-02 eta: 19:39:34 time: 0.2609 data_time: 0.0071 memory: 5828 grad_norm: 3.1625 loss: 2.5080 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5080 2023/06/05 01:16:52 - mmengine - INFO - Epoch(train) [47][1620/2569] lr: 4.0000e-02 eta: 19:39:29 time: 0.2644 data_time: 0.0076 memory: 5828 grad_norm: 3.0216 loss: 2.6341 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6341 2023/06/05 01:16:57 - mmengine - INFO - Epoch(train) [47][1640/2569] lr: 4.0000e-02 eta: 19:39:24 time: 0.2671 data_time: 0.0077 memory: 5828 grad_norm: 3.0739 loss: 2.6535 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6535 2023/06/05 01:17:03 - mmengine - INFO - Epoch(train) [47][1660/2569] lr: 4.0000e-02 eta: 19:39:19 time: 0.2717 data_time: 0.0075 memory: 5828 grad_norm: 3.0632 loss: 2.6478 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.6478 2023/06/05 01:17:08 - mmengine - INFO - Epoch(train) [47][1680/2569] lr: 4.0000e-02 eta: 19:39:13 time: 0.2608 data_time: 0.0082 memory: 5828 grad_norm: 3.0576 loss: 2.5632 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5632 2023/06/05 01:17:13 - mmengine - INFO - Epoch(train) [47][1700/2569] lr: 4.0000e-02 eta: 19:39:07 time: 0.2594 data_time: 0.0079 memory: 5828 grad_norm: 3.0694 loss: 2.7653 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7653 2023/06/05 01:17:18 - mmengine - INFO - Epoch(train) [47][1720/2569] lr: 4.0000e-02 eta: 19:39:02 time: 0.2628 data_time: 0.0083 memory: 5828 grad_norm: 3.1007 loss: 2.6173 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.6173 2023/06/05 01:17:24 - mmengine - INFO - Epoch(train) [47][1740/2569] lr: 4.0000e-02 eta: 19:38:56 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.1399 loss: 2.7204 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7204 2023/06/05 01:17:29 - mmengine - INFO - Epoch(train) [47][1760/2569] lr: 4.0000e-02 eta: 19:38:51 time: 0.2672 data_time: 0.0080 memory: 5828 grad_norm: 3.1429 loss: 2.5947 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5947 2023/06/05 01:17:34 - mmengine - INFO - Epoch(train) [47][1780/2569] lr: 4.0000e-02 eta: 19:38:45 time: 0.2593 data_time: 0.0083 memory: 5828 grad_norm: 3.0569 loss: 2.7116 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7116 2023/06/05 01:17:40 - mmengine - INFO - Epoch(train) [47][1800/2569] lr: 4.0000e-02 eta: 19:38:40 time: 0.2769 data_time: 0.0078 memory: 5828 grad_norm: 3.1311 loss: 2.3629 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3629 2023/06/05 01:17:45 - mmengine - INFO - Epoch(train) [47][1820/2569] lr: 4.0000e-02 eta: 19:38:35 time: 0.2686 data_time: 0.0075 memory: 5828 grad_norm: 3.1269 loss: 2.5475 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5475 2023/06/05 01:17:47 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:17:50 - mmengine - INFO - Epoch(train) [47][1840/2569] lr: 4.0000e-02 eta: 19:38:30 time: 0.2655 data_time: 0.0079 memory: 5828 grad_norm: 3.1644 loss: 2.4297 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4297 2023/06/05 01:17:56 - mmengine - INFO - Epoch(train) [47][1860/2569] lr: 4.0000e-02 eta: 19:38:24 time: 0.2603 data_time: 0.0075 memory: 5828 grad_norm: 3.1391 loss: 2.5681 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5681 2023/06/05 01:18:01 - mmengine - INFO - Epoch(train) [47][1880/2569] lr: 4.0000e-02 eta: 19:38:19 time: 0.2692 data_time: 0.0081 memory: 5828 grad_norm: 3.1470 loss: 2.3287 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3287 2023/06/05 01:18:06 - mmengine - INFO - Epoch(train) [47][1900/2569] lr: 4.0000e-02 eta: 19:38:13 time: 0.2572 data_time: 0.0076 memory: 5828 grad_norm: 3.0561 loss: 2.5343 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5343 2023/06/05 01:18:11 - mmengine - INFO - Epoch(train) [47][1920/2569] lr: 4.0000e-02 eta: 19:38:08 time: 0.2622 data_time: 0.0076 memory: 5828 grad_norm: 3.0923 loss: 2.4807 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4807 2023/06/05 01:18:17 - mmengine - INFO - Epoch(train) [47][1940/2569] lr: 4.0000e-02 eta: 19:38:03 time: 0.2711 data_time: 0.0078 memory: 5828 grad_norm: 3.0854 loss: 2.6047 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6047 2023/06/05 01:18:22 - mmengine - INFO - Epoch(train) [47][1960/2569] lr: 4.0000e-02 eta: 19:37:57 time: 0.2697 data_time: 0.0076 memory: 5828 grad_norm: 3.1130 loss: 2.8656 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8656 2023/06/05 01:18:27 - mmengine - INFO - Epoch(train) [47][1980/2569] lr: 4.0000e-02 eta: 19:37:52 time: 0.2595 data_time: 0.0086 memory: 5828 grad_norm: 3.0420 loss: 2.3529 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3529 2023/06/05 01:18:33 - mmengine - INFO - Epoch(train) [47][2000/2569] lr: 4.0000e-02 eta: 19:37:46 time: 0.2641 data_time: 0.0086 memory: 5828 grad_norm: 3.1253 loss: 2.5706 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5706 2023/06/05 01:18:38 - mmengine - INFO - Epoch(train) [47][2020/2569] lr: 4.0000e-02 eta: 19:37:41 time: 0.2670 data_time: 0.0083 memory: 5828 grad_norm: 3.1471 loss: 2.6264 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6264 2023/06/05 01:18:43 - mmengine - INFO - Epoch(train) [47][2040/2569] lr: 4.0000e-02 eta: 19:37:36 time: 0.2691 data_time: 0.0076 memory: 5828 grad_norm: 3.1463 loss: 2.5162 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5162 2023/06/05 01:18:49 - mmengine - INFO - Epoch(train) [47][2060/2569] lr: 4.0000e-02 eta: 19:37:30 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 3.1557 loss: 2.6094 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6094 2023/06/05 01:18:54 - mmengine - INFO - Epoch(train) [47][2080/2569] lr: 4.0000e-02 eta: 19:37:25 time: 0.2604 data_time: 0.0079 memory: 5828 grad_norm: 3.0455 loss: 2.6213 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6213 2023/06/05 01:18:59 - mmengine - INFO - Epoch(train) [47][2100/2569] lr: 4.0000e-02 eta: 19:37:19 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 3.1212 loss: 2.2468 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2468 2023/06/05 01:19:05 - mmengine - INFO - Epoch(train) [47][2120/2569] lr: 4.0000e-02 eta: 19:37:14 time: 0.2718 data_time: 0.0075 memory: 5828 grad_norm: 3.0886 loss: 2.5649 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5649 2023/06/05 01:19:10 - mmengine - INFO - Epoch(train) [47][2140/2569] lr: 4.0000e-02 eta: 19:37:09 time: 0.2642 data_time: 0.0077 memory: 5828 grad_norm: 3.0725 loss: 2.8350 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8350 2023/06/05 01:19:15 - mmengine - INFO - Epoch(train) [47][2160/2569] lr: 4.0000e-02 eta: 19:37:04 time: 0.2718 data_time: 0.0076 memory: 5828 grad_norm: 3.1636 loss: 2.5526 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5526 2023/06/05 01:19:21 - mmengine - INFO - Epoch(train) [47][2180/2569] lr: 4.0000e-02 eta: 19:36:58 time: 0.2684 data_time: 0.0076 memory: 5828 grad_norm: 3.0997 loss: 2.9421 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9421 2023/06/05 01:19:26 - mmengine - INFO - Epoch(train) [47][2200/2569] lr: 4.0000e-02 eta: 19:36:53 time: 0.2615 data_time: 0.0079 memory: 5828 grad_norm: 3.1017 loss: 2.3897 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3897 2023/06/05 01:19:31 - mmengine - INFO - Epoch(train) [47][2220/2569] lr: 4.0000e-02 eta: 19:36:47 time: 0.2629 data_time: 0.0079 memory: 5828 grad_norm: 3.1090 loss: 2.5891 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5891 2023/06/05 01:19:37 - mmengine - INFO - Epoch(train) [47][2240/2569] lr: 4.0000e-02 eta: 19:36:42 time: 0.2687 data_time: 0.0081 memory: 5828 grad_norm: 3.1126 loss: 2.5165 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5165 2023/06/05 01:19:42 - mmengine - INFO - Epoch(train) [47][2260/2569] lr: 4.0000e-02 eta: 19:36:36 time: 0.2578 data_time: 0.0075 memory: 5828 grad_norm: 3.0919 loss: 2.4485 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4485 2023/06/05 01:19:47 - mmengine - INFO - Epoch(train) [47][2280/2569] lr: 4.0000e-02 eta: 19:36:31 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 3.0774 loss: 2.1342 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1342 2023/06/05 01:19:52 - mmengine - INFO - Epoch(train) [47][2300/2569] lr: 4.0000e-02 eta: 19:36:26 time: 0.2641 data_time: 0.0081 memory: 5828 grad_norm: 3.0519 loss: 2.5509 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5509 2023/06/05 01:19:58 - mmengine - INFO - Epoch(train) [47][2320/2569] lr: 4.0000e-02 eta: 19:36:20 time: 0.2637 data_time: 0.0079 memory: 5828 grad_norm: 3.1287 loss: 2.4443 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4443 2023/06/05 01:20:03 - mmengine - INFO - Epoch(train) [47][2340/2569] lr: 4.0000e-02 eta: 19:36:15 time: 0.2705 data_time: 0.0074 memory: 5828 grad_norm: 3.0868 loss: 2.5386 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5386 2023/06/05 01:20:08 - mmengine - INFO - Epoch(train) [47][2360/2569] lr: 4.0000e-02 eta: 19:36:09 time: 0.2587 data_time: 0.0081 memory: 5828 grad_norm: 3.1080 loss: 2.4687 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4687 2023/06/05 01:20:14 - mmengine - INFO - Epoch(train) [47][2380/2569] lr: 4.0000e-02 eta: 19:36:04 time: 0.2684 data_time: 0.0082 memory: 5828 grad_norm: 3.0289 loss: 2.6197 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6197 2023/06/05 01:20:19 - mmengine - INFO - Epoch(train) [47][2400/2569] lr: 4.0000e-02 eta: 19:35:59 time: 0.2715 data_time: 0.0084 memory: 5828 grad_norm: 3.1085 loss: 2.9558 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.9558 2023/06/05 01:20:24 - mmengine - INFO - Epoch(train) [47][2420/2569] lr: 4.0000e-02 eta: 19:35:53 time: 0.2622 data_time: 0.0082 memory: 5828 grad_norm: 3.1218 loss: 2.5943 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5943 2023/06/05 01:20:30 - mmengine - INFO - Epoch(train) [47][2440/2569] lr: 4.0000e-02 eta: 19:35:48 time: 0.2588 data_time: 0.0080 memory: 5828 grad_norm: 3.0718 loss: 2.7792 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7792 2023/06/05 01:20:35 - mmengine - INFO - Epoch(train) [47][2460/2569] lr: 4.0000e-02 eta: 19:35:42 time: 0.2602 data_time: 0.0078 memory: 5828 grad_norm: 3.1349 loss: 2.2540 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2540 2023/06/05 01:20:40 - mmengine - INFO - Epoch(train) [47][2480/2569] lr: 4.0000e-02 eta: 19:35:37 time: 0.2641 data_time: 0.0082 memory: 5828 grad_norm: 3.0897 loss: 2.5229 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.5229 2023/06/05 01:20:45 - mmengine - INFO - Epoch(train) [47][2500/2569] lr: 4.0000e-02 eta: 19:35:31 time: 0.2634 data_time: 0.0079 memory: 5828 grad_norm: 3.1034 loss: 2.6986 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6986 2023/06/05 01:20:51 - mmengine - INFO - Epoch(train) [47][2520/2569] lr: 4.0000e-02 eta: 19:35:26 time: 0.2636 data_time: 0.0077 memory: 5828 grad_norm: 3.1014 loss: 2.2323 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2323 2023/06/05 01:20:56 - mmengine - INFO - Epoch(train) [47][2540/2569] lr: 4.0000e-02 eta: 19:35:20 time: 0.2602 data_time: 0.0076 memory: 5828 grad_norm: 3.1260 loss: 2.6047 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6047 2023/06/05 01:21:01 - mmengine - INFO - Epoch(train) [47][2560/2569] lr: 4.0000e-02 eta: 19:35:15 time: 0.2625 data_time: 0.0077 memory: 5828 grad_norm: 3.1347 loss: 2.4872 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4872 2023/06/05 01:21:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:21:03 - mmengine - INFO - Epoch(train) [47][2569/2569] lr: 4.0000e-02 eta: 19:35:12 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 3.0935 loss: 2.4454 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.4454 2023/06/05 01:21:10 - mmengine - INFO - Epoch(train) [48][ 20/2569] lr: 4.0000e-02 eta: 19:35:10 time: 0.3375 data_time: 0.0613 memory: 5828 grad_norm: 3.0713 loss: 2.4778 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4778 2023/06/05 01:21:16 - mmengine - INFO - Epoch(train) [48][ 40/2569] lr: 4.0000e-02 eta: 19:35:05 time: 0.2800 data_time: 0.0069 memory: 5828 grad_norm: 3.0680 loss: 2.7432 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7432 2023/06/05 01:21:21 - mmengine - INFO - Epoch(train) [48][ 60/2569] lr: 4.0000e-02 eta: 19:35:00 time: 0.2669 data_time: 0.0081 memory: 5828 grad_norm: 3.0816 loss: 2.3990 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3990 2023/06/05 01:21:26 - mmengine - INFO - Epoch(train) [48][ 80/2569] lr: 4.0000e-02 eta: 19:34:54 time: 0.2669 data_time: 0.0076 memory: 5828 grad_norm: 3.0846 loss: 2.4323 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4323 2023/06/05 01:21:32 - mmengine - INFO - Epoch(train) [48][ 100/2569] lr: 4.0000e-02 eta: 19:34:49 time: 0.2689 data_time: 0.0076 memory: 5828 grad_norm: 3.0918 loss: 2.6907 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6907 2023/06/05 01:21:37 - mmengine - INFO - Epoch(train) [48][ 120/2569] lr: 4.0000e-02 eta: 19:34:44 time: 0.2685 data_time: 0.0080 memory: 5828 grad_norm: 3.0020 loss: 2.6154 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6154 2023/06/05 01:21:42 - mmengine - INFO - Epoch(train) [48][ 140/2569] lr: 4.0000e-02 eta: 19:34:39 time: 0.2657 data_time: 0.0081 memory: 5828 grad_norm: 3.0778 loss: 2.5309 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5309 2023/06/05 01:21:48 - mmengine - INFO - Epoch(train) [48][ 160/2569] lr: 4.0000e-02 eta: 19:34:34 time: 0.2718 data_time: 0.0075 memory: 5828 grad_norm: 3.0434 loss: 2.3529 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3529 2023/06/05 01:21:53 - mmengine - INFO - Epoch(train) [48][ 180/2569] lr: 4.0000e-02 eta: 19:34:28 time: 0.2650 data_time: 0.0078 memory: 5828 grad_norm: 3.0923 loss: 2.3621 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3621 2023/06/05 01:21:58 - mmengine - INFO - Epoch(train) [48][ 200/2569] lr: 4.0000e-02 eta: 19:34:22 time: 0.2584 data_time: 0.0081 memory: 5828 grad_norm: 3.1199 loss: 2.4635 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4635 2023/06/05 01:22:04 - mmengine - INFO - Epoch(train) [48][ 220/2569] lr: 4.0000e-02 eta: 19:34:17 time: 0.2720 data_time: 0.0074 memory: 5828 grad_norm: 3.0249 loss: 2.5527 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5527 2023/06/05 01:22:09 - mmengine - INFO - Epoch(train) [48][ 240/2569] lr: 4.0000e-02 eta: 19:34:12 time: 0.2578 data_time: 0.0081 memory: 5828 grad_norm: 3.0560 loss: 2.5850 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5850 2023/06/05 01:22:14 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:22:15 - mmengine - INFO - Epoch(train) [48][ 260/2569] lr: 4.0000e-02 eta: 19:34:07 time: 0.2779 data_time: 0.0071 memory: 5828 grad_norm: 3.1094 loss: 2.8592 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8592 2023/06/05 01:22:20 - mmengine - INFO - Epoch(train) [48][ 280/2569] lr: 4.0000e-02 eta: 19:34:01 time: 0.2578 data_time: 0.0078 memory: 5828 grad_norm: 3.0521 loss: 2.4354 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4354 2023/06/05 01:22:25 - mmengine - INFO - Epoch(train) [48][ 300/2569] lr: 4.0000e-02 eta: 19:33:56 time: 0.2781 data_time: 0.0079 memory: 5828 grad_norm: 3.1188 loss: 2.8071 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8071 2023/06/05 01:22:31 - mmengine - INFO - Epoch(train) [48][ 320/2569] lr: 4.0000e-02 eta: 19:33:51 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 3.1233 loss: 2.7781 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7781 2023/06/05 01:22:36 - mmengine - INFO - Epoch(train) [48][ 340/2569] lr: 4.0000e-02 eta: 19:33:46 time: 0.2677 data_time: 0.0081 memory: 5828 grad_norm: 3.0736 loss: 2.4446 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4446 2023/06/05 01:22:41 - mmengine - INFO - Epoch(train) [48][ 360/2569] lr: 4.0000e-02 eta: 19:33:40 time: 0.2594 data_time: 0.0079 memory: 5828 grad_norm: 3.0741 loss: 2.9105 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9105 2023/06/05 01:22:46 - mmengine - INFO - Epoch(train) [48][ 380/2569] lr: 4.0000e-02 eta: 19:33:34 time: 0.2623 data_time: 0.0081 memory: 5828 grad_norm: 3.0772 loss: 2.7652 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7652 2023/06/05 01:22:52 - mmengine - INFO - Epoch(train) [48][ 400/2569] lr: 4.0000e-02 eta: 19:33:29 time: 0.2598 data_time: 0.0075 memory: 5828 grad_norm: 3.0725 loss: 2.5041 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5041 2023/06/05 01:22:57 - mmengine - INFO - Epoch(train) [48][ 420/2569] lr: 4.0000e-02 eta: 19:33:23 time: 0.2608 data_time: 0.0072 memory: 5828 grad_norm: 3.1273 loss: 2.3104 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3104 2023/06/05 01:23:02 - mmengine - INFO - Epoch(train) [48][ 440/2569] lr: 4.0000e-02 eta: 19:33:18 time: 0.2633 data_time: 0.0082 memory: 5828 grad_norm: 3.0866 loss: 2.6112 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6112 2023/06/05 01:23:07 - mmengine - INFO - Epoch(train) [48][ 460/2569] lr: 4.0000e-02 eta: 19:33:12 time: 0.2643 data_time: 0.0078 memory: 5828 grad_norm: 3.0644 loss: 2.5960 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5960 2023/06/05 01:23:13 - mmengine - INFO - Epoch(train) [48][ 480/2569] lr: 4.0000e-02 eta: 19:33:07 time: 0.2632 data_time: 0.0089 memory: 5828 grad_norm: 3.0660 loss: 2.7740 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7740 2023/06/05 01:23:18 - mmengine - INFO - Epoch(train) [48][ 500/2569] lr: 4.0000e-02 eta: 19:33:01 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 3.1207 loss: 2.6333 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6333 2023/06/05 01:23:23 - mmengine - INFO - Epoch(train) [48][ 520/2569] lr: 4.0000e-02 eta: 19:32:56 time: 0.2686 data_time: 0.0080 memory: 5828 grad_norm: 3.0894 loss: 2.4742 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4742 2023/06/05 01:23:28 - mmengine - INFO - Epoch(train) [48][ 540/2569] lr: 4.0000e-02 eta: 19:32:51 time: 0.2596 data_time: 0.0078 memory: 5828 grad_norm: 3.1434 loss: 2.7996 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7996 2023/06/05 01:23:34 - mmengine - INFO - Epoch(train) [48][ 560/2569] lr: 4.0000e-02 eta: 19:32:45 time: 0.2650 data_time: 0.0078 memory: 5828 grad_norm: 3.0551 loss: 2.7873 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7873 2023/06/05 01:23:39 - mmengine - INFO - Epoch(train) [48][ 580/2569] lr: 4.0000e-02 eta: 19:32:40 time: 0.2621 data_time: 0.0078 memory: 5828 grad_norm: 3.1802 loss: 2.5214 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5214 2023/06/05 01:23:45 - mmengine - INFO - Epoch(train) [48][ 600/2569] lr: 4.0000e-02 eta: 19:32:35 time: 0.2735 data_time: 0.0077 memory: 5828 grad_norm: 3.1208 loss: 2.8179 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8179 2023/06/05 01:23:50 - mmengine - INFO - Epoch(train) [48][ 620/2569] lr: 4.0000e-02 eta: 19:32:29 time: 0.2652 data_time: 0.0082 memory: 5828 grad_norm: 3.0461 loss: 2.4090 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4090 2023/06/05 01:23:55 - mmengine - INFO - Epoch(train) [48][ 640/2569] lr: 4.0000e-02 eta: 19:32:24 time: 0.2583 data_time: 0.0078 memory: 5828 grad_norm: 3.0926 loss: 2.4864 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4864 2023/06/05 01:24:00 - mmengine - INFO - Epoch(train) [48][ 660/2569] lr: 4.0000e-02 eta: 19:32:18 time: 0.2589 data_time: 0.0080 memory: 5828 grad_norm: 3.1003 loss: 2.5450 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5450 2023/06/05 01:24:06 - mmengine - INFO - Epoch(train) [48][ 680/2569] lr: 4.0000e-02 eta: 19:32:13 time: 0.2692 data_time: 0.0079 memory: 5828 grad_norm: 3.0685 loss: 2.5644 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5644 2023/06/05 01:24:11 - mmengine - INFO - Epoch(train) [48][ 700/2569] lr: 4.0000e-02 eta: 19:32:07 time: 0.2635 data_time: 0.0079 memory: 5828 grad_norm: 3.1396 loss: 2.5331 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5331 2023/06/05 01:24:16 - mmengine - INFO - Epoch(train) [48][ 720/2569] lr: 4.0000e-02 eta: 19:32:02 time: 0.2608 data_time: 0.0076 memory: 5828 grad_norm: 3.0840 loss: 2.3385 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3385 2023/06/05 01:24:21 - mmengine - INFO - Epoch(train) [48][ 740/2569] lr: 4.0000e-02 eta: 19:31:56 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 3.0926 loss: 2.5034 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5034 2023/06/05 01:24:27 - mmengine - INFO - Epoch(train) [48][ 760/2569] lr: 4.0000e-02 eta: 19:31:51 time: 0.2609 data_time: 0.0079 memory: 5828 grad_norm: 3.1492 loss: 2.7162 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7162 2023/06/05 01:24:32 - mmengine - INFO - Epoch(train) [48][ 780/2569] lr: 4.0000e-02 eta: 19:31:46 time: 0.2743 data_time: 0.0082 memory: 5828 grad_norm: 3.0347 loss: 2.3967 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3967 2023/06/05 01:24:37 - mmengine - INFO - Epoch(train) [48][ 800/2569] lr: 4.0000e-02 eta: 19:31:40 time: 0.2588 data_time: 0.0077 memory: 5828 grad_norm: 3.1284 loss: 2.6937 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6937 2023/06/05 01:24:43 - mmengine - INFO - Epoch(train) [48][ 820/2569] lr: 4.0000e-02 eta: 19:31:35 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 3.0917 loss: 2.2313 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2313 2023/06/05 01:24:48 - mmengine - INFO - Epoch(train) [48][ 840/2569] lr: 4.0000e-02 eta: 19:31:29 time: 0.2691 data_time: 0.0077 memory: 5828 grad_norm: 3.1091 loss: 2.5285 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5285 2023/06/05 01:24:53 - mmengine - INFO - Epoch(train) [48][ 860/2569] lr: 4.0000e-02 eta: 19:31:24 time: 0.2656 data_time: 0.0077 memory: 5828 grad_norm: 3.0892 loss: 2.8522 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8522 2023/06/05 01:24:59 - mmengine - INFO - Epoch(train) [48][ 880/2569] lr: 4.0000e-02 eta: 19:31:19 time: 0.2632 data_time: 0.0077 memory: 5828 grad_norm: 3.0377 loss: 2.5666 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5666 2023/06/05 01:25:04 - mmengine - INFO - Epoch(train) [48][ 900/2569] lr: 4.0000e-02 eta: 19:31:13 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 3.1075 loss: 2.6309 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.6309 2023/06/05 01:25:09 - mmengine - INFO - Epoch(train) [48][ 920/2569] lr: 4.0000e-02 eta: 19:31:08 time: 0.2645 data_time: 0.0078 memory: 5828 grad_norm: 3.0397 loss: 2.4297 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4297 2023/06/05 01:25:15 - mmengine - INFO - Epoch(train) [48][ 940/2569] lr: 4.0000e-02 eta: 19:31:03 time: 0.2634 data_time: 0.0079 memory: 5828 grad_norm: 3.1000 loss: 2.8301 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8301 2023/06/05 01:25:20 - mmengine - INFO - Epoch(train) [48][ 960/2569] lr: 4.0000e-02 eta: 19:30:57 time: 0.2595 data_time: 0.0082 memory: 5828 grad_norm: 3.1225 loss: 2.8551 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8551 2023/06/05 01:25:25 - mmengine - INFO - Epoch(train) [48][ 980/2569] lr: 4.0000e-02 eta: 19:30:52 time: 0.2812 data_time: 0.0076 memory: 5828 grad_norm: 3.1011 loss: 2.2292 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2292 2023/06/05 01:25:31 - mmengine - INFO - Epoch(train) [48][1000/2569] lr: 4.0000e-02 eta: 19:30:47 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 3.0654 loss: 2.6533 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6533 2023/06/05 01:25:36 - mmengine - INFO - Epoch(train) [48][1020/2569] lr: 4.0000e-02 eta: 19:30:42 time: 0.2772 data_time: 0.0083 memory: 5828 grad_norm: 3.0663 loss: 2.6168 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6168 2023/06/05 01:25:41 - mmengine - INFO - Epoch(train) [48][1040/2569] lr: 4.0000e-02 eta: 19:30:36 time: 0.2592 data_time: 0.0076 memory: 5828 grad_norm: 3.1743 loss: 2.4388 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4388 2023/06/05 01:25:47 - mmengine - INFO - Epoch(train) [48][1060/2569] lr: 4.0000e-02 eta: 19:30:31 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 3.0377 loss: 2.3704 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3704 2023/06/05 01:25:52 - mmengine - INFO - Epoch(train) [48][1080/2569] lr: 4.0000e-02 eta: 19:30:25 time: 0.2587 data_time: 0.0079 memory: 5828 grad_norm: 3.1869 loss: 2.4399 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4399 2023/06/05 01:25:57 - mmengine - INFO - Epoch(train) [48][1100/2569] lr: 4.0000e-02 eta: 19:30:19 time: 0.2627 data_time: 0.0083 memory: 5828 grad_norm: 3.0752 loss: 2.2911 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2911 2023/06/05 01:26:02 - mmengine - INFO - Epoch(train) [48][1120/2569] lr: 4.0000e-02 eta: 19:30:14 time: 0.2587 data_time: 0.0079 memory: 5828 grad_norm: 3.1165 loss: 2.5877 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5877 2023/06/05 01:26:07 - mmengine - INFO - Epoch(train) [48][1140/2569] lr: 4.0000e-02 eta: 19:30:08 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 3.1480 loss: 2.7729 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7729 2023/06/05 01:26:13 - mmengine - INFO - Epoch(train) [48][1160/2569] lr: 4.0000e-02 eta: 19:30:03 time: 0.2681 data_time: 0.0081 memory: 5828 grad_norm: 3.1437 loss: 2.5184 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5184 2023/06/05 01:26:18 - mmengine - INFO - Epoch(train) [48][1180/2569] lr: 4.0000e-02 eta: 19:29:57 time: 0.2586 data_time: 0.0083 memory: 5828 grad_norm: 3.1013 loss: 2.5933 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5933 2023/06/05 01:26:23 - mmengine - INFO - Epoch(train) [48][1200/2569] lr: 4.0000e-02 eta: 19:29:52 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 3.0747 loss: 2.7089 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7089 2023/06/05 01:26:29 - mmengine - INFO - Epoch(train) [48][1220/2569] lr: 4.0000e-02 eta: 19:29:47 time: 0.2639 data_time: 0.0077 memory: 5828 grad_norm: 3.1009 loss: 2.5616 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5616 2023/06/05 01:26:34 - mmengine - INFO - Epoch(train) [48][1240/2569] lr: 4.0000e-02 eta: 19:29:41 time: 0.2612 data_time: 0.0074 memory: 5828 grad_norm: 3.0407 loss: 2.3492 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3492 2023/06/05 01:26:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:26:39 - mmengine - INFO - Epoch(train) [48][1260/2569] lr: 4.0000e-02 eta: 19:29:36 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.0939 loss: 2.3306 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3306 2023/06/05 01:26:44 - mmengine - INFO - Epoch(train) [48][1280/2569] lr: 4.0000e-02 eta: 19:29:30 time: 0.2654 data_time: 0.0076 memory: 5828 grad_norm: 3.0816 loss: 2.8169 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8169 2023/06/05 01:26:50 - mmengine - INFO - Epoch(train) [48][1300/2569] lr: 4.0000e-02 eta: 19:29:25 time: 0.2678 data_time: 0.0083 memory: 5828 grad_norm: 3.1074 loss: 2.4302 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4302 2023/06/05 01:26:55 - mmengine - INFO - Epoch(train) [48][1320/2569] lr: 4.0000e-02 eta: 19:29:19 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 3.0287 loss: 2.3751 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3751 2023/06/05 01:27:00 - mmengine - INFO - Epoch(train) [48][1340/2569] lr: 4.0000e-02 eta: 19:29:14 time: 0.2624 data_time: 0.0077 memory: 5828 grad_norm: 3.1077 loss: 2.7182 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7182 2023/06/05 01:27:06 - mmengine - INFO - Epoch(train) [48][1360/2569] lr: 4.0000e-02 eta: 19:29:08 time: 0.2601 data_time: 0.0078 memory: 5828 grad_norm: 3.1177 loss: 2.7942 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7942 2023/06/05 01:27:11 - mmengine - INFO - Epoch(train) [48][1380/2569] lr: 4.0000e-02 eta: 19:29:03 time: 0.2630 data_time: 0.0074 memory: 5828 grad_norm: 3.1038 loss: 2.1403 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1403 2023/06/05 01:27:16 - mmengine - INFO - Epoch(train) [48][1400/2569] lr: 4.0000e-02 eta: 19:28:58 time: 0.2662 data_time: 0.0075 memory: 5828 grad_norm: 3.0508 loss: 2.5356 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5356 2023/06/05 01:27:21 - mmengine - INFO - Epoch(train) [48][1420/2569] lr: 4.0000e-02 eta: 19:28:52 time: 0.2574 data_time: 0.0076 memory: 5828 grad_norm: 3.0770 loss: 2.4338 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4338 2023/06/05 01:27:27 - mmengine - INFO - Epoch(train) [48][1440/2569] lr: 4.0000e-02 eta: 19:28:47 time: 0.2727 data_time: 0.0081 memory: 5828 grad_norm: 3.0706 loss: 2.5852 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5852 2023/06/05 01:27:32 - mmengine - INFO - Epoch(train) [48][1460/2569] lr: 4.0000e-02 eta: 19:28:41 time: 0.2582 data_time: 0.0070 memory: 5828 grad_norm: 3.1185 loss: 2.5085 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5085 2023/06/05 01:27:37 - mmengine - INFO - Epoch(train) [48][1480/2569] lr: 4.0000e-02 eta: 19:28:36 time: 0.2651 data_time: 0.0078 memory: 5828 grad_norm: 3.1650 loss: 2.7527 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7527 2023/06/05 01:27:42 - mmengine - INFO - Epoch(train) [48][1500/2569] lr: 4.0000e-02 eta: 19:28:30 time: 0.2581 data_time: 0.0075 memory: 5828 grad_norm: 3.1350 loss: 2.5820 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5820 2023/06/05 01:27:48 - mmengine - INFO - Epoch(train) [48][1520/2569] lr: 4.0000e-02 eta: 19:28:25 time: 0.2652 data_time: 0.0081 memory: 5828 grad_norm: 3.0782 loss: 2.3957 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3957 2023/06/05 01:27:53 - mmengine - INFO - Epoch(train) [48][1540/2569] lr: 4.0000e-02 eta: 19:28:19 time: 0.2586 data_time: 0.0076 memory: 5828 grad_norm: 3.1542 loss: 2.2318 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2318 2023/06/05 01:27:58 - mmengine - INFO - Epoch(train) [48][1560/2569] lr: 4.0000e-02 eta: 19:28:14 time: 0.2675 data_time: 0.0081 memory: 5828 grad_norm: 3.1127 loss: 2.2886 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2886 2023/06/05 01:28:03 - mmengine - INFO - Epoch(train) [48][1580/2569] lr: 4.0000e-02 eta: 19:28:08 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 3.0630 loss: 3.0595 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0595 2023/06/05 01:28:09 - mmengine - INFO - Epoch(train) [48][1600/2569] lr: 4.0000e-02 eta: 19:28:03 time: 0.2644 data_time: 0.0076 memory: 5828 grad_norm: 3.1227 loss: 2.6111 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6111 2023/06/05 01:28:14 - mmengine - INFO - Epoch(train) [48][1620/2569] lr: 4.0000e-02 eta: 19:27:57 time: 0.2596 data_time: 0.0077 memory: 5828 grad_norm: 3.1034 loss: 2.3386 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3386 2023/06/05 01:28:19 - mmengine - INFO - Epoch(train) [48][1640/2569] lr: 4.0000e-02 eta: 19:27:52 time: 0.2618 data_time: 0.0078 memory: 5828 grad_norm: 3.1286 loss: 2.7593 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7593 2023/06/05 01:28:24 - mmengine - INFO - Epoch(train) [48][1660/2569] lr: 4.0000e-02 eta: 19:27:46 time: 0.2572 data_time: 0.0076 memory: 5828 grad_norm: 3.0778 loss: 2.5951 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5951 2023/06/05 01:28:30 - mmengine - INFO - Epoch(train) [48][1680/2569] lr: 4.0000e-02 eta: 19:27:40 time: 0.2635 data_time: 0.0080 memory: 5828 grad_norm: 3.0920 loss: 2.5522 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5522 2023/06/05 01:28:35 - mmengine - INFO - Epoch(train) [48][1700/2569] lr: 4.0000e-02 eta: 19:27:35 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 3.0766 loss: 2.6072 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6072 2023/06/05 01:28:40 - mmengine - INFO - Epoch(train) [48][1720/2569] lr: 4.0000e-02 eta: 19:27:30 time: 0.2686 data_time: 0.0084 memory: 5828 grad_norm: 3.1094 loss: 2.5054 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5054 2023/06/05 01:28:46 - mmengine - INFO - Epoch(train) [48][1740/2569] lr: 4.0000e-02 eta: 19:27:24 time: 0.2633 data_time: 0.0080 memory: 5828 grad_norm: 3.0476 loss: 2.5370 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5370 2023/06/05 01:28:51 - mmengine - INFO - Epoch(train) [48][1760/2569] lr: 4.0000e-02 eta: 19:27:19 time: 0.2656 data_time: 0.0078 memory: 5828 grad_norm: 3.0728 loss: 2.9073 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9073 2023/06/05 01:28:56 - mmengine - INFO - Epoch(train) [48][1780/2569] lr: 4.0000e-02 eta: 19:27:14 time: 0.2753 data_time: 0.0075 memory: 5828 grad_norm: 3.1014 loss: 2.5367 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5367 2023/06/05 01:29:02 - mmengine - INFO - Epoch(train) [48][1800/2569] lr: 4.0000e-02 eta: 19:27:08 time: 0.2585 data_time: 0.0075 memory: 5828 grad_norm: 3.0688 loss: 2.4499 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4499 2023/06/05 01:29:07 - mmengine - INFO - Epoch(train) [48][1820/2569] lr: 4.0000e-02 eta: 19:27:03 time: 0.2640 data_time: 0.0077 memory: 5828 grad_norm: 3.0758 loss: 2.7469 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7469 2023/06/05 01:29:12 - mmengine - INFO - Epoch(train) [48][1840/2569] lr: 4.0000e-02 eta: 19:26:57 time: 0.2581 data_time: 0.0080 memory: 5828 grad_norm: 3.0741 loss: 2.6381 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6381 2023/06/05 01:29:17 - mmengine - INFO - Epoch(train) [48][1860/2569] lr: 4.0000e-02 eta: 19:26:52 time: 0.2668 data_time: 0.0079 memory: 5828 grad_norm: 3.0766 loss: 2.5167 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5167 2023/06/05 01:29:23 - mmengine - INFO - Epoch(train) [48][1880/2569] lr: 4.0000e-02 eta: 19:26:47 time: 0.2690 data_time: 0.0079 memory: 5828 grad_norm: 3.0687 loss: 2.5210 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5210 2023/06/05 01:29:28 - mmengine - INFO - Epoch(train) [48][1900/2569] lr: 4.0000e-02 eta: 19:26:41 time: 0.2577 data_time: 0.0076 memory: 5828 grad_norm: 3.1073 loss: 2.4364 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4364 2023/06/05 01:29:33 - mmengine - INFO - Epoch(train) [48][1920/2569] lr: 4.0000e-02 eta: 19:26:35 time: 0.2577 data_time: 0.0083 memory: 5828 grad_norm: 3.1123 loss: 2.5365 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5365 2023/06/05 01:29:38 - mmengine - INFO - Epoch(train) [48][1940/2569] lr: 4.0000e-02 eta: 19:26:30 time: 0.2594 data_time: 0.0076 memory: 5828 grad_norm: 3.0639 loss: 2.7637 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7637 2023/06/05 01:29:43 - mmengine - INFO - Epoch(train) [48][1960/2569] lr: 4.0000e-02 eta: 19:26:24 time: 0.2589 data_time: 0.0080 memory: 5828 grad_norm: 3.0542 loss: 2.5227 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5227 2023/06/05 01:29:49 - mmengine - INFO - Epoch(train) [48][1980/2569] lr: 4.0000e-02 eta: 19:26:19 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 3.0647 loss: 2.3171 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3171 2023/06/05 01:29:54 - mmengine - INFO - Epoch(train) [48][2000/2569] lr: 4.0000e-02 eta: 19:26:13 time: 0.2637 data_time: 0.0080 memory: 5828 grad_norm: 3.1187 loss: 2.5643 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5643 2023/06/05 01:29:59 - mmengine - INFO - Epoch(train) [48][2020/2569] lr: 4.0000e-02 eta: 19:26:08 time: 0.2627 data_time: 0.0077 memory: 5828 grad_norm: 3.0433 loss: 2.6676 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6676 2023/06/05 01:30:05 - mmengine - INFO - Epoch(train) [48][2040/2569] lr: 4.0000e-02 eta: 19:26:02 time: 0.2599 data_time: 0.0076 memory: 5828 grad_norm: 3.0957 loss: 2.6560 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6560 2023/06/05 01:30:10 - mmengine - INFO - Epoch(train) [48][2060/2569] lr: 4.0000e-02 eta: 19:25:56 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.1159 loss: 2.7394 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7394 2023/06/05 01:30:15 - mmengine - INFO - Epoch(train) [48][2080/2569] lr: 4.0000e-02 eta: 19:25:51 time: 0.2570 data_time: 0.0076 memory: 5828 grad_norm: 3.1048 loss: 2.2380 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2380 2023/06/05 01:30:20 - mmengine - INFO - Epoch(train) [48][2100/2569] lr: 4.0000e-02 eta: 19:25:45 time: 0.2571 data_time: 0.0075 memory: 5828 grad_norm: 3.1104 loss: 2.3538 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3538 2023/06/05 01:30:25 - mmengine - INFO - Epoch(train) [48][2120/2569] lr: 4.0000e-02 eta: 19:25:39 time: 0.2627 data_time: 0.0077 memory: 5828 grad_norm: 3.0529 loss: 2.5273 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5273 2023/06/05 01:30:31 - mmengine - INFO - Epoch(train) [48][2140/2569] lr: 4.0000e-02 eta: 19:25:34 time: 0.2602 data_time: 0.0078 memory: 5828 grad_norm: 3.0270 loss: 2.5506 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5506 2023/06/05 01:30:36 - mmengine - INFO - Epoch(train) [48][2160/2569] lr: 4.0000e-02 eta: 19:25:28 time: 0.2624 data_time: 0.0081 memory: 5828 grad_norm: 3.0854 loss: 2.4582 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4582 2023/06/05 01:30:41 - mmengine - INFO - Epoch(train) [48][2180/2569] lr: 4.0000e-02 eta: 19:25:23 time: 0.2601 data_time: 0.0081 memory: 5828 grad_norm: 3.1125 loss: 2.5776 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5776 2023/06/05 01:30:46 - mmengine - INFO - Epoch(train) [48][2200/2569] lr: 4.0000e-02 eta: 19:25:17 time: 0.2626 data_time: 0.0080 memory: 5828 grad_norm: 3.1513 loss: 2.4126 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4126 2023/06/05 01:30:52 - mmengine - INFO - Epoch(train) [48][2220/2569] lr: 4.0000e-02 eta: 19:25:12 time: 0.2648 data_time: 0.0077 memory: 5828 grad_norm: 3.0792 loss: 2.5278 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5278 2023/06/05 01:30:57 - mmengine - INFO - Epoch(train) [48][2240/2569] lr: 4.0000e-02 eta: 19:25:07 time: 0.2682 data_time: 0.0077 memory: 5828 grad_norm: 3.0489 loss: 2.5069 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5069 2023/06/05 01:31:01 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:31:02 - mmengine - INFO - Epoch(train) [48][2260/2569] lr: 4.0000e-02 eta: 19:25:01 time: 0.2576 data_time: 0.0079 memory: 5828 grad_norm: 3.1568 loss: 2.4171 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4171 2023/06/05 01:31:07 - mmengine - INFO - Epoch(train) [48][2280/2569] lr: 4.0000e-02 eta: 19:24:56 time: 0.2716 data_time: 0.0075 memory: 5828 grad_norm: 3.0913 loss: 2.1875 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1875 2023/06/05 01:31:13 - mmengine - INFO - Epoch(train) [48][2300/2569] lr: 4.0000e-02 eta: 19:24:50 time: 0.2593 data_time: 0.0080 memory: 5828 grad_norm: 3.1029 loss: 2.6365 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6365 2023/06/05 01:31:18 - mmengine - INFO - Epoch(train) [48][2320/2569] lr: 4.0000e-02 eta: 19:24:45 time: 0.2694 data_time: 0.0078 memory: 5828 grad_norm: 3.1338 loss: 2.4689 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4689 2023/06/05 01:31:23 - mmengine - INFO - Epoch(train) [48][2340/2569] lr: 4.0000e-02 eta: 19:24:39 time: 0.2591 data_time: 0.0076 memory: 5828 grad_norm: 3.1578 loss: 2.7168 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7168 2023/06/05 01:31:29 - mmengine - INFO - Epoch(train) [48][2360/2569] lr: 4.0000e-02 eta: 19:24:34 time: 0.2666 data_time: 0.0083 memory: 5828 grad_norm: 3.0978 loss: 2.6504 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6504 2023/06/05 01:31:34 - mmengine - INFO - Epoch(train) [48][2380/2569] lr: 4.0000e-02 eta: 19:24:28 time: 0.2589 data_time: 0.0076 memory: 5828 grad_norm: 3.0909 loss: 2.6884 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6884 2023/06/05 01:31:39 - mmengine - INFO - Epoch(train) [48][2400/2569] lr: 4.0000e-02 eta: 19:24:23 time: 0.2594 data_time: 0.0075 memory: 5828 grad_norm: 3.1368 loss: 3.0166 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 3.0166 2023/06/05 01:31:44 - mmengine - INFO - Epoch(train) [48][2420/2569] lr: 4.0000e-02 eta: 19:24:17 time: 0.2581 data_time: 0.0079 memory: 5828 grad_norm: 3.1431 loss: 2.7038 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7038 2023/06/05 01:31:50 - mmengine - INFO - Epoch(train) [48][2440/2569] lr: 4.0000e-02 eta: 19:24:12 time: 0.2705 data_time: 0.0078 memory: 5828 grad_norm: 3.1611 loss: 2.2869 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2869 2023/06/05 01:31:55 - mmengine - INFO - Epoch(train) [48][2460/2569] lr: 4.0000e-02 eta: 19:24:06 time: 0.2615 data_time: 0.0080 memory: 5828 grad_norm: 3.1014 loss: 2.6148 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6148 2023/06/05 01:32:00 - mmengine - INFO - Epoch(train) [48][2480/2569] lr: 4.0000e-02 eta: 19:24:01 time: 0.2643 data_time: 0.0077 memory: 5828 grad_norm: 3.0746 loss: 2.5593 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5593 2023/06/05 01:32:05 - mmengine - INFO - Epoch(train) [48][2500/2569] lr: 4.0000e-02 eta: 19:23:55 time: 0.2580 data_time: 0.0077 memory: 5828 grad_norm: 3.0451 loss: 2.5296 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5296 2023/06/05 01:32:10 - mmengine - INFO - Epoch(train) [48][2520/2569] lr: 4.0000e-02 eta: 19:23:50 time: 0.2610 data_time: 0.0079 memory: 5828 grad_norm: 3.0643 loss: 2.5787 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5787 2023/06/05 01:32:16 - mmengine - INFO - Epoch(train) [48][2540/2569] lr: 4.0000e-02 eta: 19:23:44 time: 0.2667 data_time: 0.0079 memory: 5828 grad_norm: 3.0908 loss: 2.3613 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3613 2023/06/05 01:32:21 - mmengine - INFO - Epoch(train) [48][2560/2569] lr: 4.0000e-02 eta: 19:23:39 time: 0.2609 data_time: 0.0081 memory: 5828 grad_norm: 3.1581 loss: 2.5199 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5199 2023/06/05 01:32:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:32:23 - mmengine - INFO - Epoch(train) [48][2569/2569] lr: 4.0000e-02 eta: 19:23:36 time: 0.2498 data_time: 0.0075 memory: 5828 grad_norm: 3.1462 loss: 2.6971 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.6971 2023/06/05 01:32:23 - mmengine - INFO - Saving checkpoint at 48 epochs 2023/06/05 01:32:31 - mmengine - INFO - Epoch(train) [49][ 20/2569] lr: 4.0000e-02 eta: 19:23:32 time: 0.2938 data_time: 0.0447 memory: 5828 grad_norm: 3.0253 loss: 2.5754 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5754 2023/06/05 01:32:36 - mmengine - INFO - Epoch(train) [49][ 40/2569] lr: 4.0000e-02 eta: 19:23:26 time: 0.2626 data_time: 0.0078 memory: 5828 grad_norm: 3.1621 loss: 2.3981 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3981 2023/06/05 01:32:42 - mmengine - INFO - Epoch(train) [49][ 60/2569] lr: 4.0000e-02 eta: 19:23:21 time: 0.2684 data_time: 0.0079 memory: 5828 grad_norm: 3.0513 loss: 2.4497 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4497 2023/06/05 01:32:47 - mmengine - INFO - Epoch(train) [49][ 80/2569] lr: 4.0000e-02 eta: 19:23:16 time: 0.2658 data_time: 0.0083 memory: 5828 grad_norm: 3.0678 loss: 2.8905 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8905 2023/06/05 01:32:52 - mmengine - INFO - Epoch(train) [49][ 100/2569] lr: 4.0000e-02 eta: 19:23:10 time: 0.2621 data_time: 0.0077 memory: 5828 grad_norm: 3.0724 loss: 2.5306 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5306 2023/06/05 01:32:58 - mmengine - INFO - Epoch(train) [49][ 120/2569] lr: 4.0000e-02 eta: 19:23:05 time: 0.2680 data_time: 0.0081 memory: 5828 grad_norm: 3.0864 loss: 2.1103 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1103 2023/06/05 01:33:03 - mmengine - INFO - Epoch(train) [49][ 140/2569] lr: 4.0000e-02 eta: 19:23:00 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.1441 loss: 2.3729 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3729 2023/06/05 01:33:08 - mmengine - INFO - Epoch(train) [49][ 160/2569] lr: 4.0000e-02 eta: 19:22:54 time: 0.2697 data_time: 0.0080 memory: 5828 grad_norm: 3.0563 loss: 2.4929 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4929 2023/06/05 01:33:14 - mmengine - INFO - Epoch(train) [49][ 180/2569] lr: 4.0000e-02 eta: 19:22:49 time: 0.2666 data_time: 0.0074 memory: 5828 grad_norm: 3.1346 loss: 2.5020 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5020 2023/06/05 01:33:19 - mmengine - INFO - Epoch(train) [49][ 200/2569] lr: 4.0000e-02 eta: 19:22:44 time: 0.2632 data_time: 0.0076 memory: 5828 grad_norm: 3.0780 loss: 2.5553 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5553 2023/06/05 01:33:24 - mmengine - INFO - Epoch(train) [49][ 220/2569] lr: 4.0000e-02 eta: 19:22:38 time: 0.2704 data_time: 0.0072 memory: 5828 grad_norm: 3.1210 loss: 2.4772 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4772 2023/06/05 01:33:30 - mmengine - INFO - Epoch(train) [49][ 240/2569] lr: 4.0000e-02 eta: 19:22:33 time: 0.2612 data_time: 0.0079 memory: 5828 grad_norm: 3.1167 loss: 2.3009 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3009 2023/06/05 01:33:35 - mmengine - INFO - Epoch(train) [49][ 260/2569] lr: 4.0000e-02 eta: 19:22:28 time: 0.2663 data_time: 0.0079 memory: 5828 grad_norm: 3.1398 loss: 2.5470 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5470 2023/06/05 01:33:40 - mmengine - INFO - Epoch(train) [49][ 280/2569] lr: 4.0000e-02 eta: 19:22:22 time: 0.2651 data_time: 0.0081 memory: 5828 grad_norm: 3.0853 loss: 2.5097 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5097 2023/06/05 01:33:46 - mmengine - INFO - Epoch(train) [49][ 300/2569] lr: 4.0000e-02 eta: 19:22:17 time: 0.2687 data_time: 0.0078 memory: 5828 grad_norm: 3.0633 loss: 2.6145 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6145 2023/06/05 01:33:51 - mmengine - INFO - Epoch(train) [49][ 320/2569] lr: 4.0000e-02 eta: 19:22:11 time: 0.2619 data_time: 0.0077 memory: 5828 grad_norm: 3.0947 loss: 2.4389 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4389 2023/06/05 01:33:56 - mmengine - INFO - Epoch(train) [49][ 340/2569] lr: 4.0000e-02 eta: 19:22:06 time: 0.2677 data_time: 0.0078 memory: 5828 grad_norm: 3.1012 loss: 2.5952 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5952 2023/06/05 01:34:02 - mmengine - INFO - Epoch(train) [49][ 360/2569] lr: 4.0000e-02 eta: 19:22:01 time: 0.2680 data_time: 0.0080 memory: 5828 grad_norm: 3.0608 loss: 2.4026 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4026 2023/06/05 01:34:07 - mmengine - INFO - Epoch(train) [49][ 380/2569] lr: 4.0000e-02 eta: 19:21:56 time: 0.2745 data_time: 0.0076 memory: 5828 grad_norm: 3.1627 loss: 2.3525 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3525 2023/06/05 01:34:12 - mmengine - INFO - Epoch(train) [49][ 400/2569] lr: 4.0000e-02 eta: 19:21:50 time: 0.2627 data_time: 0.0081 memory: 5828 grad_norm: 3.0396 loss: 2.5606 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5606 2023/06/05 01:34:18 - mmengine - INFO - Epoch(train) [49][ 420/2569] lr: 4.0000e-02 eta: 19:21:45 time: 0.2711 data_time: 0.0086 memory: 5828 grad_norm: 3.0597 loss: 2.6318 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6318 2023/06/05 01:34:23 - mmengine - INFO - Epoch(train) [49][ 440/2569] lr: 4.0000e-02 eta: 19:21:40 time: 0.2654 data_time: 0.0078 memory: 5828 grad_norm: 3.1388 loss: 2.4349 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4349 2023/06/05 01:34:29 - mmengine - INFO - Epoch(train) [49][ 460/2569] lr: 4.0000e-02 eta: 19:21:35 time: 0.2858 data_time: 0.0080 memory: 5828 grad_norm: 3.0457 loss: 2.4833 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4833 2023/06/05 01:34:34 - mmengine - INFO - Epoch(train) [49][ 480/2569] lr: 4.0000e-02 eta: 19:21:30 time: 0.2579 data_time: 0.0082 memory: 5828 grad_norm: 3.0729 loss: 2.4547 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4547 2023/06/05 01:34:39 - mmengine - INFO - Epoch(train) [49][ 500/2569] lr: 4.0000e-02 eta: 19:21:24 time: 0.2629 data_time: 0.0078 memory: 5828 grad_norm: 3.1068 loss: 2.3565 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3565 2023/06/05 01:34:44 - mmengine - INFO - Epoch(train) [49][ 520/2569] lr: 4.0000e-02 eta: 19:21:19 time: 0.2593 data_time: 0.0076 memory: 5828 grad_norm: 3.1008 loss: 2.7574 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7574 2023/06/05 01:34:50 - mmengine - INFO - Epoch(train) [49][ 540/2569] lr: 4.0000e-02 eta: 19:21:13 time: 0.2625 data_time: 0.0079 memory: 5828 grad_norm: 3.0905 loss: 2.4965 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4965 2023/06/05 01:34:55 - mmengine - INFO - Epoch(train) [49][ 560/2569] lr: 4.0000e-02 eta: 19:21:07 time: 0.2573 data_time: 0.0070 memory: 5828 grad_norm: 2.9947 loss: 2.5986 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5986 2023/06/05 01:35:00 - mmengine - INFO - Epoch(train) [49][ 580/2569] lr: 4.0000e-02 eta: 19:21:02 time: 0.2628 data_time: 0.0081 memory: 5828 grad_norm: 3.0944 loss: 2.4215 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4215 2023/06/05 01:35:05 - mmengine - INFO - Epoch(train) [49][ 600/2569] lr: 4.0000e-02 eta: 19:20:57 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 3.1749 loss: 2.0839 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0839 2023/06/05 01:35:11 - mmengine - INFO - Epoch(train) [49][ 620/2569] lr: 4.0000e-02 eta: 19:20:52 time: 0.2741 data_time: 0.0075 memory: 5828 grad_norm: 3.0840 loss: 2.5331 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5331 2023/06/05 01:35:16 - mmengine - INFO - Epoch(train) [49][ 640/2569] lr: 4.0000e-02 eta: 19:20:46 time: 0.2583 data_time: 0.0079 memory: 5828 grad_norm: 3.0770 loss: 2.4392 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4392 2023/06/05 01:35:22 - mmengine - INFO - Epoch(train) [49][ 660/2569] lr: 4.0000e-02 eta: 19:20:41 time: 0.2724 data_time: 0.0076 memory: 5828 grad_norm: 3.1498 loss: 2.7307 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7307 2023/06/05 01:35:27 - mmengine - INFO - Epoch(train) [49][ 680/2569] lr: 4.0000e-02 eta: 19:20:35 time: 0.2623 data_time: 0.0076 memory: 5828 grad_norm: 3.1204 loss: 2.5020 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5020 2023/06/05 01:35:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:35:32 - mmengine - INFO - Epoch(train) [49][ 700/2569] lr: 4.0000e-02 eta: 19:20:30 time: 0.2590 data_time: 0.0073 memory: 5828 grad_norm: 3.0785 loss: 2.5820 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5820 2023/06/05 01:35:37 - mmengine - INFO - Epoch(train) [49][ 720/2569] lr: 4.0000e-02 eta: 19:20:24 time: 0.2637 data_time: 0.0076 memory: 5828 grad_norm: 3.1189 loss: 2.3036 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3036 2023/06/05 01:35:43 - mmengine - INFO - Epoch(train) [49][ 740/2569] lr: 4.0000e-02 eta: 19:20:19 time: 0.2666 data_time: 0.0076 memory: 5828 grad_norm: 3.1533 loss: 2.5869 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5869 2023/06/05 01:35:48 - mmengine - INFO - Epoch(train) [49][ 760/2569] lr: 4.0000e-02 eta: 19:20:13 time: 0.2572 data_time: 0.0079 memory: 5828 grad_norm: 3.0953 loss: 2.8092 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8092 2023/06/05 01:35:53 - mmengine - INFO - Epoch(train) [49][ 780/2569] lr: 4.0000e-02 eta: 19:20:08 time: 0.2634 data_time: 0.0079 memory: 5828 grad_norm: 3.0654 loss: 2.5920 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5920 2023/06/05 01:35:58 - mmengine - INFO - Epoch(train) [49][ 800/2569] lr: 4.0000e-02 eta: 19:20:02 time: 0.2571 data_time: 0.0076 memory: 5828 grad_norm: 3.0610 loss: 2.5802 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5802 2023/06/05 01:36:03 - mmengine - INFO - Epoch(train) [49][ 820/2569] lr: 4.0000e-02 eta: 19:19:56 time: 0.2589 data_time: 0.0076 memory: 5828 grad_norm: 3.0932 loss: 2.2809 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2809 2023/06/05 01:36:09 - mmengine - INFO - Epoch(train) [49][ 840/2569] lr: 4.0000e-02 eta: 19:19:51 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 3.0757 loss: 2.8552 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8552 2023/06/05 01:36:14 - mmengine - INFO - Epoch(train) [49][ 860/2569] lr: 4.0000e-02 eta: 19:19:45 time: 0.2639 data_time: 0.0078 memory: 5828 grad_norm: 3.1451 loss: 2.3006 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3006 2023/06/05 01:36:19 - mmengine - INFO - Epoch(train) [49][ 880/2569] lr: 4.0000e-02 eta: 19:19:40 time: 0.2596 data_time: 0.0074 memory: 5828 grad_norm: 3.0250 loss: 2.4965 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4965 2023/06/05 01:36:25 - mmengine - INFO - Epoch(train) [49][ 900/2569] lr: 4.0000e-02 eta: 19:19:35 time: 0.2692 data_time: 0.0092 memory: 5828 grad_norm: 3.1086 loss: 2.9139 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9139 2023/06/05 01:36:30 - mmengine - INFO - Epoch(train) [49][ 920/2569] lr: 4.0000e-02 eta: 19:19:29 time: 0.2583 data_time: 0.0080 memory: 5828 grad_norm: 3.0607 loss: 2.6041 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6041 2023/06/05 01:36:35 - mmengine - INFO - Epoch(train) [49][ 940/2569] lr: 4.0000e-02 eta: 19:19:24 time: 0.2651 data_time: 0.0077 memory: 5828 grad_norm: 3.1362 loss: 2.6807 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6807 2023/06/05 01:36:40 - mmengine - INFO - Epoch(train) [49][ 960/2569] lr: 4.0000e-02 eta: 19:19:18 time: 0.2615 data_time: 0.0079 memory: 5828 grad_norm: 3.1163 loss: 2.3514 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3514 2023/06/05 01:36:46 - mmengine - INFO - Epoch(train) [49][ 980/2569] lr: 4.0000e-02 eta: 19:19:13 time: 0.2642 data_time: 0.0080 memory: 5828 grad_norm: 3.1163 loss: 2.4685 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4685 2023/06/05 01:36:51 - mmengine - INFO - Epoch(train) [49][1000/2569] lr: 4.0000e-02 eta: 19:19:07 time: 0.2577 data_time: 0.0081 memory: 5828 grad_norm: 3.0820 loss: 2.4623 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4623 2023/06/05 01:36:56 - mmengine - INFO - Epoch(train) [49][1020/2569] lr: 4.0000e-02 eta: 19:19:01 time: 0.2573 data_time: 0.0072 memory: 5828 grad_norm: 3.1749 loss: 2.5519 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5519 2023/06/05 01:37:01 - mmengine - INFO - Epoch(train) [49][1040/2569] lr: 4.0000e-02 eta: 19:18:56 time: 0.2700 data_time: 0.0223 memory: 5828 grad_norm: 3.1391 loss: 2.7057 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7057 2023/06/05 01:37:07 - mmengine - INFO - Epoch(train) [49][1060/2569] lr: 4.0000e-02 eta: 19:18:51 time: 0.2822 data_time: 0.0239 memory: 5828 grad_norm: 3.1420 loss: 2.5521 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5521 2023/06/05 01:37:12 - mmengine - INFO - Epoch(train) [49][1080/2569] lr: 4.0000e-02 eta: 19:18:46 time: 0.2576 data_time: 0.0076 memory: 5828 grad_norm: 3.1050 loss: 2.4591 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4591 2023/06/05 01:37:17 - mmengine - INFO - Epoch(train) [49][1100/2569] lr: 4.0000e-02 eta: 19:18:41 time: 0.2717 data_time: 0.0128 memory: 5828 grad_norm: 3.0752 loss: 2.4473 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4473 2023/06/05 01:37:23 - mmengine - INFO - Epoch(train) [49][1120/2569] lr: 4.0000e-02 eta: 19:18:35 time: 0.2642 data_time: 0.0076 memory: 5828 grad_norm: 3.0622 loss: 2.6691 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6691 2023/06/05 01:37:28 - mmengine - INFO - Epoch(train) [49][1140/2569] lr: 4.0000e-02 eta: 19:18:29 time: 0.2568 data_time: 0.0079 memory: 5828 grad_norm: 3.0964 loss: 2.6109 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6109 2023/06/05 01:37:33 - mmengine - INFO - Epoch(train) [49][1160/2569] lr: 4.0000e-02 eta: 19:18:24 time: 0.2654 data_time: 0.0080 memory: 5828 grad_norm: 3.2116 loss: 2.5898 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5898 2023/06/05 01:37:38 - mmengine - INFO - Epoch(train) [49][1180/2569] lr: 4.0000e-02 eta: 19:18:18 time: 0.2579 data_time: 0.0081 memory: 5828 grad_norm: 3.1310 loss: 2.2746 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2746 2023/06/05 01:37:44 - mmengine - INFO - Epoch(train) [49][1200/2569] lr: 4.0000e-02 eta: 19:18:13 time: 0.2654 data_time: 0.0074 memory: 5828 grad_norm: 3.1042 loss: 2.5523 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5523 2023/06/05 01:37:49 - mmengine - INFO - Epoch(train) [49][1220/2569] lr: 4.0000e-02 eta: 19:18:07 time: 0.2588 data_time: 0.0083 memory: 5828 grad_norm: 3.1224 loss: 2.4262 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4262 2023/06/05 01:37:54 - mmengine - INFO - Epoch(train) [49][1240/2569] lr: 4.0000e-02 eta: 19:18:02 time: 0.2626 data_time: 0.0076 memory: 5828 grad_norm: 3.0611 loss: 2.2486 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2486 2023/06/05 01:38:00 - mmengine - INFO - Epoch(train) [49][1260/2569] lr: 4.0000e-02 eta: 19:17:57 time: 0.2721 data_time: 0.0077 memory: 5828 grad_norm: 3.0792 loss: 3.0926 top1_acc: 0.0000 top5_acc: 0.7500 loss_cls: 3.0926 2023/06/05 01:38:05 - mmengine - INFO - Epoch(train) [49][1280/2569] lr: 4.0000e-02 eta: 19:17:51 time: 0.2622 data_time: 0.0080 memory: 5828 grad_norm: 3.1780 loss: 2.7994 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7994 2023/06/05 01:38:10 - mmengine - INFO - Epoch(train) [49][1300/2569] lr: 4.0000e-02 eta: 19:17:46 time: 0.2691 data_time: 0.0081 memory: 5828 grad_norm: 3.1338 loss: 2.6268 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6268 2023/06/05 01:38:16 - mmengine - INFO - Epoch(train) [49][1320/2569] lr: 4.0000e-02 eta: 19:17:41 time: 0.2683 data_time: 0.0081 memory: 5828 grad_norm: 3.1103 loss: 2.4448 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4448 2023/06/05 01:38:21 - mmengine - INFO - Epoch(train) [49][1340/2569] lr: 4.0000e-02 eta: 19:17:36 time: 0.2729 data_time: 0.0078 memory: 5828 grad_norm: 3.1327 loss: 2.6902 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6902 2023/06/05 01:38:26 - mmengine - INFO - Epoch(train) [49][1360/2569] lr: 4.0000e-02 eta: 19:17:30 time: 0.2591 data_time: 0.0079 memory: 5828 grad_norm: 3.0654 loss: 2.6329 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6329 2023/06/05 01:38:32 - mmengine - INFO - Epoch(train) [49][1380/2569] lr: 4.0000e-02 eta: 19:17:25 time: 0.2670 data_time: 0.0077 memory: 5828 grad_norm: 3.1791 loss: 2.5190 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5190 2023/06/05 01:38:37 - mmengine - INFO - Epoch(train) [49][1400/2569] lr: 4.0000e-02 eta: 19:17:19 time: 0.2589 data_time: 0.0082 memory: 5828 grad_norm: 3.0876 loss: 2.5096 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5096 2023/06/05 01:38:42 - mmengine - INFO - Epoch(train) [49][1420/2569] lr: 4.0000e-02 eta: 19:17:14 time: 0.2670 data_time: 0.0075 memory: 5828 grad_norm: 3.0634 loss: 2.4165 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4165 2023/06/05 01:38:47 - mmengine - INFO - Epoch(train) [49][1440/2569] lr: 4.0000e-02 eta: 19:17:09 time: 0.2670 data_time: 0.0080 memory: 5828 grad_norm: 3.1097 loss: 2.6235 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6235 2023/06/05 01:38:53 - mmengine - INFO - Epoch(train) [49][1460/2569] lr: 4.0000e-02 eta: 19:17:03 time: 0.2728 data_time: 0.0078 memory: 5828 grad_norm: 3.1424 loss: 2.6650 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6650 2023/06/05 01:38:58 - mmengine - INFO - Epoch(train) [49][1480/2569] lr: 4.0000e-02 eta: 19:16:58 time: 0.2667 data_time: 0.0078 memory: 5828 grad_norm: 3.0436 loss: 2.7488 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7488 2023/06/05 01:39:04 - mmengine - INFO - Epoch(train) [49][1500/2569] lr: 4.0000e-02 eta: 19:16:53 time: 0.2655 data_time: 0.0071 memory: 5828 grad_norm: 3.1186 loss: 2.2658 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2658 2023/06/05 01:39:09 - mmengine - INFO - Epoch(train) [49][1520/2569] lr: 4.0000e-02 eta: 19:16:47 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 3.1301 loss: 2.7352 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7352 2023/06/05 01:39:14 - mmengine - INFO - Epoch(train) [49][1540/2569] lr: 4.0000e-02 eta: 19:16:42 time: 0.2626 data_time: 0.0076 memory: 5828 grad_norm: 3.1079 loss: 2.9622 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9622 2023/06/05 01:39:20 - mmengine - INFO - Epoch(train) [49][1560/2569] lr: 4.0000e-02 eta: 19:16:37 time: 0.2668 data_time: 0.0080 memory: 5828 grad_norm: 3.0584 loss: 2.5777 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5777 2023/06/05 01:39:25 - mmengine - INFO - Epoch(train) [49][1580/2569] lr: 4.0000e-02 eta: 19:16:31 time: 0.2688 data_time: 0.0071 memory: 5828 grad_norm: 3.0830 loss: 2.4846 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4846 2023/06/05 01:39:30 - mmengine - INFO - Epoch(train) [49][1600/2569] lr: 4.0000e-02 eta: 19:16:26 time: 0.2637 data_time: 0.0075 memory: 5828 grad_norm: 3.0687 loss: 2.3804 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3804 2023/06/05 01:39:35 - mmengine - INFO - Epoch(train) [49][1620/2569] lr: 4.0000e-02 eta: 19:16:20 time: 0.2583 data_time: 0.0074 memory: 5828 grad_norm: 3.0895 loss: 2.5585 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5585 2023/06/05 01:39:41 - mmengine - INFO - Epoch(train) [49][1640/2569] lr: 4.0000e-02 eta: 19:16:15 time: 0.2629 data_time: 0.0078 memory: 5828 grad_norm: 3.0941 loss: 2.5441 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5441 2023/06/05 01:39:46 - mmengine - INFO - Epoch(train) [49][1660/2569] lr: 4.0000e-02 eta: 19:16:09 time: 0.2647 data_time: 0.0078 memory: 5828 grad_norm: 3.0815 loss: 2.6494 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6494 2023/06/05 01:39:51 - mmengine - INFO - Epoch(train) [49][1680/2569] lr: 4.0000e-02 eta: 19:16:04 time: 0.2636 data_time: 0.0080 memory: 5828 grad_norm: 3.1128 loss: 2.5880 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5880 2023/06/05 01:39:53 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:39:57 - mmengine - INFO - Epoch(train) [49][1700/2569] lr: 4.0000e-02 eta: 19:15:59 time: 0.2686 data_time: 0.0081 memory: 5828 grad_norm: 3.1370 loss: 2.4181 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4181 2023/06/05 01:40:02 - mmengine - INFO - Epoch(train) [49][1720/2569] lr: 4.0000e-02 eta: 19:15:53 time: 0.2671 data_time: 0.0080 memory: 5828 grad_norm: 3.1092 loss: 2.7716 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7716 2023/06/05 01:40:07 - mmengine - INFO - Epoch(train) [49][1740/2569] lr: 4.0000e-02 eta: 19:15:48 time: 0.2596 data_time: 0.0074 memory: 5828 grad_norm: 3.0572 loss: 2.6007 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6007 2023/06/05 01:40:12 - mmengine - INFO - Epoch(train) [49][1760/2569] lr: 4.0000e-02 eta: 19:15:42 time: 0.2576 data_time: 0.0080 memory: 5828 grad_norm: 3.1065 loss: 2.8512 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.8512 2023/06/05 01:40:17 - mmengine - INFO - Epoch(train) [49][1780/2569] lr: 4.0000e-02 eta: 19:15:37 time: 0.2580 data_time: 0.0077 memory: 5828 grad_norm: 3.0917 loss: 2.3024 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3024 2023/06/05 01:40:23 - mmengine - INFO - Epoch(train) [49][1800/2569] lr: 4.0000e-02 eta: 19:15:31 time: 0.2583 data_time: 0.0074 memory: 5828 grad_norm: 3.0793 loss: 2.6501 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6501 2023/06/05 01:40:28 - mmengine - INFO - Epoch(train) [49][1820/2569] lr: 4.0000e-02 eta: 19:15:25 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 3.2076 loss: 2.3575 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3575 2023/06/05 01:40:33 - mmengine - INFO - Epoch(train) [49][1840/2569] lr: 4.0000e-02 eta: 19:15:20 time: 0.2572 data_time: 0.0078 memory: 5828 grad_norm: 3.0861 loss: 2.6005 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6005 2023/06/05 01:40:38 - mmengine - INFO - Epoch(train) [49][1860/2569] lr: 4.0000e-02 eta: 19:15:14 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 3.0978 loss: 2.6820 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6820 2023/06/05 01:40:44 - mmengine - INFO - Epoch(train) [49][1880/2569] lr: 4.0000e-02 eta: 19:15:09 time: 0.2695 data_time: 0.0079 memory: 5828 grad_norm: 3.0790 loss: 2.4794 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4794 2023/06/05 01:40:49 - mmengine - INFO - Epoch(train) [49][1900/2569] lr: 4.0000e-02 eta: 19:15:04 time: 0.2656 data_time: 0.0081 memory: 5828 grad_norm: 3.1155 loss: 2.4868 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4868 2023/06/05 01:40:54 - mmengine - INFO - Epoch(train) [49][1920/2569] lr: 4.0000e-02 eta: 19:14:59 time: 0.2688 data_time: 0.0080 memory: 5828 grad_norm: 3.0805 loss: 2.8655 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8655 2023/06/05 01:41:00 - mmengine - INFO - Epoch(train) [49][1940/2569] lr: 4.0000e-02 eta: 19:14:53 time: 0.2607 data_time: 0.0075 memory: 5828 grad_norm: 3.0966 loss: 2.7124 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7124 2023/06/05 01:41:05 - mmengine - INFO - Epoch(train) [49][1960/2569] lr: 4.0000e-02 eta: 19:14:47 time: 0.2598 data_time: 0.0080 memory: 5828 grad_norm: 3.0960 loss: 2.2963 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2963 2023/06/05 01:41:10 - mmengine - INFO - Epoch(train) [49][1980/2569] lr: 4.0000e-02 eta: 19:14:42 time: 0.2584 data_time: 0.0076 memory: 5828 grad_norm: 3.1260 loss: 2.2198 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2198 2023/06/05 01:41:15 - mmengine - INFO - Epoch(train) [49][2000/2569] lr: 4.0000e-02 eta: 19:14:36 time: 0.2693 data_time: 0.0078 memory: 5828 grad_norm: 3.1322 loss: 2.5038 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5038 2023/06/05 01:41:21 - mmengine - INFO - Epoch(train) [49][2020/2569] lr: 4.0000e-02 eta: 19:14:31 time: 0.2583 data_time: 0.0074 memory: 5828 grad_norm: 3.1643 loss: 2.7015 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7015 2023/06/05 01:41:26 - mmengine - INFO - Epoch(train) [49][2040/2569] lr: 4.0000e-02 eta: 19:14:25 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 3.1295 loss: 2.3533 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3533 2023/06/05 01:41:31 - mmengine - INFO - Epoch(train) [49][2060/2569] lr: 4.0000e-02 eta: 19:14:20 time: 0.2687 data_time: 0.0080 memory: 5828 grad_norm: 3.0684 loss: 2.5426 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5426 2023/06/05 01:41:37 - mmengine - INFO - Epoch(train) [49][2080/2569] lr: 4.0000e-02 eta: 19:14:15 time: 0.2586 data_time: 0.0081 memory: 5828 grad_norm: 3.1212 loss: 2.3472 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.3472 2023/06/05 01:41:42 - mmengine - INFO - Epoch(train) [49][2100/2569] lr: 4.0000e-02 eta: 19:14:09 time: 0.2579 data_time: 0.0073 memory: 5828 grad_norm: 3.1085 loss: 2.7313 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7313 2023/06/05 01:41:47 - mmengine - INFO - Epoch(train) [49][2120/2569] lr: 4.0000e-02 eta: 19:14:03 time: 0.2572 data_time: 0.0083 memory: 5828 grad_norm: 3.1002 loss: 2.2782 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.2782 2023/06/05 01:41:52 - mmengine - INFO - Epoch(train) [49][2140/2569] lr: 4.0000e-02 eta: 19:13:58 time: 0.2681 data_time: 0.0077 memory: 5828 grad_norm: 3.0898 loss: 2.1817 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1817 2023/06/05 01:41:57 - mmengine - INFO - Epoch(train) [49][2160/2569] lr: 4.0000e-02 eta: 19:13:52 time: 0.2619 data_time: 0.0080 memory: 5828 grad_norm: 3.0792 loss: 2.4183 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4183 2023/06/05 01:42:03 - mmengine - INFO - Epoch(train) [49][2180/2569] lr: 4.0000e-02 eta: 19:13:47 time: 0.2649 data_time: 0.0078 memory: 5828 grad_norm: 3.1027 loss: 2.8011 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8011 2023/06/05 01:42:08 - mmengine - INFO - Epoch(train) [49][2200/2569] lr: 4.0000e-02 eta: 19:13:42 time: 0.2665 data_time: 0.0077 memory: 5828 grad_norm: 3.1511 loss: 2.4803 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4803 2023/06/05 01:42:13 - mmengine - INFO - Epoch(train) [49][2220/2569] lr: 4.0000e-02 eta: 19:13:37 time: 0.2711 data_time: 0.0076 memory: 5828 grad_norm: 3.1067 loss: 2.6295 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 2.6295 2023/06/05 01:42:19 - mmengine - INFO - Epoch(train) [49][2240/2569] lr: 4.0000e-02 eta: 19:13:31 time: 0.2590 data_time: 0.0084 memory: 5828 grad_norm: 3.0564 loss: 2.7055 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7055 2023/06/05 01:42:24 - mmengine - INFO - Epoch(train) [49][2260/2569] lr: 4.0000e-02 eta: 19:13:25 time: 0.2637 data_time: 0.0077 memory: 5828 grad_norm: 3.0864 loss: 2.5528 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5528 2023/06/05 01:42:29 - mmengine - INFO - Epoch(train) [49][2280/2569] lr: 4.0000e-02 eta: 19:13:20 time: 0.2641 data_time: 0.0080 memory: 5828 grad_norm: 3.0686 loss: 2.8222 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8222 2023/06/05 01:42:34 - mmengine - INFO - Epoch(train) [49][2300/2569] lr: 4.0000e-02 eta: 19:13:14 time: 0.2588 data_time: 0.0081 memory: 5828 grad_norm: 3.1205 loss: 2.5985 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5985 2023/06/05 01:42:40 - mmengine - INFO - Epoch(train) [49][2320/2569] lr: 4.0000e-02 eta: 19:13:09 time: 0.2682 data_time: 0.0076 memory: 5828 grad_norm: 3.0802 loss: 2.6862 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6862 2023/06/05 01:42:45 - mmengine - INFO - Epoch(train) [49][2340/2569] lr: 4.0000e-02 eta: 19:13:04 time: 0.2668 data_time: 0.0076 memory: 5828 grad_norm: 3.0889 loss: 2.7878 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7878 2023/06/05 01:42:51 - mmengine - INFO - Epoch(train) [49][2360/2569] lr: 4.0000e-02 eta: 19:12:59 time: 0.2692 data_time: 0.0081 memory: 5828 grad_norm: 3.1107 loss: 2.6053 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6053 2023/06/05 01:42:56 - mmengine - INFO - Epoch(train) [49][2380/2569] lr: 4.0000e-02 eta: 19:12:53 time: 0.2642 data_time: 0.0078 memory: 5828 grad_norm: 3.1508 loss: 2.3520 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3520 2023/06/05 01:43:01 - mmengine - INFO - Epoch(train) [49][2400/2569] lr: 4.0000e-02 eta: 19:12:48 time: 0.2586 data_time: 0.0079 memory: 5828 grad_norm: 3.1112 loss: 2.4933 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4933 2023/06/05 01:43:06 - mmengine - INFO - Epoch(train) [49][2420/2569] lr: 4.0000e-02 eta: 19:12:42 time: 0.2591 data_time: 0.0074 memory: 5828 grad_norm: 3.1259 loss: 2.5644 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5644 2023/06/05 01:43:11 - mmengine - INFO - Epoch(train) [49][2440/2569] lr: 4.0000e-02 eta: 19:12:36 time: 0.2600 data_time: 0.0082 memory: 5828 grad_norm: 3.0876 loss: 2.6198 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6198 2023/06/05 01:43:17 - mmengine - INFO - Epoch(train) [49][2460/2569] lr: 4.0000e-02 eta: 19:12:31 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 3.0527 loss: 2.8463 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8463 2023/06/05 01:43:22 - mmengine - INFO - Epoch(train) [49][2480/2569] lr: 4.0000e-02 eta: 19:12:25 time: 0.2575 data_time: 0.0078 memory: 5828 grad_norm: 3.1283 loss: 2.3114 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3114 2023/06/05 01:43:27 - mmengine - INFO - Epoch(train) [49][2500/2569] lr: 4.0000e-02 eta: 19:12:20 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 3.1345 loss: 2.7582 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7582 2023/06/05 01:43:32 - mmengine - INFO - Epoch(train) [49][2520/2569] lr: 4.0000e-02 eta: 19:12:14 time: 0.2570 data_time: 0.0077 memory: 5828 grad_norm: 3.0231 loss: 2.4411 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4411 2023/06/05 01:43:37 - mmengine - INFO - Epoch(train) [49][2540/2569] lr: 4.0000e-02 eta: 19:12:09 time: 0.2577 data_time: 0.0078 memory: 5828 grad_norm: 3.0802 loss: 2.7532 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7532 2023/06/05 01:43:43 - mmengine - INFO - Epoch(train) [49][2560/2569] lr: 4.0000e-02 eta: 19:12:03 time: 0.2598 data_time: 0.0080 memory: 5828 grad_norm: 3.0712 loss: 2.6901 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6901 2023/06/05 01:43:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:43:45 - mmengine - INFO - Epoch(train) [49][2569/2569] lr: 4.0000e-02 eta: 19:12:00 time: 0.2492 data_time: 0.0076 memory: 5828 grad_norm: 3.0599 loss: 2.6901 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.6901 2023/06/05 01:43:52 - mmengine - INFO - Epoch(train) [50][ 20/2569] lr: 4.0000e-02 eta: 19:11:58 time: 0.3397 data_time: 0.0531 memory: 5828 grad_norm: 3.0677 loss: 2.7108 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7108 2023/06/05 01:43:57 - mmengine - INFO - Epoch(train) [50][ 40/2569] lr: 4.0000e-02 eta: 19:11:52 time: 0.2666 data_time: 0.0078 memory: 5828 grad_norm: 3.1758 loss: 2.4552 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4552 2023/06/05 01:44:02 - mmengine - INFO - Epoch(train) [50][ 60/2569] lr: 4.0000e-02 eta: 19:11:47 time: 0.2723 data_time: 0.0074 memory: 5828 grad_norm: 3.1307 loss: 2.6166 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6166 2023/06/05 01:44:08 - mmengine - INFO - Epoch(train) [50][ 80/2569] lr: 4.0000e-02 eta: 19:11:42 time: 0.2653 data_time: 0.0080 memory: 5828 grad_norm: 3.0222 loss: 2.5927 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5927 2023/06/05 01:44:13 - mmengine - INFO - Epoch(train) [50][ 100/2569] lr: 4.0000e-02 eta: 19:11:37 time: 0.2672 data_time: 0.0075 memory: 5828 grad_norm: 3.1877 loss: 2.6415 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6415 2023/06/05 01:44:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:44:18 - mmengine - INFO - Epoch(train) [50][ 120/2569] lr: 4.0000e-02 eta: 19:11:31 time: 0.2595 data_time: 0.0083 memory: 5828 grad_norm: 3.1018 loss: 2.6579 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6579 2023/06/05 01:44:24 - mmengine - INFO - Epoch(train) [50][ 140/2569] lr: 4.0000e-02 eta: 19:11:26 time: 0.2748 data_time: 0.0076 memory: 5828 grad_norm: 3.0882 loss: 2.3191 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3191 2023/06/05 01:44:29 - mmengine - INFO - Epoch(train) [50][ 160/2569] lr: 4.0000e-02 eta: 19:11:21 time: 0.2590 data_time: 0.0079 memory: 5828 grad_norm: 3.1465 loss: 2.4955 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4955 2023/06/05 01:44:34 - mmengine - INFO - Epoch(train) [50][ 180/2569] lr: 4.0000e-02 eta: 19:11:15 time: 0.2574 data_time: 0.0077 memory: 5828 grad_norm: 3.0963 loss: 2.7991 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7991 2023/06/05 01:44:39 - mmengine - INFO - Epoch(train) [50][ 200/2569] lr: 4.0000e-02 eta: 19:11:09 time: 0.2590 data_time: 0.0079 memory: 5828 grad_norm: 3.1523 loss: 2.5565 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5565 2023/06/05 01:44:45 - mmengine - INFO - Epoch(train) [50][ 220/2569] lr: 4.0000e-02 eta: 19:11:04 time: 0.2588 data_time: 0.0074 memory: 5828 grad_norm: 3.1233 loss: 2.7611 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7611 2023/06/05 01:44:50 - mmengine - INFO - Epoch(train) [50][ 240/2569] lr: 4.0000e-02 eta: 19:10:58 time: 0.2680 data_time: 0.0080 memory: 5828 grad_norm: 3.0726 loss: 2.2453 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2453 2023/06/05 01:44:55 - mmengine - INFO - Epoch(train) [50][ 260/2569] lr: 4.0000e-02 eta: 19:10:53 time: 0.2579 data_time: 0.0080 memory: 5828 grad_norm: 3.0807 loss: 2.1153 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1153 2023/06/05 01:45:00 - mmengine - INFO - Epoch(train) [50][ 280/2569] lr: 4.0000e-02 eta: 19:10:47 time: 0.2594 data_time: 0.0071 memory: 5828 grad_norm: 3.1905 loss: 2.7520 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7520 2023/06/05 01:45:06 - mmengine - INFO - Epoch(train) [50][ 300/2569] lr: 4.0000e-02 eta: 19:10:42 time: 0.2676 data_time: 0.0075 memory: 5828 grad_norm: 3.1059 loss: 2.6079 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6079 2023/06/05 01:45:11 - mmengine - INFO - Epoch(train) [50][ 320/2569] lr: 4.0000e-02 eta: 19:10:36 time: 0.2621 data_time: 0.0081 memory: 5828 grad_norm: 3.1788 loss: 2.6593 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6593 2023/06/05 01:45:16 - mmengine - INFO - Epoch(train) [50][ 340/2569] lr: 4.0000e-02 eta: 19:10:31 time: 0.2627 data_time: 0.0078 memory: 5828 grad_norm: 3.0576 loss: 2.7779 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7779 2023/06/05 01:45:21 - mmengine - INFO - Epoch(train) [50][ 360/2569] lr: 4.0000e-02 eta: 19:10:25 time: 0.2614 data_time: 0.0079 memory: 5828 grad_norm: 3.1191 loss: 2.4795 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4795 2023/06/05 01:45:27 - mmengine - INFO - Epoch(train) [50][ 380/2569] lr: 4.0000e-02 eta: 19:10:20 time: 0.2640 data_time: 0.0078 memory: 5828 grad_norm: 3.0624 loss: 2.5913 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5913 2023/06/05 01:45:32 - mmengine - INFO - Epoch(train) [50][ 400/2569] lr: 4.0000e-02 eta: 19:10:15 time: 0.2701 data_time: 0.0079 memory: 5828 grad_norm: 3.0721 loss: 2.7134 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7134 2023/06/05 01:45:37 - mmengine - INFO - Epoch(train) [50][ 420/2569] lr: 4.0000e-02 eta: 19:10:09 time: 0.2643 data_time: 0.0079 memory: 5828 grad_norm: 3.0946 loss: 2.3956 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3956 2023/06/05 01:45:43 - mmengine - INFO - Epoch(train) [50][ 440/2569] lr: 4.0000e-02 eta: 19:10:04 time: 0.2600 data_time: 0.0076 memory: 5828 grad_norm: 3.0434 loss: 3.0136 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 3.0136 2023/06/05 01:45:48 - mmengine - INFO - Epoch(train) [50][ 460/2569] lr: 4.0000e-02 eta: 19:09:58 time: 0.2619 data_time: 0.0077 memory: 5828 grad_norm: 3.0913 loss: 2.8761 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8761 2023/06/05 01:45:53 - mmengine - INFO - Epoch(train) [50][ 480/2569] lr: 4.0000e-02 eta: 19:09:52 time: 0.2588 data_time: 0.0073 memory: 5828 grad_norm: 3.1417 loss: 2.6200 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6200 2023/06/05 01:45:58 - mmengine - INFO - Epoch(train) [50][ 500/2569] lr: 4.0000e-02 eta: 19:09:47 time: 0.2632 data_time: 0.0076 memory: 5828 grad_norm: 3.0901 loss: 2.3430 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3430 2023/06/05 01:46:03 - mmengine - INFO - Epoch(train) [50][ 520/2569] lr: 4.0000e-02 eta: 19:09:41 time: 0.2600 data_time: 0.0079 memory: 5828 grad_norm: 3.1015 loss: 2.4006 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4006 2023/06/05 01:46:09 - mmengine - INFO - Epoch(train) [50][ 540/2569] lr: 4.0000e-02 eta: 19:09:36 time: 0.2636 data_time: 0.0077 memory: 5828 grad_norm: 3.0067 loss: 2.2198 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2198 2023/06/05 01:46:14 - mmengine - INFO - Epoch(train) [50][ 560/2569] lr: 4.0000e-02 eta: 19:09:31 time: 0.2642 data_time: 0.0078 memory: 5828 grad_norm: 3.1315 loss: 2.6075 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6075 2023/06/05 01:46:19 - mmengine - INFO - Epoch(train) [50][ 580/2569] lr: 4.0000e-02 eta: 19:09:25 time: 0.2591 data_time: 0.0080 memory: 5828 grad_norm: 3.1297 loss: 3.0300 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 3.0300 2023/06/05 01:46:25 - mmengine - INFO - Epoch(train) [50][ 600/2569] lr: 4.0000e-02 eta: 19:09:19 time: 0.2645 data_time: 0.0080 memory: 5828 grad_norm: 3.1727 loss: 2.4476 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4476 2023/06/05 01:46:30 - mmengine - INFO - Epoch(train) [50][ 620/2569] lr: 4.0000e-02 eta: 19:09:14 time: 0.2584 data_time: 0.0073 memory: 5828 grad_norm: 3.0518 loss: 2.1990 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1990 2023/06/05 01:46:35 - mmengine - INFO - Epoch(train) [50][ 640/2569] lr: 4.0000e-02 eta: 19:09:08 time: 0.2628 data_time: 0.0077 memory: 5828 grad_norm: 3.1308 loss: 2.7196 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7196 2023/06/05 01:46:40 - mmengine - INFO - Epoch(train) [50][ 660/2569] lr: 4.0000e-02 eta: 19:09:03 time: 0.2631 data_time: 0.0077 memory: 5828 grad_norm: 3.1240 loss: 2.6492 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6492 2023/06/05 01:46:45 - mmengine - INFO - Epoch(train) [50][ 680/2569] lr: 4.0000e-02 eta: 19:08:57 time: 0.2587 data_time: 0.0079 memory: 5828 grad_norm: 3.0658 loss: 2.5745 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5745 2023/06/05 01:46:51 - mmengine - INFO - Epoch(train) [50][ 700/2569] lr: 4.0000e-02 eta: 19:08:52 time: 0.2630 data_time: 0.0079 memory: 5828 grad_norm: 3.0625 loss: 2.9685 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9685 2023/06/05 01:46:56 - mmengine - INFO - Epoch(train) [50][ 720/2569] lr: 4.0000e-02 eta: 19:08:46 time: 0.2591 data_time: 0.0078 memory: 5828 grad_norm: 3.1070 loss: 2.4662 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4662 2023/06/05 01:47:01 - mmengine - INFO - Epoch(train) [50][ 740/2569] lr: 4.0000e-02 eta: 19:08:41 time: 0.2635 data_time: 0.0076 memory: 5828 grad_norm: 3.1026 loss: 2.2574 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2574 2023/06/05 01:47:06 - mmengine - INFO - Epoch(train) [50][ 760/2569] lr: 4.0000e-02 eta: 19:08:35 time: 0.2586 data_time: 0.0080 memory: 5828 grad_norm: 3.0688 loss: 2.5550 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5550 2023/06/05 01:47:12 - mmengine - INFO - Epoch(train) [50][ 780/2569] lr: 4.0000e-02 eta: 19:08:30 time: 0.2632 data_time: 0.0076 memory: 5828 grad_norm: 3.1436 loss: 2.5468 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.5468 2023/06/05 01:47:17 - mmengine - INFO - Epoch(train) [50][ 800/2569] lr: 4.0000e-02 eta: 19:08:24 time: 0.2687 data_time: 0.0078 memory: 5828 grad_norm: 3.1304 loss: 2.5185 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5185 2023/06/05 01:47:22 - mmengine - INFO - Epoch(train) [50][ 820/2569] lr: 4.0000e-02 eta: 19:08:19 time: 0.2633 data_time: 0.0073 memory: 5828 grad_norm: 3.0845 loss: 2.4691 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4691 2023/06/05 01:47:27 - mmengine - INFO - Epoch(train) [50][ 840/2569] lr: 4.0000e-02 eta: 19:08:13 time: 0.2634 data_time: 0.0091 memory: 5828 grad_norm: 3.0855 loss: 2.7307 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.7307 2023/06/05 01:47:33 - mmengine - INFO - Epoch(train) [50][ 860/2569] lr: 4.0000e-02 eta: 19:08:08 time: 0.2740 data_time: 0.0075 memory: 5828 grad_norm: 3.2409 loss: 2.7821 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.7821 2023/06/05 01:47:38 - mmengine - INFO - Epoch(train) [50][ 880/2569] lr: 4.0000e-02 eta: 19:08:03 time: 0.2627 data_time: 0.0081 memory: 5828 grad_norm: 3.0834 loss: 2.6420 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6420 2023/06/05 01:47:44 - mmengine - INFO - Epoch(train) [50][ 900/2569] lr: 4.0000e-02 eta: 19:07:58 time: 0.2738 data_time: 0.0072 memory: 5828 grad_norm: 3.1093 loss: 2.5027 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5027 2023/06/05 01:47:49 - mmengine - INFO - Epoch(train) [50][ 920/2569] lr: 4.0000e-02 eta: 19:07:53 time: 0.2653 data_time: 0.0077 memory: 5828 grad_norm: 3.0853 loss: 2.7156 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7156 2023/06/05 01:47:54 - mmengine - INFO - Epoch(train) [50][ 940/2569] lr: 4.0000e-02 eta: 19:07:47 time: 0.2622 data_time: 0.0077 memory: 5828 grad_norm: 3.1079 loss: 2.6525 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6525 2023/06/05 01:48:00 - mmengine - INFO - Epoch(train) [50][ 960/2569] lr: 4.0000e-02 eta: 19:07:42 time: 0.2678 data_time: 0.0077 memory: 5828 grad_norm: 3.1434 loss: 2.9407 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9407 2023/06/05 01:48:05 - mmengine - INFO - Epoch(train) [50][ 980/2569] lr: 4.0000e-02 eta: 19:07:37 time: 0.2680 data_time: 0.0075 memory: 5828 grad_norm: 3.1494 loss: 2.5644 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5644 2023/06/05 01:48:10 - mmengine - INFO - Epoch(train) [50][1000/2569] lr: 4.0000e-02 eta: 19:07:31 time: 0.2632 data_time: 0.0079 memory: 5828 grad_norm: 3.1094 loss: 2.7112 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7112 2023/06/05 01:48:16 - mmengine - INFO - Epoch(train) [50][1020/2569] lr: 4.0000e-02 eta: 19:07:26 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 3.0584 loss: 2.7241 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7241 2023/06/05 01:48:21 - mmengine - INFO - Epoch(train) [50][1040/2569] lr: 4.0000e-02 eta: 19:07:20 time: 0.2596 data_time: 0.0081 memory: 5828 grad_norm: 3.1355 loss: 2.4215 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.4215 2023/06/05 01:48:26 - mmengine - INFO - Epoch(train) [50][1060/2569] lr: 4.0000e-02 eta: 19:07:15 time: 0.2655 data_time: 0.0073 memory: 5828 grad_norm: 3.2374 loss: 2.7362 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7362 2023/06/05 01:48:31 - mmengine - INFO - Epoch(train) [50][1080/2569] lr: 4.0000e-02 eta: 19:07:09 time: 0.2649 data_time: 0.0079 memory: 5828 grad_norm: 3.1150 loss: 2.3805 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3805 2023/06/05 01:48:37 - mmengine - INFO - Epoch(train) [50][1100/2569] lr: 4.0000e-02 eta: 19:07:04 time: 0.2727 data_time: 0.0075 memory: 5828 grad_norm: 3.0615 loss: 2.5275 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5275 2023/06/05 01:48:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:48:42 - mmengine - INFO - Epoch(train) [50][1120/2569] lr: 4.0000e-02 eta: 19:06:59 time: 0.2697 data_time: 0.0079 memory: 5828 grad_norm: 3.0885 loss: 2.3781 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3781 2023/06/05 01:48:48 - mmengine - INFO - Epoch(train) [50][1140/2569] lr: 4.0000e-02 eta: 19:06:54 time: 0.2648 data_time: 0.0076 memory: 5828 grad_norm: 3.1367 loss: 2.4895 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4895 2023/06/05 01:48:53 - mmengine - INFO - Epoch(train) [50][1160/2569] lr: 4.0000e-02 eta: 19:06:48 time: 0.2695 data_time: 0.0081 memory: 5828 grad_norm: 3.1231 loss: 2.6326 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6326 2023/06/05 01:48:58 - mmengine - INFO - Epoch(train) [50][1180/2569] lr: 4.0000e-02 eta: 19:06:43 time: 0.2580 data_time: 0.0080 memory: 5828 grad_norm: 3.1634 loss: 2.5068 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5068 2023/06/05 01:49:03 - mmengine - INFO - Epoch(train) [50][1200/2569] lr: 4.0000e-02 eta: 19:06:38 time: 0.2684 data_time: 0.0076 memory: 5828 grad_norm: 3.1086 loss: 2.4926 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4926 2023/06/05 01:49:09 - mmengine - INFO - Epoch(train) [50][1220/2569] lr: 4.0000e-02 eta: 19:06:32 time: 0.2590 data_time: 0.0078 memory: 5828 grad_norm: 3.0969 loss: 2.3564 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3564 2023/06/05 01:49:14 - mmengine - INFO - Epoch(train) [50][1240/2569] lr: 4.0000e-02 eta: 19:06:27 time: 0.2815 data_time: 0.0083 memory: 5828 grad_norm: 3.1459 loss: 2.9063 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.9063 2023/06/05 01:49:20 - mmengine - INFO - Epoch(train) [50][1260/2569] lr: 4.0000e-02 eta: 19:06:22 time: 0.2624 data_time: 0.0077 memory: 5828 grad_norm: 3.0919 loss: 2.8386 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8386 2023/06/05 01:49:25 - mmengine - INFO - Epoch(train) [50][1280/2569] lr: 4.0000e-02 eta: 19:06:16 time: 0.2632 data_time: 0.0077 memory: 5828 grad_norm: 3.1561 loss: 2.7520 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7520 2023/06/05 01:49:30 - mmengine - INFO - Epoch(train) [50][1300/2569] lr: 4.0000e-02 eta: 19:06:11 time: 0.2570 data_time: 0.0080 memory: 5828 grad_norm: 3.1245 loss: 2.3575 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3575 2023/06/05 01:49:35 - mmengine - INFO - Epoch(train) [50][1320/2569] lr: 4.0000e-02 eta: 19:06:05 time: 0.2636 data_time: 0.0077 memory: 5828 grad_norm: 3.0930 loss: 2.6326 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6326 2023/06/05 01:49:40 - mmengine - INFO - Epoch(train) [50][1340/2569] lr: 4.0000e-02 eta: 19:05:59 time: 0.2583 data_time: 0.0076 memory: 5828 grad_norm: 3.1024 loss: 2.7073 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7073 2023/06/05 01:49:46 - mmengine - INFO - Epoch(train) [50][1360/2569] lr: 4.0000e-02 eta: 19:05:54 time: 0.2636 data_time: 0.0097 memory: 5828 grad_norm: 3.1343 loss: 2.4591 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4591 2023/06/05 01:49:51 - mmengine - INFO - Epoch(train) [50][1380/2569] lr: 4.0000e-02 eta: 19:05:49 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 3.0394 loss: 2.6639 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6639 2023/06/05 01:49:56 - mmengine - INFO - Epoch(train) [50][1400/2569] lr: 4.0000e-02 eta: 19:05:43 time: 0.2638 data_time: 0.0078 memory: 5828 grad_norm: 3.0994 loss: 2.5820 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5820 2023/06/05 01:50:02 - mmengine - INFO - Epoch(train) [50][1420/2569] lr: 4.0000e-02 eta: 19:05:38 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 3.1832 loss: 2.2014 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2014 2023/06/05 01:50:07 - mmengine - INFO - Epoch(train) [50][1440/2569] lr: 4.0000e-02 eta: 19:05:32 time: 0.2591 data_time: 0.0079 memory: 5828 grad_norm: 3.0945 loss: 2.5991 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5991 2023/06/05 01:50:12 - mmengine - INFO - Epoch(train) [50][1460/2569] lr: 4.0000e-02 eta: 19:05:27 time: 0.2623 data_time: 0.0076 memory: 5828 grad_norm: 3.0543 loss: 2.5382 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5382 2023/06/05 01:50:17 - mmengine - INFO - Epoch(train) [50][1480/2569] lr: 4.0000e-02 eta: 19:05:21 time: 0.2607 data_time: 0.0077 memory: 5828 grad_norm: 3.1090 loss: 2.3463 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3463 2023/06/05 01:50:22 - mmengine - INFO - Epoch(train) [50][1500/2569] lr: 4.0000e-02 eta: 19:05:16 time: 0.2634 data_time: 0.0080 memory: 5828 grad_norm: 3.1362 loss: 2.5744 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5744 2023/06/05 01:50:28 - mmengine - INFO - Epoch(train) [50][1520/2569] lr: 4.0000e-02 eta: 19:05:10 time: 0.2574 data_time: 0.0082 memory: 5828 grad_norm: 3.1258 loss: 2.5428 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5428 2023/06/05 01:50:33 - mmengine - INFO - Epoch(train) [50][1540/2569] lr: 4.0000e-02 eta: 19:05:04 time: 0.2607 data_time: 0.0077 memory: 5828 grad_norm: 3.1324 loss: 2.6799 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6799 2023/06/05 01:50:38 - mmengine - INFO - Epoch(train) [50][1560/2569] lr: 4.0000e-02 eta: 19:04:59 time: 0.2648 data_time: 0.0076 memory: 5828 grad_norm: 3.1204 loss: 3.0251 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.0251 2023/06/05 01:50:43 - mmengine - INFO - Epoch(train) [50][1580/2569] lr: 4.0000e-02 eta: 19:04:53 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 3.1035 loss: 2.7532 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7532 2023/06/05 01:50:49 - mmengine - INFO - Epoch(train) [50][1600/2569] lr: 4.0000e-02 eta: 19:04:48 time: 0.2743 data_time: 0.0078 memory: 5828 grad_norm: 3.0687 loss: 2.6691 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6691 2023/06/05 01:50:54 - mmengine - INFO - Epoch(train) [50][1620/2569] lr: 4.0000e-02 eta: 19:04:43 time: 0.2603 data_time: 0.0076 memory: 5828 grad_norm: 3.0944 loss: 2.8296 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8296 2023/06/05 01:50:59 - mmengine - INFO - Epoch(train) [50][1640/2569] lr: 4.0000e-02 eta: 19:04:37 time: 0.2598 data_time: 0.0077 memory: 5828 grad_norm: 3.0571 loss: 2.5976 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5976 2023/06/05 01:51:04 - mmengine - INFO - Epoch(train) [50][1660/2569] lr: 4.0000e-02 eta: 19:04:32 time: 0.2595 data_time: 0.0076 memory: 5828 grad_norm: 3.0649 loss: 2.3421 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3421 2023/06/05 01:51:10 - mmengine - INFO - Epoch(train) [50][1680/2569] lr: 4.0000e-02 eta: 19:04:26 time: 0.2646 data_time: 0.0077 memory: 5828 grad_norm: 3.0909 loss: 2.6014 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6014 2023/06/05 01:51:15 - mmengine - INFO - Epoch(train) [50][1700/2569] lr: 4.0000e-02 eta: 19:04:21 time: 0.2601 data_time: 0.0078 memory: 5828 grad_norm: 3.0732 loss: 2.6294 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6294 2023/06/05 01:51:20 - mmengine - INFO - Epoch(train) [50][1720/2569] lr: 4.0000e-02 eta: 19:04:15 time: 0.2608 data_time: 0.0075 memory: 5828 grad_norm: 3.2009 loss: 2.7269 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7269 2023/06/05 01:51:25 - mmengine - INFO - Epoch(train) [50][1740/2569] lr: 4.0000e-02 eta: 19:04:10 time: 0.2625 data_time: 0.0076 memory: 5828 grad_norm: 3.1067 loss: 2.7781 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7781 2023/06/05 01:51:31 - mmengine - INFO - Epoch(train) [50][1760/2569] lr: 4.0000e-02 eta: 19:04:04 time: 0.2633 data_time: 0.0073 memory: 5828 grad_norm: 3.1482 loss: 2.4278 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4278 2023/06/05 01:51:36 - mmengine - INFO - Epoch(train) [50][1780/2569] lr: 4.0000e-02 eta: 19:03:59 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 3.0836 loss: 2.4200 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4200 2023/06/05 01:51:41 - mmengine - INFO - Epoch(train) [50][1800/2569] lr: 4.0000e-02 eta: 19:03:53 time: 0.2657 data_time: 0.0080 memory: 5828 grad_norm: 3.0820 loss: 2.4161 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4161 2023/06/05 01:51:47 - mmengine - INFO - Epoch(train) [50][1820/2569] lr: 4.0000e-02 eta: 19:03:48 time: 0.2680 data_time: 0.0074 memory: 5828 grad_norm: 3.0815 loss: 2.4047 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4047 2023/06/05 01:51:52 - mmengine - INFO - Epoch(train) [50][1840/2569] lr: 4.0000e-02 eta: 19:03:43 time: 0.2661 data_time: 0.0077 memory: 5828 grad_norm: 3.1008 loss: 2.6268 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6268 2023/06/05 01:51:57 - mmengine - INFO - Epoch(train) [50][1860/2569] lr: 4.0000e-02 eta: 19:03:37 time: 0.2582 data_time: 0.0075 memory: 5828 grad_norm: 3.0934 loss: 2.6149 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6149 2023/06/05 01:52:02 - mmengine - INFO - Epoch(train) [50][1880/2569] lr: 4.0000e-02 eta: 19:03:31 time: 0.2586 data_time: 0.0076 memory: 5828 grad_norm: 3.0590 loss: 2.4720 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4720 2023/06/05 01:52:07 - mmengine - INFO - Epoch(train) [50][1900/2569] lr: 4.0000e-02 eta: 19:03:26 time: 0.2596 data_time: 0.0078 memory: 5828 grad_norm: 3.0004 loss: 2.5618 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5618 2023/06/05 01:52:13 - mmengine - INFO - Epoch(train) [50][1920/2569] lr: 4.0000e-02 eta: 19:03:21 time: 0.2692 data_time: 0.0074 memory: 5828 grad_norm: 3.1267 loss: 2.3796 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3796 2023/06/05 01:52:18 - mmengine - INFO - Epoch(train) [50][1940/2569] lr: 4.0000e-02 eta: 19:03:15 time: 0.2577 data_time: 0.0077 memory: 5828 grad_norm: 3.1864 loss: 2.3562 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3562 2023/06/05 01:52:23 - mmengine - INFO - Epoch(train) [50][1960/2569] lr: 4.0000e-02 eta: 19:03:09 time: 0.2647 data_time: 0.0081 memory: 5828 grad_norm: 3.2055 loss: 2.4060 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4060 2023/06/05 01:52:29 - mmengine - INFO - Epoch(train) [50][1980/2569] lr: 4.0000e-02 eta: 19:03:04 time: 0.2636 data_time: 0.0095 memory: 5828 grad_norm: 3.1160 loss: 2.5555 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5555 2023/06/05 01:52:34 - mmengine - INFO - Epoch(train) [50][2000/2569] lr: 4.0000e-02 eta: 19:02:59 time: 0.2631 data_time: 0.0081 memory: 5828 grad_norm: 3.0472 loss: 2.5928 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5928 2023/06/05 01:52:39 - mmengine - INFO - Epoch(train) [50][2020/2569] lr: 4.0000e-02 eta: 19:02:53 time: 0.2590 data_time: 0.0078 memory: 5828 grad_norm: 3.1368 loss: 2.4370 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4370 2023/06/05 01:52:45 - mmengine - INFO - Epoch(train) [50][2040/2569] lr: 4.0000e-02 eta: 19:02:48 time: 0.2820 data_time: 0.0074 memory: 5828 grad_norm: 3.0719 loss: 2.2165 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2165 2023/06/05 01:52:50 - mmengine - INFO - Epoch(train) [50][2060/2569] lr: 4.0000e-02 eta: 19:02:43 time: 0.2640 data_time: 0.0078 memory: 5828 grad_norm: 3.1133 loss: 2.6700 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6700 2023/06/05 01:52:55 - mmengine - INFO - Epoch(train) [50][2080/2569] lr: 4.0000e-02 eta: 19:02:37 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 3.1276 loss: 2.6173 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.6173 2023/06/05 01:53:01 - mmengine - INFO - Epoch(train) [50][2100/2569] lr: 4.0000e-02 eta: 19:02:32 time: 0.2665 data_time: 0.0076 memory: 5828 grad_norm: 3.0845 loss: 2.4896 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4896 2023/06/05 01:53:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:53:06 - mmengine - INFO - Epoch(train) [50][2120/2569] lr: 4.0000e-02 eta: 19:02:27 time: 0.2675 data_time: 0.0079 memory: 5828 grad_norm: 3.1348 loss: 2.7716 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7716 2023/06/05 01:53:11 - mmengine - INFO - Epoch(train) [50][2140/2569] lr: 4.0000e-02 eta: 19:02:21 time: 0.2634 data_time: 0.0082 memory: 5828 grad_norm: 3.0832 loss: 2.4817 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4817 2023/06/05 01:53:17 - mmengine - INFO - Epoch(train) [50][2160/2569] lr: 4.0000e-02 eta: 19:02:17 time: 0.2794 data_time: 0.0076 memory: 5828 grad_norm: 3.1605 loss: 2.4252 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4252 2023/06/05 01:53:22 - mmengine - INFO - Epoch(train) [50][2180/2569] lr: 4.0000e-02 eta: 19:02:11 time: 0.2571 data_time: 0.0075 memory: 5828 grad_norm: 3.1216 loss: 2.4927 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4927 2023/06/05 01:53:27 - mmengine - INFO - Epoch(train) [50][2200/2569] lr: 4.0000e-02 eta: 19:02:05 time: 0.2570 data_time: 0.0076 memory: 5828 grad_norm: 3.0846 loss: 2.2517 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2517 2023/06/05 01:53:32 - mmengine - INFO - Epoch(train) [50][2220/2569] lr: 4.0000e-02 eta: 19:02:00 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 3.1059 loss: 2.9698 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9698 2023/06/05 01:53:38 - mmengine - INFO - Epoch(train) [50][2240/2569] lr: 4.0000e-02 eta: 19:01:54 time: 0.2629 data_time: 0.0077 memory: 5828 grad_norm: 3.0437 loss: 2.4449 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4449 2023/06/05 01:53:43 - mmengine - INFO - Epoch(train) [50][2260/2569] lr: 4.0000e-02 eta: 19:01:48 time: 0.2585 data_time: 0.0079 memory: 5828 grad_norm: 3.1160 loss: 2.6850 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6850 2023/06/05 01:53:48 - mmengine - INFO - Epoch(train) [50][2280/2569] lr: 4.0000e-02 eta: 19:01:43 time: 0.2680 data_time: 0.0076 memory: 5828 grad_norm: 3.0869 loss: 2.4523 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4523 2023/06/05 01:53:53 - mmengine - INFO - Epoch(train) [50][2300/2569] lr: 4.0000e-02 eta: 19:01:38 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.1082 loss: 2.7962 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7962 2023/06/05 01:53:59 - mmengine - INFO - Epoch(train) [50][2320/2569] lr: 4.0000e-02 eta: 19:01:33 time: 0.2742 data_time: 0.0076 memory: 5828 grad_norm: 3.0474 loss: 2.7496 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7496 2023/06/05 01:54:04 - mmengine - INFO - Epoch(train) [50][2340/2569] lr: 4.0000e-02 eta: 19:01:27 time: 0.2595 data_time: 0.0088 memory: 5828 grad_norm: 3.1284 loss: 2.4502 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4502 2023/06/05 01:54:09 - mmengine - INFO - Epoch(train) [50][2360/2569] lr: 4.0000e-02 eta: 19:01:22 time: 0.2644 data_time: 0.0076 memory: 5828 grad_norm: 3.0971 loss: 2.4622 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4622 2023/06/05 01:54:15 - mmengine - INFO - Epoch(train) [50][2380/2569] lr: 4.0000e-02 eta: 19:01:17 time: 0.2718 data_time: 0.0074 memory: 5828 grad_norm: 3.1396 loss: 2.7510 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7510 2023/06/05 01:54:20 - mmengine - INFO - Epoch(train) [50][2400/2569] lr: 4.0000e-02 eta: 19:01:11 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 3.1212 loss: 2.6703 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6703 2023/06/05 01:54:25 - mmengine - INFO - Epoch(train) [50][2420/2569] lr: 4.0000e-02 eta: 19:01:06 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 3.0673 loss: 2.8893 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8893 2023/06/05 01:54:31 - mmengine - INFO - Epoch(train) [50][2440/2569] lr: 4.0000e-02 eta: 19:01:00 time: 0.2587 data_time: 0.0079 memory: 5828 grad_norm: 3.0718 loss: 2.3688 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3688 2023/06/05 01:54:36 - mmengine - INFO - Epoch(train) [50][2460/2569] lr: 4.0000e-02 eta: 19:00:55 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 3.1215 loss: 2.5582 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5582 2023/06/05 01:54:41 - mmengine - INFO - Epoch(train) [50][2480/2569] lr: 4.0000e-02 eta: 19:00:50 time: 0.2632 data_time: 0.0083 memory: 5828 grad_norm: 3.0987 loss: 2.6214 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6214 2023/06/05 01:54:47 - mmengine - INFO - Epoch(train) [50][2500/2569] lr: 4.0000e-02 eta: 19:00:44 time: 0.2658 data_time: 0.0080 memory: 5828 grad_norm: 3.1126 loss: 2.7601 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7601 2023/06/05 01:54:52 - mmengine - INFO - Epoch(train) [50][2520/2569] lr: 4.0000e-02 eta: 19:00:39 time: 0.2646 data_time: 0.0083 memory: 5828 grad_norm: 3.0463 loss: 2.6917 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6917 2023/06/05 01:54:57 - mmengine - INFO - Epoch(train) [50][2540/2569] lr: 4.0000e-02 eta: 19:00:33 time: 0.2652 data_time: 0.0080 memory: 5828 grad_norm: 3.0628 loss: 2.8194 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8194 2023/06/05 01:55:02 - mmengine - INFO - Epoch(train) [50][2560/2569] lr: 4.0000e-02 eta: 19:00:28 time: 0.2553 data_time: 0.0081 memory: 5828 grad_norm: 3.1462 loss: 2.6434 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6434 2023/06/05 01:55:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:55:05 - mmengine - INFO - Epoch(train) [50][2569/2569] lr: 4.0000e-02 eta: 19:00:25 time: 0.2499 data_time: 0.0078 memory: 5828 grad_norm: 3.1340 loss: 2.5616 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.5616 2023/06/05 01:55:08 - mmengine - INFO - Epoch(val) [50][ 20/260] eta: 0:00:43 time: 0.1826 data_time: 0.1230 memory: 1238 2023/06/05 01:55:11 - mmengine - INFO - Epoch(val) [50][ 40/260] eta: 0:00:36 time: 0.1464 data_time: 0.0876 memory: 1238 2023/06/05 01:55:14 - mmengine - INFO - Epoch(val) [50][ 60/260] eta: 0:00:32 time: 0.1556 data_time: 0.0969 memory: 1238 2023/06/05 01:55:17 - mmengine - INFO - Epoch(val) [50][ 80/260] eta: 0:00:27 time: 0.1160 data_time: 0.0573 memory: 1238 2023/06/05 01:55:20 - mmengine - INFO - Epoch(val) [50][100/260] eta: 0:00:23 time: 0.1477 data_time: 0.0891 memory: 1238 2023/06/05 01:55:22 - mmengine - INFO - Epoch(val) [50][120/260] eta: 0:00:20 time: 0.1328 data_time: 0.0748 memory: 1238 2023/06/05 01:55:25 - mmengine - INFO - Epoch(val) [50][140/260] eta: 0:00:17 time: 0.1271 data_time: 0.0688 memory: 1238 2023/06/05 01:55:28 - mmengine - INFO - Epoch(val) [50][160/260] eta: 0:00:14 time: 0.1397 data_time: 0.0814 memory: 1238 2023/06/05 01:55:31 - mmengine - INFO - Epoch(val) [50][180/260] eta: 0:00:11 time: 0.1583 data_time: 0.0993 memory: 1238 2023/06/05 01:55:33 - mmengine - INFO - Epoch(val) [50][200/260] eta: 0:00:08 time: 0.1252 data_time: 0.0670 memory: 1238 2023/06/05 01:55:36 - mmengine - INFO - Epoch(val) [50][220/260] eta: 0:00:05 time: 0.1424 data_time: 0.0838 memory: 1238 2023/06/05 01:55:39 - mmengine - INFO - Epoch(val) [50][240/260] eta: 0:00:02 time: 0.1293 data_time: 0.0710 memory: 1238 2023/06/05 01:55:41 - mmengine - INFO - Epoch(val) [50][260/260] eta: 0:00:00 time: 0.1283 data_time: 0.0717 memory: 1238 2023/06/05 01:55:49 - mmengine - INFO - Epoch(val) [50][260/260] acc/top1: 0.4916 acc/top5: 0.7346 acc/mean1: 0.4822 data_time: 0.0821 time: 0.1405 2023/06/05 01:55:56 - mmengine - INFO - Epoch(train) [51][ 20/2569] lr: 4.0000e-02 eta: 19:00:22 time: 0.3352 data_time: 0.0646 memory: 5828 grad_norm: 3.0668 loss: 2.2715 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2715 2023/06/05 01:56:01 - mmengine - INFO - Epoch(train) [51][ 40/2569] lr: 4.0000e-02 eta: 19:00:17 time: 0.2596 data_time: 0.0078 memory: 5828 grad_norm: 3.0359 loss: 2.1354 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1354 2023/06/05 01:56:06 - mmengine - INFO - Epoch(train) [51][ 60/2569] lr: 4.0000e-02 eta: 19:00:11 time: 0.2606 data_time: 0.0077 memory: 5828 grad_norm: 3.1277 loss: 2.3655 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3655 2023/06/05 01:56:12 - mmengine - INFO - Epoch(train) [51][ 80/2569] lr: 4.0000e-02 eta: 19:00:06 time: 0.2654 data_time: 0.0074 memory: 5828 grad_norm: 3.0671 loss: 2.7090 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7090 2023/06/05 01:56:17 - mmengine - INFO - Epoch(train) [51][ 100/2569] lr: 4.0000e-02 eta: 19:00:01 time: 0.2672 data_time: 0.0076 memory: 5828 grad_norm: 3.1194 loss: 2.4694 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4694 2023/06/05 01:56:22 - mmengine - INFO - Epoch(train) [51][ 120/2569] lr: 4.0000e-02 eta: 18:59:56 time: 0.2741 data_time: 0.0079 memory: 5828 grad_norm: 3.1477 loss: 2.3544 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3544 2023/06/05 01:56:28 - mmengine - INFO - Epoch(train) [51][ 140/2569] lr: 4.0000e-02 eta: 18:59:50 time: 0.2682 data_time: 0.0078 memory: 5828 grad_norm: 3.0823 loss: 2.7426 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7426 2023/06/05 01:56:33 - mmengine - INFO - Epoch(train) [51][ 160/2569] lr: 4.0000e-02 eta: 18:59:45 time: 0.2631 data_time: 0.0079 memory: 5828 grad_norm: 3.1002 loss: 2.5612 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5612 2023/06/05 01:56:38 - mmengine - INFO - Epoch(train) [51][ 180/2569] lr: 4.0000e-02 eta: 18:59:39 time: 0.2664 data_time: 0.0076 memory: 5828 grad_norm: 3.0780 loss: 2.4450 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4450 2023/06/05 01:56:43 - mmengine - INFO - Epoch(train) [51][ 200/2569] lr: 4.0000e-02 eta: 18:59:34 time: 0.2574 data_time: 0.0076 memory: 5828 grad_norm: 3.0297 loss: 2.5518 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5518 2023/06/05 01:56:49 - mmengine - INFO - Epoch(train) [51][ 220/2569] lr: 4.0000e-02 eta: 18:59:28 time: 0.2609 data_time: 0.0073 memory: 5828 grad_norm: 3.1031 loss: 2.3484 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3484 2023/06/05 01:56:54 - mmengine - INFO - Epoch(train) [51][ 240/2569] lr: 4.0000e-02 eta: 18:59:23 time: 0.2747 data_time: 0.0074 memory: 5828 grad_norm: 3.1043 loss: 2.4001 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4001 2023/06/05 01:56:59 - mmengine - INFO - Epoch(train) [51][ 260/2569] lr: 4.0000e-02 eta: 18:59:18 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 3.0794 loss: 2.7607 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7607 2023/06/05 01:57:05 - mmengine - INFO - Epoch(train) [51][ 280/2569] lr: 4.0000e-02 eta: 18:59:12 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 3.1193 loss: 2.3032 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3032 2023/06/05 01:57:10 - mmengine - INFO - Epoch(train) [51][ 300/2569] lr: 4.0000e-02 eta: 18:59:07 time: 0.2683 data_time: 0.0079 memory: 5828 grad_norm: 3.1025 loss: 2.5418 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5418 2023/06/05 01:57:15 - mmengine - INFO - Epoch(train) [51][ 320/2569] lr: 4.0000e-02 eta: 18:59:02 time: 0.2611 data_time: 0.0078 memory: 5828 grad_norm: 3.0812 loss: 2.4617 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4617 2023/06/05 01:57:21 - mmengine - INFO - Epoch(train) [51][ 340/2569] lr: 4.0000e-02 eta: 18:58:56 time: 0.2598 data_time: 0.0078 memory: 5828 grad_norm: 3.1268 loss: 2.5244 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5244 2023/06/05 01:57:26 - mmengine - INFO - Epoch(train) [51][ 360/2569] lr: 4.0000e-02 eta: 18:58:50 time: 0.2600 data_time: 0.0082 memory: 5828 grad_norm: 3.1062 loss: 2.5828 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5828 2023/06/05 01:57:31 - mmengine - INFO - Epoch(train) [51][ 380/2569] lr: 4.0000e-02 eta: 18:58:45 time: 0.2585 data_time: 0.0082 memory: 5828 grad_norm: 3.0964 loss: 2.4644 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4644 2023/06/05 01:57:36 - mmengine - INFO - Epoch(train) [51][ 400/2569] lr: 4.0000e-02 eta: 18:58:40 time: 0.2747 data_time: 0.0077 memory: 5828 grad_norm: 3.1407 loss: 2.9350 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.9350 2023/06/05 01:57:42 - mmengine - INFO - Epoch(train) [51][ 420/2569] lr: 4.0000e-02 eta: 18:58:34 time: 0.2642 data_time: 0.0078 memory: 5828 grad_norm: 3.0898 loss: 2.5029 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5029 2023/06/05 01:57:47 - mmengine - INFO - Epoch(train) [51][ 440/2569] lr: 4.0000e-02 eta: 18:58:29 time: 0.2626 data_time: 0.0078 memory: 5828 grad_norm: 3.0626 loss: 2.6545 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6545 2023/06/05 01:57:52 - mmengine - INFO - Epoch(train) [51][ 460/2569] lr: 4.0000e-02 eta: 18:58:24 time: 0.2717 data_time: 0.0075 memory: 5828 grad_norm: 3.0922 loss: 2.5437 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5437 2023/06/05 01:57:58 - mmengine - INFO - Epoch(train) [51][ 480/2569] lr: 4.0000e-02 eta: 18:58:18 time: 0.2587 data_time: 0.0074 memory: 5828 grad_norm: 3.0910 loss: 2.4553 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4553 2023/06/05 01:58:03 - mmengine - INFO - Epoch(train) [51][ 500/2569] lr: 4.0000e-02 eta: 18:58:13 time: 0.2630 data_time: 0.0071 memory: 5828 grad_norm: 3.1379 loss: 2.6044 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6044 2023/06/05 01:58:08 - mmengine - INFO - Epoch(train) [51][ 520/2569] lr: 4.0000e-02 eta: 18:58:07 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 3.1577 loss: 2.3508 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3508 2023/06/05 01:58:13 - mmengine - INFO - Epoch(train) [51][ 540/2569] lr: 4.0000e-02 eta: 18:58:02 time: 0.2580 data_time: 0.0076 memory: 5828 grad_norm: 3.1486 loss: 2.1864 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1864 2023/06/05 01:58:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 01:58:19 - mmengine - INFO - Epoch(train) [51][ 560/2569] lr: 4.0000e-02 eta: 18:57:56 time: 0.2671 data_time: 0.0078 memory: 5828 grad_norm: 3.0818 loss: 2.4776 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4776 2023/06/05 01:58:24 - mmengine - INFO - Epoch(train) [51][ 580/2569] lr: 4.0000e-02 eta: 18:57:51 time: 0.2675 data_time: 0.0079 memory: 5828 grad_norm: 3.1225 loss: 2.3483 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3483 2023/06/05 01:58:30 - mmengine - INFO - Epoch(train) [51][ 600/2569] lr: 4.0000e-02 eta: 18:57:46 time: 0.2736 data_time: 0.0075 memory: 5828 grad_norm: 3.1084 loss: 2.4305 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4305 2023/06/05 01:58:35 - mmengine - INFO - Epoch(train) [51][ 620/2569] lr: 4.0000e-02 eta: 18:57:41 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 3.0973 loss: 2.3624 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3624 2023/06/05 01:58:40 - mmengine - INFO - Epoch(train) [51][ 640/2569] lr: 4.0000e-02 eta: 18:57:36 time: 0.2744 data_time: 0.0082 memory: 5828 grad_norm: 3.0549 loss: 2.4932 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4932 2023/06/05 01:58:46 - mmengine - INFO - Epoch(train) [51][ 660/2569] lr: 4.0000e-02 eta: 18:57:30 time: 0.2623 data_time: 0.0080 memory: 5828 grad_norm: 3.0848 loss: 2.7814 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7814 2023/06/05 01:58:51 - mmengine - INFO - Epoch(train) [51][ 680/2569] lr: 4.0000e-02 eta: 18:57:25 time: 0.2726 data_time: 0.0075 memory: 5828 grad_norm: 3.0683 loss: 2.7585 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7585 2023/06/05 01:58:56 - mmengine - INFO - Epoch(train) [51][ 700/2569] lr: 4.0000e-02 eta: 18:57:20 time: 0.2727 data_time: 0.0079 memory: 5828 grad_norm: 3.0701 loss: 2.2261 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2261 2023/06/05 01:59:02 - mmengine - INFO - Epoch(train) [51][ 720/2569] lr: 4.0000e-02 eta: 18:57:14 time: 0.2634 data_time: 0.0076 memory: 5828 grad_norm: 3.1203 loss: 2.5215 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5215 2023/06/05 01:59:07 - mmengine - INFO - Epoch(train) [51][ 740/2569] lr: 4.0000e-02 eta: 18:57:09 time: 0.2724 data_time: 0.0073 memory: 5828 grad_norm: 3.0968 loss: 2.3030 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3030 2023/06/05 01:59:13 - mmengine - INFO - Epoch(train) [51][ 760/2569] lr: 4.0000e-02 eta: 18:57:04 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 3.1019 loss: 2.5350 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5350 2023/06/05 01:59:18 - mmengine - INFO - Epoch(train) [51][ 780/2569] lr: 4.0000e-02 eta: 18:56:59 time: 0.2673 data_time: 0.0077 memory: 5828 grad_norm: 3.0565 loss: 2.2044 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2044 2023/06/05 01:59:23 - mmengine - INFO - Epoch(train) [51][ 800/2569] lr: 4.0000e-02 eta: 18:56:54 time: 0.2747 data_time: 0.0077 memory: 5828 grad_norm: 3.1345 loss: 2.6005 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6005 2023/06/05 01:59:29 - mmengine - INFO - Epoch(train) [51][ 820/2569] lr: 4.0000e-02 eta: 18:56:48 time: 0.2578 data_time: 0.0082 memory: 5828 grad_norm: 3.1418 loss: 2.4280 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4280 2023/06/05 01:59:34 - mmengine - INFO - Epoch(train) [51][ 840/2569] lr: 4.0000e-02 eta: 18:56:43 time: 0.2704 data_time: 0.0080 memory: 5828 grad_norm: 3.0809 loss: 2.9361 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9361 2023/06/05 01:59:39 - mmengine - INFO - Epoch(train) [51][ 860/2569] lr: 4.0000e-02 eta: 18:56:38 time: 0.2632 data_time: 0.0083 memory: 5828 grad_norm: 3.0907 loss: 2.6143 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6143 2023/06/05 01:59:44 - mmengine - INFO - Epoch(train) [51][ 880/2569] lr: 4.0000e-02 eta: 18:56:32 time: 0.2635 data_time: 0.0075 memory: 5828 grad_norm: 3.1843 loss: 2.8322 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8322 2023/06/05 01:59:50 - mmengine - INFO - Epoch(train) [51][ 900/2569] lr: 4.0000e-02 eta: 18:56:26 time: 0.2590 data_time: 0.0078 memory: 5828 grad_norm: 3.1275 loss: 2.3785 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3785 2023/06/05 01:59:55 - mmengine - INFO - Epoch(train) [51][ 920/2569] lr: 4.0000e-02 eta: 18:56:21 time: 0.2675 data_time: 0.0071 memory: 5828 grad_norm: 3.1041 loss: 2.3145 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3145 2023/06/05 02:00:00 - mmengine - INFO - Epoch(train) [51][ 940/2569] lr: 4.0000e-02 eta: 18:56:16 time: 0.2600 data_time: 0.0075 memory: 5828 grad_norm: 3.1742 loss: 2.6415 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6415 2023/06/05 02:00:05 - mmengine - INFO - Epoch(train) [51][ 960/2569] lr: 4.0000e-02 eta: 18:56:10 time: 0.2597 data_time: 0.0076 memory: 5828 grad_norm: 3.0895 loss: 2.5226 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5226 2023/06/05 02:00:11 - mmengine - INFO - Epoch(train) [51][ 980/2569] lr: 4.0000e-02 eta: 18:56:05 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 3.1279 loss: 2.7019 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7019 2023/06/05 02:00:16 - mmengine - INFO - Epoch(train) [51][1000/2569] lr: 4.0000e-02 eta: 18:55:59 time: 0.2590 data_time: 0.0076 memory: 5828 grad_norm: 3.0981 loss: 2.5620 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5620 2023/06/05 02:00:21 - mmengine - INFO - Epoch(train) [51][1020/2569] lr: 4.0000e-02 eta: 18:55:54 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 2.9989 loss: 2.3780 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3780 2023/06/05 02:00:27 - mmengine - INFO - Epoch(train) [51][1040/2569] lr: 4.0000e-02 eta: 18:55:48 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 3.0593 loss: 2.5318 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5318 2023/06/05 02:00:32 - mmengine - INFO - Epoch(train) [51][1060/2569] lr: 4.0000e-02 eta: 18:55:43 time: 0.2580 data_time: 0.0081 memory: 5828 grad_norm: 3.1364 loss: 2.5280 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5280 2023/06/05 02:00:37 - mmengine - INFO - Epoch(train) [51][1080/2569] lr: 4.0000e-02 eta: 18:55:37 time: 0.2638 data_time: 0.0078 memory: 5828 grad_norm: 3.0375 loss: 2.6079 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6079 2023/06/05 02:00:42 - mmengine - INFO - Epoch(train) [51][1100/2569] lr: 4.0000e-02 eta: 18:55:32 time: 0.2564 data_time: 0.0078 memory: 5828 grad_norm: 3.0827 loss: 2.5453 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5453 2023/06/05 02:00:47 - mmengine - INFO - Epoch(train) [51][1120/2569] lr: 4.0000e-02 eta: 18:55:26 time: 0.2573 data_time: 0.0080 memory: 5828 grad_norm: 3.1588 loss: 2.4235 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4235 2023/06/05 02:00:53 - mmengine - INFO - Epoch(train) [51][1140/2569] lr: 4.0000e-02 eta: 18:55:21 time: 0.2692 data_time: 0.0078 memory: 5828 grad_norm: 3.0886 loss: 2.1860 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.1860 2023/06/05 02:00:58 - mmengine - INFO - Epoch(train) [51][1160/2569] lr: 4.0000e-02 eta: 18:55:15 time: 0.2632 data_time: 0.0081 memory: 5828 grad_norm: 3.1630 loss: 2.7146 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7146 2023/06/05 02:01:03 - mmengine - INFO - Epoch(train) [51][1180/2569] lr: 4.0000e-02 eta: 18:55:10 time: 0.2619 data_time: 0.0077 memory: 5828 grad_norm: 3.1400 loss: 2.7781 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7781 2023/06/05 02:01:08 - mmengine - INFO - Epoch(train) [51][1200/2569] lr: 4.0000e-02 eta: 18:55:04 time: 0.2572 data_time: 0.0081 memory: 5828 grad_norm: 3.0672 loss: 2.3837 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3837 2023/06/05 02:01:14 - mmengine - INFO - Epoch(train) [51][1220/2569] lr: 4.0000e-02 eta: 18:54:59 time: 0.2710 data_time: 0.0089 memory: 5828 grad_norm: 3.1169 loss: 2.7376 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7376 2023/06/05 02:01:19 - mmengine - INFO - Epoch(train) [51][1240/2569] lr: 4.0000e-02 eta: 18:54:53 time: 0.2630 data_time: 0.0076 memory: 5828 grad_norm: 3.1206 loss: 2.6030 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6030 2023/06/05 02:01:24 - mmengine - INFO - Epoch(train) [51][1260/2569] lr: 4.0000e-02 eta: 18:54:48 time: 0.2581 data_time: 0.0093 memory: 5828 grad_norm: 3.0765 loss: 2.7253 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7253 2023/06/05 02:01:29 - mmengine - INFO - Epoch(train) [51][1280/2569] lr: 4.0000e-02 eta: 18:54:42 time: 0.2573 data_time: 0.0077 memory: 5828 grad_norm: 3.1558 loss: 2.4393 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4393 2023/06/05 02:01:35 - mmengine - INFO - Epoch(train) [51][1300/2569] lr: 4.0000e-02 eta: 18:54:37 time: 0.2638 data_time: 0.0075 memory: 5828 grad_norm: 3.1547 loss: 2.2802 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2802 2023/06/05 02:01:40 - mmengine - INFO - Epoch(train) [51][1320/2569] lr: 4.0000e-02 eta: 18:54:31 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 3.1937 loss: 2.3112 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3112 2023/06/05 02:01:45 - mmengine - INFO - Epoch(train) [51][1340/2569] lr: 4.0000e-02 eta: 18:54:26 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 3.1605 loss: 2.7828 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7828 2023/06/05 02:01:51 - mmengine - INFO - Epoch(train) [51][1360/2569] lr: 4.0000e-02 eta: 18:54:20 time: 0.2631 data_time: 0.0081 memory: 5828 grad_norm: 3.0928 loss: 2.5383 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5383 2023/06/05 02:01:56 - mmengine - INFO - Epoch(train) [51][1380/2569] lr: 4.0000e-02 eta: 18:54:15 time: 0.2699 data_time: 0.0075 memory: 5828 grad_norm: 3.0608 loss: 2.5234 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5234 2023/06/05 02:02:01 - mmengine - INFO - Epoch(train) [51][1400/2569] lr: 4.0000e-02 eta: 18:54:10 time: 0.2711 data_time: 0.0081 memory: 5828 grad_norm: 3.1455 loss: 2.7969 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.7969 2023/06/05 02:02:07 - mmengine - INFO - Epoch(train) [51][1420/2569] lr: 4.0000e-02 eta: 18:54:05 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 3.1992 loss: 2.6741 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6741 2023/06/05 02:02:12 - mmengine - INFO - Epoch(train) [51][1440/2569] lr: 4.0000e-02 eta: 18:53:59 time: 0.2578 data_time: 0.0075 memory: 5828 grad_norm: 3.0771 loss: 2.4365 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4365 2023/06/05 02:02:17 - mmengine - INFO - Epoch(train) [51][1460/2569] lr: 4.0000e-02 eta: 18:53:54 time: 0.2703 data_time: 0.0078 memory: 5828 grad_norm: 3.1373 loss: 2.5598 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5598 2023/06/05 02:02:22 - mmengine - INFO - Epoch(train) [51][1480/2569] lr: 4.0000e-02 eta: 18:53:48 time: 0.2566 data_time: 0.0078 memory: 5828 grad_norm: 3.0687 loss: 2.5726 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5726 2023/06/05 02:02:28 - mmengine - INFO - Epoch(train) [51][1500/2569] lr: 4.0000e-02 eta: 18:53:43 time: 0.2659 data_time: 0.0077 memory: 5828 grad_norm: 3.2210 loss: 2.5690 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5690 2023/06/05 02:02:33 - mmengine - INFO - Epoch(train) [51][1520/2569] lr: 4.0000e-02 eta: 18:53:38 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.1251 loss: 2.3813 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3813 2023/06/05 02:02:38 - mmengine - INFO - Epoch(train) [51][1540/2569] lr: 4.0000e-02 eta: 18:53:32 time: 0.2595 data_time: 0.0072 memory: 5828 grad_norm: 3.1391 loss: 2.6826 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6826 2023/06/05 02:02:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:02:44 - mmengine - INFO - Epoch(train) [51][1560/2569] lr: 4.0000e-02 eta: 18:53:27 time: 0.2634 data_time: 0.0081 memory: 5828 grad_norm: 3.0532 loss: 2.5757 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5757 2023/06/05 02:02:49 - mmengine - INFO - Epoch(train) [51][1580/2569] lr: 4.0000e-02 eta: 18:53:21 time: 0.2603 data_time: 0.0076 memory: 5828 grad_norm: 3.0507 loss: 2.2054 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2054 2023/06/05 02:02:54 - mmengine - INFO - Epoch(train) [51][1600/2569] lr: 4.0000e-02 eta: 18:53:16 time: 0.2643 data_time: 0.0081 memory: 5828 grad_norm: 3.1109 loss: 2.5989 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5989 2023/06/05 02:02:59 - mmengine - INFO - Epoch(train) [51][1620/2569] lr: 4.0000e-02 eta: 18:53:10 time: 0.2596 data_time: 0.0075 memory: 5828 grad_norm: 3.1323 loss: 2.2433 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2433 2023/06/05 02:03:04 - mmengine - INFO - Epoch(train) [51][1640/2569] lr: 4.0000e-02 eta: 18:53:04 time: 0.2600 data_time: 0.0077 memory: 5828 grad_norm: 3.0544 loss: 2.4511 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4511 2023/06/05 02:03:10 - mmengine - INFO - Epoch(train) [51][1660/2569] lr: 4.0000e-02 eta: 18:52:59 time: 0.2733 data_time: 0.0076 memory: 5828 grad_norm: 3.1439 loss: 2.6588 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6588 2023/06/05 02:03:15 - mmengine - INFO - Epoch(train) [51][1680/2569] lr: 4.0000e-02 eta: 18:52:54 time: 0.2686 data_time: 0.0078 memory: 5828 grad_norm: 3.1132 loss: 2.5611 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5611 2023/06/05 02:03:21 - mmengine - INFO - Epoch(train) [51][1700/2569] lr: 4.0000e-02 eta: 18:52:49 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 3.1434 loss: 2.3059 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3059 2023/06/05 02:03:26 - mmengine - INFO - Epoch(train) [51][1720/2569] lr: 4.0000e-02 eta: 18:52:43 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 3.1068 loss: 2.5300 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5300 2023/06/05 02:03:31 - mmengine - INFO - Epoch(train) [51][1740/2569] lr: 4.0000e-02 eta: 18:52:38 time: 0.2603 data_time: 0.0076 memory: 5828 grad_norm: 3.1088 loss: 2.8411 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8411 2023/06/05 02:03:36 - mmengine - INFO - Epoch(train) [51][1760/2569] lr: 4.0000e-02 eta: 18:52:32 time: 0.2571 data_time: 0.0074 memory: 5828 grad_norm: 3.1366 loss: 2.4467 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4467 2023/06/05 02:03:41 - mmengine - INFO - Epoch(train) [51][1780/2569] lr: 4.0000e-02 eta: 18:52:26 time: 0.2582 data_time: 0.0075 memory: 5828 grad_norm: 3.0880 loss: 2.5948 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5948 2023/06/05 02:03:47 - mmengine - INFO - Epoch(train) [51][1800/2569] lr: 4.0000e-02 eta: 18:52:21 time: 0.2570 data_time: 0.0077 memory: 5828 grad_norm: 3.1087 loss: 2.8375 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8375 2023/06/05 02:03:52 - mmengine - INFO - Epoch(train) [51][1820/2569] lr: 4.0000e-02 eta: 18:52:15 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 3.0626 loss: 2.6056 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6056 2023/06/05 02:03:57 - mmengine - INFO - Epoch(train) [51][1840/2569] lr: 4.0000e-02 eta: 18:52:10 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 3.1029 loss: 2.6494 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6494 2023/06/05 02:04:02 - mmengine - INFO - Epoch(train) [51][1860/2569] lr: 4.0000e-02 eta: 18:52:04 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 3.1236 loss: 2.6308 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6308 2023/06/05 02:04:08 - mmengine - INFO - Epoch(train) [51][1880/2569] lr: 4.0000e-02 eta: 18:51:59 time: 0.2599 data_time: 0.0077 memory: 5828 grad_norm: 3.1072 loss: 2.6287 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6287 2023/06/05 02:04:13 - mmengine - INFO - Epoch(train) [51][1900/2569] lr: 4.0000e-02 eta: 18:51:54 time: 0.2724 data_time: 0.0073 memory: 5828 grad_norm: 3.1199 loss: 2.5859 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5859 2023/06/05 02:04:18 - mmengine - INFO - Epoch(train) [51][1920/2569] lr: 4.0000e-02 eta: 18:51:49 time: 0.2721 data_time: 0.0074 memory: 5828 grad_norm: 3.0743 loss: 2.4081 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4081 2023/06/05 02:04:24 - mmengine - INFO - Epoch(train) [51][1940/2569] lr: 4.0000e-02 eta: 18:51:43 time: 0.2627 data_time: 0.0076 memory: 5828 grad_norm: 3.0671 loss: 2.5405 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5405 2023/06/05 02:04:29 - mmengine - INFO - Epoch(train) [51][1960/2569] lr: 4.0000e-02 eta: 18:51:38 time: 0.2638 data_time: 0.0076 memory: 5828 grad_norm: 3.1028 loss: 2.3099 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3099 2023/06/05 02:04:34 - mmengine - INFO - Epoch(train) [51][1980/2569] lr: 4.0000e-02 eta: 18:51:32 time: 0.2584 data_time: 0.0074 memory: 5828 grad_norm: 3.0990 loss: 2.4889 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4889 2023/06/05 02:04:39 - mmengine - INFO - Epoch(train) [51][2000/2569] lr: 4.0000e-02 eta: 18:51:26 time: 0.2609 data_time: 0.0074 memory: 5828 grad_norm: 3.0956 loss: 2.5404 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.5404 2023/06/05 02:04:45 - mmengine - INFO - Epoch(train) [51][2020/2569] lr: 4.0000e-02 eta: 18:51:21 time: 0.2682 data_time: 0.0074 memory: 5828 grad_norm: 3.1431 loss: 2.4590 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4590 2023/06/05 02:04:50 - mmengine - INFO - Epoch(train) [51][2040/2569] lr: 4.0000e-02 eta: 18:51:15 time: 0.2564 data_time: 0.0075 memory: 5828 grad_norm: 3.1113 loss: 2.6777 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6777 2023/06/05 02:04:55 - mmengine - INFO - Epoch(train) [51][2060/2569] lr: 4.0000e-02 eta: 18:51:10 time: 0.2694 data_time: 0.0069 memory: 5828 grad_norm: 3.1279 loss: 2.5017 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5017 2023/06/05 02:05:00 - mmengine - INFO - Epoch(train) [51][2080/2569] lr: 4.0000e-02 eta: 18:51:05 time: 0.2568 data_time: 0.0077 memory: 5828 grad_norm: 3.1227 loss: 2.5203 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5203 2023/06/05 02:05:06 - mmengine - INFO - Epoch(train) [51][2100/2569] lr: 4.0000e-02 eta: 18:50:59 time: 0.2653 data_time: 0.0075 memory: 5828 grad_norm: 3.0478 loss: 2.4599 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4599 2023/06/05 02:05:11 - mmengine - INFO - Epoch(train) [51][2120/2569] lr: 4.0000e-02 eta: 18:50:54 time: 0.2756 data_time: 0.0075 memory: 5828 grad_norm: 3.0501 loss: 2.5902 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5902 2023/06/05 02:05:17 - mmengine - INFO - Epoch(train) [51][2140/2569] lr: 4.0000e-02 eta: 18:50:49 time: 0.2801 data_time: 0.0073 memory: 5828 grad_norm: 3.1700 loss: 2.4549 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4549 2023/06/05 02:05:22 - mmengine - INFO - Epoch(train) [51][2160/2569] lr: 4.0000e-02 eta: 18:50:44 time: 0.2577 data_time: 0.0079 memory: 5828 grad_norm: 3.1056 loss: 2.5497 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5497 2023/06/05 02:05:27 - mmengine - INFO - Epoch(train) [51][2180/2569] lr: 4.0000e-02 eta: 18:50:39 time: 0.2710 data_time: 0.0083 memory: 5828 grad_norm: 3.1065 loss: 2.6576 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6576 2023/06/05 02:05:33 - mmengine - INFO - Epoch(train) [51][2200/2569] lr: 4.0000e-02 eta: 18:50:33 time: 0.2635 data_time: 0.0076 memory: 5828 grad_norm: 3.1297 loss: 2.6272 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6272 2023/06/05 02:05:38 - mmengine - INFO - Epoch(train) [51][2220/2569] lr: 4.0000e-02 eta: 18:50:28 time: 0.2744 data_time: 0.0082 memory: 5828 grad_norm: 3.1278 loss: 2.5732 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5732 2023/06/05 02:05:43 - mmengine - INFO - Epoch(train) [51][2240/2569] lr: 4.0000e-02 eta: 18:50:23 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 3.0708 loss: 2.2990 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2990 2023/06/05 02:05:49 - mmengine - INFO - Epoch(train) [51][2260/2569] lr: 4.0000e-02 eta: 18:50:17 time: 0.2625 data_time: 0.0077 memory: 5828 grad_norm: 3.1134 loss: 2.5576 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5576 2023/06/05 02:05:54 - mmengine - INFO - Epoch(train) [51][2280/2569] lr: 4.0000e-02 eta: 18:50:12 time: 0.2592 data_time: 0.0072 memory: 5828 grad_norm: 3.0461 loss: 2.4612 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4612 2023/06/05 02:05:59 - mmengine - INFO - Epoch(train) [51][2300/2569] lr: 4.0000e-02 eta: 18:50:06 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 3.0917 loss: 2.5765 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5765 2023/06/05 02:06:04 - mmengine - INFO - Epoch(train) [51][2320/2569] lr: 4.0000e-02 eta: 18:50:00 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 3.0726 loss: 2.6147 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6147 2023/06/05 02:06:10 - mmengine - INFO - Epoch(train) [51][2340/2569] lr: 4.0000e-02 eta: 18:49:56 time: 0.2766 data_time: 0.0076 memory: 5828 grad_norm: 3.1456 loss: 2.7291 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7291 2023/06/05 02:06:15 - mmengine - INFO - Epoch(train) [51][2360/2569] lr: 4.0000e-02 eta: 18:49:50 time: 0.2579 data_time: 0.0081 memory: 5828 grad_norm: 3.1598 loss: 2.6575 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6575 2023/06/05 02:06:20 - mmengine - INFO - Epoch(train) [51][2380/2569] lr: 4.0000e-02 eta: 18:49:44 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 3.0486 loss: 2.3099 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3099 2023/06/05 02:06:26 - mmengine - INFO - Epoch(train) [51][2400/2569] lr: 4.0000e-02 eta: 18:49:39 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 3.1145 loss: 2.5691 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5691 2023/06/05 02:06:31 - mmengine - INFO - Epoch(train) [51][2420/2569] lr: 4.0000e-02 eta: 18:49:34 time: 0.2583 data_time: 0.0078 memory: 5828 grad_norm: 3.0219 loss: 2.3916 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3916 2023/06/05 02:06:36 - mmengine - INFO - Epoch(train) [51][2440/2569] lr: 4.0000e-02 eta: 18:49:28 time: 0.2579 data_time: 0.0074 memory: 5828 grad_norm: 3.1350 loss: 2.4832 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4832 2023/06/05 02:06:41 - mmengine - INFO - Epoch(train) [51][2460/2569] lr: 4.0000e-02 eta: 18:49:22 time: 0.2623 data_time: 0.0068 memory: 5828 grad_norm: 3.0886 loss: 2.8855 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8855 2023/06/05 02:06:46 - mmengine - INFO - Epoch(train) [51][2480/2569] lr: 4.0000e-02 eta: 18:49:17 time: 0.2573 data_time: 0.0074 memory: 5828 grad_norm: 3.1160 loss: 2.5253 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5253 2023/06/05 02:06:52 - mmengine - INFO - Epoch(train) [51][2500/2569] lr: 4.0000e-02 eta: 18:49:11 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.0684 loss: 2.7436 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7436 2023/06/05 02:06:57 - mmengine - INFO - Epoch(train) [51][2520/2569] lr: 4.0000e-02 eta: 18:49:06 time: 0.2581 data_time: 0.0073 memory: 5828 grad_norm: 3.0407 loss: 2.8039 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8039 2023/06/05 02:07:02 - mmengine - INFO - Epoch(train) [51][2540/2569] lr: 4.0000e-02 eta: 18:49:00 time: 0.2629 data_time: 0.0080 memory: 5828 grad_norm: 3.1585 loss: 2.5606 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5606 2023/06/05 02:07:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:07:07 - mmengine - INFO - Epoch(train) [51][2560/2569] lr: 4.0000e-02 eta: 18:48:55 time: 0.2623 data_time: 0.0079 memory: 5828 grad_norm: 3.1081 loss: 2.4993 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4993 2023/06/05 02:07:10 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:07:10 - mmengine - INFO - Epoch(train) [51][2569/2569] lr: 4.0000e-02 eta: 18:48:52 time: 0.2573 data_time: 0.0078 memory: 5828 grad_norm: 3.0945 loss: 2.7694 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7694 2023/06/05 02:07:16 - mmengine - INFO - Epoch(train) [52][ 20/2569] lr: 4.0000e-02 eta: 18:48:50 time: 0.3455 data_time: 0.0452 memory: 5828 grad_norm: 3.1057 loss: 2.8015 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8015 2023/06/05 02:07:22 - mmengine - INFO - Epoch(train) [52][ 40/2569] lr: 4.0000e-02 eta: 18:48:44 time: 0.2660 data_time: 0.0082 memory: 5828 grad_norm: 3.0717 loss: 2.4870 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4870 2023/06/05 02:07:27 - mmengine - INFO - Epoch(train) [52][ 60/2569] lr: 4.0000e-02 eta: 18:48:39 time: 0.2589 data_time: 0.0091 memory: 5828 grad_norm: 3.0736 loss: 2.4911 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4911 2023/06/05 02:07:32 - mmengine - INFO - Epoch(train) [52][ 80/2569] lr: 4.0000e-02 eta: 18:48:33 time: 0.2634 data_time: 0.0073 memory: 5828 grad_norm: 3.0664 loss: 2.5669 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5669 2023/06/05 02:07:38 - mmengine - INFO - Epoch(train) [52][ 100/2569] lr: 4.0000e-02 eta: 18:48:28 time: 0.2743 data_time: 0.0080 memory: 5828 grad_norm: 3.0517 loss: 2.4983 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4983 2023/06/05 02:07:43 - mmengine - INFO - Epoch(train) [52][ 120/2569] lr: 4.0000e-02 eta: 18:48:23 time: 0.2649 data_time: 0.0071 memory: 5828 grad_norm: 3.0643 loss: 2.6913 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6913 2023/06/05 02:07:48 - mmengine - INFO - Epoch(train) [52][ 140/2569] lr: 4.0000e-02 eta: 18:48:18 time: 0.2709 data_time: 0.0073 memory: 5828 grad_norm: 3.1610 loss: 2.3599 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3599 2023/06/05 02:07:54 - mmengine - INFO - Epoch(train) [52][ 160/2569] lr: 4.0000e-02 eta: 18:48:12 time: 0.2672 data_time: 0.0083 memory: 5828 grad_norm: 3.1614 loss: 2.5807 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5807 2023/06/05 02:07:59 - mmengine - INFO - Epoch(train) [52][ 180/2569] lr: 4.0000e-02 eta: 18:48:07 time: 0.2696 data_time: 0.0071 memory: 5828 grad_norm: 3.0580 loss: 2.0113 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0113 2023/06/05 02:08:05 - mmengine - INFO - Epoch(train) [52][ 200/2569] lr: 4.0000e-02 eta: 18:48:02 time: 0.2695 data_time: 0.0076 memory: 5828 grad_norm: 3.0859 loss: 2.3063 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3063 2023/06/05 02:08:10 - mmengine - INFO - Epoch(train) [52][ 220/2569] lr: 4.0000e-02 eta: 18:47:57 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 3.0645 loss: 2.4285 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4285 2023/06/05 02:08:15 - mmengine - INFO - Epoch(train) [52][ 240/2569] lr: 4.0000e-02 eta: 18:47:51 time: 0.2664 data_time: 0.0079 memory: 5828 grad_norm: 3.0980 loss: 2.2693 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2693 2023/06/05 02:08:20 - mmengine - INFO - Epoch(train) [52][ 260/2569] lr: 4.0000e-02 eta: 18:47:46 time: 0.2584 data_time: 0.0076 memory: 5828 grad_norm: 3.0655 loss: 2.5153 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5153 2023/06/05 02:08:26 - mmengine - INFO - Epoch(train) [52][ 280/2569] lr: 4.0000e-02 eta: 18:47:40 time: 0.2657 data_time: 0.0077 memory: 5828 grad_norm: 3.0714 loss: 2.5937 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5937 2023/06/05 02:08:31 - mmengine - INFO - Epoch(train) [52][ 300/2569] lr: 4.0000e-02 eta: 18:47:35 time: 0.2627 data_time: 0.0070 memory: 5828 grad_norm: 3.1111 loss: 2.7018 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7018 2023/06/05 02:08:36 - mmengine - INFO - Epoch(train) [52][ 320/2569] lr: 4.0000e-02 eta: 18:47:29 time: 0.2607 data_time: 0.0073 memory: 5828 grad_norm: 3.1163 loss: 2.5416 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5416 2023/06/05 02:08:41 - mmengine - INFO - Epoch(train) [52][ 340/2569] lr: 4.0000e-02 eta: 18:47:24 time: 0.2628 data_time: 0.0074 memory: 5828 grad_norm: 3.1132 loss: 2.3718 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3718 2023/06/05 02:08:47 - mmengine - INFO - Epoch(train) [52][ 360/2569] lr: 4.0000e-02 eta: 18:47:18 time: 0.2624 data_time: 0.0071 memory: 5828 grad_norm: 3.1189 loss: 2.6889 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.6889 2023/06/05 02:08:52 - mmengine - INFO - Epoch(train) [52][ 380/2569] lr: 4.0000e-02 eta: 18:47:13 time: 0.2633 data_time: 0.0076 memory: 5828 grad_norm: 3.1108 loss: 2.6741 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6741 2023/06/05 02:08:57 - mmengine - INFO - Epoch(train) [52][ 400/2569] lr: 4.0000e-02 eta: 18:47:08 time: 0.2691 data_time: 0.0077 memory: 5828 grad_norm: 3.1135 loss: 2.6574 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6574 2023/06/05 02:09:03 - mmengine - INFO - Epoch(train) [52][ 420/2569] lr: 4.0000e-02 eta: 18:47:03 time: 0.2716 data_time: 0.0076 memory: 5828 grad_norm: 3.0748 loss: 2.6080 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6080 2023/06/05 02:09:08 - mmengine - INFO - Epoch(train) [52][ 440/2569] lr: 4.0000e-02 eta: 18:46:57 time: 0.2670 data_time: 0.0074 memory: 5828 grad_norm: 3.1093 loss: 2.7132 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7132 2023/06/05 02:09:14 - mmengine - INFO - Epoch(train) [52][ 460/2569] lr: 4.0000e-02 eta: 18:46:52 time: 0.2773 data_time: 0.0075 memory: 5828 grad_norm: 3.1009 loss: 2.2131 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2131 2023/06/05 02:09:19 - mmengine - INFO - Epoch(train) [52][ 480/2569] lr: 4.0000e-02 eta: 18:46:47 time: 0.2754 data_time: 0.0076 memory: 5828 grad_norm: 3.0911 loss: 2.6743 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6743 2023/06/05 02:09:25 - mmengine - INFO - Epoch(train) [52][ 500/2569] lr: 4.0000e-02 eta: 18:46:42 time: 0.2702 data_time: 0.0073 memory: 5828 grad_norm: 3.0730 loss: 2.4947 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4947 2023/06/05 02:09:30 - mmengine - INFO - Epoch(train) [52][ 520/2569] lr: 4.0000e-02 eta: 18:46:37 time: 0.2602 data_time: 0.0078 memory: 5828 grad_norm: 3.0636 loss: 2.5042 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5042 2023/06/05 02:09:35 - mmengine - INFO - Epoch(train) [52][ 540/2569] lr: 4.0000e-02 eta: 18:46:31 time: 0.2704 data_time: 0.0078 memory: 5828 grad_norm: 3.1181 loss: 2.6803 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6803 2023/06/05 02:09:41 - mmengine - INFO - Epoch(train) [52][ 560/2569] lr: 4.0000e-02 eta: 18:46:26 time: 0.2714 data_time: 0.0076 memory: 5828 grad_norm: 3.0807 loss: 2.3707 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3707 2023/06/05 02:09:46 - mmengine - INFO - Epoch(train) [52][ 580/2569] lr: 4.0000e-02 eta: 18:46:21 time: 0.2616 data_time: 0.0079 memory: 5828 grad_norm: 3.0513 loss: 2.3334 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3334 2023/06/05 02:09:51 - mmengine - INFO - Epoch(train) [52][ 600/2569] lr: 4.0000e-02 eta: 18:46:15 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 3.0940 loss: 2.3891 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3891 2023/06/05 02:09:56 - mmengine - INFO - Epoch(train) [52][ 620/2569] lr: 4.0000e-02 eta: 18:46:10 time: 0.2587 data_time: 0.0076 memory: 5828 grad_norm: 3.1294 loss: 2.4476 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4476 2023/06/05 02:10:02 - mmengine - INFO - Epoch(train) [52][ 640/2569] lr: 4.0000e-02 eta: 18:46:04 time: 0.2633 data_time: 0.0076 memory: 5828 grad_norm: 3.0699 loss: 2.7015 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7015 2023/06/05 02:10:07 - mmengine - INFO - Epoch(train) [52][ 660/2569] lr: 4.0000e-02 eta: 18:45:59 time: 0.2639 data_time: 0.0078 memory: 5828 grad_norm: 3.1039 loss: 2.4604 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4604 2023/06/05 02:10:12 - mmengine - INFO - Epoch(train) [52][ 680/2569] lr: 4.0000e-02 eta: 18:45:53 time: 0.2629 data_time: 0.0075 memory: 5828 grad_norm: 3.0421 loss: 2.4528 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4528 2023/06/05 02:10:17 - mmengine - INFO - Epoch(train) [52][ 700/2569] lr: 4.0000e-02 eta: 18:45:48 time: 0.2579 data_time: 0.0076 memory: 5828 grad_norm: 3.1151 loss: 2.6946 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6946 2023/06/05 02:10:22 - mmengine - INFO - Epoch(train) [52][ 720/2569] lr: 4.0000e-02 eta: 18:45:42 time: 0.2564 data_time: 0.0076 memory: 5828 grad_norm: 3.0884 loss: 2.4325 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4325 2023/06/05 02:10:28 - mmengine - INFO - Epoch(train) [52][ 740/2569] lr: 4.0000e-02 eta: 18:45:37 time: 0.2665 data_time: 0.0081 memory: 5828 grad_norm: 3.1025 loss: 2.3138 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3138 2023/06/05 02:10:33 - mmengine - INFO - Epoch(train) [52][ 760/2569] lr: 4.0000e-02 eta: 18:45:31 time: 0.2573 data_time: 0.0075 memory: 5828 grad_norm: 3.1322 loss: 2.4539 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4539 2023/06/05 02:10:38 - mmengine - INFO - Epoch(train) [52][ 780/2569] lr: 4.0000e-02 eta: 18:45:26 time: 0.2749 data_time: 0.0076 memory: 5828 grad_norm: 3.1051 loss: 2.3345 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3345 2023/06/05 02:10:44 - mmengine - INFO - Epoch(train) [52][ 800/2569] lr: 4.0000e-02 eta: 18:45:21 time: 0.2670 data_time: 0.0076 memory: 5828 grad_norm: 3.1388 loss: 2.7438 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7438 2023/06/05 02:10:49 - mmengine - INFO - Epoch(train) [52][ 820/2569] lr: 4.0000e-02 eta: 18:45:15 time: 0.2675 data_time: 0.0075 memory: 5828 grad_norm: 3.1041 loss: 2.4326 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4326 2023/06/05 02:10:54 - mmengine - INFO - Epoch(train) [52][ 840/2569] lr: 4.0000e-02 eta: 18:45:10 time: 0.2628 data_time: 0.0082 memory: 5828 grad_norm: 3.0970 loss: 2.4698 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4698 2023/06/05 02:11:00 - mmengine - INFO - Epoch(train) [52][ 860/2569] lr: 4.0000e-02 eta: 18:45:05 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 3.0794 loss: 2.8117 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8117 2023/06/05 02:11:05 - mmengine - INFO - Epoch(train) [52][ 880/2569] lr: 4.0000e-02 eta: 18:44:59 time: 0.2578 data_time: 0.0084 memory: 5828 grad_norm: 3.1564 loss: 2.7787 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7787 2023/06/05 02:11:10 - mmengine - INFO - Epoch(train) [52][ 900/2569] lr: 4.0000e-02 eta: 18:44:53 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 3.1667 loss: 2.6455 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6455 2023/06/05 02:11:15 - mmengine - INFO - Epoch(train) [52][ 920/2569] lr: 4.0000e-02 eta: 18:44:48 time: 0.2574 data_time: 0.0080 memory: 5828 grad_norm: 3.1501 loss: 2.4328 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4328 2023/06/05 02:11:20 - mmengine - INFO - Epoch(train) [52][ 940/2569] lr: 4.0000e-02 eta: 18:44:42 time: 0.2579 data_time: 0.0073 memory: 5828 grad_norm: 3.0726 loss: 2.8649 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8649 2023/06/05 02:11:26 - mmengine - INFO - Epoch(train) [52][ 960/2569] lr: 4.0000e-02 eta: 18:44:36 time: 0.2586 data_time: 0.0075 memory: 5828 grad_norm: 3.1512 loss: 2.5671 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5671 2023/06/05 02:11:31 - mmengine - INFO - Epoch(train) [52][ 980/2569] lr: 4.0000e-02 eta: 18:44:31 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 3.0981 loss: 2.7644 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7644 2023/06/05 02:11:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:11:36 - mmengine - INFO - Epoch(train) [52][1000/2569] lr: 4.0000e-02 eta: 18:44:26 time: 0.2695 data_time: 0.0077 memory: 5828 grad_norm: 3.1057 loss: 2.6539 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6539 2023/06/05 02:11:41 - mmengine - INFO - Epoch(train) [52][1020/2569] lr: 4.0000e-02 eta: 18:44:20 time: 0.2591 data_time: 0.0076 memory: 5828 grad_norm: 3.1184 loss: 2.4171 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4171 2023/06/05 02:11:47 - mmengine - INFO - Epoch(train) [52][1040/2569] lr: 4.0000e-02 eta: 18:44:15 time: 0.2666 data_time: 0.0071 memory: 5828 grad_norm: 3.1345 loss: 2.4491 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4491 2023/06/05 02:11:52 - mmengine - INFO - Epoch(train) [52][1060/2569] lr: 4.0000e-02 eta: 18:44:09 time: 0.2581 data_time: 0.0077 memory: 5828 grad_norm: 3.0939 loss: 2.4265 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4265 2023/06/05 02:11:58 - mmengine - INFO - Epoch(train) [52][1080/2569] lr: 4.0000e-02 eta: 18:44:05 time: 0.2866 data_time: 0.0074 memory: 5828 grad_norm: 3.1210 loss: 2.6316 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6316 2023/06/05 02:12:03 - mmengine - INFO - Epoch(train) [52][1100/2569] lr: 4.0000e-02 eta: 18:43:59 time: 0.2587 data_time: 0.0074 memory: 5828 grad_norm: 3.0977 loss: 2.3415 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3415 2023/06/05 02:12:08 - mmengine - INFO - Epoch(train) [52][1120/2569] lr: 4.0000e-02 eta: 18:43:54 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 3.1086 loss: 2.6347 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6347 2023/06/05 02:12:13 - mmengine - INFO - Epoch(train) [52][1140/2569] lr: 4.0000e-02 eta: 18:43:48 time: 0.2623 data_time: 0.0074 memory: 5828 grad_norm: 3.1482 loss: 2.4468 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4468 2023/06/05 02:12:19 - mmengine - INFO - Epoch(train) [52][1160/2569] lr: 4.0000e-02 eta: 18:43:43 time: 0.2711 data_time: 0.0074 memory: 5828 grad_norm: 3.1293 loss: 2.8192 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8192 2023/06/05 02:12:24 - mmengine - INFO - Epoch(train) [52][1180/2569] lr: 4.0000e-02 eta: 18:43:38 time: 0.2692 data_time: 0.0078 memory: 5828 grad_norm: 3.1305 loss: 2.4848 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4848 2023/06/05 02:12:29 - mmengine - INFO - Epoch(train) [52][1200/2569] lr: 4.0000e-02 eta: 18:43:32 time: 0.2636 data_time: 0.0072 memory: 5828 grad_norm: 3.1458 loss: 3.0140 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0140 2023/06/05 02:12:35 - mmengine - INFO - Epoch(train) [52][1220/2569] lr: 4.0000e-02 eta: 18:43:27 time: 0.2733 data_time: 0.0079 memory: 5828 grad_norm: 3.1569 loss: 2.7477 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7477 2023/06/05 02:12:40 - mmengine - INFO - Epoch(train) [52][1240/2569] lr: 4.0000e-02 eta: 18:43:22 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 3.1234 loss: 2.4431 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4431 2023/06/05 02:12:46 - mmengine - INFO - Epoch(train) [52][1260/2569] lr: 4.0000e-02 eta: 18:43:17 time: 0.2692 data_time: 0.0076 memory: 5828 grad_norm: 3.1157 loss: 2.6406 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6406 2023/06/05 02:12:51 - mmengine - INFO - Epoch(train) [52][1280/2569] lr: 4.0000e-02 eta: 18:43:11 time: 0.2679 data_time: 0.0078 memory: 5828 grad_norm: 3.1009 loss: 2.6033 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6033 2023/06/05 02:12:56 - mmengine - INFO - Epoch(train) [52][1300/2569] lr: 4.0000e-02 eta: 18:43:06 time: 0.2583 data_time: 0.0079 memory: 5828 grad_norm: 3.1732 loss: 2.7941 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.7941 2023/06/05 02:13:01 - mmengine - INFO - Epoch(train) [52][1320/2569] lr: 4.0000e-02 eta: 18:43:00 time: 0.2632 data_time: 0.0082 memory: 5828 grad_norm: 3.0874 loss: 2.3658 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3658 2023/06/05 02:13:07 - mmengine - INFO - Epoch(train) [52][1340/2569] lr: 4.0000e-02 eta: 18:42:55 time: 0.2588 data_time: 0.0078 memory: 5828 grad_norm: 3.1665 loss: 2.5197 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5197 2023/06/05 02:13:12 - mmengine - INFO - Epoch(train) [52][1360/2569] lr: 4.0000e-02 eta: 18:42:49 time: 0.2640 data_time: 0.0082 memory: 5828 grad_norm: 3.1881 loss: 2.6685 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6685 2023/06/05 02:13:17 - mmengine - INFO - Epoch(train) [52][1380/2569] lr: 4.0000e-02 eta: 18:42:44 time: 0.2681 data_time: 0.0078 memory: 5828 grad_norm: 3.0705 loss: 2.6929 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6929 2023/06/05 02:13:23 - mmengine - INFO - Epoch(train) [52][1400/2569] lr: 4.0000e-02 eta: 18:42:39 time: 0.2646 data_time: 0.0074 memory: 5828 grad_norm: 3.1119 loss: 2.8346 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8346 2023/06/05 02:13:28 - mmengine - INFO - Epoch(train) [52][1420/2569] lr: 4.0000e-02 eta: 18:42:33 time: 0.2582 data_time: 0.0088 memory: 5828 grad_norm: 3.1457 loss: 2.8803 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8803 2023/06/05 02:13:33 - mmengine - INFO - Epoch(train) [52][1440/2569] lr: 4.0000e-02 eta: 18:42:28 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 3.1398 loss: 2.4179 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4179 2023/06/05 02:13:38 - mmengine - INFO - Epoch(train) [52][1460/2569] lr: 4.0000e-02 eta: 18:42:22 time: 0.2656 data_time: 0.0075 memory: 5828 grad_norm: 3.1155 loss: 2.4560 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4560 2023/06/05 02:13:44 - mmengine - INFO - Epoch(train) [52][1480/2569] lr: 4.0000e-02 eta: 18:42:17 time: 0.2612 data_time: 0.0077 memory: 5828 grad_norm: 3.1552 loss: 2.9036 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.9036 2023/06/05 02:13:49 - mmengine - INFO - Epoch(train) [52][1500/2569] lr: 4.0000e-02 eta: 18:42:11 time: 0.2668 data_time: 0.0076 memory: 5828 grad_norm: 3.1696 loss: 2.3312 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3312 2023/06/05 02:13:54 - mmengine - INFO - Epoch(train) [52][1520/2569] lr: 4.0000e-02 eta: 18:42:07 time: 0.2771 data_time: 0.0075 memory: 5828 grad_norm: 3.1100 loss: 2.4993 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4993 2023/06/05 02:14:00 - mmengine - INFO - Epoch(train) [52][1540/2569] lr: 4.0000e-02 eta: 18:42:01 time: 0.2624 data_time: 0.0074 memory: 5828 grad_norm: 3.0927 loss: 2.7752 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7752 2023/06/05 02:14:05 - mmengine - INFO - Epoch(train) [52][1560/2569] lr: 4.0000e-02 eta: 18:41:56 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 3.0742 loss: 2.8468 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.8468 2023/06/05 02:14:10 - mmengine - INFO - Epoch(train) [52][1580/2569] lr: 4.0000e-02 eta: 18:41:50 time: 0.2604 data_time: 0.0082 memory: 5828 grad_norm: 3.1164 loss: 2.6074 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6074 2023/06/05 02:14:16 - mmengine - INFO - Epoch(train) [52][1600/2569] lr: 4.0000e-02 eta: 18:41:45 time: 0.2620 data_time: 0.0075 memory: 5828 grad_norm: 3.1014 loss: 2.3901 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3901 2023/06/05 02:14:21 - mmengine - INFO - Epoch(train) [52][1620/2569] lr: 4.0000e-02 eta: 18:41:39 time: 0.2604 data_time: 0.0079 memory: 5828 grad_norm: 3.1194 loss: 2.3031 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3031 2023/06/05 02:14:26 - mmengine - INFO - Epoch(train) [52][1640/2569] lr: 4.0000e-02 eta: 18:41:34 time: 0.2616 data_time: 0.0080 memory: 5828 grad_norm: 3.0724 loss: 2.6672 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6672 2023/06/05 02:14:31 - mmengine - INFO - Epoch(train) [52][1660/2569] lr: 4.0000e-02 eta: 18:41:28 time: 0.2687 data_time: 0.0076 memory: 5828 grad_norm: 3.1264 loss: 2.6921 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6921 2023/06/05 02:14:37 - mmengine - INFO - Epoch(train) [52][1680/2569] lr: 4.0000e-02 eta: 18:41:23 time: 0.2604 data_time: 0.0080 memory: 5828 grad_norm: 3.1261 loss: 2.4575 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4575 2023/06/05 02:14:42 - mmengine - INFO - Epoch(train) [52][1700/2569] lr: 4.0000e-02 eta: 18:41:17 time: 0.2640 data_time: 0.0077 memory: 5828 grad_norm: 3.1934 loss: 2.3323 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3323 2023/06/05 02:14:47 - mmengine - INFO - Epoch(train) [52][1720/2569] lr: 4.0000e-02 eta: 18:41:12 time: 0.2756 data_time: 0.0073 memory: 5828 grad_norm: 3.0638 loss: 2.7832 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7832 2023/06/05 02:14:53 - mmengine - INFO - Epoch(train) [52][1740/2569] lr: 4.0000e-02 eta: 18:41:07 time: 0.2577 data_time: 0.0076 memory: 5828 grad_norm: 3.0781 loss: 2.5838 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5838 2023/06/05 02:14:58 - mmengine - INFO - Epoch(train) [52][1760/2569] lr: 4.0000e-02 eta: 18:41:01 time: 0.2662 data_time: 0.0073 memory: 5828 grad_norm: 2.9888 loss: 2.5703 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5703 2023/06/05 02:15:03 - mmengine - INFO - Epoch(train) [52][1780/2569] lr: 4.0000e-02 eta: 18:40:56 time: 0.2631 data_time: 0.0089 memory: 5828 grad_norm: 3.0870 loss: 2.6570 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6570 2023/06/05 02:15:08 - mmengine - INFO - Epoch(train) [52][1800/2569] lr: 4.0000e-02 eta: 18:40:51 time: 0.2680 data_time: 0.0074 memory: 5828 grad_norm: 3.0922 loss: 2.4795 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4795 2023/06/05 02:15:14 - mmengine - INFO - Epoch(train) [52][1820/2569] lr: 4.0000e-02 eta: 18:40:45 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 3.1419 loss: 2.2881 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2881 2023/06/05 02:15:19 - mmengine - INFO - Epoch(train) [52][1840/2569] lr: 4.0000e-02 eta: 18:40:40 time: 0.2579 data_time: 0.0077 memory: 5828 grad_norm: 3.1413 loss: 2.7340 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7340 2023/06/05 02:15:24 - mmengine - INFO - Epoch(train) [52][1860/2569] lr: 4.0000e-02 eta: 18:40:34 time: 0.2638 data_time: 0.0087 memory: 5828 grad_norm: 3.1236 loss: 2.7973 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7973 2023/06/05 02:15:30 - mmengine - INFO - Epoch(train) [52][1880/2569] lr: 4.0000e-02 eta: 18:40:29 time: 0.2613 data_time: 0.0084 memory: 5828 grad_norm: 3.0973 loss: 2.6474 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6474 2023/06/05 02:15:35 - mmengine - INFO - Epoch(train) [52][1900/2569] lr: 4.0000e-02 eta: 18:40:23 time: 0.2636 data_time: 0.0077 memory: 5828 grad_norm: 3.0494 loss: 2.4900 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4900 2023/06/05 02:15:40 - mmengine - INFO - Epoch(train) [52][1920/2569] lr: 4.0000e-02 eta: 18:40:18 time: 0.2646 data_time: 0.0080 memory: 5828 grad_norm: 3.0932 loss: 2.3216 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3216 2023/06/05 02:15:45 - mmengine - INFO - Epoch(train) [52][1940/2569] lr: 4.0000e-02 eta: 18:40:12 time: 0.2579 data_time: 0.0078 memory: 5828 grad_norm: 3.0841 loss: 2.5781 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5781 2023/06/05 02:15:50 - mmengine - INFO - Epoch(train) [52][1960/2569] lr: 4.0000e-02 eta: 18:40:07 time: 0.2570 data_time: 0.0078 memory: 5828 grad_norm: 3.1090 loss: 2.4043 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4043 2023/06/05 02:15:56 - mmengine - INFO - Epoch(train) [52][1980/2569] lr: 4.0000e-02 eta: 18:40:02 time: 0.2738 data_time: 0.0077 memory: 5828 grad_norm: 3.0871 loss: 2.5536 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5536 2023/06/05 02:15:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:16:01 - mmengine - INFO - Epoch(train) [52][2000/2569] lr: 4.0000e-02 eta: 18:39:56 time: 0.2558 data_time: 0.0076 memory: 5828 grad_norm: 3.1250 loss: 2.6232 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6232 2023/06/05 02:16:06 - mmengine - INFO - Epoch(train) [52][2020/2569] lr: 4.0000e-02 eta: 18:39:50 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 3.0824 loss: 2.5162 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5162 2023/06/05 02:16:11 - mmengine - INFO - Epoch(train) [52][2040/2569] lr: 4.0000e-02 eta: 18:39:45 time: 0.2587 data_time: 0.0076 memory: 5828 grad_norm: 3.0602 loss: 2.6035 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6035 2023/06/05 02:16:17 - mmengine - INFO - Epoch(train) [52][2060/2569] lr: 4.0000e-02 eta: 18:39:39 time: 0.2570 data_time: 0.0078 memory: 5828 grad_norm: 3.0605 loss: 2.7389 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7389 2023/06/05 02:16:22 - mmengine - INFO - Epoch(train) [52][2080/2569] lr: 4.0000e-02 eta: 18:39:34 time: 0.2578 data_time: 0.0079 memory: 5828 grad_norm: 3.1212 loss: 2.5211 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5211 2023/06/05 02:16:27 - mmengine - INFO - Epoch(train) [52][2100/2569] lr: 4.0000e-02 eta: 18:39:28 time: 0.2616 data_time: 0.0078 memory: 5828 grad_norm: 3.0796 loss: 2.7239 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7239 2023/06/05 02:16:32 - mmengine - INFO - Epoch(train) [52][2120/2569] lr: 4.0000e-02 eta: 18:39:22 time: 0.2585 data_time: 0.0076 memory: 5828 grad_norm: 3.1114 loss: 2.6792 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6792 2023/06/05 02:16:37 - mmengine - INFO - Epoch(train) [52][2140/2569] lr: 4.0000e-02 eta: 18:39:17 time: 0.2580 data_time: 0.0076 memory: 5828 grad_norm: 3.1092 loss: 2.9764 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9764 2023/06/05 02:16:43 - mmengine - INFO - Epoch(train) [52][2160/2569] lr: 4.0000e-02 eta: 18:39:11 time: 0.2653 data_time: 0.0077 memory: 5828 grad_norm: 3.1005 loss: 2.3089 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3089 2023/06/05 02:16:48 - mmengine - INFO - Epoch(train) [52][2180/2569] lr: 4.0000e-02 eta: 18:39:06 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 3.0849 loss: 2.9031 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9031 2023/06/05 02:16:53 - mmengine - INFO - Epoch(train) [52][2200/2569] lr: 4.0000e-02 eta: 18:39:00 time: 0.2573 data_time: 0.0072 memory: 5828 grad_norm: 3.1413 loss: 2.5091 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5091 2023/06/05 02:16:58 - mmengine - INFO - Epoch(train) [52][2220/2569] lr: 4.0000e-02 eta: 18:38:55 time: 0.2696 data_time: 0.0077 memory: 5828 grad_norm: 3.1189 loss: 2.7529 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7529 2023/06/05 02:17:04 - mmengine - INFO - Epoch(train) [52][2240/2569] lr: 4.0000e-02 eta: 18:38:50 time: 0.2681 data_time: 0.0077 memory: 5828 grad_norm: 3.1065 loss: 2.2809 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2809 2023/06/05 02:17:09 - mmengine - INFO - Epoch(train) [52][2260/2569] lr: 4.0000e-02 eta: 18:38:44 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 3.1559 loss: 2.7014 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7014 2023/06/05 02:17:14 - mmengine - INFO - Epoch(train) [52][2280/2569] lr: 4.0000e-02 eta: 18:38:39 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 3.0787 loss: 2.7248 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7248 2023/06/05 02:17:19 - mmengine - INFO - Epoch(train) [52][2300/2569] lr: 4.0000e-02 eta: 18:38:33 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 3.1083 loss: 2.3756 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3756 2023/06/05 02:17:25 - mmengine - INFO - Epoch(train) [52][2320/2569] lr: 4.0000e-02 eta: 18:38:28 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 3.1332 loss: 2.3637 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3637 2023/06/05 02:17:30 - mmengine - INFO - Epoch(train) [52][2340/2569] lr: 4.0000e-02 eta: 18:38:22 time: 0.2691 data_time: 0.0075 memory: 5828 grad_norm: 3.1535 loss: 2.3632 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3632 2023/06/05 02:17:35 - mmengine - INFO - Epoch(train) [52][2360/2569] lr: 4.0000e-02 eta: 18:38:17 time: 0.2605 data_time: 0.0073 memory: 5828 grad_norm: 3.1002 loss: 2.7388 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7388 2023/06/05 02:17:40 - mmengine - INFO - Epoch(train) [52][2380/2569] lr: 4.0000e-02 eta: 18:38:11 time: 0.2582 data_time: 0.0078 memory: 5828 grad_norm: 3.1226 loss: 2.3389 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3389 2023/06/05 02:17:46 - mmengine - INFO - Epoch(train) [52][2400/2569] lr: 4.0000e-02 eta: 18:38:06 time: 0.2571 data_time: 0.0086 memory: 5828 grad_norm: 3.0772 loss: 2.0405 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0405 2023/06/05 02:17:51 - mmengine - INFO - Epoch(train) [52][2420/2569] lr: 4.0000e-02 eta: 18:38:00 time: 0.2608 data_time: 0.0078 memory: 5828 grad_norm: 3.0803 loss: 2.2392 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2392 2023/06/05 02:17:56 - mmengine - INFO - Epoch(train) [52][2440/2569] lr: 4.0000e-02 eta: 18:37:55 time: 0.2603 data_time: 0.0071 memory: 5828 grad_norm: 3.1629 loss: 2.8426 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8426 2023/06/05 02:18:01 - mmengine - INFO - Epoch(train) [52][2460/2569] lr: 4.0000e-02 eta: 18:37:49 time: 0.2574 data_time: 0.0077 memory: 5828 grad_norm: 3.1082 loss: 2.4446 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4446 2023/06/05 02:18:07 - mmengine - INFO - Epoch(train) [52][2480/2569] lr: 4.0000e-02 eta: 18:37:44 time: 0.2669 data_time: 0.0076 memory: 5828 grad_norm: 3.0941 loss: 2.3958 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3958 2023/06/05 02:18:12 - mmengine - INFO - Epoch(train) [52][2500/2569] lr: 4.0000e-02 eta: 18:37:38 time: 0.2620 data_time: 0.0078 memory: 5828 grad_norm: 3.1449 loss: 2.6374 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6374 2023/06/05 02:18:17 - mmengine - INFO - Epoch(train) [52][2520/2569] lr: 4.0000e-02 eta: 18:37:33 time: 0.2616 data_time: 0.0082 memory: 5828 grad_norm: 3.0909 loss: 2.6213 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6213 2023/06/05 02:18:22 - mmengine - INFO - Epoch(train) [52][2540/2569] lr: 4.0000e-02 eta: 18:37:27 time: 0.2653 data_time: 0.0077 memory: 5828 grad_norm: 3.1309 loss: 2.3947 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3947 2023/06/05 02:18:28 - mmengine - INFO - Epoch(train) [52][2560/2569] lr: 4.0000e-02 eta: 18:37:22 time: 0.2740 data_time: 0.0079 memory: 5828 grad_norm: 3.0924 loss: 2.7770 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7770 2023/06/05 02:18:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:18:30 - mmengine - INFO - Epoch(train) [52][2569/2569] lr: 4.0000e-02 eta: 18:37:20 time: 0.2700 data_time: 0.0075 memory: 5828 grad_norm: 3.1281 loss: 2.4691 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.4691 2023/06/05 02:18:30 - mmengine - INFO - Saving checkpoint at 52 epochs 2023/06/05 02:18:38 - mmengine - INFO - Epoch(train) [53][ 20/2569] lr: 4.0000e-02 eta: 18:37:16 time: 0.3023 data_time: 0.0379 memory: 5828 grad_norm: 3.1451 loss: 2.6812 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6812 2023/06/05 02:18:43 - mmengine - INFO - Epoch(train) [53][ 40/2569] lr: 4.0000e-02 eta: 18:37:10 time: 0.2653 data_time: 0.0075 memory: 5828 grad_norm: 3.0877 loss: 2.3742 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.3742 2023/06/05 02:18:49 - mmengine - INFO - Epoch(train) [53][ 60/2569] lr: 4.0000e-02 eta: 18:37:05 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 3.1205 loss: 2.5889 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5889 2023/06/05 02:18:54 - mmengine - INFO - Epoch(train) [53][ 80/2569] lr: 4.0000e-02 eta: 18:37:00 time: 0.2684 data_time: 0.0074 memory: 5828 grad_norm: 3.1150 loss: 2.6104 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6104 2023/06/05 02:18:59 - mmengine - INFO - Epoch(train) [53][ 100/2569] lr: 4.0000e-02 eta: 18:36:54 time: 0.2608 data_time: 0.0072 memory: 5828 grad_norm: 3.0461 loss: 2.4005 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4005 2023/06/05 02:19:05 - mmengine - INFO - Epoch(train) [53][ 120/2569] lr: 4.0000e-02 eta: 18:36:49 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 3.0884 loss: 2.7053 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7053 2023/06/05 02:19:10 - mmengine - INFO - Epoch(train) [53][ 140/2569] lr: 4.0000e-02 eta: 18:36:43 time: 0.2612 data_time: 0.0072 memory: 5828 grad_norm: 3.0061 loss: 2.6864 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6864 2023/06/05 02:19:15 - mmengine - INFO - Epoch(train) [53][ 160/2569] lr: 4.0000e-02 eta: 18:36:38 time: 0.2674 data_time: 0.0078 memory: 5828 grad_norm: 3.1202 loss: 2.6862 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6862 2023/06/05 02:19:20 - mmengine - INFO - Epoch(train) [53][ 180/2569] lr: 4.0000e-02 eta: 18:36:33 time: 0.2666 data_time: 0.0071 memory: 5828 grad_norm: 3.0996 loss: 2.5907 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5907 2023/06/05 02:19:26 - mmengine - INFO - Epoch(train) [53][ 200/2569] lr: 4.0000e-02 eta: 18:36:28 time: 0.2744 data_time: 0.0078 memory: 5828 grad_norm: 3.0850 loss: 2.5650 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5650 2023/06/05 02:19:31 - mmengine - INFO - Epoch(train) [53][ 220/2569] lr: 4.0000e-02 eta: 18:36:22 time: 0.2574 data_time: 0.0078 memory: 5828 grad_norm: 3.1584 loss: 2.4156 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4156 2023/06/05 02:19:36 - mmengine - INFO - Epoch(train) [53][ 240/2569] lr: 4.0000e-02 eta: 18:36:16 time: 0.2569 data_time: 0.0081 memory: 5828 grad_norm: 3.1637 loss: 2.4420 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4420 2023/06/05 02:19:41 - mmengine - INFO - Epoch(train) [53][ 260/2569] lr: 4.0000e-02 eta: 18:36:11 time: 0.2573 data_time: 0.0074 memory: 5828 grad_norm: 3.0680 loss: 2.7487 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7487 2023/06/05 02:19:47 - mmengine - INFO - Epoch(train) [53][ 280/2569] lr: 4.0000e-02 eta: 18:36:06 time: 0.2760 data_time: 0.0080 memory: 5828 grad_norm: 3.0610 loss: 2.7564 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7564 2023/06/05 02:19:52 - mmengine - INFO - Epoch(train) [53][ 300/2569] lr: 4.0000e-02 eta: 18:36:00 time: 0.2686 data_time: 0.0076 memory: 5828 grad_norm: 3.1204 loss: 2.1311 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1311 2023/06/05 02:19:58 - mmengine - INFO - Epoch(train) [53][ 320/2569] lr: 4.0000e-02 eta: 18:35:55 time: 0.2714 data_time: 0.0077 memory: 5828 grad_norm: 3.1737 loss: 2.8429 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8429 2023/06/05 02:20:03 - mmengine - INFO - Epoch(train) [53][ 340/2569] lr: 4.0000e-02 eta: 18:35:50 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 3.1316 loss: 2.5370 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5370 2023/06/05 02:20:08 - mmengine - INFO - Epoch(train) [53][ 360/2569] lr: 4.0000e-02 eta: 18:35:45 time: 0.2709 data_time: 0.0077 memory: 5828 grad_norm: 3.0669 loss: 3.0586 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0586 2023/06/05 02:20:14 - mmengine - INFO - Epoch(train) [53][ 380/2569] lr: 4.0000e-02 eta: 18:35:39 time: 0.2653 data_time: 0.0084 memory: 5828 grad_norm: 3.1115 loss: 2.4718 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4718 2023/06/05 02:20:19 - mmengine - INFO - Epoch(train) [53][ 400/2569] lr: 4.0000e-02 eta: 18:35:34 time: 0.2786 data_time: 0.0073 memory: 5828 grad_norm: 3.0750 loss: 2.5840 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5840 2023/06/05 02:20:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:20:25 - mmengine - INFO - Epoch(train) [53][ 420/2569] lr: 4.0000e-02 eta: 18:35:29 time: 0.2628 data_time: 0.0083 memory: 5828 grad_norm: 3.0968 loss: 2.6465 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6465 2023/06/05 02:20:30 - mmengine - INFO - Epoch(train) [53][ 440/2569] lr: 4.0000e-02 eta: 18:35:24 time: 0.2744 data_time: 0.0074 memory: 5828 grad_norm: 3.1534 loss: 2.7254 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7254 2023/06/05 02:20:35 - mmengine - INFO - Epoch(train) [53][ 460/2569] lr: 4.0000e-02 eta: 18:35:19 time: 0.2621 data_time: 0.0072 memory: 5828 grad_norm: 3.0921 loss: 2.4130 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4130 2023/06/05 02:20:41 - mmengine - INFO - Epoch(train) [53][ 480/2569] lr: 4.0000e-02 eta: 18:35:13 time: 0.2722 data_time: 0.0076 memory: 5828 grad_norm: 3.0846 loss: 2.4619 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4619 2023/06/05 02:20:46 - mmengine - INFO - Epoch(train) [53][ 500/2569] lr: 4.0000e-02 eta: 18:35:08 time: 0.2703 data_time: 0.0072 memory: 5828 grad_norm: 3.0892 loss: 2.3767 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3767 2023/06/05 02:20:51 - mmengine - INFO - Epoch(train) [53][ 520/2569] lr: 4.0000e-02 eta: 18:35:03 time: 0.2649 data_time: 0.0071 memory: 5828 grad_norm: 3.0570 loss: 2.5794 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5794 2023/06/05 02:20:57 - mmengine - INFO - Epoch(train) [53][ 540/2569] lr: 4.0000e-02 eta: 18:34:57 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 3.0918 loss: 2.6053 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6053 2023/06/05 02:21:02 - mmengine - INFO - Epoch(train) [53][ 560/2569] lr: 4.0000e-02 eta: 18:34:52 time: 0.2681 data_time: 0.0074 memory: 5828 grad_norm: 3.1374 loss: 2.3516 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3516 2023/06/05 02:21:07 - mmengine - INFO - Epoch(train) [53][ 580/2569] lr: 4.0000e-02 eta: 18:34:47 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 3.0997 loss: 2.5724 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5724 2023/06/05 02:21:13 - mmengine - INFO - Epoch(train) [53][ 600/2569] lr: 4.0000e-02 eta: 18:34:41 time: 0.2639 data_time: 0.0080 memory: 5828 grad_norm: 3.1045 loss: 2.4534 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4534 2023/06/05 02:21:18 - mmengine - INFO - Epoch(train) [53][ 620/2569] lr: 4.0000e-02 eta: 18:34:36 time: 0.2670 data_time: 0.0077 memory: 5828 grad_norm: 3.0879 loss: 2.5789 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5789 2023/06/05 02:21:23 - mmengine - INFO - Epoch(train) [53][ 640/2569] lr: 4.0000e-02 eta: 18:34:30 time: 0.2601 data_time: 0.0073 memory: 5828 grad_norm: 3.1378 loss: 2.1129 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.1129 2023/06/05 02:21:29 - mmengine - INFO - Epoch(train) [53][ 660/2569] lr: 4.0000e-02 eta: 18:34:25 time: 0.2691 data_time: 0.0072 memory: 5828 grad_norm: 3.0782 loss: 2.3690 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3690 2023/06/05 02:21:34 - mmengine - INFO - Epoch(train) [53][ 680/2569] lr: 4.0000e-02 eta: 18:34:20 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 3.1746 loss: 2.4858 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4858 2023/06/05 02:21:39 - mmengine - INFO - Epoch(train) [53][ 700/2569] lr: 4.0000e-02 eta: 18:34:14 time: 0.2621 data_time: 0.0077 memory: 5828 grad_norm: 3.1395 loss: 2.6523 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6523 2023/06/05 02:21:45 - mmengine - INFO - Epoch(train) [53][ 720/2569] lr: 4.0000e-02 eta: 18:34:09 time: 0.2799 data_time: 0.0073 memory: 5828 grad_norm: 3.1499 loss: 2.6055 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6055 2023/06/05 02:21:50 - mmengine - INFO - Epoch(train) [53][ 740/2569] lr: 4.0000e-02 eta: 18:34:04 time: 0.2575 data_time: 0.0073 memory: 5828 grad_norm: 3.0835 loss: 2.2339 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2339 2023/06/05 02:21:55 - mmengine - INFO - Epoch(train) [53][ 760/2569] lr: 4.0000e-02 eta: 18:33:58 time: 0.2661 data_time: 0.0070 memory: 5828 grad_norm: 3.0718 loss: 2.4885 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4885 2023/06/05 02:22:00 - mmengine - INFO - Epoch(train) [53][ 780/2569] lr: 4.0000e-02 eta: 18:33:53 time: 0.2595 data_time: 0.0075 memory: 5828 grad_norm: 3.1199 loss: 2.7584 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7584 2023/06/05 02:22:06 - mmengine - INFO - Epoch(train) [53][ 800/2569] lr: 4.0000e-02 eta: 18:33:48 time: 0.2675 data_time: 0.0072 memory: 5828 grad_norm: 3.1210 loss: 2.8493 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8493 2023/06/05 02:22:11 - mmengine - INFO - Epoch(train) [53][ 820/2569] lr: 4.0000e-02 eta: 18:33:42 time: 0.2577 data_time: 0.0076 memory: 5828 grad_norm: 3.1585 loss: 2.5241 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5241 2023/06/05 02:22:16 - mmengine - INFO - Epoch(train) [53][ 840/2569] lr: 4.0000e-02 eta: 18:33:36 time: 0.2571 data_time: 0.0077 memory: 5828 grad_norm: 3.0452 loss: 2.5104 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5104 2023/06/05 02:22:21 - mmengine - INFO - Epoch(train) [53][ 860/2569] lr: 4.0000e-02 eta: 18:33:31 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 3.0689 loss: 2.3436 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3436 2023/06/05 02:22:27 - mmengine - INFO - Epoch(train) [53][ 880/2569] lr: 4.0000e-02 eta: 18:33:25 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 3.1425 loss: 2.5691 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5691 2023/06/05 02:22:32 - mmengine - INFO - Epoch(train) [53][ 900/2569] lr: 4.0000e-02 eta: 18:33:20 time: 0.2581 data_time: 0.0080 memory: 5828 grad_norm: 3.0930 loss: 2.5650 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5650 2023/06/05 02:22:37 - mmengine - INFO - Epoch(train) [53][ 920/2569] lr: 4.0000e-02 eta: 18:33:15 time: 0.2700 data_time: 0.0076 memory: 5828 grad_norm: 3.1434 loss: 2.6565 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6565 2023/06/05 02:22:42 - mmengine - INFO - Epoch(train) [53][ 940/2569] lr: 4.0000e-02 eta: 18:33:09 time: 0.2607 data_time: 0.0073 memory: 5828 grad_norm: 3.1100 loss: 2.5037 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5037 2023/06/05 02:22:48 - mmengine - INFO - Epoch(train) [53][ 960/2569] lr: 4.0000e-02 eta: 18:33:04 time: 0.2780 data_time: 0.0072 memory: 5828 grad_norm: 3.0784 loss: 2.6738 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6738 2023/06/05 02:22:53 - mmengine - INFO - Epoch(train) [53][ 980/2569] lr: 4.0000e-02 eta: 18:32:59 time: 0.2573 data_time: 0.0076 memory: 5828 grad_norm: 3.1343 loss: 2.7429 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7429 2023/06/05 02:22:59 - mmengine - INFO - Epoch(train) [53][1000/2569] lr: 4.0000e-02 eta: 18:32:53 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 3.1379 loss: 2.4651 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4651 2023/06/05 02:23:04 - mmengine - INFO - Epoch(train) [53][1020/2569] lr: 4.0000e-02 eta: 18:32:48 time: 0.2697 data_time: 0.0075 memory: 5828 grad_norm: 3.1137 loss: 2.7112 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7112 2023/06/05 02:23:09 - mmengine - INFO - Epoch(train) [53][1040/2569] lr: 4.0000e-02 eta: 18:32:43 time: 0.2629 data_time: 0.0085 memory: 5828 grad_norm: 3.0924 loss: 2.4509 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4509 2023/06/05 02:23:15 - mmengine - INFO - Epoch(train) [53][1060/2569] lr: 4.0000e-02 eta: 18:32:37 time: 0.2659 data_time: 0.0077 memory: 5828 grad_norm: 3.1323 loss: 2.5314 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5314 2023/06/05 02:23:20 - mmengine - INFO - Epoch(train) [53][1080/2569] lr: 4.0000e-02 eta: 18:32:32 time: 0.2633 data_time: 0.0077 memory: 5828 grad_norm: 3.1359 loss: 2.6400 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6400 2023/06/05 02:23:25 - mmengine - INFO - Epoch(train) [53][1100/2569] lr: 4.0000e-02 eta: 18:32:27 time: 0.2650 data_time: 0.0078 memory: 5828 grad_norm: 3.1816 loss: 2.6181 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6181 2023/06/05 02:23:30 - mmengine - INFO - Epoch(train) [53][1120/2569] lr: 4.0000e-02 eta: 18:32:21 time: 0.2577 data_time: 0.0072 memory: 5828 grad_norm: 3.1042 loss: 2.6870 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6870 2023/06/05 02:23:35 - mmengine - INFO - Epoch(train) [53][1140/2569] lr: 4.0000e-02 eta: 18:32:15 time: 0.2610 data_time: 0.0076 memory: 5828 grad_norm: 3.1316 loss: 2.3357 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3357 2023/06/05 02:23:41 - mmengine - INFO - Epoch(train) [53][1160/2569] lr: 4.0000e-02 eta: 18:32:10 time: 0.2583 data_time: 0.0076 memory: 5828 grad_norm: 3.1167 loss: 2.4615 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4615 2023/06/05 02:23:46 - mmengine - INFO - Epoch(train) [53][1180/2569] lr: 4.0000e-02 eta: 18:32:04 time: 0.2635 data_time: 0.0075 memory: 5828 grad_norm: 3.0512 loss: 2.8285 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8285 2023/06/05 02:23:51 - mmengine - INFO - Epoch(train) [53][1200/2569] lr: 4.0000e-02 eta: 18:31:59 time: 0.2591 data_time: 0.0072 memory: 5828 grad_norm: 3.0696 loss: 2.4129 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4129 2023/06/05 02:23:56 - mmengine - INFO - Epoch(train) [53][1220/2569] lr: 4.0000e-02 eta: 18:31:53 time: 0.2613 data_time: 0.0072 memory: 5828 grad_norm: 3.1807 loss: 2.8462 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8462 2023/06/05 02:24:02 - mmengine - INFO - Epoch(train) [53][1240/2569] lr: 4.0000e-02 eta: 18:31:48 time: 0.2582 data_time: 0.0076 memory: 5828 grad_norm: 3.0532 loss: 2.6726 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6726 2023/06/05 02:24:07 - mmengine - INFO - Epoch(train) [53][1260/2569] lr: 4.0000e-02 eta: 18:31:42 time: 0.2679 data_time: 0.0076 memory: 5828 grad_norm: 3.0816 loss: 2.6086 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6086 2023/06/05 02:24:12 - mmengine - INFO - Epoch(train) [53][1280/2569] lr: 4.0000e-02 eta: 18:31:37 time: 0.2576 data_time: 0.0076 memory: 5828 grad_norm: 3.1274 loss: 2.9681 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9681 2023/06/05 02:24:17 - mmengine - INFO - Epoch(train) [53][1300/2569] lr: 4.0000e-02 eta: 18:31:31 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 3.0926 loss: 2.6557 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6557 2023/06/05 02:24:23 - mmengine - INFO - Epoch(train) [53][1320/2569] lr: 4.0000e-02 eta: 18:31:26 time: 0.2578 data_time: 0.0073 memory: 5828 grad_norm: 3.1391 loss: 2.4801 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4801 2023/06/05 02:24:28 - mmengine - INFO - Epoch(train) [53][1340/2569] lr: 4.0000e-02 eta: 18:31:20 time: 0.2580 data_time: 0.0075 memory: 5828 grad_norm: 3.0887 loss: 2.3673 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3673 2023/06/05 02:24:33 - mmengine - INFO - Epoch(train) [53][1360/2569] lr: 4.0000e-02 eta: 18:31:15 time: 0.2649 data_time: 0.0076 memory: 5828 grad_norm: 3.0968 loss: 2.4654 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4654 2023/06/05 02:24:38 - mmengine - INFO - Epoch(train) [53][1380/2569] lr: 4.0000e-02 eta: 18:31:09 time: 0.2628 data_time: 0.0078 memory: 5828 grad_norm: 3.0884 loss: 2.9065 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.9065 2023/06/05 02:24:43 - mmengine - INFO - Epoch(train) [53][1400/2569] lr: 4.0000e-02 eta: 18:31:04 time: 0.2594 data_time: 0.0076 memory: 5828 grad_norm: 3.1176 loss: 2.1361 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1361 2023/06/05 02:24:47 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:24:49 - mmengine - INFO - Epoch(train) [53][1420/2569] lr: 4.0000e-02 eta: 18:30:58 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.1329 loss: 2.6976 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6976 2023/06/05 02:24:54 - mmengine - INFO - Epoch(train) [53][1440/2569] lr: 4.0000e-02 eta: 18:30:53 time: 0.2591 data_time: 0.0079 memory: 5828 grad_norm: 3.1691 loss: 2.5468 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5468 2023/06/05 02:24:59 - mmengine - INFO - Epoch(train) [53][1460/2569] lr: 4.0000e-02 eta: 18:30:47 time: 0.2631 data_time: 0.0070 memory: 5828 grad_norm: 3.1218 loss: 2.4000 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.4000 2023/06/05 02:25:05 - mmengine - INFO - Epoch(train) [53][1480/2569] lr: 4.0000e-02 eta: 18:30:42 time: 0.2690 data_time: 0.0074 memory: 5828 grad_norm: 3.1602 loss: 2.6177 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6177 2023/06/05 02:25:10 - mmengine - INFO - Epoch(train) [53][1500/2569] lr: 4.0000e-02 eta: 18:30:36 time: 0.2585 data_time: 0.0074 memory: 5828 grad_norm: 3.1288 loss: 2.5832 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5832 2023/06/05 02:25:15 - mmengine - INFO - Epoch(train) [53][1520/2569] lr: 4.0000e-02 eta: 18:30:31 time: 0.2658 data_time: 0.0076 memory: 5828 grad_norm: 3.0843 loss: 2.5334 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5334 2023/06/05 02:25:20 - mmengine - INFO - Epoch(train) [53][1540/2569] lr: 4.0000e-02 eta: 18:30:26 time: 0.2632 data_time: 0.0079 memory: 5828 grad_norm: 3.1006 loss: 2.4975 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4975 2023/06/05 02:25:26 - mmengine - INFO - Epoch(train) [53][1560/2569] lr: 4.0000e-02 eta: 18:30:20 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 3.1613 loss: 2.3805 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3805 2023/06/05 02:25:31 - mmengine - INFO - Epoch(train) [53][1580/2569] lr: 4.0000e-02 eta: 18:30:15 time: 0.2613 data_time: 0.0082 memory: 5828 grad_norm: 3.0609 loss: 2.9596 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9596 2023/06/05 02:25:36 - mmengine - INFO - Epoch(train) [53][1600/2569] lr: 4.0000e-02 eta: 18:30:09 time: 0.2629 data_time: 0.0076 memory: 5828 grad_norm: 3.0821 loss: 2.4327 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4327 2023/06/05 02:25:41 - mmengine - INFO - Epoch(train) [53][1620/2569] lr: 4.0000e-02 eta: 18:30:04 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 3.0757 loss: 2.6849 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6849 2023/06/05 02:25:46 - mmengine - INFO - Epoch(train) [53][1640/2569] lr: 4.0000e-02 eta: 18:29:58 time: 0.2561 data_time: 0.0073 memory: 5828 grad_norm: 3.1593 loss: 2.1907 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1907 2023/06/05 02:25:52 - mmengine - INFO - Epoch(train) [53][1660/2569] lr: 4.0000e-02 eta: 18:29:53 time: 0.2627 data_time: 0.0089 memory: 5828 grad_norm: 3.1117 loss: 2.6135 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6135 2023/06/05 02:25:57 - mmengine - INFO - Epoch(train) [53][1680/2569] lr: 4.0000e-02 eta: 18:29:47 time: 0.2565 data_time: 0.0076 memory: 5828 grad_norm: 3.1214 loss: 2.8126 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8126 2023/06/05 02:26:02 - mmengine - INFO - Epoch(train) [53][1700/2569] lr: 4.0000e-02 eta: 18:29:41 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 3.0923 loss: 2.2826 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2826 2023/06/05 02:26:07 - mmengine - INFO - Epoch(train) [53][1720/2569] lr: 4.0000e-02 eta: 18:29:36 time: 0.2680 data_time: 0.0075 memory: 5828 grad_norm: 3.1452 loss: 2.6874 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6874 2023/06/05 02:26:13 - mmengine - INFO - Epoch(train) [53][1740/2569] lr: 4.0000e-02 eta: 18:29:31 time: 0.2617 data_time: 0.0070 memory: 5828 grad_norm: 3.0950 loss: 2.4881 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4881 2023/06/05 02:26:18 - mmengine - INFO - Epoch(train) [53][1760/2569] lr: 4.0000e-02 eta: 18:29:25 time: 0.2579 data_time: 0.0075 memory: 5828 grad_norm: 3.0948 loss: 2.6474 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6474 2023/06/05 02:26:23 - mmengine - INFO - Epoch(train) [53][1780/2569] lr: 4.0000e-02 eta: 18:29:19 time: 0.2587 data_time: 0.0077 memory: 5828 grad_norm: 3.1113 loss: 2.5758 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5758 2023/06/05 02:26:28 - mmengine - INFO - Epoch(train) [53][1800/2569] lr: 4.0000e-02 eta: 18:29:14 time: 0.2632 data_time: 0.0077 memory: 5828 grad_norm: 3.0525 loss: 2.4688 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4688 2023/06/05 02:26:34 - mmengine - INFO - Epoch(train) [53][1820/2569] lr: 4.0000e-02 eta: 18:29:08 time: 0.2601 data_time: 0.0075 memory: 5828 grad_norm: 3.0505 loss: 2.5075 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5075 2023/06/05 02:26:39 - mmengine - INFO - Epoch(train) [53][1840/2569] lr: 4.0000e-02 eta: 18:29:03 time: 0.2596 data_time: 0.0071 memory: 5828 grad_norm: 3.1477 loss: 2.6085 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6085 2023/06/05 02:26:44 - mmengine - INFO - Epoch(train) [53][1860/2569] lr: 4.0000e-02 eta: 18:28:57 time: 0.2615 data_time: 0.0071 memory: 5828 grad_norm: 3.1406 loss: 2.4081 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4081 2023/06/05 02:26:49 - mmengine - INFO - Epoch(train) [53][1880/2569] lr: 4.0000e-02 eta: 18:28:52 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 3.0944 loss: 2.4174 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4174 2023/06/05 02:26:55 - mmengine - INFO - Epoch(train) [53][1900/2569] lr: 4.0000e-02 eta: 18:28:46 time: 0.2675 data_time: 0.0069 memory: 5828 grad_norm: 3.0815 loss: 2.4822 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4822 2023/06/05 02:27:00 - mmengine - INFO - Epoch(train) [53][1920/2569] lr: 4.0000e-02 eta: 18:28:41 time: 0.2595 data_time: 0.0076 memory: 5828 grad_norm: 3.1635 loss: 2.3713 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3713 2023/06/05 02:27:05 - mmengine - INFO - Epoch(train) [53][1940/2569] lr: 4.0000e-02 eta: 18:28:35 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 3.1227 loss: 2.2712 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2712 2023/06/05 02:27:10 - mmengine - INFO - Epoch(train) [53][1960/2569] lr: 4.0000e-02 eta: 18:28:30 time: 0.2550 data_time: 0.0074 memory: 5828 grad_norm: 3.0925 loss: 2.5934 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5934 2023/06/05 02:27:15 - mmengine - INFO - Epoch(train) [53][1980/2569] lr: 4.0000e-02 eta: 18:28:24 time: 0.2624 data_time: 0.0074 memory: 5828 grad_norm: 3.1096 loss: 2.4161 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4161 2023/06/05 02:27:21 - mmengine - INFO - Epoch(train) [53][2000/2569] lr: 4.0000e-02 eta: 18:28:19 time: 0.2666 data_time: 0.0074 memory: 5828 grad_norm: 3.0747 loss: 2.2148 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2148 2023/06/05 02:27:26 - mmengine - INFO - Epoch(train) [53][2020/2569] lr: 4.0000e-02 eta: 18:28:13 time: 0.2599 data_time: 0.0073 memory: 5828 grad_norm: 3.1039 loss: 2.5014 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5014 2023/06/05 02:27:31 - mmengine - INFO - Epoch(train) [53][2040/2569] lr: 4.0000e-02 eta: 18:28:08 time: 0.2569 data_time: 0.0075 memory: 5828 grad_norm: 3.1227 loss: 2.4865 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4865 2023/06/05 02:27:36 - mmengine - INFO - Epoch(train) [53][2060/2569] lr: 4.0000e-02 eta: 18:28:02 time: 0.2634 data_time: 0.0076 memory: 5828 grad_norm: 3.1486 loss: 2.7519 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7519 2023/06/05 02:27:41 - mmengine - INFO - Epoch(train) [53][2080/2569] lr: 4.0000e-02 eta: 18:27:57 time: 0.2572 data_time: 0.0073 memory: 5828 grad_norm: 3.0921 loss: 2.7430 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7430 2023/06/05 02:27:47 - mmengine - INFO - Epoch(train) [53][2100/2569] lr: 4.0000e-02 eta: 18:27:51 time: 0.2705 data_time: 0.0076 memory: 5828 grad_norm: 3.0625 loss: 2.4929 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4929 2023/06/05 02:27:52 - mmengine - INFO - Epoch(train) [53][2120/2569] lr: 4.0000e-02 eta: 18:27:46 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 3.1051 loss: 2.3819 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3819 2023/06/05 02:27:58 - mmengine - INFO - Epoch(train) [53][2140/2569] lr: 4.0000e-02 eta: 18:27:41 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 3.0326 loss: 2.7768 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7768 2023/06/05 02:28:03 - mmengine - INFO - Epoch(train) [53][2160/2569] lr: 4.0000e-02 eta: 18:27:35 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 3.1461 loss: 2.5936 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5936 2023/06/05 02:28:08 - mmengine - INFO - Epoch(train) [53][2180/2569] lr: 4.0000e-02 eta: 18:27:30 time: 0.2570 data_time: 0.0071 memory: 5828 grad_norm: 3.1012 loss: 2.6429 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6429 2023/06/05 02:28:13 - mmengine - INFO - Epoch(train) [53][2200/2569] lr: 4.0000e-02 eta: 18:27:24 time: 0.2695 data_time: 0.0073 memory: 5828 grad_norm: 3.1334 loss: 2.4689 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4689 2023/06/05 02:28:19 - mmengine - INFO - Epoch(train) [53][2220/2569] lr: 4.0000e-02 eta: 18:27:19 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 3.1701 loss: 2.5093 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5093 2023/06/05 02:28:24 - mmengine - INFO - Epoch(train) [53][2240/2569] lr: 4.0000e-02 eta: 18:27:13 time: 0.2631 data_time: 0.0072 memory: 5828 grad_norm: 3.1482 loss: 2.0987 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0987 2023/06/05 02:28:29 - mmengine - INFO - Epoch(train) [53][2260/2569] lr: 4.0000e-02 eta: 18:27:08 time: 0.2596 data_time: 0.0076 memory: 5828 grad_norm: 3.0993 loss: 2.3029 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3029 2023/06/05 02:28:34 - mmengine - INFO - Epoch(train) [53][2280/2569] lr: 4.0000e-02 eta: 18:27:02 time: 0.2608 data_time: 0.0081 memory: 5828 grad_norm: 3.1065 loss: 2.7234 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7234 2023/06/05 02:28:40 - mmengine - INFO - Epoch(train) [53][2300/2569] lr: 4.0000e-02 eta: 18:26:57 time: 0.2705 data_time: 0.0076 memory: 5828 grad_norm: 3.1611 loss: 2.4113 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4113 2023/06/05 02:28:45 - mmengine - INFO - Epoch(train) [53][2320/2569] lr: 4.0000e-02 eta: 18:26:52 time: 0.2583 data_time: 0.0077 memory: 5828 grad_norm: 3.0708 loss: 2.7281 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7281 2023/06/05 02:28:50 - mmengine - INFO - Epoch(train) [53][2340/2569] lr: 4.0000e-02 eta: 18:26:46 time: 0.2687 data_time: 0.0075 memory: 5828 grad_norm: 3.0596 loss: 2.5039 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5039 2023/06/05 02:28:55 - mmengine - INFO - Epoch(train) [53][2360/2569] lr: 4.0000e-02 eta: 18:26:41 time: 0.2623 data_time: 0.0076 memory: 5828 grad_norm: 3.1444 loss: 2.4192 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4192 2023/06/05 02:29:01 - mmengine - INFO - Epoch(train) [53][2380/2569] lr: 4.0000e-02 eta: 18:26:35 time: 0.2562 data_time: 0.0076 memory: 5828 grad_norm: 3.0413 loss: 2.4050 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4050 2023/06/05 02:29:06 - mmengine - INFO - Epoch(train) [53][2400/2569] lr: 4.0000e-02 eta: 18:26:30 time: 0.2696 data_time: 0.0071 memory: 5828 grad_norm: 3.1125 loss: 2.6094 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6094 2023/06/05 02:29:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:29:11 - mmengine - INFO - Epoch(train) [53][2420/2569] lr: 4.0000e-02 eta: 18:26:24 time: 0.2575 data_time: 0.0079 memory: 5828 grad_norm: 3.1631 loss: 2.5099 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5099 2023/06/05 02:29:17 - mmengine - INFO - Epoch(train) [53][2440/2569] lr: 4.0000e-02 eta: 18:26:19 time: 0.2755 data_time: 0.0081 memory: 5828 grad_norm: 3.0827 loss: 2.2151 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2151 2023/06/05 02:29:22 - mmengine - INFO - Epoch(train) [53][2460/2569] lr: 4.0000e-02 eta: 18:26:14 time: 0.2627 data_time: 0.0079 memory: 5828 grad_norm: 3.1351 loss: 2.5447 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5447 2023/06/05 02:29:27 - mmengine - INFO - Epoch(train) [53][2480/2569] lr: 4.0000e-02 eta: 18:26:09 time: 0.2686 data_time: 0.0074 memory: 5828 grad_norm: 3.1102 loss: 2.4801 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4801 2023/06/05 02:29:33 - mmengine - INFO - Epoch(train) [53][2500/2569] lr: 4.0000e-02 eta: 18:26:03 time: 0.2673 data_time: 0.0078 memory: 5828 grad_norm: 3.1015 loss: 2.4047 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4047 2023/06/05 02:29:38 - mmengine - INFO - Epoch(train) [53][2520/2569] lr: 4.0000e-02 eta: 18:25:58 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 3.0564 loss: 2.8058 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8058 2023/06/05 02:29:43 - mmengine - INFO - Epoch(train) [53][2540/2569] lr: 4.0000e-02 eta: 18:25:52 time: 0.2577 data_time: 0.0073 memory: 5828 grad_norm: 3.1923 loss: 2.9933 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.9933 2023/06/05 02:29:48 - mmengine - INFO - Epoch(train) [53][2560/2569] lr: 4.0000e-02 eta: 18:25:47 time: 0.2631 data_time: 0.0076 memory: 5828 grad_norm: 3.0348 loss: 2.0579 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0579 2023/06/05 02:29:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:29:51 - mmengine - INFO - Epoch(train) [53][2569/2569] lr: 4.0000e-02 eta: 18:25:44 time: 0.2538 data_time: 0.0073 memory: 5828 grad_norm: 3.0847 loss: 2.3991 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.3991 2023/06/05 02:29:58 - mmengine - INFO - Epoch(train) [54][ 20/2569] lr: 4.0000e-02 eta: 18:25:42 time: 0.3447 data_time: 0.0590 memory: 5828 grad_norm: 3.0926 loss: 2.5988 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5988 2023/06/05 02:30:03 - mmengine - INFO - Epoch(train) [54][ 40/2569] lr: 4.0000e-02 eta: 18:25:36 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 3.1344 loss: 2.6546 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6546 2023/06/05 02:30:08 - mmengine - INFO - Epoch(train) [54][ 60/2569] lr: 4.0000e-02 eta: 18:25:31 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 3.0853 loss: 2.6755 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6755 2023/06/05 02:30:13 - mmengine - INFO - Epoch(train) [54][ 80/2569] lr: 4.0000e-02 eta: 18:25:25 time: 0.2584 data_time: 0.0076 memory: 5828 grad_norm: 3.1129 loss: 2.5159 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5159 2023/06/05 02:30:19 - mmengine - INFO - Epoch(train) [54][ 100/2569] lr: 4.0000e-02 eta: 18:25:20 time: 0.2621 data_time: 0.0072 memory: 5828 grad_norm: 3.1119 loss: 3.0347 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0347 2023/06/05 02:30:24 - mmengine - INFO - Epoch(train) [54][ 120/2569] lr: 4.0000e-02 eta: 18:25:14 time: 0.2580 data_time: 0.0077 memory: 5828 grad_norm: 3.1116 loss: 2.3054 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3054 2023/06/05 02:30:29 - mmengine - INFO - Epoch(train) [54][ 140/2569] lr: 4.0000e-02 eta: 18:25:09 time: 0.2722 data_time: 0.0073 memory: 5828 grad_norm: 3.0740 loss: 2.7423 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7423 2023/06/05 02:30:35 - mmengine - INFO - Epoch(train) [54][ 160/2569] lr: 4.0000e-02 eta: 18:25:04 time: 0.2718 data_time: 0.0070 memory: 5828 grad_norm: 3.0821 loss: 2.3431 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3431 2023/06/05 02:30:40 - mmengine - INFO - Epoch(train) [54][ 180/2569] lr: 4.0000e-02 eta: 18:24:59 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 3.1214 loss: 2.8026 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8026 2023/06/05 02:30:45 - mmengine - INFO - Epoch(train) [54][ 200/2569] lr: 4.0000e-02 eta: 18:24:53 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 3.1111 loss: 2.6369 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6369 2023/06/05 02:30:50 - mmengine - INFO - Epoch(train) [54][ 220/2569] lr: 4.0000e-02 eta: 18:24:48 time: 0.2599 data_time: 0.0073 memory: 5828 grad_norm: 3.1602 loss: 2.5142 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5142 2023/06/05 02:30:55 - mmengine - INFO - Epoch(train) [54][ 240/2569] lr: 4.0000e-02 eta: 18:24:42 time: 0.2577 data_time: 0.0075 memory: 5828 grad_norm: 3.0668 loss: 2.4768 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4768 2023/06/05 02:31:01 - mmengine - INFO - Epoch(train) [54][ 260/2569] lr: 4.0000e-02 eta: 18:24:37 time: 0.2646 data_time: 0.0074 memory: 5828 grad_norm: 3.1371 loss: 2.5604 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5604 2023/06/05 02:31:06 - mmengine - INFO - Epoch(train) [54][ 280/2569] lr: 4.0000e-02 eta: 18:24:31 time: 0.2625 data_time: 0.0078 memory: 5828 grad_norm: 3.0771 loss: 2.3654 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3654 2023/06/05 02:31:11 - mmengine - INFO - Epoch(train) [54][ 300/2569] lr: 4.0000e-02 eta: 18:24:26 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 3.1179 loss: 2.3178 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3178 2023/06/05 02:31:17 - mmengine - INFO - Epoch(train) [54][ 320/2569] lr: 4.0000e-02 eta: 18:24:20 time: 0.2583 data_time: 0.0081 memory: 5828 grad_norm: 3.0760 loss: 2.2166 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2166 2023/06/05 02:31:22 - mmengine - INFO - Epoch(train) [54][ 340/2569] lr: 4.0000e-02 eta: 18:24:15 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 3.1566 loss: 2.4304 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4304 2023/06/05 02:31:27 - mmengine - INFO - Epoch(train) [54][ 360/2569] lr: 4.0000e-02 eta: 18:24:09 time: 0.2564 data_time: 0.0074 memory: 5828 grad_norm: 3.1520 loss: 2.5648 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5648 2023/06/05 02:31:33 - mmengine - INFO - Epoch(train) [54][ 380/2569] lr: 4.0000e-02 eta: 18:24:06 time: 0.3297 data_time: 0.0076 memory: 5828 grad_norm: 3.1257 loss: 2.3561 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3561 2023/06/05 02:31:39 - mmengine - INFO - Epoch(train) [54][ 400/2569] lr: 4.0000e-02 eta: 18:24:01 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 3.1233 loss: 2.8134 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.8134 2023/06/05 02:31:44 - mmengine - INFO - Epoch(train) [54][ 420/2569] lr: 4.0000e-02 eta: 18:23:55 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 3.1644 loss: 2.8258 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8258 2023/06/05 02:31:50 - mmengine - INFO - Epoch(train) [54][ 440/2569] lr: 4.0000e-02 eta: 18:23:50 time: 0.2777 data_time: 0.0073 memory: 5828 grad_norm: 3.1021 loss: 2.7263 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7263 2023/06/05 02:31:55 - mmengine - INFO - Epoch(train) [54][ 460/2569] lr: 4.0000e-02 eta: 18:23:45 time: 0.2581 data_time: 0.0074 memory: 5828 grad_norm: 3.1252 loss: 2.7604 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7604 2023/06/05 02:32:00 - mmengine - INFO - Epoch(train) [54][ 480/2569] lr: 4.0000e-02 eta: 18:23:39 time: 0.2604 data_time: 0.0073 memory: 5828 grad_norm: 3.1030 loss: 2.6219 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6219 2023/06/05 02:32:05 - mmengine - INFO - Epoch(train) [54][ 500/2569] lr: 4.0000e-02 eta: 18:23:34 time: 0.2571 data_time: 0.0071 memory: 5828 grad_norm: 3.0773 loss: 2.2935 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2935 2023/06/05 02:32:10 - mmengine - INFO - Epoch(train) [54][ 520/2569] lr: 4.0000e-02 eta: 18:23:28 time: 0.2582 data_time: 0.0073 memory: 5828 grad_norm: 3.0486 loss: 2.7519 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.7519 2023/06/05 02:32:16 - mmengine - INFO - Epoch(train) [54][ 540/2569] lr: 4.0000e-02 eta: 18:23:22 time: 0.2605 data_time: 0.0071 memory: 5828 grad_norm: 3.1269 loss: 2.6913 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6913 2023/06/05 02:32:21 - mmengine - INFO - Epoch(train) [54][ 560/2569] lr: 4.0000e-02 eta: 18:23:17 time: 0.2668 data_time: 0.0077 memory: 5828 grad_norm: 3.0719 loss: 2.5180 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5180 2023/06/05 02:32:26 - mmengine - INFO - Epoch(train) [54][ 580/2569] lr: 4.0000e-02 eta: 18:23:12 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 3.0893 loss: 2.8173 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8173 2023/06/05 02:32:31 - mmengine - INFO - Epoch(train) [54][ 600/2569] lr: 4.0000e-02 eta: 18:23:06 time: 0.2620 data_time: 0.0079 memory: 5828 grad_norm: 3.1666 loss: 2.6036 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6036 2023/06/05 02:32:37 - mmengine - INFO - Epoch(train) [54][ 620/2569] lr: 4.0000e-02 eta: 18:23:01 time: 0.2633 data_time: 0.0073 memory: 5828 grad_norm: 3.1030 loss: 2.7114 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7114 2023/06/05 02:32:42 - mmengine - INFO - Epoch(train) [54][ 640/2569] lr: 4.0000e-02 eta: 18:22:55 time: 0.2585 data_time: 0.0077 memory: 5828 grad_norm: 3.1706 loss: 2.4717 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4717 2023/06/05 02:32:47 - mmengine - INFO - Epoch(train) [54][ 660/2569] lr: 4.0000e-02 eta: 18:22:50 time: 0.2615 data_time: 0.0069 memory: 5828 grad_norm: 3.0685 loss: 2.4450 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4450 2023/06/05 02:32:52 - mmengine - INFO - Epoch(train) [54][ 680/2569] lr: 4.0000e-02 eta: 18:22:44 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 3.1541 loss: 2.8298 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8298 2023/06/05 02:32:58 - mmengine - INFO - Epoch(train) [54][ 700/2569] lr: 4.0000e-02 eta: 18:22:39 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 3.0779 loss: 2.6643 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6643 2023/06/05 02:33:03 - mmengine - INFO - Epoch(train) [54][ 720/2569] lr: 4.0000e-02 eta: 18:22:33 time: 0.2623 data_time: 0.0078 memory: 5828 grad_norm: 3.0889 loss: 2.6739 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6739 2023/06/05 02:33:08 - mmengine - INFO - Epoch(train) [54][ 740/2569] lr: 4.0000e-02 eta: 18:22:28 time: 0.2659 data_time: 0.0069 memory: 5828 grad_norm: 3.0727 loss: 2.4817 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4817 2023/06/05 02:33:13 - mmengine - INFO - Epoch(train) [54][ 760/2569] lr: 4.0000e-02 eta: 18:22:22 time: 0.2573 data_time: 0.0078 memory: 5828 grad_norm: 3.1642 loss: 2.5806 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5806 2023/06/05 02:33:19 - mmengine - INFO - Epoch(train) [54][ 780/2569] lr: 4.0000e-02 eta: 18:22:17 time: 0.2583 data_time: 0.0072 memory: 5828 grad_norm: 3.1058 loss: 2.6025 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6025 2023/06/05 02:33:24 - mmengine - INFO - Epoch(train) [54][ 800/2569] lr: 4.0000e-02 eta: 18:22:11 time: 0.2687 data_time: 0.0081 memory: 5828 grad_norm: 3.1158 loss: 2.3688 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3688 2023/06/05 02:33:29 - mmengine - INFO - Epoch(train) [54][ 820/2569] lr: 4.0000e-02 eta: 18:22:06 time: 0.2574 data_time: 0.0080 memory: 5828 grad_norm: 3.0738 loss: 2.7279 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7279 2023/06/05 02:33:34 - mmengine - INFO - Epoch(train) [54][ 840/2569] lr: 4.0000e-02 eta: 18:22:01 time: 0.2704 data_time: 0.0075 memory: 5828 grad_norm: 3.1256 loss: 2.7941 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7941 2023/06/05 02:33:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:33:40 - mmengine - INFO - Epoch(train) [54][ 860/2569] lr: 4.0000e-02 eta: 18:21:55 time: 0.2657 data_time: 0.0074 memory: 5828 grad_norm: 3.0697 loss: 2.6096 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6096 2023/06/05 02:33:45 - mmengine - INFO - Epoch(train) [54][ 880/2569] lr: 4.0000e-02 eta: 18:21:50 time: 0.2579 data_time: 0.0073 memory: 5828 grad_norm: 3.0973 loss: 2.6961 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6961 2023/06/05 02:33:50 - mmengine - INFO - Epoch(train) [54][ 900/2569] lr: 4.0000e-02 eta: 18:21:44 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 3.1415 loss: 2.6180 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6180 2023/06/05 02:33:56 - mmengine - INFO - Epoch(train) [54][ 920/2569] lr: 4.0000e-02 eta: 18:21:39 time: 0.2654 data_time: 0.0077 memory: 5828 grad_norm: 3.0985 loss: 2.5460 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5460 2023/06/05 02:34:01 - mmengine - INFO - Epoch(train) [54][ 940/2569] lr: 4.0000e-02 eta: 18:21:34 time: 0.2646 data_time: 0.0091 memory: 5828 grad_norm: 3.1554 loss: 2.8127 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8127 2023/06/05 02:34:06 - mmengine - INFO - Epoch(train) [54][ 960/2569] lr: 4.0000e-02 eta: 18:21:28 time: 0.2587 data_time: 0.0081 memory: 5828 grad_norm: 3.1304 loss: 2.3382 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3382 2023/06/05 02:34:11 - mmengine - INFO - Epoch(train) [54][ 980/2569] lr: 4.0000e-02 eta: 18:21:23 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.1579 loss: 2.5641 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5641 2023/06/05 02:34:16 - mmengine - INFO - Epoch(train) [54][1000/2569] lr: 4.0000e-02 eta: 18:21:17 time: 0.2568 data_time: 0.0073 memory: 5828 grad_norm: 3.1520 loss: 2.8774 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8774 2023/06/05 02:34:22 - mmengine - INFO - Epoch(train) [54][1020/2569] lr: 4.0000e-02 eta: 18:21:11 time: 0.2630 data_time: 0.0076 memory: 5828 grad_norm: 3.1218 loss: 2.3997 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3997 2023/06/05 02:34:27 - mmengine - INFO - Epoch(train) [54][1040/2569] lr: 4.0000e-02 eta: 18:21:06 time: 0.2578 data_time: 0.0073 memory: 5828 grad_norm: 3.1513 loss: 2.5977 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5977 2023/06/05 02:34:32 - mmengine - INFO - Epoch(train) [54][1060/2569] lr: 4.0000e-02 eta: 18:21:00 time: 0.2632 data_time: 0.0077 memory: 5828 grad_norm: 3.1019 loss: 2.4176 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.4176 2023/06/05 02:34:37 - mmengine - INFO - Epoch(train) [54][1080/2569] lr: 4.0000e-02 eta: 18:20:55 time: 0.2577 data_time: 0.0078 memory: 5828 grad_norm: 3.0508 loss: 2.3753 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3753 2023/06/05 02:34:43 - mmengine - INFO - Epoch(train) [54][1100/2569] lr: 4.0000e-02 eta: 18:20:49 time: 0.2630 data_time: 0.0079 memory: 5828 grad_norm: 3.0845 loss: 2.6142 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6142 2023/06/05 02:34:48 - mmengine - INFO - Epoch(train) [54][1120/2569] lr: 4.0000e-02 eta: 18:20:44 time: 0.2578 data_time: 0.0073 memory: 5828 grad_norm: 3.0929 loss: 2.6024 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6024 2023/06/05 02:34:53 - mmengine - INFO - Epoch(train) [54][1140/2569] lr: 4.0000e-02 eta: 18:20:38 time: 0.2605 data_time: 0.0074 memory: 5828 grad_norm: 3.1321 loss: 2.8285 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8285 2023/06/05 02:34:58 - mmengine - INFO - Epoch(train) [54][1160/2569] lr: 4.0000e-02 eta: 18:20:33 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 3.1464 loss: 2.3947 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3947 2023/06/05 02:35:04 - mmengine - INFO - Epoch(train) [54][1180/2569] lr: 4.0000e-02 eta: 18:20:27 time: 0.2621 data_time: 0.0083 memory: 5828 grad_norm: 3.0659 loss: 2.4169 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4169 2023/06/05 02:35:09 - mmengine - INFO - Epoch(train) [54][1200/2569] lr: 4.0000e-02 eta: 18:20:22 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 3.1615 loss: 2.7596 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.7596 2023/06/05 02:35:14 - mmengine - INFO - Epoch(train) [54][1220/2569] lr: 4.0000e-02 eta: 18:20:16 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.1001 loss: 2.6283 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6283 2023/06/05 02:35:19 - mmengine - INFO - Epoch(train) [54][1240/2569] lr: 4.0000e-02 eta: 18:20:11 time: 0.2671 data_time: 0.0076 memory: 5828 grad_norm: 3.1514 loss: 2.6663 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6663 2023/06/05 02:35:25 - mmengine - INFO - Epoch(train) [54][1260/2569] lr: 4.0000e-02 eta: 18:20:06 time: 0.2679 data_time: 0.0075 memory: 5828 grad_norm: 3.0753 loss: 2.1394 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1394 2023/06/05 02:35:30 - mmengine - INFO - Epoch(train) [54][1280/2569] lr: 4.0000e-02 eta: 18:20:00 time: 0.2604 data_time: 0.0075 memory: 5828 grad_norm: 3.1393 loss: 2.4452 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4452 2023/06/05 02:35:35 - mmengine - INFO - Epoch(train) [54][1300/2569] lr: 4.0000e-02 eta: 18:19:55 time: 0.2616 data_time: 0.0077 memory: 5828 grad_norm: 3.0807 loss: 2.9045 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9045 2023/06/05 02:35:40 - mmengine - INFO - Epoch(train) [54][1320/2569] lr: 4.0000e-02 eta: 18:19:49 time: 0.2624 data_time: 0.0077 memory: 5828 grad_norm: 3.0907 loss: 2.7228 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7228 2023/06/05 02:35:46 - mmengine - INFO - Epoch(train) [54][1340/2569] lr: 4.0000e-02 eta: 18:19:44 time: 0.2582 data_time: 0.0074 memory: 5828 grad_norm: 3.1604 loss: 2.2577 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2577 2023/06/05 02:35:51 - mmengine - INFO - Epoch(train) [54][1360/2569] lr: 4.0000e-02 eta: 18:19:38 time: 0.2574 data_time: 0.0076 memory: 5828 grad_norm: 3.1101 loss: 2.4541 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4541 2023/06/05 02:35:56 - mmengine - INFO - Epoch(train) [54][1380/2569] lr: 4.0000e-02 eta: 18:19:33 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 3.0837 loss: 2.8540 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8540 2023/06/05 02:36:01 - mmengine - INFO - Epoch(train) [54][1400/2569] lr: 4.0000e-02 eta: 18:19:27 time: 0.2564 data_time: 0.0072 memory: 5828 grad_norm: 3.0882 loss: 2.4602 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4602 2023/06/05 02:36:06 - mmengine - INFO - Epoch(train) [54][1420/2569] lr: 4.0000e-02 eta: 18:19:21 time: 0.2579 data_time: 0.0070 memory: 5828 grad_norm: 3.0465 loss: 2.5654 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5654 2023/06/05 02:36:12 - mmengine - INFO - Epoch(train) [54][1440/2569] lr: 4.0000e-02 eta: 18:19:16 time: 0.2637 data_time: 0.0076 memory: 5828 grad_norm: 3.1138 loss: 2.8885 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8885 2023/06/05 02:36:17 - mmengine - INFO - Epoch(train) [54][1460/2569] lr: 4.0000e-02 eta: 18:19:10 time: 0.2577 data_time: 0.0073 memory: 5828 grad_norm: 3.0936 loss: 2.7567 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7567 2023/06/05 02:36:22 - mmengine - INFO - Epoch(train) [54][1480/2569] lr: 4.0000e-02 eta: 18:19:05 time: 0.2662 data_time: 0.0071 memory: 5828 grad_norm: 3.1315 loss: 2.5146 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5146 2023/06/05 02:36:27 - mmengine - INFO - Epoch(train) [54][1500/2569] lr: 4.0000e-02 eta: 18:18:59 time: 0.2572 data_time: 0.0074 memory: 5828 grad_norm: 3.0946 loss: 2.2812 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2812 2023/06/05 02:36:33 - mmengine - INFO - Epoch(train) [54][1520/2569] lr: 4.0000e-02 eta: 18:18:54 time: 0.2634 data_time: 0.0076 memory: 5828 grad_norm: 3.1392 loss: 2.7151 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7151 2023/06/05 02:36:38 - mmengine - INFO - Epoch(train) [54][1540/2569] lr: 4.0000e-02 eta: 18:18:48 time: 0.2631 data_time: 0.0072 memory: 5828 grad_norm: 3.0975 loss: 2.7244 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7244 2023/06/05 02:36:43 - mmengine - INFO - Epoch(train) [54][1560/2569] lr: 4.0000e-02 eta: 18:18:43 time: 0.2645 data_time: 0.0082 memory: 5828 grad_norm: 3.1266 loss: 2.6512 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6512 2023/06/05 02:36:49 - mmengine - INFO - Epoch(train) [54][1580/2569] lr: 4.0000e-02 eta: 18:18:38 time: 0.2727 data_time: 0.0077 memory: 5828 grad_norm: 3.0685 loss: 2.7617 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7617 2023/06/05 02:36:54 - mmengine - INFO - Epoch(train) [54][1600/2569] lr: 4.0000e-02 eta: 18:18:33 time: 0.2629 data_time: 0.0071 memory: 5828 grad_norm: 3.1068 loss: 2.5070 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5070 2023/06/05 02:36:59 - mmengine - INFO - Epoch(train) [54][1620/2569] lr: 4.0000e-02 eta: 18:18:27 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 3.0899 loss: 2.4071 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4071 2023/06/05 02:37:04 - mmengine - INFO - Epoch(train) [54][1640/2569] lr: 4.0000e-02 eta: 18:18:22 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 3.0659 loss: 2.6066 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6066 2023/06/05 02:37:10 - mmengine - INFO - Epoch(train) [54][1660/2569] lr: 4.0000e-02 eta: 18:18:16 time: 0.2670 data_time: 0.0070 memory: 5828 grad_norm: 3.0465 loss: 2.3735 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3735 2023/06/05 02:37:15 - mmengine - INFO - Epoch(train) [54][1680/2569] lr: 4.0000e-02 eta: 18:18:11 time: 0.2653 data_time: 0.0075 memory: 5828 grad_norm: 3.0818 loss: 2.3246 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3246 2023/06/05 02:37:20 - mmengine - INFO - Epoch(train) [54][1700/2569] lr: 4.0000e-02 eta: 18:18:05 time: 0.2631 data_time: 0.0075 memory: 5828 grad_norm: 3.1703 loss: 2.4882 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4882 2023/06/05 02:37:25 - mmengine - INFO - Epoch(train) [54][1720/2569] lr: 4.0000e-02 eta: 18:18:00 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 3.0535 loss: 2.4201 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4201 2023/06/05 02:37:31 - mmengine - INFO - Epoch(train) [54][1740/2569] lr: 4.0000e-02 eta: 18:17:54 time: 0.2574 data_time: 0.0073 memory: 5828 grad_norm: 3.0801 loss: 2.3743 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3743 2023/06/05 02:37:36 - mmengine - INFO - Epoch(train) [54][1760/2569] lr: 4.0000e-02 eta: 18:17:49 time: 0.2633 data_time: 0.0072 memory: 5828 grad_norm: 3.1678 loss: 2.3826 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3826 2023/06/05 02:37:41 - mmengine - INFO - Epoch(train) [54][1780/2569] lr: 4.0000e-02 eta: 18:17:43 time: 0.2566 data_time: 0.0078 memory: 5828 grad_norm: 3.0415 loss: 2.7045 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7045 2023/06/05 02:37:46 - mmengine - INFO - Epoch(train) [54][1800/2569] lr: 4.0000e-02 eta: 18:17:38 time: 0.2626 data_time: 0.0073 memory: 5828 grad_norm: 3.1567 loss: 2.5730 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5730 2023/06/05 02:37:52 - mmengine - INFO - Epoch(train) [54][1820/2569] lr: 4.0000e-02 eta: 18:17:32 time: 0.2636 data_time: 0.0069 memory: 5828 grad_norm: 3.0902 loss: 2.4634 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4634 2023/06/05 02:37:57 - mmengine - INFO - Epoch(train) [54][1840/2569] lr: 4.0000e-02 eta: 18:17:27 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 3.1093 loss: 2.7766 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7766 2023/06/05 02:37:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:38:02 - mmengine - INFO - Epoch(train) [54][1860/2569] lr: 4.0000e-02 eta: 18:17:21 time: 0.2616 data_time: 0.0071 memory: 5828 grad_norm: 3.1125 loss: 2.8092 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8092 2023/06/05 02:38:08 - mmengine - INFO - Epoch(train) [54][1880/2569] lr: 4.0000e-02 eta: 18:17:16 time: 0.2724 data_time: 0.0072 memory: 5828 grad_norm: 3.1368 loss: 2.8984 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8984 2023/06/05 02:38:13 - mmengine - INFO - Epoch(train) [54][1900/2569] lr: 4.0000e-02 eta: 18:17:11 time: 0.2599 data_time: 0.0074 memory: 5828 grad_norm: 3.1043 loss: 2.3890 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3890 2023/06/05 02:38:18 - mmengine - INFO - Epoch(train) [54][1920/2569] lr: 4.0000e-02 eta: 18:17:05 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 3.1560 loss: 2.6570 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6570 2023/06/05 02:38:23 - mmengine - INFO - Epoch(train) [54][1940/2569] lr: 4.0000e-02 eta: 18:17:00 time: 0.2567 data_time: 0.0072 memory: 5828 grad_norm: 3.1118 loss: 2.5542 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5542 2023/06/05 02:38:28 - mmengine - INFO - Epoch(train) [54][1960/2569] lr: 4.0000e-02 eta: 18:16:54 time: 0.2689 data_time: 0.0071 memory: 5828 grad_norm: 3.1009 loss: 2.4578 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4578 2023/06/05 02:38:34 - mmengine - INFO - Epoch(train) [54][1980/2569] lr: 4.0000e-02 eta: 18:16:49 time: 0.2563 data_time: 0.0069 memory: 5828 grad_norm: 3.1040 loss: 2.3300 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3300 2023/06/05 02:38:39 - mmengine - INFO - Epoch(train) [54][2000/2569] lr: 4.0000e-02 eta: 18:16:43 time: 0.2573 data_time: 0.0076 memory: 5828 grad_norm: 3.0658 loss: 2.4858 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4858 2023/06/05 02:38:44 - mmengine - INFO - Epoch(train) [54][2020/2569] lr: 4.0000e-02 eta: 18:16:37 time: 0.2573 data_time: 0.0078 memory: 5828 grad_norm: 3.0642 loss: 2.6209 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6209 2023/06/05 02:38:49 - mmengine - INFO - Epoch(train) [54][2040/2569] lr: 4.0000e-02 eta: 18:16:32 time: 0.2629 data_time: 0.0075 memory: 5828 grad_norm: 3.1013 loss: 2.7332 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7332 2023/06/05 02:38:55 - mmengine - INFO - Epoch(train) [54][2060/2569] lr: 4.0000e-02 eta: 18:16:27 time: 0.2749 data_time: 0.0076 memory: 5828 grad_norm: 3.0968 loss: 2.7830 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7830 2023/06/05 02:39:00 - mmengine - INFO - Epoch(train) [54][2080/2569] lr: 4.0000e-02 eta: 18:16:21 time: 0.2596 data_time: 0.0078 memory: 5828 grad_norm: 3.0623 loss: 2.3707 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3707 2023/06/05 02:39:05 - mmengine - INFO - Epoch(train) [54][2100/2569] lr: 4.0000e-02 eta: 18:16:16 time: 0.2695 data_time: 0.0071 memory: 5828 grad_norm: 3.1208 loss: 2.6671 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6671 2023/06/05 02:39:10 - mmengine - INFO - Epoch(train) [54][2120/2569] lr: 4.0000e-02 eta: 18:16:11 time: 0.2576 data_time: 0.0076 memory: 5828 grad_norm: 3.1414 loss: 2.3488 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3488 2023/06/05 02:39:16 - mmengine - INFO - Epoch(train) [54][2140/2569] lr: 4.0000e-02 eta: 18:16:05 time: 0.2592 data_time: 0.0075 memory: 5828 grad_norm: 3.1209 loss: 2.4736 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4736 2023/06/05 02:39:21 - mmengine - INFO - Epoch(train) [54][2160/2569] lr: 4.0000e-02 eta: 18:15:59 time: 0.2589 data_time: 0.0076 memory: 5828 grad_norm: 3.0696 loss: 2.7561 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7561 2023/06/05 02:39:26 - mmengine - INFO - Epoch(train) [54][2180/2569] lr: 4.0000e-02 eta: 18:15:54 time: 0.2646 data_time: 0.0078 memory: 5828 grad_norm: 3.0839 loss: 2.1550 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1550 2023/06/05 02:39:31 - mmengine - INFO - Epoch(train) [54][2200/2569] lr: 4.0000e-02 eta: 18:15:49 time: 0.2612 data_time: 0.0076 memory: 5828 grad_norm: 3.1106 loss: 2.5776 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5776 2023/06/05 02:39:37 - mmengine - INFO - Epoch(train) [54][2220/2569] lr: 4.0000e-02 eta: 18:15:43 time: 0.2705 data_time: 0.0080 memory: 5828 grad_norm: 3.0772 loss: 2.6325 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6325 2023/06/05 02:39:42 - mmengine - INFO - Epoch(train) [54][2240/2569] lr: 4.0000e-02 eta: 18:15:38 time: 0.2564 data_time: 0.0073 memory: 5828 grad_norm: 3.1286 loss: 2.7316 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7316 2023/06/05 02:39:47 - mmengine - INFO - Epoch(train) [54][2260/2569] lr: 4.0000e-02 eta: 18:15:32 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.1410 loss: 2.5870 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5870 2023/06/05 02:39:52 - mmengine - INFO - Epoch(train) [54][2280/2569] lr: 4.0000e-02 eta: 18:15:27 time: 0.2585 data_time: 0.0076 memory: 5828 grad_norm: 3.0495 loss: 2.7592 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7592 2023/06/05 02:39:58 - mmengine - INFO - Epoch(train) [54][2300/2569] lr: 4.0000e-02 eta: 18:15:21 time: 0.2630 data_time: 0.0086 memory: 5828 grad_norm: 3.1143 loss: 2.7643 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7643 2023/06/05 02:40:03 - mmengine - INFO - Epoch(train) [54][2320/2569] lr: 4.0000e-02 eta: 18:15:16 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 3.1116 loss: 2.5853 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5853 2023/06/05 02:40:08 - mmengine - INFO - Epoch(train) [54][2340/2569] lr: 4.0000e-02 eta: 18:15:10 time: 0.2586 data_time: 0.0071 memory: 5828 grad_norm: 3.1473 loss: 2.5403 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5403 2023/06/05 02:40:13 - mmengine - INFO - Epoch(train) [54][2360/2569] lr: 4.0000e-02 eta: 18:15:05 time: 0.2697 data_time: 0.0072 memory: 5828 grad_norm: 3.1284 loss: 2.1875 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1875 2023/06/05 02:40:19 - mmengine - INFO - Epoch(train) [54][2380/2569] lr: 4.0000e-02 eta: 18:15:00 time: 0.2628 data_time: 0.0078 memory: 5828 grad_norm: 3.1626 loss: 2.5899 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5899 2023/06/05 02:40:24 - mmengine - INFO - Epoch(train) [54][2400/2569] lr: 4.0000e-02 eta: 18:14:54 time: 0.2690 data_time: 0.0066 memory: 5828 grad_norm: 3.0738 loss: 2.5024 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5024 2023/06/05 02:40:29 - mmengine - INFO - Epoch(train) [54][2420/2569] lr: 4.0000e-02 eta: 18:14:49 time: 0.2577 data_time: 0.0069 memory: 5828 grad_norm: 3.0426 loss: 2.1803 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1803 2023/06/05 02:40:35 - mmengine - INFO - Epoch(train) [54][2440/2569] lr: 4.0000e-02 eta: 18:14:43 time: 0.2644 data_time: 0.0076 memory: 5828 grad_norm: 3.0929 loss: 2.7647 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7647 2023/06/05 02:40:40 - mmengine - INFO - Epoch(train) [54][2460/2569] lr: 4.0000e-02 eta: 18:14:38 time: 0.2630 data_time: 0.0072 memory: 5828 grad_norm: 3.0468 loss: 2.4397 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4397 2023/06/05 02:40:45 - mmengine - INFO - Epoch(train) [54][2480/2569] lr: 4.0000e-02 eta: 18:14:32 time: 0.2569 data_time: 0.0074 memory: 5828 grad_norm: 3.1295 loss: 2.4645 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4645 2023/06/05 02:40:50 - mmengine - INFO - Epoch(train) [54][2500/2569] lr: 4.0000e-02 eta: 18:14:27 time: 0.2732 data_time: 0.0073 memory: 5828 grad_norm: 3.1296 loss: 2.3125 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3125 2023/06/05 02:40:56 - mmengine - INFO - Epoch(train) [54][2520/2569] lr: 4.0000e-02 eta: 18:14:22 time: 0.2678 data_time: 0.0074 memory: 5828 grad_norm: 3.1157 loss: 2.6983 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6983 2023/06/05 02:41:01 - mmengine - INFO - Epoch(train) [54][2540/2569] lr: 4.0000e-02 eta: 18:14:16 time: 0.2605 data_time: 0.0076 memory: 5828 grad_norm: 3.0753 loss: 2.9770 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9770 2023/06/05 02:41:06 - mmengine - INFO - Epoch(train) [54][2560/2569] lr: 4.0000e-02 eta: 18:14:11 time: 0.2601 data_time: 0.0073 memory: 5828 grad_norm: 3.1211 loss: 2.4449 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4449 2023/06/05 02:41:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:41:09 - mmengine - INFO - Epoch(train) [54][2569/2569] lr: 4.0000e-02 eta: 18:14:08 time: 0.2599 data_time: 0.0071 memory: 5828 grad_norm: 3.1152 loss: 2.2985 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.2985 2023/06/05 02:41:15 - mmengine - INFO - Epoch(train) [55][ 20/2569] lr: 4.0000e-02 eta: 18:14:05 time: 0.3330 data_time: 0.0515 memory: 5828 grad_norm: 3.0840 loss: 2.3367 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3367 2023/06/05 02:41:20 - mmengine - INFO - Epoch(train) [55][ 40/2569] lr: 4.0000e-02 eta: 18:14:00 time: 0.2619 data_time: 0.0075 memory: 5828 grad_norm: 3.0909 loss: 2.3889 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3889 2023/06/05 02:41:26 - mmengine - INFO - Epoch(train) [55][ 60/2569] lr: 4.0000e-02 eta: 18:13:54 time: 0.2580 data_time: 0.0073 memory: 5828 grad_norm: 3.0162 loss: 2.3083 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3083 2023/06/05 02:41:31 - mmengine - INFO - Epoch(train) [55][ 80/2569] lr: 4.0000e-02 eta: 18:13:49 time: 0.2589 data_time: 0.0074 memory: 5828 grad_norm: 3.0969 loss: 2.6244 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6244 2023/06/05 02:41:36 - mmengine - INFO - Epoch(train) [55][ 100/2569] lr: 4.0000e-02 eta: 18:13:44 time: 0.2700 data_time: 0.0075 memory: 5828 grad_norm: 3.1722 loss: 2.4924 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4924 2023/06/05 02:41:42 - mmengine - INFO - Epoch(train) [55][ 120/2569] lr: 4.0000e-02 eta: 18:13:38 time: 0.2675 data_time: 0.0077 memory: 5828 grad_norm: 3.0951 loss: 2.7777 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7777 2023/06/05 02:41:47 - mmengine - INFO - Epoch(train) [55][ 140/2569] lr: 4.0000e-02 eta: 18:13:33 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 3.1027 loss: 2.7057 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7057 2023/06/05 02:41:52 - mmengine - INFO - Epoch(train) [55][ 160/2569] lr: 4.0000e-02 eta: 18:13:27 time: 0.2555 data_time: 0.0074 memory: 5828 grad_norm: 3.1427 loss: 2.7268 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7268 2023/06/05 02:41:57 - mmengine - INFO - Epoch(train) [55][ 180/2569] lr: 4.0000e-02 eta: 18:13:22 time: 0.2715 data_time: 0.0077 memory: 5828 grad_norm: 3.0462 loss: 2.4840 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4840 2023/06/05 02:42:03 - mmengine - INFO - Epoch(train) [55][ 200/2569] lr: 4.0000e-02 eta: 18:13:16 time: 0.2577 data_time: 0.0072 memory: 5828 grad_norm: 3.1099 loss: 2.6787 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6787 2023/06/05 02:42:08 - mmengine - INFO - Epoch(train) [55][ 220/2569] lr: 4.0000e-02 eta: 18:13:11 time: 0.2650 data_time: 0.0080 memory: 5828 grad_norm: 3.1561 loss: 2.4952 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4952 2023/06/05 02:42:13 - mmengine - INFO - Epoch(train) [55][ 240/2569] lr: 4.0000e-02 eta: 18:13:05 time: 0.2569 data_time: 0.0075 memory: 5828 grad_norm: 3.0690 loss: 2.8087 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8087 2023/06/05 02:42:18 - mmengine - INFO - Epoch(train) [55][ 260/2569] lr: 4.0000e-02 eta: 18:13:00 time: 0.2577 data_time: 0.0075 memory: 5828 grad_norm: 3.1107 loss: 2.7453 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7453 2023/06/05 02:42:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:42:23 - mmengine - INFO - Epoch(train) [55][ 280/2569] lr: 4.0000e-02 eta: 18:12:54 time: 0.2562 data_time: 0.0071 memory: 5828 grad_norm: 3.1190 loss: 2.4454 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4454 2023/06/05 02:42:28 - mmengine - INFO - Epoch(train) [55][ 300/2569] lr: 4.0000e-02 eta: 18:12:48 time: 0.2558 data_time: 0.0075 memory: 5828 grad_norm: 3.1361 loss: 2.6580 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6580 2023/06/05 02:42:34 - mmengine - INFO - Epoch(train) [55][ 320/2569] lr: 4.0000e-02 eta: 18:12:43 time: 0.2593 data_time: 0.0070 memory: 5828 grad_norm: 3.1355 loss: 2.1840 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1840 2023/06/05 02:42:39 - mmengine - INFO - Epoch(train) [55][ 340/2569] lr: 4.0000e-02 eta: 18:12:37 time: 0.2561 data_time: 0.0073 memory: 5828 grad_norm: 3.0590 loss: 2.3674 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3674 2023/06/05 02:42:44 - mmengine - INFO - Epoch(train) [55][ 360/2569] lr: 4.0000e-02 eta: 18:12:31 time: 0.2572 data_time: 0.0074 memory: 5828 grad_norm: 3.0858 loss: 2.3238 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3238 2023/06/05 02:42:49 - mmengine - INFO - Epoch(train) [55][ 380/2569] lr: 4.0000e-02 eta: 18:12:26 time: 0.2569 data_time: 0.0072 memory: 5828 grad_norm: 3.1131 loss: 2.6503 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6503 2023/06/05 02:42:54 - mmengine - INFO - Epoch(train) [55][ 400/2569] lr: 4.0000e-02 eta: 18:12:20 time: 0.2575 data_time: 0.0076 memory: 5828 grad_norm: 3.0659 loss: 2.4652 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4652 2023/06/05 02:43:00 - mmengine - INFO - Epoch(train) [55][ 420/2569] lr: 4.0000e-02 eta: 18:12:15 time: 0.2712 data_time: 0.0067 memory: 5828 grad_norm: 3.1045 loss: 2.6097 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6097 2023/06/05 02:43:05 - mmengine - INFO - Epoch(train) [55][ 440/2569] lr: 4.0000e-02 eta: 18:12:10 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 3.0972 loss: 2.4166 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4166 2023/06/05 02:43:10 - mmengine - INFO - Epoch(train) [55][ 460/2569] lr: 4.0000e-02 eta: 18:12:04 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 3.1138 loss: 2.2806 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.2806 2023/06/05 02:43:15 - mmengine - INFO - Epoch(train) [55][ 480/2569] lr: 4.0000e-02 eta: 18:11:59 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.0593 loss: 2.5641 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5641 2023/06/05 02:43:21 - mmengine - INFO - Epoch(train) [55][ 500/2569] lr: 4.0000e-02 eta: 18:11:54 time: 0.2718 data_time: 0.0072 memory: 5828 grad_norm: 3.1130 loss: 2.4633 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4633 2023/06/05 02:43:26 - mmengine - INFO - Epoch(train) [55][ 520/2569] lr: 4.0000e-02 eta: 18:11:48 time: 0.2663 data_time: 0.0075 memory: 5828 grad_norm: 3.0821 loss: 2.2298 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2298 2023/06/05 02:43:32 - mmengine - INFO - Epoch(train) [55][ 540/2569] lr: 4.0000e-02 eta: 18:11:43 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 3.0220 loss: 2.4861 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4861 2023/06/05 02:43:37 - mmengine - INFO - Epoch(train) [55][ 560/2569] lr: 4.0000e-02 eta: 18:11:37 time: 0.2566 data_time: 0.0075 memory: 5828 grad_norm: 3.1060 loss: 2.3043 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3043 2023/06/05 02:43:42 - mmengine - INFO - Epoch(train) [55][ 580/2569] lr: 4.0000e-02 eta: 18:11:32 time: 0.2638 data_time: 0.0078 memory: 5828 grad_norm: 3.1250 loss: 2.5351 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5351 2023/06/05 02:43:47 - mmengine - INFO - Epoch(train) [55][ 600/2569] lr: 4.0000e-02 eta: 18:11:26 time: 0.2569 data_time: 0.0072 memory: 5828 grad_norm: 3.1215 loss: 2.4432 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4432 2023/06/05 02:43:52 - mmengine - INFO - Epoch(train) [55][ 620/2569] lr: 4.0000e-02 eta: 18:11:21 time: 0.2574 data_time: 0.0073 memory: 5828 grad_norm: 3.1714 loss: 2.7937 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7937 2023/06/05 02:43:58 - mmengine - INFO - Epoch(train) [55][ 640/2569] lr: 4.0000e-02 eta: 18:11:15 time: 0.2673 data_time: 0.0072 memory: 5828 grad_norm: 3.1077 loss: 2.3674 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3674 2023/06/05 02:44:03 - mmengine - INFO - Epoch(train) [55][ 660/2569] lr: 4.0000e-02 eta: 18:11:10 time: 0.2620 data_time: 0.0070 memory: 5828 grad_norm: 3.1560 loss: 2.5098 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5098 2023/06/05 02:44:08 - mmengine - INFO - Epoch(train) [55][ 680/2569] lr: 4.0000e-02 eta: 18:11:04 time: 0.2636 data_time: 0.0078 memory: 5828 grad_norm: 3.1046 loss: 2.3732 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.3732 2023/06/05 02:44:13 - mmengine - INFO - Epoch(train) [55][ 700/2569] lr: 4.0000e-02 eta: 18:10:59 time: 0.2665 data_time: 0.0074 memory: 5828 grad_norm: 3.0843 loss: 2.4765 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4765 2023/06/05 02:44:19 - mmengine - INFO - Epoch(train) [55][ 720/2569] lr: 4.0000e-02 eta: 18:10:54 time: 0.2568 data_time: 0.0078 memory: 5828 grad_norm: 3.1450 loss: 2.4647 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4647 2023/06/05 02:44:24 - mmengine - INFO - Epoch(train) [55][ 740/2569] lr: 4.0000e-02 eta: 18:10:48 time: 0.2723 data_time: 0.0070 memory: 5828 grad_norm: 3.0938 loss: 2.6379 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6379 2023/06/05 02:44:29 - mmengine - INFO - Epoch(train) [55][ 760/2569] lr: 4.0000e-02 eta: 18:10:43 time: 0.2717 data_time: 0.0072 memory: 5828 grad_norm: 3.1022 loss: 2.3042 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3042 2023/06/05 02:44:35 - mmengine - INFO - Epoch(train) [55][ 780/2569] lr: 4.0000e-02 eta: 18:10:38 time: 0.2692 data_time: 0.0075 memory: 5828 grad_norm: 3.0969 loss: 2.5186 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5186 2023/06/05 02:44:40 - mmengine - INFO - Epoch(train) [55][ 800/2569] lr: 4.0000e-02 eta: 18:10:33 time: 0.2665 data_time: 0.0074 memory: 5828 grad_norm: 3.1204 loss: 2.4848 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4848 2023/06/05 02:44:45 - mmengine - INFO - Epoch(train) [55][ 820/2569] lr: 4.0000e-02 eta: 18:10:27 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 3.0925 loss: 2.6323 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6323 2023/06/05 02:44:51 - mmengine - INFO - Epoch(train) [55][ 840/2569] lr: 4.0000e-02 eta: 18:10:22 time: 0.2750 data_time: 0.0077 memory: 5828 grad_norm: 3.0379 loss: 2.7063 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7063 2023/06/05 02:44:56 - mmengine - INFO - Epoch(train) [55][ 860/2569] lr: 4.0000e-02 eta: 18:10:17 time: 0.2630 data_time: 0.0078 memory: 5828 grad_norm: 3.1653 loss: 2.3901 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3901 2023/06/05 02:45:01 - mmengine - INFO - Epoch(train) [55][ 880/2569] lr: 4.0000e-02 eta: 18:10:11 time: 0.2621 data_time: 0.0076 memory: 5828 grad_norm: 3.0857 loss: 2.5500 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5500 2023/06/05 02:45:07 - mmengine - INFO - Epoch(train) [55][ 900/2569] lr: 4.0000e-02 eta: 18:10:06 time: 0.2570 data_time: 0.0076 memory: 5828 grad_norm: 3.1213 loss: 2.3663 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3663 2023/06/05 02:45:12 - mmengine - INFO - Epoch(train) [55][ 920/2569] lr: 4.0000e-02 eta: 18:10:00 time: 0.2676 data_time: 0.0076 memory: 5828 grad_norm: 3.1412 loss: 2.6503 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6503 2023/06/05 02:45:17 - mmengine - INFO - Epoch(train) [55][ 940/2569] lr: 4.0000e-02 eta: 18:09:55 time: 0.2579 data_time: 0.0074 memory: 5828 grad_norm: 3.1243 loss: 2.8344 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8344 2023/06/05 02:45:22 - mmengine - INFO - Epoch(train) [55][ 960/2569] lr: 4.0000e-02 eta: 18:09:49 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 3.1141 loss: 2.7254 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7254 2023/06/05 02:45:28 - mmengine - INFO - Epoch(train) [55][ 980/2569] lr: 4.0000e-02 eta: 18:09:44 time: 0.2565 data_time: 0.0074 memory: 5828 grad_norm: 3.1080 loss: 2.4758 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4758 2023/06/05 02:45:33 - mmengine - INFO - Epoch(train) [55][1000/2569] lr: 4.0000e-02 eta: 18:09:38 time: 0.2663 data_time: 0.0079 memory: 5828 grad_norm: 3.1081 loss: 2.7170 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7170 2023/06/05 02:45:38 - mmengine - INFO - Epoch(train) [55][1020/2569] lr: 4.0000e-02 eta: 18:09:33 time: 0.2581 data_time: 0.0073 memory: 5828 grad_norm: 3.1122 loss: 2.4394 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4394 2023/06/05 02:45:43 - mmengine - INFO - Epoch(train) [55][1040/2569] lr: 4.0000e-02 eta: 18:09:27 time: 0.2572 data_time: 0.0075 memory: 5828 grad_norm: 3.0963 loss: 2.2969 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2969 2023/06/05 02:45:48 - mmengine - INFO - Epoch(train) [55][1060/2569] lr: 4.0000e-02 eta: 18:09:22 time: 0.2669 data_time: 0.0078 memory: 5828 grad_norm: 3.1413 loss: 2.5690 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5690 2023/06/05 02:45:54 - mmengine - INFO - Epoch(train) [55][1080/2569] lr: 4.0000e-02 eta: 18:09:16 time: 0.2578 data_time: 0.0079 memory: 5828 grad_norm: 3.1603 loss: 2.5226 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5226 2023/06/05 02:45:59 - mmengine - INFO - Epoch(train) [55][1100/2569] lr: 4.0000e-02 eta: 18:09:11 time: 0.2676 data_time: 0.0071 memory: 5828 grad_norm: 3.0865 loss: 2.6381 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6381 2023/06/05 02:46:04 - mmengine - INFO - Epoch(train) [55][1120/2569] lr: 4.0000e-02 eta: 18:09:05 time: 0.2579 data_time: 0.0073 memory: 5828 grad_norm: 3.1465 loss: 2.6039 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6039 2023/06/05 02:46:09 - mmengine - INFO - Epoch(train) [55][1140/2569] lr: 4.0000e-02 eta: 18:09:00 time: 0.2651 data_time: 0.0077 memory: 5828 grad_norm: 3.1939 loss: 2.5342 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5342 2023/06/05 02:46:15 - mmengine - INFO - Epoch(train) [55][1160/2569] lr: 4.0000e-02 eta: 18:08:54 time: 0.2616 data_time: 0.0072 memory: 5828 grad_norm: 3.1168 loss: 2.7857 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7857 2023/06/05 02:46:20 - mmengine - INFO - Epoch(train) [55][1180/2569] lr: 4.0000e-02 eta: 18:08:49 time: 0.2569 data_time: 0.0072 memory: 5828 grad_norm: 3.1095 loss: 2.3488 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3488 2023/06/05 02:46:25 - mmengine - INFO - Epoch(train) [55][1200/2569] lr: 4.0000e-02 eta: 18:08:44 time: 0.2677 data_time: 0.0075 memory: 5828 grad_norm: 3.1259 loss: 2.4043 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4043 2023/06/05 02:46:30 - mmengine - INFO - Epoch(train) [55][1220/2569] lr: 4.0000e-02 eta: 18:08:38 time: 0.2587 data_time: 0.0077 memory: 5828 grad_norm: 3.1007 loss: 2.6610 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6610 2023/06/05 02:46:36 - mmengine - INFO - Epoch(train) [55][1240/2569] lr: 4.0000e-02 eta: 18:08:33 time: 0.2626 data_time: 0.0072 memory: 5828 grad_norm: 3.0971 loss: 2.5508 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5508 2023/06/05 02:46:41 - mmengine - INFO - Epoch(train) [55][1260/2569] lr: 4.0000e-02 eta: 18:08:27 time: 0.2572 data_time: 0.0075 memory: 5828 grad_norm: 3.1676 loss: 2.2254 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2254 2023/06/05 02:46:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:46:46 - mmengine - INFO - Epoch(train) [55][1280/2569] lr: 4.0000e-02 eta: 18:08:21 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 3.1168 loss: 2.4399 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4399 2023/06/05 02:46:51 - mmengine - INFO - Epoch(train) [55][1300/2569] lr: 4.0000e-02 eta: 18:08:16 time: 0.2601 data_time: 0.0073 memory: 5828 grad_norm: 3.1053 loss: 2.7576 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7576 2023/06/05 02:46:57 - mmengine - INFO - Epoch(train) [55][1320/2569] lr: 4.0000e-02 eta: 18:08:11 time: 0.2655 data_time: 0.0073 memory: 5828 grad_norm: 3.1072 loss: 2.7096 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7096 2023/06/05 02:47:02 - mmengine - INFO - Epoch(train) [55][1340/2569] lr: 4.0000e-02 eta: 18:08:05 time: 0.2615 data_time: 0.0073 memory: 5828 grad_norm: 2.9855 loss: 2.4835 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4835 2023/06/05 02:47:07 - mmengine - INFO - Epoch(train) [55][1360/2569] lr: 4.0000e-02 eta: 18:07:59 time: 0.2587 data_time: 0.0079 memory: 5828 grad_norm: 3.0805 loss: 2.6726 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6726 2023/06/05 02:47:12 - mmengine - INFO - Epoch(train) [55][1380/2569] lr: 4.0000e-02 eta: 18:07:54 time: 0.2674 data_time: 0.0076 memory: 5828 grad_norm: 3.1365 loss: 2.4954 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4954 2023/06/05 02:47:18 - mmengine - INFO - Epoch(train) [55][1400/2569] lr: 4.0000e-02 eta: 18:07:49 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 3.0133 loss: 2.7684 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7684 2023/06/05 02:47:23 - mmengine - INFO - Epoch(train) [55][1420/2569] lr: 4.0000e-02 eta: 18:07:43 time: 0.2571 data_time: 0.0074 memory: 5828 grad_norm: 3.1335 loss: 2.4233 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4233 2023/06/05 02:47:28 - mmengine - INFO - Epoch(train) [55][1440/2569] lr: 4.0000e-02 eta: 18:07:38 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 3.1283 loss: 2.3729 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3729 2023/06/05 02:47:33 - mmengine - INFO - Epoch(train) [55][1460/2569] lr: 4.0000e-02 eta: 18:07:32 time: 0.2572 data_time: 0.0080 memory: 5828 grad_norm: 3.1567 loss: 2.3986 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3986 2023/06/05 02:47:39 - mmengine - INFO - Epoch(train) [55][1480/2569] lr: 4.0000e-02 eta: 18:07:27 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 3.0831 loss: 2.5100 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5100 2023/06/05 02:47:44 - mmengine - INFO - Epoch(train) [55][1500/2569] lr: 4.0000e-02 eta: 18:07:21 time: 0.2641 data_time: 0.0076 memory: 5828 grad_norm: 3.1173 loss: 2.6270 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6270 2023/06/05 02:47:49 - mmengine - INFO - Epoch(train) [55][1520/2569] lr: 4.0000e-02 eta: 18:07:16 time: 0.2756 data_time: 0.0080 memory: 5828 grad_norm: 3.1057 loss: 2.4968 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4968 2023/06/05 02:47:55 - mmengine - INFO - Epoch(train) [55][1540/2569] lr: 4.0000e-02 eta: 18:07:11 time: 0.2613 data_time: 0.0073 memory: 5828 grad_norm: 3.1254 loss: 2.4932 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4932 2023/06/05 02:48:00 - mmengine - INFO - Epoch(train) [55][1560/2569] lr: 4.0000e-02 eta: 18:07:06 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 3.0533 loss: 2.7675 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7675 2023/06/05 02:48:05 - mmengine - INFO - Epoch(train) [55][1580/2569] lr: 4.0000e-02 eta: 18:07:00 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 3.1051 loss: 2.4566 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4566 2023/06/05 02:48:10 - mmengine - INFO - Epoch(train) [55][1600/2569] lr: 4.0000e-02 eta: 18:06:55 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 3.1782 loss: 2.4654 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4654 2023/06/05 02:48:16 - mmengine - INFO - Epoch(train) [55][1620/2569] lr: 4.0000e-02 eta: 18:06:49 time: 0.2577 data_time: 0.0072 memory: 5828 grad_norm: 3.1659 loss: 2.8206 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8206 2023/06/05 02:48:21 - mmengine - INFO - Epoch(train) [55][1640/2569] lr: 4.0000e-02 eta: 18:06:44 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 3.0781 loss: 2.6053 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6053 2023/06/05 02:48:26 - mmengine - INFO - Epoch(train) [55][1660/2569] lr: 4.0000e-02 eta: 18:06:38 time: 0.2585 data_time: 0.0071 memory: 5828 grad_norm: 3.1025 loss: 2.4722 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4722 2023/06/05 02:48:31 - mmengine - INFO - Epoch(train) [55][1680/2569] lr: 4.0000e-02 eta: 18:06:33 time: 0.2616 data_time: 0.0070 memory: 5828 grad_norm: 3.0648 loss: 2.6521 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 2.6521 2023/06/05 02:48:36 - mmengine - INFO - Epoch(train) [55][1700/2569] lr: 4.0000e-02 eta: 18:06:27 time: 0.2590 data_time: 0.0073 memory: 5828 grad_norm: 3.1801 loss: 2.3121 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3121 2023/06/05 02:48:42 - mmengine - INFO - Epoch(train) [55][1720/2569] lr: 4.0000e-02 eta: 18:06:22 time: 0.2700 data_time: 0.0076 memory: 5828 grad_norm: 3.1666 loss: 2.2808 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2808 2023/06/05 02:48:47 - mmengine - INFO - Epoch(train) [55][1740/2569] lr: 4.0000e-02 eta: 18:06:16 time: 0.2581 data_time: 0.0073 memory: 5828 grad_norm: 3.2078 loss: 2.6816 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6816 2023/06/05 02:48:52 - mmengine - INFO - Epoch(train) [55][1760/2569] lr: 4.0000e-02 eta: 18:06:11 time: 0.2583 data_time: 0.0071 memory: 5828 grad_norm: 3.1248 loss: 2.3825 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3825 2023/06/05 02:48:58 - mmengine - INFO - Epoch(train) [55][1780/2569] lr: 4.0000e-02 eta: 18:06:05 time: 0.2648 data_time: 0.0075 memory: 5828 grad_norm: 3.0509 loss: 2.6731 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6731 2023/06/05 02:49:03 - mmengine - INFO - Epoch(train) [55][1800/2569] lr: 4.0000e-02 eta: 18:06:00 time: 0.2576 data_time: 0.0078 memory: 5828 grad_norm: 3.1263 loss: 2.2873 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2873 2023/06/05 02:49:08 - mmengine - INFO - Epoch(train) [55][1820/2569] lr: 4.0000e-02 eta: 18:05:54 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 3.1068 loss: 2.3824 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3824 2023/06/05 02:49:13 - mmengine - INFO - Epoch(train) [55][1840/2569] lr: 4.0000e-02 eta: 18:05:49 time: 0.2632 data_time: 0.0077 memory: 5828 grad_norm: 3.1625 loss: 2.7144 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7144 2023/06/05 02:49:19 - mmengine - INFO - Epoch(train) [55][1860/2569] lr: 4.0000e-02 eta: 18:05:43 time: 0.2617 data_time: 0.0075 memory: 5828 grad_norm: 3.1789 loss: 2.6377 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6377 2023/06/05 02:49:24 - mmengine - INFO - Epoch(train) [55][1880/2569] lr: 4.0000e-02 eta: 18:05:38 time: 0.2587 data_time: 0.0076 memory: 5828 grad_norm: 3.0694 loss: 2.6480 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6480 2023/06/05 02:49:29 - mmengine - INFO - Epoch(train) [55][1900/2569] lr: 4.0000e-02 eta: 18:05:33 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 3.0996 loss: 2.6003 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6003 2023/06/05 02:49:35 - mmengine - INFO - Epoch(train) [55][1920/2569] lr: 4.0000e-02 eta: 18:05:28 time: 0.2765 data_time: 0.0075 memory: 5828 grad_norm: 3.0812 loss: 2.7399 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7399 2023/06/05 02:49:40 - mmengine - INFO - Epoch(train) [55][1940/2569] lr: 4.0000e-02 eta: 18:05:22 time: 0.2587 data_time: 0.0079 memory: 5828 grad_norm: 3.0871 loss: 2.6455 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6455 2023/06/05 02:49:45 - mmengine - INFO - Epoch(train) [55][1960/2569] lr: 4.0000e-02 eta: 18:05:17 time: 0.2784 data_time: 0.0079 memory: 5828 grad_norm: 3.1630 loss: 2.6046 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6046 2023/06/05 02:49:51 - mmengine - INFO - Epoch(train) [55][1980/2569] lr: 4.0000e-02 eta: 18:05:12 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 3.1085 loss: 2.6675 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6675 2023/06/05 02:49:56 - mmengine - INFO - Epoch(train) [55][2000/2569] lr: 4.0000e-02 eta: 18:05:06 time: 0.2605 data_time: 0.0074 memory: 5828 grad_norm: 3.1155 loss: 2.5282 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5282 2023/06/05 02:50:01 - mmengine - INFO - Epoch(train) [55][2020/2569] lr: 4.0000e-02 eta: 18:05:01 time: 0.2603 data_time: 0.0078 memory: 5828 grad_norm: 3.0554 loss: 2.4997 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4997 2023/06/05 02:50:06 - mmengine - INFO - Epoch(train) [55][2040/2569] lr: 4.0000e-02 eta: 18:04:55 time: 0.2579 data_time: 0.0074 memory: 5828 grad_norm: 3.1623 loss: 2.3733 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3733 2023/06/05 02:50:11 - mmengine - INFO - Epoch(train) [55][2060/2569] lr: 4.0000e-02 eta: 18:04:49 time: 0.2583 data_time: 0.0073 memory: 5828 grad_norm: 3.1799 loss: 2.5334 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5334 2023/06/05 02:50:17 - mmengine - INFO - Epoch(train) [55][2080/2569] lr: 4.0000e-02 eta: 18:04:44 time: 0.2707 data_time: 0.0090 memory: 5828 grad_norm: 3.0938 loss: 2.4586 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4586 2023/06/05 02:50:22 - mmengine - INFO - Epoch(train) [55][2100/2569] lr: 4.0000e-02 eta: 18:04:39 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 3.1259 loss: 2.3719 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3719 2023/06/05 02:50:27 - mmengine - INFO - Epoch(train) [55][2120/2569] lr: 4.0000e-02 eta: 18:04:33 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 3.1410 loss: 2.4390 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4390 2023/06/05 02:50:33 - mmengine - INFO - Epoch(train) [55][2140/2569] lr: 4.0000e-02 eta: 18:04:28 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 3.1388 loss: 2.6543 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6543 2023/06/05 02:50:38 - mmengine - INFO - Epoch(train) [55][2160/2569] lr: 4.0000e-02 eta: 18:04:22 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 3.0809 loss: 2.6964 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6964 2023/06/05 02:50:43 - mmengine - INFO - Epoch(train) [55][2180/2569] lr: 4.0000e-02 eta: 18:04:18 time: 0.2793 data_time: 0.0074 memory: 5828 grad_norm: 3.0428 loss: 2.2773 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2773 2023/06/05 02:50:49 - mmengine - INFO - Epoch(train) [55][2200/2569] lr: 4.0000e-02 eta: 18:04:12 time: 0.2607 data_time: 0.0073 memory: 5828 grad_norm: 3.0445 loss: 2.7846 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7846 2023/06/05 02:50:54 - mmengine - INFO - Epoch(train) [55][2220/2569] lr: 4.0000e-02 eta: 18:04:07 time: 0.2747 data_time: 0.0072 memory: 5828 grad_norm: 3.0819 loss: 2.6095 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6095 2023/06/05 02:50:59 - mmengine - INFO - Epoch(train) [55][2240/2569] lr: 4.0000e-02 eta: 18:04:02 time: 0.2598 data_time: 0.0072 memory: 5828 grad_norm: 3.1425 loss: 2.5713 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5713 2023/06/05 02:51:05 - mmengine - INFO - Epoch(train) [55][2260/2569] lr: 4.0000e-02 eta: 18:03:56 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 3.0006 loss: 2.4037 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4037 2023/06/05 02:51:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:51:10 - mmengine - INFO - Epoch(train) [55][2280/2569] lr: 4.0000e-02 eta: 18:03:51 time: 0.2635 data_time: 0.0075 memory: 5828 grad_norm: 3.1236 loss: 2.6845 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6845 2023/06/05 02:51:15 - mmengine - INFO - Epoch(train) [55][2300/2569] lr: 4.0000e-02 eta: 18:03:45 time: 0.2616 data_time: 0.0076 memory: 5828 grad_norm: 3.1373 loss: 2.7189 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7189 2023/06/05 02:51:20 - mmengine - INFO - Epoch(train) [55][2320/2569] lr: 4.0000e-02 eta: 18:03:40 time: 0.2630 data_time: 0.0077 memory: 5828 grad_norm: 3.1017 loss: 2.4176 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4176 2023/06/05 02:51:26 - mmengine - INFO - Epoch(train) [55][2340/2569] lr: 4.0000e-02 eta: 18:03:34 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.0420 loss: 2.5787 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5787 2023/06/05 02:51:31 - mmengine - INFO - Epoch(train) [55][2360/2569] lr: 4.0000e-02 eta: 18:03:29 time: 0.2573 data_time: 0.0073 memory: 5828 grad_norm: 3.1165 loss: 2.4776 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4776 2023/06/05 02:51:36 - mmengine - INFO - Epoch(train) [55][2380/2569] lr: 4.0000e-02 eta: 18:03:23 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 3.0128 loss: 2.2879 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2879 2023/06/05 02:51:41 - mmengine - INFO - Epoch(train) [55][2400/2569] lr: 4.0000e-02 eta: 18:03:18 time: 0.2575 data_time: 0.0069 memory: 5828 grad_norm: 3.0594 loss: 2.6174 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6174 2023/06/05 02:51:47 - mmengine - INFO - Epoch(train) [55][2420/2569] lr: 4.0000e-02 eta: 18:03:13 time: 0.2750 data_time: 0.0072 memory: 5828 grad_norm: 3.1337 loss: 2.6491 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6491 2023/06/05 02:51:52 - mmengine - INFO - Epoch(train) [55][2440/2569] lr: 4.0000e-02 eta: 18:03:07 time: 0.2579 data_time: 0.0076 memory: 5828 grad_norm: 3.0675 loss: 2.7406 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7406 2023/06/05 02:51:58 - mmengine - INFO - Epoch(train) [55][2460/2569] lr: 4.0000e-02 eta: 18:03:03 time: 0.2908 data_time: 0.0072 memory: 5828 grad_norm: 3.1082 loss: 2.2714 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2714 2023/06/05 02:52:03 - mmengine - INFO - Epoch(train) [55][2480/2569] lr: 4.0000e-02 eta: 18:02:57 time: 0.2621 data_time: 0.0071 memory: 5828 grad_norm: 3.1020 loss: 2.5803 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5803 2023/06/05 02:52:08 - mmengine - INFO - Epoch(train) [55][2500/2569] lr: 4.0000e-02 eta: 18:02:52 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 3.0855 loss: 2.2023 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.2023 2023/06/05 02:52:14 - mmengine - INFO - Epoch(train) [55][2520/2569] lr: 4.0000e-02 eta: 18:02:47 time: 0.2673 data_time: 0.0069 memory: 5828 grad_norm: 3.1265 loss: 2.3442 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3442 2023/06/05 02:52:19 - mmengine - INFO - Epoch(train) [55][2540/2569] lr: 4.0000e-02 eta: 18:02:41 time: 0.2596 data_time: 0.0071 memory: 5828 grad_norm: 3.0650 loss: 2.3560 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3560 2023/06/05 02:52:24 - mmengine - INFO - Epoch(train) [55][2560/2569] lr: 4.0000e-02 eta: 18:02:35 time: 0.2556 data_time: 0.0078 memory: 5828 grad_norm: 3.0756 loss: 2.1682 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1682 2023/06/05 02:52:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:52:26 - mmengine - INFO - Epoch(train) [55][2569/2569] lr: 4.0000e-02 eta: 18:02:33 time: 0.2498 data_time: 0.0074 memory: 5828 grad_norm: 3.0925 loss: 2.3359 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.3359 2023/06/05 02:52:30 - mmengine - INFO - Epoch(val) [55][ 20/260] eta: 0:00:41 time: 0.1747 data_time: 0.1159 memory: 1238 2023/06/05 02:52:33 - mmengine - INFO - Epoch(val) [55][ 40/260] eta: 0:00:35 time: 0.1516 data_time: 0.0929 memory: 1238 2023/06/05 02:52:36 - mmengine - INFO - Epoch(val) [55][ 60/260] eta: 0:00:32 time: 0.1557 data_time: 0.0972 memory: 1238 2023/06/05 02:52:39 - mmengine - INFO - Epoch(val) [55][ 80/260] eta: 0:00:27 time: 0.1347 data_time: 0.0765 memory: 1238 2023/06/05 02:52:42 - mmengine - INFO - Epoch(val) [55][100/260] eta: 0:00:24 time: 0.1500 data_time: 0.0914 memory: 1238 2023/06/05 02:52:45 - mmengine - INFO - Epoch(val) [55][120/260] eta: 0:00:21 time: 0.1513 data_time: 0.0925 memory: 1238 2023/06/05 02:52:47 - mmengine - INFO - Epoch(val) [55][140/260] eta: 0:00:18 time: 0.1376 data_time: 0.0794 memory: 1238 2023/06/05 02:52:50 - mmengine - INFO - Epoch(val) [55][160/260] eta: 0:00:15 time: 0.1466 data_time: 0.0878 memory: 1238 2023/06/05 02:52:53 - mmengine - INFO - Epoch(val) [55][180/260] eta: 0:00:12 time: 0.1502 data_time: 0.0918 memory: 1238 2023/06/05 02:52:56 - mmengine - INFO - Epoch(val) [55][200/260] eta: 0:00:08 time: 0.1354 data_time: 0.0763 memory: 1238 2023/06/05 02:52:59 - mmengine - INFO - Epoch(val) [55][220/260] eta: 0:00:05 time: 0.1435 data_time: 0.0847 memory: 1238 2023/06/05 02:53:01 - mmengine - INFO - Epoch(val) [55][240/260] eta: 0:00:02 time: 0.1294 data_time: 0.0713 memory: 1238 2023/06/05 02:53:04 - mmengine - INFO - Epoch(val) [55][260/260] eta: 0:00:00 time: 0.1365 data_time: 0.0802 memory: 1238 2023/06/05 02:53:11 - mmengine - INFO - Epoch(val) [55][260/260] acc/top1: 0.4939 acc/top5: 0.7384 acc/mean1: 0.4874 data_time: 0.0872 time: 0.1456 2023/06/05 02:53:18 - mmengine - INFO - Epoch(train) [56][ 20/2569] lr: 4.0000e-02 eta: 18:02:30 time: 0.3398 data_time: 0.0489 memory: 5828 grad_norm: 3.1259 loss: 2.6726 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6726 2023/06/05 02:53:23 - mmengine - INFO - Epoch(train) [56][ 40/2569] lr: 4.0000e-02 eta: 18:02:24 time: 0.2596 data_time: 0.0074 memory: 5828 grad_norm: 3.1268 loss: 2.6699 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6699 2023/06/05 02:53:28 - mmengine - INFO - Epoch(train) [56][ 60/2569] lr: 4.0000e-02 eta: 18:02:19 time: 0.2582 data_time: 0.0073 memory: 5828 grad_norm: 3.1027 loss: 2.6346 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6346 2023/06/05 02:53:33 - mmengine - INFO - Epoch(train) [56][ 80/2569] lr: 4.0000e-02 eta: 18:02:13 time: 0.2596 data_time: 0.0077 memory: 5828 grad_norm: 3.1083 loss: 2.3321 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3321 2023/06/05 02:53:39 - mmengine - INFO - Epoch(train) [56][ 100/2569] lr: 4.0000e-02 eta: 18:02:08 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 3.0337 loss: 2.4168 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4168 2023/06/05 02:53:44 - mmengine - INFO - Epoch(train) [56][ 120/2569] lr: 4.0000e-02 eta: 18:02:03 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 3.1306 loss: 2.3825 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3825 2023/06/05 02:53:49 - mmengine - INFO - Epoch(train) [56][ 140/2569] lr: 4.0000e-02 eta: 18:01:57 time: 0.2591 data_time: 0.0073 memory: 5828 grad_norm: 3.0913 loss: 2.1173 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1173 2023/06/05 02:53:55 - mmengine - INFO - Epoch(train) [56][ 160/2569] lr: 4.0000e-02 eta: 18:01:52 time: 0.2733 data_time: 0.0074 memory: 5828 grad_norm: 3.1638 loss: 2.5912 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5912 2023/06/05 02:54:00 - mmengine - INFO - Epoch(train) [56][ 180/2569] lr: 4.0000e-02 eta: 18:01:47 time: 0.2809 data_time: 0.0074 memory: 5828 grad_norm: 3.0843 loss: 2.4752 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4752 2023/06/05 02:54:06 - mmengine - INFO - Epoch(train) [56][ 200/2569] lr: 4.0000e-02 eta: 18:01:42 time: 0.2648 data_time: 0.0077 memory: 5828 grad_norm: 3.1030 loss: 2.2998 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2998 2023/06/05 02:54:11 - mmengine - INFO - Epoch(train) [56][ 220/2569] lr: 4.0000e-02 eta: 18:01:37 time: 0.2729 data_time: 0.0074 memory: 5828 grad_norm: 3.0935 loss: 2.4083 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4083 2023/06/05 02:54:16 - mmengine - INFO - Epoch(train) [56][ 240/2569] lr: 4.0000e-02 eta: 18:01:31 time: 0.2617 data_time: 0.0077 memory: 5828 grad_norm: 3.0784 loss: 2.5114 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5114 2023/06/05 02:54:21 - mmengine - INFO - Epoch(train) [56][ 260/2569] lr: 4.0000e-02 eta: 18:01:25 time: 0.2573 data_time: 0.0074 memory: 5828 grad_norm: 3.1673 loss: 2.6480 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6480 2023/06/05 02:54:27 - mmengine - INFO - Epoch(train) [56][ 280/2569] lr: 4.0000e-02 eta: 18:01:20 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 3.0877 loss: 2.4968 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4968 2023/06/05 02:54:32 - mmengine - INFO - Epoch(train) [56][ 300/2569] lr: 4.0000e-02 eta: 18:01:15 time: 0.2602 data_time: 0.0071 memory: 5828 grad_norm: 3.1516 loss: 2.6579 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6579 2023/06/05 02:54:37 - mmengine - INFO - Epoch(train) [56][ 320/2569] lr: 4.0000e-02 eta: 18:01:09 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 3.1291 loss: 2.5094 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5094 2023/06/05 02:54:43 - mmengine - INFO - Epoch(train) [56][ 340/2569] lr: 4.0000e-02 eta: 18:01:04 time: 0.2689 data_time: 0.0074 memory: 5828 grad_norm: 3.1061 loss: 2.3258 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3258 2023/06/05 02:54:48 - mmengine - INFO - Epoch(train) [56][ 360/2569] lr: 4.0000e-02 eta: 18:00:58 time: 0.2571 data_time: 0.0073 memory: 5828 grad_norm: 3.0975 loss: 2.5151 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5151 2023/06/05 02:54:53 - mmengine - INFO - Epoch(train) [56][ 380/2569] lr: 4.0000e-02 eta: 18:00:53 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 3.1217 loss: 2.4225 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.4225 2023/06/05 02:54:58 - mmengine - INFO - Epoch(train) [56][ 400/2569] lr: 4.0000e-02 eta: 18:00:48 time: 0.2692 data_time: 0.0070 memory: 5828 grad_norm: 3.1066 loss: 2.5727 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5727 2023/06/05 02:55:04 - mmengine - INFO - Epoch(train) [56][ 420/2569] lr: 4.0000e-02 eta: 18:00:43 time: 0.2719 data_time: 0.0070 memory: 5828 grad_norm: 3.0792 loss: 2.6296 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6296 2023/06/05 02:55:09 - mmengine - INFO - Epoch(train) [56][ 440/2569] lr: 4.0000e-02 eta: 18:00:37 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 3.1857 loss: 2.6758 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6758 2023/06/05 02:55:15 - mmengine - INFO - Epoch(train) [56][ 460/2569] lr: 4.0000e-02 eta: 18:00:32 time: 0.2734 data_time: 0.0071 memory: 5828 grad_norm: 3.1539 loss: 2.1768 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1768 2023/06/05 02:55:20 - mmengine - INFO - Epoch(train) [56][ 480/2569] lr: 4.0000e-02 eta: 18:00:27 time: 0.2605 data_time: 0.0080 memory: 5828 grad_norm: 3.0715 loss: 2.5764 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5764 2023/06/05 02:55:25 - mmengine - INFO - Epoch(train) [56][ 500/2569] lr: 4.0000e-02 eta: 18:00:22 time: 0.2741 data_time: 0.0078 memory: 5828 grad_norm: 3.1215 loss: 2.5688 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5688 2023/06/05 02:55:31 - mmengine - INFO - Epoch(train) [56][ 520/2569] lr: 4.0000e-02 eta: 18:00:16 time: 0.2683 data_time: 0.0078 memory: 5828 grad_norm: 3.0932 loss: 2.6497 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6497 2023/06/05 02:55:36 - mmengine - INFO - Epoch(train) [56][ 540/2569] lr: 4.0000e-02 eta: 18:00:11 time: 0.2702 data_time: 0.0072 memory: 5828 grad_norm: 3.0910 loss: 2.3508 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3508 2023/06/05 02:55:42 - mmengine - INFO - Epoch(train) [56][ 560/2569] lr: 4.0000e-02 eta: 18:00:06 time: 0.2691 data_time: 0.0076 memory: 5828 grad_norm: 3.1629 loss: 2.6849 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6849 2023/06/05 02:55:47 - mmengine - INFO - Epoch(train) [56][ 580/2569] lr: 4.0000e-02 eta: 18:00:01 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.1212 loss: 2.5429 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5429 2023/06/05 02:55:52 - mmengine - INFO - Epoch(train) [56][ 600/2569] lr: 4.0000e-02 eta: 17:59:55 time: 0.2691 data_time: 0.0072 memory: 5828 grad_norm: 3.2149 loss: 2.4960 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4960 2023/06/05 02:55:58 - mmengine - INFO - Epoch(train) [56][ 620/2569] lr: 4.0000e-02 eta: 17:59:50 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 3.0572 loss: 2.5279 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5279 2023/06/05 02:56:03 - mmengine - INFO - Epoch(train) [56][ 640/2569] lr: 4.0000e-02 eta: 17:59:44 time: 0.2556 data_time: 0.0076 memory: 5828 grad_norm: 3.1141 loss: 2.4776 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4776 2023/06/05 02:56:08 - mmengine - INFO - Epoch(train) [56][ 660/2569] lr: 4.0000e-02 eta: 17:59:39 time: 0.2649 data_time: 0.0070 memory: 5828 grad_norm: 3.1569 loss: 2.8849 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.8849 2023/06/05 02:56:13 - mmengine - INFO - Epoch(train) [56][ 680/2569] lr: 4.0000e-02 eta: 17:59:33 time: 0.2582 data_time: 0.0073 memory: 5828 grad_norm: 3.1439 loss: 2.3697 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3697 2023/06/05 02:56:18 - mmengine - INFO - Epoch(train) [56][ 700/2569] lr: 4.0000e-02 eta: 17:59:28 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 3.1128 loss: 3.0189 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0189 2023/06/05 02:56:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 02:56:24 - mmengine - INFO - Epoch(train) [56][ 720/2569] lr: 4.0000e-02 eta: 17:59:23 time: 0.2569 data_time: 0.0074 memory: 5828 grad_norm: 3.1181 loss: 2.4432 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4432 2023/06/05 02:56:29 - mmengine - INFO - Epoch(train) [56][ 740/2569] lr: 4.0000e-02 eta: 17:59:18 time: 0.2772 data_time: 0.0073 memory: 5828 grad_norm: 3.1144 loss: 2.3273 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3273 2023/06/05 02:56:35 - mmengine - INFO - Epoch(train) [56][ 760/2569] lr: 4.0000e-02 eta: 17:59:12 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 3.1279 loss: 2.5468 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5468 2023/06/05 02:56:40 - mmengine - INFO - Epoch(train) [56][ 780/2569] lr: 4.0000e-02 eta: 17:59:07 time: 0.2729 data_time: 0.0074 memory: 5828 grad_norm: 3.0589 loss: 2.2785 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2785 2023/06/05 02:56:45 - mmengine - INFO - Epoch(train) [56][ 800/2569] lr: 4.0000e-02 eta: 17:59:02 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 3.1489 loss: 2.7674 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7674 2023/06/05 02:56:51 - mmengine - INFO - Epoch(train) [56][ 820/2569] lr: 4.0000e-02 eta: 17:58:56 time: 0.2574 data_time: 0.0075 memory: 5828 grad_norm: 3.1302 loss: 2.5673 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5673 2023/06/05 02:56:56 - mmengine - INFO - Epoch(train) [56][ 840/2569] lr: 4.0000e-02 eta: 17:58:51 time: 0.2698 data_time: 0.0075 memory: 5828 grad_norm: 3.0861 loss: 2.6999 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6999 2023/06/05 02:57:01 - mmengine - INFO - Epoch(train) [56][ 860/2569] lr: 4.0000e-02 eta: 17:58:46 time: 0.2588 data_time: 0.0070 memory: 5828 grad_norm: 3.0980 loss: 2.5362 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5362 2023/06/05 02:57:06 - mmengine - INFO - Epoch(train) [56][ 880/2569] lr: 4.0000e-02 eta: 17:58:40 time: 0.2605 data_time: 0.0071 memory: 5828 grad_norm: 3.1271 loss: 2.3230 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3230 2023/06/05 02:57:12 - mmengine - INFO - Epoch(train) [56][ 900/2569] lr: 4.0000e-02 eta: 17:58:35 time: 0.2694 data_time: 0.0074 memory: 5828 grad_norm: 3.1846 loss: 2.5860 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5860 2023/06/05 02:57:17 - mmengine - INFO - Epoch(train) [56][ 920/2569] lr: 4.0000e-02 eta: 17:58:30 time: 0.2693 data_time: 0.0074 memory: 5828 grad_norm: 3.1822 loss: 2.7830 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7830 2023/06/05 02:57:22 - mmengine - INFO - Epoch(train) [56][ 940/2569] lr: 4.0000e-02 eta: 17:58:24 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 3.0759 loss: 2.5676 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5676 2023/06/05 02:57:28 - mmengine - INFO - Epoch(train) [56][ 960/2569] lr: 4.0000e-02 eta: 17:58:19 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.1207 loss: 2.5670 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5670 2023/06/05 02:57:33 - mmengine - INFO - Epoch(train) [56][ 980/2569] lr: 4.0000e-02 eta: 17:58:13 time: 0.2584 data_time: 0.0076 memory: 5828 grad_norm: 3.1334 loss: 2.3976 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3976 2023/06/05 02:57:38 - mmengine - INFO - Epoch(train) [56][1000/2569] lr: 4.0000e-02 eta: 17:58:08 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 3.1554 loss: 2.7030 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7030 2023/06/05 02:57:43 - mmengine - INFO - Epoch(train) [56][1020/2569] lr: 4.0000e-02 eta: 17:58:03 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 3.0950 loss: 2.6440 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6440 2023/06/05 02:57:49 - mmengine - INFO - Epoch(train) [56][1040/2569] lr: 4.0000e-02 eta: 17:57:57 time: 0.2582 data_time: 0.0085 memory: 5828 grad_norm: 3.1028 loss: 2.6274 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6274 2023/06/05 02:57:54 - mmengine - INFO - Epoch(train) [56][1060/2569] lr: 4.0000e-02 eta: 17:57:52 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 3.0352 loss: 2.4841 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4841 2023/06/05 02:57:59 - mmengine - INFO - Epoch(train) [56][1080/2569] lr: 4.0000e-02 eta: 17:57:46 time: 0.2583 data_time: 0.0075 memory: 5828 grad_norm: 3.1852 loss: 2.6345 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6345 2023/06/05 02:58:04 - mmengine - INFO - Epoch(train) [56][1100/2569] lr: 4.0000e-02 eta: 17:57:40 time: 0.2574 data_time: 0.0074 memory: 5828 grad_norm: 3.0678 loss: 2.3516 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3516 2023/06/05 02:58:10 - mmengine - INFO - Epoch(train) [56][1120/2569] lr: 4.0000e-02 eta: 17:57:35 time: 0.2675 data_time: 0.0072 memory: 5828 grad_norm: 3.1024 loss: 2.4515 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4515 2023/06/05 02:58:15 - mmengine - INFO - Epoch(train) [56][1140/2569] lr: 4.0000e-02 eta: 17:57:29 time: 0.2576 data_time: 0.0073 memory: 5828 grad_norm: 3.1105 loss: 2.3021 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3021 2023/06/05 02:58:20 - mmengine - INFO - Epoch(train) [56][1160/2569] lr: 4.0000e-02 eta: 17:57:24 time: 0.2709 data_time: 0.0072 memory: 5828 grad_norm: 3.0229 loss: 2.7094 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7094 2023/06/05 02:58:25 - mmengine - INFO - Epoch(train) [56][1180/2569] lr: 4.0000e-02 eta: 17:57:19 time: 0.2577 data_time: 0.0071 memory: 5828 grad_norm: 3.0509 loss: 2.9153 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9153 2023/06/05 02:58:31 - mmengine - INFO - Epoch(train) [56][1200/2569] lr: 4.0000e-02 eta: 17:57:13 time: 0.2641 data_time: 0.0077 memory: 5828 grad_norm: 3.1115 loss: 2.5600 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5600 2023/06/05 02:58:36 - mmengine - INFO - Epoch(train) [56][1220/2569] lr: 4.0000e-02 eta: 17:57:08 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 3.1186 loss: 2.4272 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4272 2023/06/05 02:58:41 - mmengine - INFO - Epoch(train) [56][1240/2569] lr: 4.0000e-02 eta: 17:57:02 time: 0.2562 data_time: 0.0072 memory: 5828 grad_norm: 3.0798 loss: 2.6885 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6885 2023/06/05 02:58:46 - mmengine - INFO - Epoch(train) [56][1260/2569] lr: 4.0000e-02 eta: 17:56:57 time: 0.2604 data_time: 0.0078 memory: 5828 grad_norm: 3.1486 loss: 2.6403 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6403 2023/06/05 02:58:51 - mmengine - INFO - Epoch(train) [56][1280/2569] lr: 4.0000e-02 eta: 17:56:51 time: 0.2566 data_time: 0.0083 memory: 5828 grad_norm: 3.1168 loss: 2.7512 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7512 2023/06/05 02:58:57 - mmengine - INFO - Epoch(train) [56][1300/2569] lr: 4.0000e-02 eta: 17:56:46 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 3.1339 loss: 2.7248 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7248 2023/06/05 02:59:02 - mmengine - INFO - Epoch(train) [56][1320/2569] lr: 4.0000e-02 eta: 17:56:40 time: 0.2568 data_time: 0.0076 memory: 5828 grad_norm: 3.0758 loss: 2.6231 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6231 2023/06/05 02:59:07 - mmengine - INFO - Epoch(train) [56][1340/2569] lr: 4.0000e-02 eta: 17:56:35 time: 0.2583 data_time: 0.0074 memory: 5828 grad_norm: 3.0864 loss: 2.5512 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5512 2023/06/05 02:59:12 - mmengine - INFO - Epoch(train) [56][1360/2569] lr: 4.0000e-02 eta: 17:56:29 time: 0.2571 data_time: 0.0072 memory: 5828 grad_norm: 3.0186 loss: 2.5429 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5429 2023/06/05 02:59:18 - mmengine - INFO - Epoch(train) [56][1380/2569] lr: 4.0000e-02 eta: 17:56:24 time: 0.2654 data_time: 0.0084 memory: 5828 grad_norm: 3.1191 loss: 2.3551 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3551 2023/06/05 02:59:23 - mmengine - INFO - Epoch(train) [56][1400/2569] lr: 4.0000e-02 eta: 17:56:18 time: 0.2596 data_time: 0.0070 memory: 5828 grad_norm: 3.0459 loss: 2.7160 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7160 2023/06/05 02:59:28 - mmengine - INFO - Epoch(train) [56][1420/2569] lr: 4.0000e-02 eta: 17:56:13 time: 0.2656 data_time: 0.0077 memory: 5828 grad_norm: 3.0369 loss: 2.3634 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3634 2023/06/05 02:59:33 - mmengine - INFO - Epoch(train) [56][1440/2569] lr: 4.0000e-02 eta: 17:56:07 time: 0.2573 data_time: 0.0079 memory: 5828 grad_norm: 3.0096 loss: 2.8413 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8413 2023/06/05 02:59:38 - mmengine - INFO - Epoch(train) [56][1460/2569] lr: 4.0000e-02 eta: 17:56:02 time: 0.2637 data_time: 0.0081 memory: 5828 grad_norm: 3.1480 loss: 3.0966 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0966 2023/06/05 02:59:44 - mmengine - INFO - Epoch(train) [56][1480/2569] lr: 4.0000e-02 eta: 17:55:56 time: 0.2620 data_time: 0.0076 memory: 5828 grad_norm: 3.1032 loss: 2.7697 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7697 2023/06/05 02:59:49 - mmengine - INFO - Epoch(train) [56][1500/2569] lr: 4.0000e-02 eta: 17:55:51 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 3.1845 loss: 2.2443 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2443 2023/06/05 02:59:54 - mmengine - INFO - Epoch(train) [56][1520/2569] lr: 4.0000e-02 eta: 17:55:45 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 3.0973 loss: 2.7699 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.7699 2023/06/05 02:59:59 - mmengine - INFO - Epoch(train) [56][1540/2569] lr: 4.0000e-02 eta: 17:55:40 time: 0.2595 data_time: 0.0072 memory: 5828 grad_norm: 3.1085 loss: 2.6427 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6427 2023/06/05 03:00:05 - mmengine - INFO - Epoch(train) [56][1560/2569] lr: 4.0000e-02 eta: 17:55:34 time: 0.2629 data_time: 0.0070 memory: 5828 grad_norm: 3.1503 loss: 2.3898 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3898 2023/06/05 03:00:10 - mmengine - INFO - Epoch(train) [56][1580/2569] lr: 4.0000e-02 eta: 17:55:29 time: 0.2745 data_time: 0.0074 memory: 5828 grad_norm: 3.0935 loss: 2.6319 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6319 2023/06/05 03:00:15 - mmengine - INFO - Epoch(train) [56][1600/2569] lr: 4.0000e-02 eta: 17:55:24 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 3.1339 loss: 2.5020 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5020 2023/06/05 03:00:21 - mmengine - INFO - Epoch(train) [56][1620/2569] lr: 4.0000e-02 eta: 17:55:19 time: 0.2720 data_time: 0.0073 memory: 5828 grad_norm: 3.0935 loss: 2.3164 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3164 2023/06/05 03:00:26 - mmengine - INFO - Epoch(train) [56][1640/2569] lr: 4.0000e-02 eta: 17:55:13 time: 0.2657 data_time: 0.0077 memory: 5828 grad_norm: 3.0586 loss: 2.3543 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3543 2023/06/05 03:00:31 - mmengine - INFO - Epoch(train) [56][1660/2569] lr: 4.0000e-02 eta: 17:55:08 time: 0.2574 data_time: 0.0078 memory: 5828 grad_norm: 3.1322 loss: 2.6961 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6961 2023/06/05 03:00:37 - mmengine - INFO - Epoch(train) [56][1680/2569] lr: 4.0000e-02 eta: 17:55:02 time: 0.2633 data_time: 0.0073 memory: 5828 grad_norm: 3.1295 loss: 2.7537 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7537 2023/06/05 03:00:42 - mmengine - INFO - Epoch(train) [56][1700/2569] lr: 4.0000e-02 eta: 17:54:57 time: 0.2630 data_time: 0.0075 memory: 5828 grad_norm: 3.0693 loss: 2.5903 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5903 2023/06/05 03:00:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:00:47 - mmengine - INFO - Epoch(train) [56][1720/2569] lr: 4.0000e-02 eta: 17:54:51 time: 0.2609 data_time: 0.0072 memory: 5828 grad_norm: 3.1348 loss: 2.5725 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5725 2023/06/05 03:00:52 - mmengine - INFO - Epoch(train) [56][1740/2569] lr: 4.0000e-02 eta: 17:54:46 time: 0.2640 data_time: 0.0075 memory: 5828 grad_norm: 3.0664 loss: 2.6113 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6113 2023/06/05 03:00:58 - mmengine - INFO - Epoch(train) [56][1760/2569] lr: 4.0000e-02 eta: 17:54:41 time: 0.2711 data_time: 0.0073 memory: 5828 grad_norm: 3.1776 loss: 2.6119 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6119 2023/06/05 03:01:03 - mmengine - INFO - Epoch(train) [56][1780/2569] lr: 4.0000e-02 eta: 17:54:35 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.1468 loss: 2.5948 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5948 2023/06/05 03:01:08 - mmengine - INFO - Epoch(train) [56][1800/2569] lr: 4.0000e-02 eta: 17:54:30 time: 0.2690 data_time: 0.0074 memory: 5828 grad_norm: 3.1294 loss: 2.4993 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4993 2023/06/05 03:01:14 - mmengine - INFO - Epoch(train) [56][1820/2569] lr: 4.0000e-02 eta: 17:54:25 time: 0.2658 data_time: 0.0069 memory: 5828 grad_norm: 3.1525 loss: 2.6221 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6221 2023/06/05 03:01:19 - mmengine - INFO - Epoch(train) [56][1840/2569] lr: 4.0000e-02 eta: 17:54:19 time: 0.2635 data_time: 0.0074 memory: 5828 grad_norm: 3.0845 loss: 2.5799 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5799 2023/06/05 03:01:24 - mmengine - INFO - Epoch(train) [56][1860/2569] lr: 4.0000e-02 eta: 17:54:14 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 3.1121 loss: 2.6956 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6956 2023/06/05 03:01:30 - mmengine - INFO - Epoch(train) [56][1880/2569] lr: 4.0000e-02 eta: 17:54:08 time: 0.2571 data_time: 0.0072 memory: 5828 grad_norm: 3.0689 loss: 2.1970 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1970 2023/06/05 03:01:35 - mmengine - INFO - Epoch(train) [56][1900/2569] lr: 4.0000e-02 eta: 17:54:03 time: 0.2655 data_time: 0.0079 memory: 5828 grad_norm: 3.1301 loss: 2.3691 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3691 2023/06/05 03:01:40 - mmengine - INFO - Epoch(train) [56][1920/2569] lr: 4.0000e-02 eta: 17:53:58 time: 0.2635 data_time: 0.0077 memory: 5828 grad_norm: 3.0763 loss: 2.5826 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5826 2023/06/05 03:01:45 - mmengine - INFO - Epoch(train) [56][1940/2569] lr: 4.0000e-02 eta: 17:53:52 time: 0.2569 data_time: 0.0069 memory: 5828 grad_norm: 3.0893 loss: 2.6935 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6935 2023/06/05 03:01:50 - mmengine - INFO - Epoch(train) [56][1960/2569] lr: 4.0000e-02 eta: 17:53:46 time: 0.2578 data_time: 0.0081 memory: 5828 grad_norm: 3.0374 loss: 2.8917 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8917 2023/06/05 03:01:56 - mmengine - INFO - Epoch(train) [56][1980/2569] lr: 4.0000e-02 eta: 17:53:41 time: 0.2644 data_time: 0.0071 memory: 5828 grad_norm: 3.1321 loss: 2.4039 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4039 2023/06/05 03:02:01 - mmengine - INFO - Epoch(train) [56][2000/2569] lr: 4.0000e-02 eta: 17:53:35 time: 0.2577 data_time: 0.0072 memory: 5828 grad_norm: 3.0994 loss: 2.3119 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.3119 2023/06/05 03:02:06 - mmengine - INFO - Epoch(train) [56][2020/2569] lr: 4.0000e-02 eta: 17:53:30 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 3.1352 loss: 2.3878 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3878 2023/06/05 03:02:11 - mmengine - INFO - Epoch(train) [56][2040/2569] lr: 4.0000e-02 eta: 17:53:25 time: 0.2614 data_time: 0.0075 memory: 5828 grad_norm: 3.1710 loss: 2.6133 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6133 2023/06/05 03:02:17 - mmengine - INFO - Epoch(train) [56][2060/2569] lr: 4.0000e-02 eta: 17:53:19 time: 0.2619 data_time: 0.0076 memory: 5828 grad_norm: 3.1148 loss: 2.6249 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6249 2023/06/05 03:02:22 - mmengine - INFO - Epoch(train) [56][2080/2569] lr: 4.0000e-02 eta: 17:53:14 time: 0.2651 data_time: 0.0071 memory: 5828 grad_norm: 3.0825 loss: 2.3682 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3682 2023/06/05 03:02:27 - mmengine - INFO - Epoch(train) [56][2100/2569] lr: 4.0000e-02 eta: 17:53:08 time: 0.2637 data_time: 0.0069 memory: 5828 grad_norm: 3.1230 loss: 2.7541 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7541 2023/06/05 03:02:32 - mmengine - INFO - Epoch(train) [56][2120/2569] lr: 4.0000e-02 eta: 17:53:03 time: 0.2591 data_time: 0.0075 memory: 5828 grad_norm: 3.1189 loss: 2.5392 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5392 2023/06/05 03:02:38 - mmengine - INFO - Epoch(train) [56][2140/2569] lr: 4.0000e-02 eta: 17:52:58 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.0631 loss: 2.6085 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6085 2023/06/05 03:02:43 - mmengine - INFO - Epoch(train) [56][2160/2569] lr: 4.0000e-02 eta: 17:52:52 time: 0.2654 data_time: 0.0074 memory: 5828 grad_norm: 3.1684 loss: 2.4240 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4240 2023/06/05 03:02:48 - mmengine - INFO - Epoch(train) [56][2180/2569] lr: 4.0000e-02 eta: 17:52:47 time: 0.2613 data_time: 0.0078 memory: 5828 grad_norm: 3.0883 loss: 2.5267 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5267 2023/06/05 03:02:54 - mmengine - INFO - Epoch(train) [56][2200/2569] lr: 4.0000e-02 eta: 17:52:41 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 3.1833 loss: 2.6561 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6561 2023/06/05 03:02:59 - mmengine - INFO - Epoch(train) [56][2220/2569] lr: 4.0000e-02 eta: 17:52:36 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.0686 loss: 2.6039 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6039 2023/06/05 03:03:04 - mmengine - INFO - Epoch(train) [56][2240/2569] lr: 4.0000e-02 eta: 17:52:30 time: 0.2679 data_time: 0.0075 memory: 5828 grad_norm: 3.1286 loss: 2.6824 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6824 2023/06/05 03:03:10 - mmengine - INFO - Epoch(train) [56][2260/2569] lr: 4.0000e-02 eta: 17:52:25 time: 0.2688 data_time: 0.0078 memory: 5828 grad_norm: 3.1301 loss: 2.2239 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2239 2023/06/05 03:03:15 - mmengine - INFO - Epoch(train) [56][2280/2569] lr: 4.0000e-02 eta: 17:52:20 time: 0.2697 data_time: 0.0076 memory: 5828 grad_norm: 3.1038 loss: 2.1692 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1692 2023/06/05 03:03:20 - mmengine - INFO - Epoch(train) [56][2300/2569] lr: 4.0000e-02 eta: 17:52:14 time: 0.2561 data_time: 0.0077 memory: 5828 grad_norm: 3.1759 loss: 2.8549 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8549 2023/06/05 03:03:25 - mmengine - INFO - Epoch(train) [56][2320/2569] lr: 4.0000e-02 eta: 17:52:09 time: 0.2632 data_time: 0.0076 memory: 5828 grad_norm: 3.0875 loss: 2.3656 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3656 2023/06/05 03:03:31 - mmengine - INFO - Epoch(train) [56][2340/2569] lr: 4.0000e-02 eta: 17:52:04 time: 0.2691 data_time: 0.0077 memory: 5828 grad_norm: 3.0592 loss: 2.4304 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.4304 2023/06/05 03:03:36 - mmengine - INFO - Epoch(train) [56][2360/2569] lr: 4.0000e-02 eta: 17:51:58 time: 0.2635 data_time: 0.0077 memory: 5828 grad_norm: 3.1042 loss: 2.3983 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.3983 2023/06/05 03:03:41 - mmengine - INFO - Epoch(train) [56][2380/2569] lr: 4.0000e-02 eta: 17:51:53 time: 0.2582 data_time: 0.0076 memory: 5828 grad_norm: 3.1399 loss: 2.7913 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7913 2023/06/05 03:03:47 - mmengine - INFO - Epoch(train) [56][2400/2569] lr: 4.0000e-02 eta: 17:51:48 time: 0.2689 data_time: 0.0072 memory: 5828 grad_norm: 3.0512 loss: 2.3569 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3569 2023/06/05 03:03:52 - mmengine - INFO - Epoch(train) [56][2420/2569] lr: 4.0000e-02 eta: 17:51:42 time: 0.2570 data_time: 0.0076 memory: 5828 grad_norm: 3.1779 loss: 2.3012 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3012 2023/06/05 03:03:57 - mmengine - INFO - Epoch(train) [56][2440/2569] lr: 4.0000e-02 eta: 17:51:37 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 3.1580 loss: 2.5069 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5069 2023/06/05 03:04:02 - mmengine - INFO - Epoch(train) [56][2460/2569] lr: 4.0000e-02 eta: 17:51:31 time: 0.2586 data_time: 0.0075 memory: 5828 grad_norm: 3.0463 loss: 2.5017 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5017 2023/06/05 03:04:08 - mmengine - INFO - Epoch(train) [56][2480/2569] lr: 4.0000e-02 eta: 17:51:26 time: 0.2723 data_time: 0.0070 memory: 5828 grad_norm: 3.1178 loss: 2.4545 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4545 2023/06/05 03:04:13 - mmengine - INFO - Epoch(train) [56][2500/2569] lr: 4.0000e-02 eta: 17:51:21 time: 0.2633 data_time: 0.0069 memory: 5828 grad_norm: 3.0956 loss: 2.3854 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3854 2023/06/05 03:04:18 - mmengine - INFO - Epoch(train) [56][2520/2569] lr: 4.0000e-02 eta: 17:51:15 time: 0.2568 data_time: 0.0076 memory: 5828 grad_norm: 3.1446 loss: 2.7191 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7191 2023/06/05 03:04:24 - mmengine - INFO - Epoch(train) [56][2540/2569] lr: 4.0000e-02 eta: 17:51:10 time: 0.2703 data_time: 0.0071 memory: 5828 grad_norm: 3.1111 loss: 2.5268 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5268 2023/06/05 03:04:29 - mmengine - INFO - Epoch(train) [56][2560/2569] lr: 4.0000e-02 eta: 17:51:04 time: 0.2561 data_time: 0.0082 memory: 5828 grad_norm: 3.0741 loss: 2.6115 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6115 2023/06/05 03:04:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:04:31 - mmengine - INFO - Epoch(train) [56][2569/2569] lr: 4.0000e-02 eta: 17:51:02 time: 0.2613 data_time: 0.0077 memory: 5828 grad_norm: 3.1551 loss: 2.4017 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4017 2023/06/05 03:04:31 - mmengine - INFO - Saving checkpoint at 56 epochs 2023/06/05 03:04:39 - mmengine - INFO - Epoch(train) [57][ 20/2569] lr: 4.0000e-02 eta: 17:50:58 time: 0.3071 data_time: 0.0565 memory: 5828 grad_norm: 3.1069 loss: 2.6308 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6308 2023/06/05 03:04:44 - mmengine - INFO - Epoch(train) [57][ 40/2569] lr: 4.0000e-02 eta: 17:50:52 time: 0.2649 data_time: 0.0079 memory: 5828 grad_norm: 3.1150 loss: 2.5360 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5360 2023/06/05 03:04:50 - mmengine - INFO - Epoch(train) [57][ 60/2569] lr: 4.0000e-02 eta: 17:50:47 time: 0.2585 data_time: 0.0075 memory: 5828 grad_norm: 3.0427 loss: 2.7069 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7069 2023/06/05 03:04:55 - mmengine - INFO - Epoch(train) [57][ 80/2569] lr: 4.0000e-02 eta: 17:50:41 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 3.1343 loss: 2.4525 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4525 2023/06/05 03:05:00 - mmengine - INFO - Epoch(train) [57][ 100/2569] lr: 4.0000e-02 eta: 17:50:36 time: 0.2575 data_time: 0.0073 memory: 5828 grad_norm: 3.0654 loss: 2.5597 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5597 2023/06/05 03:05:05 - mmengine - INFO - Epoch(train) [57][ 120/2569] lr: 4.0000e-02 eta: 17:50:30 time: 0.2635 data_time: 0.0079 memory: 5828 grad_norm: 3.1260 loss: 2.2740 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2740 2023/06/05 03:05:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:05:11 - mmengine - INFO - Epoch(train) [57][ 140/2569] lr: 4.0000e-02 eta: 17:50:25 time: 0.2621 data_time: 0.0077 memory: 5828 grad_norm: 3.1129 loss: 2.4833 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4833 2023/06/05 03:05:16 - mmengine - INFO - Epoch(train) [57][ 160/2569] lr: 4.0000e-02 eta: 17:50:19 time: 0.2619 data_time: 0.0075 memory: 5828 grad_norm: 3.1065 loss: 2.6060 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6060 2023/06/05 03:05:21 - mmengine - INFO - Epoch(train) [57][ 180/2569] lr: 4.0000e-02 eta: 17:50:14 time: 0.2723 data_time: 0.0071 memory: 5828 grad_norm: 3.1362 loss: 2.2627 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2627 2023/06/05 03:05:26 - mmengine - INFO - Epoch(train) [57][ 200/2569] lr: 4.0000e-02 eta: 17:50:09 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 3.1628 loss: 2.5519 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5519 2023/06/05 03:05:32 - mmengine - INFO - Epoch(train) [57][ 220/2569] lr: 4.0000e-02 eta: 17:50:03 time: 0.2614 data_time: 0.0078 memory: 5828 grad_norm: 3.1276 loss: 2.9605 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9605 2023/06/05 03:05:37 - mmengine - INFO - Epoch(train) [57][ 240/2569] lr: 4.0000e-02 eta: 17:49:58 time: 0.2626 data_time: 0.0077 memory: 5828 grad_norm: 3.0651 loss: 2.4647 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4647 2023/06/05 03:05:42 - mmengine - INFO - Epoch(train) [57][ 260/2569] lr: 4.0000e-02 eta: 17:49:53 time: 0.2674 data_time: 0.0075 memory: 5828 grad_norm: 3.1488 loss: 2.4386 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4386 2023/06/05 03:05:48 - mmengine - INFO - Epoch(train) [57][ 280/2569] lr: 4.0000e-02 eta: 17:49:47 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 3.1781 loss: 2.4097 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4097 2023/06/05 03:05:53 - mmengine - INFO - Epoch(train) [57][ 300/2569] lr: 4.0000e-02 eta: 17:49:42 time: 0.2702 data_time: 0.0075 memory: 5828 grad_norm: 3.1827 loss: 2.6348 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6348 2023/06/05 03:05:58 - mmengine - INFO - Epoch(train) [57][ 320/2569] lr: 4.0000e-02 eta: 17:49:36 time: 0.2568 data_time: 0.0072 memory: 5828 grad_norm: 3.1208 loss: 2.4908 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4908 2023/06/05 03:06:03 - mmengine - INFO - Epoch(train) [57][ 340/2569] lr: 4.0000e-02 eta: 17:49:31 time: 0.2619 data_time: 0.0074 memory: 5828 grad_norm: 3.0859 loss: 2.5492 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5492 2023/06/05 03:06:08 - mmengine - INFO - Epoch(train) [57][ 360/2569] lr: 4.0000e-02 eta: 17:49:25 time: 0.2563 data_time: 0.0074 memory: 5828 grad_norm: 3.1252 loss: 2.6789 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6789 2023/06/05 03:06:14 - mmengine - INFO - Epoch(train) [57][ 380/2569] lr: 4.0000e-02 eta: 17:49:20 time: 0.2621 data_time: 0.0072 memory: 5828 grad_norm: 3.1300 loss: 2.6554 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6554 2023/06/05 03:06:19 - mmengine - INFO - Epoch(train) [57][ 400/2569] lr: 4.0000e-02 eta: 17:49:14 time: 0.2575 data_time: 0.0077 memory: 5828 grad_norm: 3.1052 loss: 2.7358 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7358 2023/06/05 03:06:24 - mmengine - INFO - Epoch(train) [57][ 420/2569] lr: 4.0000e-02 eta: 17:49:09 time: 0.2717 data_time: 0.0075 memory: 5828 grad_norm: 3.0901 loss: 2.4212 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4212 2023/06/05 03:06:30 - mmengine - INFO - Epoch(train) [57][ 440/2569] lr: 4.0000e-02 eta: 17:49:04 time: 0.2630 data_time: 0.0076 memory: 5828 grad_norm: 3.1294 loss: 2.5299 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.5299 2023/06/05 03:06:35 - mmengine - INFO - Epoch(train) [57][ 460/2569] lr: 4.0000e-02 eta: 17:48:58 time: 0.2580 data_time: 0.0078 memory: 5828 grad_norm: 3.1433 loss: 2.4261 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4261 2023/06/05 03:06:40 - mmengine - INFO - Epoch(train) [57][ 480/2569] lr: 4.0000e-02 eta: 17:48:53 time: 0.2606 data_time: 0.0077 memory: 5828 grad_norm: 3.1081 loss: 2.5045 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5045 2023/06/05 03:06:45 - mmengine - INFO - Epoch(train) [57][ 500/2569] lr: 4.0000e-02 eta: 17:48:47 time: 0.2640 data_time: 0.0075 memory: 5828 grad_norm: 3.0663 loss: 2.6548 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6548 2023/06/05 03:06:50 - mmengine - INFO - Epoch(train) [57][ 520/2569] lr: 4.0000e-02 eta: 17:48:42 time: 0.2575 data_time: 0.0079 memory: 5828 grad_norm: 3.0911 loss: 2.6595 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6595 2023/06/05 03:06:56 - mmengine - INFO - Epoch(train) [57][ 540/2569] lr: 4.0000e-02 eta: 17:48:36 time: 0.2629 data_time: 0.0079 memory: 5828 grad_norm: 3.0969 loss: 2.5726 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5726 2023/06/05 03:07:01 - mmengine - INFO - Epoch(train) [57][ 560/2569] lr: 4.0000e-02 eta: 17:48:31 time: 0.2577 data_time: 0.0068 memory: 5828 grad_norm: 3.0995 loss: 2.4017 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4017 2023/06/05 03:07:06 - mmengine - INFO - Epoch(train) [57][ 580/2569] lr: 4.0000e-02 eta: 17:48:25 time: 0.2690 data_time: 0.0076 memory: 5828 grad_norm: 3.1399 loss: 2.5603 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5603 2023/06/05 03:07:12 - mmengine - INFO - Epoch(train) [57][ 600/2569] lr: 4.0000e-02 eta: 17:48:20 time: 0.2699 data_time: 0.0074 memory: 5828 grad_norm: 3.1869 loss: 2.4186 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4186 2023/06/05 03:07:17 - mmengine - INFO - Epoch(train) [57][ 620/2569] lr: 4.0000e-02 eta: 17:48:15 time: 0.2672 data_time: 0.0076 memory: 5828 grad_norm: 3.1010 loss: 2.4566 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4566 2023/06/05 03:07:22 - mmengine - INFO - Epoch(train) [57][ 640/2569] lr: 4.0000e-02 eta: 17:48:10 time: 0.2681 data_time: 0.0077 memory: 5828 grad_norm: 3.1143 loss: 2.5087 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5087 2023/06/05 03:07:28 - mmengine - INFO - Epoch(train) [57][ 660/2569] lr: 4.0000e-02 eta: 17:48:05 time: 0.2747 data_time: 0.0078 memory: 5828 grad_norm: 3.1245 loss: 2.1993 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1993 2023/06/05 03:07:33 - mmengine - INFO - Epoch(train) [57][ 680/2569] lr: 4.0000e-02 eta: 17:48:00 time: 0.2785 data_time: 0.0075 memory: 5828 grad_norm: 3.0412 loss: 2.4558 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4558 2023/06/05 03:07:39 - mmengine - INFO - Epoch(train) [57][ 700/2569] lr: 4.0000e-02 eta: 17:47:54 time: 0.2559 data_time: 0.0077 memory: 5828 grad_norm: 3.0835 loss: 2.3534 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3534 2023/06/05 03:07:44 - mmengine - INFO - Epoch(train) [57][ 720/2569] lr: 4.0000e-02 eta: 17:47:48 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 3.0731 loss: 3.2830 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.2830 2023/06/05 03:07:49 - mmengine - INFO - Epoch(train) [57][ 740/2569] lr: 4.0000e-02 eta: 17:47:43 time: 0.2725 data_time: 0.0074 memory: 5828 grad_norm: 3.1115 loss: 2.8039 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8039 2023/06/05 03:07:54 - mmengine - INFO - Epoch(train) [57][ 760/2569] lr: 4.0000e-02 eta: 17:47:38 time: 0.2628 data_time: 0.0079 memory: 5828 grad_norm: 3.1246 loss: 2.6545 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6545 2023/06/05 03:08:00 - mmengine - INFO - Epoch(train) [57][ 780/2569] lr: 4.0000e-02 eta: 17:47:32 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 3.1045 loss: 2.2670 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2670 2023/06/05 03:08:05 - mmengine - INFO - Epoch(train) [57][ 800/2569] lr: 4.0000e-02 eta: 17:47:27 time: 0.2583 data_time: 0.0074 memory: 5828 grad_norm: 3.1198 loss: 2.2524 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2524 2023/06/05 03:08:10 - mmengine - INFO - Epoch(train) [57][ 820/2569] lr: 4.0000e-02 eta: 17:47:22 time: 0.2690 data_time: 0.0074 memory: 5828 grad_norm: 3.1094 loss: 2.7024 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.7024 2023/06/05 03:08:15 - mmengine - INFO - Epoch(train) [57][ 840/2569] lr: 4.0000e-02 eta: 17:47:16 time: 0.2579 data_time: 0.0078 memory: 5828 grad_norm: 3.0192 loss: 2.7807 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7807 2023/06/05 03:08:21 - mmengine - INFO - Epoch(train) [57][ 860/2569] lr: 4.0000e-02 eta: 17:47:11 time: 0.2630 data_time: 0.0077 memory: 5828 grad_norm: 3.1189 loss: 2.1096 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1096 2023/06/05 03:08:26 - mmengine - INFO - Epoch(train) [57][ 880/2569] lr: 4.0000e-02 eta: 17:47:06 time: 0.2786 data_time: 0.0075 memory: 5828 grad_norm: 3.1032 loss: 2.4139 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4139 2023/06/05 03:08:32 - mmengine - INFO - Epoch(train) [57][ 900/2569] lr: 4.0000e-02 eta: 17:47:00 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.0728 loss: 2.4930 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4930 2023/06/05 03:08:37 - mmengine - INFO - Epoch(train) [57][ 920/2569] lr: 4.0000e-02 eta: 17:46:55 time: 0.2733 data_time: 0.0074 memory: 5828 grad_norm: 3.1582 loss: 2.6925 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6925 2023/06/05 03:08:42 - mmengine - INFO - Epoch(train) [57][ 940/2569] lr: 4.0000e-02 eta: 17:46:50 time: 0.2629 data_time: 0.0070 memory: 5828 grad_norm: 3.0735 loss: 2.5070 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5070 2023/06/05 03:08:47 - mmengine - INFO - Epoch(train) [57][ 960/2569] lr: 4.0000e-02 eta: 17:46:44 time: 0.2577 data_time: 0.0072 memory: 5828 grad_norm: 3.1873 loss: 2.3062 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3062 2023/06/05 03:08:53 - mmengine - INFO - Epoch(train) [57][ 980/2569] lr: 4.0000e-02 eta: 17:46:39 time: 0.2629 data_time: 0.0079 memory: 5828 grad_norm: 3.0594 loss: 2.5823 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5823 2023/06/05 03:08:58 - mmengine - INFO - Epoch(train) [57][1000/2569] lr: 4.0000e-02 eta: 17:46:33 time: 0.2611 data_time: 0.0078 memory: 5828 grad_norm: 3.0361 loss: 2.8517 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8517 2023/06/05 03:09:03 - mmengine - INFO - Epoch(train) [57][1020/2569] lr: 4.0000e-02 eta: 17:46:28 time: 0.2578 data_time: 0.0074 memory: 5828 grad_norm: 3.1887 loss: 2.4387 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4387 2023/06/05 03:09:08 - mmengine - INFO - Epoch(train) [57][1040/2569] lr: 4.0000e-02 eta: 17:46:22 time: 0.2703 data_time: 0.0070 memory: 5828 grad_norm: 3.1617 loss: 2.4280 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4280 2023/06/05 03:09:14 - mmengine - INFO - Epoch(train) [57][1060/2569] lr: 4.0000e-02 eta: 17:46:17 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 3.0890 loss: 2.2491 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2491 2023/06/05 03:09:19 - mmengine - INFO - Epoch(train) [57][1080/2569] lr: 4.0000e-02 eta: 17:46:12 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 3.1339 loss: 2.7041 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7041 2023/06/05 03:09:24 - mmengine - INFO - Epoch(train) [57][1100/2569] lr: 4.0000e-02 eta: 17:46:06 time: 0.2637 data_time: 0.0077 memory: 5828 grad_norm: 3.0854 loss: 2.0989 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0989 2023/06/05 03:09:29 - mmengine - INFO - Epoch(train) [57][1120/2569] lr: 4.0000e-02 eta: 17:46:01 time: 0.2571 data_time: 0.0073 memory: 5828 grad_norm: 3.0641 loss: 2.3869 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3869 2023/06/05 03:09:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:09:35 - mmengine - INFO - Epoch(train) [57][1140/2569] lr: 4.0000e-02 eta: 17:45:55 time: 0.2615 data_time: 0.0071 memory: 5828 grad_norm: 3.1123 loss: 2.4370 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4370 2023/06/05 03:09:40 - mmengine - INFO - Epoch(train) [57][1160/2569] lr: 4.0000e-02 eta: 17:45:50 time: 0.2571 data_time: 0.0072 memory: 5828 grad_norm: 3.0569 loss: 2.5365 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5365 2023/06/05 03:09:45 - mmengine - INFO - Epoch(train) [57][1180/2569] lr: 4.0000e-02 eta: 17:45:44 time: 0.2635 data_time: 0.0078 memory: 5828 grad_norm: 3.0964 loss: 2.6456 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6456 2023/06/05 03:09:50 - mmengine - INFO - Epoch(train) [57][1200/2569] lr: 4.0000e-02 eta: 17:45:38 time: 0.2565 data_time: 0.0071 memory: 5828 grad_norm: 3.0869 loss: 2.5856 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5856 2023/06/05 03:09:55 - mmengine - INFO - Epoch(train) [57][1220/2569] lr: 4.0000e-02 eta: 17:45:33 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 3.0814 loss: 2.6737 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6737 2023/06/05 03:10:01 - mmengine - INFO - Epoch(train) [57][1240/2569] lr: 4.0000e-02 eta: 17:45:28 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 3.0699 loss: 2.7582 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7582 2023/06/05 03:10:06 - mmengine - INFO - Epoch(train) [57][1260/2569] lr: 4.0000e-02 eta: 17:45:22 time: 0.2575 data_time: 0.0075 memory: 5828 grad_norm: 3.0897 loss: 2.2194 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2194 2023/06/05 03:10:11 - mmengine - INFO - Epoch(train) [57][1280/2569] lr: 4.0000e-02 eta: 17:45:17 time: 0.2698 data_time: 0.0075 memory: 5828 grad_norm: 3.1223 loss: 2.7052 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7052 2023/06/05 03:10:17 - mmengine - INFO - Epoch(train) [57][1300/2569] lr: 4.0000e-02 eta: 17:45:12 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 3.1340 loss: 2.2449 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.2449 2023/06/05 03:10:22 - mmengine - INFO - Epoch(train) [57][1320/2569] lr: 4.0000e-02 eta: 17:45:06 time: 0.2576 data_time: 0.0072 memory: 5828 grad_norm: 3.1361 loss: 2.3846 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3846 2023/06/05 03:10:27 - mmengine - INFO - Epoch(train) [57][1340/2569] lr: 4.0000e-02 eta: 17:45:01 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 3.0896 loss: 2.5504 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5504 2023/06/05 03:10:32 - mmengine - INFO - Epoch(train) [57][1360/2569] lr: 4.0000e-02 eta: 17:44:55 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 3.1270 loss: 2.4879 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4879 2023/06/05 03:10:38 - mmengine - INFO - Epoch(train) [57][1380/2569] lr: 4.0000e-02 eta: 17:44:50 time: 0.2582 data_time: 0.0076 memory: 5828 grad_norm: 3.1120 loss: 2.4461 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4461 2023/06/05 03:10:43 - mmengine - INFO - Epoch(train) [57][1400/2569] lr: 4.0000e-02 eta: 17:44:44 time: 0.2568 data_time: 0.0071 memory: 5828 grad_norm: 3.0893 loss: 2.4036 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4036 2023/06/05 03:10:48 - mmengine - INFO - Epoch(train) [57][1420/2569] lr: 4.0000e-02 eta: 17:44:39 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 3.1381 loss: 2.6732 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6732 2023/06/05 03:10:54 - mmengine - INFO - Epoch(train) [57][1440/2569] lr: 4.0000e-02 eta: 17:44:34 time: 0.2727 data_time: 0.0075 memory: 5828 grad_norm: 3.0704 loss: 2.2267 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2267 2023/06/05 03:10:59 - mmengine - INFO - Epoch(train) [57][1460/2569] lr: 4.0000e-02 eta: 17:44:28 time: 0.2589 data_time: 0.0072 memory: 5828 grad_norm: 3.1425 loss: 2.6001 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6001 2023/06/05 03:11:04 - mmengine - INFO - Epoch(train) [57][1480/2569] lr: 4.0000e-02 eta: 17:44:23 time: 0.2694 data_time: 0.0074 memory: 5828 grad_norm: 3.0875 loss: 2.9113 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9113 2023/06/05 03:11:09 - mmengine - INFO - Epoch(train) [57][1500/2569] lr: 4.0000e-02 eta: 17:44:17 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 3.0967 loss: 2.4909 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4909 2023/06/05 03:11:15 - mmengine - INFO - Epoch(train) [57][1520/2569] lr: 4.0000e-02 eta: 17:44:12 time: 0.2576 data_time: 0.0073 memory: 5828 grad_norm: 3.1668 loss: 2.8977 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8977 2023/06/05 03:11:20 - mmengine - INFO - Epoch(train) [57][1540/2569] lr: 4.0000e-02 eta: 17:44:06 time: 0.2576 data_time: 0.0075 memory: 5828 grad_norm: 3.1372 loss: 2.6434 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6434 2023/06/05 03:11:25 - mmengine - INFO - Epoch(train) [57][1560/2569] lr: 4.0000e-02 eta: 17:44:01 time: 0.2671 data_time: 0.0075 memory: 5828 grad_norm: 3.0537 loss: 2.5258 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5258 2023/06/05 03:11:30 - mmengine - INFO - Epoch(train) [57][1580/2569] lr: 4.0000e-02 eta: 17:43:56 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 3.0769 loss: 2.7764 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7764 2023/06/05 03:11:36 - mmengine - INFO - Epoch(train) [57][1600/2569] lr: 4.0000e-02 eta: 17:43:50 time: 0.2589 data_time: 0.0072 memory: 5828 grad_norm: 3.1313 loss: 2.4691 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4691 2023/06/05 03:11:41 - mmengine - INFO - Epoch(train) [57][1620/2569] lr: 4.0000e-02 eta: 17:43:45 time: 0.2583 data_time: 0.0074 memory: 5828 grad_norm: 3.1016 loss: 2.4471 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4471 2023/06/05 03:11:46 - mmengine - INFO - Epoch(train) [57][1640/2569] lr: 4.0000e-02 eta: 17:43:39 time: 0.2623 data_time: 0.0071 memory: 5828 grad_norm: 3.2080 loss: 2.2550 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2550 2023/06/05 03:11:51 - mmengine - INFO - Epoch(train) [57][1660/2569] lr: 4.0000e-02 eta: 17:43:34 time: 0.2581 data_time: 0.0073 memory: 5828 grad_norm: 3.0897 loss: 2.4705 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4705 2023/06/05 03:11:56 - mmengine - INFO - Epoch(train) [57][1680/2569] lr: 4.0000e-02 eta: 17:43:28 time: 0.2577 data_time: 0.0075 memory: 5828 grad_norm: 3.0950 loss: 2.5826 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5826 2023/06/05 03:12:02 - mmengine - INFO - Epoch(train) [57][1700/2569] lr: 4.0000e-02 eta: 17:43:22 time: 0.2614 data_time: 0.0075 memory: 5828 grad_norm: 3.1395 loss: 2.8063 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8063 2023/06/05 03:12:07 - mmengine - INFO - Epoch(train) [57][1720/2569] lr: 4.0000e-02 eta: 17:43:17 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 3.0758 loss: 2.6528 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6528 2023/06/05 03:12:12 - mmengine - INFO - Epoch(train) [57][1740/2569] lr: 4.0000e-02 eta: 17:43:12 time: 0.2643 data_time: 0.0075 memory: 5828 grad_norm: 3.1361 loss: 2.4507 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4507 2023/06/05 03:12:17 - mmengine - INFO - Epoch(train) [57][1760/2569] lr: 4.0000e-02 eta: 17:43:06 time: 0.2590 data_time: 0.0075 memory: 5828 grad_norm: 3.1512 loss: 2.6655 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.6655 2023/06/05 03:12:23 - mmengine - INFO - Epoch(train) [57][1780/2569] lr: 4.0000e-02 eta: 17:43:01 time: 0.2590 data_time: 0.0072 memory: 5828 grad_norm: 3.1490 loss: 2.5037 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5037 2023/06/05 03:12:28 - mmengine - INFO - Epoch(train) [57][1800/2569] lr: 4.0000e-02 eta: 17:42:55 time: 0.2674 data_time: 0.0074 memory: 5828 grad_norm: 3.1268 loss: 2.6924 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6924 2023/06/05 03:12:33 - mmengine - INFO - Epoch(train) [57][1820/2569] lr: 4.0000e-02 eta: 17:42:50 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.1195 loss: 2.7224 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7224 2023/06/05 03:12:39 - mmengine - INFO - Epoch(train) [57][1840/2569] lr: 4.0000e-02 eta: 17:42:45 time: 0.2640 data_time: 0.0077 memory: 5828 grad_norm: 3.1083 loss: 2.7661 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7661 2023/06/05 03:12:44 - mmengine - INFO - Epoch(train) [57][1860/2569] lr: 4.0000e-02 eta: 17:42:39 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 3.0497 loss: 2.3032 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3032 2023/06/05 03:12:49 - mmengine - INFO - Epoch(train) [57][1880/2569] lr: 4.0000e-02 eta: 17:42:34 time: 0.2569 data_time: 0.0078 memory: 5828 grad_norm: 3.0949 loss: 2.6876 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6876 2023/06/05 03:12:54 - mmengine - INFO - Epoch(train) [57][1900/2569] lr: 4.0000e-02 eta: 17:42:28 time: 0.2655 data_time: 0.0074 memory: 5828 grad_norm: 3.1210 loss: 2.6931 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6931 2023/06/05 03:13:00 - mmengine - INFO - Epoch(train) [57][1920/2569] lr: 4.0000e-02 eta: 17:42:23 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 3.1034 loss: 2.7116 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7116 2023/06/05 03:13:05 - mmengine - INFO - Epoch(train) [57][1940/2569] lr: 4.0000e-02 eta: 17:42:17 time: 0.2609 data_time: 0.0071 memory: 5828 grad_norm: 3.1105 loss: 2.2695 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2695 2023/06/05 03:13:10 - mmengine - INFO - Epoch(train) [57][1960/2569] lr: 4.0000e-02 eta: 17:42:12 time: 0.2579 data_time: 0.0076 memory: 5828 grad_norm: 3.1202 loss: 2.7895 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7895 2023/06/05 03:13:15 - mmengine - INFO - Epoch(train) [57][1980/2569] lr: 4.0000e-02 eta: 17:42:06 time: 0.2597 data_time: 0.0073 memory: 5828 grad_norm: 3.1343 loss: 2.3640 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3640 2023/06/05 03:13:21 - mmengine - INFO - Epoch(train) [57][2000/2569] lr: 4.0000e-02 eta: 17:42:01 time: 0.2707 data_time: 0.0075 memory: 5828 grad_norm: 3.0487 loss: 2.3540 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3540 2023/06/05 03:13:26 - mmengine - INFO - Epoch(train) [57][2020/2569] lr: 4.0000e-02 eta: 17:41:56 time: 0.2619 data_time: 0.0075 memory: 5828 grad_norm: 3.1203 loss: 2.5812 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5812 2023/06/05 03:13:31 - mmengine - INFO - Epoch(train) [57][2040/2569] lr: 4.0000e-02 eta: 17:41:51 time: 0.2732 data_time: 0.0075 memory: 5828 grad_norm: 3.0813 loss: 2.6096 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6096 2023/06/05 03:13:37 - mmengine - INFO - Epoch(train) [57][2060/2569] lr: 4.0000e-02 eta: 17:41:45 time: 0.2656 data_time: 0.0075 memory: 5828 grad_norm: 3.1357 loss: 2.5733 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5733 2023/06/05 03:13:42 - mmengine - INFO - Epoch(train) [57][2080/2569] lr: 4.0000e-02 eta: 17:41:40 time: 0.2630 data_time: 0.0076 memory: 5828 grad_norm: 3.1444 loss: 2.7335 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7335 2023/06/05 03:13:47 - mmengine - INFO - Epoch(train) [57][2100/2569] lr: 4.0000e-02 eta: 17:41:34 time: 0.2576 data_time: 0.0072 memory: 5828 grad_norm: 3.0664 loss: 2.6100 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6100 2023/06/05 03:13:52 - mmengine - INFO - Epoch(train) [57][2120/2569] lr: 4.0000e-02 eta: 17:41:29 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 3.0777 loss: 2.4742 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4742 2023/06/05 03:13:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:13:58 - mmengine - INFO - Epoch(train) [57][2140/2569] lr: 4.0000e-02 eta: 17:41:24 time: 0.2727 data_time: 0.0075 memory: 5828 grad_norm: 3.1113 loss: 2.3636 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3636 2023/06/05 03:14:03 - mmengine - INFO - Epoch(train) [57][2160/2569] lr: 4.0000e-02 eta: 17:41:18 time: 0.2619 data_time: 0.0079 memory: 5828 grad_norm: 3.0833 loss: 2.4867 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4867 2023/06/05 03:14:08 - mmengine - INFO - Epoch(train) [57][2180/2569] lr: 4.0000e-02 eta: 17:41:13 time: 0.2724 data_time: 0.0076 memory: 5828 grad_norm: 3.1157 loss: 2.4268 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4268 2023/06/05 03:14:14 - mmengine - INFO - Epoch(train) [57][2200/2569] lr: 4.0000e-02 eta: 17:41:08 time: 0.2661 data_time: 0.0077 memory: 5828 grad_norm: 3.0830 loss: 2.4749 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4749 2023/06/05 03:14:19 - mmengine - INFO - Epoch(train) [57][2220/2569] lr: 4.0000e-02 eta: 17:41:02 time: 0.2573 data_time: 0.0076 memory: 5828 grad_norm: 3.0707 loss: 2.4187 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4187 2023/06/05 03:14:24 - mmengine - INFO - Epoch(train) [57][2240/2569] lr: 4.0000e-02 eta: 17:40:57 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 3.1427 loss: 2.3841 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.3841 2023/06/05 03:14:30 - mmengine - INFO - Epoch(train) [57][2260/2569] lr: 4.0000e-02 eta: 17:40:51 time: 0.2631 data_time: 0.0072 memory: 5828 grad_norm: 3.0500 loss: 2.6513 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6513 2023/06/05 03:14:35 - mmengine - INFO - Epoch(train) [57][2280/2569] lr: 4.0000e-02 eta: 17:40:46 time: 0.2668 data_time: 0.0074 memory: 5828 grad_norm: 3.1197 loss: 2.2893 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.2893 2023/06/05 03:14:40 - mmengine - INFO - Epoch(train) [57][2300/2569] lr: 4.0000e-02 eta: 17:40:41 time: 0.2703 data_time: 0.0073 memory: 5828 grad_norm: 3.1141 loss: 2.5237 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5237 2023/06/05 03:14:46 - mmengine - INFO - Epoch(train) [57][2320/2569] lr: 4.0000e-02 eta: 17:40:36 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 3.0243 loss: 2.5716 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5716 2023/06/05 03:14:51 - mmengine - INFO - Epoch(train) [57][2340/2569] lr: 4.0000e-02 eta: 17:40:30 time: 0.2699 data_time: 0.0074 memory: 5828 grad_norm: 3.1232 loss: 3.0740 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0740 2023/06/05 03:14:57 - mmengine - INFO - Epoch(train) [57][2360/2569] lr: 4.0000e-02 eta: 17:40:25 time: 0.2732 data_time: 0.0070 memory: 5828 grad_norm: 3.1337 loss: 2.6349 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6349 2023/06/05 03:15:02 - mmengine - INFO - Epoch(train) [57][2380/2569] lr: 4.0000e-02 eta: 17:40:20 time: 0.2689 data_time: 0.0075 memory: 5828 grad_norm: 3.0654 loss: 2.4536 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4536 2023/06/05 03:15:07 - mmengine - INFO - Epoch(train) [57][2400/2569] lr: 4.0000e-02 eta: 17:40:15 time: 0.2633 data_time: 0.0080 memory: 5828 grad_norm: 3.1203 loss: 3.0469 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0469 2023/06/05 03:15:12 - mmengine - INFO - Epoch(train) [57][2420/2569] lr: 4.0000e-02 eta: 17:40:09 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 3.0920 loss: 2.5951 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5951 2023/06/05 03:15:18 - mmengine - INFO - Epoch(train) [57][2440/2569] lr: 4.0000e-02 eta: 17:40:04 time: 0.2573 data_time: 0.0070 memory: 5828 grad_norm: 3.1354 loss: 2.4407 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4407 2023/06/05 03:15:23 - mmengine - INFO - Epoch(train) [57][2460/2569] lr: 4.0000e-02 eta: 17:39:58 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 3.1223 loss: 2.3731 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3731 2023/06/05 03:15:28 - mmengine - INFO - Epoch(train) [57][2480/2569] lr: 4.0000e-02 eta: 17:39:53 time: 0.2745 data_time: 0.0072 memory: 5828 grad_norm: 3.0789 loss: 2.7538 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7538 2023/06/05 03:15:34 - mmengine - INFO - Epoch(train) [57][2500/2569] lr: 4.0000e-02 eta: 17:39:48 time: 0.2685 data_time: 0.0076 memory: 5828 grad_norm: 3.0946 loss: 2.3315 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3315 2023/06/05 03:15:39 - mmengine - INFO - Epoch(train) [57][2520/2569] lr: 4.0000e-02 eta: 17:39:43 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.0602 loss: 2.7668 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7668 2023/06/05 03:15:44 - mmengine - INFO - Epoch(train) [57][2540/2569] lr: 4.0000e-02 eta: 17:39:37 time: 0.2584 data_time: 0.0076 memory: 5828 grad_norm: 3.0989 loss: 2.7274 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7274 2023/06/05 03:15:49 - mmengine - INFO - Epoch(train) [57][2560/2569] lr: 4.0000e-02 eta: 17:39:32 time: 0.2660 data_time: 0.0077 memory: 5828 grad_norm: 3.1191 loss: 2.5577 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5577 2023/06/05 03:15:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:15:52 - mmengine - INFO - Epoch(train) [57][2569/2569] lr: 4.0000e-02 eta: 17:39:29 time: 0.2591 data_time: 0.0074 memory: 5828 grad_norm: 3.1363 loss: 2.3679 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.3679 2023/06/05 03:15:59 - mmengine - INFO - Epoch(train) [58][ 20/2569] lr: 4.0000e-02 eta: 17:39:26 time: 0.3415 data_time: 0.0683 memory: 5828 grad_norm: 3.0690 loss: 2.8318 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8318 2023/06/05 03:16:04 - mmengine - INFO - Epoch(train) [58][ 40/2569] lr: 4.0000e-02 eta: 17:39:21 time: 0.2722 data_time: 0.0078 memory: 5828 grad_norm: 3.1149 loss: 2.5021 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5021 2023/06/05 03:16:09 - mmengine - INFO - Epoch(train) [58][ 60/2569] lr: 4.0000e-02 eta: 17:39:15 time: 0.2573 data_time: 0.0073 memory: 5828 grad_norm: 3.0949 loss: 2.4292 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4292 2023/06/05 03:16:15 - mmengine - INFO - Epoch(train) [58][ 80/2569] lr: 4.0000e-02 eta: 17:39:10 time: 0.2690 data_time: 0.0074 memory: 5828 grad_norm: 3.1547 loss: 2.6273 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6273 2023/06/05 03:16:20 - mmengine - INFO - Epoch(train) [58][ 100/2569] lr: 4.0000e-02 eta: 17:39:05 time: 0.2591 data_time: 0.0071 memory: 5828 grad_norm: 3.1439 loss: 2.6456 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6456 2023/06/05 03:16:25 - mmengine - INFO - Epoch(train) [58][ 120/2569] lr: 4.0000e-02 eta: 17:38:59 time: 0.2608 data_time: 0.0077 memory: 5828 grad_norm: 3.1100 loss: 2.7412 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7412 2023/06/05 03:16:30 - mmengine - INFO - Epoch(train) [58][ 140/2569] lr: 4.0000e-02 eta: 17:38:54 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 3.1666 loss: 2.2791 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2791 2023/06/05 03:16:35 - mmengine - INFO - Epoch(train) [58][ 160/2569] lr: 4.0000e-02 eta: 17:38:48 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.1267 loss: 2.5012 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5012 2023/06/05 03:16:41 - mmengine - INFO - Epoch(train) [58][ 180/2569] lr: 4.0000e-02 eta: 17:38:43 time: 0.2700 data_time: 0.0073 memory: 5828 grad_norm: 3.0511 loss: 2.3754 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3754 2023/06/05 03:16:46 - mmengine - INFO - Epoch(train) [58][ 200/2569] lr: 4.0000e-02 eta: 17:38:37 time: 0.2562 data_time: 0.0077 memory: 5828 grad_norm: 3.0787 loss: 2.2906 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2906 2023/06/05 03:16:51 - mmengine - INFO - Epoch(train) [58][ 220/2569] lr: 4.0000e-02 eta: 17:38:32 time: 0.2610 data_time: 0.0072 memory: 5828 grad_norm: 3.1722 loss: 2.7336 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7336 2023/06/05 03:16:56 - mmengine - INFO - Epoch(train) [58][ 240/2569] lr: 4.0000e-02 eta: 17:38:26 time: 0.2606 data_time: 0.0074 memory: 5828 grad_norm: 3.1074 loss: 2.3523 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3523 2023/06/05 03:17:02 - mmengine - INFO - Epoch(train) [58][ 260/2569] lr: 4.0000e-02 eta: 17:38:21 time: 0.2606 data_time: 0.0077 memory: 5828 grad_norm: 3.1392 loss: 2.7081 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7081 2023/06/05 03:17:07 - mmengine - INFO - Epoch(train) [58][ 280/2569] lr: 4.0000e-02 eta: 17:38:15 time: 0.2606 data_time: 0.0074 memory: 5828 grad_norm: 3.0790 loss: 2.4965 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4965 2023/06/05 03:17:12 - mmengine - INFO - Epoch(train) [58][ 300/2569] lr: 4.0000e-02 eta: 17:38:10 time: 0.2572 data_time: 0.0073 memory: 5828 grad_norm: 3.1236 loss: 2.6929 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6929 2023/06/05 03:17:17 - mmengine - INFO - Epoch(train) [58][ 320/2569] lr: 4.0000e-02 eta: 17:38:05 time: 0.2717 data_time: 0.0071 memory: 5828 grad_norm: 3.1243 loss: 2.5460 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5460 2023/06/05 03:17:23 - mmengine - INFO - Epoch(train) [58][ 340/2569] lr: 4.0000e-02 eta: 17:37:59 time: 0.2565 data_time: 0.0074 memory: 5828 grad_norm: 3.1294 loss: 2.6624 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6624 2023/06/05 03:17:28 - mmengine - INFO - Epoch(train) [58][ 360/2569] lr: 4.0000e-02 eta: 17:37:54 time: 0.2597 data_time: 0.0077 memory: 5828 grad_norm: 3.0505 loss: 2.5644 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5644 2023/06/05 03:17:33 - mmengine - INFO - Epoch(train) [58][ 380/2569] lr: 4.0000e-02 eta: 17:37:48 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 3.0888 loss: 2.2333 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2333 2023/06/05 03:17:39 - mmengine - INFO - Epoch(train) [58][ 400/2569] lr: 4.0000e-02 eta: 17:37:43 time: 0.2696 data_time: 0.0077 memory: 5828 grad_norm: 3.2197 loss: 2.2492 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2492 2023/06/05 03:17:44 - mmengine - INFO - Epoch(train) [58][ 420/2569] lr: 4.0000e-02 eta: 17:37:38 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 3.1178 loss: 2.6660 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6660 2023/06/05 03:17:49 - mmengine - INFO - Epoch(train) [58][ 440/2569] lr: 4.0000e-02 eta: 17:37:32 time: 0.2592 data_time: 0.0078 memory: 5828 grad_norm: 3.1032 loss: 2.5473 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5473 2023/06/05 03:17:54 - mmengine - INFO - Epoch(train) [58][ 460/2569] lr: 4.0000e-02 eta: 17:37:27 time: 0.2636 data_time: 0.0078 memory: 5828 grad_norm: 3.1275 loss: 2.6104 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6104 2023/06/05 03:18:00 - mmengine - INFO - Epoch(train) [58][ 480/2569] lr: 4.0000e-02 eta: 17:37:21 time: 0.2582 data_time: 0.0087 memory: 5828 grad_norm: 3.0862 loss: 2.5156 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5156 2023/06/05 03:18:05 - mmengine - INFO - Epoch(train) [58][ 500/2569] lr: 4.0000e-02 eta: 17:37:16 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 3.1622 loss: 2.7120 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7120 2023/06/05 03:18:10 - mmengine - INFO - Epoch(train) [58][ 520/2569] lr: 4.0000e-02 eta: 17:37:10 time: 0.2594 data_time: 0.0077 memory: 5828 grad_norm: 3.1143 loss: 2.7086 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7086 2023/06/05 03:18:15 - mmengine - INFO - Epoch(train) [58][ 540/2569] lr: 4.0000e-02 eta: 17:37:05 time: 0.2628 data_time: 0.0069 memory: 5828 grad_norm: 3.1697 loss: 2.3333 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3333 2023/06/05 03:18:20 - mmengine - INFO - Epoch(train) [58][ 560/2569] lr: 4.0000e-02 eta: 17:36:59 time: 0.2563 data_time: 0.0073 memory: 5828 grad_norm: 3.0686 loss: 2.5310 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5310 2023/06/05 03:18:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:18:26 - mmengine - INFO - Epoch(train) [58][ 580/2569] lr: 4.0000e-02 eta: 17:36:54 time: 0.2683 data_time: 0.0074 memory: 5828 grad_norm: 3.0763 loss: 2.6671 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6671 2023/06/05 03:18:31 - mmengine - INFO - Epoch(train) [58][ 600/2569] lr: 4.0000e-02 eta: 17:36:48 time: 0.2589 data_time: 0.0071 memory: 5828 grad_norm: 3.1272 loss: 2.5574 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5574 2023/06/05 03:18:36 - mmengine - INFO - Epoch(train) [58][ 620/2569] lr: 4.0000e-02 eta: 17:36:43 time: 0.2631 data_time: 0.0080 memory: 5828 grad_norm: 3.1485 loss: 2.4171 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4171 2023/06/05 03:18:41 - mmengine - INFO - Epoch(train) [58][ 640/2569] lr: 4.0000e-02 eta: 17:36:38 time: 0.2595 data_time: 0.0073 memory: 5828 grad_norm: 3.1264 loss: 2.3602 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3602 2023/06/05 03:18:47 - mmengine - INFO - Epoch(train) [58][ 660/2569] lr: 4.0000e-02 eta: 17:36:32 time: 0.2564 data_time: 0.0071 memory: 5828 grad_norm: 3.0998 loss: 2.4834 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4834 2023/06/05 03:18:52 - mmengine - INFO - Epoch(train) [58][ 680/2569] lr: 4.0000e-02 eta: 17:36:27 time: 0.2705 data_time: 0.0070 memory: 5828 grad_norm: 3.1081 loss: 2.4167 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4167 2023/06/05 03:18:57 - mmengine - INFO - Epoch(train) [58][ 700/2569] lr: 4.0000e-02 eta: 17:36:21 time: 0.2565 data_time: 0.0075 memory: 5828 grad_norm: 3.0903 loss: 2.4043 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4043 2023/06/05 03:19:02 - mmengine - INFO - Epoch(train) [58][ 720/2569] lr: 4.0000e-02 eta: 17:36:16 time: 0.2654 data_time: 0.0068 memory: 5828 grad_norm: 3.1826 loss: 2.1645 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1645 2023/06/05 03:19:08 - mmengine - INFO - Epoch(train) [58][ 740/2569] lr: 4.0000e-02 eta: 17:36:10 time: 0.2649 data_time: 0.0069 memory: 5828 grad_norm: 3.1147 loss: 2.6357 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6357 2023/06/05 03:19:13 - mmengine - INFO - Epoch(train) [58][ 760/2569] lr: 4.0000e-02 eta: 17:36:05 time: 0.2581 data_time: 0.0073 memory: 5828 grad_norm: 3.0604 loss: 2.6005 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6005 2023/06/05 03:19:18 - mmengine - INFO - Epoch(train) [58][ 780/2569] lr: 4.0000e-02 eta: 17:35:59 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 3.1709 loss: 3.0721 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0721 2023/06/05 03:19:23 - mmengine - INFO - Epoch(train) [58][ 800/2569] lr: 4.0000e-02 eta: 17:35:54 time: 0.2593 data_time: 0.0075 memory: 5828 grad_norm: 3.1076 loss: 2.4325 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4325 2023/06/05 03:19:29 - mmengine - INFO - Epoch(train) [58][ 820/2569] lr: 4.0000e-02 eta: 17:35:49 time: 0.2663 data_time: 0.0071 memory: 5828 grad_norm: 3.0675 loss: 2.4477 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4477 2023/06/05 03:19:34 - mmengine - INFO - Epoch(train) [58][ 840/2569] lr: 4.0000e-02 eta: 17:35:43 time: 0.2608 data_time: 0.0076 memory: 5828 grad_norm: 3.1042 loss: 2.2933 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2933 2023/06/05 03:19:39 - mmengine - INFO - Epoch(train) [58][ 860/2569] lr: 4.0000e-02 eta: 17:35:38 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.1220 loss: 2.7593 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7593 2023/06/05 03:19:44 - mmengine - INFO - Epoch(train) [58][ 880/2569] lr: 4.0000e-02 eta: 17:35:32 time: 0.2576 data_time: 0.0072 memory: 5828 grad_norm: 3.0822 loss: 2.3575 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3575 2023/06/05 03:19:50 - mmengine - INFO - Epoch(train) [58][ 900/2569] lr: 4.0000e-02 eta: 17:35:26 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 3.1497 loss: 2.8008 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8008 2023/06/05 03:19:55 - mmengine - INFO - Epoch(train) [58][ 920/2569] lr: 4.0000e-02 eta: 17:35:21 time: 0.2641 data_time: 0.0071 memory: 5828 grad_norm: 3.0799 loss: 2.7848 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7848 2023/06/05 03:20:00 - mmengine - INFO - Epoch(train) [58][ 940/2569] lr: 4.0000e-02 eta: 17:35:15 time: 0.2574 data_time: 0.0073 memory: 5828 grad_norm: 3.1381 loss: 2.7942 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7942 2023/06/05 03:20:05 - mmengine - INFO - Epoch(train) [58][ 960/2569] lr: 4.0000e-02 eta: 17:35:10 time: 0.2582 data_time: 0.0076 memory: 5828 grad_norm: 3.1170 loss: 2.8514 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8514 2023/06/05 03:20:11 - mmengine - INFO - Epoch(train) [58][ 980/2569] lr: 4.0000e-02 eta: 17:35:05 time: 0.2697 data_time: 0.0075 memory: 5828 grad_norm: 3.1827 loss: 2.3058 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3058 2023/06/05 03:20:16 - mmengine - INFO - Epoch(train) [58][1000/2569] lr: 4.0000e-02 eta: 17:34:59 time: 0.2578 data_time: 0.0072 memory: 5828 grad_norm: 3.0376 loss: 2.5304 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5304 2023/06/05 03:20:21 - mmengine - INFO - Epoch(train) [58][1020/2569] lr: 4.0000e-02 eta: 17:34:54 time: 0.2584 data_time: 0.0074 memory: 5828 grad_norm: 3.0792 loss: 2.4907 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4907 2023/06/05 03:20:26 - mmengine - INFO - Epoch(train) [58][1040/2569] lr: 4.0000e-02 eta: 17:34:48 time: 0.2617 data_time: 0.0076 memory: 5828 grad_norm: 3.0940 loss: 2.6426 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6426 2023/06/05 03:20:32 - mmengine - INFO - Epoch(train) [58][1060/2569] lr: 4.0000e-02 eta: 17:34:43 time: 0.2695 data_time: 0.0081 memory: 5828 grad_norm: 3.1600 loss: 2.3936 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3936 2023/06/05 03:20:37 - mmengine - INFO - Epoch(train) [58][1080/2569] lr: 4.0000e-02 eta: 17:34:37 time: 0.2581 data_time: 0.0081 memory: 5828 grad_norm: 3.1415 loss: 2.7497 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7497 2023/06/05 03:20:42 - mmengine - INFO - Epoch(train) [58][1100/2569] lr: 4.0000e-02 eta: 17:34:32 time: 0.2635 data_time: 0.0074 memory: 5828 grad_norm: 3.0937 loss: 2.4988 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4988 2023/06/05 03:20:47 - mmengine - INFO - Epoch(train) [58][1120/2569] lr: 4.0000e-02 eta: 17:34:26 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 3.1534 loss: 2.4665 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4665 2023/06/05 03:20:52 - mmengine - INFO - Epoch(train) [58][1140/2569] lr: 4.0000e-02 eta: 17:34:21 time: 0.2631 data_time: 0.0092 memory: 5828 grad_norm: 3.0981 loss: 2.6823 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6823 2023/06/05 03:20:58 - mmengine - INFO - Epoch(train) [58][1160/2569] lr: 4.0000e-02 eta: 17:34:16 time: 0.2715 data_time: 0.0077 memory: 5828 grad_norm: 3.0937 loss: 2.0973 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0973 2023/06/05 03:21:03 - mmengine - INFO - Epoch(train) [58][1180/2569] lr: 4.0000e-02 eta: 17:34:11 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 3.1328 loss: 2.4539 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4539 2023/06/05 03:21:09 - mmengine - INFO - Epoch(train) [58][1200/2569] lr: 4.0000e-02 eta: 17:34:05 time: 0.2696 data_time: 0.0074 memory: 5828 grad_norm: 3.1027 loss: 2.6042 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6042 2023/06/05 03:21:14 - mmengine - INFO - Epoch(train) [58][1220/2569] lr: 4.0000e-02 eta: 17:34:00 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 3.1259 loss: 2.7078 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7078 2023/06/05 03:21:19 - mmengine - INFO - Epoch(train) [58][1240/2569] lr: 4.0000e-02 eta: 17:33:55 time: 0.2690 data_time: 0.0069 memory: 5828 grad_norm: 3.1705 loss: 2.2575 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2575 2023/06/05 03:21:25 - mmengine - INFO - Epoch(train) [58][1260/2569] lr: 4.0000e-02 eta: 17:33:49 time: 0.2660 data_time: 0.0072 memory: 5828 grad_norm: 3.1658 loss: 2.5989 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5989 2023/06/05 03:21:30 - mmengine - INFO - Epoch(train) [58][1280/2569] lr: 4.0000e-02 eta: 17:33:44 time: 0.2741 data_time: 0.0073 memory: 5828 grad_norm: 3.1459 loss: 2.3538 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3538 2023/06/05 03:21:35 - mmengine - INFO - Epoch(train) [58][1300/2569] lr: 4.0000e-02 eta: 17:33:39 time: 0.2607 data_time: 0.0073 memory: 5828 grad_norm: 3.1494 loss: 2.4773 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4773 2023/06/05 03:21:41 - mmengine - INFO - Epoch(train) [58][1320/2569] lr: 4.0000e-02 eta: 17:33:33 time: 0.2626 data_time: 0.0072 memory: 5828 grad_norm: 3.1688 loss: 2.5514 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5514 2023/06/05 03:21:46 - mmengine - INFO - Epoch(train) [58][1340/2569] lr: 4.0000e-02 eta: 17:33:28 time: 0.2577 data_time: 0.0072 memory: 5828 grad_norm: 3.1130 loss: 2.7725 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7725 2023/06/05 03:21:51 - mmengine - INFO - Epoch(train) [58][1360/2569] lr: 4.0000e-02 eta: 17:33:22 time: 0.2652 data_time: 0.0073 memory: 5828 grad_norm: 3.0906 loss: 2.4430 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4430 2023/06/05 03:21:56 - mmengine - INFO - Epoch(train) [58][1380/2569] lr: 4.0000e-02 eta: 17:33:17 time: 0.2713 data_time: 0.0072 memory: 5828 grad_norm: 3.0684 loss: 2.6345 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6345 2023/06/05 03:22:02 - mmengine - INFO - Epoch(train) [58][1400/2569] lr: 4.0000e-02 eta: 17:33:12 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 3.0717 loss: 2.6495 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6495 2023/06/05 03:22:07 - mmengine - INFO - Epoch(train) [58][1420/2569] lr: 4.0000e-02 eta: 17:33:07 time: 0.2695 data_time: 0.0074 memory: 5828 grad_norm: 3.2034 loss: 2.4806 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4806 2023/06/05 03:22:12 - mmengine - INFO - Epoch(train) [58][1440/2569] lr: 4.0000e-02 eta: 17:33:01 time: 0.2590 data_time: 0.0073 memory: 5828 grad_norm: 3.1556 loss: 2.6798 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6798 2023/06/05 03:22:18 - mmengine - INFO - Epoch(train) [58][1460/2569] lr: 4.0000e-02 eta: 17:32:56 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 3.0488 loss: 2.2046 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2046 2023/06/05 03:22:23 - mmengine - INFO - Epoch(train) [58][1480/2569] lr: 4.0000e-02 eta: 17:32:51 time: 0.2764 data_time: 0.0074 memory: 5828 grad_norm: 3.0960 loss: 2.5294 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5294 2023/06/05 03:22:28 - mmengine - INFO - Epoch(train) [58][1500/2569] lr: 4.0000e-02 eta: 17:32:45 time: 0.2587 data_time: 0.0069 memory: 5828 grad_norm: 3.1357 loss: 2.2432 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2432 2023/06/05 03:22:34 - mmengine - INFO - Epoch(train) [58][1520/2569] lr: 4.0000e-02 eta: 17:32:40 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 3.1331 loss: 2.3517 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3517 2023/06/05 03:22:39 - mmengine - INFO - Epoch(train) [58][1540/2569] lr: 4.0000e-02 eta: 17:32:34 time: 0.2584 data_time: 0.0075 memory: 5828 grad_norm: 3.1547 loss: 2.2573 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2573 2023/06/05 03:22:44 - mmengine - INFO - Epoch(train) [58][1560/2569] lr: 4.0000e-02 eta: 17:32:29 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 3.0780 loss: 2.4172 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4172 2023/06/05 03:22:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:22:49 - mmengine - INFO - Epoch(train) [58][1580/2569] lr: 4.0000e-02 eta: 17:32:24 time: 0.2579 data_time: 0.0073 memory: 5828 grad_norm: 3.0560 loss: 2.5681 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5681 2023/06/05 03:22:55 - mmengine - INFO - Epoch(train) [58][1600/2569] lr: 4.0000e-02 eta: 17:32:18 time: 0.2663 data_time: 0.0073 memory: 5828 grad_norm: 3.1166 loss: 2.4106 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4106 2023/06/05 03:23:00 - mmengine - INFO - Epoch(train) [58][1620/2569] lr: 4.0000e-02 eta: 17:32:13 time: 0.2587 data_time: 0.0078 memory: 5828 grad_norm: 3.2319 loss: 2.5379 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5379 2023/06/05 03:23:05 - mmengine - INFO - Epoch(train) [58][1640/2569] lr: 4.0000e-02 eta: 17:32:07 time: 0.2607 data_time: 0.0072 memory: 5828 grad_norm: 3.1162 loss: 2.4561 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4561 2023/06/05 03:23:10 - mmengine - INFO - Epoch(train) [58][1660/2569] lr: 4.0000e-02 eta: 17:32:02 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 3.1463 loss: 2.3359 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.3359 2023/06/05 03:23:16 - mmengine - INFO - Epoch(train) [58][1680/2569] lr: 4.0000e-02 eta: 17:31:56 time: 0.2606 data_time: 0.0076 memory: 5828 grad_norm: 3.1320 loss: 2.4621 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4621 2023/06/05 03:23:21 - mmengine - INFO - Epoch(train) [58][1700/2569] lr: 4.0000e-02 eta: 17:31:51 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 3.1818 loss: 2.7766 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7766 2023/06/05 03:23:26 - mmengine - INFO - Epoch(train) [58][1720/2569] lr: 4.0000e-02 eta: 17:31:45 time: 0.2578 data_time: 0.0073 memory: 5828 grad_norm: 3.1336 loss: 2.6132 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6132 2023/06/05 03:23:31 - mmengine - INFO - Epoch(train) [58][1740/2569] lr: 4.0000e-02 eta: 17:31:40 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.0722 loss: 2.5138 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5138 2023/06/05 03:23:37 - mmengine - INFO - Epoch(train) [58][1760/2569] lr: 4.0000e-02 eta: 17:31:34 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 3.1165 loss: 2.5524 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.5524 2023/06/05 03:23:42 - mmengine - INFO - Epoch(train) [58][1780/2569] lr: 4.0000e-02 eta: 17:31:29 time: 0.2655 data_time: 0.0072 memory: 5828 grad_norm: 3.1239 loss: 2.7587 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7587 2023/06/05 03:23:47 - mmengine - INFO - Epoch(train) [58][1800/2569] lr: 4.0000e-02 eta: 17:31:24 time: 0.2650 data_time: 0.0078 memory: 5828 grad_norm: 3.0606 loss: 2.4544 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4544 2023/06/05 03:23:52 - mmengine - INFO - Epoch(train) [58][1820/2569] lr: 4.0000e-02 eta: 17:31:18 time: 0.2604 data_time: 0.0073 memory: 5828 grad_norm: 3.0835 loss: 2.3816 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3816 2023/06/05 03:23:58 - mmengine - INFO - Epoch(train) [58][1840/2569] lr: 4.0000e-02 eta: 17:31:13 time: 0.2695 data_time: 0.0076 memory: 5828 grad_norm: 3.1445 loss: 2.2055 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2055 2023/06/05 03:24:03 - mmengine - INFO - Epoch(train) [58][1860/2569] lr: 4.0000e-02 eta: 17:31:07 time: 0.2581 data_time: 0.0074 memory: 5828 grad_norm: 3.0848 loss: 2.7080 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7080 2023/06/05 03:24:08 - mmengine - INFO - Epoch(train) [58][1880/2569] lr: 4.0000e-02 eta: 17:31:02 time: 0.2676 data_time: 0.0073 memory: 5828 grad_norm: 3.0863 loss: 2.8156 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8156 2023/06/05 03:24:14 - mmengine - INFO - Epoch(train) [58][1900/2569] lr: 4.0000e-02 eta: 17:30:57 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.1024 loss: 2.2765 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.2765 2023/06/05 03:24:19 - mmengine - INFO - Epoch(train) [58][1920/2569] lr: 4.0000e-02 eta: 17:30:51 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.0902 loss: 2.4615 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4615 2023/06/05 03:24:24 - mmengine - INFO - Epoch(train) [58][1940/2569] lr: 4.0000e-02 eta: 17:30:46 time: 0.2601 data_time: 0.0073 memory: 5828 grad_norm: 3.0906 loss: 2.7988 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7988 2023/06/05 03:24:29 - mmengine - INFO - Epoch(train) [58][1960/2569] lr: 4.0000e-02 eta: 17:30:40 time: 0.2606 data_time: 0.0075 memory: 5828 grad_norm: 3.1564 loss: 2.5389 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5389 2023/06/05 03:24:34 - mmengine - INFO - Epoch(train) [58][1980/2569] lr: 4.0000e-02 eta: 17:30:35 time: 0.2592 data_time: 0.0077 memory: 5828 grad_norm: 3.1705 loss: 2.5756 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5756 2023/06/05 03:24:40 - mmengine - INFO - Epoch(train) [58][2000/2569] lr: 4.0000e-02 eta: 17:30:29 time: 0.2575 data_time: 0.0077 memory: 5828 grad_norm: 3.1080 loss: 2.8932 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8932 2023/06/05 03:24:45 - mmengine - INFO - Epoch(train) [58][2020/2569] lr: 4.0000e-02 eta: 17:30:24 time: 0.2574 data_time: 0.0076 memory: 5828 grad_norm: 3.1639 loss: 2.7098 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7098 2023/06/05 03:24:50 - mmengine - INFO - Epoch(train) [58][2040/2569] lr: 4.0000e-02 eta: 17:30:18 time: 0.2598 data_time: 0.0075 memory: 5828 grad_norm: 3.1291 loss: 2.7522 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7522 2023/06/05 03:24:55 - mmengine - INFO - Epoch(train) [58][2060/2569] lr: 4.0000e-02 eta: 17:30:13 time: 0.2661 data_time: 0.0074 memory: 5828 grad_norm: 3.1478 loss: 2.5187 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5187 2023/06/05 03:25:01 - mmengine - INFO - Epoch(train) [58][2080/2569] lr: 4.0000e-02 eta: 17:30:07 time: 0.2627 data_time: 0.0080 memory: 5828 grad_norm: 3.0857 loss: 2.5966 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5966 2023/06/05 03:25:06 - mmengine - INFO - Epoch(train) [58][2100/2569] lr: 4.0000e-02 eta: 17:30:02 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 3.0918 loss: 2.9117 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.9117 2023/06/05 03:25:11 - mmengine - INFO - Epoch(train) [58][2120/2569] lr: 4.0000e-02 eta: 17:29:57 time: 0.2612 data_time: 0.0074 memory: 5828 grad_norm: 3.1425 loss: 2.5373 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5373 2023/06/05 03:25:16 - mmengine - INFO - Epoch(train) [58][2140/2569] lr: 4.0000e-02 eta: 17:29:51 time: 0.2598 data_time: 0.0078 memory: 5828 grad_norm: 3.1998 loss: 2.4267 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4267 2023/06/05 03:25:22 - mmengine - INFO - Epoch(train) [58][2160/2569] lr: 4.0000e-02 eta: 17:29:46 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.1719 loss: 2.5917 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5917 2023/06/05 03:25:27 - mmengine - INFO - Epoch(train) [58][2180/2569] lr: 4.0000e-02 eta: 17:29:40 time: 0.2621 data_time: 0.0087 memory: 5828 grad_norm: 3.0936 loss: 2.2494 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2494 2023/06/05 03:25:32 - mmengine - INFO - Epoch(train) [58][2200/2569] lr: 4.0000e-02 eta: 17:29:35 time: 0.2724 data_time: 0.0074 memory: 5828 grad_norm: 3.1289 loss: 2.2334 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2334 2023/06/05 03:25:38 - mmengine - INFO - Epoch(train) [58][2220/2569] lr: 4.0000e-02 eta: 17:29:30 time: 0.2600 data_time: 0.0071 memory: 5828 grad_norm: 3.0297 loss: 2.4574 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4574 2023/06/05 03:25:43 - mmengine - INFO - Epoch(train) [58][2240/2569] lr: 4.0000e-02 eta: 17:29:24 time: 0.2689 data_time: 0.0074 memory: 5828 grad_norm: 3.2078 loss: 2.5678 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5678 2023/06/05 03:25:48 - mmengine - INFO - Epoch(train) [58][2260/2569] lr: 4.0000e-02 eta: 17:29:19 time: 0.2587 data_time: 0.0073 memory: 5828 grad_norm: 3.0999 loss: 2.7545 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7545 2023/06/05 03:25:53 - mmengine - INFO - Epoch(train) [58][2280/2569] lr: 4.0000e-02 eta: 17:29:13 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 3.1580 loss: 2.6116 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6116 2023/06/05 03:25:59 - mmengine - INFO - Epoch(train) [58][2300/2569] lr: 4.0000e-02 eta: 17:29:08 time: 0.2597 data_time: 0.0082 memory: 5828 grad_norm: 3.1126 loss: 2.9326 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9326 2023/06/05 03:26:04 - mmengine - INFO - Epoch(train) [58][2320/2569] lr: 4.0000e-02 eta: 17:29:03 time: 0.2689 data_time: 0.0084 memory: 5828 grad_norm: 3.1098 loss: 2.6811 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6811 2023/06/05 03:26:09 - mmengine - INFO - Epoch(train) [58][2340/2569] lr: 4.0000e-02 eta: 17:28:57 time: 0.2588 data_time: 0.0078 memory: 5828 grad_norm: 3.1421 loss: 2.5361 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5361 2023/06/05 03:26:14 - mmengine - INFO - Epoch(train) [58][2360/2569] lr: 4.0000e-02 eta: 17:28:52 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 3.1255 loss: 2.8670 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8670 2023/06/05 03:26:20 - mmengine - INFO - Epoch(train) [58][2380/2569] lr: 4.0000e-02 eta: 17:28:46 time: 0.2680 data_time: 0.0078 memory: 5828 grad_norm: 3.1010 loss: 2.5137 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5137 2023/06/05 03:26:25 - mmengine - INFO - Epoch(train) [58][2400/2569] lr: 4.0000e-02 eta: 17:28:41 time: 0.2631 data_time: 0.0072 memory: 5828 grad_norm: 3.1237 loss: 2.6102 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6102 2023/06/05 03:26:30 - mmengine - INFO - Epoch(train) [58][2420/2569] lr: 4.0000e-02 eta: 17:28:36 time: 0.2675 data_time: 0.0072 memory: 5828 grad_norm: 3.0672 loss: 2.1988 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1988 2023/06/05 03:26:36 - mmengine - INFO - Epoch(train) [58][2440/2569] lr: 4.0000e-02 eta: 17:28:31 time: 0.2725 data_time: 0.0074 memory: 5828 grad_norm: 3.0831 loss: 2.6991 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6991 2023/06/05 03:26:41 - mmengine - INFO - Epoch(train) [58][2460/2569] lr: 4.0000e-02 eta: 17:28:25 time: 0.2636 data_time: 0.0072 memory: 5828 grad_norm: 3.1166 loss: 2.9189 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9189 2023/06/05 03:26:46 - mmengine - INFO - Epoch(train) [58][2480/2569] lr: 4.0000e-02 eta: 17:28:20 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 3.0747 loss: 2.2825 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2825 2023/06/05 03:26:52 - mmengine - INFO - Epoch(train) [58][2500/2569] lr: 4.0000e-02 eta: 17:28:14 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 3.0704 loss: 2.4003 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4003 2023/06/05 03:26:57 - mmengine - INFO - Epoch(train) [58][2520/2569] lr: 4.0000e-02 eta: 17:28:09 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 3.0744 loss: 2.3438 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3438 2023/06/05 03:27:02 - mmengine - INFO - Epoch(train) [58][2540/2569] lr: 4.0000e-02 eta: 17:28:03 time: 0.2577 data_time: 0.0075 memory: 5828 grad_norm: 3.0786 loss: 2.3382 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3382 2023/06/05 03:27:07 - mmengine - INFO - Epoch(train) [58][2560/2569] lr: 4.0000e-02 eta: 17:27:58 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 3.1313 loss: 2.3340 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3340 2023/06/05 03:27:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:27:10 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:27:10 - mmengine - INFO - Epoch(train) [58][2569/2569] lr: 4.0000e-02 eta: 17:27:55 time: 0.2565 data_time: 0.0071 memory: 5828 grad_norm: 3.1717 loss: 2.3112 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.3112 2023/06/05 03:27:16 - mmengine - INFO - Epoch(train) [59][ 20/2569] lr: 4.0000e-02 eta: 17:27:52 time: 0.3380 data_time: 0.0535 memory: 5828 grad_norm: 3.0754 loss: 2.3655 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3655 2023/06/05 03:27:22 - mmengine - INFO - Epoch(train) [59][ 40/2569] lr: 4.0000e-02 eta: 17:27:47 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 3.0544 loss: 3.0629 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 3.0629 2023/06/05 03:27:27 - mmengine - INFO - Epoch(train) [59][ 60/2569] lr: 4.0000e-02 eta: 17:27:42 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 3.1521 loss: 2.3379 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3379 2023/06/05 03:27:32 - mmengine - INFO - Epoch(train) [59][ 80/2569] lr: 4.0000e-02 eta: 17:27:36 time: 0.2583 data_time: 0.0073 memory: 5828 grad_norm: 3.0985 loss: 2.3093 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3093 2023/06/05 03:27:38 - mmengine - INFO - Epoch(train) [59][ 100/2569] lr: 4.0000e-02 eta: 17:27:31 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 3.1161 loss: 2.6726 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6726 2023/06/05 03:27:43 - mmengine - INFO - Epoch(train) [59][ 120/2569] lr: 4.0000e-02 eta: 17:27:26 time: 0.2707 data_time: 0.0075 memory: 5828 grad_norm: 3.1020 loss: 2.5121 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5121 2023/06/05 03:27:48 - mmengine - INFO - Epoch(train) [59][ 140/2569] lr: 4.0000e-02 eta: 17:27:20 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.0973 loss: 2.3200 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3200 2023/06/05 03:27:54 - mmengine - INFO - Epoch(train) [59][ 160/2569] lr: 4.0000e-02 eta: 17:27:15 time: 0.2744 data_time: 0.0073 memory: 5828 grad_norm: 3.0914 loss: 2.5759 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5759 2023/06/05 03:27:59 - mmengine - INFO - Epoch(train) [59][ 180/2569] lr: 4.0000e-02 eta: 17:27:10 time: 0.2672 data_time: 0.0075 memory: 5828 grad_norm: 3.1646 loss: 2.5473 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5473 2023/06/05 03:28:04 - mmengine - INFO - Epoch(train) [59][ 200/2569] lr: 4.0000e-02 eta: 17:27:04 time: 0.2579 data_time: 0.0071 memory: 5828 grad_norm: 3.1308 loss: 2.5620 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5620 2023/06/05 03:28:10 - mmengine - INFO - Epoch(train) [59][ 220/2569] lr: 4.0000e-02 eta: 17:26:59 time: 0.2655 data_time: 0.0070 memory: 5828 grad_norm: 3.1621 loss: 2.3765 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3765 2023/06/05 03:28:15 - mmengine - INFO - Epoch(train) [59][ 240/2569] lr: 4.0000e-02 eta: 17:26:54 time: 0.2598 data_time: 0.0072 memory: 5828 grad_norm: 3.1009 loss: 2.2822 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2822 2023/06/05 03:28:20 - mmengine - INFO - Epoch(train) [59][ 260/2569] lr: 4.0000e-02 eta: 17:26:48 time: 0.2648 data_time: 0.0071 memory: 5828 grad_norm: 3.1215 loss: 2.2797 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2797 2023/06/05 03:28:25 - mmengine - INFO - Epoch(train) [59][ 280/2569] lr: 4.0000e-02 eta: 17:26:43 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 3.1374 loss: 2.5165 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5165 2023/06/05 03:28:31 - mmengine - INFO - Epoch(train) [59][ 300/2569] lr: 4.0000e-02 eta: 17:26:38 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 3.0814 loss: 2.2287 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.2287 2023/06/05 03:28:36 - mmengine - INFO - Epoch(train) [59][ 320/2569] lr: 4.0000e-02 eta: 17:26:32 time: 0.2700 data_time: 0.0075 memory: 5828 grad_norm: 3.0950 loss: 2.4332 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4332 2023/06/05 03:28:41 - mmengine - INFO - Epoch(train) [59][ 340/2569] lr: 4.0000e-02 eta: 17:26:27 time: 0.2615 data_time: 0.0073 memory: 5828 grad_norm: 3.1459 loss: 2.7267 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7267 2023/06/05 03:28:47 - mmengine - INFO - Epoch(train) [59][ 360/2569] lr: 4.0000e-02 eta: 17:26:22 time: 0.2803 data_time: 0.0071 memory: 5828 grad_norm: 3.1507 loss: 2.4555 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4555 2023/06/05 03:28:52 - mmengine - INFO - Epoch(train) [59][ 380/2569] lr: 4.0000e-02 eta: 17:26:17 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 3.1019 loss: 2.9407 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9407 2023/06/05 03:28:57 - mmengine - INFO - Epoch(train) [59][ 400/2569] lr: 4.0000e-02 eta: 17:26:11 time: 0.2581 data_time: 0.0073 memory: 5828 grad_norm: 3.1254 loss: 2.6314 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6314 2023/06/05 03:29:03 - mmengine - INFO - Epoch(train) [59][ 420/2569] lr: 4.0000e-02 eta: 17:26:05 time: 0.2588 data_time: 0.0072 memory: 5828 grad_norm: 3.1028 loss: 2.6681 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6681 2023/06/05 03:29:08 - mmengine - INFO - Epoch(train) [59][ 440/2569] lr: 4.0000e-02 eta: 17:26:00 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 3.0846 loss: 2.4051 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4051 2023/06/05 03:29:13 - mmengine - INFO - Epoch(train) [59][ 460/2569] lr: 4.0000e-02 eta: 17:25:55 time: 0.2596 data_time: 0.0072 memory: 5828 grad_norm: 3.0847 loss: 2.5352 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5352 2023/06/05 03:29:18 - mmengine - INFO - Epoch(train) [59][ 480/2569] lr: 4.0000e-02 eta: 17:25:49 time: 0.2598 data_time: 0.0076 memory: 5828 grad_norm: 3.0881 loss: 2.6270 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6270 2023/06/05 03:29:24 - mmengine - INFO - Epoch(train) [59][ 500/2569] lr: 4.0000e-02 eta: 17:25:44 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 3.0853 loss: 2.4990 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4990 2023/06/05 03:29:29 - mmengine - INFO - Epoch(train) [59][ 520/2569] lr: 4.0000e-02 eta: 17:25:39 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 3.1284 loss: 2.4653 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4653 2023/06/05 03:29:34 - mmengine - INFO - Epoch(train) [59][ 540/2569] lr: 4.0000e-02 eta: 17:25:33 time: 0.2621 data_time: 0.0071 memory: 5828 grad_norm: 3.0796 loss: 2.6410 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6410 2023/06/05 03:29:40 - mmengine - INFO - Epoch(train) [59][ 560/2569] lr: 4.0000e-02 eta: 17:25:28 time: 0.2623 data_time: 0.0074 memory: 5828 grad_norm: 3.0984 loss: 2.3203 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3203 2023/06/05 03:29:45 - mmengine - INFO - Epoch(train) [59][ 580/2569] lr: 4.0000e-02 eta: 17:25:22 time: 0.2581 data_time: 0.0071 memory: 5828 grad_norm: 3.0691 loss: 2.1083 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1083 2023/06/05 03:29:50 - mmengine - INFO - Epoch(train) [59][ 600/2569] lr: 4.0000e-02 eta: 17:25:17 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 3.1662 loss: 2.5650 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5650 2023/06/05 03:29:55 - mmengine - INFO - Epoch(train) [59][ 620/2569] lr: 4.0000e-02 eta: 17:25:11 time: 0.2594 data_time: 0.0074 memory: 5828 grad_norm: 3.1047 loss: 2.7879 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7879 2023/06/05 03:30:00 - mmengine - INFO - Epoch(train) [59][ 640/2569] lr: 4.0000e-02 eta: 17:25:06 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 3.1457 loss: 2.5086 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5086 2023/06/05 03:30:06 - mmengine - INFO - Epoch(train) [59][ 660/2569] lr: 4.0000e-02 eta: 17:25:00 time: 0.2629 data_time: 0.0077 memory: 5828 grad_norm: 3.1223 loss: 2.7506 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7506 2023/06/05 03:30:11 - mmengine - INFO - Epoch(train) [59][ 680/2569] lr: 4.0000e-02 eta: 17:24:55 time: 0.2605 data_time: 0.0070 memory: 5828 grad_norm: 3.0815 loss: 2.7267 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.7267 2023/06/05 03:30:16 - mmengine - INFO - Epoch(train) [59][ 700/2569] lr: 4.0000e-02 eta: 17:24:49 time: 0.2612 data_time: 0.0072 memory: 5828 grad_norm: 3.1253 loss: 2.5240 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5240 2023/06/05 03:30:22 - mmengine - INFO - Epoch(train) [59][ 720/2569] lr: 4.0000e-02 eta: 17:24:44 time: 0.2746 data_time: 0.0074 memory: 5828 grad_norm: 3.1186 loss: 2.3385 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3385 2023/06/05 03:30:27 - mmengine - INFO - Epoch(train) [59][ 740/2569] lr: 4.0000e-02 eta: 17:24:39 time: 0.2579 data_time: 0.0072 memory: 5828 grad_norm: 3.0947 loss: 2.6402 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6402 2023/06/05 03:30:32 - mmengine - INFO - Epoch(train) [59][ 760/2569] lr: 4.0000e-02 eta: 17:24:34 time: 0.2764 data_time: 0.0072 memory: 5828 grad_norm: 3.1657 loss: 2.7281 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7281 2023/06/05 03:30:37 - mmengine - INFO - Epoch(train) [59][ 780/2569] lr: 4.0000e-02 eta: 17:24:28 time: 0.2578 data_time: 0.0078 memory: 5828 grad_norm: 3.0979 loss: 2.7139 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7139 2023/06/05 03:30:43 - mmengine - INFO - Epoch(train) [59][ 800/2569] lr: 4.0000e-02 eta: 17:24:23 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.1952 loss: 2.6819 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6819 2023/06/05 03:30:48 - mmengine - INFO - Epoch(train) [59][ 820/2569] lr: 4.0000e-02 eta: 17:24:17 time: 0.2596 data_time: 0.0075 memory: 5828 grad_norm: 3.1711 loss: 2.5225 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5225 2023/06/05 03:30:53 - mmengine - INFO - Epoch(train) [59][ 840/2569] lr: 4.0000e-02 eta: 17:24:12 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 3.0906 loss: 2.4432 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4432 2023/06/05 03:30:58 - mmengine - INFO - Epoch(train) [59][ 860/2569] lr: 4.0000e-02 eta: 17:24:06 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 3.1406 loss: 2.3481 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3481 2023/06/05 03:31:04 - mmengine - INFO - Epoch(train) [59][ 880/2569] lr: 4.0000e-02 eta: 17:24:01 time: 0.2597 data_time: 0.0071 memory: 5828 grad_norm: 3.1146 loss: 2.4875 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4875 2023/06/05 03:31:09 - mmengine - INFO - Epoch(train) [59][ 900/2569] lr: 4.0000e-02 eta: 17:23:55 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 3.1366 loss: 2.4189 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4189 2023/06/05 03:31:14 - mmengine - INFO - Epoch(train) [59][ 920/2569] lr: 4.0000e-02 eta: 17:23:50 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 3.1176 loss: 2.4535 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4535 2023/06/05 03:31:20 - mmengine - INFO - Epoch(train) [59][ 940/2569] lr: 4.0000e-02 eta: 17:23:45 time: 0.2717 data_time: 0.0071 memory: 5828 grad_norm: 3.0904 loss: 2.4162 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4162 2023/06/05 03:31:25 - mmengine - INFO - Epoch(train) [59][ 960/2569] lr: 4.0000e-02 eta: 17:23:39 time: 0.2580 data_time: 0.0080 memory: 5828 grad_norm: 3.1617 loss: 2.5553 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5553 2023/06/05 03:31:30 - mmengine - INFO - Epoch(train) [59][ 980/2569] lr: 4.0000e-02 eta: 17:23:34 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 3.1339 loss: 2.8287 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8287 2023/06/05 03:31:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:31:35 - mmengine - INFO - Epoch(train) [59][1000/2569] lr: 4.0000e-02 eta: 17:23:28 time: 0.2566 data_time: 0.0072 memory: 5828 grad_norm: 3.0957 loss: 2.6218 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6218 2023/06/05 03:31:40 - mmengine - INFO - Epoch(train) [59][1020/2569] lr: 4.0000e-02 eta: 17:23:23 time: 0.2585 data_time: 0.0071 memory: 5828 grad_norm: 3.1474 loss: 2.7937 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7937 2023/06/05 03:31:46 - mmengine - INFO - Epoch(train) [59][1040/2569] lr: 4.0000e-02 eta: 17:23:17 time: 0.2586 data_time: 0.0075 memory: 5828 grad_norm: 3.1596 loss: 2.5408 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5408 2023/06/05 03:31:51 - mmengine - INFO - Epoch(train) [59][1060/2569] lr: 4.0000e-02 eta: 17:23:12 time: 0.2629 data_time: 0.0073 memory: 5828 grad_norm: 3.0986 loss: 2.7174 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7174 2023/06/05 03:31:56 - mmengine - INFO - Epoch(train) [59][1080/2569] lr: 4.0000e-02 eta: 17:23:06 time: 0.2580 data_time: 0.0074 memory: 5828 grad_norm: 3.1449 loss: 2.2945 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2945 2023/06/05 03:32:01 - mmengine - INFO - Epoch(train) [59][1100/2569] lr: 4.0000e-02 eta: 17:23:01 time: 0.2631 data_time: 0.0081 memory: 5828 grad_norm: 3.2284 loss: 2.3842 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3842 2023/06/05 03:32:06 - mmengine - INFO - Epoch(train) [59][1120/2569] lr: 4.0000e-02 eta: 17:22:55 time: 0.2645 data_time: 0.0070 memory: 5828 grad_norm: 3.0429 loss: 2.4526 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4526 2023/06/05 03:32:12 - mmengine - INFO - Epoch(train) [59][1140/2569] lr: 4.0000e-02 eta: 17:22:50 time: 0.2651 data_time: 0.0075 memory: 5828 grad_norm: 3.1222 loss: 2.6687 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6687 2023/06/05 03:32:17 - mmengine - INFO - Epoch(train) [59][1160/2569] lr: 4.0000e-02 eta: 17:22:44 time: 0.2599 data_time: 0.0070 memory: 5828 grad_norm: 3.0991 loss: 2.7781 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7781 2023/06/05 03:32:22 - mmengine - INFO - Epoch(train) [59][1180/2569] lr: 4.0000e-02 eta: 17:22:39 time: 0.2648 data_time: 0.0066 memory: 5828 grad_norm: 3.1527 loss: 2.8439 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8439 2023/06/05 03:32:28 - mmengine - INFO - Epoch(train) [59][1200/2569] lr: 4.0000e-02 eta: 17:22:34 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 3.1125 loss: 2.8093 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8093 2023/06/05 03:32:33 - mmengine - INFO - Epoch(train) [59][1220/2569] lr: 4.0000e-02 eta: 17:22:28 time: 0.2615 data_time: 0.0070 memory: 5828 grad_norm: 3.1747 loss: 2.5285 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5285 2023/06/05 03:32:38 - mmengine - INFO - Epoch(train) [59][1240/2569] lr: 4.0000e-02 eta: 17:22:23 time: 0.2675 data_time: 0.0076 memory: 5828 grad_norm: 3.0722 loss: 2.4811 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4811 2023/06/05 03:32:43 - mmengine - INFO - Epoch(train) [59][1260/2569] lr: 4.0000e-02 eta: 17:22:18 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.1433 loss: 2.5833 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5833 2023/06/05 03:32:49 - mmengine - INFO - Epoch(train) [59][1280/2569] lr: 4.0000e-02 eta: 17:22:12 time: 0.2694 data_time: 0.0072 memory: 5828 grad_norm: 3.0743 loss: 2.7436 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7436 2023/06/05 03:32:54 - mmengine - INFO - Epoch(train) [59][1300/2569] lr: 4.0000e-02 eta: 17:22:07 time: 0.2618 data_time: 0.0080 memory: 5828 grad_norm: 3.1295 loss: 2.6192 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.6192 2023/06/05 03:32:59 - mmengine - INFO - Epoch(train) [59][1320/2569] lr: 4.0000e-02 eta: 17:22:01 time: 0.2602 data_time: 0.0071 memory: 5828 grad_norm: 3.1302 loss: 2.4403 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4403 2023/06/05 03:33:05 - mmengine - INFO - Epoch(train) [59][1340/2569] lr: 4.0000e-02 eta: 17:21:56 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 3.0240 loss: 2.5972 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5972 2023/06/05 03:33:10 - mmengine - INFO - Epoch(train) [59][1360/2569] lr: 4.0000e-02 eta: 17:21:50 time: 0.2583 data_time: 0.0078 memory: 5828 grad_norm: 3.1101 loss: 2.3751 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3751 2023/06/05 03:33:15 - mmengine - INFO - Epoch(train) [59][1380/2569] lr: 4.0000e-02 eta: 17:21:45 time: 0.2620 data_time: 0.0070 memory: 5828 grad_norm: 3.1567 loss: 2.4758 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4758 2023/06/05 03:33:20 - mmengine - INFO - Epoch(train) [59][1400/2569] lr: 4.0000e-02 eta: 17:21:39 time: 0.2567 data_time: 0.0075 memory: 5828 grad_norm: 3.1062 loss: 2.8142 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8142 2023/06/05 03:33:26 - mmengine - INFO - Epoch(train) [59][1420/2569] lr: 4.0000e-02 eta: 17:21:34 time: 0.2736 data_time: 0.0075 memory: 5828 grad_norm: 3.1683 loss: 2.3789 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3789 2023/06/05 03:33:31 - mmengine - INFO - Epoch(train) [59][1440/2569] lr: 4.0000e-02 eta: 17:21:29 time: 0.2577 data_time: 0.0076 memory: 5828 grad_norm: 3.1264 loss: 3.1226 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.1226 2023/06/05 03:33:36 - mmengine - INFO - Epoch(train) [59][1460/2569] lr: 4.0000e-02 eta: 17:21:23 time: 0.2681 data_time: 0.0073 memory: 5828 grad_norm: 3.1355 loss: 2.7257 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7257 2023/06/05 03:33:41 - mmengine - INFO - Epoch(train) [59][1480/2569] lr: 4.0000e-02 eta: 17:21:18 time: 0.2653 data_time: 0.0070 memory: 5828 grad_norm: 3.1122 loss: 2.5464 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5464 2023/06/05 03:33:47 - mmengine - INFO - Epoch(train) [59][1500/2569] lr: 4.0000e-02 eta: 17:21:13 time: 0.2763 data_time: 0.0070 memory: 5828 grad_norm: 3.1641 loss: 2.4831 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4831 2023/06/05 03:33:52 - mmengine - INFO - Epoch(train) [59][1520/2569] lr: 4.0000e-02 eta: 17:21:07 time: 0.2581 data_time: 0.0074 memory: 5828 grad_norm: 3.1687 loss: 2.5869 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5869 2023/06/05 03:33:58 - mmengine - INFO - Epoch(train) [59][1540/2569] lr: 4.0000e-02 eta: 17:21:02 time: 0.2752 data_time: 0.0074 memory: 5828 grad_norm: 3.0340 loss: 2.4999 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4999 2023/06/05 03:34:03 - mmengine - INFO - Epoch(train) [59][1560/2569] lr: 4.0000e-02 eta: 17:20:57 time: 0.2690 data_time: 0.0077 memory: 5828 grad_norm: 3.0747 loss: 2.5248 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5248 2023/06/05 03:34:08 - mmengine - INFO - Epoch(train) [59][1580/2569] lr: 4.0000e-02 eta: 17:20:52 time: 0.2623 data_time: 0.0071 memory: 5828 grad_norm: 3.1023 loss: 2.7567 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7567 2023/06/05 03:34:14 - mmengine - INFO - Epoch(train) [59][1600/2569] lr: 4.0000e-02 eta: 17:20:46 time: 0.2630 data_time: 0.0071 memory: 5828 grad_norm: 3.1766 loss: 2.5554 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5554 2023/06/05 03:34:19 - mmengine - INFO - Epoch(train) [59][1620/2569] lr: 4.0000e-02 eta: 17:20:41 time: 0.2579 data_time: 0.0073 memory: 5828 grad_norm: 3.1795 loss: 2.4610 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4610 2023/06/05 03:34:24 - mmengine - INFO - Epoch(train) [59][1640/2569] lr: 4.0000e-02 eta: 17:20:35 time: 0.2579 data_time: 0.0076 memory: 5828 grad_norm: 3.1254 loss: 2.4087 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4087 2023/06/05 03:34:29 - mmengine - INFO - Epoch(train) [59][1660/2569] lr: 4.0000e-02 eta: 17:20:30 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 3.0576 loss: 2.4610 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4610 2023/06/05 03:34:35 - mmengine - INFO - Epoch(train) [59][1680/2569] lr: 4.0000e-02 eta: 17:20:25 time: 0.2693 data_time: 0.0075 memory: 5828 grad_norm: 3.1748 loss: 2.3513 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3513 2023/06/05 03:34:40 - mmengine - INFO - Epoch(train) [59][1700/2569] lr: 4.0000e-02 eta: 17:20:19 time: 0.2696 data_time: 0.0074 memory: 5828 grad_norm: 3.1049 loss: 2.6774 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6774 2023/06/05 03:34:45 - mmengine - INFO - Epoch(train) [59][1720/2569] lr: 4.0000e-02 eta: 17:20:14 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 3.0760 loss: 2.7276 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7276 2023/06/05 03:34:51 - mmengine - INFO - Epoch(train) [59][1740/2569] lr: 4.0000e-02 eta: 17:20:09 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 3.1137 loss: 3.1473 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 3.1473 2023/06/05 03:34:56 - mmengine - INFO - Epoch(train) [59][1760/2569] lr: 4.0000e-02 eta: 17:20:03 time: 0.2657 data_time: 0.0073 memory: 5828 grad_norm: 3.0969 loss: 2.7024 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7024 2023/06/05 03:35:01 - mmengine - INFO - Epoch(train) [59][1780/2569] lr: 4.0000e-02 eta: 17:19:58 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 3.1087 loss: 2.4900 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4900 2023/06/05 03:35:07 - mmengine - INFO - Epoch(train) [59][1800/2569] lr: 4.0000e-02 eta: 17:19:53 time: 0.2709 data_time: 0.0073 memory: 5828 grad_norm: 3.1535 loss: 2.5348 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5348 2023/06/05 03:35:12 - mmengine - INFO - Epoch(train) [59][1820/2569] lr: 4.0000e-02 eta: 17:19:48 time: 0.2740 data_time: 0.0071 memory: 5828 grad_norm: 3.1168 loss: 2.4956 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4956 2023/06/05 03:35:17 - mmengine - INFO - Epoch(train) [59][1840/2569] lr: 4.0000e-02 eta: 17:19:42 time: 0.2638 data_time: 0.0076 memory: 5828 grad_norm: 3.1248 loss: 2.5255 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5255 2023/06/05 03:35:23 - mmengine - INFO - Epoch(train) [59][1860/2569] lr: 4.0000e-02 eta: 17:19:37 time: 0.2599 data_time: 0.0071 memory: 5828 grad_norm: 3.1681 loss: 2.5180 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5180 2023/06/05 03:35:28 - mmengine - INFO - Epoch(train) [59][1880/2569] lr: 4.0000e-02 eta: 17:19:31 time: 0.2584 data_time: 0.0079 memory: 5828 grad_norm: 3.1403 loss: 2.3751 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3751 2023/06/05 03:35:33 - mmengine - INFO - Epoch(train) [59][1900/2569] lr: 4.0000e-02 eta: 17:19:26 time: 0.2701 data_time: 0.0070 memory: 5828 grad_norm: 3.1360 loss: 2.7845 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7845 2023/06/05 03:35:38 - mmengine - INFO - Epoch(train) [59][1920/2569] lr: 4.0000e-02 eta: 17:19:21 time: 0.2666 data_time: 0.0074 memory: 5828 grad_norm: 3.1210 loss: 2.5004 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5004 2023/06/05 03:35:44 - mmengine - INFO - Epoch(train) [59][1940/2569] lr: 4.0000e-02 eta: 17:19:15 time: 0.2652 data_time: 0.0074 memory: 5828 grad_norm: 3.1792 loss: 2.4562 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4562 2023/06/05 03:35:49 - mmengine - INFO - Epoch(train) [59][1960/2569] lr: 4.0000e-02 eta: 17:19:10 time: 0.2733 data_time: 0.0079 memory: 5828 grad_norm: 3.0677 loss: 2.5282 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5282 2023/06/05 03:35:55 - mmengine - INFO - Epoch(train) [59][1980/2569] lr: 4.0000e-02 eta: 17:19:05 time: 0.2655 data_time: 0.0072 memory: 5828 grad_norm: 3.1318 loss: 2.6749 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6749 2023/06/05 03:35:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:36:00 - mmengine - INFO - Epoch(train) [59][2000/2569] lr: 4.0000e-02 eta: 17:19:00 time: 0.2637 data_time: 0.0072 memory: 5828 grad_norm: 3.1685 loss: 2.3040 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3040 2023/06/05 03:36:05 - mmengine - INFO - Epoch(train) [59][2020/2569] lr: 4.0000e-02 eta: 17:18:54 time: 0.2682 data_time: 0.0072 memory: 5828 grad_norm: 3.0775 loss: 2.3662 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3662 2023/06/05 03:36:10 - mmengine - INFO - Epoch(train) [59][2040/2569] lr: 4.0000e-02 eta: 17:18:49 time: 0.2636 data_time: 0.0078 memory: 5828 grad_norm: 3.0642 loss: 2.4290 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4290 2023/06/05 03:36:16 - mmengine - INFO - Epoch(train) [59][2060/2569] lr: 4.0000e-02 eta: 17:18:44 time: 0.2631 data_time: 0.0076 memory: 5828 grad_norm: 3.1237 loss: 2.4099 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4099 2023/06/05 03:36:21 - mmengine - INFO - Epoch(train) [59][2080/2569] lr: 4.0000e-02 eta: 17:18:38 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 3.1016 loss: 2.3001 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3001 2023/06/05 03:36:26 - mmengine - INFO - Epoch(train) [59][2100/2569] lr: 4.0000e-02 eta: 17:18:33 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 3.1088 loss: 2.3578 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3578 2023/06/05 03:36:32 - mmengine - INFO - Epoch(train) [59][2120/2569] lr: 4.0000e-02 eta: 17:18:28 time: 0.2618 data_time: 0.0068 memory: 5828 grad_norm: 3.1092 loss: 2.4398 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4398 2023/06/05 03:36:37 - mmengine - INFO - Epoch(train) [59][2140/2569] lr: 4.0000e-02 eta: 17:18:22 time: 0.2744 data_time: 0.0073 memory: 5828 grad_norm: 3.1066 loss: 2.7276 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7276 2023/06/05 03:36:42 - mmengine - INFO - Epoch(train) [59][2160/2569] lr: 4.0000e-02 eta: 17:18:17 time: 0.2597 data_time: 0.0073 memory: 5828 grad_norm: 3.1471 loss: 2.5668 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5668 2023/06/05 03:36:48 - mmengine - INFO - Epoch(train) [59][2180/2569] lr: 4.0000e-02 eta: 17:18:12 time: 0.2729 data_time: 0.0075 memory: 5828 grad_norm: 3.1052 loss: 2.2803 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2803 2023/06/05 03:36:53 - mmengine - INFO - Epoch(train) [59][2200/2569] lr: 4.0000e-02 eta: 17:18:06 time: 0.2592 data_time: 0.0073 memory: 5828 grad_norm: 3.1367 loss: 2.4716 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4716 2023/06/05 03:36:58 - mmengine - INFO - Epoch(train) [59][2220/2569] lr: 4.0000e-02 eta: 17:18:01 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 3.1492 loss: 2.4124 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4124 2023/06/05 03:37:04 - mmengine - INFO - Epoch(train) [59][2240/2569] lr: 4.0000e-02 eta: 17:17:55 time: 0.2627 data_time: 0.0075 memory: 5828 grad_norm: 3.1471 loss: 2.4299 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4299 2023/06/05 03:37:09 - mmengine - INFO - Epoch(train) [59][2260/2569] lr: 4.0000e-02 eta: 17:17:50 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 3.1555 loss: 2.3900 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3900 2023/06/05 03:37:14 - mmengine - INFO - Epoch(train) [59][2280/2569] lr: 4.0000e-02 eta: 17:17:45 time: 0.2646 data_time: 0.0072 memory: 5828 grad_norm: 3.1447 loss: 2.5451 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5451 2023/06/05 03:37:20 - mmengine - INFO - Epoch(train) [59][2300/2569] lr: 4.0000e-02 eta: 17:17:40 time: 0.2681 data_time: 0.0074 memory: 5828 grad_norm: 3.1274 loss: 2.4056 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4056 2023/06/05 03:37:25 - mmengine - INFO - Epoch(train) [59][2320/2569] lr: 4.0000e-02 eta: 17:17:34 time: 0.2570 data_time: 0.0076 memory: 5828 grad_norm: 3.1432 loss: 2.5982 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5982 2023/06/05 03:37:30 - mmengine - INFO - Epoch(train) [59][2340/2569] lr: 4.0000e-02 eta: 17:17:29 time: 0.2792 data_time: 0.0075 memory: 5828 grad_norm: 3.0877 loss: 2.8109 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8109 2023/06/05 03:37:36 - mmengine - INFO - Epoch(train) [59][2360/2569] lr: 4.0000e-02 eta: 17:17:24 time: 0.2613 data_time: 0.0070 memory: 5828 grad_norm: 3.1772 loss: 2.3155 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3155 2023/06/05 03:37:41 - mmengine - INFO - Epoch(train) [59][2380/2569] lr: 4.0000e-02 eta: 17:17:18 time: 0.2700 data_time: 0.0073 memory: 5828 grad_norm: 3.1125 loss: 2.5032 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5032 2023/06/05 03:37:46 - mmengine - INFO - Epoch(train) [59][2400/2569] lr: 4.0000e-02 eta: 17:17:13 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.0778 loss: 2.6035 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6035 2023/06/05 03:37:52 - mmengine - INFO - Epoch(train) [59][2420/2569] lr: 4.0000e-02 eta: 17:17:08 time: 0.2683 data_time: 0.0070 memory: 5828 grad_norm: 3.0666 loss: 2.6263 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6263 2023/06/05 03:37:57 - mmengine - INFO - Epoch(train) [59][2440/2569] lr: 4.0000e-02 eta: 17:17:02 time: 0.2638 data_time: 0.0079 memory: 5828 grad_norm: 3.1742 loss: 2.4500 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4500 2023/06/05 03:38:02 - mmengine - INFO - Epoch(train) [59][2460/2569] lr: 4.0000e-02 eta: 17:16:57 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.1636 loss: 2.1864 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1864 2023/06/05 03:38:07 - mmengine - INFO - Epoch(train) [59][2480/2569] lr: 4.0000e-02 eta: 17:16:52 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 3.1297 loss: 2.2942 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2942 2023/06/05 03:38:13 - mmengine - INFO - Epoch(train) [59][2500/2569] lr: 4.0000e-02 eta: 17:16:46 time: 0.2571 data_time: 0.0070 memory: 5828 grad_norm: 3.1126 loss: 2.7814 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 2.7814 2023/06/05 03:38:18 - mmengine - INFO - Epoch(train) [59][2520/2569] lr: 4.0000e-02 eta: 17:16:40 time: 0.2577 data_time: 0.0077 memory: 5828 grad_norm: 3.1278 loss: 2.8720 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8720 2023/06/05 03:38:23 - mmengine - INFO - Epoch(train) [59][2540/2569] lr: 4.0000e-02 eta: 17:16:35 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 3.0610 loss: 2.7427 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7427 2023/06/05 03:38:28 - mmengine - INFO - Epoch(train) [59][2560/2569] lr: 4.0000e-02 eta: 17:16:30 time: 0.2607 data_time: 0.0076 memory: 5828 grad_norm: 3.1127 loss: 2.6304 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6304 2023/06/05 03:38:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:38:30 - mmengine - INFO - Epoch(train) [59][2569/2569] lr: 4.0000e-02 eta: 17:16:27 time: 0.2547 data_time: 0.0073 memory: 5828 grad_norm: 3.1069 loss: 2.6971 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6971 2023/06/05 03:38:38 - mmengine - INFO - Epoch(train) [60][ 20/2569] lr: 4.0000e-02 eta: 17:16:24 time: 0.3519 data_time: 0.0510 memory: 5828 grad_norm: 3.1842 loss: 2.3051 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3051 2023/06/05 03:38:43 - mmengine - INFO - Epoch(train) [60][ 40/2569] lr: 4.0000e-02 eta: 17:16:19 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 3.1869 loss: 2.5881 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5881 2023/06/05 03:38:48 - mmengine - INFO - Epoch(train) [60][ 60/2569] lr: 4.0000e-02 eta: 17:16:13 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 3.1417 loss: 2.4906 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4906 2023/06/05 03:38:53 - mmengine - INFO - Epoch(train) [60][ 80/2569] lr: 4.0000e-02 eta: 17:16:08 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 3.0563 loss: 2.3622 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3622 2023/06/05 03:38:59 - mmengine - INFO - Epoch(train) [60][ 100/2569] lr: 4.0000e-02 eta: 17:16:03 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 3.0857 loss: 2.6290 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6290 2023/06/05 03:39:04 - mmengine - INFO - Epoch(train) [60][ 120/2569] lr: 4.0000e-02 eta: 17:15:57 time: 0.2753 data_time: 0.0076 memory: 5828 grad_norm: 3.0775 loss: 2.4806 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4806 2023/06/05 03:39:09 - mmengine - INFO - Epoch(train) [60][ 140/2569] lr: 4.0000e-02 eta: 17:15:52 time: 0.2570 data_time: 0.0069 memory: 5828 grad_norm: 3.0795 loss: 2.5179 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5179 2023/06/05 03:39:14 - mmengine - INFO - Epoch(train) [60][ 160/2569] lr: 4.0000e-02 eta: 17:15:46 time: 0.2576 data_time: 0.0073 memory: 5828 grad_norm: 3.0604 loss: 2.7021 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7021 2023/06/05 03:39:20 - mmengine - INFO - Epoch(train) [60][ 180/2569] lr: 4.0000e-02 eta: 17:15:41 time: 0.2729 data_time: 0.0080 memory: 5828 grad_norm: 3.1054 loss: 2.8392 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8392 2023/06/05 03:39:25 - mmengine - INFO - Epoch(train) [60][ 200/2569] lr: 4.0000e-02 eta: 17:15:36 time: 0.2626 data_time: 0.0087 memory: 5828 grad_norm: 3.1226 loss: 2.3353 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3353 2023/06/05 03:39:30 - mmengine - INFO - Epoch(train) [60][ 220/2569] lr: 4.0000e-02 eta: 17:15:30 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 3.1627 loss: 2.3538 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3538 2023/06/05 03:39:36 - mmengine - INFO - Epoch(train) [60][ 240/2569] lr: 4.0000e-02 eta: 17:15:25 time: 0.2612 data_time: 0.0076 memory: 5828 grad_norm: 3.0715 loss: 2.7271 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7271 2023/06/05 03:39:41 - mmengine - INFO - Epoch(train) [60][ 260/2569] lr: 4.0000e-02 eta: 17:15:19 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 3.1577 loss: 2.5634 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5634 2023/06/05 03:39:46 - mmengine - INFO - Epoch(train) [60][ 280/2569] lr: 4.0000e-02 eta: 17:15:14 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 3.0929 loss: 2.4613 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4613 2023/06/05 03:39:51 - mmengine - INFO - Epoch(train) [60][ 300/2569] lr: 4.0000e-02 eta: 17:15:09 time: 0.2638 data_time: 0.0071 memory: 5828 grad_norm: 3.0882 loss: 2.1922 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1922 2023/06/05 03:39:57 - mmengine - INFO - Epoch(train) [60][ 320/2569] lr: 4.0000e-02 eta: 17:15:04 time: 0.2683 data_time: 0.0079 memory: 5828 grad_norm: 3.1530 loss: 2.4090 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4090 2023/06/05 03:40:02 - mmengine - INFO - Epoch(train) [60][ 340/2569] lr: 4.0000e-02 eta: 17:14:58 time: 0.2698 data_time: 0.0072 memory: 5828 grad_norm: 3.1036 loss: 2.6126 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6126 2023/06/05 03:40:07 - mmengine - INFO - Epoch(train) [60][ 360/2569] lr: 4.0000e-02 eta: 17:14:53 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 3.1341 loss: 2.6321 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6321 2023/06/05 03:40:13 - mmengine - INFO - Epoch(train) [60][ 380/2569] lr: 4.0000e-02 eta: 17:14:47 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 3.0909 loss: 2.6563 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6563 2023/06/05 03:40:18 - mmengine - INFO - Epoch(train) [60][ 400/2569] lr: 4.0000e-02 eta: 17:14:42 time: 0.2634 data_time: 0.0073 memory: 5828 grad_norm: 3.1709 loss: 2.7986 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 2.7986 2023/06/05 03:40:23 - mmengine - INFO - Epoch(train) [60][ 420/2569] lr: 4.0000e-02 eta: 17:14:37 time: 0.2614 data_time: 0.0076 memory: 5828 grad_norm: 3.1074 loss: 2.5407 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5407 2023/06/05 03:40:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:40:29 - mmengine - INFO - Epoch(train) [60][ 440/2569] lr: 4.0000e-02 eta: 17:14:31 time: 0.2685 data_time: 0.0070 memory: 5828 grad_norm: 3.1035 loss: 2.2965 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2965 2023/06/05 03:40:34 - mmengine - INFO - Epoch(train) [60][ 460/2569] lr: 4.0000e-02 eta: 17:14:26 time: 0.2627 data_time: 0.0075 memory: 5828 grad_norm: 3.0535 loss: 3.2614 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 3.2614 2023/06/05 03:40:39 - mmengine - INFO - Epoch(train) [60][ 480/2569] lr: 4.0000e-02 eta: 17:14:21 time: 0.2689 data_time: 0.0075 memory: 5828 grad_norm: 3.0985 loss: 2.3468 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3468 2023/06/05 03:40:45 - mmengine - INFO - Epoch(train) [60][ 500/2569] lr: 4.0000e-02 eta: 17:14:15 time: 0.2644 data_time: 0.0075 memory: 5828 grad_norm: 3.0699 loss: 2.5105 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5105 2023/06/05 03:40:50 - mmengine - INFO - Epoch(train) [60][ 520/2569] lr: 4.0000e-02 eta: 17:14:10 time: 0.2655 data_time: 0.0074 memory: 5828 grad_norm: 3.0761 loss: 2.6012 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6012 2023/06/05 03:40:55 - mmengine - INFO - Epoch(train) [60][ 540/2569] lr: 4.0000e-02 eta: 17:14:04 time: 0.2584 data_time: 0.0073 memory: 5828 grad_norm: 3.1525 loss: 2.6752 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6752 2023/06/05 03:41:00 - mmengine - INFO - Epoch(train) [60][ 560/2569] lr: 4.0000e-02 eta: 17:13:59 time: 0.2619 data_time: 0.0082 memory: 5828 grad_norm: 3.1202 loss: 2.4637 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4637 2023/06/05 03:41:05 - mmengine - INFO - Epoch(train) [60][ 580/2569] lr: 4.0000e-02 eta: 17:13:53 time: 0.2571 data_time: 0.0078 memory: 5828 grad_norm: 3.1135 loss: 2.4958 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4958 2023/06/05 03:41:11 - mmengine - INFO - Epoch(train) [60][ 600/2569] lr: 4.0000e-02 eta: 17:13:48 time: 0.2670 data_time: 0.0083 memory: 5828 grad_norm: 3.1347 loss: 2.4071 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4071 2023/06/05 03:41:16 - mmengine - INFO - Epoch(train) [60][ 620/2569] lr: 4.0000e-02 eta: 17:13:43 time: 0.2724 data_time: 0.0076 memory: 5828 grad_norm: 3.1263 loss: 2.4504 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4504 2023/06/05 03:41:21 - mmengine - INFO - Epoch(train) [60][ 640/2569] lr: 4.0000e-02 eta: 17:13:37 time: 0.2580 data_time: 0.0082 memory: 5828 grad_norm: 3.1603 loss: 2.6506 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6506 2023/06/05 03:41:27 - mmengine - INFO - Epoch(train) [60][ 660/2569] lr: 4.0000e-02 eta: 17:13:32 time: 0.2657 data_time: 0.0068 memory: 5828 grad_norm: 3.0459 loss: 2.5752 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5752 2023/06/05 03:41:32 - mmengine - INFO - Epoch(train) [60][ 680/2569] lr: 4.0000e-02 eta: 17:13:27 time: 0.2630 data_time: 0.0076 memory: 5828 grad_norm: 3.1492 loss: 2.0829 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0829 2023/06/05 03:41:37 - mmengine - INFO - Epoch(train) [60][ 700/2569] lr: 4.0000e-02 eta: 17:13:22 time: 0.2702 data_time: 0.0073 memory: 5828 grad_norm: 3.1496 loss: 2.5766 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.5766 2023/06/05 03:41:43 - mmengine - INFO - Epoch(train) [60][ 720/2569] lr: 4.0000e-02 eta: 17:13:16 time: 0.2632 data_time: 0.0078 memory: 5828 grad_norm: 3.0725 loss: 2.6356 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6356 2023/06/05 03:41:48 - mmengine - INFO - Epoch(train) [60][ 740/2569] lr: 4.0000e-02 eta: 17:13:11 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 3.1155 loss: 2.4973 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4973 2023/06/05 03:41:53 - mmengine - INFO - Epoch(train) [60][ 760/2569] lr: 4.0000e-02 eta: 17:13:05 time: 0.2585 data_time: 0.0077 memory: 5828 grad_norm: 3.0974 loss: 2.6222 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6222 2023/06/05 03:41:58 - mmengine - INFO - Epoch(train) [60][ 780/2569] lr: 4.0000e-02 eta: 17:13:00 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.1186 loss: 2.5951 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5951 2023/06/05 03:42:04 - mmengine - INFO - Epoch(train) [60][ 800/2569] lr: 4.0000e-02 eta: 17:12:54 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 3.1426 loss: 2.7702 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7702 2023/06/05 03:42:09 - mmengine - INFO - Epoch(train) [60][ 820/2569] lr: 4.0000e-02 eta: 17:12:49 time: 0.2617 data_time: 0.0075 memory: 5828 grad_norm: 3.0722 loss: 2.6199 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6199 2023/06/05 03:42:14 - mmengine - INFO - Epoch(train) [60][ 840/2569] lr: 4.0000e-02 eta: 17:12:44 time: 0.2753 data_time: 0.0071 memory: 5828 grad_norm: 3.1083 loss: 2.4213 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4213 2023/06/05 03:42:20 - mmengine - INFO - Epoch(train) [60][ 860/2569] lr: 4.0000e-02 eta: 17:12:38 time: 0.2590 data_time: 0.0072 memory: 5828 grad_norm: 3.1054 loss: 2.7305 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7305 2023/06/05 03:42:25 - mmengine - INFO - Epoch(train) [60][ 880/2569] lr: 4.0000e-02 eta: 17:12:33 time: 0.2706 data_time: 0.0073 memory: 5828 grad_norm: 3.1139 loss: 2.5432 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5432 2023/06/05 03:42:30 - mmengine - INFO - Epoch(train) [60][ 900/2569] lr: 4.0000e-02 eta: 17:12:27 time: 0.2574 data_time: 0.0075 memory: 5828 grad_norm: 3.1748 loss: 2.2098 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2098 2023/06/05 03:42:35 - mmengine - INFO - Epoch(train) [60][ 920/2569] lr: 4.0000e-02 eta: 17:12:22 time: 0.2626 data_time: 0.0068 memory: 5828 grad_norm: 3.0657 loss: 2.4105 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4105 2023/06/05 03:42:41 - mmengine - INFO - Epoch(train) [60][ 940/2569] lr: 4.0000e-02 eta: 17:12:17 time: 0.2584 data_time: 0.0070 memory: 5828 grad_norm: 3.1308 loss: 2.2163 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2163 2023/06/05 03:42:46 - mmengine - INFO - Epoch(train) [60][ 960/2569] lr: 4.0000e-02 eta: 17:12:11 time: 0.2601 data_time: 0.0076 memory: 5828 grad_norm: 3.1485 loss: 2.7215 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7215 2023/06/05 03:42:51 - mmengine - INFO - Epoch(train) [60][ 980/2569] lr: 4.0000e-02 eta: 17:12:06 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 3.0964 loss: 2.2846 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2846 2023/06/05 03:42:56 - mmengine - INFO - Epoch(train) [60][1000/2569] lr: 4.0000e-02 eta: 17:12:00 time: 0.2637 data_time: 0.0071 memory: 5828 grad_norm: 3.1238 loss: 2.7226 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7226 2023/06/05 03:43:02 - mmengine - INFO - Epoch(train) [60][1020/2569] lr: 4.0000e-02 eta: 17:11:55 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 2.9936 loss: 2.4615 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4615 2023/06/05 03:43:07 - mmengine - INFO - Epoch(train) [60][1040/2569] lr: 4.0000e-02 eta: 17:11:49 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 3.1507 loss: 2.5436 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5436 2023/06/05 03:43:12 - mmengine - INFO - Epoch(train) [60][1060/2569] lr: 4.0000e-02 eta: 17:11:44 time: 0.2590 data_time: 0.0073 memory: 5828 grad_norm: 3.1840 loss: 2.5654 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5654 2023/06/05 03:43:17 - mmengine - INFO - Epoch(train) [60][1080/2569] lr: 4.0000e-02 eta: 17:11:38 time: 0.2583 data_time: 0.0077 memory: 5828 grad_norm: 3.0741 loss: 2.6687 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6687 2023/06/05 03:43:22 - mmengine - INFO - Epoch(train) [60][1100/2569] lr: 4.0000e-02 eta: 17:11:33 time: 0.2622 data_time: 0.0071 memory: 5828 grad_norm: 3.1207 loss: 2.4939 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4939 2023/06/05 03:43:28 - mmengine - INFO - Epoch(train) [60][1120/2569] lr: 4.0000e-02 eta: 17:11:27 time: 0.2625 data_time: 0.0077 memory: 5828 grad_norm: 3.1476 loss: 2.3630 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3630 2023/06/05 03:43:33 - mmengine - INFO - Epoch(train) [60][1140/2569] lr: 4.0000e-02 eta: 17:11:22 time: 0.2594 data_time: 0.0074 memory: 5828 grad_norm: 3.1360 loss: 2.4019 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4019 2023/06/05 03:43:38 - mmengine - INFO - Epoch(train) [60][1160/2569] lr: 4.0000e-02 eta: 17:11:17 time: 0.2637 data_time: 0.0075 memory: 5828 grad_norm: 3.1485 loss: 2.8521 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8521 2023/06/05 03:43:43 - mmengine - INFO - Epoch(train) [60][1180/2569] lr: 4.0000e-02 eta: 17:11:11 time: 0.2628 data_time: 0.0079 memory: 5828 grad_norm: 3.1372 loss: 2.3942 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3942 2023/06/05 03:43:49 - mmengine - INFO - Epoch(train) [60][1200/2569] lr: 4.0000e-02 eta: 17:11:06 time: 0.2689 data_time: 0.0075 memory: 5828 grad_norm: 3.0763 loss: 2.5158 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5158 2023/06/05 03:43:54 - mmengine - INFO - Epoch(train) [60][1220/2569] lr: 4.0000e-02 eta: 17:11:00 time: 0.2635 data_time: 0.0079 memory: 5828 grad_norm: 3.0884 loss: 2.3902 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3902 2023/06/05 03:44:00 - mmengine - INFO - Epoch(train) [60][1240/2569] lr: 4.0000e-02 eta: 17:10:55 time: 0.2730 data_time: 0.0076 memory: 5828 grad_norm: 3.0883 loss: 2.5832 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5832 2023/06/05 03:44:05 - mmengine - INFO - Epoch(train) [60][1260/2569] lr: 4.0000e-02 eta: 17:10:50 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 3.1367 loss: 2.4788 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4788 2023/06/05 03:44:10 - mmengine - INFO - Epoch(train) [60][1280/2569] lr: 4.0000e-02 eta: 17:10:44 time: 0.2587 data_time: 0.0075 memory: 5828 grad_norm: 3.0564 loss: 2.4962 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4962 2023/06/05 03:44:15 - mmengine - INFO - Epoch(train) [60][1300/2569] lr: 4.0000e-02 eta: 17:10:39 time: 0.2647 data_time: 0.0071 memory: 5828 grad_norm: 3.0571 loss: 2.0962 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0962 2023/06/05 03:44:21 - mmengine - INFO - Epoch(train) [60][1320/2569] lr: 4.0000e-02 eta: 17:10:34 time: 0.2595 data_time: 0.0074 memory: 5828 grad_norm: 3.1221 loss: 2.6662 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6662 2023/06/05 03:44:26 - mmengine - INFO - Epoch(train) [60][1340/2569] lr: 4.0000e-02 eta: 17:10:28 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 3.0953 loss: 2.4816 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4816 2023/06/05 03:44:31 - mmengine - INFO - Epoch(train) [60][1360/2569] lr: 4.0000e-02 eta: 17:10:22 time: 0.2589 data_time: 0.0074 memory: 5828 grad_norm: 3.1333 loss: 2.5620 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5620 2023/06/05 03:44:36 - mmengine - INFO - Epoch(train) [60][1380/2569] lr: 4.0000e-02 eta: 17:10:17 time: 0.2593 data_time: 0.0073 memory: 5828 grad_norm: 3.0959 loss: 2.2997 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2997 2023/06/05 03:44:41 - mmengine - INFO - Epoch(train) [60][1400/2569] lr: 4.0000e-02 eta: 17:10:12 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 3.1385 loss: 2.8327 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8327 2023/06/05 03:44:47 - mmengine - INFO - Epoch(train) [60][1420/2569] lr: 4.0000e-02 eta: 17:10:06 time: 0.2588 data_time: 0.0073 memory: 5828 grad_norm: 3.1433 loss: 2.3411 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3411 2023/06/05 03:44:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:44:52 - mmengine - INFO - Epoch(train) [60][1440/2569] lr: 4.0000e-02 eta: 17:10:01 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 3.1596 loss: 2.7208 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7208 2023/06/05 03:44:57 - mmengine - INFO - Epoch(train) [60][1460/2569] lr: 4.0000e-02 eta: 17:09:55 time: 0.2583 data_time: 0.0070 memory: 5828 grad_norm: 3.1505 loss: 2.6199 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6199 2023/06/05 03:45:02 - mmengine - INFO - Epoch(train) [60][1480/2569] lr: 4.0000e-02 eta: 17:09:50 time: 0.2569 data_time: 0.0073 memory: 5828 grad_norm: 3.1743 loss: 2.5031 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5031 2023/06/05 03:45:08 - mmengine - INFO - Epoch(train) [60][1500/2569] lr: 4.0000e-02 eta: 17:09:44 time: 0.2704 data_time: 0.0071 memory: 5828 grad_norm: 3.0848 loss: 2.6708 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6708 2023/06/05 03:45:13 - mmengine - INFO - Epoch(train) [60][1520/2569] lr: 4.0000e-02 eta: 17:09:39 time: 0.2573 data_time: 0.0071 memory: 5828 grad_norm: 3.1459 loss: 2.4326 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4326 2023/06/05 03:45:18 - mmengine - INFO - Epoch(train) [60][1540/2569] lr: 4.0000e-02 eta: 17:09:33 time: 0.2640 data_time: 0.0075 memory: 5828 grad_norm: 3.1473 loss: 2.8115 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8115 2023/06/05 03:45:23 - mmengine - INFO - Epoch(train) [60][1560/2569] lr: 4.0000e-02 eta: 17:09:28 time: 0.2580 data_time: 0.0076 memory: 5828 grad_norm: 3.1708 loss: 2.6420 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6420 2023/06/05 03:45:28 - mmengine - INFO - Epoch(train) [60][1580/2569] lr: 4.0000e-02 eta: 17:09:22 time: 0.2579 data_time: 0.0072 memory: 5828 grad_norm: 3.1538 loss: 2.9450 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9450 2023/06/05 03:45:34 - mmengine - INFO - Epoch(train) [60][1600/2569] lr: 4.0000e-02 eta: 17:09:17 time: 0.2615 data_time: 0.0078 memory: 5828 grad_norm: 3.0289 loss: 2.1832 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1832 2023/06/05 03:45:39 - mmengine - INFO - Epoch(train) [60][1620/2569] lr: 4.0000e-02 eta: 17:09:12 time: 0.2649 data_time: 0.0083 memory: 5828 grad_norm: 3.0376 loss: 2.1445 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1445 2023/06/05 03:45:44 - mmengine - INFO - Epoch(train) [60][1640/2569] lr: 4.0000e-02 eta: 17:09:06 time: 0.2581 data_time: 0.0076 memory: 5828 grad_norm: 3.1447 loss: 2.5871 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5871 2023/06/05 03:45:49 - mmengine - INFO - Epoch(train) [60][1660/2569] lr: 4.0000e-02 eta: 17:09:00 time: 0.2608 data_time: 0.0082 memory: 5828 grad_norm: 3.1493 loss: 2.3163 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3163 2023/06/05 03:45:55 - mmengine - INFO - Epoch(train) [60][1680/2569] lr: 4.0000e-02 eta: 17:08:55 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 3.0866 loss: 2.5296 top1_acc: 0.0000 top5_acc: 0.8750 loss_cls: 2.5296 2023/06/05 03:46:00 - mmengine - INFO - Epoch(train) [60][1700/2569] lr: 4.0000e-02 eta: 17:08:50 time: 0.2730 data_time: 0.0073 memory: 5828 grad_norm: 3.1620 loss: 2.5240 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5240 2023/06/05 03:46:06 - mmengine - INFO - Epoch(train) [60][1720/2569] lr: 4.0000e-02 eta: 17:08:45 time: 0.2747 data_time: 0.0076 memory: 5828 grad_norm: 3.1033 loss: 2.7744 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7744 2023/06/05 03:46:11 - mmengine - INFO - Epoch(train) [60][1740/2569] lr: 4.0000e-02 eta: 17:08:40 time: 0.2619 data_time: 0.0071 memory: 5828 grad_norm: 3.0961 loss: 2.5483 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5483 2023/06/05 03:46:16 - mmengine - INFO - Epoch(train) [60][1760/2569] lr: 4.0000e-02 eta: 17:08:34 time: 0.2600 data_time: 0.0073 memory: 5828 grad_norm: 3.1798 loss: 2.4406 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4406 2023/06/05 03:46:21 - mmengine - INFO - Epoch(train) [60][1780/2569] lr: 4.0000e-02 eta: 17:08:29 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 3.1479 loss: 2.4548 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4548 2023/06/05 03:46:27 - mmengine - INFO - Epoch(train) [60][1800/2569] lr: 4.0000e-02 eta: 17:08:24 time: 0.2705 data_time: 0.0069 memory: 5828 grad_norm: 3.2076 loss: 2.3617 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3617 2023/06/05 03:46:32 - mmengine - INFO - Epoch(train) [60][1820/2569] lr: 4.0000e-02 eta: 17:08:18 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 3.1494 loss: 2.6356 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6356 2023/06/05 03:46:37 - mmengine - INFO - Epoch(train) [60][1840/2569] lr: 4.0000e-02 eta: 17:08:13 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 3.1225 loss: 2.8436 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8436 2023/06/05 03:46:43 - mmengine - INFO - Epoch(train) [60][1860/2569] lr: 4.0000e-02 eta: 17:08:07 time: 0.2591 data_time: 0.0072 memory: 5828 grad_norm: 3.1179 loss: 2.8098 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8098 2023/06/05 03:46:48 - mmengine - INFO - Epoch(train) [60][1880/2569] lr: 4.0000e-02 eta: 17:08:02 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 3.1191 loss: 2.4986 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4986 2023/06/05 03:46:53 - mmengine - INFO - Epoch(train) [60][1900/2569] lr: 4.0000e-02 eta: 17:07:57 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 3.0532 loss: 2.4948 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4948 2023/06/05 03:46:59 - mmengine - INFO - Epoch(train) [60][1920/2569] lr: 4.0000e-02 eta: 17:07:51 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 3.0929 loss: 2.8368 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8368 2023/06/05 03:47:04 - mmengine - INFO - Epoch(train) [60][1940/2569] lr: 4.0000e-02 eta: 17:07:46 time: 0.2742 data_time: 0.0072 memory: 5828 grad_norm: 3.1703 loss: 2.6949 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6949 2023/06/05 03:47:09 - mmengine - INFO - Epoch(train) [60][1960/2569] lr: 4.0000e-02 eta: 17:07:41 time: 0.2633 data_time: 0.0072 memory: 5828 grad_norm: 3.1490 loss: 2.6427 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6427 2023/06/05 03:47:15 - mmengine - INFO - Epoch(train) [60][1980/2569] lr: 4.0000e-02 eta: 17:07:36 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 3.1327 loss: 2.6977 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6977 2023/06/05 03:47:20 - mmengine - INFO - Epoch(train) [60][2000/2569] lr: 4.0000e-02 eta: 17:07:30 time: 0.2677 data_time: 0.0082 memory: 5828 grad_norm: 3.1382 loss: 2.6071 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6071 2023/06/05 03:47:25 - mmengine - INFO - Epoch(train) [60][2020/2569] lr: 4.0000e-02 eta: 17:07:25 time: 0.2681 data_time: 0.0078 memory: 5828 grad_norm: 3.0813 loss: 2.4637 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4637 2023/06/05 03:47:31 - mmengine - INFO - Epoch(train) [60][2040/2569] lr: 4.0000e-02 eta: 17:07:20 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 3.1744 loss: 2.3140 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3140 2023/06/05 03:47:36 - mmengine - INFO - Epoch(train) [60][2060/2569] lr: 4.0000e-02 eta: 17:07:14 time: 0.2587 data_time: 0.0075 memory: 5828 grad_norm: 3.1449 loss: 2.6506 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6506 2023/06/05 03:47:41 - mmengine - INFO - Epoch(train) [60][2080/2569] lr: 4.0000e-02 eta: 17:07:09 time: 0.2579 data_time: 0.0077 memory: 5828 grad_norm: 3.1070 loss: 2.6993 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6993 2023/06/05 03:47:46 - mmengine - INFO - Epoch(train) [60][2100/2569] lr: 4.0000e-02 eta: 17:07:03 time: 0.2568 data_time: 0.0069 memory: 5828 grad_norm: 3.1161 loss: 3.1148 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 3.1148 2023/06/05 03:47:51 - mmengine - INFO - Epoch(train) [60][2120/2569] lr: 4.0000e-02 eta: 17:06:57 time: 0.2579 data_time: 0.0073 memory: 5828 grad_norm: 3.0902 loss: 2.4058 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4058 2023/06/05 03:47:57 - mmengine - INFO - Epoch(train) [60][2140/2569] lr: 4.0000e-02 eta: 17:06:52 time: 0.2592 data_time: 0.0077 memory: 5828 grad_norm: 3.0734 loss: 2.6632 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6632 2023/06/05 03:48:02 - mmengine - INFO - Epoch(train) [60][2160/2569] lr: 4.0000e-02 eta: 17:06:46 time: 0.2615 data_time: 0.0073 memory: 5828 grad_norm: 3.1037 loss: 2.7348 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7348 2023/06/05 03:48:07 - mmengine - INFO - Epoch(train) [60][2180/2569] lr: 4.0000e-02 eta: 17:06:41 time: 0.2694 data_time: 0.0075 memory: 5828 grad_norm: 3.0367 loss: 2.6063 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6063 2023/06/05 03:48:13 - mmengine - INFO - Epoch(train) [60][2200/2569] lr: 4.0000e-02 eta: 17:06:36 time: 0.2702 data_time: 0.0068 memory: 5828 grad_norm: 3.0614 loss: 2.2397 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2397 2023/06/05 03:48:18 - mmengine - INFO - Epoch(train) [60][2220/2569] lr: 4.0000e-02 eta: 17:06:31 time: 0.2618 data_time: 0.0079 memory: 5828 grad_norm: 3.1591 loss: 2.6358 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6358 2023/06/05 03:48:23 - mmengine - INFO - Epoch(train) [60][2240/2569] lr: 4.0000e-02 eta: 17:06:25 time: 0.2663 data_time: 0.0073 memory: 5828 grad_norm: 3.1652 loss: 2.2765 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2765 2023/06/05 03:48:28 - mmengine - INFO - Epoch(train) [60][2260/2569] lr: 4.0000e-02 eta: 17:06:20 time: 0.2643 data_time: 0.0080 memory: 5828 grad_norm: 3.0575 loss: 2.6536 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6536 2023/06/05 03:48:34 - mmengine - INFO - Epoch(train) [60][2280/2569] lr: 4.0000e-02 eta: 17:06:15 time: 0.2676 data_time: 0.0071 memory: 5828 grad_norm: 3.1287 loss: 2.3426 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3426 2023/06/05 03:48:39 - mmengine - INFO - Epoch(train) [60][2300/2569] lr: 4.0000e-02 eta: 17:06:09 time: 0.2628 data_time: 0.0073 memory: 5828 grad_norm: 3.1188 loss: 3.0207 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 3.0207 2023/06/05 03:48:44 - mmengine - INFO - Epoch(train) [60][2320/2569] lr: 4.0000e-02 eta: 17:06:04 time: 0.2587 data_time: 0.0073 memory: 5828 grad_norm: 3.0510 loss: 2.2142 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2142 2023/06/05 03:48:50 - mmengine - INFO - Epoch(train) [60][2340/2569] lr: 4.0000e-02 eta: 17:05:58 time: 0.2626 data_time: 0.0072 memory: 5828 grad_norm: 3.1367 loss: 2.5698 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5698 2023/06/05 03:48:55 - mmengine - INFO - Epoch(train) [60][2360/2569] lr: 4.0000e-02 eta: 17:05:53 time: 0.2628 data_time: 0.0069 memory: 5828 grad_norm: 3.1256 loss: 2.7700 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7700 2023/06/05 03:49:00 - mmengine - INFO - Epoch(train) [60][2380/2569] lr: 4.0000e-02 eta: 17:05:47 time: 0.2561 data_time: 0.0077 memory: 5828 grad_norm: 3.1333 loss: 2.7776 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7776 2023/06/05 03:49:05 - mmengine - INFO - Epoch(train) [60][2400/2569] lr: 4.0000e-02 eta: 17:05:42 time: 0.2685 data_time: 0.0069 memory: 5828 grad_norm: 3.1237 loss: 2.4097 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4097 2023/06/05 03:49:10 - mmengine - INFO - Epoch(train) [60][2420/2569] lr: 4.0000e-02 eta: 17:05:36 time: 0.2597 data_time: 0.0071 memory: 5828 grad_norm: 3.1302 loss: 2.5300 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5300 2023/06/05 03:49:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:49:16 - mmengine - INFO - Epoch(train) [60][2440/2569] lr: 4.0000e-02 eta: 17:05:31 time: 0.2591 data_time: 0.0072 memory: 5828 grad_norm: 3.0897 loss: 2.2680 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2680 2023/06/05 03:49:21 - mmengine - INFO - Epoch(train) [60][2460/2569] lr: 4.0000e-02 eta: 17:05:26 time: 0.2626 data_time: 0.0092 memory: 5828 grad_norm: 3.1281 loss: 2.8828 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8828 2023/06/05 03:49:26 - mmengine - INFO - Epoch(train) [60][2480/2569] lr: 4.0000e-02 eta: 17:05:20 time: 0.2604 data_time: 0.0075 memory: 5828 grad_norm: 3.1220 loss: 2.7178 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7178 2023/06/05 03:49:32 - mmengine - INFO - Epoch(train) [60][2500/2569] lr: 4.0000e-02 eta: 17:05:15 time: 0.2689 data_time: 0.0074 memory: 5828 grad_norm: 3.1411 loss: 2.8881 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8881 2023/06/05 03:49:37 - mmengine - INFO - Epoch(train) [60][2520/2569] lr: 4.0000e-02 eta: 17:05:09 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 3.1027 loss: 2.6743 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6743 2023/06/05 03:49:42 - mmengine - INFO - Epoch(train) [60][2540/2569] lr: 4.0000e-02 eta: 17:05:04 time: 0.2649 data_time: 0.0073 memory: 5828 grad_norm: 3.1186 loss: 2.7365 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7365 2023/06/05 03:49:47 - mmengine - INFO - Epoch(train) [60][2560/2569] lr: 4.0000e-02 eta: 17:04:59 time: 0.2610 data_time: 0.0078 memory: 5828 grad_norm: 3.1361 loss: 2.7675 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7675 2023/06/05 03:49:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:49:49 - mmengine - INFO - Epoch(train) [60][2569/2569] lr: 4.0000e-02 eta: 17:04:56 time: 0.2498 data_time: 0.0076 memory: 5828 grad_norm: 3.1991 loss: 2.5030 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.5030 2023/06/05 03:49:50 - mmengine - INFO - Saving checkpoint at 60 epochs 2023/06/05 03:49:56 - mmengine - INFO - Epoch(val) [60][ 20/260] eta: 0:00:43 time: 0.1800 data_time: 0.1206 memory: 1238 2023/06/05 03:49:59 - mmengine - INFO - Epoch(val) [60][ 40/260] eta: 0:00:36 time: 0.1524 data_time: 0.0937 memory: 1238 2023/06/05 03:50:02 - mmengine - INFO - Epoch(val) [60][ 60/260] eta: 0:00:32 time: 0.1529 data_time: 0.0945 memory: 1238 2023/06/05 03:50:04 - mmengine - INFO - Epoch(val) [60][ 80/260] eta: 0:00:27 time: 0.1349 data_time: 0.0760 memory: 1238 2023/06/05 03:50:07 - mmengine - INFO - Epoch(val) [60][100/260] eta: 0:00:24 time: 0.1382 data_time: 0.0794 memory: 1238 2023/06/05 03:50:10 - mmengine - INFO - Epoch(val) [60][120/260] eta: 0:00:20 time: 0.1301 data_time: 0.0717 memory: 1238 2023/06/05 03:50:13 - mmengine - INFO - Epoch(val) [60][140/260] eta: 0:00:17 time: 0.1473 data_time: 0.0887 memory: 1238 2023/06/05 03:50:15 - mmengine - INFO - Epoch(val) [60][160/260] eta: 0:00:14 time: 0.1406 data_time: 0.0820 memory: 1238 2023/06/05 03:50:19 - mmengine - INFO - Epoch(val) [60][180/260] eta: 0:00:11 time: 0.1594 data_time: 0.1011 memory: 1238 2023/06/05 03:50:21 - mmengine - INFO - Epoch(val) [60][200/260] eta: 0:00:08 time: 0.1259 data_time: 0.0672 memory: 1238 2023/06/05 03:50:24 - mmengine - INFO - Epoch(val) [60][220/260] eta: 0:00:05 time: 0.1558 data_time: 0.0977 memory: 1238 2023/06/05 03:50:27 - mmengine - INFO - Epoch(val) [60][240/260] eta: 0:00:02 time: 0.1160 data_time: 0.0589 memory: 1238 2023/06/05 03:50:29 - mmengine - INFO - Epoch(val) [60][260/260] eta: 0:00:00 time: 0.1063 data_time: 0.0508 memory: 1238 2023/06/05 03:50:35 - mmengine - INFO - Epoch(val) [60][260/260] acc/top1: 0.4992 acc/top5: 0.7431 acc/mean1: 0.4902 data_time: 0.0829 time: 0.1412 2023/06/05 03:50:42 - mmengine - INFO - Epoch(train) [61][ 20/2569] lr: 4.0000e-02 eta: 17:04:52 time: 0.3300 data_time: 0.0675 memory: 5828 grad_norm: 3.0796 loss: 2.6095 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6095 2023/06/05 03:50:47 - mmengine - INFO - Epoch(train) [61][ 40/2569] lr: 4.0000e-02 eta: 17:04:47 time: 0.2577 data_time: 0.0072 memory: 5828 grad_norm: 3.1648 loss: 2.7668 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7668 2023/06/05 03:50:53 - mmengine - INFO - Epoch(train) [61][ 60/2569] lr: 4.0000e-02 eta: 17:04:42 time: 0.2731 data_time: 0.0070 memory: 5828 grad_norm: 3.1076 loss: 2.4375 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4375 2023/06/05 03:50:58 - mmengine - INFO - Epoch(train) [61][ 80/2569] lr: 4.0000e-02 eta: 17:04:36 time: 0.2645 data_time: 0.0076 memory: 5828 grad_norm: 3.0808 loss: 2.2561 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2561 2023/06/05 03:51:03 - mmengine - INFO - Epoch(train) [61][ 100/2569] lr: 4.0000e-02 eta: 17:04:31 time: 0.2717 data_time: 0.0073 memory: 5828 grad_norm: 3.0490 loss: 2.4056 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4056 2023/06/05 03:51:09 - mmengine - INFO - Epoch(train) [61][ 120/2569] lr: 4.0000e-02 eta: 17:04:26 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 3.1170 loss: 2.5574 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5574 2023/06/05 03:51:14 - mmengine - INFO - Epoch(train) [61][ 140/2569] lr: 4.0000e-02 eta: 17:04:20 time: 0.2588 data_time: 0.0074 memory: 5828 grad_norm: 3.1669 loss: 2.3441 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3441 2023/06/05 03:51:19 - mmengine - INFO - Epoch(train) [61][ 160/2569] lr: 4.0000e-02 eta: 17:04:15 time: 0.2594 data_time: 0.0076 memory: 5828 grad_norm: 3.1152 loss: 2.5671 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.5671 2023/06/05 03:51:24 - mmengine - INFO - Epoch(train) [61][ 180/2569] lr: 4.0000e-02 eta: 17:04:09 time: 0.2600 data_time: 0.0071 memory: 5828 grad_norm: 3.0394 loss: 2.6764 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6764 2023/06/05 03:51:30 - mmengine - INFO - Epoch(train) [61][ 200/2569] lr: 4.0000e-02 eta: 17:04:04 time: 0.2641 data_time: 0.0071 memory: 5828 grad_norm: 3.1115 loss: 2.6878 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6878 2023/06/05 03:51:35 - mmengine - INFO - Epoch(train) [61][ 220/2569] lr: 4.0000e-02 eta: 17:03:58 time: 0.2594 data_time: 0.0075 memory: 5828 grad_norm: 3.1233 loss: 2.4597 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4597 2023/06/05 03:51:40 - mmengine - INFO - Epoch(train) [61][ 240/2569] lr: 4.0000e-02 eta: 17:03:53 time: 0.2588 data_time: 0.0080 memory: 5828 grad_norm: 3.0385 loss: 2.3184 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3184 2023/06/05 03:51:45 - mmengine - INFO - Epoch(train) [61][ 260/2569] lr: 4.0000e-02 eta: 17:03:47 time: 0.2603 data_time: 0.0079 memory: 5828 grad_norm: 3.0818 loss: 2.5286 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5286 2023/06/05 03:51:50 - mmengine - INFO - Epoch(train) [61][ 280/2569] lr: 4.0000e-02 eta: 17:03:42 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 3.0898 loss: 2.5478 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5478 2023/06/05 03:51:56 - mmengine - INFO - Epoch(train) [61][ 300/2569] lr: 4.0000e-02 eta: 17:03:37 time: 0.2702 data_time: 0.0070 memory: 5828 grad_norm: 3.1386 loss: 2.4306 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4306 2023/06/05 03:52:01 - mmengine - INFO - Epoch(train) [61][ 320/2569] lr: 4.0000e-02 eta: 17:03:31 time: 0.2585 data_time: 0.0077 memory: 5828 grad_norm: 3.1588 loss: 2.3819 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3819 2023/06/05 03:52:06 - mmengine - INFO - Epoch(train) [61][ 340/2569] lr: 4.0000e-02 eta: 17:03:26 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 3.0717 loss: 2.5465 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5465 2023/06/05 03:52:12 - mmengine - INFO - Epoch(train) [61][ 360/2569] lr: 4.0000e-02 eta: 17:03:21 time: 0.2733 data_time: 0.0079 memory: 5828 grad_norm: 3.1302 loss: 2.4516 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4516 2023/06/05 03:52:17 - mmengine - INFO - Epoch(train) [61][ 380/2569] lr: 4.0000e-02 eta: 17:03:15 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 3.1315 loss: 2.7483 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7483 2023/06/05 03:52:22 - mmengine - INFO - Epoch(train) [61][ 400/2569] lr: 4.0000e-02 eta: 17:03:10 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 3.0873 loss: 2.5669 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5669 2023/06/05 03:52:28 - mmengine - INFO - Epoch(train) [61][ 420/2569] lr: 4.0000e-02 eta: 17:03:05 time: 0.2666 data_time: 0.0069 memory: 5828 grad_norm: 3.1165 loss: 2.6364 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6364 2023/06/05 03:52:33 - mmengine - INFO - Epoch(train) [61][ 440/2569] lr: 4.0000e-02 eta: 17:02:59 time: 0.2690 data_time: 0.0077 memory: 5828 grad_norm: 3.0934 loss: 2.1903 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1903 2023/06/05 03:52:38 - mmengine - INFO - Epoch(train) [61][ 460/2569] lr: 4.0000e-02 eta: 17:02:54 time: 0.2560 data_time: 0.0072 memory: 5828 grad_norm: 3.1483 loss: 2.2159 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2159 2023/06/05 03:52:43 - mmengine - INFO - Epoch(train) [61][ 480/2569] lr: 4.0000e-02 eta: 17:02:48 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.1712 loss: 2.3348 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3348 2023/06/05 03:52:49 - mmengine - INFO - Epoch(train) [61][ 500/2569] lr: 4.0000e-02 eta: 17:02:43 time: 0.2743 data_time: 0.0072 memory: 5828 grad_norm: 3.1591 loss: 2.8190 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8190 2023/06/05 03:52:54 - mmengine - INFO - Epoch(train) [61][ 520/2569] lr: 4.0000e-02 eta: 17:02:38 time: 0.2723 data_time: 0.0072 memory: 5828 grad_norm: 3.1429 loss: 2.3597 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3597 2023/06/05 03:53:00 - mmengine - INFO - Epoch(train) [61][ 540/2569] lr: 4.0000e-02 eta: 17:02:33 time: 0.2628 data_time: 0.0077 memory: 5828 grad_norm: 3.1091 loss: 2.5398 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5398 2023/06/05 03:53:05 - mmengine - INFO - Epoch(train) [61][ 560/2569] lr: 4.0000e-02 eta: 17:02:28 time: 0.2792 data_time: 0.0078 memory: 5828 grad_norm: 3.1181 loss: 2.4865 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4865 2023/06/05 03:53:10 - mmengine - INFO - Epoch(train) [61][ 580/2569] lr: 4.0000e-02 eta: 17:02:23 time: 0.2629 data_time: 0.0071 memory: 5828 grad_norm: 3.1453 loss: 2.2607 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2607 2023/06/05 03:53:16 - mmengine - INFO - Epoch(train) [61][ 600/2569] lr: 4.0000e-02 eta: 17:02:17 time: 0.2631 data_time: 0.0072 memory: 5828 grad_norm: 3.1422 loss: 2.3262 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3262 2023/06/05 03:53:21 - mmengine - INFO - Epoch(train) [61][ 620/2569] lr: 4.0000e-02 eta: 17:02:12 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 3.1432 loss: 2.2408 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2408 2023/06/05 03:53:26 - mmengine - INFO - Epoch(train) [61][ 640/2569] lr: 4.0000e-02 eta: 17:02:07 time: 0.2667 data_time: 0.0075 memory: 5828 grad_norm: 3.0549 loss: 2.5418 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5418 2023/06/05 03:53:32 - mmengine - INFO - Epoch(train) [61][ 660/2569] lr: 4.0000e-02 eta: 17:02:01 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 3.1232 loss: 2.5932 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5932 2023/06/05 03:53:37 - mmengine - INFO - Epoch(train) [61][ 680/2569] lr: 4.0000e-02 eta: 17:01:56 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 3.1711 loss: 3.0211 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0211 2023/06/05 03:53:43 - mmengine - INFO - Epoch(train) [61][ 700/2569] lr: 4.0000e-02 eta: 17:01:51 time: 0.2706 data_time: 0.0074 memory: 5828 grad_norm: 3.1269 loss: 2.4732 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4732 2023/06/05 03:53:48 - mmengine - INFO - Epoch(train) [61][ 720/2569] lr: 4.0000e-02 eta: 17:01:45 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 3.0719 loss: 2.3334 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.3334 2023/06/05 03:53:53 - mmengine - INFO - Epoch(train) [61][ 740/2569] lr: 4.0000e-02 eta: 17:01:40 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 3.1773 loss: 2.2601 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2601 2023/06/05 03:53:58 - mmengine - INFO - Epoch(train) [61][ 760/2569] lr: 4.0000e-02 eta: 17:01:35 time: 0.2636 data_time: 0.0072 memory: 5828 grad_norm: 3.0527 loss: 2.4742 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4742 2023/06/05 03:54:04 - mmengine - INFO - Epoch(train) [61][ 780/2569] lr: 4.0000e-02 eta: 17:01:29 time: 0.2673 data_time: 0.0070 memory: 5828 grad_norm: 3.2061 loss: 2.6447 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6447 2023/06/05 03:54:09 - mmengine - INFO - Epoch(train) [61][ 800/2569] lr: 4.0000e-02 eta: 17:01:24 time: 0.2656 data_time: 0.0072 memory: 5828 grad_norm: 3.0988 loss: 2.7497 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7497 2023/06/05 03:54:14 - mmengine - INFO - Epoch(train) [61][ 820/2569] lr: 4.0000e-02 eta: 17:01:19 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 3.1378 loss: 2.4640 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4640 2023/06/05 03:54:20 - mmengine - INFO - Epoch(train) [61][ 840/2569] lr: 4.0000e-02 eta: 17:01:13 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.0092 loss: 2.8042 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8042 2023/06/05 03:54:25 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:54:25 - mmengine - INFO - Epoch(train) [61][ 860/2569] lr: 4.0000e-02 eta: 17:01:08 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 3.1017 loss: 2.7629 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7629 2023/06/05 03:54:30 - mmengine - INFO - Epoch(train) [61][ 880/2569] lr: 4.0000e-02 eta: 17:01:02 time: 0.2651 data_time: 0.0072 memory: 5828 grad_norm: 3.1130 loss: 2.4950 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4950 2023/06/05 03:54:35 - mmengine - INFO - Epoch(train) [61][ 900/2569] lr: 4.0000e-02 eta: 17:00:57 time: 0.2584 data_time: 0.0075 memory: 5828 grad_norm: 3.1392 loss: 2.5953 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5953 2023/06/05 03:54:41 - mmengine - INFO - Epoch(train) [61][ 920/2569] lr: 4.0000e-02 eta: 17:00:51 time: 0.2636 data_time: 0.0078 memory: 5828 grad_norm: 3.0906 loss: 2.8847 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8847 2023/06/05 03:54:46 - mmengine - INFO - Epoch(train) [61][ 940/2569] lr: 4.0000e-02 eta: 17:00:46 time: 0.2586 data_time: 0.0076 memory: 5828 grad_norm: 3.1319 loss: 2.4024 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4024 2023/06/05 03:54:51 - mmengine - INFO - Epoch(train) [61][ 960/2569] lr: 4.0000e-02 eta: 17:00:41 time: 0.2672 data_time: 0.0075 memory: 5828 grad_norm: 3.1776 loss: 2.3823 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3823 2023/06/05 03:54:56 - mmengine - INFO - Epoch(train) [61][ 980/2569] lr: 4.0000e-02 eta: 17:00:35 time: 0.2637 data_time: 0.0076 memory: 5828 grad_norm: 3.1599 loss: 2.4708 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4708 2023/06/05 03:55:02 - mmengine - INFO - Epoch(train) [61][1000/2569] lr: 4.0000e-02 eta: 17:00:30 time: 0.2654 data_time: 0.0078 memory: 5828 grad_norm: 3.1136 loss: 2.5554 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5554 2023/06/05 03:55:07 - mmengine - INFO - Epoch(train) [61][1020/2569] lr: 4.0000e-02 eta: 17:00:25 time: 0.2691 data_time: 0.0072 memory: 5828 grad_norm: 3.0938 loss: 2.3441 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3441 2023/06/05 03:55:12 - mmengine - INFO - Epoch(train) [61][1040/2569] lr: 4.0000e-02 eta: 17:00:19 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 3.1040 loss: 2.2037 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2037 2023/06/05 03:55:18 - mmengine - INFO - Epoch(train) [61][1060/2569] lr: 4.0000e-02 eta: 17:00:14 time: 0.2723 data_time: 0.0072 memory: 5828 grad_norm: 3.1214 loss: 2.7867 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7867 2023/06/05 03:55:23 - mmengine - INFO - Epoch(train) [61][1080/2569] lr: 4.0000e-02 eta: 17:00:09 time: 0.2693 data_time: 0.0074 memory: 5828 grad_norm: 3.1282 loss: 2.4171 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4171 2023/06/05 03:55:28 - mmengine - INFO - Epoch(train) [61][1100/2569] lr: 4.0000e-02 eta: 17:00:04 time: 0.2602 data_time: 0.0073 memory: 5828 grad_norm: 3.1938 loss: 2.6251 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6251 2023/06/05 03:55:34 - mmengine - INFO - Epoch(train) [61][1120/2569] lr: 4.0000e-02 eta: 16:59:58 time: 0.2621 data_time: 0.0069 memory: 5828 grad_norm: 3.1896 loss: 2.4504 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4504 2023/06/05 03:55:39 - mmengine - INFO - Epoch(train) [61][1140/2569] lr: 4.0000e-02 eta: 16:59:53 time: 0.2578 data_time: 0.0072 memory: 5828 grad_norm: 3.1462 loss: 2.5647 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5647 2023/06/05 03:55:44 - mmengine - INFO - Epoch(train) [61][1160/2569] lr: 4.0000e-02 eta: 16:59:47 time: 0.2735 data_time: 0.0074 memory: 5828 grad_norm: 3.0895 loss: 2.6237 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6237 2023/06/05 03:55:50 - mmengine - INFO - Epoch(train) [61][1180/2569] lr: 4.0000e-02 eta: 16:59:42 time: 0.2583 data_time: 0.0068 memory: 5828 grad_norm: 3.0727 loss: 2.6020 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6020 2023/06/05 03:55:55 - mmengine - INFO - Epoch(train) [61][1200/2569] lr: 4.0000e-02 eta: 16:59:36 time: 0.2616 data_time: 0.0067 memory: 5828 grad_norm: 3.1083 loss: 2.4565 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4565 2023/06/05 03:56:00 - mmengine - INFO - Epoch(train) [61][1220/2569] lr: 4.0000e-02 eta: 16:59:31 time: 0.2609 data_time: 0.0072 memory: 5828 grad_norm: 3.1110 loss: 2.4417 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4417 2023/06/05 03:56:05 - mmengine - INFO - Epoch(train) [61][1240/2569] lr: 4.0000e-02 eta: 16:59:26 time: 0.2635 data_time: 0.0071 memory: 5828 grad_norm: 3.1210 loss: 2.3942 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3942 2023/06/05 03:56:11 - mmengine - INFO - Epoch(train) [61][1260/2569] lr: 4.0000e-02 eta: 16:59:20 time: 0.2687 data_time: 0.0074 memory: 5828 grad_norm: 3.0906 loss: 2.5309 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5309 2023/06/05 03:56:16 - mmengine - INFO - Epoch(train) [61][1280/2569] lr: 4.0000e-02 eta: 16:59:15 time: 0.2603 data_time: 0.0074 memory: 5828 grad_norm: 3.1069 loss: 2.4699 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4699 2023/06/05 03:56:21 - mmengine - INFO - Epoch(train) [61][1300/2569] lr: 4.0000e-02 eta: 16:59:10 time: 0.2727 data_time: 0.0079 memory: 5828 grad_norm: 3.0902 loss: 2.2355 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2355 2023/06/05 03:56:27 - mmengine - INFO - Epoch(train) [61][1320/2569] lr: 4.0000e-02 eta: 16:59:04 time: 0.2584 data_time: 0.0073 memory: 5828 grad_norm: 3.1533 loss: 2.1812 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1812 2023/06/05 03:56:32 - mmengine - INFO - Epoch(train) [61][1340/2569] lr: 4.0000e-02 eta: 16:58:59 time: 0.2668 data_time: 0.0075 memory: 5828 grad_norm: 3.1183 loss: 2.8598 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8598 2023/06/05 03:56:37 - mmengine - INFO - Epoch(train) [61][1360/2569] lr: 4.0000e-02 eta: 16:58:54 time: 0.2638 data_time: 0.0076 memory: 5828 grad_norm: 3.0304 loss: 2.7916 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7916 2023/06/05 03:56:42 - mmengine - INFO - Epoch(train) [61][1380/2569] lr: 4.0000e-02 eta: 16:58:48 time: 0.2607 data_time: 0.0074 memory: 5828 grad_norm: 3.1700 loss: 2.5692 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5692 2023/06/05 03:56:48 - mmengine - INFO - Epoch(train) [61][1400/2569] lr: 4.0000e-02 eta: 16:58:43 time: 0.2590 data_time: 0.0078 memory: 5828 grad_norm: 3.1268 loss: 2.6213 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6213 2023/06/05 03:56:53 - mmengine - INFO - Epoch(train) [61][1420/2569] lr: 4.0000e-02 eta: 16:58:37 time: 0.2573 data_time: 0.0077 memory: 5828 grad_norm: 3.0400 loss: 2.5022 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5022 2023/06/05 03:56:58 - mmengine - INFO - Epoch(train) [61][1440/2569] lr: 4.0000e-02 eta: 16:58:32 time: 0.2624 data_time: 0.0069 memory: 5828 grad_norm: 3.1905 loss: 2.4636 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4636 2023/06/05 03:57:03 - mmengine - INFO - Epoch(train) [61][1460/2569] lr: 4.0000e-02 eta: 16:58:26 time: 0.2652 data_time: 0.0074 memory: 5828 grad_norm: 3.1305 loss: 2.4324 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4324 2023/06/05 03:57:08 - mmengine - INFO - Epoch(train) [61][1480/2569] lr: 4.0000e-02 eta: 16:58:21 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 3.1015 loss: 2.4693 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4693 2023/06/05 03:57:14 - mmengine - INFO - Epoch(train) [61][1500/2569] lr: 4.0000e-02 eta: 16:58:15 time: 0.2577 data_time: 0.0072 memory: 5828 grad_norm: 3.0720 loss: 2.7081 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7081 2023/06/05 03:57:19 - mmengine - INFO - Epoch(train) [61][1520/2569] lr: 4.0000e-02 eta: 16:58:10 time: 0.2628 data_time: 0.0070 memory: 5828 grad_norm: 3.0549 loss: 2.3234 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3234 2023/06/05 03:57:24 - mmengine - INFO - Epoch(train) [61][1540/2569] lr: 4.0000e-02 eta: 16:58:04 time: 0.2575 data_time: 0.0074 memory: 5828 grad_norm: 3.1560 loss: 2.4930 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4930 2023/06/05 03:57:29 - mmengine - INFO - Epoch(train) [61][1560/2569] lr: 4.0000e-02 eta: 16:57:59 time: 0.2626 data_time: 0.0072 memory: 5828 grad_norm: 3.0656 loss: 2.8354 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8354 2023/06/05 03:57:34 - mmengine - INFO - Epoch(train) [61][1580/2569] lr: 4.0000e-02 eta: 16:57:53 time: 0.2578 data_time: 0.0070 memory: 5828 grad_norm: 3.0592 loss: 2.3967 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3967 2023/06/05 03:57:40 - mmengine - INFO - Epoch(train) [61][1600/2569] lr: 4.0000e-02 eta: 16:57:48 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 3.1968 loss: 2.4614 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4614 2023/06/05 03:57:45 - mmengine - INFO - Epoch(train) [61][1620/2569] lr: 4.0000e-02 eta: 16:57:43 time: 0.2715 data_time: 0.0074 memory: 5828 grad_norm: 3.0984 loss: 2.6038 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6038 2023/06/05 03:57:50 - mmengine - INFO - Epoch(train) [61][1640/2569] lr: 4.0000e-02 eta: 16:57:37 time: 0.2581 data_time: 0.0073 memory: 5828 grad_norm: 3.0776 loss: 2.5968 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5968 2023/06/05 03:57:56 - mmengine - INFO - Epoch(train) [61][1660/2569] lr: 4.0000e-02 eta: 16:57:32 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 3.1299 loss: 2.3354 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3354 2023/06/05 03:58:01 - mmengine - INFO - Epoch(train) [61][1680/2569] lr: 4.0000e-02 eta: 16:57:26 time: 0.2578 data_time: 0.0084 memory: 5828 grad_norm: 3.1204 loss: 2.4025 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4025 2023/06/05 03:58:06 - mmengine - INFO - Epoch(train) [61][1700/2569] lr: 4.0000e-02 eta: 16:57:21 time: 0.2720 data_time: 0.0073 memory: 5828 grad_norm: 3.1119 loss: 2.5712 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5712 2023/06/05 03:58:12 - mmengine - INFO - Epoch(train) [61][1720/2569] lr: 4.0000e-02 eta: 16:57:16 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 3.0901 loss: 2.9576 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9576 2023/06/05 03:58:17 - mmengine - INFO - Epoch(train) [61][1740/2569] lr: 4.0000e-02 eta: 16:57:10 time: 0.2609 data_time: 0.0072 memory: 5828 grad_norm: 3.1071 loss: 2.7383 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7383 2023/06/05 03:58:22 - mmengine - INFO - Epoch(train) [61][1760/2569] lr: 4.0000e-02 eta: 16:57:05 time: 0.2684 data_time: 0.0075 memory: 5828 grad_norm: 3.0668 loss: 2.2885 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2885 2023/06/05 03:58:28 - mmengine - INFO - Epoch(train) [61][1780/2569] lr: 4.0000e-02 eta: 16:57:00 time: 0.2706 data_time: 0.0072 memory: 5828 grad_norm: 3.0952 loss: 2.3216 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3216 2023/06/05 03:58:33 - mmengine - INFO - Epoch(train) [61][1800/2569] lr: 4.0000e-02 eta: 16:56:54 time: 0.2630 data_time: 0.0073 memory: 5828 grad_norm: 3.1685 loss: 2.6214 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6214 2023/06/05 03:58:38 - mmengine - INFO - Epoch(train) [61][1820/2569] lr: 4.0000e-02 eta: 16:56:49 time: 0.2637 data_time: 0.0074 memory: 5828 grad_norm: 3.1689 loss: 2.4808 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4808 2023/06/05 03:58:43 - mmengine - INFO - Epoch(train) [61][1840/2569] lr: 4.0000e-02 eta: 16:56:44 time: 0.2633 data_time: 0.0071 memory: 5828 grad_norm: 3.0968 loss: 2.8593 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8593 2023/06/05 03:58:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 03:58:49 - mmengine - INFO - Epoch(train) [61][1860/2569] lr: 4.0000e-02 eta: 16:56:38 time: 0.2600 data_time: 0.0070 memory: 5828 grad_norm: 3.1124 loss: 2.5184 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5184 2023/06/05 03:58:54 - mmengine - INFO - Epoch(train) [61][1880/2569] lr: 4.0000e-02 eta: 16:56:33 time: 0.2635 data_time: 0.0077 memory: 5828 grad_norm: 3.1364 loss: 2.2785 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2785 2023/06/05 03:58:59 - mmengine - INFO - Epoch(train) [61][1900/2569] lr: 4.0000e-02 eta: 16:56:28 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 3.0868 loss: 2.4999 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4999 2023/06/05 03:59:05 - mmengine - INFO - Epoch(train) [61][1920/2569] lr: 4.0000e-02 eta: 16:56:23 time: 0.2822 data_time: 0.0074 memory: 5828 grad_norm: 3.0679 loss: 2.3558 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3558 2023/06/05 03:59:10 - mmengine - INFO - Epoch(train) [61][1940/2569] lr: 4.0000e-02 eta: 16:56:17 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 3.1161 loss: 2.3767 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3767 2023/06/05 03:59:16 - mmengine - INFO - Epoch(train) [61][1960/2569] lr: 4.0000e-02 eta: 16:56:12 time: 0.2676 data_time: 0.0069 memory: 5828 grad_norm: 3.1143 loss: 2.9361 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9361 2023/06/05 03:59:21 - mmengine - INFO - Epoch(train) [61][1980/2569] lr: 4.0000e-02 eta: 16:56:07 time: 0.2706 data_time: 0.0070 memory: 5828 grad_norm: 3.1295 loss: 2.5041 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5041 2023/06/05 03:59:26 - mmengine - INFO - Epoch(train) [61][2000/2569] lr: 4.0000e-02 eta: 16:56:02 time: 0.2721 data_time: 0.0073 memory: 5828 grad_norm: 3.0743 loss: 2.4409 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4409 2023/06/05 03:59:32 - mmengine - INFO - Epoch(train) [61][2020/2569] lr: 4.0000e-02 eta: 16:55:56 time: 0.2581 data_time: 0.0078 memory: 5828 grad_norm: 3.1033 loss: 2.6237 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6237 2023/06/05 03:59:37 - mmengine - INFO - Epoch(train) [61][2040/2569] lr: 4.0000e-02 eta: 16:55:51 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 3.1639 loss: 2.6605 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6605 2023/06/05 03:59:42 - mmengine - INFO - Epoch(train) [61][2060/2569] lr: 4.0000e-02 eta: 16:55:45 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 3.0804 loss: 2.4998 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4998 2023/06/05 03:59:47 - mmengine - INFO - Epoch(train) [61][2080/2569] lr: 4.0000e-02 eta: 16:55:40 time: 0.2596 data_time: 0.0074 memory: 5828 grad_norm: 3.1002 loss: 2.6064 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6064 2023/06/05 03:59:53 - mmengine - INFO - Epoch(train) [61][2100/2569] lr: 4.0000e-02 eta: 16:55:34 time: 0.2627 data_time: 0.0076 memory: 5828 grad_norm: 3.1373 loss: 2.6240 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6240 2023/06/05 03:59:58 - mmengine - INFO - Epoch(train) [61][2120/2569] lr: 4.0000e-02 eta: 16:55:29 time: 0.2649 data_time: 0.0076 memory: 5828 grad_norm: 3.1449 loss: 2.1863 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1863 2023/06/05 04:00:03 - mmengine - INFO - Epoch(train) [61][2140/2569] lr: 4.0000e-02 eta: 16:55:23 time: 0.2582 data_time: 0.0075 memory: 5828 grad_norm: 3.1265 loss: 2.5999 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5999 2023/06/05 04:00:08 - mmengine - INFO - Epoch(train) [61][2160/2569] lr: 4.0000e-02 eta: 16:55:18 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 3.0776 loss: 2.3992 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3992 2023/06/05 04:00:14 - mmengine - INFO - Epoch(train) [61][2180/2569] lr: 4.0000e-02 eta: 16:55:13 time: 0.2583 data_time: 0.0073 memory: 5828 grad_norm: 3.0403 loss: 2.5038 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5038 2023/06/05 04:00:19 - mmengine - INFO - Epoch(train) [61][2200/2569] lr: 4.0000e-02 eta: 16:55:07 time: 0.2702 data_time: 0.0074 memory: 5828 grad_norm: 3.0462 loss: 2.7068 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7068 2023/06/05 04:00:24 - mmengine - INFO - Epoch(train) [61][2220/2569] lr: 4.0000e-02 eta: 16:55:02 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 3.1248 loss: 2.5551 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5551 2023/06/05 04:00:30 - mmengine - INFO - Epoch(train) [61][2240/2569] lr: 4.0000e-02 eta: 16:54:57 time: 0.2670 data_time: 0.0075 memory: 5828 grad_norm: 3.1540 loss: 2.8975 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8975 2023/06/05 04:00:35 - mmengine - INFO - Epoch(train) [61][2260/2569] lr: 4.0000e-02 eta: 16:54:51 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 3.1049 loss: 2.6652 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6652 2023/06/05 04:00:40 - mmengine - INFO - Epoch(train) [61][2280/2569] lr: 4.0000e-02 eta: 16:54:46 time: 0.2599 data_time: 0.0071 memory: 5828 grad_norm: 3.1198 loss: 2.6207 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6207 2023/06/05 04:00:45 - mmengine - INFO - Epoch(train) [61][2300/2569] lr: 4.0000e-02 eta: 16:54:40 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 3.0765 loss: 1.9802 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9802 2023/06/05 04:00:50 - mmengine - INFO - Epoch(train) [61][2320/2569] lr: 4.0000e-02 eta: 16:54:35 time: 0.2577 data_time: 0.0077 memory: 5828 grad_norm: 3.1575 loss: 2.9035 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9035 2023/06/05 04:00:56 - mmengine - INFO - Epoch(train) [61][2340/2569] lr: 4.0000e-02 eta: 16:54:29 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 3.1084 loss: 2.7513 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7513 2023/06/05 04:01:01 - mmengine - INFO - Epoch(train) [61][2360/2569] lr: 4.0000e-02 eta: 16:54:24 time: 0.2572 data_time: 0.0074 memory: 5828 grad_norm: 3.0875 loss: 2.6596 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6596 2023/06/05 04:01:06 - mmengine - INFO - Epoch(train) [61][2380/2569] lr: 4.0000e-02 eta: 16:54:18 time: 0.2628 data_time: 0.0077 memory: 5828 grad_norm: 3.1515 loss: 2.5735 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5735 2023/06/05 04:01:11 - mmengine - INFO - Epoch(train) [61][2400/2569] lr: 4.0000e-02 eta: 16:54:13 time: 0.2572 data_time: 0.0077 memory: 5828 grad_norm: 3.1329 loss: 2.6887 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6887 2023/06/05 04:01:17 - mmengine - INFO - Epoch(train) [61][2420/2569] lr: 4.0000e-02 eta: 16:54:07 time: 0.2616 data_time: 0.0075 memory: 5828 grad_norm: 3.1744 loss: 2.4040 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4040 2023/06/05 04:01:22 - mmengine - INFO - Epoch(train) [61][2440/2569] lr: 4.0000e-02 eta: 16:54:02 time: 0.2671 data_time: 0.0077 memory: 5828 grad_norm: 3.0999 loss: 2.5958 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5958 2023/06/05 04:01:27 - mmengine - INFO - Epoch(train) [61][2460/2569] lr: 4.0000e-02 eta: 16:53:57 time: 0.2570 data_time: 0.0078 memory: 5828 grad_norm: 3.1159 loss: 2.4375 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4375 2023/06/05 04:01:32 - mmengine - INFO - Epoch(train) [61][2480/2569] lr: 4.0000e-02 eta: 16:53:51 time: 0.2629 data_time: 0.0075 memory: 5828 grad_norm: 3.1162 loss: 2.6557 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6557 2023/06/05 04:01:38 - mmengine - INFO - Epoch(train) [61][2500/2569] lr: 4.0000e-02 eta: 16:53:46 time: 0.2740 data_time: 0.0076 memory: 5828 grad_norm: 3.1103 loss: 2.3083 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3083 2023/06/05 04:01:43 - mmengine - INFO - Epoch(train) [61][2520/2569] lr: 4.0000e-02 eta: 16:53:41 time: 0.2634 data_time: 0.0076 memory: 5828 grad_norm: 3.0668 loss: 2.7516 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7516 2023/06/05 04:01:48 - mmengine - INFO - Epoch(train) [61][2540/2569] lr: 4.0000e-02 eta: 16:53:35 time: 0.2617 data_time: 0.0071 memory: 5828 grad_norm: 3.0907 loss: 2.5617 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5617 2023/06/05 04:01:54 - mmengine - INFO - Epoch(train) [61][2560/2569] lr: 4.0000e-02 eta: 16:53:30 time: 0.2640 data_time: 0.0075 memory: 5828 grad_norm: 3.0774 loss: 2.4549 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4549 2023/06/05 04:01:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:01:56 - mmengine - INFO - Epoch(train) [61][2569/2569] lr: 4.0000e-02 eta: 16:53:27 time: 0.2516 data_time: 0.0072 memory: 5828 grad_norm: 3.0784 loss: 2.3024 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.3024 2023/06/05 04:02:03 - mmengine - INFO - Epoch(train) [62][ 20/2569] lr: 4.0000e-02 eta: 16:53:24 time: 0.3416 data_time: 0.0556 memory: 5828 grad_norm: 3.1387 loss: 2.2326 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2326 2023/06/05 04:02:08 - mmengine - INFO - Epoch(train) [62][ 40/2569] lr: 4.0000e-02 eta: 16:53:19 time: 0.2789 data_time: 0.0077 memory: 5828 grad_norm: 3.3906 loss: 2.4437 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4437 2023/06/05 04:02:13 - mmengine - INFO - Epoch(train) [62][ 60/2569] lr: 4.0000e-02 eta: 16:53:14 time: 0.2591 data_time: 0.0074 memory: 5828 grad_norm: 3.1679 loss: 2.2642 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2642 2023/06/05 04:02:19 - mmengine - INFO - Epoch(train) [62][ 80/2569] lr: 4.0000e-02 eta: 16:53:08 time: 0.2587 data_time: 0.0075 memory: 5828 grad_norm: 3.1922 loss: 2.5678 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5678 2023/06/05 04:02:24 - mmengine - INFO - Epoch(train) [62][ 100/2569] lr: 4.0000e-02 eta: 16:53:03 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 3.0935 loss: 2.5093 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5093 2023/06/05 04:02:29 - mmengine - INFO - Epoch(train) [62][ 120/2569] lr: 4.0000e-02 eta: 16:52:57 time: 0.2600 data_time: 0.0078 memory: 5828 grad_norm: 3.1115 loss: 2.8217 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8217 2023/06/05 04:02:34 - mmengine - INFO - Epoch(train) [62][ 140/2569] lr: 4.0000e-02 eta: 16:52:52 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 3.1132 loss: 2.4978 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4978 2023/06/05 04:02:40 - mmengine - INFO - Epoch(train) [62][ 160/2569] lr: 4.0000e-02 eta: 16:52:46 time: 0.2573 data_time: 0.0071 memory: 5828 grad_norm: 3.0995 loss: 2.6282 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6282 2023/06/05 04:02:45 - mmengine - INFO - Epoch(train) [62][ 180/2569] lr: 4.0000e-02 eta: 16:52:41 time: 0.2653 data_time: 0.0073 memory: 5828 grad_norm: 3.1126 loss: 2.2827 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2827 2023/06/05 04:02:50 - mmengine - INFO - Epoch(train) [62][ 200/2569] lr: 4.0000e-02 eta: 16:52:35 time: 0.2581 data_time: 0.0075 memory: 5828 grad_norm: 3.0989 loss: 2.5273 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5273 2023/06/05 04:02:55 - mmengine - INFO - Epoch(train) [62][ 220/2569] lr: 4.0000e-02 eta: 16:52:30 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 3.1318 loss: 2.4553 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4553 2023/06/05 04:03:01 - mmengine - INFO - Epoch(train) [62][ 240/2569] lr: 4.0000e-02 eta: 16:52:25 time: 0.2582 data_time: 0.0076 memory: 5828 grad_norm: 3.1376 loss: 2.6908 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6908 2023/06/05 04:03:06 - mmengine - INFO - Epoch(train) [62][ 260/2569] lr: 4.0000e-02 eta: 16:52:19 time: 0.2584 data_time: 0.0072 memory: 5828 grad_norm: 3.0973 loss: 2.3773 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3773 2023/06/05 04:03:11 - mmengine - INFO - Epoch(train) [62][ 280/2569] lr: 4.0000e-02 eta: 16:52:14 time: 0.2594 data_time: 0.0071 memory: 5828 grad_norm: 3.1232 loss: 2.6310 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6310 2023/06/05 04:03:14 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:03:16 - mmengine - INFO - Epoch(train) [62][ 300/2569] lr: 4.0000e-02 eta: 16:52:08 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 3.0871 loss: 2.6669 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6669 2023/06/05 04:03:21 - mmengine - INFO - Epoch(train) [62][ 320/2569] lr: 4.0000e-02 eta: 16:52:03 time: 0.2576 data_time: 0.0074 memory: 5828 grad_norm: 3.1315 loss: 2.3971 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3971 2023/06/05 04:03:27 - mmengine - INFO - Epoch(train) [62][ 340/2569] lr: 4.0000e-02 eta: 16:51:57 time: 0.2666 data_time: 0.0075 memory: 5828 grad_norm: 3.1524 loss: 2.5710 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5710 2023/06/05 04:03:32 - mmengine - INFO - Epoch(train) [62][ 360/2569] lr: 4.0000e-02 eta: 16:51:52 time: 0.2589 data_time: 0.0076 memory: 5828 grad_norm: 3.0347 loss: 2.5906 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5906 2023/06/05 04:03:37 - mmengine - INFO - Epoch(train) [62][ 380/2569] lr: 4.0000e-02 eta: 16:51:47 time: 0.2681 data_time: 0.0074 memory: 5828 grad_norm: 3.1354 loss: 2.7455 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7455 2023/06/05 04:03:43 - mmengine - INFO - Epoch(train) [62][ 400/2569] lr: 4.0000e-02 eta: 16:51:41 time: 0.2722 data_time: 0.0074 memory: 5828 grad_norm: 3.1018 loss: 2.1509 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1509 2023/06/05 04:03:48 - mmengine - INFO - Epoch(train) [62][ 420/2569] lr: 4.0000e-02 eta: 16:51:36 time: 0.2603 data_time: 0.0072 memory: 5828 grad_norm: 3.0751 loss: 2.7184 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7184 2023/06/05 04:03:53 - mmengine - INFO - Epoch(train) [62][ 440/2569] lr: 4.0000e-02 eta: 16:51:30 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 3.1145 loss: 2.3677 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3677 2023/06/05 04:03:59 - mmengine - INFO - Epoch(train) [62][ 460/2569] lr: 4.0000e-02 eta: 16:51:25 time: 0.2683 data_time: 0.0074 memory: 5828 grad_norm: 3.0856 loss: 2.5920 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5920 2023/06/05 04:04:04 - mmengine - INFO - Epoch(train) [62][ 480/2569] lr: 4.0000e-02 eta: 16:51:20 time: 0.2637 data_time: 0.0075 memory: 5828 grad_norm: 3.1630 loss: 2.4789 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4789 2023/06/05 04:04:09 - mmengine - INFO - Epoch(train) [62][ 500/2569] lr: 4.0000e-02 eta: 16:51:14 time: 0.2632 data_time: 0.0078 memory: 5828 grad_norm: 3.1300 loss: 2.5867 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5867 2023/06/05 04:04:14 - mmengine - INFO - Epoch(train) [62][ 520/2569] lr: 4.0000e-02 eta: 16:51:09 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 3.0985 loss: 2.1627 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1627 2023/06/05 04:04:20 - mmengine - INFO - Epoch(train) [62][ 540/2569] lr: 4.0000e-02 eta: 16:51:04 time: 0.2587 data_time: 0.0074 memory: 5828 grad_norm: 3.1305 loss: 2.9483 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9483 2023/06/05 04:04:25 - mmengine - INFO - Epoch(train) [62][ 560/2569] lr: 4.0000e-02 eta: 16:50:58 time: 0.2646 data_time: 0.0074 memory: 5828 grad_norm: 3.0681 loss: 2.5708 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5708 2023/06/05 04:04:30 - mmengine - INFO - Epoch(train) [62][ 580/2569] lr: 4.0000e-02 eta: 16:50:53 time: 0.2580 data_time: 0.0074 memory: 5828 grad_norm: 3.1520 loss: 2.7661 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7661 2023/06/05 04:04:35 - mmengine - INFO - Epoch(train) [62][ 600/2569] lr: 4.0000e-02 eta: 16:50:47 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 3.0709 loss: 2.3357 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3357 2023/06/05 04:04:41 - mmengine - INFO - Epoch(train) [62][ 620/2569] lr: 4.0000e-02 eta: 16:50:42 time: 0.2653 data_time: 0.0077 memory: 5828 grad_norm: 3.1342 loss: 2.5100 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5100 2023/06/05 04:04:46 - mmengine - INFO - Epoch(train) [62][ 640/2569] lr: 4.0000e-02 eta: 16:50:37 time: 0.2592 data_time: 0.0075 memory: 5828 grad_norm: 3.1094 loss: 2.5360 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5360 2023/06/05 04:04:51 - mmengine - INFO - Epoch(train) [62][ 660/2569] lr: 4.0000e-02 eta: 16:50:31 time: 0.2567 data_time: 0.0081 memory: 5828 grad_norm: 3.0745 loss: 2.1568 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1568 2023/06/05 04:04:56 - mmengine - INFO - Epoch(train) [62][ 680/2569] lr: 4.0000e-02 eta: 16:50:26 time: 0.2582 data_time: 0.0074 memory: 5828 grad_norm: 3.1513 loss: 2.7468 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 2.7468 2023/06/05 04:05:02 - mmengine - INFO - Epoch(train) [62][ 700/2569] lr: 4.0000e-02 eta: 16:50:20 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 3.0502 loss: 2.9014 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9014 2023/06/05 04:05:07 - mmengine - INFO - Epoch(train) [62][ 720/2569] lr: 4.0000e-02 eta: 16:50:15 time: 0.2631 data_time: 0.0079 memory: 5828 grad_norm: 3.0711 loss: 3.1995 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 3.1995 2023/06/05 04:05:12 - mmengine - INFO - Epoch(train) [62][ 740/2569] lr: 4.0000e-02 eta: 16:50:09 time: 0.2591 data_time: 0.0073 memory: 5828 grad_norm: 3.1318 loss: 2.5894 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5894 2023/06/05 04:05:17 - mmengine - INFO - Epoch(train) [62][ 760/2569] lr: 4.0000e-02 eta: 16:50:04 time: 0.2636 data_time: 0.0077 memory: 5828 grad_norm: 3.0638 loss: 2.3514 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3514 2023/06/05 04:05:23 - mmengine - INFO - Epoch(train) [62][ 780/2569] lr: 4.0000e-02 eta: 16:49:59 time: 0.2729 data_time: 0.0074 memory: 5828 grad_norm: 3.1291 loss: 2.8009 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8009 2023/06/05 04:05:28 - mmengine - INFO - Epoch(train) [62][ 800/2569] lr: 4.0000e-02 eta: 16:49:53 time: 0.2690 data_time: 0.0073 memory: 5828 grad_norm: 3.1143 loss: 2.6948 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6948 2023/06/05 04:05:33 - mmengine - INFO - Epoch(train) [62][ 820/2569] lr: 4.0000e-02 eta: 16:49:48 time: 0.2580 data_time: 0.0080 memory: 5828 grad_norm: 3.0787 loss: 2.5012 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5012 2023/06/05 04:05:39 - mmengine - INFO - Epoch(train) [62][ 840/2569] lr: 4.0000e-02 eta: 16:49:43 time: 0.2640 data_time: 0.0072 memory: 5828 grad_norm: 3.1529 loss: 2.8027 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8027 2023/06/05 04:05:44 - mmengine - INFO - Epoch(train) [62][ 860/2569] lr: 4.0000e-02 eta: 16:49:37 time: 0.2646 data_time: 0.0074 memory: 5828 grad_norm: 3.1147 loss: 2.3091 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3091 2023/06/05 04:05:49 - mmengine - INFO - Epoch(train) [62][ 880/2569] lr: 4.0000e-02 eta: 16:49:32 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 3.1898 loss: 2.4412 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4412 2023/06/05 04:05:54 - mmengine - INFO - Epoch(train) [62][ 900/2569] lr: 4.0000e-02 eta: 16:49:26 time: 0.2585 data_time: 0.0075 memory: 5828 grad_norm: 3.1427 loss: 2.6102 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6102 2023/06/05 04:06:00 - mmengine - INFO - Epoch(train) [62][ 920/2569] lr: 4.0000e-02 eta: 16:49:21 time: 0.2589 data_time: 0.0081 memory: 5828 grad_norm: 3.0276 loss: 2.4491 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4491 2023/06/05 04:06:05 - mmengine - INFO - Epoch(train) [62][ 940/2569] lr: 4.0000e-02 eta: 16:49:15 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 3.1476 loss: 2.6708 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6708 2023/06/05 04:06:10 - mmengine - INFO - Epoch(train) [62][ 960/2569] lr: 4.0000e-02 eta: 16:49:10 time: 0.2575 data_time: 0.0075 memory: 5828 grad_norm: 3.1601 loss: 2.6151 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6151 2023/06/05 04:06:15 - mmengine - INFO - Epoch(train) [62][ 980/2569] lr: 4.0000e-02 eta: 16:49:05 time: 0.2678 data_time: 0.0072 memory: 5828 grad_norm: 3.0906 loss: 2.8106 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8106 2023/06/05 04:06:21 - mmengine - INFO - Epoch(train) [62][1000/2569] lr: 4.0000e-02 eta: 16:48:59 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 3.0895 loss: 2.5164 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5164 2023/06/05 04:06:26 - mmengine - INFO - Epoch(train) [62][1020/2569] lr: 4.0000e-02 eta: 16:48:54 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 3.0733 loss: 2.3789 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3789 2023/06/05 04:06:31 - mmengine - INFO - Epoch(train) [62][1040/2569] lr: 4.0000e-02 eta: 16:48:48 time: 0.2573 data_time: 0.0077 memory: 5828 grad_norm: 3.1038 loss: 2.2146 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2146 2023/06/05 04:06:36 - mmengine - INFO - Epoch(train) [62][1060/2569] lr: 4.0000e-02 eta: 16:48:43 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 3.0880 loss: 2.4411 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4411 2023/06/05 04:06:42 - mmengine - INFO - Epoch(train) [62][1080/2569] lr: 4.0000e-02 eta: 16:48:37 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 3.0714 loss: 2.6466 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6466 2023/06/05 04:06:47 - mmengine - INFO - Epoch(train) [62][1100/2569] lr: 4.0000e-02 eta: 16:48:32 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 3.0829 loss: 2.3209 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.3209 2023/06/05 04:06:52 - mmengine - INFO - Epoch(train) [62][1120/2569] lr: 4.0000e-02 eta: 16:48:26 time: 0.2571 data_time: 0.0074 memory: 5828 grad_norm: 3.1292 loss: 2.6149 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6149 2023/06/05 04:06:57 - mmengine - INFO - Epoch(train) [62][1140/2569] lr: 4.0000e-02 eta: 16:48:21 time: 0.2570 data_time: 0.0079 memory: 5828 grad_norm: 3.1921 loss: 2.7432 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.7432 2023/06/05 04:07:02 - mmengine - INFO - Epoch(train) [62][1160/2569] lr: 4.0000e-02 eta: 16:48:15 time: 0.2560 data_time: 0.0074 memory: 5828 grad_norm: 3.1714 loss: 2.7049 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7049 2023/06/05 04:07:07 - mmengine - INFO - Epoch(train) [62][1180/2569] lr: 4.0000e-02 eta: 16:48:10 time: 0.2634 data_time: 0.0077 memory: 5828 grad_norm: 3.0720 loss: 2.4376 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4376 2023/06/05 04:07:13 - mmengine - INFO - Epoch(train) [62][1200/2569] lr: 4.0000e-02 eta: 16:48:04 time: 0.2573 data_time: 0.0079 memory: 5828 grad_norm: 3.1288 loss: 2.7531 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7531 2023/06/05 04:07:18 - mmengine - INFO - Epoch(train) [62][1220/2569] lr: 4.0000e-02 eta: 16:47:59 time: 0.2682 data_time: 0.0076 memory: 5828 grad_norm: 3.0963 loss: 2.4626 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4626 2023/06/05 04:07:23 - mmengine - INFO - Epoch(train) [62][1240/2569] lr: 4.0000e-02 eta: 16:47:54 time: 0.2698 data_time: 0.0077 memory: 5828 grad_norm: 3.0864 loss: 2.8892 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8892 2023/06/05 04:07:29 - mmengine - INFO - Epoch(train) [62][1260/2569] lr: 4.0000e-02 eta: 16:47:48 time: 0.2632 data_time: 0.0078 memory: 5828 grad_norm: 3.0744 loss: 2.9653 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.9653 2023/06/05 04:07:34 - mmengine - INFO - Epoch(train) [62][1280/2569] lr: 4.0000e-02 eta: 16:47:43 time: 0.2628 data_time: 0.0079 memory: 5828 grad_norm: 3.1994 loss: 2.4348 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4348 2023/06/05 04:07:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:07:39 - mmengine - INFO - Epoch(train) [62][1300/2569] lr: 4.0000e-02 eta: 16:47:37 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 3.0561 loss: 2.5532 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5532 2023/06/05 04:07:45 - mmengine - INFO - Epoch(train) [62][1320/2569] lr: 4.0000e-02 eta: 16:47:32 time: 0.2751 data_time: 0.0075 memory: 5828 grad_norm: 3.1574 loss: 2.6281 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6281 2023/06/05 04:07:50 - mmengine - INFO - Epoch(train) [62][1340/2569] lr: 4.0000e-02 eta: 16:47:27 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.1403 loss: 2.5620 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5620 2023/06/05 04:07:55 - mmengine - INFO - Epoch(train) [62][1360/2569] lr: 4.0000e-02 eta: 16:47:21 time: 0.2598 data_time: 0.0075 memory: 5828 grad_norm: 3.0396 loss: 2.5915 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5915 2023/06/05 04:08:00 - mmengine - INFO - Epoch(train) [62][1380/2569] lr: 4.0000e-02 eta: 16:47:16 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 3.1636 loss: 2.6624 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6624 2023/06/05 04:08:06 - mmengine - INFO - Epoch(train) [62][1400/2569] lr: 4.0000e-02 eta: 16:47:11 time: 0.2577 data_time: 0.0074 memory: 5828 grad_norm: 3.0867 loss: 2.4542 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4542 2023/06/05 04:08:11 - mmengine - INFO - Epoch(train) [62][1420/2569] lr: 4.0000e-02 eta: 16:47:05 time: 0.2738 data_time: 0.0072 memory: 5828 grad_norm: 3.1465 loss: 2.4744 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4744 2023/06/05 04:08:16 - mmengine - INFO - Epoch(train) [62][1440/2569] lr: 4.0000e-02 eta: 16:47:00 time: 0.2727 data_time: 0.0077 memory: 5828 grad_norm: 3.1005 loss: 2.7589 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7589 2023/06/05 04:08:22 - mmengine - INFO - Epoch(train) [62][1460/2569] lr: 4.0000e-02 eta: 16:46:55 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 3.1104 loss: 2.7417 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7417 2023/06/05 04:08:27 - mmengine - INFO - Epoch(train) [62][1480/2569] lr: 4.0000e-02 eta: 16:46:50 time: 0.2692 data_time: 0.0074 memory: 5828 grad_norm: 3.1034 loss: 2.7765 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7765 2023/06/05 04:08:32 - mmengine - INFO - Epoch(train) [62][1500/2569] lr: 4.0000e-02 eta: 16:46:44 time: 0.2589 data_time: 0.0075 memory: 5828 grad_norm: 3.1371 loss: 2.8440 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8440 2023/06/05 04:08:37 - mmengine - INFO - Epoch(train) [62][1520/2569] lr: 4.0000e-02 eta: 16:46:39 time: 0.2630 data_time: 0.0072 memory: 5828 grad_norm: 3.0808 loss: 2.6804 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6804 2023/06/05 04:08:43 - mmengine - INFO - Epoch(train) [62][1540/2569] lr: 4.0000e-02 eta: 16:46:33 time: 0.2639 data_time: 0.0071 memory: 5828 grad_norm: 3.1348 loss: 2.9756 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9756 2023/06/05 04:08:48 - mmengine - INFO - Epoch(train) [62][1560/2569] lr: 4.0000e-02 eta: 16:46:28 time: 0.2581 data_time: 0.0075 memory: 5828 grad_norm: 3.1618 loss: 2.5727 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5727 2023/06/05 04:08:53 - mmengine - INFO - Epoch(train) [62][1580/2569] lr: 4.0000e-02 eta: 16:46:22 time: 0.2582 data_time: 0.0071 memory: 5828 grad_norm: 3.1018 loss: 2.5311 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5311 2023/06/05 04:08:58 - mmengine - INFO - Epoch(train) [62][1600/2569] lr: 4.0000e-02 eta: 16:46:17 time: 0.2585 data_time: 0.0074 memory: 5828 grad_norm: 3.1525 loss: 2.5671 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5671 2023/06/05 04:09:04 - mmengine - INFO - Epoch(train) [62][1620/2569] lr: 4.0000e-02 eta: 16:46:11 time: 0.2616 data_time: 0.0072 memory: 5828 grad_norm: 3.1352 loss: 2.7059 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7059 2023/06/05 04:09:09 - mmengine - INFO - Epoch(train) [62][1640/2569] lr: 4.0000e-02 eta: 16:46:06 time: 0.2692 data_time: 0.0074 memory: 5828 grad_norm: 3.0911 loss: 2.8655 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.8655 2023/06/05 04:09:14 - mmengine - INFO - Epoch(train) [62][1660/2569] lr: 4.0000e-02 eta: 16:46:00 time: 0.2580 data_time: 0.0071 memory: 5828 grad_norm: 3.1444 loss: 2.2147 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2147 2023/06/05 04:09:19 - mmengine - INFO - Epoch(train) [62][1680/2569] lr: 4.0000e-02 eta: 16:45:55 time: 0.2690 data_time: 0.0073 memory: 5828 grad_norm: 3.0744 loss: 2.6199 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6199 2023/06/05 04:09:25 - mmengine - INFO - Epoch(train) [62][1700/2569] lr: 4.0000e-02 eta: 16:45:50 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 3.1359 loss: 3.0042 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0042 2023/06/05 04:09:30 - mmengine - INFO - Epoch(train) [62][1720/2569] lr: 4.0000e-02 eta: 16:45:44 time: 0.2614 data_time: 0.0075 memory: 5828 grad_norm: 3.1304 loss: 2.2677 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.2677 2023/06/05 04:09:35 - mmengine - INFO - Epoch(train) [62][1740/2569] lr: 4.0000e-02 eta: 16:45:39 time: 0.2640 data_time: 0.0078 memory: 5828 grad_norm: 3.0818 loss: 2.5728 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5728 2023/06/05 04:09:41 - mmengine - INFO - Epoch(train) [62][1760/2569] lr: 4.0000e-02 eta: 16:45:34 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 3.1367 loss: 2.5374 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5374 2023/06/05 04:09:46 - mmengine - INFO - Epoch(train) [62][1780/2569] lr: 4.0000e-02 eta: 16:45:28 time: 0.2616 data_time: 0.0072 memory: 5828 grad_norm: 3.1060 loss: 2.6202 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6202 2023/06/05 04:09:51 - mmengine - INFO - Epoch(train) [62][1800/2569] lr: 4.0000e-02 eta: 16:45:23 time: 0.2778 data_time: 0.0072 memory: 5828 grad_norm: 3.1212 loss: 2.5240 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5240 2023/06/05 04:09:57 - mmengine - INFO - Epoch(train) [62][1820/2569] lr: 4.0000e-02 eta: 16:45:18 time: 0.2642 data_time: 0.0078 memory: 5828 grad_norm: 3.1476 loss: 2.3175 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3175 2023/06/05 04:10:02 - mmengine - INFO - Epoch(train) [62][1840/2569] lr: 4.0000e-02 eta: 16:45:12 time: 0.2588 data_time: 0.0075 memory: 5828 grad_norm: 3.1623 loss: 2.6626 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6626 2023/06/05 04:10:07 - mmengine - INFO - Epoch(train) [62][1860/2569] lr: 4.0000e-02 eta: 16:45:07 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 3.1164 loss: 2.5362 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5362 2023/06/05 04:10:12 - mmengine - INFO - Epoch(train) [62][1880/2569] lr: 4.0000e-02 eta: 16:45:01 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.0843 loss: 2.6506 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6506 2023/06/05 04:10:18 - mmengine - INFO - Epoch(train) [62][1900/2569] lr: 4.0000e-02 eta: 16:44:56 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 3.0645 loss: 2.3424 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3424 2023/06/05 04:10:23 - mmengine - INFO - Epoch(train) [62][1920/2569] lr: 4.0000e-02 eta: 16:44:51 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 3.1235 loss: 2.5607 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5607 2023/06/05 04:10:28 - mmengine - INFO - Epoch(train) [62][1940/2569] lr: 4.0000e-02 eta: 16:44:45 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 3.1379 loss: 2.6327 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6327 2023/06/05 04:10:33 - mmengine - INFO - Epoch(train) [62][1960/2569] lr: 4.0000e-02 eta: 16:44:40 time: 0.2595 data_time: 0.0075 memory: 5828 grad_norm: 3.1337 loss: 2.6316 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6316 2023/06/05 04:10:39 - mmengine - INFO - Epoch(train) [62][1980/2569] lr: 4.0000e-02 eta: 16:44:35 time: 0.2755 data_time: 0.0070 memory: 5828 grad_norm: 3.0583 loss: 2.3968 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3968 2023/06/05 04:10:44 - mmengine - INFO - Epoch(train) [62][2000/2569] lr: 4.0000e-02 eta: 16:44:30 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.1643 loss: 2.4554 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4554 2023/06/05 04:10:49 - mmengine - INFO - Epoch(train) [62][2020/2569] lr: 4.0000e-02 eta: 16:44:24 time: 0.2580 data_time: 0.0071 memory: 5828 grad_norm: 3.1069 loss: 2.3194 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3194 2023/06/05 04:10:55 - mmengine - INFO - Epoch(train) [62][2040/2569] lr: 4.0000e-02 eta: 16:44:19 time: 0.2649 data_time: 0.0069 memory: 5828 grad_norm: 3.0672 loss: 2.9875 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.9875 2023/06/05 04:11:00 - mmengine - INFO - Epoch(train) [62][2060/2569] lr: 4.0000e-02 eta: 16:44:13 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 3.1224 loss: 2.3688 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3688 2023/06/05 04:11:05 - mmengine - INFO - Epoch(train) [62][2080/2569] lr: 4.0000e-02 eta: 16:44:08 time: 0.2713 data_time: 0.0069 memory: 5828 grad_norm: 3.1560 loss: 2.4103 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4103 2023/06/05 04:11:11 - mmengine - INFO - Epoch(train) [62][2100/2569] lr: 4.0000e-02 eta: 16:44:03 time: 0.2705 data_time: 0.0079 memory: 5828 grad_norm: 3.1476 loss: 2.7426 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7426 2023/06/05 04:11:16 - mmengine - INFO - Epoch(train) [62][2120/2569] lr: 4.0000e-02 eta: 16:43:58 time: 0.2707 data_time: 0.0078 memory: 5828 grad_norm: 3.0551 loss: 2.3908 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3908 2023/06/05 04:11:21 - mmengine - INFO - Epoch(train) [62][2140/2569] lr: 4.0000e-02 eta: 16:43:52 time: 0.2578 data_time: 0.0076 memory: 5828 grad_norm: 3.1083 loss: 2.3969 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3969 2023/06/05 04:11:27 - mmengine - INFO - Epoch(train) [62][2160/2569] lr: 4.0000e-02 eta: 16:43:47 time: 0.2758 data_time: 0.0069 memory: 5828 grad_norm: 3.1516 loss: 2.3141 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3141 2023/06/05 04:11:32 - mmengine - INFO - Epoch(train) [62][2180/2569] lr: 4.0000e-02 eta: 16:43:42 time: 0.2591 data_time: 0.0072 memory: 5828 grad_norm: 3.1659 loss: 2.4738 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4738 2023/06/05 04:11:37 - mmengine - INFO - Epoch(train) [62][2200/2569] lr: 4.0000e-02 eta: 16:43:36 time: 0.2638 data_time: 0.0076 memory: 5828 grad_norm: 3.1155 loss: 2.6924 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6924 2023/06/05 04:11:43 - mmengine - INFO - Epoch(train) [62][2220/2569] lr: 4.0000e-02 eta: 16:43:31 time: 0.2598 data_time: 0.0077 memory: 5828 grad_norm: 3.1049 loss: 2.4062 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4062 2023/06/05 04:11:48 - mmengine - INFO - Epoch(train) [62][2240/2569] lr: 4.0000e-02 eta: 16:43:26 time: 0.2697 data_time: 0.0075 memory: 5828 grad_norm: 3.0707 loss: 2.5603 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5603 2023/06/05 04:11:53 - mmengine - INFO - Epoch(train) [62][2260/2569] lr: 4.0000e-02 eta: 16:43:20 time: 0.2568 data_time: 0.0077 memory: 5828 grad_norm: 3.1402 loss: 2.4928 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4928 2023/06/05 04:11:59 - mmengine - INFO - Epoch(train) [62][2280/2569] lr: 4.0000e-02 eta: 16:43:15 time: 0.2646 data_time: 0.0074 memory: 5828 grad_norm: 3.1366 loss: 2.6907 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6907 2023/06/05 04:12:01 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:12:04 - mmengine - INFO - Epoch(train) [62][2300/2569] lr: 4.0000e-02 eta: 16:43:09 time: 0.2589 data_time: 0.0072 memory: 5828 grad_norm: 3.0386 loss: 2.5231 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5231 2023/06/05 04:12:09 - mmengine - INFO - Epoch(train) [62][2320/2569] lr: 4.0000e-02 eta: 16:43:04 time: 0.2691 data_time: 0.0071 memory: 5828 grad_norm: 3.0540 loss: 2.4206 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4206 2023/06/05 04:12:15 - mmengine - INFO - Epoch(train) [62][2340/2569] lr: 4.0000e-02 eta: 16:42:59 time: 0.2764 data_time: 0.0072 memory: 5828 grad_norm: 3.1537 loss: 2.3918 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3918 2023/06/05 04:12:20 - mmengine - INFO - Epoch(train) [62][2360/2569] lr: 4.0000e-02 eta: 16:42:54 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 3.0746 loss: 2.3644 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3644 2023/06/05 04:12:25 - mmengine - INFO - Epoch(train) [62][2380/2569] lr: 4.0000e-02 eta: 16:42:48 time: 0.2583 data_time: 0.0074 memory: 5828 grad_norm: 3.0831 loss: 2.3019 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3019 2023/06/05 04:12:30 - mmengine - INFO - Epoch(train) [62][2400/2569] lr: 4.0000e-02 eta: 16:42:43 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 3.1340 loss: 2.5282 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5282 2023/06/05 04:12:36 - mmengine - INFO - Epoch(train) [62][2420/2569] lr: 4.0000e-02 eta: 16:42:37 time: 0.2648 data_time: 0.0076 memory: 5828 grad_norm: 3.1203 loss: 2.5766 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5766 2023/06/05 04:12:41 - mmengine - INFO - Epoch(train) [62][2440/2569] lr: 4.0000e-02 eta: 16:42:32 time: 0.2696 data_time: 0.0075 memory: 5828 grad_norm: 3.1074 loss: 2.4559 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4559 2023/06/05 04:12:47 - mmengine - INFO - Epoch(train) [62][2460/2569] lr: 4.0000e-02 eta: 16:42:27 time: 0.2690 data_time: 0.0075 memory: 5828 grad_norm: 3.1672 loss: 2.3401 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3401 2023/06/05 04:12:52 - mmengine - INFO - Epoch(train) [62][2480/2569] lr: 4.0000e-02 eta: 16:42:22 time: 0.2782 data_time: 0.0077 memory: 5828 grad_norm: 3.1582 loss: 2.5475 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5475 2023/06/05 04:12:57 - mmengine - INFO - Epoch(train) [62][2500/2569] lr: 4.0000e-02 eta: 16:42:17 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.1322 loss: 2.5785 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5785 2023/06/05 04:13:03 - mmengine - INFO - Epoch(train) [62][2520/2569] lr: 4.0000e-02 eta: 16:42:11 time: 0.2589 data_time: 0.0080 memory: 5828 grad_norm: 3.1692 loss: 2.9380 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9380 2023/06/05 04:13:08 - mmengine - INFO - Epoch(train) [62][2540/2569] lr: 4.0000e-02 eta: 16:42:06 time: 0.2623 data_time: 0.0069 memory: 5828 grad_norm: 3.1576 loss: 2.5904 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5904 2023/06/05 04:13:13 - mmengine - INFO - Epoch(train) [62][2560/2569] lr: 4.0000e-02 eta: 16:42:00 time: 0.2556 data_time: 0.0077 memory: 5828 grad_norm: 3.1617 loss: 2.4727 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4727 2023/06/05 04:13:15 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:13:15 - mmengine - INFO - Epoch(train) [62][2569/2569] lr: 4.0000e-02 eta: 16:41:57 time: 0.2505 data_time: 0.0068 memory: 5828 grad_norm: 3.1361 loss: 2.3460 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.3460 2023/06/05 04:13:22 - mmengine - INFO - Epoch(train) [63][ 20/2569] lr: 4.0000e-02 eta: 16:41:55 time: 0.3523 data_time: 0.0519 memory: 5828 grad_norm: 3.0700 loss: 2.3885 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3885 2023/06/05 04:13:28 - mmengine - INFO - Epoch(train) [63][ 40/2569] lr: 4.0000e-02 eta: 16:41:49 time: 0.2647 data_time: 0.0086 memory: 5828 grad_norm: 3.1099 loss: 2.3647 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3647 2023/06/05 04:13:33 - mmengine - INFO - Epoch(train) [63][ 60/2569] lr: 4.0000e-02 eta: 16:41:44 time: 0.2578 data_time: 0.0078 memory: 5828 grad_norm: 3.1205 loss: 2.1774 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1774 2023/06/05 04:13:38 - mmengine - INFO - Epoch(train) [63][ 80/2569] lr: 4.0000e-02 eta: 16:41:38 time: 0.2665 data_time: 0.0072 memory: 5828 grad_norm: 3.1341 loss: 2.4086 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4086 2023/06/05 04:13:43 - mmengine - INFO - Epoch(train) [63][ 100/2569] lr: 4.0000e-02 eta: 16:41:33 time: 0.2580 data_time: 0.0071 memory: 5828 grad_norm: 3.0812 loss: 2.3801 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3801 2023/06/05 04:13:48 - mmengine - INFO - Epoch(train) [63][ 120/2569] lr: 4.0000e-02 eta: 16:41:27 time: 0.2611 data_time: 0.0071 memory: 5828 grad_norm: 3.1037 loss: 2.4143 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4143 2023/06/05 04:13:54 - mmengine - INFO - Epoch(train) [63][ 140/2569] lr: 4.0000e-02 eta: 16:41:22 time: 0.2588 data_time: 0.0073 memory: 5828 grad_norm: 3.0954 loss: 2.4335 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4335 2023/06/05 04:13:59 - mmengine - INFO - Epoch(train) [63][ 160/2569] lr: 4.0000e-02 eta: 16:41:16 time: 0.2645 data_time: 0.0076 memory: 5828 grad_norm: 3.1849 loss: 2.5597 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5597 2023/06/05 04:14:04 - mmengine - INFO - Epoch(train) [63][ 180/2569] lr: 4.0000e-02 eta: 16:41:11 time: 0.2640 data_time: 0.0071 memory: 5828 grad_norm: 3.1651 loss: 2.8727 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8727 2023/06/05 04:14:09 - mmengine - INFO - Epoch(train) [63][ 200/2569] lr: 4.0000e-02 eta: 16:41:06 time: 0.2579 data_time: 0.0074 memory: 5828 grad_norm: 3.0997 loss: 2.7650 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7650 2023/06/05 04:14:15 - mmengine - INFO - Epoch(train) [63][ 220/2569] lr: 4.0000e-02 eta: 16:41:00 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 3.1251 loss: 2.4466 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4466 2023/06/05 04:14:20 - mmengine - INFO - Epoch(train) [63][ 240/2569] lr: 4.0000e-02 eta: 16:40:55 time: 0.2651 data_time: 0.0075 memory: 5828 grad_norm: 3.1595 loss: 2.7136 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.7136 2023/06/05 04:14:25 - mmengine - INFO - Epoch(train) [63][ 260/2569] lr: 4.0000e-02 eta: 16:40:49 time: 0.2689 data_time: 0.0072 memory: 5828 grad_norm: 3.0737 loss: 2.2185 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2185 2023/06/05 04:14:31 - mmengine - INFO - Epoch(train) [63][ 280/2569] lr: 4.0000e-02 eta: 16:40:44 time: 0.2686 data_time: 0.0075 memory: 5828 grad_norm: 3.1788 loss: 2.6220 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6220 2023/06/05 04:14:36 - mmengine - INFO - Epoch(train) [63][ 300/2569] lr: 4.0000e-02 eta: 16:40:39 time: 0.2646 data_time: 0.0086 memory: 5828 grad_norm: 3.1526 loss: 2.7887 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7887 2023/06/05 04:14:41 - mmengine - INFO - Epoch(train) [63][ 320/2569] lr: 4.0000e-02 eta: 16:40:33 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 3.0981 loss: 2.3682 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3682 2023/06/05 04:14:46 - mmengine - INFO - Epoch(train) [63][ 340/2569] lr: 4.0000e-02 eta: 16:40:28 time: 0.2576 data_time: 0.0073 memory: 5828 grad_norm: 3.1699 loss: 2.4627 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4627 2023/06/05 04:14:52 - mmengine - INFO - Epoch(train) [63][ 360/2569] lr: 4.0000e-02 eta: 16:40:23 time: 0.2742 data_time: 0.0076 memory: 5828 grad_norm: 3.0819 loss: 2.0670 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0670 2023/06/05 04:14:57 - mmengine - INFO - Epoch(train) [63][ 380/2569] lr: 4.0000e-02 eta: 16:40:17 time: 0.2564 data_time: 0.0070 memory: 5828 grad_norm: 3.1420 loss: 2.4278 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4278 2023/06/05 04:15:02 - mmengine - INFO - Epoch(train) [63][ 400/2569] lr: 4.0000e-02 eta: 16:40:12 time: 0.2662 data_time: 0.0069 memory: 5828 grad_norm: 3.1115 loss: 2.4648 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4648 2023/06/05 04:15:08 - mmengine - INFO - Epoch(train) [63][ 420/2569] lr: 4.0000e-02 eta: 16:40:07 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 3.1296 loss: 2.3679 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3679 2023/06/05 04:15:13 - mmengine - INFO - Epoch(train) [63][ 440/2569] lr: 4.0000e-02 eta: 16:40:01 time: 0.2678 data_time: 0.0074 memory: 5828 grad_norm: 3.1039 loss: 2.8440 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8440 2023/06/05 04:15:18 - mmengine - INFO - Epoch(train) [63][ 460/2569] lr: 4.0000e-02 eta: 16:39:56 time: 0.2641 data_time: 0.0071 memory: 5828 grad_norm: 3.1352 loss: 2.2061 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2061 2023/06/05 04:15:24 - mmengine - INFO - Epoch(train) [63][ 480/2569] lr: 4.0000e-02 eta: 16:39:51 time: 0.2711 data_time: 0.0073 memory: 5828 grad_norm: 2.9918 loss: 2.4656 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4656 2023/06/05 04:15:29 - mmengine - INFO - Epoch(train) [63][ 500/2569] lr: 4.0000e-02 eta: 16:39:45 time: 0.2651 data_time: 0.0070 memory: 5828 grad_norm: 3.1308 loss: 2.2975 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2975 2023/06/05 04:15:34 - mmengine - INFO - Epoch(train) [63][ 520/2569] lr: 4.0000e-02 eta: 16:39:40 time: 0.2625 data_time: 0.0078 memory: 5828 grad_norm: 3.1496 loss: 2.4844 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4844 2023/06/05 04:15:39 - mmengine - INFO - Epoch(train) [63][ 540/2569] lr: 4.0000e-02 eta: 16:39:34 time: 0.2572 data_time: 0.0074 memory: 5828 grad_norm: 3.0728 loss: 2.6313 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6313 2023/06/05 04:15:45 - mmengine - INFO - Epoch(train) [63][ 560/2569] lr: 4.0000e-02 eta: 16:39:29 time: 0.2615 data_time: 0.0078 memory: 5828 grad_norm: 3.1243 loss: 2.7044 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7044 2023/06/05 04:15:50 - mmengine - INFO - Epoch(train) [63][ 580/2569] lr: 4.0000e-02 eta: 16:39:24 time: 0.2648 data_time: 0.0073 memory: 5828 grad_norm: 3.1648 loss: 2.6200 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6200 2023/06/05 04:15:55 - mmengine - INFO - Epoch(train) [63][ 600/2569] lr: 4.0000e-02 eta: 16:39:18 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 3.0280 loss: 2.5712 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5712 2023/06/05 04:16:01 - mmengine - INFO - Epoch(train) [63][ 620/2569] lr: 4.0000e-02 eta: 16:39:13 time: 0.2683 data_time: 0.0076 memory: 5828 grad_norm: 3.0936 loss: 2.5101 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5101 2023/06/05 04:16:06 - mmengine - INFO - Epoch(train) [63][ 640/2569] lr: 4.0000e-02 eta: 16:39:07 time: 0.2581 data_time: 0.0073 memory: 5828 grad_norm: 3.0912 loss: 2.4587 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4587 2023/06/05 04:16:11 - mmengine - INFO - Epoch(train) [63][ 660/2569] lr: 4.0000e-02 eta: 16:39:02 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 3.0975 loss: 2.6096 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6096 2023/06/05 04:16:16 - mmengine - INFO - Epoch(train) [63][ 680/2569] lr: 4.0000e-02 eta: 16:38:57 time: 0.2587 data_time: 0.0076 memory: 5828 grad_norm: 3.1207 loss: 2.7972 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7972 2023/06/05 04:16:22 - mmengine - INFO - Epoch(train) [63][ 700/2569] lr: 4.0000e-02 eta: 16:38:51 time: 0.2686 data_time: 0.0074 memory: 5828 grad_norm: 3.1112 loss: 2.4569 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4569 2023/06/05 04:16:27 - mmengine - INFO - Epoch(train) [63][ 720/2569] lr: 4.0000e-02 eta: 16:38:46 time: 0.2589 data_time: 0.0076 memory: 5828 grad_norm: 3.1291 loss: 2.2550 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2550 2023/06/05 04:16:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:16:32 - mmengine - INFO - Epoch(train) [63][ 740/2569] lr: 4.0000e-02 eta: 16:38:40 time: 0.2629 data_time: 0.0068 memory: 5828 grad_norm: 3.1753 loss: 2.3313 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3313 2023/06/05 04:16:37 - mmengine - INFO - Epoch(train) [63][ 760/2569] lr: 4.0000e-02 eta: 16:38:35 time: 0.2630 data_time: 0.0074 memory: 5828 grad_norm: 3.0653 loss: 2.8883 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8883 2023/06/05 04:16:43 - mmengine - INFO - Epoch(train) [63][ 780/2569] lr: 4.0000e-02 eta: 16:38:30 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 3.1670 loss: 2.7437 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7437 2023/06/05 04:16:48 - mmengine - INFO - Epoch(train) [63][ 800/2569] lr: 4.0000e-02 eta: 16:38:24 time: 0.2574 data_time: 0.0075 memory: 5828 grad_norm: 3.1259 loss: 2.3848 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3848 2023/06/05 04:16:53 - mmengine - INFO - Epoch(train) [63][ 820/2569] lr: 4.0000e-02 eta: 16:38:19 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 3.1495 loss: 2.1158 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1158 2023/06/05 04:16:58 - mmengine - INFO - Epoch(train) [63][ 840/2569] lr: 4.0000e-02 eta: 16:38:13 time: 0.2678 data_time: 0.0071 memory: 5828 grad_norm: 3.0950 loss: 2.1536 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1536 2023/06/05 04:17:04 - mmengine - INFO - Epoch(train) [63][ 860/2569] lr: 4.0000e-02 eta: 16:38:08 time: 0.2595 data_time: 0.0071 memory: 5828 grad_norm: 3.1145 loss: 2.5271 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.5271 2023/06/05 04:17:09 - mmengine - INFO - Epoch(train) [63][ 880/2569] lr: 4.0000e-02 eta: 16:38:02 time: 0.2626 data_time: 0.0072 memory: 5828 grad_norm: 3.1469 loss: 2.4080 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4080 2023/06/05 04:17:14 - mmengine - INFO - Epoch(train) [63][ 900/2569] lr: 4.0000e-02 eta: 16:37:57 time: 0.2636 data_time: 0.0076 memory: 5828 grad_norm: 3.1710 loss: 2.5970 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5970 2023/06/05 04:17:19 - mmengine - INFO - Epoch(train) [63][ 920/2569] lr: 4.0000e-02 eta: 16:37:52 time: 0.2698 data_time: 0.0078 memory: 5828 grad_norm: 3.1227 loss: 2.5212 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5212 2023/06/05 04:17:25 - mmengine - INFO - Epoch(train) [63][ 940/2569] lr: 4.0000e-02 eta: 16:37:47 time: 0.2632 data_time: 0.0070 memory: 5828 grad_norm: 3.1278 loss: 2.6419 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6419 2023/06/05 04:17:30 - mmengine - INFO - Epoch(train) [63][ 960/2569] lr: 4.0000e-02 eta: 16:37:41 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 3.1650 loss: 2.3504 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3504 2023/06/05 04:17:35 - mmengine - INFO - Epoch(train) [63][ 980/2569] lr: 4.0000e-02 eta: 16:37:36 time: 0.2595 data_time: 0.0074 memory: 5828 grad_norm: 3.1067 loss: 2.8309 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.8309 2023/06/05 04:17:41 - mmengine - INFO - Epoch(train) [63][1000/2569] lr: 4.0000e-02 eta: 16:37:30 time: 0.2642 data_time: 0.0075 memory: 5828 grad_norm: 3.1121 loss: 2.2525 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2525 2023/06/05 04:17:46 - mmengine - INFO - Epoch(train) [63][1020/2569] lr: 4.0000e-02 eta: 16:37:25 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.0946 loss: 2.5918 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5918 2023/06/05 04:17:51 - mmengine - INFO - Epoch(train) [63][1040/2569] lr: 4.0000e-02 eta: 16:37:19 time: 0.2618 data_time: 0.0076 memory: 5828 grad_norm: 3.1286 loss: 2.7918 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7918 2023/06/05 04:17:56 - mmengine - INFO - Epoch(train) [63][1060/2569] lr: 4.0000e-02 eta: 16:37:14 time: 0.2631 data_time: 0.0076 memory: 5828 grad_norm: 3.1452 loss: 2.1738 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1738 2023/06/05 04:18:01 - mmengine - INFO - Epoch(train) [63][1080/2569] lr: 4.0000e-02 eta: 16:37:09 time: 0.2597 data_time: 0.0077 memory: 5828 grad_norm: 3.1147 loss: 2.6016 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6016 2023/06/05 04:18:07 - mmengine - INFO - Epoch(train) [63][1100/2569] lr: 4.0000e-02 eta: 16:37:03 time: 0.2584 data_time: 0.0078 memory: 5828 grad_norm: 3.0965 loss: 2.5199 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5199 2023/06/05 04:18:12 - mmengine - INFO - Epoch(train) [63][1120/2569] lr: 4.0000e-02 eta: 16:36:58 time: 0.2653 data_time: 0.0071 memory: 5828 grad_norm: 3.1877 loss: 2.7135 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7135 2023/06/05 04:18:17 - mmengine - INFO - Epoch(train) [63][1140/2569] lr: 4.0000e-02 eta: 16:36:52 time: 0.2673 data_time: 0.0076 memory: 5828 grad_norm: 3.1047 loss: 2.8286 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8286 2023/06/05 04:18:23 - mmengine - INFO - Epoch(train) [63][1160/2569] lr: 4.0000e-02 eta: 16:36:47 time: 0.2642 data_time: 0.0080 memory: 5828 grad_norm: 3.0807 loss: 2.5695 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5695 2023/06/05 04:18:28 - mmengine - INFO - Epoch(train) [63][1180/2569] lr: 4.0000e-02 eta: 16:36:42 time: 0.2709 data_time: 0.0077 memory: 5828 grad_norm: 3.0518 loss: 2.7721 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7721 2023/06/05 04:18:33 - mmengine - INFO - Epoch(train) [63][1200/2569] lr: 4.0000e-02 eta: 16:36:36 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.1236 loss: 2.3448 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3448 2023/06/05 04:18:39 - mmengine - INFO - Epoch(train) [63][1220/2569] lr: 4.0000e-02 eta: 16:36:31 time: 0.2639 data_time: 0.0072 memory: 5828 grad_norm: 3.1518 loss: 2.6758 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6758 2023/06/05 04:18:44 - mmengine - INFO - Epoch(train) [63][1240/2569] lr: 4.0000e-02 eta: 16:36:26 time: 0.2584 data_time: 0.0072 memory: 5828 grad_norm: 3.1296 loss: 2.5236 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5236 2023/06/05 04:18:49 - mmengine - INFO - Epoch(train) [63][1260/2569] lr: 4.0000e-02 eta: 16:36:20 time: 0.2641 data_time: 0.0071 memory: 5828 grad_norm: 3.0711 loss: 2.3843 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3843 2023/06/05 04:18:54 - mmengine - INFO - Epoch(train) [63][1280/2569] lr: 4.0000e-02 eta: 16:36:15 time: 0.2621 data_time: 0.0070 memory: 5828 grad_norm: 3.1069 loss: 2.7440 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7440 2023/06/05 04:19:00 - mmengine - INFO - Epoch(train) [63][1300/2569] lr: 4.0000e-02 eta: 16:36:09 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 3.1507 loss: 2.4290 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4290 2023/06/05 04:19:05 - mmengine - INFO - Epoch(train) [63][1320/2569] lr: 4.0000e-02 eta: 16:36:04 time: 0.2738 data_time: 0.0076 memory: 5828 grad_norm: 3.1446 loss: 2.4415 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.4415 2023/06/05 04:19:10 - mmengine - INFO - Epoch(train) [63][1340/2569] lr: 4.0000e-02 eta: 16:35:59 time: 0.2582 data_time: 0.0075 memory: 5828 grad_norm: 3.0603 loss: 2.4308 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4308 2023/06/05 04:19:16 - mmengine - INFO - Epoch(train) [63][1360/2569] lr: 4.0000e-02 eta: 16:35:54 time: 0.2715 data_time: 0.0073 memory: 5828 grad_norm: 3.1102 loss: 2.5429 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5429 2023/06/05 04:19:21 - mmengine - INFO - Epoch(train) [63][1380/2569] lr: 4.0000e-02 eta: 16:35:48 time: 0.2560 data_time: 0.0078 memory: 5828 grad_norm: 3.1340 loss: 2.4040 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4040 2023/06/05 04:19:26 - mmengine - INFO - Epoch(train) [63][1400/2569] lr: 4.0000e-02 eta: 16:35:43 time: 0.2661 data_time: 0.0070 memory: 5828 grad_norm: 3.1139 loss: 2.4513 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.4513 2023/06/05 04:19:31 - mmengine - INFO - Epoch(train) [63][1420/2569] lr: 4.0000e-02 eta: 16:35:37 time: 0.2637 data_time: 0.0074 memory: 5828 grad_norm: 3.0184 loss: 2.1986 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1986 2023/06/05 04:19:37 - mmengine - INFO - Epoch(train) [63][1440/2569] lr: 4.0000e-02 eta: 16:35:32 time: 0.2596 data_time: 0.0072 memory: 5828 grad_norm: 3.0728 loss: 2.8903 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8903 2023/06/05 04:19:42 - mmengine - INFO - Epoch(train) [63][1460/2569] lr: 4.0000e-02 eta: 16:35:26 time: 0.2590 data_time: 0.0078 memory: 5828 grad_norm: 3.0948 loss: 2.5550 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5550 2023/06/05 04:19:47 - mmengine - INFO - Epoch(train) [63][1480/2569] lr: 4.0000e-02 eta: 16:35:21 time: 0.2694 data_time: 0.0073 memory: 5828 grad_norm: 3.1203 loss: 3.1121 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.1121 2023/06/05 04:19:52 - mmengine - INFO - Epoch(train) [63][1500/2569] lr: 4.0000e-02 eta: 16:35:16 time: 0.2590 data_time: 0.0076 memory: 5828 grad_norm: 3.1329 loss: 2.8956 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8956 2023/06/05 04:19:58 - mmengine - INFO - Epoch(train) [63][1520/2569] lr: 4.0000e-02 eta: 16:35:10 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 3.1515 loss: 2.5944 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5944 2023/06/05 04:20:03 - mmengine - INFO - Epoch(train) [63][1540/2569] lr: 4.0000e-02 eta: 16:35:05 time: 0.2587 data_time: 0.0069 memory: 5828 grad_norm: 3.0924 loss: 2.5809 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5809 2023/06/05 04:20:08 - mmengine - INFO - Epoch(train) [63][1560/2569] lr: 4.0000e-02 eta: 16:34:59 time: 0.2626 data_time: 0.0078 memory: 5828 grad_norm: 3.1640 loss: 2.7142 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7142 2023/06/05 04:20:14 - mmengine - INFO - Epoch(train) [63][1580/2569] lr: 4.0000e-02 eta: 16:34:54 time: 0.2688 data_time: 0.0071 memory: 5828 grad_norm: 3.0984 loss: 2.6410 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6410 2023/06/05 04:20:19 - mmengine - INFO - Epoch(train) [63][1600/2569] lr: 4.0000e-02 eta: 16:34:49 time: 0.2582 data_time: 0.0074 memory: 5828 grad_norm: 3.1299 loss: 2.0380 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0380 2023/06/05 04:20:24 - mmengine - INFO - Epoch(train) [63][1620/2569] lr: 4.0000e-02 eta: 16:34:43 time: 0.2726 data_time: 0.0075 memory: 5828 grad_norm: 3.1297 loss: 2.4015 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4015 2023/06/05 04:20:29 - mmengine - INFO - Epoch(train) [63][1640/2569] lr: 4.0000e-02 eta: 16:34:38 time: 0.2610 data_time: 0.0074 memory: 5828 grad_norm: 3.1039 loss: 2.1892 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1892 2023/06/05 04:20:35 - mmengine - INFO - Epoch(train) [63][1660/2569] lr: 4.0000e-02 eta: 16:34:33 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 3.1261 loss: 2.3757 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3757 2023/06/05 04:20:40 - mmengine - INFO - Epoch(train) [63][1680/2569] lr: 4.0000e-02 eta: 16:34:27 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 3.1097 loss: 2.5387 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.5387 2023/06/05 04:20:45 - mmengine - INFO - Epoch(train) [63][1700/2569] lr: 4.0000e-02 eta: 16:34:22 time: 0.2677 data_time: 0.0076 memory: 5828 grad_norm: 3.1810 loss: 2.5700 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5700 2023/06/05 04:20:51 - mmengine - INFO - Epoch(train) [63][1720/2569] lr: 4.0000e-02 eta: 16:34:17 time: 0.2690 data_time: 0.0072 memory: 5828 grad_norm: 3.0388 loss: 2.3973 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.3973 2023/06/05 04:20:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:20:56 - mmengine - INFO - Epoch(train) [63][1740/2569] lr: 4.0000e-02 eta: 16:34:11 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 3.1948 loss: 2.5263 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5263 2023/06/05 04:21:01 - mmengine - INFO - Epoch(train) [63][1760/2569] lr: 4.0000e-02 eta: 16:34:06 time: 0.2692 data_time: 0.0075 memory: 5828 grad_norm: 3.0789 loss: 2.4276 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4276 2023/06/05 04:21:07 - mmengine - INFO - Epoch(train) [63][1780/2569] lr: 4.0000e-02 eta: 16:34:01 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 3.1547 loss: 2.3296 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3296 2023/06/05 04:21:12 - mmengine - INFO - Epoch(train) [63][1800/2569] lr: 4.0000e-02 eta: 16:33:55 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 3.0827 loss: 2.7650 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7650 2023/06/05 04:21:17 - mmengine - INFO - Epoch(train) [63][1820/2569] lr: 4.0000e-02 eta: 16:33:50 time: 0.2597 data_time: 0.0072 memory: 5828 grad_norm: 3.1799 loss: 2.6042 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6042 2023/06/05 04:21:23 - mmengine - INFO - Epoch(train) [63][1840/2569] lr: 4.0000e-02 eta: 16:33:45 time: 0.2647 data_time: 0.0076 memory: 5828 grad_norm: 3.0880 loss: 2.6360 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6360 2023/06/05 04:21:28 - mmengine - INFO - Epoch(train) [63][1860/2569] lr: 4.0000e-02 eta: 16:33:39 time: 0.2598 data_time: 0.0078 memory: 5828 grad_norm: 3.1408 loss: 2.6703 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6703 2023/06/05 04:21:33 - mmengine - INFO - Epoch(train) [63][1880/2569] lr: 4.0000e-02 eta: 16:33:34 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 3.1446 loss: 2.8481 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8481 2023/06/05 04:21:38 - mmengine - INFO - Epoch(train) [63][1900/2569] lr: 4.0000e-02 eta: 16:33:28 time: 0.2647 data_time: 0.0071 memory: 5828 grad_norm: 3.1442 loss: 2.8889 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8889 2023/06/05 04:21:43 - mmengine - INFO - Epoch(train) [63][1920/2569] lr: 4.0000e-02 eta: 16:33:23 time: 0.2578 data_time: 0.0073 memory: 5828 grad_norm: 3.1345 loss: 2.6083 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6083 2023/06/05 04:21:49 - mmengine - INFO - Epoch(train) [63][1940/2569] lr: 4.0000e-02 eta: 16:33:18 time: 0.2671 data_time: 0.0077 memory: 5828 grad_norm: 3.0877 loss: 2.5643 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5643 2023/06/05 04:21:54 - mmengine - INFO - Epoch(train) [63][1960/2569] lr: 4.0000e-02 eta: 16:33:12 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 3.1266 loss: 2.5514 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5514 2023/06/05 04:21:59 - mmengine - INFO - Epoch(train) [63][1980/2569] lr: 4.0000e-02 eta: 16:33:07 time: 0.2619 data_time: 0.0071 memory: 5828 grad_norm: 3.0865 loss: 2.4339 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4339 2023/06/05 04:22:05 - mmengine - INFO - Epoch(train) [63][2000/2569] lr: 4.0000e-02 eta: 16:33:02 time: 0.2674 data_time: 0.0075 memory: 5828 grad_norm: 3.0687 loss: 2.6150 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6150 2023/06/05 04:22:10 - mmengine - INFO - Epoch(train) [63][2020/2569] lr: 4.0000e-02 eta: 16:32:56 time: 0.2614 data_time: 0.0077 memory: 5828 grad_norm: 3.1095 loss: 2.4037 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4037 2023/06/05 04:22:15 - mmengine - INFO - Epoch(train) [63][2040/2569] lr: 4.0000e-02 eta: 16:32:51 time: 0.2696 data_time: 0.0079 memory: 5828 grad_norm: 3.1322 loss: 2.3908 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3908 2023/06/05 04:22:21 - mmengine - INFO - Epoch(train) [63][2060/2569] lr: 4.0000e-02 eta: 16:32:46 time: 0.2732 data_time: 0.0077 memory: 5828 grad_norm: 3.0674 loss: 2.6250 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6250 2023/06/05 04:22:26 - mmengine - INFO - Epoch(train) [63][2080/2569] lr: 4.0000e-02 eta: 16:32:40 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 3.1088 loss: 2.6900 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6900 2023/06/05 04:22:31 - mmengine - INFO - Epoch(train) [63][2100/2569] lr: 4.0000e-02 eta: 16:32:35 time: 0.2699 data_time: 0.0076 memory: 5828 grad_norm: 3.1021 loss: 2.7348 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7348 2023/06/05 04:22:37 - mmengine - INFO - Epoch(train) [63][2120/2569] lr: 4.0000e-02 eta: 16:32:30 time: 0.2692 data_time: 0.0074 memory: 5828 grad_norm: 3.1503 loss: 2.4185 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4185 2023/06/05 04:22:42 - mmengine - INFO - Epoch(train) [63][2140/2569] lr: 4.0000e-02 eta: 16:32:24 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 3.1358 loss: 2.5788 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5788 2023/06/05 04:22:47 - mmengine - INFO - Epoch(train) [63][2160/2569] lr: 4.0000e-02 eta: 16:32:19 time: 0.2660 data_time: 0.0079 memory: 5828 grad_norm: 3.2142 loss: 2.6305 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6305 2023/06/05 04:22:53 - mmengine - INFO - Epoch(train) [63][2180/2569] lr: 4.0000e-02 eta: 16:32:14 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 3.0663 loss: 2.4083 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4083 2023/06/05 04:22:58 - mmengine - INFO - Epoch(train) [63][2200/2569] lr: 4.0000e-02 eta: 16:32:08 time: 0.2600 data_time: 0.0075 memory: 5828 grad_norm: 3.1315 loss: 2.5146 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5146 2023/06/05 04:23:03 - mmengine - INFO - Epoch(train) [63][2220/2569] lr: 4.0000e-02 eta: 16:32:03 time: 0.2665 data_time: 0.0076 memory: 5828 grad_norm: 3.1196 loss: 2.4091 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4091 2023/06/05 04:23:09 - mmengine - INFO - Epoch(train) [63][2240/2569] lr: 4.0000e-02 eta: 16:31:58 time: 0.2630 data_time: 0.0073 memory: 5828 grad_norm: 3.1438 loss: 2.6975 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6975 2023/06/05 04:23:14 - mmengine - INFO - Epoch(train) [63][2260/2569] lr: 4.0000e-02 eta: 16:31:52 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 3.1073 loss: 2.4369 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4369 2023/06/05 04:23:19 - mmengine - INFO - Epoch(train) [63][2280/2569] lr: 4.0000e-02 eta: 16:31:47 time: 0.2588 data_time: 0.0074 memory: 5828 grad_norm: 3.0869 loss: 2.5502 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5502 2023/06/05 04:23:24 - mmengine - INFO - Epoch(train) [63][2300/2569] lr: 4.0000e-02 eta: 16:31:41 time: 0.2581 data_time: 0.0074 memory: 5828 grad_norm: 3.0371 loss: 2.3122 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3122 2023/06/05 04:23:30 - mmengine - INFO - Epoch(train) [63][2320/2569] lr: 4.0000e-02 eta: 16:31:36 time: 0.2610 data_time: 0.0072 memory: 5828 grad_norm: 3.0836 loss: 2.5517 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5517 2023/06/05 04:23:35 - mmengine - INFO - Epoch(train) [63][2340/2569] lr: 4.0000e-02 eta: 16:31:31 time: 0.2644 data_time: 0.0079 memory: 5828 grad_norm: 3.0351 loss: 2.4191 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4191 2023/06/05 04:23:40 - mmengine - INFO - Epoch(train) [63][2360/2569] lr: 4.0000e-02 eta: 16:31:25 time: 0.2580 data_time: 0.0068 memory: 5828 grad_norm: 3.1483 loss: 3.0160 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0160 2023/06/05 04:23:45 - mmengine - INFO - Epoch(train) [63][2380/2569] lr: 4.0000e-02 eta: 16:31:19 time: 0.2573 data_time: 0.0072 memory: 5828 grad_norm: 3.0558 loss: 2.7687 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7687 2023/06/05 04:23:51 - mmengine - INFO - Epoch(train) [63][2400/2569] lr: 4.0000e-02 eta: 16:31:14 time: 0.2691 data_time: 0.0074 memory: 5828 grad_norm: 3.1019 loss: 2.6030 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6030 2023/06/05 04:23:56 - mmengine - INFO - Epoch(train) [63][2420/2569] lr: 4.0000e-02 eta: 16:31:09 time: 0.2641 data_time: 0.0077 memory: 5828 grad_norm: 3.1250 loss: 2.2541 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2541 2023/06/05 04:24:01 - mmengine - INFO - Epoch(train) [63][2440/2569] lr: 4.0000e-02 eta: 16:31:03 time: 0.2582 data_time: 0.0079 memory: 5828 grad_norm: 3.1033 loss: 2.5227 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5227 2023/06/05 04:24:06 - mmengine - INFO - Epoch(train) [63][2460/2569] lr: 4.0000e-02 eta: 16:30:58 time: 0.2571 data_time: 0.0077 memory: 5828 grad_norm: 3.0996 loss: 2.6368 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6368 2023/06/05 04:24:11 - mmengine - INFO - Epoch(train) [63][2480/2569] lr: 4.0000e-02 eta: 16:30:52 time: 0.2593 data_time: 0.0072 memory: 5828 grad_norm: 3.1025 loss: 3.1023 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.1023 2023/06/05 04:24:17 - mmengine - INFO - Epoch(train) [63][2500/2569] lr: 4.0000e-02 eta: 16:30:47 time: 0.2652 data_time: 0.0069 memory: 5828 grad_norm: 3.2487 loss: 2.7432 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7432 2023/06/05 04:24:22 - mmengine - INFO - Epoch(train) [63][2520/2569] lr: 4.0000e-02 eta: 16:30:42 time: 0.2666 data_time: 0.0072 memory: 5828 grad_norm: 3.0807 loss: 2.2763 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2763 2023/06/05 04:24:27 - mmengine - INFO - Epoch(train) [63][2540/2569] lr: 4.0000e-02 eta: 16:30:36 time: 0.2689 data_time: 0.0070 memory: 5828 grad_norm: 3.0966 loss: 2.7702 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7702 2023/06/05 04:24:33 - mmengine - INFO - Epoch(train) [63][2560/2569] lr: 4.0000e-02 eta: 16:30:31 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 3.1140 loss: 2.4397 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4397 2023/06/05 04:24:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:24:35 - mmengine - INFO - Epoch(train) [63][2569/2569] lr: 4.0000e-02 eta: 16:30:29 time: 0.2648 data_time: 0.0070 memory: 5828 grad_norm: 3.1014 loss: 2.3847 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.3847 2023/06/05 04:24:42 - mmengine - INFO - Epoch(train) [64][ 20/2569] lr: 4.0000e-02 eta: 16:30:25 time: 0.3400 data_time: 0.0578 memory: 5828 grad_norm: 3.1143 loss: 2.7504 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7504 2023/06/05 04:24:47 - mmengine - INFO - Epoch(train) [64][ 40/2569] lr: 4.0000e-02 eta: 16:30:20 time: 0.2747 data_time: 0.0083 memory: 5828 grad_norm: 3.1351 loss: 2.5646 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5646 2023/06/05 04:24:53 - mmengine - INFO - Epoch(train) [64][ 60/2569] lr: 4.0000e-02 eta: 16:30:15 time: 0.2740 data_time: 0.0073 memory: 5828 grad_norm: 3.1070 loss: 2.7799 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7799 2023/06/05 04:24:58 - mmengine - INFO - Epoch(train) [64][ 80/2569] lr: 4.0000e-02 eta: 16:30:10 time: 0.2653 data_time: 0.0078 memory: 5828 grad_norm: 3.1523 loss: 2.5262 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5262 2023/06/05 04:25:04 - mmengine - INFO - Epoch(train) [64][ 100/2569] lr: 4.0000e-02 eta: 16:30:05 time: 0.2740 data_time: 0.0087 memory: 5828 grad_norm: 3.1156 loss: 2.7648 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7648 2023/06/05 04:25:09 - mmengine - INFO - Epoch(train) [64][ 120/2569] lr: 4.0000e-02 eta: 16:30:00 time: 0.2767 data_time: 0.0072 memory: 5828 grad_norm: 3.1333 loss: 2.5458 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5458 2023/06/05 04:25:15 - mmengine - INFO - Epoch(train) [64][ 140/2569] lr: 4.0000e-02 eta: 16:29:54 time: 0.2647 data_time: 0.0079 memory: 5828 grad_norm: 3.1359 loss: 2.3455 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3455 2023/06/05 04:25:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:25:20 - mmengine - INFO - Epoch(train) [64][ 160/2569] lr: 4.0000e-02 eta: 16:29:49 time: 0.2738 data_time: 0.0081 memory: 5828 grad_norm: 3.2163 loss: 2.3386 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3386 2023/06/05 04:25:25 - mmengine - INFO - Epoch(train) [64][ 180/2569] lr: 4.0000e-02 eta: 16:29:44 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 3.1272 loss: 2.7026 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7026 2023/06/05 04:25:31 - mmengine - INFO - Epoch(train) [64][ 200/2569] lr: 4.0000e-02 eta: 16:29:39 time: 0.2707 data_time: 0.0077 memory: 5828 grad_norm: 3.0936 loss: 2.5067 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5067 2023/06/05 04:25:36 - mmengine - INFO - Epoch(train) [64][ 220/2569] lr: 4.0000e-02 eta: 16:29:33 time: 0.2655 data_time: 0.0071 memory: 5828 grad_norm: 3.1657 loss: 2.7090 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7090 2023/06/05 04:25:41 - mmengine - INFO - Epoch(train) [64][ 240/2569] lr: 4.0000e-02 eta: 16:29:28 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 3.0909 loss: 2.5073 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5073 2023/06/05 04:25:47 - mmengine - INFO - Epoch(train) [64][ 260/2569] lr: 4.0000e-02 eta: 16:29:23 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.1151 loss: 2.4394 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4394 2023/06/05 04:25:52 - mmengine - INFO - Epoch(train) [64][ 280/2569] lr: 4.0000e-02 eta: 16:29:18 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 3.0834 loss: 2.4233 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4233 2023/06/05 04:25:57 - mmengine - INFO - Epoch(train) [64][ 300/2569] lr: 4.0000e-02 eta: 16:29:12 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.1417 loss: 2.0727 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0727 2023/06/05 04:26:03 - mmengine - INFO - Epoch(train) [64][ 320/2569] lr: 4.0000e-02 eta: 16:29:07 time: 0.2722 data_time: 0.0078 memory: 5828 grad_norm: 3.0958 loss: 2.5693 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5693 2023/06/05 04:26:08 - mmengine - INFO - Epoch(train) [64][ 340/2569] lr: 4.0000e-02 eta: 16:29:02 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.1986 loss: 2.4000 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4000 2023/06/05 04:26:13 - mmengine - INFO - Epoch(train) [64][ 360/2569] lr: 4.0000e-02 eta: 16:28:56 time: 0.2586 data_time: 0.0079 memory: 5828 grad_norm: 3.1496 loss: 2.7437 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7437 2023/06/05 04:26:19 - mmengine - INFO - Epoch(train) [64][ 380/2569] lr: 4.0000e-02 eta: 16:28:51 time: 0.2626 data_time: 0.0070 memory: 5828 grad_norm: 3.0915 loss: 2.4790 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4790 2023/06/05 04:26:24 - mmengine - INFO - Epoch(train) [64][ 400/2569] lr: 4.0000e-02 eta: 16:28:45 time: 0.2606 data_time: 0.0071 memory: 5828 grad_norm: 3.1805 loss: 2.5871 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5871 2023/06/05 04:26:29 - mmengine - INFO - Epoch(train) [64][ 420/2569] lr: 4.0000e-02 eta: 16:28:40 time: 0.2720 data_time: 0.0077 memory: 5828 grad_norm: 3.1230 loss: 2.8506 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8506 2023/06/05 04:26:34 - mmengine - INFO - Epoch(train) [64][ 440/2569] lr: 4.0000e-02 eta: 16:28:35 time: 0.2623 data_time: 0.0074 memory: 5828 grad_norm: 3.0504 loss: 2.3987 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3987 2023/06/05 04:26:40 - mmengine - INFO - Epoch(train) [64][ 460/2569] lr: 4.0000e-02 eta: 16:28:30 time: 0.2696 data_time: 0.0077 memory: 5828 grad_norm: 3.1265 loss: 2.9176 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9176 2023/06/05 04:26:45 - mmengine - INFO - Epoch(train) [64][ 480/2569] lr: 4.0000e-02 eta: 16:28:24 time: 0.2601 data_time: 0.0074 memory: 5828 grad_norm: 3.1081 loss: 2.6380 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6380 2023/06/05 04:26:50 - mmengine - INFO - Epoch(train) [64][ 500/2569] lr: 4.0000e-02 eta: 16:28:19 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 3.1159 loss: 2.6332 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6332 2023/06/05 04:26:55 - mmengine - INFO - Epoch(train) [64][ 520/2569] lr: 4.0000e-02 eta: 16:28:13 time: 0.2576 data_time: 0.0073 memory: 5828 grad_norm: 3.1344 loss: 2.6792 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6792 2023/06/05 04:27:01 - mmengine - INFO - Epoch(train) [64][ 540/2569] lr: 4.0000e-02 eta: 16:28:08 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.0955 loss: 2.6662 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6662 2023/06/05 04:27:06 - mmengine - INFO - Epoch(train) [64][ 560/2569] lr: 4.0000e-02 eta: 16:28:02 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 3.0697 loss: 2.5291 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5291 2023/06/05 04:27:11 - mmengine - INFO - Epoch(train) [64][ 580/2569] lr: 4.0000e-02 eta: 16:27:57 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.0502 loss: 2.1589 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1589 2023/06/05 04:27:17 - mmengine - INFO - Epoch(train) [64][ 600/2569] lr: 4.0000e-02 eta: 16:27:52 time: 0.2764 data_time: 0.0068 memory: 5828 grad_norm: 3.1386 loss: 2.3950 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3950 2023/06/05 04:27:22 - mmengine - INFO - Epoch(train) [64][ 620/2569] lr: 4.0000e-02 eta: 16:27:47 time: 0.2704 data_time: 0.0072 memory: 5828 grad_norm: 3.1939 loss: 2.7211 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7211 2023/06/05 04:27:28 - mmengine - INFO - Epoch(train) [64][ 640/2569] lr: 4.0000e-02 eta: 16:27:41 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 3.1060 loss: 2.7431 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7431 2023/06/05 04:27:33 - mmengine - INFO - Epoch(train) [64][ 660/2569] lr: 4.0000e-02 eta: 16:27:36 time: 0.2611 data_time: 0.0072 memory: 5828 grad_norm: 3.1578 loss: 2.5889 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5889 2023/06/05 04:27:38 - mmengine - INFO - Epoch(train) [64][ 680/2569] lr: 4.0000e-02 eta: 16:27:30 time: 0.2588 data_time: 0.0069 memory: 5828 grad_norm: 3.0851 loss: 2.4631 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4631 2023/06/05 04:27:43 - mmengine - INFO - Epoch(train) [64][ 700/2569] lr: 4.0000e-02 eta: 16:27:25 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 3.1225 loss: 2.3474 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3474 2023/06/05 04:27:49 - mmengine - INFO - Epoch(train) [64][ 720/2569] lr: 4.0000e-02 eta: 16:27:20 time: 0.2587 data_time: 0.0074 memory: 5828 grad_norm: 3.1438 loss: 2.4296 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4296 2023/06/05 04:27:54 - mmengine - INFO - Epoch(train) [64][ 740/2569] lr: 4.0000e-02 eta: 16:27:14 time: 0.2635 data_time: 0.0072 memory: 5828 grad_norm: 3.1270 loss: 2.7686 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7686 2023/06/05 04:27:59 - mmengine - INFO - Epoch(train) [64][ 760/2569] lr: 4.0000e-02 eta: 16:27:09 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 3.1600 loss: 2.1628 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1628 2023/06/05 04:28:04 - mmengine - INFO - Epoch(train) [64][ 780/2569] lr: 4.0000e-02 eta: 16:27:04 time: 0.2673 data_time: 0.0080 memory: 5828 grad_norm: 3.1660 loss: 2.4648 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4648 2023/06/05 04:28:10 - mmengine - INFO - Epoch(train) [64][ 800/2569] lr: 4.0000e-02 eta: 16:26:58 time: 0.2599 data_time: 0.0074 memory: 5828 grad_norm: 3.1233 loss: 2.3121 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3121 2023/06/05 04:28:15 - mmengine - INFO - Epoch(train) [64][ 820/2569] lr: 4.0000e-02 eta: 16:26:53 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 3.1229 loss: 2.4505 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4505 2023/06/05 04:28:20 - mmengine - INFO - Epoch(train) [64][ 840/2569] lr: 4.0000e-02 eta: 16:26:47 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 3.1113 loss: 2.4542 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4542 2023/06/05 04:28:26 - mmengine - INFO - Epoch(train) [64][ 860/2569] lr: 4.0000e-02 eta: 16:26:42 time: 0.2704 data_time: 0.0072 memory: 5828 grad_norm: 3.1593 loss: 2.5537 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5537 2023/06/05 04:28:31 - mmengine - INFO - Epoch(train) [64][ 880/2569] lr: 4.0000e-02 eta: 16:26:37 time: 0.2630 data_time: 0.0073 memory: 5828 grad_norm: 3.1129 loss: 2.8134 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8134 2023/06/05 04:28:36 - mmengine - INFO - Epoch(train) [64][ 900/2569] lr: 4.0000e-02 eta: 16:26:31 time: 0.2649 data_time: 0.0078 memory: 5828 grad_norm: 3.1472 loss: 2.6522 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6522 2023/06/05 04:28:41 - mmengine - INFO - Epoch(train) [64][ 920/2569] lr: 4.0000e-02 eta: 16:26:26 time: 0.2613 data_time: 0.0071 memory: 5828 grad_norm: 3.1196 loss: 2.8380 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8380 2023/06/05 04:28:47 - mmengine - INFO - Epoch(train) [64][ 940/2569] lr: 4.0000e-02 eta: 16:26:21 time: 0.2600 data_time: 0.0071 memory: 5828 grad_norm: 3.1114 loss: 2.4384 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4384 2023/06/05 04:28:52 - mmengine - INFO - Epoch(train) [64][ 960/2569] lr: 4.0000e-02 eta: 16:26:15 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 3.1318 loss: 2.4269 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4269 2023/06/05 04:28:57 - mmengine - INFO - Epoch(train) [64][ 980/2569] lr: 4.0000e-02 eta: 16:26:10 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 3.1584 loss: 2.5666 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5666 2023/06/05 04:29:02 - mmengine - INFO - Epoch(train) [64][1000/2569] lr: 4.0000e-02 eta: 16:26:04 time: 0.2593 data_time: 0.0069 memory: 5828 grad_norm: 3.0496 loss: 2.6422 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6422 2023/06/05 04:29:08 - mmengine - INFO - Epoch(train) [64][1020/2569] lr: 4.0000e-02 eta: 16:25:59 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 3.1448 loss: 2.3714 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3714 2023/06/05 04:29:13 - mmengine - INFO - Epoch(train) [64][1040/2569] lr: 4.0000e-02 eta: 16:25:53 time: 0.2683 data_time: 0.0071 memory: 5828 grad_norm: 3.0534 loss: 2.4814 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4814 2023/06/05 04:29:18 - mmengine - INFO - Epoch(train) [64][1060/2569] lr: 4.0000e-02 eta: 16:25:48 time: 0.2603 data_time: 0.0074 memory: 5828 grad_norm: 3.1564 loss: 2.8980 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8980 2023/06/05 04:29:23 - mmengine - INFO - Epoch(train) [64][1080/2569] lr: 4.0000e-02 eta: 16:25:43 time: 0.2653 data_time: 0.0073 memory: 5828 grad_norm: 3.1505 loss: 2.4002 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4002 2023/06/05 04:29:29 - mmengine - INFO - Epoch(train) [64][1100/2569] lr: 4.0000e-02 eta: 16:25:37 time: 0.2600 data_time: 0.0074 memory: 5828 grad_norm: 3.1633 loss: 2.6787 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6787 2023/06/05 04:29:34 - mmengine - INFO - Epoch(train) [64][1120/2569] lr: 4.0000e-02 eta: 16:25:32 time: 0.2752 data_time: 0.0076 memory: 5828 grad_norm: 3.1518 loss: 2.3093 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3093 2023/06/05 04:29:39 - mmengine - INFO - Epoch(train) [64][1140/2569] lr: 4.0000e-02 eta: 16:25:27 time: 0.2583 data_time: 0.0072 memory: 5828 grad_norm: 3.0863 loss: 2.5482 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5482 2023/06/05 04:29:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:29:45 - mmengine - INFO - Epoch(train) [64][1160/2569] lr: 4.0000e-02 eta: 16:25:21 time: 0.2643 data_time: 0.0076 memory: 5828 grad_norm: 3.1483 loss: 2.6366 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6366 2023/06/05 04:29:50 - mmengine - INFO - Epoch(train) [64][1180/2569] lr: 4.0000e-02 eta: 16:25:16 time: 0.2585 data_time: 0.0078 memory: 5828 grad_norm: 3.0519 loss: 2.3688 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3688 2023/06/05 04:29:55 - mmengine - INFO - Epoch(train) [64][1200/2569] lr: 4.0000e-02 eta: 16:25:10 time: 0.2589 data_time: 0.0074 memory: 5828 grad_norm: 3.1152 loss: 2.6545 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6545 2023/06/05 04:30:00 - mmengine - INFO - Epoch(train) [64][1220/2569] lr: 4.0000e-02 eta: 16:25:05 time: 0.2585 data_time: 0.0071 memory: 5828 grad_norm: 3.1181 loss: 2.4605 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4605 2023/06/05 04:30:06 - mmengine - INFO - Epoch(train) [64][1240/2569] lr: 4.0000e-02 eta: 16:24:59 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 3.1584 loss: 2.3635 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3635 2023/06/05 04:30:11 - mmengine - INFO - Epoch(train) [64][1260/2569] lr: 4.0000e-02 eta: 16:24:54 time: 0.2581 data_time: 0.0074 memory: 5828 grad_norm: 3.0534 loss: 2.5822 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5822 2023/06/05 04:30:16 - mmengine - INFO - Epoch(train) [64][1280/2569] lr: 4.0000e-02 eta: 16:24:48 time: 0.2599 data_time: 0.0072 memory: 5828 grad_norm: 3.1435 loss: 2.6352 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6352 2023/06/05 04:30:21 - mmengine - INFO - Epoch(train) [64][1300/2569] lr: 4.0000e-02 eta: 16:24:43 time: 0.2605 data_time: 0.0071 memory: 5828 grad_norm: 3.1320 loss: 2.1954 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1954 2023/06/05 04:30:26 - mmengine - INFO - Epoch(train) [64][1320/2569] lr: 4.0000e-02 eta: 16:24:38 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 3.0529 loss: 2.7407 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7407 2023/06/05 04:30:32 - mmengine - INFO - Epoch(train) [64][1340/2569] lr: 4.0000e-02 eta: 16:24:32 time: 0.2646 data_time: 0.0071 memory: 5828 grad_norm: 3.1602 loss: 2.4991 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4991 2023/06/05 04:30:37 - mmengine - INFO - Epoch(train) [64][1360/2569] lr: 4.0000e-02 eta: 16:24:27 time: 0.2598 data_time: 0.0076 memory: 5828 grad_norm: 3.0907 loss: 2.6053 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6053 2023/06/05 04:30:42 - mmengine - INFO - Epoch(train) [64][1380/2569] lr: 4.0000e-02 eta: 16:24:22 time: 0.2719 data_time: 0.0073 memory: 5828 grad_norm: 3.0845 loss: 2.9025 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 2.9025 2023/06/05 04:30:48 - mmengine - INFO - Epoch(train) [64][1400/2569] lr: 4.0000e-02 eta: 16:24:16 time: 0.2633 data_time: 0.0071 memory: 5828 grad_norm: 3.0889 loss: 2.3432 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3432 2023/06/05 04:30:53 - mmengine - INFO - Epoch(train) [64][1420/2569] lr: 4.0000e-02 eta: 16:24:11 time: 0.2720 data_time: 0.0075 memory: 5828 grad_norm: 3.1118 loss: 2.7065 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.7065 2023/06/05 04:30:58 - mmengine - INFO - Epoch(train) [64][1440/2569] lr: 4.0000e-02 eta: 16:24:06 time: 0.2666 data_time: 0.0072 memory: 5828 grad_norm: 3.0613 loss: 2.7058 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7058 2023/06/05 04:31:04 - mmengine - INFO - Epoch(train) [64][1460/2569] lr: 4.0000e-02 eta: 16:24:01 time: 0.2710 data_time: 0.0075 memory: 5828 grad_norm: 3.3103 loss: 2.4211 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4211 2023/06/05 04:31:09 - mmengine - INFO - Epoch(train) [64][1480/2569] lr: 4.0000e-02 eta: 16:23:55 time: 0.2664 data_time: 0.0075 memory: 5828 grad_norm: 3.1395 loss: 2.3678 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3678 2023/06/05 04:31:14 - mmengine - INFO - Epoch(train) [64][1500/2569] lr: 4.0000e-02 eta: 16:23:50 time: 0.2613 data_time: 0.0072 memory: 5828 grad_norm: 3.1536 loss: 2.4005 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4005 2023/06/05 04:31:20 - mmengine - INFO - Epoch(train) [64][1520/2569] lr: 4.0000e-02 eta: 16:23:44 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 3.1277 loss: 2.3090 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3090 2023/06/05 04:31:25 - mmengine - INFO - Epoch(train) [64][1540/2569] lr: 4.0000e-02 eta: 16:23:39 time: 0.2574 data_time: 0.0070 memory: 5828 grad_norm: 3.1620 loss: 2.5364 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5364 2023/06/05 04:31:30 - mmengine - INFO - Epoch(train) [64][1560/2569] lr: 4.0000e-02 eta: 16:23:34 time: 0.2647 data_time: 0.0071 memory: 5828 grad_norm: 3.1910 loss: 2.2690 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2690 2023/06/05 04:31:35 - mmengine - INFO - Epoch(train) [64][1580/2569] lr: 4.0000e-02 eta: 16:23:28 time: 0.2658 data_time: 0.0070 memory: 5828 grad_norm: 3.1137 loss: 2.1543 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 2.1543 2023/06/05 04:31:41 - mmengine - INFO - Epoch(train) [64][1600/2569] lr: 4.0000e-02 eta: 16:23:23 time: 0.2586 data_time: 0.0072 memory: 5828 grad_norm: 3.1216 loss: 2.7887 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7887 2023/06/05 04:31:46 - mmengine - INFO - Epoch(train) [64][1620/2569] lr: 4.0000e-02 eta: 16:23:17 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 3.1027 loss: 2.5076 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5076 2023/06/05 04:31:51 - mmengine - INFO - Epoch(train) [64][1640/2569] lr: 4.0000e-02 eta: 16:23:12 time: 0.2588 data_time: 0.0077 memory: 5828 grad_norm: 3.1800 loss: 2.5523 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5523 2023/06/05 04:31:56 - mmengine - INFO - Epoch(train) [64][1660/2569] lr: 4.0000e-02 eta: 16:23:06 time: 0.2634 data_time: 0.0076 memory: 5828 grad_norm: 3.1095 loss: 2.6196 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6196 2023/06/05 04:32:02 - mmengine - INFO - Epoch(train) [64][1680/2569] lr: 4.0000e-02 eta: 16:23:01 time: 0.2614 data_time: 0.0071 memory: 5828 grad_norm: 3.1682 loss: 2.4997 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4997 2023/06/05 04:32:07 - mmengine - INFO - Epoch(train) [64][1700/2569] lr: 4.0000e-02 eta: 16:22:55 time: 0.2610 data_time: 0.0076 memory: 5828 grad_norm: 3.1594 loss: 2.5634 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5634 2023/06/05 04:32:12 - mmengine - INFO - Epoch(train) [64][1720/2569] lr: 4.0000e-02 eta: 16:22:50 time: 0.2643 data_time: 0.0077 memory: 5828 grad_norm: 3.1070 loss: 2.4694 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4694 2023/06/05 04:32:17 - mmengine - INFO - Epoch(train) [64][1740/2569] lr: 4.0000e-02 eta: 16:22:45 time: 0.2585 data_time: 0.0075 memory: 5828 grad_norm: 3.0678 loss: 2.7053 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7053 2023/06/05 04:32:23 - mmengine - INFO - Epoch(train) [64][1760/2569] lr: 4.0000e-02 eta: 16:22:39 time: 0.2634 data_time: 0.0071 memory: 5828 grad_norm: 3.1179 loss: 2.6203 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6203 2023/06/05 04:32:28 - mmengine - INFO - Epoch(train) [64][1780/2569] lr: 4.0000e-02 eta: 16:22:34 time: 0.2572 data_time: 0.0072 memory: 5828 grad_norm: 3.0913 loss: 2.3882 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3882 2023/06/05 04:32:33 - mmengine - INFO - Epoch(train) [64][1800/2569] lr: 4.0000e-02 eta: 16:22:28 time: 0.2639 data_time: 0.0072 memory: 5828 grad_norm: 3.1685 loss: 2.1936 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1936 2023/06/05 04:32:38 - mmengine - INFO - Epoch(train) [64][1820/2569] lr: 4.0000e-02 eta: 16:22:23 time: 0.2733 data_time: 0.0074 memory: 5828 grad_norm: 3.1072 loss: 2.4024 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4024 2023/06/05 04:32:44 - mmengine - INFO - Epoch(train) [64][1840/2569] lr: 4.0000e-02 eta: 16:22:18 time: 0.2585 data_time: 0.0073 memory: 5828 grad_norm: 3.1211 loss: 2.6010 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6010 2023/06/05 04:32:49 - mmengine - INFO - Epoch(train) [64][1860/2569] lr: 4.0000e-02 eta: 16:22:12 time: 0.2695 data_time: 0.0073 memory: 5828 grad_norm: 3.0800 loss: 2.4429 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4429 2023/06/05 04:32:54 - mmengine - INFO - Epoch(train) [64][1880/2569] lr: 4.0000e-02 eta: 16:22:07 time: 0.2650 data_time: 0.0073 memory: 5828 grad_norm: 3.0935 loss: 2.6274 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6274 2023/06/05 04:33:00 - mmengine - INFO - Epoch(train) [64][1900/2569] lr: 4.0000e-02 eta: 16:22:02 time: 0.2609 data_time: 0.0071 memory: 5828 grad_norm: 3.0764 loss: 2.7501 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7501 2023/06/05 04:33:05 - mmengine - INFO - Epoch(train) [64][1920/2569] lr: 4.0000e-02 eta: 16:21:56 time: 0.2660 data_time: 0.0083 memory: 5828 grad_norm: 3.1236 loss: 2.8321 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8321 2023/06/05 04:33:10 - mmengine - INFO - Epoch(train) [64][1940/2569] lr: 4.0000e-02 eta: 16:21:51 time: 0.2643 data_time: 0.0069 memory: 5828 grad_norm: 3.0885 loss: 2.8351 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8351 2023/06/05 04:33:15 - mmengine - INFO - Epoch(train) [64][1960/2569] lr: 4.0000e-02 eta: 16:21:45 time: 0.2594 data_time: 0.0077 memory: 5828 grad_norm: 3.0898 loss: 2.5234 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5234 2023/06/05 04:33:21 - mmengine - INFO - Epoch(train) [64][1980/2569] lr: 4.0000e-02 eta: 16:21:40 time: 0.2761 data_time: 0.0074 memory: 5828 grad_norm: 3.0931 loss: 3.0234 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0234 2023/06/05 04:33:26 - mmengine - INFO - Epoch(train) [64][2000/2569] lr: 4.0000e-02 eta: 16:21:35 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 3.1107 loss: 2.6641 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6641 2023/06/05 04:33:31 - mmengine - INFO - Epoch(train) [64][2020/2569] lr: 4.0000e-02 eta: 16:21:30 time: 0.2624 data_time: 0.0070 memory: 5828 grad_norm: 3.1233 loss: 2.1705 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1705 2023/06/05 04:33:37 - mmengine - INFO - Epoch(train) [64][2040/2569] lr: 4.0000e-02 eta: 16:21:24 time: 0.2626 data_time: 0.0073 memory: 5828 grad_norm: 3.0618 loss: 2.4724 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4724 2023/06/05 04:33:42 - mmengine - INFO - Epoch(train) [64][2060/2569] lr: 4.0000e-02 eta: 16:21:19 time: 0.2597 data_time: 0.0077 memory: 5828 grad_norm: 3.1388 loss: 2.6024 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6024 2023/06/05 04:33:47 - mmengine - INFO - Epoch(train) [64][2080/2569] lr: 4.0000e-02 eta: 16:21:13 time: 0.2576 data_time: 0.0075 memory: 5828 grad_norm: 3.0834 loss: 2.5705 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5705 2023/06/05 04:33:53 - mmengine - INFO - Epoch(train) [64][2100/2569] lr: 4.0000e-02 eta: 16:21:08 time: 0.2710 data_time: 0.0071 memory: 5828 grad_norm: 3.0205 loss: 2.5164 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5164 2023/06/05 04:33:58 - mmengine - INFO - Epoch(train) [64][2120/2569] lr: 4.0000e-02 eta: 16:21:03 time: 0.2701 data_time: 0.0073 memory: 5828 grad_norm: 3.0931 loss: 2.8387 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8387 2023/06/05 04:34:03 - mmengine - INFO - Epoch(train) [64][2140/2569] lr: 4.0000e-02 eta: 16:20:57 time: 0.2618 data_time: 0.0069 memory: 5828 grad_norm: 3.1098 loss: 2.8283 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8283 2023/06/05 04:34:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:34:09 - mmengine - INFO - Epoch(train) [64][2160/2569] lr: 4.0000e-02 eta: 16:20:52 time: 0.2745 data_time: 0.0074 memory: 5828 grad_norm: 3.1812 loss: 2.4885 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4885 2023/06/05 04:34:14 - mmengine - INFO - Epoch(train) [64][2180/2569] lr: 4.0000e-02 eta: 16:20:47 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 3.0412 loss: 2.5251 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5251 2023/06/05 04:34:19 - mmengine - INFO - Epoch(train) [64][2200/2569] lr: 4.0000e-02 eta: 16:20:42 time: 0.2727 data_time: 0.0072 memory: 5828 grad_norm: 3.0648 loss: 3.0128 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0128 2023/06/05 04:34:25 - mmengine - INFO - Epoch(train) [64][2220/2569] lr: 4.0000e-02 eta: 16:20:37 time: 0.2640 data_time: 0.0076 memory: 5828 grad_norm: 3.1793 loss: 2.8006 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.8006 2023/06/05 04:34:30 - mmengine - INFO - Epoch(train) [64][2240/2569] lr: 4.0000e-02 eta: 16:20:31 time: 0.2734 data_time: 0.0074 memory: 5828 grad_norm: 3.0937 loss: 2.6878 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6878 2023/06/05 04:34:36 - mmengine - INFO - Epoch(train) [64][2260/2569] lr: 4.0000e-02 eta: 16:20:26 time: 0.2696 data_time: 0.0073 memory: 5828 grad_norm: 3.1343 loss: 2.2440 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2440 2023/06/05 04:34:41 - mmengine - INFO - Epoch(train) [64][2280/2569] lr: 4.0000e-02 eta: 16:20:21 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 3.1039 loss: 2.3360 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3360 2023/06/05 04:34:46 - mmengine - INFO - Epoch(train) [64][2300/2569] lr: 4.0000e-02 eta: 16:20:16 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 3.1621 loss: 2.6508 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6508 2023/06/05 04:34:51 - mmengine - INFO - Epoch(train) [64][2320/2569] lr: 4.0000e-02 eta: 16:20:10 time: 0.2637 data_time: 0.0072 memory: 5828 grad_norm: 3.1941 loss: 2.6147 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6147 2023/06/05 04:34:57 - mmengine - INFO - Epoch(train) [64][2340/2569] lr: 4.0000e-02 eta: 16:20:05 time: 0.2721 data_time: 0.0073 memory: 5828 grad_norm: 3.0682 loss: 2.3872 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3872 2023/06/05 04:35:02 - mmengine - INFO - Epoch(train) [64][2360/2569] lr: 4.0000e-02 eta: 16:20:00 time: 0.2637 data_time: 0.0074 memory: 5828 grad_norm: 3.0968 loss: 2.6463 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6463 2023/06/05 04:35:08 - mmengine - INFO - Epoch(train) [64][2380/2569] lr: 4.0000e-02 eta: 16:19:54 time: 0.2707 data_time: 0.0072 memory: 5828 grad_norm: 3.1354 loss: 2.5659 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5659 2023/06/05 04:35:13 - mmengine - INFO - Epoch(train) [64][2400/2569] lr: 4.0000e-02 eta: 16:19:49 time: 0.2749 data_time: 0.0071 memory: 5828 grad_norm: 3.0593 loss: 2.4913 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4913 2023/06/05 04:35:18 - mmengine - INFO - Epoch(train) [64][2420/2569] lr: 4.0000e-02 eta: 16:19:44 time: 0.2593 data_time: 0.0073 memory: 5828 grad_norm: 3.0991 loss: 2.5268 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5268 2023/06/05 04:35:24 - mmengine - INFO - Epoch(train) [64][2440/2569] lr: 4.0000e-02 eta: 16:19:39 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 3.1724 loss: 2.4901 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4901 2023/06/05 04:35:29 - mmengine - INFO - Epoch(train) [64][2460/2569] lr: 4.0000e-02 eta: 16:19:33 time: 0.2583 data_time: 0.0075 memory: 5828 grad_norm: 3.1489 loss: 2.6855 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6855 2023/06/05 04:35:34 - mmengine - INFO - Epoch(train) [64][2480/2569] lr: 4.0000e-02 eta: 16:19:28 time: 0.2793 data_time: 0.0075 memory: 5828 grad_norm: 3.1349 loss: 2.2568 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2568 2023/06/05 04:35:40 - mmengine - INFO - Epoch(train) [64][2500/2569] lr: 4.0000e-02 eta: 16:19:23 time: 0.2634 data_time: 0.0077 memory: 5828 grad_norm: 3.1018 loss: 2.5810 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5810 2023/06/05 04:35:45 - mmengine - INFO - Epoch(train) [64][2520/2569] lr: 4.0000e-02 eta: 16:19:17 time: 0.2641 data_time: 0.0076 memory: 5828 grad_norm: 3.1446 loss: 2.7511 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7511 2023/06/05 04:35:50 - mmengine - INFO - Epoch(train) [64][2540/2569] lr: 4.0000e-02 eta: 16:19:12 time: 0.2572 data_time: 0.0080 memory: 5828 grad_norm: 3.1019 loss: 2.6090 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6090 2023/06/05 04:35:55 - mmengine - INFO - Epoch(train) [64][2560/2569] lr: 4.0000e-02 eta: 16:19:06 time: 0.2666 data_time: 0.0078 memory: 5828 grad_norm: 3.1070 loss: 2.7246 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.7246 2023/06/05 04:35:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:35:58 - mmengine - INFO - Epoch(train) [64][2569/2569] lr: 4.0000e-02 eta: 16:19:04 time: 0.2612 data_time: 0.0070 memory: 5828 grad_norm: 3.1182 loss: 2.8140 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.8140 2023/06/05 04:35:58 - mmengine - INFO - Saving checkpoint at 64 epochs 2023/06/05 04:36:06 - mmengine - INFO - Epoch(train) [65][ 20/2569] lr: 4.0000e-02 eta: 16:19:00 time: 0.3146 data_time: 0.0487 memory: 5828 grad_norm: 3.0958 loss: 2.5032 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5032 2023/06/05 04:36:11 - mmengine - INFO - Epoch(train) [65][ 40/2569] lr: 4.0000e-02 eta: 16:18:54 time: 0.2600 data_time: 0.0069 memory: 5828 grad_norm: 3.1177 loss: 2.7080 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7080 2023/06/05 04:36:16 - mmengine - INFO - Epoch(train) [65][ 60/2569] lr: 4.0000e-02 eta: 16:18:49 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 3.1446 loss: 2.6674 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6674 2023/06/05 04:36:22 - mmengine - INFO - Epoch(train) [65][ 80/2569] lr: 4.0000e-02 eta: 16:18:44 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 3.1235 loss: 2.4990 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4990 2023/06/05 04:36:27 - mmengine - INFO - Epoch(train) [65][ 100/2569] lr: 4.0000e-02 eta: 16:18:38 time: 0.2665 data_time: 0.0074 memory: 5828 grad_norm: 3.1052 loss: 2.3115 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3115 2023/06/05 04:36:32 - mmengine - INFO - Epoch(train) [65][ 120/2569] lr: 4.0000e-02 eta: 16:18:33 time: 0.2633 data_time: 0.0072 memory: 5828 grad_norm: 3.1631 loss: 2.5184 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5184 2023/06/05 04:36:38 - mmengine - INFO - Epoch(train) [65][ 140/2569] lr: 4.0000e-02 eta: 16:18:28 time: 0.2628 data_time: 0.0077 memory: 5828 grad_norm: 3.1458 loss: 2.7257 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7257 2023/06/05 04:36:43 - mmengine - INFO - Epoch(train) [65][ 160/2569] lr: 4.0000e-02 eta: 16:18:22 time: 0.2592 data_time: 0.0071 memory: 5828 grad_norm: 3.0926 loss: 2.1898 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1898 2023/06/05 04:36:48 - mmengine - INFO - Epoch(train) [65][ 180/2569] lr: 4.0000e-02 eta: 16:18:17 time: 0.2621 data_time: 0.0080 memory: 5828 grad_norm: 3.0844 loss: 2.6274 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6274 2023/06/05 04:36:53 - mmengine - INFO - Epoch(train) [65][ 200/2569] lr: 4.0000e-02 eta: 16:18:11 time: 0.2634 data_time: 0.0077 memory: 5828 grad_norm: 3.1509 loss: 2.6292 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6292 2023/06/05 04:36:58 - mmengine - INFO - Epoch(train) [65][ 220/2569] lr: 4.0000e-02 eta: 16:18:06 time: 0.2599 data_time: 0.0078 memory: 5828 grad_norm: 3.0794 loss: 2.6195 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6195 2023/06/05 04:37:04 - mmengine - INFO - Epoch(train) [65][ 240/2569] lr: 4.0000e-02 eta: 16:18:00 time: 0.2581 data_time: 0.0077 memory: 5828 grad_norm: 3.1701 loss: 2.4476 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4476 2023/06/05 04:37:09 - mmengine - INFO - Epoch(train) [65][ 260/2569] lr: 4.0000e-02 eta: 16:17:55 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 3.1814 loss: 2.7907 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7907 2023/06/05 04:37:14 - mmengine - INFO - Epoch(train) [65][ 280/2569] lr: 4.0000e-02 eta: 16:17:49 time: 0.2587 data_time: 0.0076 memory: 5828 grad_norm: 3.1249 loss: 2.6249 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6249 2023/06/05 04:37:19 - mmengine - INFO - Epoch(train) [65][ 300/2569] lr: 4.0000e-02 eta: 16:17:44 time: 0.2609 data_time: 0.0070 memory: 5828 grad_norm: 3.1282 loss: 2.4341 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4341 2023/06/05 04:37:25 - mmengine - INFO - Epoch(train) [65][ 320/2569] lr: 4.0000e-02 eta: 16:17:39 time: 0.2597 data_time: 0.0075 memory: 5828 grad_norm: 3.1095 loss: 2.9022 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.9022 2023/06/05 04:37:30 - mmengine - INFO - Epoch(train) [65][ 340/2569] lr: 4.0000e-02 eta: 16:17:33 time: 0.2597 data_time: 0.0079 memory: 5828 grad_norm: 3.1611 loss: 2.5746 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5746 2023/06/05 04:37:35 - mmengine - INFO - Epoch(train) [65][ 360/2569] lr: 4.0000e-02 eta: 16:17:28 time: 0.2725 data_time: 0.0077 memory: 5828 grad_norm: 3.0987 loss: 2.6183 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6183 2023/06/05 04:37:41 - mmengine - INFO - Epoch(train) [65][ 380/2569] lr: 4.0000e-02 eta: 16:17:23 time: 0.2639 data_time: 0.0072 memory: 5828 grad_norm: 3.1154 loss: 2.6106 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6106 2023/06/05 04:37:46 - mmengine - INFO - Epoch(train) [65][ 400/2569] lr: 4.0000e-02 eta: 16:17:17 time: 0.2649 data_time: 0.0073 memory: 5828 grad_norm: 3.1382 loss: 2.9016 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9016 2023/06/05 04:37:51 - mmengine - INFO - Epoch(train) [65][ 420/2569] lr: 4.0000e-02 eta: 16:17:12 time: 0.2758 data_time: 0.0075 memory: 5828 grad_norm: 3.0920 loss: 2.2377 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2377 2023/06/05 04:37:57 - mmengine - INFO - Epoch(train) [65][ 440/2569] lr: 4.0000e-02 eta: 16:17:07 time: 0.2583 data_time: 0.0075 memory: 5828 grad_norm: 3.1456 loss: 2.6045 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6045 2023/06/05 04:38:02 - mmengine - INFO - Epoch(train) [65][ 460/2569] lr: 4.0000e-02 eta: 16:17:01 time: 0.2635 data_time: 0.0072 memory: 5828 grad_norm: 3.1277 loss: 2.2093 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2093 2023/06/05 04:38:07 - mmengine - INFO - Epoch(train) [65][ 480/2569] lr: 4.0000e-02 eta: 16:16:56 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 3.1049 loss: 2.5561 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5561 2023/06/05 04:38:12 - mmengine - INFO - Epoch(train) [65][ 500/2569] lr: 4.0000e-02 eta: 16:16:51 time: 0.2645 data_time: 0.0082 memory: 5828 grad_norm: 3.1763 loss: 2.4730 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4730 2023/06/05 04:38:18 - mmengine - INFO - Epoch(train) [65][ 520/2569] lr: 4.0000e-02 eta: 16:16:45 time: 0.2631 data_time: 0.0071 memory: 5828 grad_norm: 3.1359 loss: 2.6111 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6111 2023/06/05 04:38:23 - mmengine - INFO - Epoch(train) [65][ 540/2569] lr: 4.0000e-02 eta: 16:16:40 time: 0.2586 data_time: 0.0073 memory: 5828 grad_norm: 3.1156 loss: 2.4242 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4242 2023/06/05 04:38:28 - mmengine - INFO - Epoch(train) [65][ 560/2569] lr: 4.0000e-02 eta: 16:16:34 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 2.9963 loss: 2.6629 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6629 2023/06/05 04:38:33 - mmengine - INFO - Epoch(train) [65][ 580/2569] lr: 4.0000e-02 eta: 16:16:29 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 3.2161 loss: 2.4952 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4952 2023/06/05 04:38:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:38:39 - mmengine - INFO - Epoch(train) [65][ 600/2569] lr: 4.0000e-02 eta: 16:16:23 time: 0.2593 data_time: 0.0076 memory: 5828 grad_norm: 3.1073 loss: 2.2695 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2695 2023/06/05 04:38:44 - mmengine - INFO - Epoch(train) [65][ 620/2569] lr: 4.0000e-02 eta: 16:16:18 time: 0.2791 data_time: 0.0071 memory: 5828 grad_norm: 3.0877 loss: 2.5261 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5261 2023/06/05 04:38:49 - mmengine - INFO - Epoch(train) [65][ 640/2569] lr: 4.0000e-02 eta: 16:16:13 time: 0.2662 data_time: 0.0073 memory: 5828 grad_norm: 3.0921 loss: 2.4393 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4393 2023/06/05 04:38:55 - mmengine - INFO - Epoch(train) [65][ 660/2569] lr: 4.0000e-02 eta: 16:16:08 time: 0.2749 data_time: 0.0074 memory: 5828 grad_norm: 3.1174 loss: 2.3741 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3741 2023/06/05 04:39:00 - mmengine - INFO - Epoch(train) [65][ 680/2569] lr: 4.0000e-02 eta: 16:16:03 time: 0.2744 data_time: 0.0079 memory: 5828 grad_norm: 3.1318 loss: 2.3700 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3700 2023/06/05 04:39:06 - mmengine - INFO - Epoch(train) [65][ 700/2569] lr: 4.0000e-02 eta: 16:15:58 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 3.1157 loss: 2.7779 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7779 2023/06/05 04:39:11 - mmengine - INFO - Epoch(train) [65][ 720/2569] lr: 4.0000e-02 eta: 16:15:52 time: 0.2641 data_time: 0.0077 memory: 5828 grad_norm: 3.1124 loss: 2.4607 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4607 2023/06/05 04:39:16 - mmengine - INFO - Epoch(train) [65][ 740/2569] lr: 4.0000e-02 eta: 16:15:47 time: 0.2603 data_time: 0.0070 memory: 5828 grad_norm: 3.1678 loss: 2.5534 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5534 2023/06/05 04:39:22 - mmengine - INFO - Epoch(train) [65][ 760/2569] lr: 4.0000e-02 eta: 16:15:41 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 3.1636 loss: 2.5361 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5361 2023/06/05 04:39:27 - mmengine - INFO - Epoch(train) [65][ 780/2569] lr: 4.0000e-02 eta: 16:15:36 time: 0.2662 data_time: 0.0070 memory: 5828 grad_norm: 3.1429 loss: 2.3547 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3547 2023/06/05 04:39:32 - mmengine - INFO - Epoch(train) [65][ 800/2569] lr: 4.0000e-02 eta: 16:15:31 time: 0.2583 data_time: 0.0074 memory: 5828 grad_norm: 3.2032 loss: 2.6652 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6652 2023/06/05 04:39:37 - mmengine - INFO - Epoch(train) [65][ 820/2569] lr: 4.0000e-02 eta: 16:15:25 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 3.1561 loss: 2.6147 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6147 2023/06/05 04:39:43 - mmengine - INFO - Epoch(train) [65][ 840/2569] lr: 4.0000e-02 eta: 16:15:20 time: 0.2646 data_time: 0.0076 memory: 5828 grad_norm: 3.1771 loss: 2.8458 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8458 2023/06/05 04:39:48 - mmengine - INFO - Epoch(train) [65][ 860/2569] lr: 4.0000e-02 eta: 16:15:14 time: 0.2644 data_time: 0.0080 memory: 5828 grad_norm: 3.1610 loss: 2.7311 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7311 2023/06/05 04:39:53 - mmengine - INFO - Epoch(train) [65][ 880/2569] lr: 4.0000e-02 eta: 16:15:09 time: 0.2625 data_time: 0.0077 memory: 5828 grad_norm: 3.1222 loss: 2.6045 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6045 2023/06/05 04:39:59 - mmengine - INFO - Epoch(train) [65][ 900/2569] lr: 4.0000e-02 eta: 16:15:04 time: 0.2660 data_time: 0.0084 memory: 5828 grad_norm: 3.1312 loss: 2.8732 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8732 2023/06/05 04:40:04 - mmengine - INFO - Epoch(train) [65][ 920/2569] lr: 4.0000e-02 eta: 16:14:58 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 3.0952 loss: 2.7274 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7274 2023/06/05 04:40:09 - mmengine - INFO - Epoch(train) [65][ 940/2569] lr: 4.0000e-02 eta: 16:14:53 time: 0.2692 data_time: 0.0074 memory: 5828 grad_norm: 3.1466 loss: 2.8441 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8441 2023/06/05 04:40:14 - mmengine - INFO - Epoch(train) [65][ 960/2569] lr: 4.0000e-02 eta: 16:14:48 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 3.1227 loss: 2.3817 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3817 2023/06/05 04:40:20 - mmengine - INFO - Epoch(train) [65][ 980/2569] lr: 4.0000e-02 eta: 16:14:42 time: 0.2587 data_time: 0.0076 memory: 5828 grad_norm: 3.1039 loss: 2.7359 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7359 2023/06/05 04:40:25 - mmengine - INFO - Epoch(train) [65][1000/2569] lr: 4.0000e-02 eta: 16:14:37 time: 0.2700 data_time: 0.0073 memory: 5828 grad_norm: 3.1831 loss: 2.7157 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7157 2023/06/05 04:40:30 - mmengine - INFO - Epoch(train) [65][1020/2569] lr: 4.0000e-02 eta: 16:14:32 time: 0.2635 data_time: 0.0071 memory: 5828 grad_norm: 3.1351 loss: 2.3346 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3346 2023/06/05 04:40:36 - mmengine - INFO - Epoch(train) [65][1040/2569] lr: 4.0000e-02 eta: 16:14:26 time: 0.2666 data_time: 0.0075 memory: 5828 grad_norm: 3.0566 loss: 2.5604 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5604 2023/06/05 04:40:41 - mmengine - INFO - Epoch(train) [65][1060/2569] lr: 4.0000e-02 eta: 16:14:21 time: 0.2693 data_time: 0.0075 memory: 5828 grad_norm: 3.1279 loss: 2.6435 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6435 2023/06/05 04:40:46 - mmengine - INFO - Epoch(train) [65][1080/2569] lr: 4.0000e-02 eta: 16:14:16 time: 0.2583 data_time: 0.0075 memory: 5828 grad_norm: 3.1712 loss: 2.7221 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7221 2023/06/05 04:40:51 - mmengine - INFO - Epoch(train) [65][1100/2569] lr: 4.0000e-02 eta: 16:14:10 time: 0.2626 data_time: 0.0077 memory: 5828 grad_norm: 3.0657 loss: 2.5045 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5045 2023/06/05 04:40:57 - mmengine - INFO - Epoch(train) [65][1120/2569] lr: 4.0000e-02 eta: 16:14:05 time: 0.2597 data_time: 0.0072 memory: 5828 grad_norm: 3.1888 loss: 2.6911 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6911 2023/06/05 04:41:02 - mmengine - INFO - Epoch(train) [65][1140/2569] lr: 4.0000e-02 eta: 16:13:59 time: 0.2647 data_time: 0.0079 memory: 5828 grad_norm: 3.1653 loss: 2.6425 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6425 2023/06/05 04:41:07 - mmengine - INFO - Epoch(train) [65][1160/2569] lr: 4.0000e-02 eta: 16:13:54 time: 0.2589 data_time: 0.0075 memory: 5828 grad_norm: 3.1532 loss: 2.3867 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3867 2023/06/05 04:41:12 - mmengine - INFO - Epoch(train) [65][1180/2569] lr: 4.0000e-02 eta: 16:13:48 time: 0.2585 data_time: 0.0083 memory: 5828 grad_norm: 3.1388 loss: 2.4421 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4421 2023/06/05 04:41:18 - mmengine - INFO - Epoch(train) [65][1200/2569] lr: 4.0000e-02 eta: 16:13:43 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 3.1240 loss: 2.7698 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7698 2023/06/05 04:41:23 - mmengine - INFO - Epoch(train) [65][1220/2569] lr: 4.0000e-02 eta: 16:13:38 time: 0.2691 data_time: 0.0069 memory: 5828 grad_norm: 3.0647 loss: 2.5510 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5510 2023/06/05 04:41:28 - mmengine - INFO - Epoch(train) [65][1240/2569] lr: 4.0000e-02 eta: 16:13:32 time: 0.2649 data_time: 0.0078 memory: 5828 grad_norm: 3.1550 loss: 2.4750 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4750 2023/06/05 04:41:34 - mmengine - INFO - Epoch(train) [65][1260/2569] lr: 4.0000e-02 eta: 16:13:27 time: 0.2696 data_time: 0.0082 memory: 5828 grad_norm: 3.0884 loss: 2.7022 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7022 2023/06/05 04:41:39 - mmengine - INFO - Epoch(train) [65][1280/2569] lr: 4.0000e-02 eta: 16:13:22 time: 0.2715 data_time: 0.0072 memory: 5828 grad_norm: 3.1267 loss: 2.6566 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6566 2023/06/05 04:41:44 - mmengine - INFO - Epoch(train) [65][1300/2569] lr: 4.0000e-02 eta: 16:13:17 time: 0.2701 data_time: 0.0076 memory: 5828 grad_norm: 3.1191 loss: 2.3827 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3827 2023/06/05 04:41:50 - mmengine - INFO - Epoch(train) [65][1320/2569] lr: 4.0000e-02 eta: 16:13:11 time: 0.2590 data_time: 0.0073 memory: 5828 grad_norm: 3.0995 loss: 2.3409 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3409 2023/06/05 04:41:55 - mmengine - INFO - Epoch(train) [65][1340/2569] lr: 4.0000e-02 eta: 16:13:06 time: 0.2588 data_time: 0.0071 memory: 5828 grad_norm: 3.1298 loss: 2.4438 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4438 2023/06/05 04:42:00 - mmengine - INFO - Epoch(train) [65][1360/2569] lr: 4.0000e-02 eta: 16:13:00 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 3.1216 loss: 2.3913 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3913 2023/06/05 04:42:05 - mmengine - INFO - Epoch(train) [65][1380/2569] lr: 4.0000e-02 eta: 16:12:55 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 3.1098 loss: 2.3793 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3793 2023/06/05 04:42:11 - mmengine - INFO - Epoch(train) [65][1400/2569] lr: 4.0000e-02 eta: 16:12:49 time: 0.2592 data_time: 0.0075 memory: 5828 grad_norm: 3.1327 loss: 2.5401 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5401 2023/06/05 04:42:16 - mmengine - INFO - Epoch(train) [65][1420/2569] lr: 4.0000e-02 eta: 16:12:44 time: 0.2636 data_time: 0.0069 memory: 5828 grad_norm: 3.1058 loss: 2.7073 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7073 2023/06/05 04:42:21 - mmengine - INFO - Epoch(train) [65][1440/2569] lr: 4.0000e-02 eta: 16:12:39 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 3.1776 loss: 2.3966 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3966 2023/06/05 04:42:26 - mmengine - INFO - Epoch(train) [65][1460/2569] lr: 4.0000e-02 eta: 16:12:33 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 3.1088 loss: 2.3065 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3065 2023/06/05 04:42:32 - mmengine - INFO - Epoch(train) [65][1480/2569] lr: 4.0000e-02 eta: 16:12:28 time: 0.2730 data_time: 0.0072 memory: 5828 grad_norm: 3.1223 loss: 2.4117 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4117 2023/06/05 04:42:37 - mmengine - INFO - Epoch(train) [65][1500/2569] lr: 4.0000e-02 eta: 16:12:23 time: 0.2633 data_time: 0.0077 memory: 5828 grad_norm: 3.1550 loss: 2.2255 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2255 2023/06/05 04:42:43 - mmengine - INFO - Epoch(train) [65][1520/2569] lr: 4.0000e-02 eta: 16:12:18 time: 0.2690 data_time: 0.0077 memory: 5828 grad_norm: 3.1104 loss: 2.1978 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1978 2023/06/05 04:42:48 - mmengine - INFO - Epoch(train) [65][1540/2569] lr: 4.0000e-02 eta: 16:12:12 time: 0.2589 data_time: 0.0076 memory: 5828 grad_norm: 3.0889 loss: 2.4241 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4241 2023/06/05 04:42:53 - mmengine - INFO - Epoch(train) [65][1560/2569] lr: 4.0000e-02 eta: 16:12:07 time: 0.2692 data_time: 0.0075 memory: 5828 grad_norm: 3.1467 loss: 2.6906 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6906 2023/06/05 04:42:58 - mmengine - INFO - Epoch(train) [65][1580/2569] lr: 4.0000e-02 eta: 16:12:01 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 3.0694 loss: 2.6090 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6090 2023/06/05 04:42:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:43:04 - mmengine - INFO - Epoch(train) [65][1600/2569] lr: 4.0000e-02 eta: 16:11:56 time: 0.2608 data_time: 0.0075 memory: 5828 grad_norm: 3.0691 loss: 2.6699 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6699 2023/06/05 04:43:09 - mmengine - INFO - Epoch(train) [65][1620/2569] lr: 4.0000e-02 eta: 16:11:51 time: 0.2771 data_time: 0.0071 memory: 5828 grad_norm: 3.1228 loss: 2.5074 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5074 2023/06/05 04:43:14 - mmengine - INFO - Epoch(train) [65][1640/2569] lr: 4.0000e-02 eta: 16:11:46 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 3.1009 loss: 2.5099 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5099 2023/06/05 04:43:20 - mmengine - INFO - Epoch(train) [65][1660/2569] lr: 4.0000e-02 eta: 16:11:40 time: 0.2744 data_time: 0.0075 memory: 5828 grad_norm: 3.2033 loss: 2.3518 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3518 2023/06/05 04:43:25 - mmengine - INFO - Epoch(train) [65][1680/2569] lr: 4.0000e-02 eta: 16:11:35 time: 0.2665 data_time: 0.0075 memory: 5828 grad_norm: 3.0967 loss: 2.5570 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5570 2023/06/05 04:43:31 - mmengine - INFO - Epoch(train) [65][1700/2569] lr: 4.0000e-02 eta: 16:11:30 time: 0.2677 data_time: 0.0082 memory: 5828 grad_norm: 3.1158 loss: 2.6081 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6081 2023/06/05 04:43:36 - mmengine - INFO - Epoch(train) [65][1720/2569] lr: 4.0000e-02 eta: 16:11:25 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 3.0747 loss: 2.2699 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2699 2023/06/05 04:43:41 - mmengine - INFO - Epoch(train) [65][1740/2569] lr: 4.0000e-02 eta: 16:11:19 time: 0.2723 data_time: 0.0076 memory: 5828 grad_norm: 3.1215 loss: 2.3749 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3749 2023/06/05 04:43:47 - mmengine - INFO - Epoch(train) [65][1760/2569] lr: 4.0000e-02 eta: 16:11:14 time: 0.2662 data_time: 0.0078 memory: 5828 grad_norm: 3.0890 loss: 2.5699 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5699 2023/06/05 04:43:52 - mmengine - INFO - Epoch(train) [65][1780/2569] lr: 4.0000e-02 eta: 16:11:09 time: 0.2567 data_time: 0.0077 memory: 5828 grad_norm: 3.2165 loss: 2.3869 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3869 2023/06/05 04:43:57 - mmengine - INFO - Epoch(train) [65][1800/2569] lr: 4.0000e-02 eta: 16:11:03 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 3.1749 loss: 2.3232 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3232 2023/06/05 04:44:02 - mmengine - INFO - Epoch(train) [65][1820/2569] lr: 4.0000e-02 eta: 16:10:58 time: 0.2610 data_time: 0.0069 memory: 5828 grad_norm: 3.1368 loss: 2.5309 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5309 2023/06/05 04:44:08 - mmengine - INFO - Epoch(train) [65][1840/2569] lr: 4.0000e-02 eta: 16:10:53 time: 0.2744 data_time: 0.0074 memory: 5828 grad_norm: 3.1350 loss: 2.5077 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5077 2023/06/05 04:44:13 - mmengine - INFO - Epoch(train) [65][1860/2569] lr: 4.0000e-02 eta: 16:10:47 time: 0.2686 data_time: 0.0073 memory: 5828 grad_norm: 3.1738 loss: 2.4090 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4090 2023/06/05 04:44:18 - mmengine - INFO - Epoch(train) [65][1880/2569] lr: 4.0000e-02 eta: 16:10:42 time: 0.2601 data_time: 0.0072 memory: 5828 grad_norm: 3.1372 loss: 2.6506 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6506 2023/06/05 04:44:24 - mmengine - INFO - Epoch(train) [65][1900/2569] lr: 4.0000e-02 eta: 16:10:36 time: 0.2589 data_time: 0.0072 memory: 5828 grad_norm: 3.1235 loss: 2.6660 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6660 2023/06/05 04:44:29 - mmengine - INFO - Epoch(train) [65][1920/2569] lr: 4.0000e-02 eta: 16:10:31 time: 0.2591 data_time: 0.0074 memory: 5828 grad_norm: 3.0669 loss: 2.9136 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.9136 2023/06/05 04:44:34 - mmengine - INFO - Epoch(train) [65][1940/2569] lr: 4.0000e-02 eta: 16:10:25 time: 0.2618 data_time: 0.0071 memory: 5828 grad_norm: 3.1170 loss: 2.8702 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.8702 2023/06/05 04:44:39 - mmengine - INFO - Epoch(train) [65][1960/2569] lr: 4.0000e-02 eta: 16:10:20 time: 0.2577 data_time: 0.0072 memory: 5828 grad_norm: 3.0805 loss: 2.6482 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6482 2023/06/05 04:44:45 - mmengine - INFO - Epoch(train) [65][1980/2569] lr: 4.0000e-02 eta: 16:10:15 time: 0.2903 data_time: 0.0073 memory: 5828 grad_norm: 3.1298 loss: 2.4494 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4494 2023/06/05 04:44:50 - mmengine - INFO - Epoch(train) [65][2000/2569] lr: 4.0000e-02 eta: 16:10:10 time: 0.2637 data_time: 0.0072 memory: 5828 grad_norm: 3.0580 loss: 2.7128 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7128 2023/06/05 04:44:56 - mmengine - INFO - Epoch(train) [65][2020/2569] lr: 4.0000e-02 eta: 16:10:05 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 3.0947 loss: 2.4576 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4576 2023/06/05 04:45:01 - mmengine - INFO - Epoch(train) [65][2040/2569] lr: 4.0000e-02 eta: 16:09:59 time: 0.2580 data_time: 0.0077 memory: 5828 grad_norm: 3.1184 loss: 2.3584 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.3584 2023/06/05 04:45:06 - mmengine - INFO - Epoch(train) [65][2060/2569] lr: 4.0000e-02 eta: 16:09:54 time: 0.2642 data_time: 0.0070 memory: 5828 grad_norm: 3.0716 loss: 2.5852 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5852 2023/06/05 04:45:11 - mmengine - INFO - Epoch(train) [65][2080/2569] lr: 4.0000e-02 eta: 16:09:48 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 3.1840 loss: 2.4971 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4971 2023/06/05 04:45:16 - mmengine - INFO - Epoch(train) [65][2100/2569] lr: 4.0000e-02 eta: 16:09:43 time: 0.2568 data_time: 0.0071 memory: 5828 grad_norm: 3.0983 loss: 2.1964 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1964 2023/06/05 04:45:22 - mmengine - INFO - Epoch(train) [65][2120/2569] lr: 4.0000e-02 eta: 16:09:37 time: 0.2592 data_time: 0.0070 memory: 5828 grad_norm: 3.1405 loss: 2.4573 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4573 2023/06/05 04:45:27 - mmengine - INFO - Epoch(train) [65][2140/2569] lr: 4.0000e-02 eta: 16:09:32 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 3.1046 loss: 2.5898 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5898 2023/06/05 04:45:32 - mmengine - INFO - Epoch(train) [65][2160/2569] lr: 4.0000e-02 eta: 16:09:27 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 3.0722 loss: 2.6655 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6655 2023/06/05 04:45:38 - mmengine - INFO - Epoch(train) [65][2180/2569] lr: 4.0000e-02 eta: 16:09:21 time: 0.2608 data_time: 0.0075 memory: 5828 grad_norm: 3.0799 loss: 2.2947 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2947 2023/06/05 04:45:43 - mmengine - INFO - Epoch(train) [65][2200/2569] lr: 4.0000e-02 eta: 16:09:16 time: 0.2660 data_time: 0.0068 memory: 5828 grad_norm: 3.1394 loss: 2.3770 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3770 2023/06/05 04:45:48 - mmengine - INFO - Epoch(train) [65][2220/2569] lr: 4.0000e-02 eta: 16:09:10 time: 0.2614 data_time: 0.0070 memory: 5828 grad_norm: 3.1273 loss: 2.2730 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2730 2023/06/05 04:45:54 - mmengine - INFO - Epoch(train) [65][2240/2569] lr: 4.0000e-02 eta: 16:09:05 time: 0.2748 data_time: 0.0076 memory: 5828 grad_norm: 3.0598 loss: 2.4329 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4329 2023/06/05 04:45:59 - mmengine - INFO - Epoch(train) [65][2260/2569] lr: 4.0000e-02 eta: 16:09:00 time: 0.2586 data_time: 0.0077 memory: 5828 grad_norm: 3.0871 loss: 2.7400 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7400 2023/06/05 04:46:04 - mmengine - INFO - Epoch(train) [65][2280/2569] lr: 4.0000e-02 eta: 16:08:55 time: 0.2729 data_time: 0.0071 memory: 5828 grad_norm: 3.0513 loss: 2.4518 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4518 2023/06/05 04:46:10 - mmengine - INFO - Epoch(train) [65][2300/2569] lr: 4.0000e-02 eta: 16:08:49 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 3.0634 loss: 2.6069 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6069 2023/06/05 04:46:15 - mmengine - INFO - Epoch(train) [65][2320/2569] lr: 4.0000e-02 eta: 16:08:44 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 3.1487 loss: 2.8287 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8287 2023/06/05 04:46:20 - mmengine - INFO - Epoch(train) [65][2340/2569] lr: 4.0000e-02 eta: 16:08:38 time: 0.2593 data_time: 0.0074 memory: 5828 grad_norm: 3.0876 loss: 2.5404 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5404 2023/06/05 04:46:25 - mmengine - INFO - Epoch(train) [65][2360/2569] lr: 4.0000e-02 eta: 16:08:33 time: 0.2582 data_time: 0.0072 memory: 5828 grad_norm: 3.0930 loss: 2.6982 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.6982 2023/06/05 04:46:30 - mmengine - INFO - Epoch(train) [65][2380/2569] lr: 4.0000e-02 eta: 16:08:27 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.1392 loss: 2.5282 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5282 2023/06/05 04:46:36 - mmengine - INFO - Epoch(train) [65][2400/2569] lr: 4.0000e-02 eta: 16:08:22 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 3.0963 loss: 2.3827 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3827 2023/06/05 04:46:41 - mmengine - INFO - Epoch(train) [65][2420/2569] lr: 4.0000e-02 eta: 16:08:17 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 3.1305 loss: 2.5892 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5892 2023/06/05 04:46:46 - mmengine - INFO - Epoch(train) [65][2440/2569] lr: 4.0000e-02 eta: 16:08:11 time: 0.2616 data_time: 0.0076 memory: 5828 grad_norm: 3.0226 loss: 2.4108 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4108 2023/06/05 04:46:52 - mmengine - INFO - Epoch(train) [65][2460/2569] lr: 4.0000e-02 eta: 16:08:06 time: 0.2596 data_time: 0.0075 memory: 5828 grad_norm: 3.1250 loss: 2.4589 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4589 2023/06/05 04:46:57 - mmengine - INFO - Epoch(train) [65][2480/2569] lr: 4.0000e-02 eta: 16:08:01 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 3.0803 loss: 2.7769 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.7769 2023/06/05 04:47:02 - mmengine - INFO - Epoch(train) [65][2500/2569] lr: 4.0000e-02 eta: 16:07:55 time: 0.2583 data_time: 0.0077 memory: 5828 grad_norm: 3.0409 loss: 2.2102 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2102 2023/06/05 04:47:07 - mmengine - INFO - Epoch(train) [65][2520/2569] lr: 4.0000e-02 eta: 16:07:50 time: 0.2727 data_time: 0.0073 memory: 5828 grad_norm: 3.1473 loss: 2.5133 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5133 2023/06/05 04:47:13 - mmengine - INFO - Epoch(train) [65][2540/2569] lr: 4.0000e-02 eta: 16:07:45 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 3.1467 loss: 2.5931 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5931 2023/06/05 04:47:18 - mmengine - INFO - Epoch(train) [65][2560/2569] lr: 4.0000e-02 eta: 16:07:39 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 3.1298 loss: 2.5920 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5920 2023/06/05 04:47:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:47:20 - mmengine - INFO - Epoch(train) [65][2569/2569] lr: 4.0000e-02 eta: 16:07:37 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 3.1453 loss: 2.3924 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 2.3924 2023/06/05 04:47:24 - mmengine - INFO - Epoch(val) [65][ 20/260] eta: 0:00:43 time: 0.1832 data_time: 0.1246 memory: 1238 2023/06/05 04:47:27 - mmengine - INFO - Epoch(val) [65][ 40/260] eta: 0:00:35 time: 0.1432 data_time: 0.0842 memory: 1238 2023/06/05 04:47:30 - mmengine - INFO - Epoch(val) [65][ 60/260] eta: 0:00:31 time: 0.1523 data_time: 0.0935 memory: 1238 2023/06/05 04:47:33 - mmengine - INFO - Epoch(val) [65][ 80/260] eta: 0:00:27 time: 0.1331 data_time: 0.0738 memory: 1238 2023/06/05 04:47:36 - mmengine - INFO - Epoch(val) [65][100/260] eta: 0:00:24 time: 0.1596 data_time: 0.1007 memory: 1238 2023/06/05 04:47:38 - mmengine - INFO - Epoch(val) [65][120/260] eta: 0:00:21 time: 0.1294 data_time: 0.0705 memory: 1238 2023/06/05 04:47:41 - mmengine - INFO - Epoch(val) [65][140/260] eta: 0:00:17 time: 0.1321 data_time: 0.0737 memory: 1238 2023/06/05 04:47:44 - mmengine - INFO - Epoch(val) [65][160/260] eta: 0:00:14 time: 0.1239 data_time: 0.0653 memory: 1238 2023/06/05 04:47:47 - mmengine - INFO - Epoch(val) [65][180/260] eta: 0:00:11 time: 0.1631 data_time: 0.1038 memory: 1238 2023/06/05 04:47:50 - mmengine - INFO - Epoch(val) [65][200/260] eta: 0:00:08 time: 0.1349 data_time: 0.0764 memory: 1238 2023/06/05 04:47:53 - mmengine - INFO - Epoch(val) [65][220/260] eta: 0:00:05 time: 0.1605 data_time: 0.1023 memory: 1238 2023/06/05 04:47:56 - mmengine - INFO - Epoch(val) [65][240/260] eta: 0:00:02 time: 0.1390 data_time: 0.0805 memory: 1238 2023/06/05 04:47:58 - mmengine - INFO - Epoch(val) [65][260/260] eta: 0:00:00 time: 0.1282 data_time: 0.0718 memory: 1238 2023/06/05 04:48:05 - mmengine - INFO - Epoch(val) [65][260/260] acc/top1: 0.5005 acc/top5: 0.7413 acc/mean1: 0.4903 data_time: 0.0859 time: 0.1444 2023/06/05 04:48:05 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_40.pth is removed 2023/06/05 04:48:06 - mmengine - INFO - The best checkpoint with 0.5005 acc/top1 at 65 epoch is saved to best_acc_top1_epoch_65.pth. 2023/06/05 04:48:11 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:48:12 - mmengine - INFO - Epoch(train) [66][ 20/2569] lr: 4.0000e-02 eta: 16:07:32 time: 0.3011 data_time: 0.0523 memory: 5828 grad_norm: 3.1898 loss: 2.6341 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6341 2023/06/05 04:48:18 - mmengine - INFO - Epoch(train) [66][ 40/2569] lr: 4.0000e-02 eta: 16:07:27 time: 0.2634 data_time: 0.0069 memory: 5828 grad_norm: 3.0822 loss: 2.7164 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7164 2023/06/05 04:48:23 - mmengine - INFO - Epoch(train) [66][ 60/2569] lr: 4.0000e-02 eta: 16:07:22 time: 0.2579 data_time: 0.0071 memory: 5828 grad_norm: 3.1176 loss: 2.5717 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5717 2023/06/05 04:48:28 - mmengine - INFO - Epoch(train) [66][ 80/2569] lr: 4.0000e-02 eta: 16:07:16 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 3.0871 loss: 2.5487 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5487 2023/06/05 04:48:33 - mmengine - INFO - Epoch(train) [66][ 100/2569] lr: 4.0000e-02 eta: 16:07:11 time: 0.2593 data_time: 0.0072 memory: 5828 grad_norm: 3.0860 loss: 2.5033 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5033 2023/06/05 04:48:39 - mmengine - INFO - Epoch(train) [66][ 120/2569] lr: 4.0000e-02 eta: 16:07:06 time: 0.2682 data_time: 0.0077 memory: 5828 grad_norm: 3.1237 loss: 2.1970 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1970 2023/06/05 04:48:44 - mmengine - INFO - Epoch(train) [66][ 140/2569] lr: 4.0000e-02 eta: 16:07:00 time: 0.2637 data_time: 0.0080 memory: 5828 grad_norm: 3.1335 loss: 2.6293 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6293 2023/06/05 04:48:49 - mmengine - INFO - Epoch(train) [66][ 160/2569] lr: 4.0000e-02 eta: 16:06:55 time: 0.2574 data_time: 0.0077 memory: 5828 grad_norm: 3.0530 loss: 2.1521 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1521 2023/06/05 04:48:54 - mmengine - INFO - Epoch(train) [66][ 180/2569] lr: 4.0000e-02 eta: 16:06:49 time: 0.2607 data_time: 0.0075 memory: 5828 grad_norm: 3.1146 loss: 2.6705 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6705 2023/06/05 04:49:00 - mmengine - INFO - Epoch(train) [66][ 200/2569] lr: 4.0000e-02 eta: 16:06:44 time: 0.2638 data_time: 0.0071 memory: 5828 grad_norm: 3.0895 loss: 2.4000 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4000 2023/06/05 04:49:05 - mmengine - INFO - Epoch(train) [66][ 220/2569] lr: 4.0000e-02 eta: 16:06:38 time: 0.2639 data_time: 0.0077 memory: 5828 grad_norm: 3.1437 loss: 2.2956 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2956 2023/06/05 04:49:10 - mmengine - INFO - Epoch(train) [66][ 240/2569] lr: 4.0000e-02 eta: 16:06:33 time: 0.2620 data_time: 0.0079 memory: 5828 grad_norm: 3.1174 loss: 2.5118 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5118 2023/06/05 04:49:16 - mmengine - INFO - Epoch(train) [66][ 260/2569] lr: 4.0000e-02 eta: 16:06:28 time: 0.2662 data_time: 0.0077 memory: 5828 grad_norm: 3.1662 loss: 2.7738 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7738 2023/06/05 04:49:21 - mmengine - INFO - Epoch(train) [66][ 280/2569] lr: 4.0000e-02 eta: 16:06:22 time: 0.2690 data_time: 0.0076 memory: 5828 grad_norm: 3.1208 loss: 2.2611 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2611 2023/06/05 04:49:26 - mmengine - INFO - Epoch(train) [66][ 300/2569] lr: 4.0000e-02 eta: 16:06:17 time: 0.2627 data_time: 0.0075 memory: 5828 grad_norm: 3.0903 loss: 2.3652 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3652 2023/06/05 04:49:31 - mmengine - INFO - Epoch(train) [66][ 320/2569] lr: 4.0000e-02 eta: 16:06:12 time: 0.2583 data_time: 0.0075 memory: 5828 grad_norm: 3.1670 loss: 2.6548 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6548 2023/06/05 04:49:37 - mmengine - INFO - Epoch(train) [66][ 340/2569] lr: 4.0000e-02 eta: 16:06:06 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 3.0500 loss: 2.6130 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6130 2023/06/05 04:49:42 - mmengine - INFO - Epoch(train) [66][ 360/2569] lr: 4.0000e-02 eta: 16:06:01 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 3.1884 loss: 2.2051 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2051 2023/06/05 04:49:47 - mmengine - INFO - Epoch(train) [66][ 380/2569] lr: 4.0000e-02 eta: 16:05:55 time: 0.2589 data_time: 0.0072 memory: 5828 grad_norm: 3.1082 loss: 2.4538 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4538 2023/06/05 04:49:52 - mmengine - INFO - Epoch(train) [66][ 400/2569] lr: 4.0000e-02 eta: 16:05:50 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 3.1537 loss: 2.6908 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6908 2023/06/05 04:49:58 - mmengine - INFO - Epoch(train) [66][ 420/2569] lr: 4.0000e-02 eta: 16:05:45 time: 0.2766 data_time: 0.0070 memory: 5828 grad_norm: 3.1414 loss: 2.1880 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1880 2023/06/05 04:50:03 - mmengine - INFO - Epoch(train) [66][ 440/2569] lr: 4.0000e-02 eta: 16:05:39 time: 0.2594 data_time: 0.0073 memory: 5828 grad_norm: 3.2394 loss: 2.6650 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6650 2023/06/05 04:50:09 - mmengine - INFO - Epoch(train) [66][ 460/2569] lr: 4.0000e-02 eta: 16:05:34 time: 0.2656 data_time: 0.0070 memory: 5828 grad_norm: 3.1773 loss: 2.4060 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4060 2023/06/05 04:50:14 - mmengine - INFO - Epoch(train) [66][ 480/2569] lr: 4.0000e-02 eta: 16:05:29 time: 0.2688 data_time: 0.0076 memory: 5828 grad_norm: 3.1647 loss: 2.4634 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4634 2023/06/05 04:50:19 - mmengine - INFO - Epoch(train) [66][ 500/2569] lr: 4.0000e-02 eta: 16:05:23 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 3.1687 loss: 2.2070 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2070 2023/06/05 04:50:24 - mmengine - INFO - Epoch(train) [66][ 520/2569] lr: 4.0000e-02 eta: 16:05:18 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 3.1581 loss: 2.6902 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6902 2023/06/05 04:50:30 - mmengine - INFO - Epoch(train) [66][ 540/2569] lr: 4.0000e-02 eta: 16:05:13 time: 0.2755 data_time: 0.0075 memory: 5828 grad_norm: 3.1535 loss: 2.7347 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7347 2023/06/05 04:50:35 - mmengine - INFO - Epoch(train) [66][ 560/2569] lr: 4.0000e-02 eta: 16:05:08 time: 0.2688 data_time: 0.0075 memory: 5828 grad_norm: 3.1158 loss: 2.3988 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3988 2023/06/05 04:50:41 - mmengine - INFO - Epoch(train) [66][ 580/2569] lr: 4.0000e-02 eta: 16:05:03 time: 0.2817 data_time: 0.0079 memory: 5828 grad_norm: 3.1332 loss: 2.4849 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4849 2023/06/05 04:50:46 - mmengine - INFO - Epoch(train) [66][ 600/2569] lr: 4.0000e-02 eta: 16:04:57 time: 0.2580 data_time: 0.0071 memory: 5828 grad_norm: 3.0808 loss: 2.6455 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6455 2023/06/05 04:50:51 - mmengine - INFO - Epoch(train) [66][ 620/2569] lr: 4.0000e-02 eta: 16:04:52 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 3.1103 loss: 2.3772 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3772 2023/06/05 04:50:57 - mmengine - INFO - Epoch(train) [66][ 640/2569] lr: 4.0000e-02 eta: 16:04:47 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 3.1029 loss: 2.6455 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6455 2023/06/05 04:51:02 - mmengine - INFO - Epoch(train) [66][ 660/2569] lr: 4.0000e-02 eta: 16:04:41 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.0650 loss: 2.8050 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8050 2023/06/05 04:51:07 - mmengine - INFO - Epoch(train) [66][ 680/2569] lr: 4.0000e-02 eta: 16:04:36 time: 0.2633 data_time: 0.0080 memory: 5828 grad_norm: 3.1628 loss: 2.1488 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1488 2023/06/05 04:51:13 - mmengine - INFO - Epoch(train) [66][ 700/2569] lr: 4.0000e-02 eta: 16:04:31 time: 0.2684 data_time: 0.0074 memory: 5828 grad_norm: 3.0975 loss: 2.6893 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6893 2023/06/05 04:51:18 - mmengine - INFO - Epoch(train) [66][ 720/2569] lr: 4.0000e-02 eta: 16:04:25 time: 0.2610 data_time: 0.0078 memory: 5828 grad_norm: 3.0521 loss: 2.6406 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6406 2023/06/05 04:51:23 - mmengine - INFO - Epoch(train) [66][ 740/2569] lr: 4.0000e-02 eta: 16:04:20 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 3.1637 loss: 2.6821 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6821 2023/06/05 04:51:29 - mmengine - INFO - Epoch(train) [66][ 760/2569] lr: 4.0000e-02 eta: 16:04:15 time: 0.2698 data_time: 0.0070 memory: 5828 grad_norm: 3.1569 loss: 2.4740 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4740 2023/06/05 04:51:34 - mmengine - INFO - Epoch(train) [66][ 780/2569] lr: 4.0000e-02 eta: 16:04:09 time: 0.2582 data_time: 0.0073 memory: 5828 grad_norm: 3.0706 loss: 2.5004 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5004 2023/06/05 04:51:39 - mmengine - INFO - Epoch(train) [66][ 800/2569] lr: 4.0000e-02 eta: 16:04:04 time: 0.2707 data_time: 0.0072 memory: 5828 grad_norm: 3.1454 loss: 2.7640 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7640 2023/06/05 04:51:44 - mmengine - INFO - Epoch(train) [66][ 820/2569] lr: 4.0000e-02 eta: 16:03:59 time: 0.2578 data_time: 0.0073 memory: 5828 grad_norm: 3.1522 loss: 2.2724 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2724 2023/06/05 04:51:50 - mmengine - INFO - Epoch(train) [66][ 840/2569] lr: 4.0000e-02 eta: 16:03:53 time: 0.2601 data_time: 0.0077 memory: 5828 grad_norm: 3.1253 loss: 2.6245 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6245 2023/06/05 04:51:55 - mmengine - INFO - Epoch(train) [66][ 860/2569] lr: 4.0000e-02 eta: 16:03:48 time: 0.2600 data_time: 0.0073 memory: 5828 grad_norm: 3.1373 loss: 2.4688 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4688 2023/06/05 04:52:00 - mmengine - INFO - Epoch(train) [66][ 880/2569] lr: 4.0000e-02 eta: 16:03:42 time: 0.2686 data_time: 0.0075 memory: 5828 grad_norm: 3.1545 loss: 2.5352 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5352 2023/06/05 04:52:06 - mmengine - INFO - Epoch(train) [66][ 900/2569] lr: 4.0000e-02 eta: 16:03:37 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 3.1556 loss: 2.6462 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6462 2023/06/05 04:52:11 - mmengine - INFO - Epoch(train) [66][ 920/2569] lr: 4.0000e-02 eta: 16:03:32 time: 0.2703 data_time: 0.0073 memory: 5828 grad_norm: 3.1150 loss: 2.4987 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4987 2023/06/05 04:52:16 - mmengine - INFO - Epoch(train) [66][ 940/2569] lr: 4.0000e-02 eta: 16:03:26 time: 0.2580 data_time: 0.0071 memory: 5828 grad_norm: 3.1256 loss: 2.6935 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6935 2023/06/05 04:52:21 - mmengine - INFO - Epoch(train) [66][ 960/2569] lr: 4.0000e-02 eta: 16:03:21 time: 0.2564 data_time: 0.0073 memory: 5828 grad_norm: 3.1387 loss: 2.8636 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8636 2023/06/05 04:52:26 - mmengine - INFO - Epoch(train) [66][ 980/2569] lr: 4.0000e-02 eta: 16:03:15 time: 0.2581 data_time: 0.0068 memory: 5828 grad_norm: 3.1389 loss: 2.4805 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4805 2023/06/05 04:52:32 - mmengine - INFO - Epoch(train) [66][1000/2569] lr: 4.0000e-02 eta: 16:03:10 time: 0.2635 data_time: 0.0074 memory: 5828 grad_norm: 3.1344 loss: 2.0831 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0831 2023/06/05 04:52:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:52:37 - mmengine - INFO - Epoch(train) [66][1020/2569] lr: 4.0000e-02 eta: 16:03:04 time: 0.2562 data_time: 0.0070 memory: 5828 grad_norm: 3.1102 loss: 2.7959 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7959 2023/06/05 04:52:42 - mmengine - INFO - Epoch(train) [66][1040/2569] lr: 4.0000e-02 eta: 16:02:59 time: 0.2670 data_time: 0.0070 memory: 5828 grad_norm: 3.1529 loss: 2.5472 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5472 2023/06/05 04:52:48 - mmengine - INFO - Epoch(train) [66][1060/2569] lr: 4.0000e-02 eta: 16:02:54 time: 0.2707 data_time: 0.0072 memory: 5828 grad_norm: 3.0937 loss: 2.3192 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3192 2023/06/05 04:52:53 - mmengine - INFO - Epoch(train) [66][1080/2569] lr: 4.0000e-02 eta: 16:02:48 time: 0.2616 data_time: 0.0075 memory: 5828 grad_norm: 3.1003 loss: 2.1958 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1958 2023/06/05 04:52:58 - mmengine - INFO - Epoch(train) [66][1100/2569] lr: 4.0000e-02 eta: 16:02:43 time: 0.2624 data_time: 0.0074 memory: 5828 grad_norm: 3.1471 loss: 2.5582 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5582 2023/06/05 04:53:03 - mmengine - INFO - Epoch(train) [66][1120/2569] lr: 4.0000e-02 eta: 16:02:38 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 3.1888 loss: 2.5068 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5068 2023/06/05 04:53:09 - mmengine - INFO - Epoch(train) [66][1140/2569] lr: 4.0000e-02 eta: 16:02:32 time: 0.2593 data_time: 0.0069 memory: 5828 grad_norm: 3.1467 loss: 2.6103 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6103 2023/06/05 04:53:14 - mmengine - INFO - Epoch(train) [66][1160/2569] lr: 4.0000e-02 eta: 16:02:27 time: 0.2742 data_time: 0.0074 memory: 5828 grad_norm: 3.0892 loss: 2.8433 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8433 2023/06/05 04:53:19 - mmengine - INFO - Epoch(train) [66][1180/2569] lr: 4.0000e-02 eta: 16:02:22 time: 0.2571 data_time: 0.0075 memory: 5828 grad_norm: 3.1077 loss: 2.4608 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4608 2023/06/05 04:53:24 - mmengine - INFO - Epoch(train) [66][1200/2569] lr: 4.0000e-02 eta: 16:02:16 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.1405 loss: 2.4532 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4532 2023/06/05 04:53:30 - mmengine - INFO - Epoch(train) [66][1220/2569] lr: 4.0000e-02 eta: 16:02:11 time: 0.2603 data_time: 0.0074 memory: 5828 grad_norm: 3.0500 loss: 2.4065 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4065 2023/06/05 04:53:35 - mmengine - INFO - Epoch(train) [66][1240/2569] lr: 4.0000e-02 eta: 16:02:05 time: 0.2708 data_time: 0.0071 memory: 5828 grad_norm: 3.0567 loss: 2.3142 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3142 2023/06/05 04:53:40 - mmengine - INFO - Epoch(train) [66][1260/2569] lr: 4.0000e-02 eta: 16:02:00 time: 0.2683 data_time: 0.0070 memory: 5828 grad_norm: 3.0791 loss: 2.7819 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7819 2023/06/05 04:53:46 - mmengine - INFO - Epoch(train) [66][1280/2569] lr: 4.0000e-02 eta: 16:01:55 time: 0.2637 data_time: 0.0069 memory: 5828 grad_norm: 3.0925 loss: 2.8264 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8264 2023/06/05 04:53:51 - mmengine - INFO - Epoch(train) [66][1300/2569] lr: 4.0000e-02 eta: 16:01:49 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 3.1256 loss: 2.5117 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5117 2023/06/05 04:53:56 - mmengine - INFO - Epoch(train) [66][1320/2569] lr: 4.0000e-02 eta: 16:01:44 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 3.1100 loss: 2.3971 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3971 2023/06/05 04:54:02 - mmengine - INFO - Epoch(train) [66][1340/2569] lr: 4.0000e-02 eta: 16:01:39 time: 0.2607 data_time: 0.0072 memory: 5828 grad_norm: 3.1319 loss: 2.3365 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3365 2023/06/05 04:54:07 - mmengine - INFO - Epoch(train) [66][1360/2569] lr: 4.0000e-02 eta: 16:01:33 time: 0.2710 data_time: 0.0077 memory: 5828 grad_norm: 3.1328 loss: 2.8436 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8436 2023/06/05 04:54:12 - mmengine - INFO - Epoch(train) [66][1380/2569] lr: 4.0000e-02 eta: 16:01:28 time: 0.2661 data_time: 0.0078 memory: 5828 grad_norm: 3.1368 loss: 2.7941 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7941 2023/06/05 04:54:18 - mmengine - INFO - Epoch(train) [66][1400/2569] lr: 4.0000e-02 eta: 16:01:23 time: 0.2684 data_time: 0.0074 memory: 5828 grad_norm: 3.1388 loss: 2.5339 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5339 2023/06/05 04:54:23 - mmengine - INFO - Epoch(train) [66][1420/2569] lr: 4.0000e-02 eta: 16:01:17 time: 0.2599 data_time: 0.0074 memory: 5828 grad_norm: 3.1567 loss: 2.7129 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7129 2023/06/05 04:54:28 - mmengine - INFO - Epoch(train) [66][1440/2569] lr: 4.0000e-02 eta: 16:01:12 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 3.0927 loss: 2.8032 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8032 2023/06/05 04:54:33 - mmengine - INFO - Epoch(train) [66][1460/2569] lr: 4.0000e-02 eta: 16:01:07 time: 0.2644 data_time: 0.0071 memory: 5828 grad_norm: 3.1123 loss: 2.6857 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6857 2023/06/05 04:54:39 - mmengine - INFO - Epoch(train) [66][1480/2569] lr: 4.0000e-02 eta: 16:01:01 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 3.0936 loss: 2.7105 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7105 2023/06/05 04:54:44 - mmengine - INFO - Epoch(train) [66][1500/2569] lr: 4.0000e-02 eta: 16:00:56 time: 0.2579 data_time: 0.0070 memory: 5828 grad_norm: 3.1338 loss: 2.5375 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5375 2023/06/05 04:54:49 - mmengine - INFO - Epoch(train) [66][1520/2569] lr: 4.0000e-02 eta: 16:00:50 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 3.1875 loss: 2.4196 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4196 2023/06/05 04:54:54 - mmengine - INFO - Epoch(train) [66][1540/2569] lr: 4.0000e-02 eta: 16:00:45 time: 0.2586 data_time: 0.0075 memory: 5828 grad_norm: 3.1714 loss: 2.3149 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3149 2023/06/05 04:55:00 - mmengine - INFO - Epoch(train) [66][1560/2569] lr: 4.0000e-02 eta: 16:00:39 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 3.1479 loss: 2.3726 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3726 2023/06/05 04:55:05 - mmengine - INFO - Epoch(train) [66][1580/2569] lr: 4.0000e-02 eta: 16:00:34 time: 0.2645 data_time: 0.0075 memory: 5828 grad_norm: 3.1100 loss: 2.4364 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4364 2023/06/05 04:55:10 - mmengine - INFO - Epoch(train) [66][1600/2569] lr: 4.0000e-02 eta: 16:00:29 time: 0.2641 data_time: 0.0076 memory: 5828 grad_norm: 3.1015 loss: 2.7258 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7258 2023/06/05 04:55:15 - mmengine - INFO - Epoch(train) [66][1620/2569] lr: 4.0000e-02 eta: 16:00:23 time: 0.2591 data_time: 0.0076 memory: 5828 grad_norm: 3.1038 loss: 2.3676 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3676 2023/06/05 04:55:21 - mmengine - INFO - Epoch(train) [66][1640/2569] lr: 4.0000e-02 eta: 16:00:18 time: 0.2640 data_time: 0.0072 memory: 5828 grad_norm: 3.0678 loss: 2.5435 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5435 2023/06/05 04:55:26 - mmengine - INFO - Epoch(train) [66][1660/2569] lr: 4.0000e-02 eta: 16:00:13 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 3.1583 loss: 2.6292 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6292 2023/06/05 04:55:31 - mmengine - INFO - Epoch(train) [66][1680/2569] lr: 4.0000e-02 eta: 16:00:07 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 3.2065 loss: 2.2941 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2941 2023/06/05 04:55:36 - mmengine - INFO - Epoch(train) [66][1700/2569] lr: 4.0000e-02 eta: 16:00:02 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 3.1322 loss: 2.4839 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.4839 2023/06/05 04:55:42 - mmengine - INFO - Epoch(train) [66][1720/2569] lr: 4.0000e-02 eta: 15:59:57 time: 0.2744 data_time: 0.0077 memory: 5828 grad_norm: 3.0874 loss: 2.1289 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.1289 2023/06/05 04:55:47 - mmengine - INFO - Epoch(train) [66][1740/2569] lr: 4.0000e-02 eta: 15:59:51 time: 0.2686 data_time: 0.0072 memory: 5828 grad_norm: 3.1080 loss: 2.7971 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7971 2023/06/05 04:55:53 - mmengine - INFO - Epoch(train) [66][1760/2569] lr: 4.0000e-02 eta: 15:59:46 time: 0.2649 data_time: 0.0076 memory: 5828 grad_norm: 3.0974 loss: 2.4746 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4746 2023/06/05 04:55:58 - mmengine - INFO - Epoch(train) [66][1780/2569] lr: 4.0000e-02 eta: 15:59:41 time: 0.2703 data_time: 0.0071 memory: 5828 grad_norm: 3.0664 loss: 2.5559 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5559 2023/06/05 04:56:03 - mmengine - INFO - Epoch(train) [66][1800/2569] lr: 4.0000e-02 eta: 15:59:35 time: 0.2573 data_time: 0.0072 memory: 5828 grad_norm: 3.1927 loss: 2.5645 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5645 2023/06/05 04:56:08 - mmengine - INFO - Epoch(train) [66][1820/2569] lr: 4.0000e-02 eta: 15:59:30 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 3.0995 loss: 2.4084 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4084 2023/06/05 04:56:14 - mmengine - INFO - Epoch(train) [66][1840/2569] lr: 4.0000e-02 eta: 15:59:24 time: 0.2584 data_time: 0.0079 memory: 5828 grad_norm: 3.1430 loss: 2.5217 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5217 2023/06/05 04:56:19 - mmengine - INFO - Epoch(train) [66][1860/2569] lr: 4.0000e-02 eta: 15:59:19 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 3.1285 loss: 2.3958 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3958 2023/06/05 04:56:24 - mmengine - INFO - Epoch(train) [66][1880/2569] lr: 4.0000e-02 eta: 15:59:14 time: 0.2576 data_time: 0.0078 memory: 5828 grad_norm: 3.0663 loss: 2.5813 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5813 2023/06/05 04:56:29 - mmengine - INFO - Epoch(train) [66][1900/2569] lr: 4.0000e-02 eta: 15:59:08 time: 0.2640 data_time: 0.0077 memory: 5828 grad_norm: 3.1146 loss: 2.5538 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5538 2023/06/05 04:56:35 - mmengine - INFO - Epoch(train) [66][1920/2569] lr: 4.0000e-02 eta: 15:59:03 time: 0.2587 data_time: 0.0076 memory: 5828 grad_norm: 3.1032 loss: 2.7879 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7879 2023/06/05 04:56:40 - mmengine - INFO - Epoch(train) [66][1940/2569] lr: 4.0000e-02 eta: 15:58:57 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 3.0727 loss: 2.5970 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5970 2023/06/05 04:56:45 - mmengine - INFO - Epoch(train) [66][1960/2569] lr: 4.0000e-02 eta: 15:58:52 time: 0.2571 data_time: 0.0073 memory: 5828 grad_norm: 3.1428 loss: 2.5252 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5252 2023/06/05 04:56:50 - mmengine - INFO - Epoch(train) [66][1980/2569] lr: 4.0000e-02 eta: 15:58:47 time: 0.2718 data_time: 0.0073 memory: 5828 grad_norm: 3.1065 loss: 2.6721 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6721 2023/06/05 04:56:56 - mmengine - INFO - Epoch(train) [66][2000/2569] lr: 4.0000e-02 eta: 15:58:41 time: 0.2643 data_time: 0.0071 memory: 5828 grad_norm: 3.1684 loss: 2.4589 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4589 2023/06/05 04:57:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:57:01 - mmengine - INFO - Epoch(train) [66][2020/2569] lr: 4.0000e-02 eta: 15:58:36 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 3.1210 loss: 2.5976 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5976 2023/06/05 04:57:06 - mmengine - INFO - Epoch(train) [66][2040/2569] lr: 4.0000e-02 eta: 15:58:30 time: 0.2600 data_time: 0.0073 memory: 5828 grad_norm: 3.1825 loss: 2.9410 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9410 2023/06/05 04:57:11 - mmengine - INFO - Epoch(train) [66][2060/2569] lr: 4.0000e-02 eta: 15:58:25 time: 0.2611 data_time: 0.0072 memory: 5828 grad_norm: 3.1310 loss: 2.5361 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5361 2023/06/05 04:57:17 - mmengine - INFO - Epoch(train) [66][2080/2569] lr: 4.0000e-02 eta: 15:58:19 time: 0.2605 data_time: 0.0072 memory: 5828 grad_norm: 3.0939 loss: 2.6026 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6026 2023/06/05 04:57:22 - mmengine - INFO - Epoch(train) [66][2100/2569] lr: 4.0000e-02 eta: 15:58:14 time: 0.2684 data_time: 0.0075 memory: 5828 grad_norm: 3.1180 loss: 2.4593 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4593 2023/06/05 04:57:27 - mmengine - INFO - Epoch(train) [66][2120/2569] lr: 4.0000e-02 eta: 15:58:09 time: 0.2628 data_time: 0.0071 memory: 5828 grad_norm: 3.1824 loss: 2.5430 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5430 2023/06/05 04:57:32 - mmengine - INFO - Epoch(train) [66][2140/2569] lr: 4.0000e-02 eta: 15:58:03 time: 0.2633 data_time: 0.0071 memory: 5828 grad_norm: 3.1607 loss: 2.4435 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4435 2023/06/05 04:57:38 - mmengine - INFO - Epoch(train) [66][2160/2569] lr: 4.0000e-02 eta: 15:57:58 time: 0.2723 data_time: 0.0072 memory: 5828 grad_norm: 3.1204 loss: 2.6146 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6146 2023/06/05 04:57:43 - mmengine - INFO - Epoch(train) [66][2180/2569] lr: 4.0000e-02 eta: 15:57:53 time: 0.2617 data_time: 0.0070 memory: 5828 grad_norm: 3.1422 loss: 2.6220 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6220 2023/06/05 04:57:48 - mmengine - INFO - Epoch(train) [66][2200/2569] lr: 4.0000e-02 eta: 15:57:47 time: 0.2654 data_time: 0.0077 memory: 5828 grad_norm: 3.0996 loss: 2.3414 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3414 2023/06/05 04:57:54 - mmengine - INFO - Epoch(train) [66][2220/2569] lr: 4.0000e-02 eta: 15:57:42 time: 0.2658 data_time: 0.0075 memory: 5828 grad_norm: 3.2152 loss: 2.7042 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7042 2023/06/05 04:57:59 - mmengine - INFO - Epoch(train) [66][2240/2569] lr: 4.0000e-02 eta: 15:57:37 time: 0.2615 data_time: 0.0078 memory: 5828 grad_norm: 3.1356 loss: 2.5170 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5170 2023/06/05 04:58:04 - mmengine - INFO - Epoch(train) [66][2260/2569] lr: 4.0000e-02 eta: 15:57:31 time: 0.2593 data_time: 0.0083 memory: 5828 grad_norm: 3.1144 loss: 2.6260 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6260 2023/06/05 04:58:09 - mmengine - INFO - Epoch(train) [66][2280/2569] lr: 4.0000e-02 eta: 15:57:26 time: 0.2588 data_time: 0.0073 memory: 5828 grad_norm: 3.1301 loss: 2.2716 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.2716 2023/06/05 04:58:15 - mmengine - INFO - Epoch(train) [66][2300/2569] lr: 4.0000e-02 eta: 15:57:20 time: 0.2584 data_time: 0.0075 memory: 5828 grad_norm: 3.1261 loss: 2.5326 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5326 2023/06/05 04:58:20 - mmengine - INFO - Epoch(train) [66][2320/2569] lr: 4.0000e-02 eta: 15:57:15 time: 0.2676 data_time: 0.0082 memory: 5828 grad_norm: 3.0667 loss: 2.5792 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5792 2023/06/05 04:58:25 - mmengine - INFO - Epoch(train) [66][2340/2569] lr: 4.0000e-02 eta: 15:57:10 time: 0.2599 data_time: 0.0085 memory: 5828 grad_norm: 3.2005 loss: 2.7194 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7194 2023/06/05 04:58:30 - mmengine - INFO - Epoch(train) [66][2360/2569] lr: 4.0000e-02 eta: 15:57:04 time: 0.2596 data_time: 0.0078 memory: 5828 grad_norm: 3.1166 loss: 2.4637 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4637 2023/06/05 04:58:36 - mmengine - INFO - Epoch(train) [66][2380/2569] lr: 4.0000e-02 eta: 15:56:59 time: 0.2733 data_time: 0.0074 memory: 5828 grad_norm: 3.1393 loss: 2.3635 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3635 2023/06/05 04:58:41 - mmengine - INFO - Epoch(train) [66][2400/2569] lr: 4.0000e-02 eta: 15:56:54 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 3.1618 loss: 2.5694 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5694 2023/06/05 04:58:46 - mmengine - INFO - Epoch(train) [66][2420/2569] lr: 4.0000e-02 eta: 15:56:48 time: 0.2640 data_time: 0.0077 memory: 5828 grad_norm: 3.1037 loss: 2.4584 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4584 2023/06/05 04:58:52 - mmengine - INFO - Epoch(train) [66][2440/2569] lr: 4.0000e-02 eta: 15:56:43 time: 0.2588 data_time: 0.0077 memory: 5828 grad_norm: 3.1144 loss: 2.6162 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6162 2023/06/05 04:58:57 - mmengine - INFO - Epoch(train) [66][2460/2569] lr: 4.0000e-02 eta: 15:56:38 time: 0.2739 data_time: 0.0070 memory: 5828 grad_norm: 3.1776 loss: 2.6610 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6610 2023/06/05 04:59:02 - mmengine - INFO - Epoch(train) [66][2480/2569] lr: 4.0000e-02 eta: 15:56:32 time: 0.2637 data_time: 0.0072 memory: 5828 grad_norm: 3.1339 loss: 2.7390 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7390 2023/06/05 04:59:08 - mmengine - INFO - Epoch(train) [66][2500/2569] lr: 4.0000e-02 eta: 15:56:27 time: 0.2616 data_time: 0.0070 memory: 5828 grad_norm: 3.0787 loss: 2.2684 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.2684 2023/06/05 04:59:13 - mmengine - INFO - Epoch(train) [66][2520/2569] lr: 4.0000e-02 eta: 15:56:22 time: 0.2736 data_time: 0.0072 memory: 5828 grad_norm: 3.0837 loss: 2.2989 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2989 2023/06/05 04:59:18 - mmengine - INFO - Epoch(train) [66][2540/2569] lr: 4.0000e-02 eta: 15:56:16 time: 0.2572 data_time: 0.0074 memory: 5828 grad_norm: 3.0374 loss: 3.1275 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.1275 2023/06/05 04:59:23 - mmengine - INFO - Epoch(train) [66][2560/2569] lr: 4.0000e-02 eta: 15:56:11 time: 0.2557 data_time: 0.0079 memory: 5828 grad_norm: 3.0933 loss: 2.5750 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5750 2023/06/05 04:59:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 04:59:26 - mmengine - INFO - Epoch(train) [66][2569/2569] lr: 4.0000e-02 eta: 15:56:08 time: 0.2502 data_time: 0.0076 memory: 5828 grad_norm: 3.0846 loss: 2.6050 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.6050 2023/06/05 04:59:33 - mmengine - INFO - Epoch(train) [67][ 20/2569] lr: 4.0000e-02 eta: 15:56:05 time: 0.3473 data_time: 0.0526 memory: 5828 grad_norm: 3.1175 loss: 2.1665 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1665 2023/06/05 04:59:38 - mmengine - INFO - Epoch(train) [67][ 40/2569] lr: 4.0000e-02 eta: 15:55:59 time: 0.2585 data_time: 0.0073 memory: 5828 grad_norm: 3.1182 loss: 2.2476 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2476 2023/06/05 04:59:43 - mmengine - INFO - Epoch(train) [67][ 60/2569] lr: 4.0000e-02 eta: 15:55:54 time: 0.2771 data_time: 0.0071 memory: 5828 grad_norm: 3.1541 loss: 2.6441 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6441 2023/06/05 04:59:48 - mmengine - INFO - Epoch(train) [67][ 80/2569] lr: 4.0000e-02 eta: 15:55:49 time: 0.2592 data_time: 0.0076 memory: 5828 grad_norm: 3.0197 loss: 2.5617 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5617 2023/06/05 04:59:54 - mmengine - INFO - Epoch(train) [67][ 100/2569] lr: 4.0000e-02 eta: 15:55:43 time: 0.2691 data_time: 0.0072 memory: 5828 grad_norm: 3.0574 loss: 2.4557 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4557 2023/06/05 04:59:59 - mmengine - INFO - Epoch(train) [67][ 120/2569] lr: 4.0000e-02 eta: 15:55:38 time: 0.2630 data_time: 0.0078 memory: 5828 grad_norm: 3.1421 loss: 2.5033 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.5033 2023/06/05 05:00:04 - mmengine - INFO - Epoch(train) [67][ 140/2569] lr: 4.0000e-02 eta: 15:55:33 time: 0.2588 data_time: 0.0072 memory: 5828 grad_norm: 3.1596 loss: 2.6238 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6238 2023/06/05 05:00:09 - mmengine - INFO - Epoch(train) [67][ 160/2569] lr: 4.0000e-02 eta: 15:55:27 time: 0.2582 data_time: 0.0075 memory: 5828 grad_norm: 3.1276 loss: 2.6270 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6270 2023/06/05 05:00:15 - mmengine - INFO - Epoch(train) [67][ 180/2569] lr: 4.0000e-02 eta: 15:55:22 time: 0.2643 data_time: 0.0070 memory: 5828 grad_norm: 3.1058 loss: 2.4561 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4561 2023/06/05 05:00:20 - mmengine - INFO - Epoch(train) [67][ 200/2569] lr: 4.0000e-02 eta: 15:55:16 time: 0.2577 data_time: 0.0073 memory: 5828 grad_norm: 3.0845 loss: 2.4187 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4187 2023/06/05 05:00:25 - mmengine - INFO - Epoch(train) [67][ 220/2569] lr: 4.0000e-02 eta: 15:55:11 time: 0.2603 data_time: 0.0074 memory: 5828 grad_norm: 3.1296 loss: 2.4108 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4108 2023/06/05 05:00:30 - mmengine - INFO - Epoch(train) [67][ 240/2569] lr: 4.0000e-02 eta: 15:55:05 time: 0.2652 data_time: 0.0070 memory: 5828 grad_norm: 3.1302 loss: 2.3412 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.3412 2023/06/05 05:00:36 - mmengine - INFO - Epoch(train) [67][ 260/2569] lr: 4.0000e-02 eta: 15:55:00 time: 0.2595 data_time: 0.0075 memory: 5828 grad_norm: 3.1601 loss: 2.7236 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7236 2023/06/05 05:00:41 - mmengine - INFO - Epoch(train) [67][ 280/2569] lr: 4.0000e-02 eta: 15:54:55 time: 0.2659 data_time: 0.0072 memory: 5828 grad_norm: 3.1071 loss: 2.4551 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4551 2023/06/05 05:00:46 - mmengine - INFO - Epoch(train) [67][ 300/2569] lr: 4.0000e-02 eta: 15:54:49 time: 0.2660 data_time: 0.0070 memory: 5828 grad_norm: 3.1603 loss: 2.6842 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6842 2023/06/05 05:00:52 - mmengine - INFO - Epoch(train) [67][ 320/2569] lr: 4.0000e-02 eta: 15:54:44 time: 0.2704 data_time: 0.0077 memory: 5828 grad_norm: 3.0533 loss: 2.4348 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4348 2023/06/05 05:00:57 - mmengine - INFO - Epoch(train) [67][ 340/2569] lr: 4.0000e-02 eta: 15:54:39 time: 0.2644 data_time: 0.0075 memory: 5828 grad_norm: 3.1587 loss: 2.6060 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6060 2023/06/05 05:01:02 - mmengine - INFO - Epoch(train) [67][ 360/2569] lr: 4.0000e-02 eta: 15:54:34 time: 0.2733 data_time: 0.0072 memory: 5828 grad_norm: 3.1154 loss: 2.6093 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6093 2023/06/05 05:01:08 - mmengine - INFO - Epoch(train) [67][ 380/2569] lr: 4.0000e-02 eta: 15:54:28 time: 0.2569 data_time: 0.0074 memory: 5828 grad_norm: 3.1798 loss: 2.2534 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2534 2023/06/05 05:01:13 - mmengine - INFO - Epoch(train) [67][ 400/2569] lr: 4.0000e-02 eta: 15:54:23 time: 0.2786 data_time: 0.0072 memory: 5828 grad_norm: 3.1565 loss: 2.7917 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7917 2023/06/05 05:01:19 - mmengine - INFO - Epoch(train) [67][ 420/2569] lr: 4.0000e-02 eta: 15:54:18 time: 0.2675 data_time: 0.0070 memory: 5828 grad_norm: 3.0762 loss: 2.4095 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4095 2023/06/05 05:01:24 - mmengine - INFO - Epoch(train) [67][ 440/2569] lr: 4.0000e-02 eta: 15:54:12 time: 0.2652 data_time: 0.0074 memory: 5828 grad_norm: 3.1162 loss: 2.7305 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7305 2023/06/05 05:01:25 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:01:29 - mmengine - INFO - Epoch(train) [67][ 460/2569] lr: 4.0000e-02 eta: 15:54:07 time: 0.2644 data_time: 0.0077 memory: 5828 grad_norm: 3.1249 loss: 2.4257 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4257 2023/06/05 05:01:35 - mmengine - INFO - Epoch(train) [67][ 480/2569] lr: 4.0000e-02 eta: 15:54:02 time: 0.2755 data_time: 0.0077 memory: 5828 grad_norm: 3.1407 loss: 2.6475 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6475 2023/06/05 05:01:40 - mmengine - INFO - Epoch(train) [67][ 500/2569] lr: 4.0000e-02 eta: 15:53:56 time: 0.2585 data_time: 0.0071 memory: 5828 grad_norm: 3.1348 loss: 2.9283 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9283 2023/06/05 05:01:45 - mmengine - INFO - Epoch(train) [67][ 520/2569] lr: 4.0000e-02 eta: 15:53:51 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 3.0966 loss: 2.4309 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4309 2023/06/05 05:01:50 - mmengine - INFO - Epoch(train) [67][ 540/2569] lr: 4.0000e-02 eta: 15:53:46 time: 0.2580 data_time: 0.0072 memory: 5828 grad_norm: 3.1412 loss: 2.4270 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4270 2023/06/05 05:01:56 - mmengine - INFO - Epoch(train) [67][ 560/2569] lr: 4.0000e-02 eta: 15:53:40 time: 0.2621 data_time: 0.0076 memory: 5828 grad_norm: 3.0720 loss: 2.4864 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4864 2023/06/05 05:02:01 - mmengine - INFO - Epoch(train) [67][ 580/2569] lr: 4.0000e-02 eta: 15:53:35 time: 0.2620 data_time: 0.0076 memory: 5828 grad_norm: 3.2420 loss: 2.5725 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5725 2023/06/05 05:02:06 - mmengine - INFO - Epoch(train) [67][ 600/2569] lr: 4.0000e-02 eta: 15:53:29 time: 0.2604 data_time: 0.0072 memory: 5828 grad_norm: 3.1050 loss: 2.6375 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6375 2023/06/05 05:02:11 - mmengine - INFO - Epoch(train) [67][ 620/2569] lr: 4.0000e-02 eta: 15:53:24 time: 0.2637 data_time: 0.0076 memory: 5828 grad_norm: 3.0314 loss: 2.6291 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6291 2023/06/05 05:02:17 - mmengine - INFO - Epoch(train) [67][ 640/2569] lr: 4.0000e-02 eta: 15:53:19 time: 0.2591 data_time: 0.0076 memory: 5828 grad_norm: 3.1381 loss: 2.4484 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4484 2023/06/05 05:02:22 - mmengine - INFO - Epoch(train) [67][ 660/2569] lr: 4.0000e-02 eta: 15:53:13 time: 0.2604 data_time: 0.0076 memory: 5828 grad_norm: 3.1687 loss: 2.5569 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5569 2023/06/05 05:02:27 - mmengine - INFO - Epoch(train) [67][ 680/2569] lr: 4.0000e-02 eta: 15:53:08 time: 0.2636 data_time: 0.0072 memory: 5828 grad_norm: 3.0713 loss: 2.4579 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4579 2023/06/05 05:02:32 - mmengine - INFO - Epoch(train) [67][ 700/2569] lr: 4.0000e-02 eta: 15:53:02 time: 0.2621 data_time: 0.0080 memory: 5828 grad_norm: 3.0768 loss: 2.4850 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4850 2023/06/05 05:02:37 - mmengine - INFO - Epoch(train) [67][ 720/2569] lr: 4.0000e-02 eta: 15:52:57 time: 0.2581 data_time: 0.0075 memory: 5828 grad_norm: 3.1280 loss: 2.8146 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8146 2023/06/05 05:02:43 - mmengine - INFO - Epoch(train) [67][ 740/2569] lr: 4.0000e-02 eta: 15:52:51 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.1643 loss: 2.2826 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2826 2023/06/05 05:02:48 - mmengine - INFO - Epoch(train) [67][ 760/2569] lr: 4.0000e-02 eta: 15:52:46 time: 0.2587 data_time: 0.0079 memory: 5828 grad_norm: 3.1129 loss: 2.5304 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5304 2023/06/05 05:02:53 - mmengine - INFO - Epoch(train) [67][ 780/2569] lr: 4.0000e-02 eta: 15:52:41 time: 0.2646 data_time: 0.0071 memory: 5828 grad_norm: 3.1185 loss: 2.4179 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4179 2023/06/05 05:02:58 - mmengine - INFO - Epoch(train) [67][ 800/2569] lr: 4.0000e-02 eta: 15:52:35 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 3.1870 loss: 2.3405 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3405 2023/06/05 05:03:04 - mmengine - INFO - Epoch(train) [67][ 820/2569] lr: 4.0000e-02 eta: 15:52:30 time: 0.2587 data_time: 0.0070 memory: 5828 grad_norm: 3.0699 loss: 2.5109 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5109 2023/06/05 05:03:09 - mmengine - INFO - Epoch(train) [67][ 840/2569] lr: 4.0000e-02 eta: 15:52:24 time: 0.2574 data_time: 0.0074 memory: 5828 grad_norm: 3.0668 loss: 2.6882 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6882 2023/06/05 05:03:14 - mmengine - INFO - Epoch(train) [67][ 860/2569] lr: 4.0000e-02 eta: 15:52:19 time: 0.2662 data_time: 0.0076 memory: 5828 grad_norm: 3.1054 loss: 2.5765 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5765 2023/06/05 05:03:20 - mmengine - INFO - Epoch(train) [67][ 880/2569] lr: 4.0000e-02 eta: 15:52:14 time: 0.2838 data_time: 0.0074 memory: 5828 grad_norm: 3.1521 loss: 2.7438 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7438 2023/06/05 05:03:25 - mmengine - INFO - Epoch(train) [67][ 900/2569] lr: 4.0000e-02 eta: 15:52:09 time: 0.2688 data_time: 0.0077 memory: 5828 grad_norm: 3.1227 loss: 2.4514 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4514 2023/06/05 05:03:30 - mmengine - INFO - Epoch(train) [67][ 920/2569] lr: 4.0000e-02 eta: 15:52:03 time: 0.2649 data_time: 0.0076 memory: 5828 grad_norm: 3.0882 loss: 2.7214 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7214 2023/06/05 05:03:36 - mmengine - INFO - Epoch(train) [67][ 940/2569] lr: 4.0000e-02 eta: 15:51:58 time: 0.2630 data_time: 0.0075 memory: 5828 grad_norm: 3.0747 loss: 2.1579 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1579 2023/06/05 05:03:41 - mmengine - INFO - Epoch(train) [67][ 960/2569] lr: 4.0000e-02 eta: 15:51:53 time: 0.2581 data_time: 0.0077 memory: 5828 grad_norm: 3.0922 loss: 2.6003 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6003 2023/06/05 05:03:46 - mmengine - INFO - Epoch(train) [67][ 980/2569] lr: 4.0000e-02 eta: 15:51:47 time: 0.2581 data_time: 0.0070 memory: 5828 grad_norm: 3.1185 loss: 2.7147 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7147 2023/06/05 05:03:51 - mmengine - INFO - Epoch(train) [67][1000/2569] lr: 4.0000e-02 eta: 15:51:42 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 3.1719 loss: 2.7443 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7443 2023/06/05 05:03:57 - mmengine - INFO - Epoch(train) [67][1020/2569] lr: 4.0000e-02 eta: 15:51:36 time: 0.2703 data_time: 0.0073 memory: 5828 grad_norm: 3.0496 loss: 2.6577 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6577 2023/06/05 05:04:02 - mmengine - INFO - Epoch(train) [67][1040/2569] lr: 4.0000e-02 eta: 15:51:31 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 3.0886 loss: 2.3660 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3660 2023/06/05 05:04:07 - mmengine - INFO - Epoch(train) [67][1060/2569] lr: 4.0000e-02 eta: 15:51:26 time: 0.2593 data_time: 0.0076 memory: 5828 grad_norm: 3.1637 loss: 2.6638 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6638 2023/06/05 05:04:13 - mmengine - INFO - Epoch(train) [67][1080/2569] lr: 4.0000e-02 eta: 15:51:20 time: 0.2690 data_time: 0.0073 memory: 5828 grad_norm: 3.1806 loss: 2.5687 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5687 2023/06/05 05:04:18 - mmengine - INFO - Epoch(train) [67][1100/2569] lr: 4.0000e-02 eta: 15:51:15 time: 0.2590 data_time: 0.0083 memory: 5828 grad_norm: 3.1179 loss: 2.6866 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6866 2023/06/05 05:04:23 - mmengine - INFO - Epoch(train) [67][1120/2569] lr: 4.0000e-02 eta: 15:51:09 time: 0.2583 data_time: 0.0082 memory: 5828 grad_norm: 3.0740 loss: 2.6661 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6661 2023/06/05 05:04:28 - mmengine - INFO - Epoch(train) [67][1140/2569] lr: 4.0000e-02 eta: 15:51:04 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 3.1154 loss: 2.2689 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2689 2023/06/05 05:04:34 - mmengine - INFO - Epoch(train) [67][1160/2569] lr: 4.0000e-02 eta: 15:50:59 time: 0.2585 data_time: 0.0076 memory: 5828 grad_norm: 3.1454 loss: 2.5047 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5047 2023/06/05 05:04:39 - mmengine - INFO - Epoch(train) [67][1180/2569] lr: 4.0000e-02 eta: 15:50:53 time: 0.2630 data_time: 0.0074 memory: 5828 grad_norm: 3.1343 loss: 2.6162 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6162 2023/06/05 05:04:44 - mmengine - INFO - Epoch(train) [67][1200/2569] lr: 4.0000e-02 eta: 15:50:48 time: 0.2577 data_time: 0.0075 memory: 5828 grad_norm: 3.1086 loss: 2.7766 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7766 2023/06/05 05:04:49 - mmengine - INFO - Epoch(train) [67][1220/2569] lr: 4.0000e-02 eta: 15:50:42 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 3.1268 loss: 2.2777 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2777 2023/06/05 05:04:54 - mmengine - INFO - Epoch(train) [67][1240/2569] lr: 4.0000e-02 eta: 15:50:37 time: 0.2595 data_time: 0.0075 memory: 5828 grad_norm: 3.1082 loss: 2.5069 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5069 2023/06/05 05:05:00 - mmengine - INFO - Epoch(train) [67][1260/2569] lr: 4.0000e-02 eta: 15:50:31 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 3.1388 loss: 2.6605 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6605 2023/06/05 05:05:05 - mmengine - INFO - Epoch(train) [67][1280/2569] lr: 4.0000e-02 eta: 15:50:27 time: 0.2836 data_time: 0.0075 memory: 5828 grad_norm: 3.1749 loss: 2.3435 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3435 2023/06/05 05:05:11 - mmengine - INFO - Epoch(train) [67][1300/2569] lr: 4.0000e-02 eta: 15:50:21 time: 0.2575 data_time: 0.0073 memory: 5828 grad_norm: 3.1560 loss: 2.6066 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.6066 2023/06/05 05:05:16 - mmengine - INFO - Epoch(train) [67][1320/2569] lr: 4.0000e-02 eta: 15:50:16 time: 0.2702 data_time: 0.0073 memory: 5828 grad_norm: 3.1041 loss: 2.4136 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4136 2023/06/05 05:05:21 - mmengine - INFO - Epoch(train) [67][1340/2569] lr: 4.0000e-02 eta: 15:50:10 time: 0.2639 data_time: 0.0072 memory: 5828 grad_norm: 3.1425 loss: 2.3788 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3788 2023/06/05 05:05:27 - mmengine - INFO - Epoch(train) [67][1360/2569] lr: 4.0000e-02 eta: 15:50:05 time: 0.2698 data_time: 0.0077 memory: 5828 grad_norm: 3.1375 loss: 2.4155 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4155 2023/06/05 05:05:32 - mmengine - INFO - Epoch(train) [67][1380/2569] lr: 4.0000e-02 eta: 15:50:00 time: 0.2698 data_time: 0.0074 memory: 5828 grad_norm: 3.0815 loss: 2.8245 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8245 2023/06/05 05:05:37 - mmengine - INFO - Epoch(train) [67][1400/2569] lr: 4.0000e-02 eta: 15:49:55 time: 0.2600 data_time: 0.0072 memory: 5828 grad_norm: 3.1560 loss: 2.5865 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5865 2023/06/05 05:05:43 - mmengine - INFO - Epoch(train) [67][1420/2569] lr: 4.0000e-02 eta: 15:49:49 time: 0.2672 data_time: 0.0076 memory: 5828 grad_norm: 3.1418 loss: 3.0228 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0228 2023/06/05 05:05:48 - mmengine - INFO - Epoch(train) [67][1440/2569] lr: 4.0000e-02 eta: 15:49:44 time: 0.2581 data_time: 0.0075 memory: 5828 grad_norm: 3.0443 loss: 2.6273 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6273 2023/06/05 05:05:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:05:53 - mmengine - INFO - Epoch(train) [67][1460/2569] lr: 4.0000e-02 eta: 15:49:39 time: 0.2719 data_time: 0.0076 memory: 5828 grad_norm: 3.1111 loss: 2.9261 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9261 2023/06/05 05:05:59 - mmengine - INFO - Epoch(train) [67][1480/2569] lr: 4.0000e-02 eta: 15:49:33 time: 0.2712 data_time: 0.0075 memory: 5828 grad_norm: 3.1246 loss: 2.4070 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4070 2023/06/05 05:06:04 - mmengine - INFO - Epoch(train) [67][1500/2569] lr: 4.0000e-02 eta: 15:49:28 time: 0.2639 data_time: 0.0076 memory: 5828 grad_norm: 3.1618 loss: 2.5660 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5660 2023/06/05 05:06:09 - mmengine - INFO - Epoch(train) [67][1520/2569] lr: 4.0000e-02 eta: 15:49:23 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 3.1368 loss: 2.1368 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1368 2023/06/05 05:06:15 - mmengine - INFO - Epoch(train) [67][1540/2569] lr: 4.0000e-02 eta: 15:49:18 time: 0.2668 data_time: 0.0074 memory: 5828 grad_norm: 3.1875 loss: 2.3612 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3612 2023/06/05 05:06:20 - mmengine - INFO - Epoch(train) [67][1560/2569] lr: 4.0000e-02 eta: 15:49:12 time: 0.2698 data_time: 0.0079 memory: 5828 grad_norm: 3.0577 loss: 2.1982 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1982 2023/06/05 05:06:26 - mmengine - INFO - Epoch(train) [67][1580/2569] lr: 4.0000e-02 eta: 15:49:07 time: 0.2728 data_time: 0.0074 memory: 5828 grad_norm: 3.0788 loss: 2.5287 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5287 2023/06/05 05:06:31 - mmengine - INFO - Epoch(train) [67][1600/2569] lr: 4.0000e-02 eta: 15:49:02 time: 0.2629 data_time: 0.0071 memory: 5828 grad_norm: 3.1505 loss: 2.5846 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5846 2023/06/05 05:06:36 - mmengine - INFO - Epoch(train) [67][1620/2569] lr: 4.0000e-02 eta: 15:48:57 time: 0.2696 data_time: 0.0071 memory: 5828 grad_norm: 3.0855 loss: 2.9526 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.9526 2023/06/05 05:06:41 - mmengine - INFO - Epoch(train) [67][1640/2569] lr: 4.0000e-02 eta: 15:48:51 time: 0.2638 data_time: 0.0082 memory: 5828 grad_norm: 3.0241 loss: 2.5272 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5272 2023/06/05 05:06:47 - mmengine - INFO - Epoch(train) [67][1660/2569] lr: 4.0000e-02 eta: 15:48:46 time: 0.2586 data_time: 0.0076 memory: 5828 grad_norm: 3.1375 loss: 2.3335 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3335 2023/06/05 05:06:52 - mmengine - INFO - Epoch(train) [67][1680/2569] lr: 4.0000e-02 eta: 15:48:40 time: 0.2683 data_time: 0.0074 memory: 5828 grad_norm: 3.0909 loss: 2.7205 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7205 2023/06/05 05:06:57 - mmengine - INFO - Epoch(train) [67][1700/2569] lr: 4.0000e-02 eta: 15:48:35 time: 0.2566 data_time: 0.0072 memory: 5828 grad_norm: 3.1473 loss: 2.8825 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8825 2023/06/05 05:07:02 - mmengine - INFO - Epoch(train) [67][1720/2569] lr: 4.0000e-02 eta: 15:48:30 time: 0.2655 data_time: 0.0073 memory: 5828 grad_norm: 3.1631 loss: 2.4919 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4919 2023/06/05 05:07:08 - mmengine - INFO - Epoch(train) [67][1740/2569] lr: 4.0000e-02 eta: 15:48:24 time: 0.2709 data_time: 0.0073 memory: 5828 grad_norm: 3.1131 loss: 2.4412 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4412 2023/06/05 05:07:13 - mmengine - INFO - Epoch(train) [67][1760/2569] lr: 4.0000e-02 eta: 15:48:19 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.1433 loss: 2.2821 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2821 2023/06/05 05:07:18 - mmengine - INFO - Epoch(train) [67][1780/2569] lr: 4.0000e-02 eta: 15:48:14 time: 0.2637 data_time: 0.0071 memory: 5828 grad_norm: 3.1381 loss: 2.3037 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3037 2023/06/05 05:07:24 - mmengine - INFO - Epoch(train) [67][1800/2569] lr: 4.0000e-02 eta: 15:48:08 time: 0.2577 data_time: 0.0073 memory: 5828 grad_norm: 3.1540 loss: 2.4343 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4343 2023/06/05 05:07:29 - mmengine - INFO - Epoch(train) [67][1820/2569] lr: 4.0000e-02 eta: 15:48:03 time: 0.2623 data_time: 0.0070 memory: 5828 grad_norm: 3.0897 loss: 2.5765 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5765 2023/06/05 05:07:34 - mmengine - INFO - Epoch(train) [67][1840/2569] lr: 4.0000e-02 eta: 15:47:57 time: 0.2566 data_time: 0.0076 memory: 5828 grad_norm: 3.1180 loss: 2.4304 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4304 2023/06/05 05:07:39 - mmengine - INFO - Epoch(train) [67][1860/2569] lr: 4.0000e-02 eta: 15:47:52 time: 0.2697 data_time: 0.0072 memory: 5828 grad_norm: 3.1327 loss: 2.4107 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4107 2023/06/05 05:07:45 - mmengine - INFO - Epoch(train) [67][1880/2569] lr: 4.0000e-02 eta: 15:47:46 time: 0.2581 data_time: 0.0081 memory: 5828 grad_norm: 3.0558 loss: 2.7183 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7183 2023/06/05 05:07:50 - mmengine - INFO - Epoch(train) [67][1900/2569] lr: 4.0000e-02 eta: 15:47:41 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 3.1564 loss: 2.4357 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4357 2023/06/05 05:07:55 - mmengine - INFO - Epoch(train) [67][1920/2569] lr: 4.0000e-02 eta: 15:47:36 time: 0.2578 data_time: 0.0072 memory: 5828 grad_norm: 3.2149 loss: 2.7368 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7368 2023/06/05 05:08:00 - mmengine - INFO - Epoch(train) [67][1940/2569] lr: 4.0000e-02 eta: 15:47:30 time: 0.2663 data_time: 0.0075 memory: 5828 grad_norm: 3.1014 loss: 2.4037 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4037 2023/06/05 05:08:06 - mmengine - INFO - Epoch(train) [67][1960/2569] lr: 4.0000e-02 eta: 15:47:25 time: 0.2582 data_time: 0.0074 memory: 5828 grad_norm: 3.1600 loss: 2.5764 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5764 2023/06/05 05:08:11 - mmengine - INFO - Epoch(train) [67][1980/2569] lr: 4.0000e-02 eta: 15:47:19 time: 0.2572 data_time: 0.0082 memory: 5828 grad_norm: 3.1165 loss: 2.5235 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5235 2023/06/05 05:08:16 - mmengine - INFO - Epoch(train) [67][2000/2569] lr: 4.0000e-02 eta: 15:47:14 time: 0.2635 data_time: 0.0076 memory: 5828 grad_norm: 3.0801 loss: 2.5041 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5041 2023/06/05 05:08:21 - mmengine - INFO - Epoch(train) [67][2020/2569] lr: 4.0000e-02 eta: 15:47:08 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 3.0744 loss: 2.2969 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2969 2023/06/05 05:08:27 - mmengine - INFO - Epoch(train) [67][2040/2569] lr: 4.0000e-02 eta: 15:47:03 time: 0.2713 data_time: 0.0073 memory: 5828 grad_norm: 3.1235 loss: 2.4115 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4115 2023/06/05 05:08:32 - mmengine - INFO - Epoch(train) [67][2060/2569] lr: 4.0000e-02 eta: 15:46:58 time: 0.2566 data_time: 0.0074 memory: 5828 grad_norm: 3.0344 loss: 2.4867 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4867 2023/06/05 05:08:37 - mmengine - INFO - Epoch(train) [67][2080/2569] lr: 4.0000e-02 eta: 15:46:52 time: 0.2603 data_time: 0.0076 memory: 5828 grad_norm: 3.1878 loss: 2.7120 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7120 2023/06/05 05:08:42 - mmengine - INFO - Epoch(train) [67][2100/2569] lr: 4.0000e-02 eta: 15:46:47 time: 0.2605 data_time: 0.0072 memory: 5828 grad_norm: 3.1614 loss: 2.5026 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5026 2023/06/05 05:08:48 - mmengine - INFO - Epoch(train) [67][2120/2569] lr: 4.0000e-02 eta: 15:46:42 time: 0.2803 data_time: 0.0073 memory: 5828 grad_norm: 3.0919 loss: 2.6669 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6669 2023/06/05 05:08:53 - mmengine - INFO - Epoch(train) [67][2140/2569] lr: 4.0000e-02 eta: 15:46:36 time: 0.2583 data_time: 0.0079 memory: 5828 grad_norm: 3.2122 loss: 2.3660 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3660 2023/06/05 05:08:58 - mmengine - INFO - Epoch(train) [67][2160/2569] lr: 4.0000e-02 eta: 15:46:31 time: 0.2629 data_time: 0.0074 memory: 5828 grad_norm: 3.0724 loss: 2.4135 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4135 2023/06/05 05:09:04 - mmengine - INFO - Epoch(train) [67][2180/2569] lr: 4.0000e-02 eta: 15:46:26 time: 0.2638 data_time: 0.0075 memory: 5828 grad_norm: 3.0929 loss: 2.6604 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6604 2023/06/05 05:09:09 - mmengine - INFO - Epoch(train) [67][2200/2569] lr: 4.0000e-02 eta: 15:46:20 time: 0.2683 data_time: 0.0071 memory: 5828 grad_norm: 3.1878 loss: 2.1995 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.1995 2023/06/05 05:09:14 - mmengine - INFO - Epoch(train) [67][2220/2569] lr: 4.0000e-02 eta: 15:46:15 time: 0.2598 data_time: 0.0076 memory: 5828 grad_norm: 3.1868 loss: 2.8574 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8574 2023/06/05 05:09:19 - mmengine - INFO - Epoch(train) [67][2240/2569] lr: 4.0000e-02 eta: 15:46:10 time: 0.2694 data_time: 0.0074 memory: 5828 grad_norm: 3.1836 loss: 2.6362 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6362 2023/06/05 05:09:25 - mmengine - INFO - Epoch(train) [67][2260/2569] lr: 4.0000e-02 eta: 15:46:04 time: 0.2695 data_time: 0.0073 memory: 5828 grad_norm: 3.1061 loss: 2.5452 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5452 2023/06/05 05:09:30 - mmengine - INFO - Epoch(train) [67][2280/2569] lr: 4.0000e-02 eta: 15:45:59 time: 0.2577 data_time: 0.0074 memory: 5828 grad_norm: 3.1338 loss: 2.9127 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9127 2023/06/05 05:09:35 - mmengine - INFO - Epoch(train) [67][2300/2569] lr: 4.0000e-02 eta: 15:45:54 time: 0.2662 data_time: 0.0075 memory: 5828 grad_norm: 3.1117 loss: 2.8954 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8954 2023/06/05 05:09:41 - mmengine - INFO - Epoch(train) [67][2320/2569] lr: 4.0000e-02 eta: 15:45:48 time: 0.2616 data_time: 0.0077 memory: 5828 grad_norm: 3.1848 loss: 2.5506 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5506 2023/06/05 05:09:46 - mmengine - INFO - Epoch(train) [67][2340/2569] lr: 4.0000e-02 eta: 15:45:43 time: 0.2669 data_time: 0.0075 memory: 5828 grad_norm: 3.1097 loss: 2.5563 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5563 2023/06/05 05:09:51 - mmengine - INFO - Epoch(train) [67][2360/2569] lr: 4.0000e-02 eta: 15:45:37 time: 0.2631 data_time: 0.0076 memory: 5828 grad_norm: 3.1373 loss: 2.4729 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4729 2023/06/05 05:09:56 - mmengine - INFO - Epoch(train) [67][2380/2569] lr: 4.0000e-02 eta: 15:45:32 time: 0.2582 data_time: 0.0073 memory: 5828 grad_norm: 3.1164 loss: 2.5189 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5189 2023/06/05 05:10:02 - mmengine - INFO - Epoch(train) [67][2400/2569] lr: 4.0000e-02 eta: 15:45:27 time: 0.2634 data_time: 0.0077 memory: 5828 grad_norm: 3.0923 loss: 2.6767 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.6767 2023/06/05 05:10:07 - mmengine - INFO - Epoch(train) [67][2420/2569] lr: 4.0000e-02 eta: 15:45:21 time: 0.2636 data_time: 0.0077 memory: 5828 grad_norm: 3.1416 loss: 2.6160 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6160 2023/06/05 05:10:12 - mmengine - INFO - Epoch(train) [67][2440/2569] lr: 4.0000e-02 eta: 15:45:16 time: 0.2606 data_time: 0.0075 memory: 5828 grad_norm: 3.1898 loss: 2.7833 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7833 2023/06/05 05:10:14 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:10:17 - mmengine - INFO - Epoch(train) [67][2460/2569] lr: 4.0000e-02 eta: 15:45:10 time: 0.2602 data_time: 0.0068 memory: 5828 grad_norm: 3.0105 loss: 2.7405 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7405 2023/06/05 05:10:23 - mmengine - INFO - Epoch(train) [67][2480/2569] lr: 4.0000e-02 eta: 15:45:05 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 3.1383 loss: 2.4512 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4512 2023/06/05 05:10:28 - mmengine - INFO - Epoch(train) [67][2500/2569] lr: 4.0000e-02 eta: 15:45:00 time: 0.2661 data_time: 0.0071 memory: 5828 grad_norm: 3.1496 loss: 2.7230 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7230 2023/06/05 05:10:33 - mmengine - INFO - Epoch(train) [67][2520/2569] lr: 4.0000e-02 eta: 15:44:54 time: 0.2581 data_time: 0.0076 memory: 5828 grad_norm: 3.0193 loss: 2.4592 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4592 2023/06/05 05:10:39 - mmengine - INFO - Epoch(train) [67][2540/2569] lr: 4.0000e-02 eta: 15:44:49 time: 0.2629 data_time: 0.0073 memory: 5828 grad_norm: 3.0548 loss: 2.6164 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6164 2023/06/05 05:10:44 - mmengine - INFO - Epoch(train) [67][2560/2569] lr: 4.0000e-02 eta: 15:44:43 time: 0.2559 data_time: 0.0076 memory: 5828 grad_norm: 3.1345 loss: 2.1657 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1657 2023/06/05 05:10:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:10:46 - mmengine - INFO - Epoch(train) [67][2569/2569] lr: 4.0000e-02 eta: 15:44:41 time: 0.2538 data_time: 0.0072 memory: 5828 grad_norm: 3.1428 loss: 2.3385 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.3385 2023/06/05 05:10:53 - mmengine - INFO - Epoch(train) [68][ 20/2569] lr: 4.0000e-02 eta: 15:44:37 time: 0.3417 data_time: 0.0478 memory: 5828 grad_norm: 3.0855 loss: 2.4471 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4471 2023/06/05 05:10:58 - mmengine - INFO - Epoch(train) [68][ 40/2569] lr: 4.0000e-02 eta: 15:44:32 time: 0.2641 data_time: 0.0076 memory: 5828 grad_norm: 3.0966 loss: 2.5505 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5505 2023/06/05 05:11:03 - mmengine - INFO - Epoch(train) [68][ 60/2569] lr: 4.0000e-02 eta: 15:44:26 time: 0.2602 data_time: 0.0076 memory: 5828 grad_norm: 3.1401 loss: 2.2636 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2636 2023/06/05 05:11:08 - mmengine - INFO - Epoch(train) [68][ 80/2569] lr: 4.0000e-02 eta: 15:44:21 time: 0.2590 data_time: 0.0072 memory: 5828 grad_norm: 3.1071 loss: 2.4989 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4989 2023/06/05 05:11:14 - mmengine - INFO - Epoch(train) [68][ 100/2569] lr: 4.0000e-02 eta: 15:44:16 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 3.0849 loss: 2.6869 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6869 2023/06/05 05:11:19 - mmengine - INFO - Epoch(train) [68][ 120/2569] lr: 4.0000e-02 eta: 15:44:10 time: 0.2581 data_time: 0.0071 memory: 5828 grad_norm: 3.1065 loss: 2.4341 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4341 2023/06/05 05:11:24 - mmengine - INFO - Epoch(train) [68][ 140/2569] lr: 4.0000e-02 eta: 15:44:05 time: 0.2595 data_time: 0.0073 memory: 5828 grad_norm: 3.1212 loss: 2.4123 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4123 2023/06/05 05:11:29 - mmengine - INFO - Epoch(train) [68][ 160/2569] lr: 4.0000e-02 eta: 15:43:59 time: 0.2635 data_time: 0.0083 memory: 5828 grad_norm: 3.1252 loss: 2.6598 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6598 2023/06/05 05:11:35 - mmengine - INFO - Epoch(train) [68][ 180/2569] lr: 4.0000e-02 eta: 15:43:54 time: 0.2585 data_time: 0.0074 memory: 5828 grad_norm: 3.1389 loss: 2.5291 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5291 2023/06/05 05:11:40 - mmengine - INFO - Epoch(train) [68][ 200/2569] lr: 4.0000e-02 eta: 15:43:48 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.0484 loss: 2.5627 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5627 2023/06/05 05:11:45 - mmengine - INFO - Epoch(train) [68][ 220/2569] lr: 4.0000e-02 eta: 15:43:43 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 3.1356 loss: 2.6181 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6181 2023/06/05 05:11:50 - mmengine - INFO - Epoch(train) [68][ 240/2569] lr: 4.0000e-02 eta: 15:43:38 time: 0.2591 data_time: 0.0069 memory: 5828 grad_norm: 3.1116 loss: 2.6357 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6357 2023/06/05 05:11:56 - mmengine - INFO - Epoch(train) [68][ 260/2569] lr: 4.0000e-02 eta: 15:43:32 time: 0.2700 data_time: 0.0074 memory: 5828 grad_norm: 3.1128 loss: 2.6079 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6079 2023/06/05 05:12:01 - mmengine - INFO - Epoch(train) [68][ 280/2569] lr: 4.0000e-02 eta: 15:43:27 time: 0.2664 data_time: 0.0072 memory: 5828 grad_norm: 3.1445 loss: 2.3536 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3536 2023/06/05 05:12:06 - mmengine - INFO - Epoch(train) [68][ 300/2569] lr: 4.0000e-02 eta: 15:43:22 time: 0.2687 data_time: 0.0074 memory: 5828 grad_norm: 3.1613 loss: 2.6851 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6851 2023/06/05 05:12:12 - mmengine - INFO - Epoch(train) [68][ 320/2569] lr: 4.0000e-02 eta: 15:43:17 time: 0.2673 data_time: 0.0070 memory: 5828 grad_norm: 3.1421 loss: 2.6194 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6194 2023/06/05 05:12:17 - mmengine - INFO - Epoch(train) [68][ 340/2569] lr: 4.0000e-02 eta: 15:43:11 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 3.0531 loss: 2.4864 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4864 2023/06/05 05:12:22 - mmengine - INFO - Epoch(train) [68][ 360/2569] lr: 4.0000e-02 eta: 15:43:06 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 3.1201 loss: 2.8329 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8329 2023/06/05 05:12:28 - mmengine - INFO - Epoch(train) [68][ 380/2569] lr: 4.0000e-02 eta: 15:43:00 time: 0.2581 data_time: 0.0070 memory: 5828 grad_norm: 3.1346 loss: 2.4603 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4603 2023/06/05 05:12:33 - mmengine - INFO - Epoch(train) [68][ 400/2569] lr: 4.0000e-02 eta: 15:42:55 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 3.1460 loss: 2.4241 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4241 2023/06/05 05:12:38 - mmengine - INFO - Epoch(train) [68][ 420/2569] lr: 4.0000e-02 eta: 15:42:50 time: 0.2590 data_time: 0.0072 memory: 5828 grad_norm: 3.0503 loss: 3.0066 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0066 2023/06/05 05:12:43 - mmengine - INFO - Epoch(train) [68][ 440/2569] lr: 4.0000e-02 eta: 15:42:44 time: 0.2588 data_time: 0.0072 memory: 5828 grad_norm: 3.0981 loss: 2.5936 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5936 2023/06/05 05:12:48 - mmengine - INFO - Epoch(train) [68][ 460/2569] lr: 4.0000e-02 eta: 15:42:39 time: 0.2586 data_time: 0.0074 memory: 5828 grad_norm: 3.1608 loss: 2.5213 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5213 2023/06/05 05:12:54 - mmengine - INFO - Epoch(train) [68][ 480/2569] lr: 4.0000e-02 eta: 15:42:33 time: 0.2630 data_time: 0.0078 memory: 5828 grad_norm: 3.0977 loss: 2.5639 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5639 2023/06/05 05:12:59 - mmengine - INFO - Epoch(train) [68][ 500/2569] lr: 4.0000e-02 eta: 15:42:28 time: 0.2594 data_time: 0.0075 memory: 5828 grad_norm: 3.2429 loss: 2.8676 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8676 2023/06/05 05:13:04 - mmengine - INFO - Epoch(train) [68][ 520/2569] lr: 4.0000e-02 eta: 15:42:22 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 3.1368 loss: 2.8048 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8048 2023/06/05 05:13:09 - mmengine - INFO - Epoch(train) [68][ 540/2569] lr: 4.0000e-02 eta: 15:42:17 time: 0.2597 data_time: 0.0074 memory: 5828 grad_norm: 3.0833 loss: 2.5573 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5573 2023/06/05 05:13:15 - mmengine - INFO - Epoch(train) [68][ 560/2569] lr: 4.0000e-02 eta: 15:42:12 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 3.0512 loss: 2.5864 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5864 2023/06/05 05:13:20 - mmengine - INFO - Epoch(train) [68][ 580/2569] lr: 4.0000e-02 eta: 15:42:06 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 3.0997 loss: 2.5004 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5004 2023/06/05 05:13:25 - mmengine - INFO - Epoch(train) [68][ 600/2569] lr: 4.0000e-02 eta: 15:42:01 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.1651 loss: 2.7129 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7129 2023/06/05 05:13:31 - mmengine - INFO - Epoch(train) [68][ 620/2569] lr: 4.0000e-02 eta: 15:41:55 time: 0.2694 data_time: 0.0071 memory: 5828 grad_norm: 3.1328 loss: 2.5952 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5952 2023/06/05 05:13:36 - mmengine - INFO - Epoch(train) [68][ 640/2569] lr: 4.0000e-02 eta: 15:41:50 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 3.1404 loss: 2.2192 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2192 2023/06/05 05:13:41 - mmengine - INFO - Epoch(train) [68][ 660/2569] lr: 4.0000e-02 eta: 15:41:45 time: 0.2630 data_time: 0.0071 memory: 5828 grad_norm: 3.1256 loss: 2.1603 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1603 2023/06/05 05:13:47 - mmengine - INFO - Epoch(train) [68][ 680/2569] lr: 4.0000e-02 eta: 15:41:40 time: 0.2741 data_time: 0.0076 memory: 5828 grad_norm: 3.0462 loss: 2.5112 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5112 2023/06/05 05:13:52 - mmengine - INFO - Epoch(train) [68][ 700/2569] lr: 4.0000e-02 eta: 15:41:35 time: 0.2763 data_time: 0.0074 memory: 5828 grad_norm: 3.1123 loss: 2.6990 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6990 2023/06/05 05:13:58 - mmengine - INFO - Epoch(train) [68][ 720/2569] lr: 4.0000e-02 eta: 15:41:29 time: 0.2696 data_time: 0.0072 memory: 5828 grad_norm: 3.0677 loss: 2.5999 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5999 2023/06/05 05:14:03 - mmengine - INFO - Epoch(train) [68][ 740/2569] lr: 4.0000e-02 eta: 15:41:24 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 3.1242 loss: 2.5897 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5897 2023/06/05 05:14:08 - mmengine - INFO - Epoch(train) [68][ 760/2569] lr: 4.0000e-02 eta: 15:41:19 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 3.1357 loss: 2.2740 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2740 2023/06/05 05:14:13 - mmengine - INFO - Epoch(train) [68][ 780/2569] lr: 4.0000e-02 eta: 15:41:13 time: 0.2703 data_time: 0.0081 memory: 5828 grad_norm: 3.1850 loss: 2.6009 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6009 2023/06/05 05:14:19 - mmengine - INFO - Epoch(train) [68][ 800/2569] lr: 4.0000e-02 eta: 15:41:08 time: 0.2731 data_time: 0.0076 memory: 5828 grad_norm: 3.1663 loss: 2.6521 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6521 2023/06/05 05:14:24 - mmengine - INFO - Epoch(train) [68][ 820/2569] lr: 4.0000e-02 eta: 15:41:03 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 3.1596 loss: 2.8644 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.8644 2023/06/05 05:14:30 - mmengine - INFO - Epoch(train) [68][ 840/2569] lr: 4.0000e-02 eta: 15:40:57 time: 0.2643 data_time: 0.0076 memory: 5828 grad_norm: 3.1503 loss: 2.6527 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6527 2023/06/05 05:14:35 - mmengine - INFO - Epoch(train) [68][ 860/2569] lr: 4.0000e-02 eta: 15:40:52 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 3.1309 loss: 2.5442 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5442 2023/06/05 05:14:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:14:40 - mmengine - INFO - Epoch(train) [68][ 880/2569] lr: 4.0000e-02 eta: 15:40:47 time: 0.2640 data_time: 0.0076 memory: 5828 grad_norm: 3.1339 loss: 2.5240 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5240 2023/06/05 05:14:46 - mmengine - INFO - Epoch(train) [68][ 900/2569] lr: 4.0000e-02 eta: 15:40:42 time: 0.2698 data_time: 0.0073 memory: 5828 grad_norm: 3.1977 loss: 2.3500 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3500 2023/06/05 05:14:51 - mmengine - INFO - Epoch(train) [68][ 920/2569] lr: 4.0000e-02 eta: 15:40:36 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 3.1545 loss: 2.3461 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3461 2023/06/05 05:14:56 - mmengine - INFO - Epoch(train) [68][ 940/2569] lr: 4.0000e-02 eta: 15:40:31 time: 0.2752 data_time: 0.0077 memory: 5828 grad_norm: 3.0836 loss: 2.4504 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4504 2023/06/05 05:15:02 - mmengine - INFO - Epoch(train) [68][ 960/2569] lr: 4.0000e-02 eta: 15:40:26 time: 0.2638 data_time: 0.0077 memory: 5828 grad_norm: 3.0848 loss: 2.6433 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6433 2023/06/05 05:15:07 - mmengine - INFO - Epoch(train) [68][ 980/2569] lr: 4.0000e-02 eta: 15:40:21 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 3.1203 loss: 2.4154 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4154 2023/06/05 05:15:12 - mmengine - INFO - Epoch(train) [68][1000/2569] lr: 4.0000e-02 eta: 15:40:15 time: 0.2701 data_time: 0.0076 memory: 5828 grad_norm: 3.1097 loss: 2.5191 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5191 2023/06/05 05:15:18 - mmengine - INFO - Epoch(train) [68][1020/2569] lr: 4.0000e-02 eta: 15:40:10 time: 0.2825 data_time: 0.0074 memory: 5828 grad_norm: 3.1445 loss: 2.5487 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5487 2023/06/05 05:15:23 - mmengine - INFO - Epoch(train) [68][1040/2569] lr: 4.0000e-02 eta: 15:40:05 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 3.0373 loss: 2.5179 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5179 2023/06/05 05:15:29 - mmengine - INFO - Epoch(train) [68][1060/2569] lr: 4.0000e-02 eta: 15:40:00 time: 0.2684 data_time: 0.0071 memory: 5828 grad_norm: 3.1302 loss: 2.5593 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5593 2023/06/05 05:15:34 - mmengine - INFO - Epoch(train) [68][1080/2569] lr: 4.0000e-02 eta: 15:39:54 time: 0.2586 data_time: 0.0078 memory: 5828 grad_norm: 3.1848 loss: 2.4898 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4898 2023/06/05 05:15:39 - mmengine - INFO - Epoch(train) [68][1100/2569] lr: 4.0000e-02 eta: 15:39:49 time: 0.2692 data_time: 0.0074 memory: 5828 grad_norm: 3.1411 loss: 2.2288 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2288 2023/06/05 05:15:45 - mmengine - INFO - Epoch(train) [68][1120/2569] lr: 4.0000e-02 eta: 15:39:44 time: 0.2603 data_time: 0.0075 memory: 5828 grad_norm: 3.1272 loss: 2.4453 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4453 2023/06/05 05:15:50 - mmengine - INFO - Epoch(train) [68][1140/2569] lr: 4.0000e-02 eta: 15:39:38 time: 0.2593 data_time: 0.0072 memory: 5828 grad_norm: 3.1468 loss: 2.5831 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5831 2023/06/05 05:15:55 - mmengine - INFO - Epoch(train) [68][1160/2569] lr: 4.0000e-02 eta: 15:39:33 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 3.1096 loss: 2.5217 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5217 2023/06/05 05:16:00 - mmengine - INFO - Epoch(train) [68][1180/2569] lr: 4.0000e-02 eta: 15:39:28 time: 0.2650 data_time: 0.0071 memory: 5828 grad_norm: 3.1422 loss: 2.6011 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6011 2023/06/05 05:16:06 - mmengine - INFO - Epoch(train) [68][1200/2569] lr: 4.0000e-02 eta: 15:39:22 time: 0.2594 data_time: 0.0077 memory: 5828 grad_norm: 3.1219 loss: 2.4355 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4355 2023/06/05 05:16:11 - mmengine - INFO - Epoch(train) [68][1220/2569] lr: 4.0000e-02 eta: 15:39:17 time: 0.2635 data_time: 0.0075 memory: 5828 grad_norm: 3.1511 loss: 2.4091 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4091 2023/06/05 05:16:16 - mmengine - INFO - Epoch(train) [68][1240/2569] lr: 4.0000e-02 eta: 15:39:11 time: 0.2651 data_time: 0.0077 memory: 5828 grad_norm: 3.1131 loss: 2.6947 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6947 2023/06/05 05:16:21 - mmengine - INFO - Epoch(train) [68][1260/2569] lr: 4.0000e-02 eta: 15:39:06 time: 0.2636 data_time: 0.0070 memory: 5828 grad_norm: 3.1800 loss: 2.4759 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4759 2023/06/05 05:16:27 - mmengine - INFO - Epoch(train) [68][1280/2569] lr: 4.0000e-02 eta: 15:39:01 time: 0.2597 data_time: 0.0076 memory: 5828 grad_norm: 3.1007 loss: 2.3467 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3467 2023/06/05 05:16:32 - mmengine - INFO - Epoch(train) [68][1300/2569] lr: 4.0000e-02 eta: 15:38:55 time: 0.2664 data_time: 0.0078 memory: 5828 grad_norm: 3.1902 loss: 2.2358 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2358 2023/06/05 05:16:37 - mmengine - INFO - Epoch(train) [68][1320/2569] lr: 4.0000e-02 eta: 15:38:50 time: 0.2707 data_time: 0.0076 memory: 5828 grad_norm: 3.1584 loss: 2.3336 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3336 2023/06/05 05:16:43 - mmengine - INFO - Epoch(train) [68][1340/2569] lr: 4.0000e-02 eta: 15:38:45 time: 0.2648 data_time: 0.0071 memory: 5828 grad_norm: 3.1166 loss: 2.3420 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3420 2023/06/05 05:16:48 - mmengine - INFO - Epoch(train) [68][1360/2569] lr: 4.0000e-02 eta: 15:38:40 time: 0.2738 data_time: 0.0071 memory: 5828 grad_norm: 3.1486 loss: 2.6603 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6603 2023/06/05 05:16:53 - mmengine - INFO - Epoch(train) [68][1380/2569] lr: 4.0000e-02 eta: 15:38:34 time: 0.2618 data_time: 0.0070 memory: 5828 grad_norm: 3.1362 loss: 2.6949 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6949 2023/06/05 05:16:59 - mmengine - INFO - Epoch(train) [68][1400/2569] lr: 4.0000e-02 eta: 15:38:29 time: 0.2579 data_time: 0.0072 memory: 5828 grad_norm: 3.1140 loss: 2.5816 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5816 2023/06/05 05:17:04 - mmengine - INFO - Epoch(train) [68][1420/2569] lr: 4.0000e-02 eta: 15:38:24 time: 0.2738 data_time: 0.0070 memory: 5828 grad_norm: 3.1490 loss: 2.5102 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5102 2023/06/05 05:17:09 - mmengine - INFO - Epoch(train) [68][1440/2569] lr: 4.0000e-02 eta: 15:38:18 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.0808 loss: 2.5284 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5284 2023/06/05 05:17:15 - mmengine - INFO - Epoch(train) [68][1460/2569] lr: 4.0000e-02 eta: 15:38:13 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 3.1446 loss: 2.3870 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3870 2023/06/05 05:17:20 - mmengine - INFO - Epoch(train) [68][1480/2569] lr: 4.0000e-02 eta: 15:38:08 time: 0.2726 data_time: 0.0076 memory: 5828 grad_norm: 3.1457 loss: 2.4549 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4549 2023/06/05 05:17:25 - mmengine - INFO - Epoch(train) [68][1500/2569] lr: 4.0000e-02 eta: 15:38:02 time: 0.2639 data_time: 0.0076 memory: 5828 grad_norm: 3.1493 loss: 2.3710 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3710 2023/06/05 05:17:31 - mmengine - INFO - Epoch(train) [68][1520/2569] lr: 4.0000e-02 eta: 15:37:57 time: 0.2704 data_time: 0.0075 memory: 5828 grad_norm: 3.1243 loss: 2.6819 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6819 2023/06/05 05:17:36 - mmengine - INFO - Epoch(train) [68][1540/2569] lr: 4.0000e-02 eta: 15:37:52 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 3.1407 loss: 2.4973 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4973 2023/06/05 05:17:41 - mmengine - INFO - Epoch(train) [68][1560/2569] lr: 4.0000e-02 eta: 15:37:46 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 3.1734 loss: 2.4855 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4855 2023/06/05 05:17:47 - mmengine - INFO - Epoch(train) [68][1580/2569] lr: 4.0000e-02 eta: 15:37:41 time: 0.2622 data_time: 0.0074 memory: 5828 grad_norm: 3.1338 loss: 2.7270 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7270 2023/06/05 05:17:52 - mmengine - INFO - Epoch(train) [68][1600/2569] lr: 4.0000e-02 eta: 15:37:36 time: 0.2643 data_time: 0.0077 memory: 5828 grad_norm: 3.1196 loss: 2.3589 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3589 2023/06/05 05:17:57 - mmengine - INFO - Epoch(train) [68][1620/2569] lr: 4.0000e-02 eta: 15:37:30 time: 0.2637 data_time: 0.0070 memory: 5828 grad_norm: 3.1149 loss: 2.6827 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6827 2023/06/05 05:18:03 - mmengine - INFO - Epoch(train) [68][1640/2569] lr: 4.0000e-02 eta: 15:37:25 time: 0.2642 data_time: 0.0072 memory: 5828 grad_norm: 3.1030 loss: 2.7632 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7632 2023/06/05 05:18:08 - mmengine - INFO - Epoch(train) [68][1660/2569] lr: 4.0000e-02 eta: 15:37:20 time: 0.2635 data_time: 0.0074 memory: 5828 grad_norm: 3.1052 loss: 2.6195 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6195 2023/06/05 05:18:13 - mmengine - INFO - Epoch(train) [68][1680/2569] lr: 4.0000e-02 eta: 15:37:14 time: 0.2630 data_time: 0.0076 memory: 5828 grad_norm: 3.1583 loss: 2.3784 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3784 2023/06/05 05:18:18 - mmengine - INFO - Epoch(train) [68][1700/2569] lr: 4.0000e-02 eta: 15:37:09 time: 0.2582 data_time: 0.0079 memory: 5828 grad_norm: 3.1451 loss: 2.4254 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4254 2023/06/05 05:18:24 - mmengine - INFO - Epoch(train) [68][1720/2569] lr: 4.0000e-02 eta: 15:37:03 time: 0.2694 data_time: 0.0073 memory: 5828 grad_norm: 3.1332 loss: 2.8131 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8131 2023/06/05 05:18:29 - mmengine - INFO - Epoch(train) [68][1740/2569] lr: 4.0000e-02 eta: 15:36:58 time: 0.2606 data_time: 0.0070 memory: 5828 grad_norm: 3.1592 loss: 2.5648 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5648 2023/06/05 05:18:34 - mmengine - INFO - Epoch(train) [68][1760/2569] lr: 4.0000e-02 eta: 15:36:53 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 3.1221 loss: 2.5086 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5086 2023/06/05 05:18:39 - mmengine - INFO - Epoch(train) [68][1780/2569] lr: 4.0000e-02 eta: 15:36:47 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.0734 loss: 2.6961 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6961 2023/06/05 05:18:45 - mmengine - INFO - Epoch(train) [68][1800/2569] lr: 4.0000e-02 eta: 15:36:42 time: 0.2627 data_time: 0.0075 memory: 5828 grad_norm: 3.1297 loss: 2.1605 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1605 2023/06/05 05:18:50 - mmengine - INFO - Epoch(train) [68][1820/2569] lr: 4.0000e-02 eta: 15:36:37 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.1439 loss: 2.5188 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5188 2023/06/05 05:18:55 - mmengine - INFO - Epoch(train) [68][1840/2569] lr: 4.0000e-02 eta: 15:36:31 time: 0.2592 data_time: 0.0073 memory: 5828 grad_norm: 3.0832 loss: 2.6608 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6608 2023/06/05 05:19:00 - mmengine - INFO - Epoch(train) [68][1860/2569] lr: 4.0000e-02 eta: 15:36:26 time: 0.2630 data_time: 0.0074 memory: 5828 grad_norm: 3.0880 loss: 2.5967 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5967 2023/06/05 05:19:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:19:06 - mmengine - INFO - Epoch(train) [68][1880/2569] lr: 4.0000e-02 eta: 15:36:20 time: 0.2582 data_time: 0.0074 memory: 5828 grad_norm: 3.1023 loss: 2.4058 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4058 2023/06/05 05:19:11 - mmengine - INFO - Epoch(train) [68][1900/2569] lr: 4.0000e-02 eta: 15:36:15 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 3.1994 loss: 2.4694 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4694 2023/06/05 05:19:16 - mmengine - INFO - Epoch(train) [68][1920/2569] lr: 4.0000e-02 eta: 15:36:09 time: 0.2571 data_time: 0.0072 memory: 5828 grad_norm: 3.1191 loss: 2.4326 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4326 2023/06/05 05:19:21 - mmengine - INFO - Epoch(train) [68][1940/2569] lr: 4.0000e-02 eta: 15:36:04 time: 0.2585 data_time: 0.0076 memory: 5828 grad_norm: 3.1703 loss: 2.3647 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3647 2023/06/05 05:19:27 - mmengine - INFO - Epoch(train) [68][1960/2569] lr: 4.0000e-02 eta: 15:35:58 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 3.1247 loss: 2.7582 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7582 2023/06/05 05:19:32 - mmengine - INFO - Epoch(train) [68][1980/2569] lr: 4.0000e-02 eta: 15:35:53 time: 0.2633 data_time: 0.0071 memory: 5828 grad_norm: 3.1257 loss: 2.4373 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4373 2023/06/05 05:19:37 - mmengine - INFO - Epoch(train) [68][2000/2569] lr: 4.0000e-02 eta: 15:35:48 time: 0.2578 data_time: 0.0076 memory: 5828 grad_norm: 3.1509 loss: 2.5808 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5808 2023/06/05 05:19:42 - mmengine - INFO - Epoch(train) [68][2020/2569] lr: 4.0000e-02 eta: 15:35:42 time: 0.2674 data_time: 0.0080 memory: 5828 grad_norm: 3.1195 loss: 2.9994 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9994 2023/06/05 05:19:48 - mmengine - INFO - Epoch(train) [68][2040/2569] lr: 4.0000e-02 eta: 15:35:37 time: 0.2778 data_time: 0.0081 memory: 5828 grad_norm: 3.1925 loss: 2.6635 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6635 2023/06/05 05:19:53 - mmengine - INFO - Epoch(train) [68][2060/2569] lr: 4.0000e-02 eta: 15:35:32 time: 0.2639 data_time: 0.0079 memory: 5828 grad_norm: 3.2074 loss: 2.7334 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7334 2023/06/05 05:19:59 - mmengine - INFO - Epoch(train) [68][2080/2569] lr: 4.0000e-02 eta: 15:35:27 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 3.1482 loss: 2.4353 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4353 2023/06/05 05:20:04 - mmengine - INFO - Epoch(train) [68][2100/2569] lr: 4.0000e-02 eta: 15:35:21 time: 0.2603 data_time: 0.0074 memory: 5828 grad_norm: 3.1103 loss: 2.4525 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4525 2023/06/05 05:20:09 - mmengine - INFO - Epoch(train) [68][2120/2569] lr: 4.0000e-02 eta: 15:35:16 time: 0.2697 data_time: 0.0075 memory: 5828 grad_norm: 3.2350 loss: 2.6500 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6500 2023/06/05 05:20:14 - mmengine - INFO - Epoch(train) [68][2140/2569] lr: 4.0000e-02 eta: 15:35:11 time: 0.2587 data_time: 0.0073 memory: 5828 grad_norm: 3.0912 loss: 2.7035 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7035 2023/06/05 05:20:20 - mmengine - INFO - Epoch(train) [68][2160/2569] lr: 4.0000e-02 eta: 15:35:05 time: 0.2697 data_time: 0.0073 memory: 5828 grad_norm: 3.0817 loss: 2.4482 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4482 2023/06/05 05:20:25 - mmengine - INFO - Epoch(train) [68][2180/2569] lr: 4.0000e-02 eta: 15:35:00 time: 0.2597 data_time: 0.0069 memory: 5828 grad_norm: 3.1210 loss: 2.5862 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5862 2023/06/05 05:20:30 - mmengine - INFO - Epoch(train) [68][2200/2569] lr: 4.0000e-02 eta: 15:34:54 time: 0.2640 data_time: 0.0075 memory: 5828 grad_norm: 3.0827 loss: 2.1747 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1747 2023/06/05 05:20:35 - mmengine - INFO - Epoch(train) [68][2220/2569] lr: 4.0000e-02 eta: 15:34:49 time: 0.2583 data_time: 0.0073 memory: 5828 grad_norm: 3.1111 loss: 2.5930 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5930 2023/06/05 05:20:41 - mmengine - INFO - Epoch(train) [68][2240/2569] lr: 4.0000e-02 eta: 15:34:44 time: 0.2603 data_time: 0.0075 memory: 5828 grad_norm: 3.1469 loss: 2.1031 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1031 2023/06/05 05:20:46 - mmengine - INFO - Epoch(train) [68][2260/2569] lr: 4.0000e-02 eta: 15:34:38 time: 0.2665 data_time: 0.0078 memory: 5828 grad_norm: 3.1955 loss: 2.6949 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6949 2023/06/05 05:20:51 - mmengine - INFO - Epoch(train) [68][2280/2569] lr: 4.0000e-02 eta: 15:34:33 time: 0.2571 data_time: 0.0076 memory: 5828 grad_norm: 3.1427 loss: 2.6107 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.6107 2023/06/05 05:20:56 - mmengine - INFO - Epoch(train) [68][2300/2569] lr: 4.0000e-02 eta: 15:34:27 time: 0.2671 data_time: 0.0071 memory: 5828 grad_norm: 3.1387 loss: 2.7932 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7932 2023/06/05 05:21:02 - mmengine - INFO - Epoch(train) [68][2320/2569] lr: 4.0000e-02 eta: 15:34:22 time: 0.2643 data_time: 0.0076 memory: 5828 grad_norm: 3.1365 loss: 2.5856 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5856 2023/06/05 05:21:07 - mmengine - INFO - Epoch(train) [68][2340/2569] lr: 4.0000e-02 eta: 15:34:17 time: 0.2596 data_time: 0.0077 memory: 5828 grad_norm: 3.1269 loss: 2.3732 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3732 2023/06/05 05:21:12 - mmengine - INFO - Epoch(train) [68][2360/2569] lr: 4.0000e-02 eta: 15:34:11 time: 0.2648 data_time: 0.0081 memory: 5828 grad_norm: 3.1337 loss: 2.5918 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5918 2023/06/05 05:21:18 - mmengine - INFO - Epoch(train) [68][2380/2569] lr: 4.0000e-02 eta: 15:34:06 time: 0.2639 data_time: 0.0076 memory: 5828 grad_norm: 3.1179 loss: 2.4738 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4738 2023/06/05 05:21:23 - mmengine - INFO - Epoch(train) [68][2400/2569] lr: 4.0000e-02 eta: 15:34:01 time: 0.2636 data_time: 0.0076 memory: 5828 grad_norm: 3.0774 loss: 2.5177 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5177 2023/06/05 05:21:28 - mmengine - INFO - Epoch(train) [68][2420/2569] lr: 4.0000e-02 eta: 15:33:55 time: 0.2698 data_time: 0.0075 memory: 5828 grad_norm: 3.0862 loss: 2.7755 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7755 2023/06/05 05:21:34 - mmengine - INFO - Epoch(train) [68][2440/2569] lr: 4.0000e-02 eta: 15:33:50 time: 0.2637 data_time: 0.0075 memory: 5828 grad_norm: 3.0709 loss: 2.4293 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4293 2023/06/05 05:21:39 - mmengine - INFO - Epoch(train) [68][2460/2569] lr: 4.0000e-02 eta: 15:33:44 time: 0.2591 data_time: 0.0071 memory: 5828 grad_norm: 3.0710 loss: 2.7505 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7505 2023/06/05 05:21:44 - mmengine - INFO - Epoch(train) [68][2480/2569] lr: 4.0000e-02 eta: 15:33:39 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 3.1551 loss: 2.4669 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4669 2023/06/05 05:21:49 - mmengine - INFO - Epoch(train) [68][2500/2569] lr: 4.0000e-02 eta: 15:33:34 time: 0.2585 data_time: 0.0074 memory: 5828 grad_norm: 3.1104 loss: 2.6771 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6771 2023/06/05 05:21:55 - mmengine - INFO - Epoch(train) [68][2520/2569] lr: 4.0000e-02 eta: 15:33:28 time: 0.2700 data_time: 0.0070 memory: 5828 grad_norm: 3.0802 loss: 2.7191 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7191 2023/06/05 05:22:00 - mmengine - INFO - Epoch(train) [68][2540/2569] lr: 4.0000e-02 eta: 15:33:23 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 3.1052 loss: 2.5171 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5171 2023/06/05 05:22:05 - mmengine - INFO - Epoch(train) [68][2560/2569] lr: 4.0000e-02 eta: 15:33:18 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 3.1008 loss: 2.1354 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1354 2023/06/05 05:22:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:22:07 - mmengine - INFO - Epoch(train) [68][2569/2569] lr: 4.0000e-02 eta: 15:33:15 time: 0.2499 data_time: 0.0070 memory: 5828 grad_norm: 3.1340 loss: 2.3689 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.3689 2023/06/05 05:22:07 - mmengine - INFO - Saving checkpoint at 68 epochs 2023/06/05 05:22:15 - mmengine - INFO - Epoch(train) [69][ 20/2569] lr: 4.0000e-02 eta: 15:33:11 time: 0.3029 data_time: 0.0533 memory: 5828 grad_norm: 3.0958 loss: 2.4800 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4800 2023/06/05 05:22:21 - mmengine - INFO - Epoch(train) [69][ 40/2569] lr: 4.0000e-02 eta: 15:33:05 time: 0.2587 data_time: 0.0074 memory: 5828 grad_norm: 3.1895 loss: 2.6859 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6859 2023/06/05 05:22:26 - mmengine - INFO - Epoch(train) [69][ 60/2569] lr: 4.0000e-02 eta: 15:33:00 time: 0.2640 data_time: 0.0076 memory: 5828 grad_norm: 3.1903 loss: 2.4288 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4288 2023/06/05 05:22:31 - mmengine - INFO - Epoch(train) [69][ 80/2569] lr: 4.0000e-02 eta: 15:32:54 time: 0.2604 data_time: 0.0072 memory: 5828 grad_norm: 3.0920 loss: 2.6327 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6327 2023/06/05 05:22:36 - mmengine - INFO - Epoch(train) [69][ 100/2569] lr: 4.0000e-02 eta: 15:32:49 time: 0.2642 data_time: 0.0072 memory: 5828 grad_norm: 3.0659 loss: 2.0893 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0893 2023/06/05 05:22:42 - mmengine - INFO - Epoch(train) [69][ 120/2569] lr: 4.0000e-02 eta: 15:32:44 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 3.1074 loss: 2.5146 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5146 2023/06/05 05:22:47 - mmengine - INFO - Epoch(train) [69][ 140/2569] lr: 4.0000e-02 eta: 15:32:38 time: 0.2573 data_time: 0.0076 memory: 5828 grad_norm: 3.1159 loss: 2.5523 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5523 2023/06/05 05:22:52 - mmengine - INFO - Epoch(train) [69][ 160/2569] lr: 4.0000e-02 eta: 15:32:33 time: 0.2589 data_time: 0.0074 memory: 5828 grad_norm: 3.1536 loss: 2.5115 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5115 2023/06/05 05:22:57 - mmengine - INFO - Epoch(train) [69][ 180/2569] lr: 4.0000e-02 eta: 15:32:27 time: 0.2585 data_time: 0.0070 memory: 5828 grad_norm: 3.1469 loss: 2.4352 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4352 2023/06/05 05:23:03 - mmengine - INFO - Epoch(train) [69][ 200/2569] lr: 4.0000e-02 eta: 15:32:22 time: 0.2679 data_time: 0.0070 memory: 5828 grad_norm: 3.1259 loss: 2.3677 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.3677 2023/06/05 05:23:08 - mmengine - INFO - Epoch(train) [69][ 220/2569] lr: 4.0000e-02 eta: 15:32:17 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 3.0971 loss: 2.2217 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2217 2023/06/05 05:23:13 - mmengine - INFO - Epoch(train) [69][ 240/2569] lr: 4.0000e-02 eta: 15:32:11 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 3.2005 loss: 2.4778 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4778 2023/06/05 05:23:19 - mmengine - INFO - Epoch(train) [69][ 260/2569] lr: 4.0000e-02 eta: 15:32:06 time: 0.2748 data_time: 0.0072 memory: 5828 grad_norm: 3.0887 loss: 2.4024 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4024 2023/06/05 05:23:24 - mmengine - INFO - Epoch(train) [69][ 280/2569] lr: 4.0000e-02 eta: 15:32:01 time: 0.2715 data_time: 0.0072 memory: 5828 grad_norm: 3.1830 loss: 2.8731 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8731 2023/06/05 05:23:29 - mmengine - INFO - Epoch(train) [69][ 300/2569] lr: 4.0000e-02 eta: 15:31:56 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 3.1073 loss: 2.4833 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4833 2023/06/05 05:23:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:23:35 - mmengine - INFO - Epoch(train) [69][ 320/2569] lr: 4.0000e-02 eta: 15:31:50 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 3.1252 loss: 2.2511 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2511 2023/06/05 05:23:40 - mmengine - INFO - Epoch(train) [69][ 340/2569] lr: 4.0000e-02 eta: 15:31:45 time: 0.2610 data_time: 0.0070 memory: 5828 grad_norm: 3.1154 loss: 2.8008 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8008 2023/06/05 05:23:45 - mmengine - INFO - Epoch(train) [69][ 360/2569] lr: 4.0000e-02 eta: 15:31:39 time: 0.2590 data_time: 0.0076 memory: 5828 grad_norm: 3.1373 loss: 2.2559 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2559 2023/06/05 05:23:50 - mmengine - INFO - Epoch(train) [69][ 380/2569] lr: 4.0000e-02 eta: 15:31:34 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 3.1286 loss: 2.4578 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4578 2023/06/05 05:23:56 - mmengine - INFO - Epoch(train) [69][ 400/2569] lr: 4.0000e-02 eta: 15:31:28 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 3.1064 loss: 2.4094 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4094 2023/06/05 05:24:01 - mmengine - INFO - Epoch(train) [69][ 420/2569] lr: 4.0000e-02 eta: 15:31:23 time: 0.2590 data_time: 0.0074 memory: 5828 grad_norm: 3.1253 loss: 2.2983 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2983 2023/06/05 05:24:06 - mmengine - INFO - Epoch(train) [69][ 440/2569] lr: 4.0000e-02 eta: 15:31:18 time: 0.2703 data_time: 0.0077 memory: 5828 grad_norm: 3.0753 loss: 2.2636 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2636 2023/06/05 05:24:11 - mmengine - INFO - Epoch(train) [69][ 460/2569] lr: 4.0000e-02 eta: 15:31:12 time: 0.2611 data_time: 0.0072 memory: 5828 grad_norm: 3.1551 loss: 2.6262 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6262 2023/06/05 05:24:17 - mmengine - INFO - Epoch(train) [69][ 480/2569] lr: 4.0000e-02 eta: 15:31:07 time: 0.2589 data_time: 0.0074 memory: 5828 grad_norm: 3.1054 loss: 2.6048 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6048 2023/06/05 05:24:22 - mmengine - INFO - Epoch(train) [69][ 500/2569] lr: 4.0000e-02 eta: 15:31:01 time: 0.2584 data_time: 0.0075 memory: 5828 grad_norm: 3.1015 loss: 2.6397 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6397 2023/06/05 05:24:27 - mmengine - INFO - Epoch(train) [69][ 520/2569] lr: 4.0000e-02 eta: 15:30:56 time: 0.2662 data_time: 0.0074 memory: 5828 grad_norm: 3.1335 loss: 2.0777 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0777 2023/06/05 05:24:32 - mmengine - INFO - Epoch(train) [69][ 540/2569] lr: 4.0000e-02 eta: 15:30:51 time: 0.2589 data_time: 0.0074 memory: 5828 grad_norm: 3.1156 loss: 2.5839 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5839 2023/06/05 05:24:38 - mmengine - INFO - Epoch(train) [69][ 560/2569] lr: 4.0000e-02 eta: 15:30:45 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 3.1849 loss: 2.4124 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4124 2023/06/05 05:24:43 - mmengine - INFO - Epoch(train) [69][ 580/2569] lr: 4.0000e-02 eta: 15:30:40 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 3.1185 loss: 2.4983 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4983 2023/06/05 05:24:48 - mmengine - INFO - Epoch(train) [69][ 600/2569] lr: 4.0000e-02 eta: 15:30:35 time: 0.2715 data_time: 0.0072 memory: 5828 grad_norm: 3.1385 loss: 2.7597 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7597 2023/06/05 05:24:54 - mmengine - INFO - Epoch(train) [69][ 620/2569] lr: 4.0000e-02 eta: 15:30:29 time: 0.2640 data_time: 0.0072 memory: 5828 grad_norm: 3.1262 loss: 2.4692 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4692 2023/06/05 05:24:59 - mmengine - INFO - Epoch(train) [69][ 640/2569] lr: 4.0000e-02 eta: 15:30:24 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 3.0732 loss: 2.4380 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4380 2023/06/05 05:25:04 - mmengine - INFO - Epoch(train) [69][ 660/2569] lr: 4.0000e-02 eta: 15:30:19 time: 0.2555 data_time: 0.0072 memory: 5828 grad_norm: 3.1507 loss: 2.3915 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3915 2023/06/05 05:25:09 - mmengine - INFO - Epoch(train) [69][ 680/2569] lr: 4.0000e-02 eta: 15:30:13 time: 0.2698 data_time: 0.0074 memory: 5828 grad_norm: 3.0711 loss: 2.5021 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5021 2023/06/05 05:25:15 - mmengine - INFO - Epoch(train) [69][ 700/2569] lr: 4.0000e-02 eta: 15:30:08 time: 0.2662 data_time: 0.0071 memory: 5828 grad_norm: 3.1814 loss: 2.8598 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8598 2023/06/05 05:25:20 - mmengine - INFO - Epoch(train) [69][ 720/2569] lr: 4.0000e-02 eta: 15:30:02 time: 0.2581 data_time: 0.0074 memory: 5828 grad_norm: 3.1406 loss: 2.5720 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5720 2023/06/05 05:25:25 - mmengine - INFO - Epoch(train) [69][ 740/2569] lr: 4.0000e-02 eta: 15:29:57 time: 0.2590 data_time: 0.0076 memory: 5828 grad_norm: 3.0959 loss: 2.6067 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6067 2023/06/05 05:25:30 - mmengine - INFO - Epoch(train) [69][ 760/2569] lr: 4.0000e-02 eta: 15:29:52 time: 0.2631 data_time: 0.0076 memory: 5828 grad_norm: 3.1801 loss: 2.5186 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5186 2023/06/05 05:25:36 - mmengine - INFO - Epoch(train) [69][ 780/2569] lr: 4.0000e-02 eta: 15:29:46 time: 0.2687 data_time: 0.0072 memory: 5828 grad_norm: 3.1328 loss: 2.4787 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4787 2023/06/05 05:25:41 - mmengine - INFO - Epoch(train) [69][ 800/2569] lr: 4.0000e-02 eta: 15:29:41 time: 0.2603 data_time: 0.0080 memory: 5828 grad_norm: 3.1398 loss: 2.6665 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6665 2023/06/05 05:25:46 - mmengine - INFO - Epoch(train) [69][ 820/2569] lr: 4.0000e-02 eta: 15:29:36 time: 0.2645 data_time: 0.0082 memory: 5828 grad_norm: 3.0507 loss: 2.3852 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3852 2023/06/05 05:25:51 - mmengine - INFO - Epoch(train) [69][ 840/2569] lr: 4.0000e-02 eta: 15:29:30 time: 0.2605 data_time: 0.0076 memory: 5828 grad_norm: 3.1426 loss: 2.4341 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4341 2023/06/05 05:25:57 - mmengine - INFO - Epoch(train) [69][ 860/2569] lr: 4.0000e-02 eta: 15:29:25 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.1022 loss: 2.6604 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6604 2023/06/05 05:26:02 - mmengine - INFO - Epoch(train) [69][ 880/2569] lr: 4.0000e-02 eta: 15:29:20 time: 0.2713 data_time: 0.0071 memory: 5828 grad_norm: 3.1552 loss: 2.5745 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5745 2023/06/05 05:26:07 - mmengine - INFO - Epoch(train) [69][ 900/2569] lr: 4.0000e-02 eta: 15:29:14 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 3.0869 loss: 2.2571 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2571 2023/06/05 05:26:13 - mmengine - INFO - Epoch(train) [69][ 920/2569] lr: 4.0000e-02 eta: 15:29:09 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 3.0644 loss: 2.3943 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3943 2023/06/05 05:26:18 - mmengine - INFO - Epoch(train) [69][ 940/2569] lr: 4.0000e-02 eta: 15:29:04 time: 0.2689 data_time: 0.0070 memory: 5828 grad_norm: 3.1313 loss: 2.3313 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3313 2023/06/05 05:26:23 - mmengine - INFO - Epoch(train) [69][ 960/2569] lr: 4.0000e-02 eta: 15:28:58 time: 0.2650 data_time: 0.0073 memory: 5828 grad_norm: 3.1167 loss: 2.3546 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3546 2023/06/05 05:26:29 - mmengine - INFO - Epoch(train) [69][ 980/2569] lr: 4.0000e-02 eta: 15:28:53 time: 0.2687 data_time: 0.0075 memory: 5828 grad_norm: 3.1515 loss: 2.5816 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5816 2023/06/05 05:26:34 - mmengine - INFO - Epoch(train) [69][1000/2569] lr: 4.0000e-02 eta: 15:28:48 time: 0.2631 data_time: 0.0072 memory: 5828 grad_norm: 3.1441 loss: 2.5968 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5968 2023/06/05 05:26:39 - mmengine - INFO - Epoch(train) [69][1020/2569] lr: 4.0000e-02 eta: 15:28:42 time: 0.2664 data_time: 0.0075 memory: 5828 grad_norm: 3.1421 loss: 2.6659 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6659 2023/06/05 05:26:45 - mmengine - INFO - Epoch(train) [69][1040/2569] lr: 4.0000e-02 eta: 15:28:37 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 3.1097 loss: 2.5318 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5318 2023/06/05 05:26:50 - mmengine - INFO - Epoch(train) [69][1060/2569] lr: 4.0000e-02 eta: 15:28:32 time: 0.2585 data_time: 0.0075 memory: 5828 grad_norm: 3.1492 loss: 2.5776 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5776 2023/06/05 05:26:55 - mmengine - INFO - Epoch(train) [69][1080/2569] lr: 4.0000e-02 eta: 15:28:26 time: 0.2727 data_time: 0.0077 memory: 5828 grad_norm: 3.1300 loss: 2.5665 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5665 2023/06/05 05:27:01 - mmengine - INFO - Epoch(train) [69][1100/2569] lr: 4.0000e-02 eta: 15:28:21 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 3.1739 loss: 2.4612 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4612 2023/06/05 05:27:06 - mmengine - INFO - Epoch(train) [69][1120/2569] lr: 4.0000e-02 eta: 15:28:16 time: 0.2605 data_time: 0.0080 memory: 5828 grad_norm: 3.1660 loss: 2.7622 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.7622 2023/06/05 05:27:11 - mmengine - INFO - Epoch(train) [69][1140/2569] lr: 4.0000e-02 eta: 15:28:10 time: 0.2651 data_time: 0.0078 memory: 5828 grad_norm: 3.1167 loss: 2.5129 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5129 2023/06/05 05:27:17 - mmengine - INFO - Epoch(train) [69][1160/2569] lr: 4.0000e-02 eta: 15:28:05 time: 0.2775 data_time: 0.0074 memory: 5828 grad_norm: 3.1097 loss: 2.3946 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3946 2023/06/05 05:27:22 - mmengine - INFO - Epoch(train) [69][1180/2569] lr: 4.0000e-02 eta: 15:28:00 time: 0.2579 data_time: 0.0073 memory: 5828 grad_norm: 3.1323 loss: 2.5669 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5669 2023/06/05 05:27:27 - mmengine - INFO - Epoch(train) [69][1200/2569] lr: 4.0000e-02 eta: 15:27:54 time: 0.2633 data_time: 0.0072 memory: 5828 grad_norm: 3.1408 loss: 2.7882 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7882 2023/06/05 05:27:32 - mmengine - INFO - Epoch(train) [69][1220/2569] lr: 4.0000e-02 eta: 15:27:49 time: 0.2583 data_time: 0.0073 memory: 5828 grad_norm: 3.1816 loss: 2.6042 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6042 2023/06/05 05:27:38 - mmengine - INFO - Epoch(train) [69][1240/2569] lr: 4.0000e-02 eta: 15:27:43 time: 0.2588 data_time: 0.0075 memory: 5828 grad_norm: 3.1459 loss: 2.3708 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3708 2023/06/05 05:27:43 - mmengine - INFO - Epoch(train) [69][1260/2569] lr: 4.0000e-02 eta: 15:27:38 time: 0.2611 data_time: 0.0072 memory: 5828 grad_norm: 3.1455 loss: 2.5263 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5263 2023/06/05 05:27:48 - mmengine - INFO - Epoch(train) [69][1280/2569] lr: 4.0000e-02 eta: 15:27:32 time: 0.2587 data_time: 0.0071 memory: 5828 grad_norm: 3.1080 loss: 2.3766 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3766 2023/06/05 05:27:53 - mmengine - INFO - Epoch(train) [69][1300/2569] lr: 4.0000e-02 eta: 15:27:27 time: 0.2616 data_time: 0.0072 memory: 5828 grad_norm: 3.0982 loss: 2.4032 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4032 2023/06/05 05:27:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:27:58 - mmengine - INFO - Epoch(train) [69][1320/2569] lr: 4.0000e-02 eta: 15:27:22 time: 0.2609 data_time: 0.0074 memory: 5828 grad_norm: 3.0815 loss: 2.4694 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4694 2023/06/05 05:28:04 - mmengine - INFO - Epoch(train) [69][1340/2569] lr: 4.0000e-02 eta: 15:27:16 time: 0.2728 data_time: 0.0068 memory: 5828 grad_norm: 3.2469 loss: 2.6689 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6689 2023/06/05 05:28:09 - mmengine - INFO - Epoch(train) [69][1360/2569] lr: 4.0000e-02 eta: 15:27:11 time: 0.2603 data_time: 0.0070 memory: 5828 grad_norm: 3.1354 loss: 2.5488 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5488 2023/06/05 05:28:15 - mmengine - INFO - Epoch(train) [69][1380/2569] lr: 4.0000e-02 eta: 15:27:06 time: 0.2777 data_time: 0.0072 memory: 5828 grad_norm: 3.1018 loss: 2.4811 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4811 2023/06/05 05:28:20 - mmengine - INFO - Epoch(train) [69][1400/2569] lr: 4.0000e-02 eta: 15:27:01 time: 0.2686 data_time: 0.0073 memory: 5828 grad_norm: 3.1740 loss: 2.5240 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5240 2023/06/05 05:28:25 - mmengine - INFO - Epoch(train) [69][1420/2569] lr: 4.0000e-02 eta: 15:26:56 time: 0.2718 data_time: 0.0076 memory: 5828 grad_norm: 3.1508 loss: 2.6880 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6880 2023/06/05 05:28:31 - mmengine - INFO - Epoch(train) [69][1440/2569] lr: 4.0000e-02 eta: 15:26:50 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 3.1006 loss: 2.8510 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8510 2023/06/05 05:28:36 - mmengine - INFO - Epoch(train) [69][1460/2569] lr: 4.0000e-02 eta: 15:26:45 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 3.1423 loss: 2.5623 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5623 2023/06/05 05:28:41 - mmengine - INFO - Epoch(train) [69][1480/2569] lr: 4.0000e-02 eta: 15:26:39 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 3.1155 loss: 2.4221 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4221 2023/06/05 05:28:47 - mmengine - INFO - Epoch(train) [69][1500/2569] lr: 4.0000e-02 eta: 15:26:34 time: 0.2672 data_time: 0.0071 memory: 5828 grad_norm: 3.0690 loss: 2.8237 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8237 2023/06/05 05:28:52 - mmengine - INFO - Epoch(train) [69][1520/2569] lr: 4.0000e-02 eta: 15:26:29 time: 0.2700 data_time: 0.0077 memory: 5828 grad_norm: 3.1038 loss: 2.5024 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5024 2023/06/05 05:28:57 - mmengine - INFO - Epoch(train) [69][1540/2569] lr: 4.0000e-02 eta: 15:26:24 time: 0.2629 data_time: 0.0074 memory: 5828 grad_norm: 3.0432 loss: 2.3354 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3354 2023/06/05 05:29:03 - mmengine - INFO - Epoch(train) [69][1560/2569] lr: 4.0000e-02 eta: 15:26:18 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 3.1300 loss: 2.9183 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9183 2023/06/05 05:29:08 - mmengine - INFO - Epoch(train) [69][1580/2569] lr: 4.0000e-02 eta: 15:26:13 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 3.1004 loss: 2.5490 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5490 2023/06/05 05:29:13 - mmengine - INFO - Epoch(train) [69][1600/2569] lr: 4.0000e-02 eta: 15:26:07 time: 0.2637 data_time: 0.0077 memory: 5828 grad_norm: 3.1364 loss: 2.3815 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3815 2023/06/05 05:29:18 - mmengine - INFO - Epoch(train) [69][1620/2569] lr: 4.0000e-02 eta: 15:26:02 time: 0.2666 data_time: 0.0075 memory: 5828 grad_norm: 3.1150 loss: 3.0070 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0070 2023/06/05 05:29:24 - mmengine - INFO - Epoch(train) [69][1640/2569] lr: 4.0000e-02 eta: 15:25:57 time: 0.2639 data_time: 0.0079 memory: 5828 grad_norm: 3.1847 loss: 2.4648 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4648 2023/06/05 05:29:29 - mmengine - INFO - Epoch(train) [69][1660/2569] lr: 4.0000e-02 eta: 15:25:51 time: 0.2593 data_time: 0.0074 memory: 5828 grad_norm: 3.1090 loss: 2.4954 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4954 2023/06/05 05:29:34 - mmengine - INFO - Epoch(train) [69][1680/2569] lr: 4.0000e-02 eta: 15:25:46 time: 0.2685 data_time: 0.0079 memory: 5828 grad_norm: 3.1246 loss: 2.7366 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7366 2023/06/05 05:29:40 - mmengine - INFO - Epoch(train) [69][1700/2569] lr: 4.0000e-02 eta: 15:25:41 time: 0.2606 data_time: 0.0078 memory: 5828 grad_norm: 3.0874 loss: 2.5108 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5108 2023/06/05 05:29:45 - mmengine - INFO - Epoch(train) [69][1720/2569] lr: 4.0000e-02 eta: 15:25:35 time: 0.2700 data_time: 0.0077 memory: 5828 grad_norm: 3.1691 loss: 2.4814 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4814 2023/06/05 05:29:50 - mmengine - INFO - Epoch(train) [69][1740/2569] lr: 4.0000e-02 eta: 15:25:30 time: 0.2586 data_time: 0.0078 memory: 5828 grad_norm: 3.0909 loss: 2.6463 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6463 2023/06/05 05:29:55 - mmengine - INFO - Epoch(train) [69][1760/2569] lr: 4.0000e-02 eta: 15:25:25 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 3.1409 loss: 2.7264 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7264 2023/06/05 05:30:01 - mmengine - INFO - Epoch(train) [69][1780/2569] lr: 4.0000e-02 eta: 15:25:19 time: 0.2594 data_time: 0.0076 memory: 5828 grad_norm: 3.1094 loss: 2.5664 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5664 2023/06/05 05:30:06 - mmengine - INFO - Epoch(train) [69][1800/2569] lr: 4.0000e-02 eta: 15:25:14 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 3.0863 loss: 2.6044 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6044 2023/06/05 05:30:11 - mmengine - INFO - Epoch(train) [69][1820/2569] lr: 4.0000e-02 eta: 15:25:08 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 3.1238 loss: 2.5190 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5190 2023/06/05 05:30:16 - mmengine - INFO - Epoch(train) [69][1840/2569] lr: 4.0000e-02 eta: 15:25:03 time: 0.2572 data_time: 0.0073 memory: 5828 grad_norm: 3.0773 loss: 2.7985 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7985 2023/06/05 05:30:21 - mmengine - INFO - Epoch(train) [69][1860/2569] lr: 4.0000e-02 eta: 15:24:57 time: 0.2578 data_time: 0.0078 memory: 5828 grad_norm: 3.1266 loss: 2.9876 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9876 2023/06/05 05:30:27 - mmengine - INFO - Epoch(train) [69][1880/2569] lr: 4.0000e-02 eta: 15:24:52 time: 0.2614 data_time: 0.0079 memory: 5828 grad_norm: 3.2061 loss: 2.5715 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5715 2023/06/05 05:30:32 - mmengine - INFO - Epoch(train) [69][1900/2569] lr: 4.0000e-02 eta: 15:24:46 time: 0.2581 data_time: 0.0071 memory: 5828 grad_norm: 3.0877 loss: 2.9672 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9672 2023/06/05 05:30:37 - mmengine - INFO - Epoch(train) [69][1920/2569] lr: 4.0000e-02 eta: 15:24:41 time: 0.2631 data_time: 0.0077 memory: 5828 grad_norm: 3.1367 loss: 2.3191 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3191 2023/06/05 05:30:42 - mmengine - INFO - Epoch(train) [69][1940/2569] lr: 4.0000e-02 eta: 15:24:36 time: 0.2637 data_time: 0.0075 memory: 5828 grad_norm: 3.1226 loss: 2.4057 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4057 2023/06/05 05:30:48 - mmengine - INFO - Epoch(train) [69][1960/2569] lr: 4.0000e-02 eta: 15:24:31 time: 0.2773 data_time: 0.0070 memory: 5828 grad_norm: 3.1055 loss: 2.6110 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6110 2023/06/05 05:30:53 - mmengine - INFO - Epoch(train) [69][1980/2569] lr: 4.0000e-02 eta: 15:24:25 time: 0.2569 data_time: 0.0077 memory: 5828 grad_norm: 3.1851 loss: 2.4035 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4035 2023/06/05 05:30:58 - mmengine - INFO - Epoch(train) [69][2000/2569] lr: 4.0000e-02 eta: 15:24:20 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.1492 loss: 2.6622 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6622 2023/06/05 05:31:04 - mmengine - INFO - Epoch(train) [69][2020/2569] lr: 4.0000e-02 eta: 15:24:14 time: 0.2622 data_time: 0.0070 memory: 5828 grad_norm: 3.1784 loss: 2.5266 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5266 2023/06/05 05:31:09 - mmengine - INFO - Epoch(train) [69][2040/2569] lr: 4.0000e-02 eta: 15:24:09 time: 0.2662 data_time: 0.0076 memory: 5828 grad_norm: 3.0960 loss: 3.0556 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0556 2023/06/05 05:31:14 - mmengine - INFO - Epoch(train) [69][2060/2569] lr: 4.0000e-02 eta: 15:24:04 time: 0.2569 data_time: 0.0071 memory: 5828 grad_norm: 3.0578 loss: 2.2800 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2800 2023/06/05 05:31:19 - mmengine - INFO - Epoch(train) [69][2080/2569] lr: 4.0000e-02 eta: 15:23:58 time: 0.2656 data_time: 0.0072 memory: 5828 grad_norm: 3.1394 loss: 2.4608 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4608 2023/06/05 05:31:25 - mmengine - INFO - Epoch(train) [69][2100/2569] lr: 4.0000e-02 eta: 15:23:53 time: 0.2576 data_time: 0.0076 memory: 5828 grad_norm: 3.0882 loss: 2.5617 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5617 2023/06/05 05:31:30 - mmengine - INFO - Epoch(train) [69][2120/2569] lr: 4.0000e-02 eta: 15:23:47 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 3.0821 loss: 2.2482 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.2482 2023/06/05 05:31:35 - mmengine - INFO - Epoch(train) [69][2140/2569] lr: 4.0000e-02 eta: 15:23:42 time: 0.2573 data_time: 0.0072 memory: 5828 grad_norm: 3.0559 loss: 2.4619 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4619 2023/06/05 05:31:40 - mmengine - INFO - Epoch(train) [69][2160/2569] lr: 4.0000e-02 eta: 15:23:36 time: 0.2619 data_time: 0.0072 memory: 5828 grad_norm: 3.1800 loss: 2.1090 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1090 2023/06/05 05:31:46 - mmengine - INFO - Epoch(train) [69][2180/2569] lr: 4.0000e-02 eta: 15:23:31 time: 0.2646 data_time: 0.0070 memory: 5828 grad_norm: 3.1695 loss: 2.7693 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7693 2023/06/05 05:31:51 - mmengine - INFO - Epoch(train) [69][2200/2569] lr: 4.0000e-02 eta: 15:23:26 time: 0.2580 data_time: 0.0076 memory: 5828 grad_norm: 3.1080 loss: 2.5274 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5274 2023/06/05 05:31:56 - mmengine - INFO - Epoch(train) [69][2220/2569] lr: 4.0000e-02 eta: 15:23:21 time: 0.2773 data_time: 0.0077 memory: 5828 grad_norm: 3.1223 loss: 2.5972 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5972 2023/06/05 05:32:02 - mmengine - INFO - Epoch(train) [69][2240/2569] lr: 4.0000e-02 eta: 15:23:15 time: 0.2567 data_time: 0.0071 memory: 5828 grad_norm: 3.1429 loss: 2.7158 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7158 2023/06/05 05:32:07 - mmengine - INFO - Epoch(train) [69][2260/2569] lr: 4.0000e-02 eta: 15:23:10 time: 0.2679 data_time: 0.0078 memory: 5828 grad_norm: 3.1883 loss: 2.4762 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4762 2023/06/05 05:32:12 - mmengine - INFO - Epoch(train) [69][2280/2569] lr: 4.0000e-02 eta: 15:23:05 time: 0.2748 data_time: 0.0078 memory: 5828 grad_norm: 3.1226 loss: 2.5125 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.5125 2023/06/05 05:32:18 - mmengine - INFO - Epoch(train) [69][2300/2569] lr: 4.0000e-02 eta: 15:22:59 time: 0.2596 data_time: 0.0075 memory: 5828 grad_norm: 3.1539 loss: 2.6153 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6153 2023/06/05 05:32:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:32:23 - mmengine - INFO - Epoch(train) [69][2320/2569] lr: 4.0000e-02 eta: 15:22:54 time: 0.2745 data_time: 0.0072 memory: 5828 grad_norm: 3.1150 loss: 2.3154 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3154 2023/06/05 05:32:28 - mmengine - INFO - Epoch(train) [69][2340/2569] lr: 4.0000e-02 eta: 15:22:49 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 3.1043 loss: 1.9934 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9934 2023/06/05 05:32:34 - mmengine - INFO - Epoch(train) [69][2360/2569] lr: 4.0000e-02 eta: 15:22:43 time: 0.2673 data_time: 0.0075 memory: 5828 grad_norm: 3.1186 loss: 2.5130 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5130 2023/06/05 05:32:39 - mmengine - INFO - Epoch(train) [69][2380/2569] lr: 4.0000e-02 eta: 15:22:38 time: 0.2685 data_time: 0.0071 memory: 5828 grad_norm: 3.1072 loss: 2.4902 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4902 2023/06/05 05:32:44 - mmengine - INFO - Epoch(train) [69][2400/2569] lr: 4.0000e-02 eta: 15:22:33 time: 0.2634 data_time: 0.0081 memory: 5828 grad_norm: 3.2230 loss: 2.5972 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5972 2023/06/05 05:32:49 - mmengine - INFO - Epoch(train) [69][2420/2569] lr: 4.0000e-02 eta: 15:22:27 time: 0.2580 data_time: 0.0079 memory: 5828 grad_norm: 3.0982 loss: 2.3509 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3509 2023/06/05 05:32:55 - mmengine - INFO - Epoch(train) [69][2440/2569] lr: 4.0000e-02 eta: 15:22:22 time: 0.2638 data_time: 0.0076 memory: 5828 grad_norm: 3.0757 loss: 2.7967 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7967 2023/06/05 05:33:00 - mmengine - INFO - Epoch(train) [69][2460/2569] lr: 4.0000e-02 eta: 15:22:16 time: 0.2583 data_time: 0.0075 memory: 5828 grad_norm: 3.1041 loss: 2.8565 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8565 2023/06/05 05:33:05 - mmengine - INFO - Epoch(train) [69][2480/2569] lr: 4.0000e-02 eta: 15:22:11 time: 0.2698 data_time: 0.0077 memory: 5828 grad_norm: 3.1511 loss: 2.4425 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4425 2023/06/05 05:33:11 - mmengine - INFO - Epoch(train) [69][2500/2569] lr: 4.0000e-02 eta: 15:22:06 time: 0.2639 data_time: 0.0067 memory: 5828 grad_norm: 3.0616 loss: 2.8531 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8531 2023/06/05 05:33:16 - mmengine - INFO - Epoch(train) [69][2520/2569] lr: 4.0000e-02 eta: 15:22:00 time: 0.2617 data_time: 0.0080 memory: 5828 grad_norm: 3.1169 loss: 2.8364 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8364 2023/06/05 05:33:21 - mmengine - INFO - Epoch(train) [69][2540/2569] lr: 4.0000e-02 eta: 15:21:55 time: 0.2587 data_time: 0.0074 memory: 5828 grad_norm: 3.0875 loss: 2.6124 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6124 2023/06/05 05:33:26 - mmengine - INFO - Epoch(train) [69][2560/2569] lr: 4.0000e-02 eta: 15:21:50 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 3.0515 loss: 2.3919 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3919 2023/06/05 05:33:29 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:33:29 - mmengine - INFO - Epoch(train) [69][2569/2569] lr: 4.0000e-02 eta: 15:21:47 time: 0.2565 data_time: 0.0072 memory: 5828 grad_norm: 3.1173 loss: 2.2086 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2086 2023/06/05 05:33:35 - mmengine - INFO - Epoch(train) [70][ 20/2569] lr: 4.0000e-02 eta: 15:21:44 time: 0.3437 data_time: 0.0610 memory: 5828 grad_norm: 3.0682 loss: 2.5029 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5029 2023/06/05 05:33:41 - mmengine - INFO - Epoch(train) [70][ 40/2569] lr: 4.0000e-02 eta: 15:21:38 time: 0.2743 data_time: 0.0077 memory: 5828 grad_norm: 3.0823 loss: 2.3297 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3297 2023/06/05 05:33:46 - mmengine - INFO - Epoch(train) [70][ 60/2569] lr: 4.0000e-02 eta: 15:21:33 time: 0.2583 data_time: 0.0073 memory: 5828 grad_norm: 3.1241 loss: 2.2489 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2489 2023/06/05 05:33:51 - mmengine - INFO - Epoch(train) [70][ 80/2569] lr: 4.0000e-02 eta: 15:21:28 time: 0.2644 data_time: 0.0073 memory: 5828 grad_norm: 3.1165 loss: 2.2671 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2671 2023/06/05 05:33:57 - mmengine - INFO - Epoch(train) [70][ 100/2569] lr: 4.0000e-02 eta: 15:21:22 time: 0.2593 data_time: 0.0070 memory: 5828 grad_norm: 3.1118 loss: 2.2129 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2129 2023/06/05 05:34:02 - mmengine - INFO - Epoch(train) [70][ 120/2569] lr: 4.0000e-02 eta: 15:21:17 time: 0.2570 data_time: 0.0073 memory: 5828 grad_norm: 3.1358 loss: 2.1106 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1106 2023/06/05 05:34:07 - mmengine - INFO - Epoch(train) [70][ 140/2569] lr: 4.0000e-02 eta: 15:21:11 time: 0.2581 data_time: 0.0074 memory: 5828 grad_norm: 3.0830 loss: 2.4831 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4831 2023/06/05 05:34:12 - mmengine - INFO - Epoch(train) [70][ 160/2569] lr: 4.0000e-02 eta: 15:21:06 time: 0.2662 data_time: 0.0074 memory: 5828 grad_norm: 3.1347 loss: 2.7052 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7052 2023/06/05 05:34:17 - mmengine - INFO - Epoch(train) [70][ 180/2569] lr: 4.0000e-02 eta: 15:21:00 time: 0.2598 data_time: 0.0076 memory: 5828 grad_norm: 3.1245 loss: 2.3165 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3165 2023/06/05 05:34:23 - mmengine - INFO - Epoch(train) [70][ 200/2569] lr: 4.0000e-02 eta: 15:20:55 time: 0.2644 data_time: 0.0071 memory: 5828 grad_norm: 3.1333 loss: 2.5267 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5267 2023/06/05 05:34:28 - mmengine - INFO - Epoch(train) [70][ 220/2569] lr: 4.0000e-02 eta: 15:20:50 time: 0.2711 data_time: 0.0074 memory: 5828 grad_norm: 3.1498 loss: 2.4500 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4500 2023/06/05 05:34:33 - mmengine - INFO - Epoch(train) [70][ 240/2569] lr: 4.0000e-02 eta: 15:20:44 time: 0.2649 data_time: 0.0072 memory: 5828 grad_norm: 3.1055 loss: 2.6100 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6100 2023/06/05 05:34:39 - mmengine - INFO - Epoch(train) [70][ 260/2569] lr: 4.0000e-02 eta: 15:20:39 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 3.0860 loss: 2.7243 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7243 2023/06/05 05:34:44 - mmengine - INFO - Epoch(train) [70][ 280/2569] lr: 4.0000e-02 eta: 15:20:34 time: 0.2573 data_time: 0.0074 memory: 5828 grad_norm: 3.1182 loss: 2.4006 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4006 2023/06/05 05:34:49 - mmengine - INFO - Epoch(train) [70][ 300/2569] lr: 4.0000e-02 eta: 15:20:28 time: 0.2629 data_time: 0.0070 memory: 5828 grad_norm: 3.1242 loss: 2.7560 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7560 2023/06/05 05:34:54 - mmengine - INFO - Epoch(train) [70][ 320/2569] lr: 4.0000e-02 eta: 15:20:23 time: 0.2575 data_time: 0.0074 memory: 5828 grad_norm: 3.0597 loss: 2.2561 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2561 2023/06/05 05:35:00 - mmengine - INFO - Epoch(train) [70][ 340/2569] lr: 4.0000e-02 eta: 15:20:17 time: 0.2586 data_time: 0.0071 memory: 5828 grad_norm: 3.1171 loss: 2.2013 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2013 2023/06/05 05:35:05 - mmengine - INFO - Epoch(train) [70][ 360/2569] lr: 4.0000e-02 eta: 15:20:12 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 3.0409 loss: 2.7124 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7124 2023/06/05 05:35:10 - mmengine - INFO - Epoch(train) [70][ 380/2569] lr: 4.0000e-02 eta: 15:20:06 time: 0.2572 data_time: 0.0075 memory: 5828 grad_norm: 3.1331 loss: 2.2115 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2115 2023/06/05 05:35:15 - mmengine - INFO - Epoch(train) [70][ 400/2569] lr: 4.0000e-02 eta: 15:20:01 time: 0.2618 data_time: 0.0070 memory: 5828 grad_norm: 3.1436 loss: 2.4127 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4127 2023/06/05 05:35:21 - mmengine - INFO - Epoch(train) [70][ 420/2569] lr: 4.0000e-02 eta: 15:19:56 time: 0.2815 data_time: 0.0068 memory: 5828 grad_norm: 3.1274 loss: 2.3197 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3197 2023/06/05 05:35:26 - mmengine - INFO - Epoch(train) [70][ 440/2569] lr: 4.0000e-02 eta: 15:19:51 time: 0.2696 data_time: 0.0072 memory: 5828 grad_norm: 3.1388 loss: 2.5730 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5730 2023/06/05 05:35:31 - mmengine - INFO - Epoch(train) [70][ 460/2569] lr: 4.0000e-02 eta: 15:19:45 time: 0.2620 data_time: 0.0069 memory: 5828 grad_norm: 3.1143 loss: 2.2033 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2033 2023/06/05 05:35:37 - mmengine - INFO - Epoch(train) [70][ 480/2569] lr: 4.0000e-02 eta: 15:19:40 time: 0.2635 data_time: 0.0079 memory: 5828 grad_norm: 3.0727 loss: 2.4263 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4263 2023/06/05 05:35:42 - mmengine - INFO - Epoch(train) [70][ 500/2569] lr: 4.0000e-02 eta: 15:19:35 time: 0.2629 data_time: 0.0075 memory: 5828 grad_norm: 3.1397 loss: 2.3461 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3461 2023/06/05 05:35:47 - mmengine - INFO - Epoch(train) [70][ 520/2569] lr: 4.0000e-02 eta: 15:19:29 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 3.1834 loss: 2.6213 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6213 2023/06/05 05:35:53 - mmengine - INFO - Epoch(train) [70][ 540/2569] lr: 4.0000e-02 eta: 15:19:24 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 3.1172 loss: 2.4343 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4343 2023/06/05 05:35:58 - mmengine - INFO - Epoch(train) [70][ 560/2569] lr: 4.0000e-02 eta: 15:19:18 time: 0.2614 data_time: 0.0078 memory: 5828 grad_norm: 3.1126 loss: 2.5171 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5171 2023/06/05 05:36:03 - mmengine - INFO - Epoch(train) [70][ 580/2569] lr: 4.0000e-02 eta: 15:19:13 time: 0.2686 data_time: 0.0074 memory: 5828 grad_norm: 3.2158 loss: 2.6793 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6793 2023/06/05 05:36:08 - mmengine - INFO - Epoch(train) [70][ 600/2569] lr: 4.0000e-02 eta: 15:19:08 time: 0.2574 data_time: 0.0072 memory: 5828 grad_norm: 3.0409 loss: 2.6694 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6694 2023/06/05 05:36:14 - mmengine - INFO - Epoch(train) [70][ 620/2569] lr: 4.0000e-02 eta: 15:19:02 time: 0.2637 data_time: 0.0072 memory: 5828 grad_norm: 3.1170 loss: 2.7291 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7291 2023/06/05 05:36:19 - mmengine - INFO - Epoch(train) [70][ 640/2569] lr: 4.0000e-02 eta: 15:18:57 time: 0.2586 data_time: 0.0072 memory: 5828 grad_norm: 3.1495 loss: 2.4328 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4328 2023/06/05 05:36:24 - mmengine - INFO - Epoch(train) [70][ 660/2569] lr: 4.0000e-02 eta: 15:18:51 time: 0.2583 data_time: 0.0072 memory: 5828 grad_norm: 3.1087 loss: 2.2505 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2505 2023/06/05 05:36:29 - mmengine - INFO - Epoch(train) [70][ 680/2569] lr: 4.0000e-02 eta: 15:18:46 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.1452 loss: 2.4711 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4711 2023/06/05 05:36:35 - mmengine - INFO - Epoch(train) [70][ 700/2569] lr: 4.0000e-02 eta: 15:18:41 time: 0.2636 data_time: 0.0072 memory: 5828 grad_norm: 3.1340 loss: 2.3055 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3055 2023/06/05 05:36:40 - mmengine - INFO - Epoch(train) [70][ 720/2569] lr: 4.0000e-02 eta: 15:18:35 time: 0.2638 data_time: 0.0071 memory: 5828 grad_norm: 3.0870 loss: 2.2734 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2734 2023/06/05 05:36:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:36:45 - mmengine - INFO - Epoch(train) [70][ 740/2569] lr: 4.0000e-02 eta: 15:18:30 time: 0.2688 data_time: 0.0071 memory: 5828 grad_norm: 3.0807 loss: 2.7387 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7387 2023/06/05 05:36:51 - mmengine - INFO - Epoch(train) [70][ 760/2569] lr: 4.0000e-02 eta: 15:18:25 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 3.0971 loss: 2.5206 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5206 2023/06/05 05:36:56 - mmengine - INFO - Epoch(train) [70][ 780/2569] lr: 4.0000e-02 eta: 15:18:20 time: 0.2790 data_time: 0.0068 memory: 5828 grad_norm: 3.1808 loss: 2.7636 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7636 2023/06/05 05:37:02 - mmengine - INFO - Epoch(train) [70][ 800/2569] lr: 4.0000e-02 eta: 15:18:15 time: 0.2754 data_time: 0.0071 memory: 5828 grad_norm: 3.1266 loss: 2.6659 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6659 2023/06/05 05:37:07 - mmengine - INFO - Epoch(train) [70][ 820/2569] lr: 4.0000e-02 eta: 15:18:09 time: 0.2685 data_time: 0.0077 memory: 5828 grad_norm: 3.0830 loss: 2.5492 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5492 2023/06/05 05:37:12 - mmengine - INFO - Epoch(train) [70][ 840/2569] lr: 4.0000e-02 eta: 15:18:04 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 3.0936 loss: 2.6957 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6957 2023/06/05 05:37:18 - mmengine - INFO - Epoch(train) [70][ 860/2569] lr: 4.0000e-02 eta: 15:17:59 time: 0.2645 data_time: 0.0076 memory: 5828 grad_norm: 3.1278 loss: 2.5290 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5290 2023/06/05 05:37:23 - mmengine - INFO - Epoch(train) [70][ 880/2569] lr: 4.0000e-02 eta: 15:17:53 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 3.0929 loss: 2.3931 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3931 2023/06/05 05:37:28 - mmengine - INFO - Epoch(train) [70][ 900/2569] lr: 4.0000e-02 eta: 15:17:48 time: 0.2580 data_time: 0.0073 memory: 5828 grad_norm: 3.1534 loss: 2.5796 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5796 2023/06/05 05:37:34 - mmengine - INFO - Epoch(train) [70][ 920/2569] lr: 4.0000e-02 eta: 15:17:43 time: 0.2739 data_time: 0.0076 memory: 5828 grad_norm: 3.1139 loss: 2.2968 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2968 2023/06/05 05:37:39 - mmengine - INFO - Epoch(train) [70][ 940/2569] lr: 4.0000e-02 eta: 15:17:37 time: 0.2602 data_time: 0.0072 memory: 5828 grad_norm: 3.1333 loss: 2.6681 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6681 2023/06/05 05:37:44 - mmengine - INFO - Epoch(train) [70][ 960/2569] lr: 4.0000e-02 eta: 15:17:32 time: 0.2647 data_time: 0.0077 memory: 5828 grad_norm: 3.1667 loss: 2.2565 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2565 2023/06/05 05:37:49 - mmengine - INFO - Epoch(train) [70][ 980/2569] lr: 4.0000e-02 eta: 15:17:27 time: 0.2684 data_time: 0.0075 memory: 5828 grad_norm: 3.1434 loss: 2.5422 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.5422 2023/06/05 05:37:55 - mmengine - INFO - Epoch(train) [70][1000/2569] lr: 4.0000e-02 eta: 15:17:21 time: 0.2570 data_time: 0.0077 memory: 5828 grad_norm: 3.1246 loss: 2.3154 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3154 2023/06/05 05:38:00 - mmengine - INFO - Epoch(train) [70][1020/2569] lr: 4.0000e-02 eta: 15:17:16 time: 0.2730 data_time: 0.0073 memory: 5828 grad_norm: 3.1684 loss: 2.2995 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2995 2023/06/05 05:38:05 - mmengine - INFO - Epoch(train) [70][1040/2569] lr: 4.0000e-02 eta: 15:17:11 time: 0.2678 data_time: 0.0076 memory: 5828 grad_norm: 3.1724 loss: 2.5737 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5737 2023/06/05 05:38:11 - mmengine - INFO - Epoch(train) [70][1060/2569] lr: 4.0000e-02 eta: 15:17:05 time: 0.2670 data_time: 0.0070 memory: 5828 grad_norm: 3.0784 loss: 2.5267 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5267 2023/06/05 05:38:16 - mmengine - INFO - Epoch(train) [70][1080/2569] lr: 4.0000e-02 eta: 15:17:00 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 3.0895 loss: 2.7108 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7108 2023/06/05 05:38:21 - mmengine - INFO - Epoch(train) [70][1100/2569] lr: 4.0000e-02 eta: 15:16:55 time: 0.2662 data_time: 0.0075 memory: 5828 grad_norm: 3.1099 loss: 2.8787 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8787 2023/06/05 05:38:27 - mmengine - INFO - Epoch(train) [70][1120/2569] lr: 4.0000e-02 eta: 15:16:49 time: 0.2585 data_time: 0.0073 memory: 5828 grad_norm: 3.0625 loss: 2.8443 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8443 2023/06/05 05:38:32 - mmengine - INFO - Epoch(train) [70][1140/2569] lr: 4.0000e-02 eta: 15:16:44 time: 0.2697 data_time: 0.0073 memory: 5828 grad_norm: 3.1163 loss: 2.4451 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4451 2023/06/05 05:38:37 - mmengine - INFO - Epoch(train) [70][1160/2569] lr: 4.0000e-02 eta: 15:16:39 time: 0.2596 data_time: 0.0074 memory: 5828 grad_norm: 3.1975 loss: 2.3664 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3664 2023/06/05 05:38:42 - mmengine - INFO - Epoch(train) [70][1180/2569] lr: 4.0000e-02 eta: 15:16:33 time: 0.2585 data_time: 0.0076 memory: 5828 grad_norm: 3.1555 loss: 2.2886 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2886 2023/06/05 05:38:48 - mmengine - INFO - Epoch(train) [70][1200/2569] lr: 4.0000e-02 eta: 15:16:28 time: 0.2663 data_time: 0.0072 memory: 5828 grad_norm: 3.0954 loss: 2.7542 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7542 2023/06/05 05:38:53 - mmengine - INFO - Epoch(train) [70][1220/2569] lr: 4.0000e-02 eta: 15:16:22 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.1898 loss: 2.6285 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6285 2023/06/05 05:38:59 - mmengine - INFO - Epoch(train) [70][1240/2569] lr: 4.0000e-02 eta: 15:16:18 time: 0.2911 data_time: 0.0077 memory: 5828 grad_norm: 3.0683 loss: 2.4980 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4980 2023/06/05 05:39:04 - mmengine - INFO - Epoch(train) [70][1260/2569] lr: 4.0000e-02 eta: 15:16:12 time: 0.2630 data_time: 0.0072 memory: 5828 grad_norm: 3.1508 loss: 2.8554 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8554 2023/06/05 05:39:09 - mmengine - INFO - Epoch(train) [70][1280/2569] lr: 4.0000e-02 eta: 15:16:07 time: 0.2620 data_time: 0.0077 memory: 5828 grad_norm: 3.1500 loss: 2.5323 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5323 2023/06/05 05:39:15 - mmengine - INFO - Epoch(train) [70][1300/2569] lr: 4.0000e-02 eta: 15:16:02 time: 0.2693 data_time: 0.0077 memory: 5828 grad_norm: 3.1237 loss: 2.6723 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6723 2023/06/05 05:39:20 - mmengine - INFO - Epoch(train) [70][1320/2569] lr: 4.0000e-02 eta: 15:15:57 time: 0.2709 data_time: 0.0084 memory: 5828 grad_norm: 3.1288 loss: 2.8831 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8831 2023/06/05 05:39:25 - mmengine - INFO - Epoch(train) [70][1340/2569] lr: 4.0000e-02 eta: 15:15:51 time: 0.2585 data_time: 0.0073 memory: 5828 grad_norm: 3.1369 loss: 2.3720 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3720 2023/06/05 05:39:31 - mmengine - INFO - Epoch(train) [70][1360/2569] lr: 4.0000e-02 eta: 15:15:46 time: 0.2655 data_time: 0.0078 memory: 5828 grad_norm: 3.2114 loss: 2.4539 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4539 2023/06/05 05:39:36 - mmengine - INFO - Epoch(train) [70][1380/2569] lr: 4.0000e-02 eta: 15:15:40 time: 0.2578 data_time: 0.0073 memory: 5828 grad_norm: 3.1036 loss: 2.8718 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8718 2023/06/05 05:39:41 - mmengine - INFO - Epoch(train) [70][1400/2569] lr: 4.0000e-02 eta: 15:15:35 time: 0.2579 data_time: 0.0077 memory: 5828 grad_norm: 3.0930 loss: 2.1515 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1515 2023/06/05 05:39:46 - mmengine - INFO - Epoch(train) [70][1420/2569] lr: 4.0000e-02 eta: 15:15:29 time: 0.2574 data_time: 0.0075 memory: 5828 grad_norm: 3.1171 loss: 2.6201 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6201 2023/06/05 05:39:51 - mmengine - INFO - Epoch(train) [70][1440/2569] lr: 4.0000e-02 eta: 15:15:24 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 3.0475 loss: 2.7475 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7475 2023/06/05 05:39:57 - mmengine - INFO - Epoch(train) [70][1460/2569] lr: 4.0000e-02 eta: 15:15:19 time: 0.2646 data_time: 0.0071 memory: 5828 grad_norm: 3.1779 loss: 2.6541 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6541 2023/06/05 05:40:02 - mmengine - INFO - Epoch(train) [70][1480/2569] lr: 4.0000e-02 eta: 15:15:13 time: 0.2619 data_time: 0.0078 memory: 5828 grad_norm: 3.1422 loss: 2.8716 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8716 2023/06/05 05:40:07 - mmengine - INFO - Epoch(train) [70][1500/2569] lr: 4.0000e-02 eta: 15:15:08 time: 0.2638 data_time: 0.0078 memory: 5828 grad_norm: 3.1064 loss: 2.6014 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6014 2023/06/05 05:40:12 - mmengine - INFO - Epoch(train) [70][1520/2569] lr: 4.0000e-02 eta: 15:15:02 time: 0.2617 data_time: 0.0078 memory: 5828 grad_norm: 3.0758 loss: 2.3889 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3889 2023/06/05 05:40:18 - mmengine - INFO - Epoch(train) [70][1540/2569] lr: 4.0000e-02 eta: 15:14:57 time: 0.2640 data_time: 0.0078 memory: 5828 grad_norm: 3.2150 loss: 2.6425 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.6425 2023/06/05 05:40:23 - mmengine - INFO - Epoch(train) [70][1560/2569] lr: 4.0000e-02 eta: 15:14:52 time: 0.2642 data_time: 0.0078 memory: 5828 grad_norm: 3.0704 loss: 2.6000 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6000 2023/06/05 05:40:28 - mmengine - INFO - Epoch(train) [70][1580/2569] lr: 4.0000e-02 eta: 15:14:46 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 3.0935 loss: 2.0704 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0704 2023/06/05 05:40:34 - mmengine - INFO - Epoch(train) [70][1600/2569] lr: 4.0000e-02 eta: 15:14:41 time: 0.2617 data_time: 0.0071 memory: 5828 grad_norm: 3.0872 loss: 2.6094 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6094 2023/06/05 05:40:39 - mmengine - INFO - Epoch(train) [70][1620/2569] lr: 4.0000e-02 eta: 15:14:36 time: 0.2611 data_time: 0.0073 memory: 5828 grad_norm: 3.1342 loss: 2.7037 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7037 2023/06/05 05:40:44 - mmengine - INFO - Epoch(train) [70][1640/2569] lr: 4.0000e-02 eta: 15:14:30 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 3.1526 loss: 2.6697 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6697 2023/06/05 05:40:50 - mmengine - INFO - Epoch(train) [70][1660/2569] lr: 4.0000e-02 eta: 15:14:25 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.0724 loss: 2.4072 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4072 2023/06/05 05:40:55 - mmengine - INFO - Epoch(train) [70][1680/2569] lr: 4.0000e-02 eta: 15:14:20 time: 0.2759 data_time: 0.0072 memory: 5828 grad_norm: 3.1327 loss: 2.3121 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3121 2023/06/05 05:41:01 - mmengine - INFO - Epoch(train) [70][1700/2569] lr: 4.0000e-02 eta: 15:14:15 time: 0.2811 data_time: 0.0071 memory: 5828 grad_norm: 3.1304 loss: 2.3567 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3567 2023/06/05 05:41:06 - mmengine - INFO - Epoch(train) [70][1720/2569] lr: 4.0000e-02 eta: 15:14:09 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 3.1479 loss: 2.7601 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7601 2023/06/05 05:41:11 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:41:11 - mmengine - INFO - Epoch(train) [70][1740/2569] lr: 4.0000e-02 eta: 15:14:04 time: 0.2704 data_time: 0.0070 memory: 5828 grad_norm: 3.0238 loss: 2.6057 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6057 2023/06/05 05:41:17 - mmengine - INFO - Epoch(train) [70][1760/2569] lr: 4.0000e-02 eta: 15:13:59 time: 0.2590 data_time: 0.0073 memory: 5828 grad_norm: 3.1657 loss: 2.4098 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4098 2023/06/05 05:41:22 - mmengine - INFO - Epoch(train) [70][1780/2569] lr: 4.0000e-02 eta: 15:13:54 time: 0.2686 data_time: 0.0076 memory: 5828 grad_norm: 3.1697 loss: 2.4280 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4280 2023/06/05 05:41:27 - mmengine - INFO - Epoch(train) [70][1800/2569] lr: 4.0000e-02 eta: 15:13:48 time: 0.2638 data_time: 0.0078 memory: 5828 grad_norm: 3.1841 loss: 2.3516 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3516 2023/06/05 05:41:33 - mmengine - INFO - Epoch(train) [70][1820/2569] lr: 4.0000e-02 eta: 15:13:43 time: 0.2673 data_time: 0.0072 memory: 5828 grad_norm: 3.1543 loss: 2.7484 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7484 2023/06/05 05:41:38 - mmengine - INFO - Epoch(train) [70][1840/2569] lr: 4.0000e-02 eta: 15:13:37 time: 0.2598 data_time: 0.0072 memory: 5828 grad_norm: 3.1440 loss: 2.5811 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5811 2023/06/05 05:41:43 - mmengine - INFO - Epoch(train) [70][1860/2569] lr: 4.0000e-02 eta: 15:13:32 time: 0.2613 data_time: 0.0072 memory: 5828 grad_norm: 3.0896 loss: 2.2813 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2813 2023/06/05 05:41:48 - mmengine - INFO - Epoch(train) [70][1880/2569] lr: 4.0000e-02 eta: 15:13:27 time: 0.2708 data_time: 0.0075 memory: 5828 grad_norm: 3.0925 loss: 2.7975 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7975 2023/06/05 05:41:54 - mmengine - INFO - Epoch(train) [70][1900/2569] lr: 4.0000e-02 eta: 15:13:21 time: 0.2603 data_time: 0.0070 memory: 5828 grad_norm: 3.1128 loss: 2.4458 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4458 2023/06/05 05:41:59 - mmengine - INFO - Epoch(train) [70][1920/2569] lr: 4.0000e-02 eta: 15:13:16 time: 0.2671 data_time: 0.0077 memory: 5828 grad_norm: 3.0971 loss: 2.3844 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3844 2023/06/05 05:42:04 - mmengine - INFO - Epoch(train) [70][1940/2569] lr: 4.0000e-02 eta: 15:13:11 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 3.1284 loss: 2.4699 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4699 2023/06/05 05:42:10 - mmengine - INFO - Epoch(train) [70][1960/2569] lr: 4.0000e-02 eta: 15:13:05 time: 0.2643 data_time: 0.0075 memory: 5828 grad_norm: 3.1136 loss: 2.7367 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7367 2023/06/05 05:42:15 - mmengine - INFO - Epoch(train) [70][1980/2569] lr: 4.0000e-02 eta: 15:13:00 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.1609 loss: 2.2849 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2849 2023/06/05 05:42:20 - mmengine - INFO - Epoch(train) [70][2000/2569] lr: 4.0000e-02 eta: 15:12:55 time: 0.2669 data_time: 0.0076 memory: 5828 grad_norm: 3.0980 loss: 2.3856 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3856 2023/06/05 05:42:26 - mmengine - INFO - Epoch(train) [70][2020/2569] lr: 4.0000e-02 eta: 15:12:50 time: 0.2649 data_time: 0.0076 memory: 5828 grad_norm: 3.2326 loss: 2.5182 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5182 2023/06/05 05:42:31 - mmengine - INFO - Epoch(train) [70][2040/2569] lr: 4.0000e-02 eta: 15:12:44 time: 0.2632 data_time: 0.0071 memory: 5828 grad_norm: 3.0542 loss: 2.5229 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5229 2023/06/05 05:42:36 - mmengine - INFO - Epoch(train) [70][2060/2569] lr: 4.0000e-02 eta: 15:12:39 time: 0.2593 data_time: 0.0073 memory: 5828 grad_norm: 3.1246 loss: 2.3825 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3825 2023/06/05 05:42:41 - mmengine - INFO - Epoch(train) [70][2080/2569] lr: 4.0000e-02 eta: 15:12:33 time: 0.2585 data_time: 0.0073 memory: 5828 grad_norm: 3.1906 loss: 2.6427 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6427 2023/06/05 05:42:46 - mmengine - INFO - Epoch(train) [70][2100/2569] lr: 4.0000e-02 eta: 15:12:28 time: 0.2598 data_time: 0.0070 memory: 5828 grad_norm: 3.0622 loss: 2.5805 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5805 2023/06/05 05:42:52 - mmengine - INFO - Epoch(train) [70][2120/2569] lr: 4.0000e-02 eta: 15:12:22 time: 0.2591 data_time: 0.0069 memory: 5828 grad_norm: 3.1249 loss: 2.6485 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6485 2023/06/05 05:42:57 - mmengine - INFO - Epoch(train) [70][2140/2569] lr: 4.0000e-02 eta: 15:12:17 time: 0.2773 data_time: 0.0068 memory: 5828 grad_norm: 3.1345 loss: 2.3715 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3715 2023/06/05 05:43:03 - mmengine - INFO - Epoch(train) [70][2160/2569] lr: 4.0000e-02 eta: 15:12:12 time: 0.2716 data_time: 0.0072 memory: 5828 grad_norm: 3.1151 loss: 2.4025 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4025 2023/06/05 05:43:08 - mmengine - INFO - Epoch(train) [70][2180/2569] lr: 4.0000e-02 eta: 15:12:07 time: 0.2655 data_time: 0.0071 memory: 5828 grad_norm: 3.1793 loss: 2.8026 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8026 2023/06/05 05:43:13 - mmengine - INFO - Epoch(train) [70][2200/2569] lr: 4.0000e-02 eta: 15:12:02 time: 0.2755 data_time: 0.0072 memory: 5828 grad_norm: 3.1084 loss: 2.5738 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5738 2023/06/05 05:43:19 - mmengine - INFO - Epoch(train) [70][2220/2569] lr: 4.0000e-02 eta: 15:11:57 time: 0.2782 data_time: 0.0070 memory: 5828 grad_norm: 3.0899 loss: 2.0754 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0754 2023/06/05 05:43:24 - mmengine - INFO - Epoch(train) [70][2240/2569] lr: 4.0000e-02 eta: 15:11:51 time: 0.2691 data_time: 0.0073 memory: 5828 grad_norm: 3.1145 loss: 2.6690 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6690 2023/06/05 05:43:30 - mmengine - INFO - Epoch(train) [70][2260/2569] lr: 4.0000e-02 eta: 15:11:46 time: 0.2643 data_time: 0.0070 memory: 5828 grad_norm: 3.0868 loss: 2.9064 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9064 2023/06/05 05:43:35 - mmengine - INFO - Epoch(train) [70][2280/2569] lr: 4.0000e-02 eta: 15:11:41 time: 0.2701 data_time: 0.0069 memory: 5828 grad_norm: 3.1295 loss: 2.9001 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9001 2023/06/05 05:43:40 - mmengine - INFO - Epoch(train) [70][2300/2569] lr: 4.0000e-02 eta: 15:11:36 time: 0.2693 data_time: 0.0075 memory: 5828 grad_norm: 3.0833 loss: 2.4261 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4261 2023/06/05 05:43:46 - mmengine - INFO - Epoch(train) [70][2320/2569] lr: 4.0000e-02 eta: 15:11:30 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 3.1320 loss: 2.4864 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4864 2023/06/05 05:43:51 - mmengine - INFO - Epoch(train) [70][2340/2569] lr: 4.0000e-02 eta: 15:11:25 time: 0.2591 data_time: 0.0069 memory: 5828 grad_norm: 3.1112 loss: 2.5642 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5642 2023/06/05 05:43:56 - mmengine - INFO - Epoch(train) [70][2360/2569] lr: 4.0000e-02 eta: 15:11:19 time: 0.2593 data_time: 0.0074 memory: 5828 grad_norm: 3.2657 loss: 2.6010 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6010 2023/06/05 05:44:02 - mmengine - INFO - Epoch(train) [70][2380/2569] lr: 4.0000e-02 eta: 15:11:14 time: 0.2702 data_time: 0.0074 memory: 5828 grad_norm: 3.2497 loss: 2.6624 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6624 2023/06/05 05:44:07 - mmengine - INFO - Epoch(train) [70][2400/2569] lr: 4.0000e-02 eta: 15:11:09 time: 0.2642 data_time: 0.0086 memory: 5828 grad_norm: 3.1063 loss: 2.1447 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1447 2023/06/05 05:44:12 - mmengine - INFO - Epoch(train) [70][2420/2569] lr: 4.0000e-02 eta: 15:11:03 time: 0.2683 data_time: 0.0074 memory: 5828 grad_norm: 3.1480 loss: 2.3340 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3340 2023/06/05 05:44:18 - mmengine - INFO - Epoch(train) [70][2440/2569] lr: 4.0000e-02 eta: 15:10:58 time: 0.2645 data_time: 0.0075 memory: 5828 grad_norm: 3.1073 loss: 2.5689 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5689 2023/06/05 05:44:23 - mmengine - INFO - Epoch(train) [70][2460/2569] lr: 4.0000e-02 eta: 15:10:53 time: 0.2578 data_time: 0.0073 memory: 5828 grad_norm: 3.1410 loss: 2.4792 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4792 2023/06/05 05:44:28 - mmengine - INFO - Epoch(train) [70][2480/2569] lr: 4.0000e-02 eta: 15:10:47 time: 0.2582 data_time: 0.0074 memory: 5828 grad_norm: 3.1704 loss: 2.6326 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6326 2023/06/05 05:44:33 - mmengine - INFO - Epoch(train) [70][2500/2569] lr: 4.0000e-02 eta: 15:10:42 time: 0.2578 data_time: 0.0076 memory: 5828 grad_norm: 3.1079 loss: 2.5862 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5862 2023/06/05 05:44:38 - mmengine - INFO - Epoch(train) [70][2520/2569] lr: 4.0000e-02 eta: 15:10:36 time: 0.2570 data_time: 0.0073 memory: 5828 grad_norm: 3.1541 loss: 2.3689 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3689 2023/06/05 05:44:43 - mmengine - INFO - Epoch(train) [70][2540/2569] lr: 4.0000e-02 eta: 15:10:31 time: 0.2640 data_time: 0.0077 memory: 5828 grad_norm: 3.1215 loss: 2.9491 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9491 2023/06/05 05:44:49 - mmengine - INFO - Epoch(train) [70][2560/2569] lr: 4.0000e-02 eta: 15:10:25 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 3.1233 loss: 2.5737 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5737 2023/06/05 05:44:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:44:51 - mmengine - INFO - Epoch(train) [70][2569/2569] lr: 4.0000e-02 eta: 15:10:23 time: 0.2677 data_time: 0.0068 memory: 5828 grad_norm: 3.1347 loss: 2.6797 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 2.6797 2023/06/05 05:44:55 - mmengine - INFO - Epoch(val) [70][ 20/260] eta: 0:00:42 time: 0.1782 data_time: 0.1189 memory: 1238 2023/06/05 05:44:58 - mmengine - INFO - Epoch(val) [70][ 40/260] eta: 0:00:36 time: 0.1515 data_time: 0.0926 memory: 1238 2023/06/05 05:45:01 - mmengine - INFO - Epoch(val) [70][ 60/260] eta: 0:00:32 time: 0.1537 data_time: 0.0945 memory: 1238 2023/06/05 05:45:03 - mmengine - INFO - Epoch(val) [70][ 80/260] eta: 0:00:26 time: 0.1103 data_time: 0.0516 memory: 1238 2023/06/05 05:45:06 - mmengine - INFO - Epoch(val) [70][100/260] eta: 0:00:24 time: 0.1570 data_time: 0.0985 memory: 1238 2023/06/05 05:45:09 - mmengine - INFO - Epoch(val) [70][120/260] eta: 0:00:20 time: 0.1229 data_time: 0.0645 memory: 1238 2023/06/05 05:45:11 - mmengine - INFO - Epoch(val) [70][140/260] eta: 0:00:17 time: 0.1353 data_time: 0.0770 memory: 1238 2023/06/05 05:45:14 - mmengine - INFO - Epoch(val) [70][160/260] eta: 0:00:14 time: 0.1402 data_time: 0.0815 memory: 1238 2023/06/05 05:45:17 - mmengine - INFO - Epoch(val) [70][180/260] eta: 0:00:11 time: 0.1620 data_time: 0.1031 memory: 1238 2023/06/05 05:45:20 - mmengine - INFO - Epoch(val) [70][200/260] eta: 0:00:08 time: 0.1209 data_time: 0.0624 memory: 1238 2023/06/05 05:45:23 - mmengine - INFO - Epoch(val) [70][220/260] eta: 0:00:05 time: 0.1578 data_time: 0.0990 memory: 1238 2023/06/05 05:45:26 - mmengine - INFO - Epoch(val) [70][240/260] eta: 0:00:02 time: 0.1387 data_time: 0.0802 memory: 1238 2023/06/05 05:45:28 - mmengine - INFO - Epoch(val) [70][260/260] eta: 0:00:00 time: 0.1325 data_time: 0.0764 memory: 1238 2023/06/05 05:45:36 - mmengine - INFO - Epoch(val) [70][260/260] acc/top1: 0.4990 acc/top5: 0.7421 acc/mean1: 0.4916 data_time: 0.0843 time: 0.1428 2023/06/05 05:45:42 - mmengine - INFO - Epoch(train) [71][ 20/2569] lr: 4.0000e-02 eta: 15:10:19 time: 0.3330 data_time: 0.0793 memory: 5828 grad_norm: 3.0705 loss: 2.4641 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4641 2023/06/05 05:45:48 - mmengine - INFO - Epoch(train) [71][ 40/2569] lr: 4.0000e-02 eta: 15:10:14 time: 0.2588 data_time: 0.0092 memory: 5828 grad_norm: 3.1458 loss: 2.4988 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4988 2023/06/05 05:45:53 - mmengine - INFO - Epoch(train) [71][ 60/2569] lr: 4.0000e-02 eta: 15:10:09 time: 0.2681 data_time: 0.0078 memory: 5828 grad_norm: 3.1320 loss: 2.4321 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4321 2023/06/05 05:45:58 - mmengine - INFO - Epoch(train) [71][ 80/2569] lr: 4.0000e-02 eta: 15:10:03 time: 0.2580 data_time: 0.0073 memory: 5828 grad_norm: 3.1739 loss: 2.6123 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6123 2023/06/05 05:46:03 - mmengine - INFO - Epoch(train) [71][ 100/2569] lr: 4.0000e-02 eta: 15:09:58 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 3.1420 loss: 2.5317 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5317 2023/06/05 05:46:09 - mmengine - INFO - Epoch(train) [71][ 120/2569] lr: 4.0000e-02 eta: 15:09:52 time: 0.2580 data_time: 0.0077 memory: 5828 grad_norm: 3.1414 loss: 2.4217 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4217 2023/06/05 05:46:14 - mmengine - INFO - Epoch(train) [71][ 140/2569] lr: 4.0000e-02 eta: 15:09:47 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 3.0633 loss: 2.7533 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7533 2023/06/05 05:46:19 - mmengine - INFO - Epoch(train) [71][ 160/2569] lr: 4.0000e-02 eta: 15:09:41 time: 0.2585 data_time: 0.0075 memory: 5828 grad_norm: 3.0957 loss: 2.4461 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4461 2023/06/05 05:46:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:46:24 - mmengine - INFO - Epoch(train) [71][ 180/2569] lr: 4.0000e-02 eta: 15:09:36 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 3.1611 loss: 2.6304 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6304 2023/06/05 05:46:30 - mmengine - INFO - Epoch(train) [71][ 200/2569] lr: 4.0000e-02 eta: 15:09:31 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 3.1436 loss: 2.3216 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3216 2023/06/05 05:46:35 - mmengine - INFO - Epoch(train) [71][ 220/2569] lr: 4.0000e-02 eta: 15:09:25 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 3.1220 loss: 2.2037 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2037 2023/06/05 05:46:40 - mmengine - INFO - Epoch(train) [71][ 240/2569] lr: 4.0000e-02 eta: 15:09:20 time: 0.2639 data_time: 0.0072 memory: 5828 grad_norm: 3.1063 loss: 2.8683 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8683 2023/06/05 05:46:45 - mmengine - INFO - Epoch(train) [71][ 260/2569] lr: 4.0000e-02 eta: 15:09:14 time: 0.2612 data_time: 0.0079 memory: 5828 grad_norm: 3.1400 loss: 2.6787 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6787 2023/06/05 05:46:51 - mmengine - INFO - Epoch(train) [71][ 280/2569] lr: 4.0000e-02 eta: 15:09:09 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 3.1501 loss: 2.2314 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2314 2023/06/05 05:46:56 - mmengine - INFO - Epoch(train) [71][ 300/2569] lr: 4.0000e-02 eta: 15:09:04 time: 0.2695 data_time: 0.0070 memory: 5828 grad_norm: 3.0791 loss: 2.4319 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4319 2023/06/05 05:47:01 - mmengine - INFO - Epoch(train) [71][ 320/2569] lr: 4.0000e-02 eta: 15:08:58 time: 0.2601 data_time: 0.0072 memory: 5828 grad_norm: 3.1607 loss: 2.7136 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7136 2023/06/05 05:47:07 - mmengine - INFO - Epoch(train) [71][ 340/2569] lr: 4.0000e-02 eta: 15:08:53 time: 0.2591 data_time: 0.0073 memory: 5828 grad_norm: 3.0945 loss: 2.2631 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2631 2023/06/05 05:47:12 - mmengine - INFO - Epoch(train) [71][ 360/2569] lr: 4.0000e-02 eta: 15:08:47 time: 0.2590 data_time: 0.0088 memory: 5828 grad_norm: 3.1024 loss: 2.6216 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6216 2023/06/05 05:47:17 - mmengine - INFO - Epoch(train) [71][ 380/2569] lr: 4.0000e-02 eta: 15:08:42 time: 0.2713 data_time: 0.0086 memory: 5828 grad_norm: 3.1179 loss: 2.2867 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2867 2023/06/05 05:47:22 - mmengine - INFO - Epoch(train) [71][ 400/2569] lr: 4.0000e-02 eta: 15:08:37 time: 0.2585 data_time: 0.0073 memory: 5828 grad_norm: 3.1380 loss: 2.3884 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3884 2023/06/05 05:47:28 - mmengine - INFO - Epoch(train) [71][ 420/2569] lr: 4.0000e-02 eta: 15:08:31 time: 0.2666 data_time: 0.0076 memory: 5828 grad_norm: 3.1338 loss: 2.3963 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3963 2023/06/05 05:47:33 - mmengine - INFO - Epoch(train) [71][ 440/2569] lr: 4.0000e-02 eta: 15:08:26 time: 0.2633 data_time: 0.0073 memory: 5828 grad_norm: 3.0799 loss: 2.5504 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5504 2023/06/05 05:47:38 - mmengine - INFO - Epoch(train) [71][ 460/2569] lr: 4.0000e-02 eta: 15:08:21 time: 0.2695 data_time: 0.0073 memory: 5828 grad_norm: 3.1024 loss: 2.4531 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4531 2023/06/05 05:47:44 - mmengine - INFO - Epoch(train) [71][ 480/2569] lr: 4.0000e-02 eta: 15:08:16 time: 0.2649 data_time: 0.0072 memory: 5828 grad_norm: 3.1980 loss: 2.4972 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4972 2023/06/05 05:47:49 - mmengine - INFO - Epoch(train) [71][ 500/2569] lr: 4.0000e-02 eta: 15:08:10 time: 0.2697 data_time: 0.0074 memory: 5828 grad_norm: 3.1107 loss: 2.4651 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4651 2023/06/05 05:47:54 - mmengine - INFO - Epoch(train) [71][ 520/2569] lr: 4.0000e-02 eta: 15:08:05 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 3.1459 loss: 2.3286 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3286 2023/06/05 05:48:00 - mmengine - INFO - Epoch(train) [71][ 540/2569] lr: 4.0000e-02 eta: 15:08:00 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 3.1784 loss: 2.6074 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6074 2023/06/05 05:48:05 - mmengine - INFO - Epoch(train) [71][ 560/2569] lr: 4.0000e-02 eta: 15:07:55 time: 0.2794 data_time: 0.0077 memory: 5828 grad_norm: 3.1083 loss: 2.5211 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5211 2023/06/05 05:48:11 - mmengine - INFO - Epoch(train) [71][ 580/2569] lr: 4.0000e-02 eta: 15:07:49 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 3.1238 loss: 2.4628 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4628 2023/06/05 05:48:16 - mmengine - INFO - Epoch(train) [71][ 600/2569] lr: 4.0000e-02 eta: 15:07:44 time: 0.2794 data_time: 0.0072 memory: 5828 grad_norm: 3.1393 loss: 2.9117 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.9117 2023/06/05 05:48:22 - mmengine - INFO - Epoch(train) [71][ 620/2569] lr: 4.0000e-02 eta: 15:07:39 time: 0.2658 data_time: 0.0074 memory: 5828 grad_norm: 3.1083 loss: 2.4867 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4867 2023/06/05 05:48:27 - mmengine - INFO - Epoch(train) [71][ 640/2569] lr: 4.0000e-02 eta: 15:07:34 time: 0.2737 data_time: 0.0069 memory: 5828 grad_norm: 3.0621 loss: 2.3606 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3606 2023/06/05 05:48:32 - mmengine - INFO - Epoch(train) [71][ 660/2569] lr: 4.0000e-02 eta: 15:07:28 time: 0.2567 data_time: 0.0073 memory: 5828 grad_norm: 3.1906 loss: 2.5664 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5664 2023/06/05 05:48:37 - mmengine - INFO - Epoch(train) [71][ 680/2569] lr: 4.0000e-02 eta: 15:07:23 time: 0.2640 data_time: 0.0076 memory: 5828 grad_norm: 3.1254 loss: 2.4593 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4593 2023/06/05 05:48:43 - mmengine - INFO - Epoch(train) [71][ 700/2569] lr: 4.0000e-02 eta: 15:07:18 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.1120 loss: 2.7322 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7322 2023/06/05 05:48:48 - mmengine - INFO - Epoch(train) [71][ 720/2569] lr: 4.0000e-02 eta: 15:07:12 time: 0.2617 data_time: 0.0076 memory: 5828 grad_norm: 3.1223 loss: 2.4375 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4375 2023/06/05 05:48:53 - mmengine - INFO - Epoch(train) [71][ 740/2569] lr: 4.0000e-02 eta: 15:07:07 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.1869 loss: 2.6370 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6370 2023/06/05 05:48:59 - mmengine - INFO - Epoch(train) [71][ 760/2569] lr: 4.0000e-02 eta: 15:07:02 time: 0.2675 data_time: 0.0075 memory: 5828 grad_norm: 3.1307 loss: 2.3807 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3807 2023/06/05 05:49:04 - mmengine - INFO - Epoch(train) [71][ 780/2569] lr: 4.0000e-02 eta: 15:06:56 time: 0.2582 data_time: 0.0070 memory: 5828 grad_norm: 3.1760 loss: 2.7454 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7454 2023/06/05 05:49:09 - mmengine - INFO - Epoch(train) [71][ 800/2569] lr: 4.0000e-02 eta: 15:06:51 time: 0.2747 data_time: 0.0078 memory: 5828 grad_norm: 3.1589 loss: 2.6494 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6494 2023/06/05 05:49:15 - mmengine - INFO - Epoch(train) [71][ 820/2569] lr: 4.0000e-02 eta: 15:06:46 time: 0.2613 data_time: 0.0069 memory: 5828 grad_norm: 3.1898 loss: 2.5549 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5549 2023/06/05 05:49:20 - mmengine - INFO - Epoch(train) [71][ 840/2569] lr: 4.0000e-02 eta: 15:06:41 time: 0.2757 data_time: 0.0073 memory: 5828 grad_norm: 3.1101 loss: 2.8273 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.8273 2023/06/05 05:49:25 - mmengine - INFO - Epoch(train) [71][ 860/2569] lr: 4.0000e-02 eta: 15:06:35 time: 0.2617 data_time: 0.0077 memory: 5828 grad_norm: 3.0826 loss: 2.6024 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6024 2023/06/05 05:49:31 - mmengine - INFO - Epoch(train) [71][ 880/2569] lr: 4.0000e-02 eta: 15:06:30 time: 0.2589 data_time: 0.0074 memory: 5828 grad_norm: 3.0652 loss: 2.3337 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3337 2023/06/05 05:49:36 - mmengine - INFO - Epoch(train) [71][ 900/2569] lr: 4.0000e-02 eta: 15:06:25 time: 0.2725 data_time: 0.0073 memory: 5828 grad_norm: 3.0938 loss: 2.7476 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7476 2023/06/05 05:49:41 - mmengine - INFO - Epoch(train) [71][ 920/2569] lr: 4.0000e-02 eta: 15:06:19 time: 0.2593 data_time: 0.0072 memory: 5828 grad_norm: 3.0895 loss: 2.5456 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5456 2023/06/05 05:49:46 - mmengine - INFO - Epoch(train) [71][ 940/2569] lr: 4.0000e-02 eta: 15:06:14 time: 0.2606 data_time: 0.0076 memory: 5828 grad_norm: 3.0958 loss: 2.2415 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2415 2023/06/05 05:49:52 - mmengine - INFO - Epoch(train) [71][ 960/2569] lr: 4.0000e-02 eta: 15:06:08 time: 0.2579 data_time: 0.0074 memory: 5828 grad_norm: 3.1865 loss: 2.7058 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7058 2023/06/05 05:49:57 - mmengine - INFO - Epoch(train) [71][ 980/2569] lr: 4.0000e-02 eta: 15:06:03 time: 0.2572 data_time: 0.0070 memory: 5828 grad_norm: 3.1135 loss: 2.2322 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.2322 2023/06/05 05:50:02 - mmengine - INFO - Epoch(train) [71][1000/2569] lr: 4.0000e-02 eta: 15:05:57 time: 0.2635 data_time: 0.0075 memory: 5828 grad_norm: 3.1529 loss: 2.3239 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3239 2023/06/05 05:50:07 - mmengine - INFO - Epoch(train) [71][1020/2569] lr: 4.0000e-02 eta: 15:05:52 time: 0.2647 data_time: 0.0072 memory: 5828 grad_norm: 3.1442 loss: 2.4679 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4679 2023/06/05 05:50:13 - mmengine - INFO - Epoch(train) [71][1040/2569] lr: 4.0000e-02 eta: 15:05:47 time: 0.2622 data_time: 0.0076 memory: 5828 grad_norm: 3.1102 loss: 2.0868 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.0868 2023/06/05 05:50:18 - mmengine - INFO - Epoch(train) [71][1060/2569] lr: 4.0000e-02 eta: 15:05:41 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 3.1649 loss: 2.3405 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3405 2023/06/05 05:50:23 - mmengine - INFO - Epoch(train) [71][1080/2569] lr: 4.0000e-02 eta: 15:05:36 time: 0.2590 data_time: 0.0075 memory: 5828 grad_norm: 3.1297 loss: 2.6640 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6640 2023/06/05 05:50:28 - mmengine - INFO - Epoch(train) [71][1100/2569] lr: 4.0000e-02 eta: 15:05:30 time: 0.2573 data_time: 0.0075 memory: 5828 grad_norm: 3.0785 loss: 2.3451 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3451 2023/06/05 05:50:33 - mmengine - INFO - Epoch(train) [71][1120/2569] lr: 4.0000e-02 eta: 15:05:25 time: 0.2652 data_time: 0.0070 memory: 5828 grad_norm: 3.1267 loss: 2.4048 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4048 2023/06/05 05:50:39 - mmengine - INFO - Epoch(train) [71][1140/2569] lr: 4.0000e-02 eta: 15:05:19 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 3.0559 loss: 2.5680 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5680 2023/06/05 05:50:44 - mmengine - INFO - Epoch(train) [71][1160/2569] lr: 4.0000e-02 eta: 15:05:14 time: 0.2585 data_time: 0.0074 memory: 5828 grad_norm: 3.1222 loss: 2.7521 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7521 2023/06/05 05:50:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:50:49 - mmengine - INFO - Epoch(train) [71][1180/2569] lr: 4.0000e-02 eta: 15:05:09 time: 0.2652 data_time: 0.0071 memory: 5828 grad_norm: 3.1579 loss: 2.2877 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2877 2023/06/05 05:50:54 - mmengine - INFO - Epoch(train) [71][1200/2569] lr: 4.0000e-02 eta: 15:05:03 time: 0.2644 data_time: 0.0077 memory: 5828 grad_norm: 3.1316 loss: 2.6188 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6188 2023/06/05 05:51:00 - mmengine - INFO - Epoch(train) [71][1220/2569] lr: 4.0000e-02 eta: 15:04:58 time: 0.2631 data_time: 0.0076 memory: 5828 grad_norm: 3.0811 loss: 2.6901 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6901 2023/06/05 05:51:05 - mmengine - INFO - Epoch(train) [71][1240/2569] lr: 4.0000e-02 eta: 15:04:53 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 3.2312 loss: 2.4216 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4216 2023/06/05 05:51:10 - mmengine - INFO - Epoch(train) [71][1260/2569] lr: 4.0000e-02 eta: 15:04:47 time: 0.2586 data_time: 0.0070 memory: 5828 grad_norm: 3.1248 loss: 2.7970 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7970 2023/06/05 05:51:16 - mmengine - INFO - Epoch(train) [71][1280/2569] lr: 4.0000e-02 eta: 15:04:42 time: 0.2736 data_time: 0.0075 memory: 5828 grad_norm: 3.1171 loss: 2.2807 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2807 2023/06/05 05:51:21 - mmengine - INFO - Epoch(train) [71][1300/2569] lr: 4.0000e-02 eta: 15:04:37 time: 0.2693 data_time: 0.0080 memory: 5828 grad_norm: 3.1223 loss: 2.6124 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6124 2023/06/05 05:51:26 - mmengine - INFO - Epoch(train) [71][1320/2569] lr: 4.0000e-02 eta: 15:04:31 time: 0.2644 data_time: 0.0082 memory: 5828 grad_norm: 3.1935 loss: 2.6984 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6984 2023/06/05 05:51:32 - mmengine - INFO - Epoch(train) [71][1340/2569] lr: 4.0000e-02 eta: 15:04:26 time: 0.2689 data_time: 0.0071 memory: 5828 grad_norm: 3.0850 loss: 2.3919 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3919 2023/06/05 05:51:37 - mmengine - INFO - Epoch(train) [71][1360/2569] lr: 4.0000e-02 eta: 15:04:21 time: 0.2573 data_time: 0.0075 memory: 5828 grad_norm: 3.1399 loss: 2.5868 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5868 2023/06/05 05:51:42 - mmengine - INFO - Epoch(train) [71][1380/2569] lr: 4.0000e-02 eta: 15:04:15 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.0940 loss: 2.8042 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8042 2023/06/05 05:51:47 - mmengine - INFO - Epoch(train) [71][1400/2569] lr: 4.0000e-02 eta: 15:04:10 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 3.1405 loss: 2.7228 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7228 2023/06/05 05:51:53 - mmengine - INFO - Epoch(train) [71][1420/2569] lr: 4.0000e-02 eta: 15:04:04 time: 0.2576 data_time: 0.0072 memory: 5828 grad_norm: 3.1431 loss: 2.3569 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.3569 2023/06/05 05:51:58 - mmengine - INFO - Epoch(train) [71][1440/2569] lr: 4.0000e-02 eta: 15:03:59 time: 0.2586 data_time: 0.0077 memory: 5828 grad_norm: 3.1415 loss: 2.9062 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9062 2023/06/05 05:52:03 - mmengine - INFO - Epoch(train) [71][1460/2569] lr: 4.0000e-02 eta: 15:03:54 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 3.1705 loss: 2.9017 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9017 2023/06/05 05:52:08 - mmengine - INFO - Epoch(train) [71][1480/2569] lr: 4.0000e-02 eta: 15:03:48 time: 0.2647 data_time: 0.0075 memory: 5828 grad_norm: 3.1772 loss: 2.7906 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7906 2023/06/05 05:52:14 - mmengine - INFO - Epoch(train) [71][1500/2569] lr: 4.0000e-02 eta: 15:03:43 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 3.1872 loss: 2.4221 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4221 2023/06/05 05:52:19 - mmengine - INFO - Epoch(train) [71][1520/2569] lr: 4.0000e-02 eta: 15:03:38 time: 0.2676 data_time: 0.0070 memory: 5828 grad_norm: 3.1706 loss: 2.7581 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7581 2023/06/05 05:52:25 - mmengine - INFO - Epoch(train) [71][1540/2569] lr: 4.0000e-02 eta: 15:03:33 time: 0.2744 data_time: 0.0070 memory: 5828 grad_norm: 3.0688 loss: 2.5810 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5810 2023/06/05 05:52:30 - mmengine - INFO - Epoch(train) [71][1560/2569] lr: 4.0000e-02 eta: 15:03:27 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 3.1589 loss: 2.2692 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2692 2023/06/05 05:52:35 - mmengine - INFO - Epoch(train) [71][1580/2569] lr: 4.0000e-02 eta: 15:03:22 time: 0.2681 data_time: 0.0078 memory: 5828 grad_norm: 3.1585 loss: 2.6627 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6627 2023/06/05 05:52:40 - mmengine - INFO - Epoch(train) [71][1600/2569] lr: 4.0000e-02 eta: 15:03:17 time: 0.2588 data_time: 0.0088 memory: 5828 grad_norm: 3.1109 loss: 2.5877 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5877 2023/06/05 05:52:46 - mmengine - INFO - Epoch(train) [71][1620/2569] lr: 4.0000e-02 eta: 15:03:11 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 3.1467 loss: 2.3146 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3146 2023/06/05 05:52:51 - mmengine - INFO - Epoch(train) [71][1640/2569] lr: 4.0000e-02 eta: 15:03:06 time: 0.2581 data_time: 0.0073 memory: 5828 grad_norm: 3.1163 loss: 2.6742 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6742 2023/06/05 05:52:56 - mmengine - INFO - Epoch(train) [71][1660/2569] lr: 4.0000e-02 eta: 15:03:00 time: 0.2698 data_time: 0.0071 memory: 5828 grad_norm: 3.0940 loss: 2.4309 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4309 2023/06/05 05:53:02 - mmengine - INFO - Epoch(train) [71][1680/2569] lr: 4.0000e-02 eta: 15:02:55 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 3.0399 loss: 2.4228 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4228 2023/06/05 05:53:07 - mmengine - INFO - Epoch(train) [71][1700/2569] lr: 4.0000e-02 eta: 15:02:50 time: 0.2592 data_time: 0.0072 memory: 5828 grad_norm: 3.1153 loss: 2.4614 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4614 2023/06/05 05:53:12 - mmengine - INFO - Epoch(train) [71][1720/2569] lr: 4.0000e-02 eta: 15:02:44 time: 0.2671 data_time: 0.0076 memory: 5828 grad_norm: 3.1269 loss: 2.4189 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4189 2023/06/05 05:53:17 - mmengine - INFO - Epoch(train) [71][1740/2569] lr: 4.0000e-02 eta: 15:02:39 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 3.0848 loss: 2.4390 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4390 2023/06/05 05:53:23 - mmengine - INFO - Epoch(train) [71][1760/2569] lr: 4.0000e-02 eta: 15:02:34 time: 0.2764 data_time: 0.0074 memory: 5828 grad_norm: 3.1141 loss: 2.4906 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.4906 2023/06/05 05:53:28 - mmengine - INFO - Epoch(train) [71][1780/2569] lr: 4.0000e-02 eta: 15:02:28 time: 0.2579 data_time: 0.0072 memory: 5828 grad_norm: 3.1308 loss: 2.4157 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4157 2023/06/05 05:53:33 - mmengine - INFO - Epoch(train) [71][1800/2569] lr: 4.0000e-02 eta: 15:02:23 time: 0.2657 data_time: 0.0074 memory: 5828 grad_norm: 3.0642 loss: 2.5595 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5595 2023/06/05 05:53:39 - mmengine - INFO - Epoch(train) [71][1820/2569] lr: 4.0000e-02 eta: 15:02:18 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.0782 loss: 2.8621 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8621 2023/06/05 05:53:44 - mmengine - INFO - Epoch(train) [71][1840/2569] lr: 4.0000e-02 eta: 15:02:12 time: 0.2591 data_time: 0.0072 memory: 5828 grad_norm: 3.1305 loss: 2.2904 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2904 2023/06/05 05:53:49 - mmengine - INFO - Epoch(train) [71][1860/2569] lr: 4.0000e-02 eta: 15:02:07 time: 0.2654 data_time: 0.0073 memory: 5828 grad_norm: 3.1148 loss: 2.4731 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4731 2023/06/05 05:53:54 - mmengine - INFO - Epoch(train) [71][1880/2569] lr: 4.0000e-02 eta: 15:02:01 time: 0.2601 data_time: 0.0072 memory: 5828 grad_norm: 3.1455 loss: 2.5026 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5026 2023/06/05 05:54:00 - mmengine - INFO - Epoch(train) [71][1900/2569] lr: 4.0000e-02 eta: 15:01:56 time: 0.2596 data_time: 0.0072 memory: 5828 grad_norm: 3.1410 loss: 2.6343 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6343 2023/06/05 05:54:05 - mmengine - INFO - Epoch(train) [71][1920/2569] lr: 4.0000e-02 eta: 15:01:51 time: 0.2650 data_time: 0.0071 memory: 5828 grad_norm: 3.1196 loss: 2.6273 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6273 2023/06/05 05:54:10 - mmengine - INFO - Epoch(train) [71][1940/2569] lr: 4.0000e-02 eta: 15:01:45 time: 0.2584 data_time: 0.0073 memory: 5828 grad_norm: 3.0911 loss: 2.0201 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0201 2023/06/05 05:54:15 - mmengine - INFO - Epoch(train) [71][1960/2569] lr: 4.0000e-02 eta: 15:01:40 time: 0.2599 data_time: 0.0079 memory: 5828 grad_norm: 3.0686 loss: 2.2992 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2992 2023/06/05 05:54:21 - mmengine - INFO - Epoch(train) [71][1980/2569] lr: 4.0000e-02 eta: 15:01:34 time: 0.2636 data_time: 0.0076 memory: 5828 grad_norm: 3.1547 loss: 2.6958 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6958 2023/06/05 05:54:26 - mmengine - INFO - Epoch(train) [71][2000/2569] lr: 4.0000e-02 eta: 15:01:29 time: 0.2741 data_time: 0.0073 memory: 5828 grad_norm: 3.1176 loss: 2.4092 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4092 2023/06/05 05:54:32 - mmengine - INFO - Epoch(train) [71][2020/2569] lr: 4.0000e-02 eta: 15:01:24 time: 0.2726 data_time: 0.0074 memory: 5828 grad_norm: 3.1300 loss: 2.7523 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.7523 2023/06/05 05:54:37 - mmengine - INFO - Epoch(train) [71][2040/2569] lr: 4.0000e-02 eta: 15:01:19 time: 0.2735 data_time: 0.0073 memory: 5828 grad_norm: 3.0989 loss: 2.6995 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6995 2023/06/05 05:54:42 - mmengine - INFO - Epoch(train) [71][2060/2569] lr: 4.0000e-02 eta: 15:01:14 time: 0.2622 data_time: 0.0074 memory: 5828 grad_norm: 3.1161 loss: 2.1999 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1999 2023/06/05 05:54:48 - mmengine - INFO - Epoch(train) [71][2080/2569] lr: 4.0000e-02 eta: 15:01:08 time: 0.2669 data_time: 0.0079 memory: 5828 grad_norm: 3.1373 loss: 2.5470 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5470 2023/06/05 05:54:53 - mmengine - INFO - Epoch(train) [71][2100/2569] lr: 4.0000e-02 eta: 15:01:03 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 3.0896 loss: 2.4443 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4443 2023/06/05 05:54:58 - mmengine - INFO - Epoch(train) [71][2120/2569] lr: 4.0000e-02 eta: 15:00:58 time: 0.2660 data_time: 0.0071 memory: 5828 grad_norm: 3.1099 loss: 2.5998 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5998 2023/06/05 05:55:03 - mmengine - INFO - Epoch(train) [71][2140/2569] lr: 4.0000e-02 eta: 15:00:52 time: 0.2577 data_time: 0.0072 memory: 5828 grad_norm: 3.0860 loss: 2.9294 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9294 2023/06/05 05:55:09 - mmengine - INFO - Epoch(train) [71][2160/2569] lr: 4.0000e-02 eta: 15:00:47 time: 0.2723 data_time: 0.0076 memory: 5828 grad_norm: 3.1050 loss: 2.6193 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6193 2023/06/05 05:55:11 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:55:14 - mmengine - INFO - Epoch(train) [71][2180/2569] lr: 4.0000e-02 eta: 15:00:42 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 3.1435 loss: 2.5796 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5796 2023/06/05 05:55:19 - mmengine - INFO - Epoch(train) [71][2200/2569] lr: 4.0000e-02 eta: 15:00:36 time: 0.2635 data_time: 0.0074 memory: 5828 grad_norm: 3.1253 loss: 2.7812 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7812 2023/06/05 05:55:25 - mmengine - INFO - Epoch(train) [71][2220/2569] lr: 4.0000e-02 eta: 15:00:31 time: 0.2654 data_time: 0.0076 memory: 5828 grad_norm: 3.0340 loss: 2.5408 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5408 2023/06/05 05:55:30 - mmengine - INFO - Epoch(train) [71][2240/2569] lr: 4.0000e-02 eta: 15:00:25 time: 0.2612 data_time: 0.0076 memory: 5828 grad_norm: 3.1794 loss: 2.5187 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5187 2023/06/05 05:55:35 - mmengine - INFO - Epoch(train) [71][2260/2569] lr: 4.0000e-02 eta: 15:00:20 time: 0.2683 data_time: 0.0074 memory: 5828 grad_norm: 3.0972 loss: 2.6495 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6495 2023/06/05 05:55:40 - mmengine - INFO - Epoch(train) [71][2280/2569] lr: 4.0000e-02 eta: 15:00:15 time: 0.2594 data_time: 0.0073 memory: 5828 grad_norm: 3.1117 loss: 2.3889 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3889 2023/06/05 05:55:46 - mmengine - INFO - Epoch(train) [71][2300/2569] lr: 4.0000e-02 eta: 15:00:10 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 3.1131 loss: 2.9474 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9474 2023/06/05 05:55:51 - mmengine - INFO - Epoch(train) [71][2320/2569] lr: 4.0000e-02 eta: 15:00:04 time: 0.2601 data_time: 0.0078 memory: 5828 grad_norm: 3.0744 loss: 2.4543 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4543 2023/06/05 05:55:56 - mmengine - INFO - Epoch(train) [71][2340/2569] lr: 4.0000e-02 eta: 14:59:59 time: 0.2605 data_time: 0.0072 memory: 5828 grad_norm: 3.1105 loss: 2.3767 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3767 2023/06/05 05:56:02 - mmengine - INFO - Epoch(train) [71][2360/2569] lr: 4.0000e-02 eta: 14:59:53 time: 0.2691 data_time: 0.0074 memory: 5828 grad_norm: 3.1670 loss: 2.5223 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5223 2023/06/05 05:56:07 - mmengine - INFO - Epoch(train) [71][2380/2569] lr: 4.0000e-02 eta: 14:59:48 time: 0.2690 data_time: 0.0082 memory: 5828 grad_norm: 3.1108 loss: 2.3954 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3954 2023/06/05 05:56:12 - mmengine - INFO - Epoch(train) [71][2400/2569] lr: 4.0000e-02 eta: 14:59:43 time: 0.2638 data_time: 0.0081 memory: 5828 grad_norm: 3.1377 loss: 2.5905 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5905 2023/06/05 05:56:18 - mmengine - INFO - Epoch(train) [71][2420/2569] lr: 4.0000e-02 eta: 14:59:37 time: 0.2575 data_time: 0.0071 memory: 5828 grad_norm: 3.1037 loss: 2.4415 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4415 2023/06/05 05:56:23 - mmengine - INFO - Epoch(train) [71][2440/2569] lr: 4.0000e-02 eta: 14:59:32 time: 0.2610 data_time: 0.0070 memory: 5828 grad_norm: 3.1370 loss: 2.2993 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2993 2023/06/05 05:56:28 - mmengine - INFO - Epoch(train) [71][2460/2569] lr: 4.0000e-02 eta: 14:59:27 time: 0.2689 data_time: 0.0076 memory: 5828 grad_norm: 3.1205 loss: 2.6010 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6010 2023/06/05 05:56:33 - mmengine - INFO - Epoch(train) [71][2480/2569] lr: 4.0000e-02 eta: 14:59:21 time: 0.2580 data_time: 0.0071 memory: 5828 grad_norm: 3.0983 loss: 2.6931 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6931 2023/06/05 05:56:39 - mmengine - INFO - Epoch(train) [71][2500/2569] lr: 4.0000e-02 eta: 14:59:16 time: 0.2713 data_time: 0.0075 memory: 5828 grad_norm: 3.1808 loss: 2.3941 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3941 2023/06/05 05:56:44 - mmengine - INFO - Epoch(train) [71][2520/2569] lr: 4.0000e-02 eta: 14:59:11 time: 0.2591 data_time: 0.0075 memory: 5828 grad_norm: 3.0823 loss: 2.3507 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3507 2023/06/05 05:56:49 - mmengine - INFO - Epoch(train) [71][2540/2569] lr: 4.0000e-02 eta: 14:59:05 time: 0.2591 data_time: 0.0075 memory: 5828 grad_norm: 3.1354 loss: 2.4420 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4420 2023/06/05 05:56:54 - mmengine - INFO - Epoch(train) [71][2560/2569] lr: 4.0000e-02 eta: 14:59:00 time: 0.2570 data_time: 0.0073 memory: 5828 grad_norm: 3.0738 loss: 2.5017 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5017 2023/06/05 05:56:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:56:57 - mmengine - INFO - Epoch(train) [71][2569/2569] lr: 4.0000e-02 eta: 14:58:57 time: 0.2506 data_time: 0.0072 memory: 5828 grad_norm: 3.1666 loss: 2.4408 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4408 2023/06/05 05:57:03 - mmengine - INFO - Epoch(train) [72][ 20/2569] lr: 4.0000e-02 eta: 14:58:53 time: 0.3447 data_time: 0.0594 memory: 5828 grad_norm: 3.0767 loss: 2.3179 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3179 2023/06/05 05:57:09 - mmengine - INFO - Epoch(train) [72][ 40/2569] lr: 4.0000e-02 eta: 14:58:48 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.1102 loss: 2.6525 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6525 2023/06/05 05:57:14 - mmengine - INFO - Epoch(train) [72][ 60/2569] lr: 4.0000e-02 eta: 14:58:43 time: 0.2645 data_time: 0.0080 memory: 5828 grad_norm: 3.0928 loss: 2.5773 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5773 2023/06/05 05:57:19 - mmengine - INFO - Epoch(train) [72][ 80/2569] lr: 4.0000e-02 eta: 14:58:37 time: 0.2585 data_time: 0.0072 memory: 5828 grad_norm: 3.1133 loss: 2.8271 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8271 2023/06/05 05:57:24 - mmengine - INFO - Epoch(train) [72][ 100/2569] lr: 4.0000e-02 eta: 14:58:32 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 3.0923 loss: 2.1689 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1689 2023/06/05 05:57:30 - mmengine - INFO - Epoch(train) [72][ 120/2569] lr: 4.0000e-02 eta: 14:58:26 time: 0.2590 data_time: 0.0074 memory: 5828 grad_norm: 3.1865 loss: 2.6012 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6012 2023/06/05 05:57:35 - mmengine - INFO - Epoch(train) [72][ 140/2569] lr: 4.0000e-02 eta: 14:58:21 time: 0.2692 data_time: 0.0070 memory: 5828 grad_norm: 3.1341 loss: 2.5145 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5145 2023/06/05 05:57:40 - mmengine - INFO - Epoch(train) [72][ 160/2569] lr: 4.0000e-02 eta: 14:58:16 time: 0.2588 data_time: 0.0075 memory: 5828 grad_norm: 3.1590 loss: 2.5021 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5021 2023/06/05 05:57:46 - mmengine - INFO - Epoch(train) [72][ 180/2569] lr: 4.0000e-02 eta: 14:58:11 time: 0.2722 data_time: 0.0072 memory: 5828 grad_norm: 3.1127 loss: 2.5683 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5683 2023/06/05 05:57:51 - mmengine - INFO - Epoch(train) [72][ 200/2569] lr: 4.0000e-02 eta: 14:58:05 time: 0.2632 data_time: 0.0070 memory: 5828 grad_norm: 3.1664 loss: 2.4037 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4037 2023/06/05 05:57:56 - mmengine - INFO - Epoch(train) [72][ 220/2569] lr: 4.0000e-02 eta: 14:58:00 time: 0.2773 data_time: 0.0073 memory: 5828 grad_norm: 3.1539 loss: 2.8498 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.8498 2023/06/05 05:58:02 - mmengine - INFO - Epoch(train) [72][ 240/2569] lr: 4.0000e-02 eta: 14:57:55 time: 0.2690 data_time: 0.0075 memory: 5828 grad_norm: 3.1267 loss: 2.6319 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6319 2023/06/05 05:58:07 - mmengine - INFO - Epoch(train) [72][ 260/2569] lr: 4.0000e-02 eta: 14:57:50 time: 0.2730 data_time: 0.0075 memory: 5828 grad_norm: 3.1383 loss: 2.6712 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6712 2023/06/05 05:58:13 - mmengine - INFO - Epoch(train) [72][ 280/2569] lr: 4.0000e-02 eta: 14:57:44 time: 0.2599 data_time: 0.0071 memory: 5828 grad_norm: 3.1227 loss: 2.2204 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2204 2023/06/05 05:58:18 - mmengine - INFO - Epoch(train) [72][ 300/2569] lr: 4.0000e-02 eta: 14:57:39 time: 0.2809 data_time: 0.0074 memory: 5828 grad_norm: 3.1118 loss: 2.6967 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6967 2023/06/05 05:58:23 - mmengine - INFO - Epoch(train) [72][ 320/2569] lr: 4.0000e-02 eta: 14:57:34 time: 0.2578 data_time: 0.0072 memory: 5828 grad_norm: 3.1596 loss: 2.3726 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3726 2023/06/05 05:58:29 - mmengine - INFO - Epoch(train) [72][ 340/2569] lr: 4.0000e-02 eta: 14:57:29 time: 0.2790 data_time: 0.0071 memory: 5828 grad_norm: 3.1422 loss: 2.2913 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2913 2023/06/05 05:58:34 - mmengine - INFO - Epoch(train) [72][ 360/2569] lr: 4.0000e-02 eta: 14:57:23 time: 0.2606 data_time: 0.0069 memory: 5828 grad_norm: 3.1412 loss: 2.2751 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2751 2023/06/05 05:58:40 - mmengine - INFO - Epoch(train) [72][ 380/2569] lr: 4.0000e-02 eta: 14:57:18 time: 0.2699 data_time: 0.0071 memory: 5828 grad_norm: 3.0986 loss: 2.6451 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6451 2023/06/05 05:58:45 - mmengine - INFO - Epoch(train) [72][ 400/2569] lr: 4.0000e-02 eta: 14:57:13 time: 0.2717 data_time: 0.0070 memory: 5828 grad_norm: 3.1296 loss: 2.5217 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5217 2023/06/05 05:58:50 - mmengine - INFO - Epoch(train) [72][ 420/2569] lr: 4.0000e-02 eta: 14:57:08 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 3.1192 loss: 2.4817 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4817 2023/06/05 05:58:56 - mmengine - INFO - Epoch(train) [72][ 440/2569] lr: 4.0000e-02 eta: 14:57:02 time: 0.2697 data_time: 0.0077 memory: 5828 grad_norm: 3.1606 loss: 2.4723 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4723 2023/06/05 05:59:01 - mmengine - INFO - Epoch(train) [72][ 460/2569] lr: 4.0000e-02 eta: 14:56:57 time: 0.2674 data_time: 0.0077 memory: 5828 grad_norm: 3.1295 loss: 2.4410 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4410 2023/06/05 05:59:06 - mmengine - INFO - Epoch(train) [72][ 480/2569] lr: 4.0000e-02 eta: 14:56:52 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 3.1096 loss: 2.7602 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7602 2023/06/05 05:59:12 - mmengine - INFO - Epoch(train) [72][ 500/2569] lr: 4.0000e-02 eta: 14:56:46 time: 0.2602 data_time: 0.0073 memory: 5828 grad_norm: 3.1762 loss: 2.3593 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3593 2023/06/05 05:59:17 - mmengine - INFO - Epoch(train) [72][ 520/2569] lr: 4.0000e-02 eta: 14:56:41 time: 0.2589 data_time: 0.0073 memory: 5828 grad_norm: 3.1634 loss: 2.5231 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5231 2023/06/05 05:59:22 - mmengine - INFO - Epoch(train) [72][ 540/2569] lr: 4.0000e-02 eta: 14:56:36 time: 0.2687 data_time: 0.0076 memory: 5828 grad_norm: 3.0926 loss: 2.5728 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5728 2023/06/05 05:59:27 - mmengine - INFO - Epoch(train) [72][ 560/2569] lr: 4.0000e-02 eta: 14:56:30 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 3.1219 loss: 2.5677 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5677 2023/06/05 05:59:33 - mmengine - INFO - Epoch(train) [72][ 580/2569] lr: 4.0000e-02 eta: 14:56:25 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 3.0586 loss: 2.2503 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2503 2023/06/05 05:59:38 - mmengine - INFO - Epoch(train) [72][ 600/2569] lr: 4.0000e-02 eta: 14:56:19 time: 0.2578 data_time: 0.0075 memory: 5828 grad_norm: 3.1560 loss: 2.6701 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6701 2023/06/05 05:59:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 05:59:43 - mmengine - INFO - Epoch(train) [72][ 620/2569] lr: 4.0000e-02 eta: 14:56:14 time: 0.2615 data_time: 0.0074 memory: 5828 grad_norm: 3.1465 loss: 2.3959 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3959 2023/06/05 05:59:48 - mmengine - INFO - Epoch(train) [72][ 640/2569] lr: 4.0000e-02 eta: 14:56:09 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 3.1138 loss: 2.3915 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3915 2023/06/05 05:59:54 - mmengine - INFO - Epoch(train) [72][ 660/2569] lr: 4.0000e-02 eta: 14:56:03 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 3.1159 loss: 2.6406 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6406 2023/06/05 05:59:59 - mmengine - INFO - Epoch(train) [72][ 680/2569] lr: 4.0000e-02 eta: 14:55:58 time: 0.2661 data_time: 0.0075 memory: 5828 grad_norm: 3.0686 loss: 2.2799 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2799 2023/06/05 06:00:04 - mmengine - INFO - Epoch(train) [72][ 700/2569] lr: 4.0000e-02 eta: 14:55:53 time: 0.2590 data_time: 0.0072 memory: 5828 grad_norm: 3.1780 loss: 2.8704 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.8704 2023/06/05 06:00:10 - mmengine - INFO - Epoch(train) [72][ 720/2569] lr: 4.0000e-02 eta: 14:55:47 time: 0.2635 data_time: 0.0075 memory: 5828 grad_norm: 3.1066 loss: 2.2773 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2773 2023/06/05 06:00:15 - mmengine - INFO - Epoch(train) [72][ 740/2569] lr: 4.0000e-02 eta: 14:55:42 time: 0.2701 data_time: 0.0075 memory: 5828 grad_norm: 3.1233 loss: 2.7634 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7634 2023/06/05 06:00:20 - mmengine - INFO - Epoch(train) [72][ 760/2569] lr: 4.0000e-02 eta: 14:55:37 time: 0.2590 data_time: 0.0073 memory: 5828 grad_norm: 3.1181 loss: 2.7627 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7627 2023/06/05 06:00:25 - mmengine - INFO - Epoch(train) [72][ 780/2569] lr: 4.0000e-02 eta: 14:55:31 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 3.1693 loss: 2.7884 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7884 2023/06/05 06:00:31 - mmengine - INFO - Epoch(train) [72][ 800/2569] lr: 4.0000e-02 eta: 14:55:26 time: 0.2589 data_time: 0.0080 memory: 5828 grad_norm: 3.0736 loss: 2.5104 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5104 2023/06/05 06:00:36 - mmengine - INFO - Epoch(train) [72][ 820/2569] lr: 4.0000e-02 eta: 14:55:20 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 3.0755 loss: 2.7191 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7191 2023/06/05 06:00:41 - mmengine - INFO - Epoch(train) [72][ 840/2569] lr: 4.0000e-02 eta: 14:55:15 time: 0.2694 data_time: 0.0077 memory: 5828 grad_norm: 3.1696 loss: 2.4113 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4113 2023/06/05 06:00:47 - mmengine - INFO - Epoch(train) [72][ 860/2569] lr: 4.0000e-02 eta: 14:55:10 time: 0.2646 data_time: 0.0072 memory: 5828 grad_norm: 3.1626 loss: 2.8319 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8319 2023/06/05 06:00:52 - mmengine - INFO - Epoch(train) [72][ 880/2569] lr: 4.0000e-02 eta: 14:55:04 time: 0.2586 data_time: 0.0072 memory: 5828 grad_norm: 3.1577 loss: 2.6337 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6337 2023/06/05 06:00:57 - mmengine - INFO - Epoch(train) [72][ 900/2569] lr: 4.0000e-02 eta: 14:54:59 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 3.1180 loss: 2.4081 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4081 2023/06/05 06:01:02 - mmengine - INFO - Epoch(train) [72][ 920/2569] lr: 4.0000e-02 eta: 14:54:54 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.0505 loss: 2.3461 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3461 2023/06/05 06:01:07 - mmengine - INFO - Epoch(train) [72][ 940/2569] lr: 4.0000e-02 eta: 14:54:48 time: 0.2583 data_time: 0.0073 memory: 5828 grad_norm: 3.0846 loss: 2.5031 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5031 2023/06/05 06:01:13 - mmengine - INFO - Epoch(train) [72][ 960/2569] lr: 4.0000e-02 eta: 14:54:43 time: 0.2640 data_time: 0.0077 memory: 5828 grad_norm: 3.1128 loss: 2.2823 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2823 2023/06/05 06:01:18 - mmengine - INFO - Epoch(train) [72][ 980/2569] lr: 4.0000e-02 eta: 14:54:37 time: 0.2586 data_time: 0.0071 memory: 5828 grad_norm: 3.0919 loss: 2.4456 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4456 2023/06/05 06:01:23 - mmengine - INFO - Epoch(train) [72][1000/2569] lr: 4.0000e-02 eta: 14:54:32 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.1117 loss: 2.3828 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3828 2023/06/05 06:01:29 - mmengine - INFO - Epoch(train) [72][1020/2569] lr: 4.0000e-02 eta: 14:54:27 time: 0.2798 data_time: 0.0071 memory: 5828 grad_norm: 3.1135 loss: 2.7145 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7145 2023/06/05 06:01:34 - mmengine - INFO - Epoch(train) [72][1040/2569] lr: 4.0000e-02 eta: 14:54:22 time: 0.2729 data_time: 0.0076 memory: 5828 grad_norm: 3.1632 loss: 2.2753 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2753 2023/06/05 06:01:40 - mmengine - INFO - Epoch(train) [72][1060/2569] lr: 4.0000e-02 eta: 14:54:17 time: 0.2717 data_time: 0.0072 memory: 5828 grad_norm: 3.0859 loss: 2.7827 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7827 2023/06/05 06:01:45 - mmengine - INFO - Epoch(train) [72][1080/2569] lr: 4.0000e-02 eta: 14:54:11 time: 0.2595 data_time: 0.0071 memory: 5828 grad_norm: 3.1579 loss: 2.6188 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6188 2023/06/05 06:01:50 - mmengine - INFO - Epoch(train) [72][1100/2569] lr: 4.0000e-02 eta: 14:54:06 time: 0.2688 data_time: 0.0072 memory: 5828 grad_norm: 3.0835 loss: 2.3322 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3322 2023/06/05 06:01:56 - mmengine - INFO - Epoch(train) [72][1120/2569] lr: 4.0000e-02 eta: 14:54:00 time: 0.2587 data_time: 0.0075 memory: 5828 grad_norm: 3.1324 loss: 2.5734 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5734 2023/06/05 06:02:01 - mmengine - INFO - Epoch(train) [72][1140/2569] lr: 4.0000e-02 eta: 14:53:55 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 3.0363 loss: 2.3991 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3991 2023/06/05 06:02:06 - mmengine - INFO - Epoch(train) [72][1160/2569] lr: 4.0000e-02 eta: 14:53:50 time: 0.2689 data_time: 0.0077 memory: 5828 grad_norm: 3.0779 loss: 2.5879 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5879 2023/06/05 06:02:11 - mmengine - INFO - Epoch(train) [72][1180/2569] lr: 4.0000e-02 eta: 14:53:44 time: 0.2635 data_time: 0.0076 memory: 5828 grad_norm: 3.0314 loss: 2.6421 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6421 2023/06/05 06:02:17 - mmengine - INFO - Epoch(train) [72][1200/2569] lr: 4.0000e-02 eta: 14:53:39 time: 0.2579 data_time: 0.0075 memory: 5828 grad_norm: 3.0975 loss: 2.4795 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4795 2023/06/05 06:02:22 - mmengine - INFO - Epoch(train) [72][1220/2569] lr: 4.0000e-02 eta: 14:53:34 time: 0.2691 data_time: 0.0071 memory: 5828 grad_norm: 3.1585 loss: 2.2343 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2343 2023/06/05 06:02:27 - mmengine - INFO - Epoch(train) [72][1240/2569] lr: 4.0000e-02 eta: 14:53:28 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 3.1535 loss: 2.5589 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5589 2023/06/05 06:02:33 - mmengine - INFO - Epoch(train) [72][1260/2569] lr: 4.0000e-02 eta: 14:53:23 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 3.1242 loss: 3.0624 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 3.0624 2023/06/05 06:02:38 - mmengine - INFO - Epoch(train) [72][1280/2569] lr: 4.0000e-02 eta: 14:53:18 time: 0.2623 data_time: 0.0081 memory: 5828 grad_norm: 3.1393 loss: 2.3592 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3592 2023/06/05 06:02:43 - mmengine - INFO - Epoch(train) [72][1300/2569] lr: 4.0000e-02 eta: 14:53:12 time: 0.2580 data_time: 0.0074 memory: 5828 grad_norm: 3.0676 loss: 2.2288 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2288 2023/06/05 06:02:48 - mmengine - INFO - Epoch(train) [72][1320/2569] lr: 4.0000e-02 eta: 14:53:07 time: 0.2569 data_time: 0.0072 memory: 5828 grad_norm: 3.2139 loss: 2.7803 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7803 2023/06/05 06:02:53 - mmengine - INFO - Epoch(train) [72][1340/2569] lr: 4.0000e-02 eta: 14:53:01 time: 0.2593 data_time: 0.0082 memory: 5828 grad_norm: 3.1223 loss: 2.4553 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4553 2023/06/05 06:02:59 - mmengine - INFO - Epoch(train) [72][1360/2569] lr: 4.0000e-02 eta: 14:52:56 time: 0.2651 data_time: 0.0071 memory: 5828 grad_norm: 3.1367 loss: 2.4850 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4850 2023/06/05 06:03:04 - mmengine - INFO - Epoch(train) [72][1380/2569] lr: 4.0000e-02 eta: 14:52:50 time: 0.2632 data_time: 0.0078 memory: 5828 grad_norm: 3.0960 loss: 2.5928 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5928 2023/06/05 06:03:09 - mmengine - INFO - Epoch(train) [72][1400/2569] lr: 4.0000e-02 eta: 14:52:45 time: 0.2570 data_time: 0.0073 memory: 5828 grad_norm: 3.1078 loss: 2.6196 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6196 2023/06/05 06:03:14 - mmengine - INFO - Epoch(train) [72][1420/2569] lr: 4.0000e-02 eta: 14:52:40 time: 0.2657 data_time: 0.0074 memory: 5828 grad_norm: 3.1297 loss: 2.4300 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4300 2023/06/05 06:03:20 - mmengine - INFO - Epoch(train) [72][1440/2569] lr: 4.0000e-02 eta: 14:52:34 time: 0.2658 data_time: 0.0076 memory: 5828 grad_norm: 3.1303 loss: 2.7705 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7705 2023/06/05 06:03:25 - mmengine - INFO - Epoch(train) [72][1460/2569] lr: 4.0000e-02 eta: 14:52:29 time: 0.2708 data_time: 0.0076 memory: 5828 grad_norm: 3.0720 loss: 2.0916 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0916 2023/06/05 06:03:31 - mmengine - INFO - Epoch(train) [72][1480/2569] lr: 4.0000e-02 eta: 14:52:24 time: 0.2724 data_time: 0.0071 memory: 5828 grad_norm: 3.1612 loss: 2.3142 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3142 2023/06/05 06:03:36 - mmengine - INFO - Epoch(train) [72][1500/2569] lr: 4.0000e-02 eta: 14:52:19 time: 0.2710 data_time: 0.0075 memory: 5828 grad_norm: 3.1345 loss: 2.3999 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3999 2023/06/05 06:03:41 - mmengine - INFO - Epoch(train) [72][1520/2569] lr: 4.0000e-02 eta: 14:52:13 time: 0.2654 data_time: 0.0076 memory: 5828 grad_norm: 3.0921 loss: 2.3962 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3962 2023/06/05 06:03:47 - mmengine - INFO - Epoch(train) [72][1540/2569] lr: 4.0000e-02 eta: 14:52:08 time: 0.2729 data_time: 0.0072 memory: 5828 grad_norm: 3.1784 loss: 2.3708 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.3708 2023/06/05 06:03:52 - mmengine - INFO - Epoch(train) [72][1560/2569] lr: 4.0000e-02 eta: 14:52:03 time: 0.2727 data_time: 0.0074 memory: 5828 grad_norm: 3.1559 loss: 2.6276 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6276 2023/06/05 06:03:57 - mmengine - INFO - Epoch(train) [72][1580/2569] lr: 4.0000e-02 eta: 14:51:58 time: 0.2590 data_time: 0.0074 memory: 5828 grad_norm: 3.1100 loss: 2.2284 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2284 2023/06/05 06:04:03 - mmengine - INFO - Epoch(train) [72][1600/2569] lr: 4.0000e-02 eta: 14:51:52 time: 0.2662 data_time: 0.0072 memory: 5828 grad_norm: 3.1299 loss: 2.3037 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3037 2023/06/05 06:04:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:04:08 - mmengine - INFO - Epoch(train) [72][1620/2569] lr: 4.0000e-02 eta: 14:51:47 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 3.0754 loss: 2.7440 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7440 2023/06/05 06:04:13 - mmengine - INFO - Epoch(train) [72][1640/2569] lr: 4.0000e-02 eta: 14:51:42 time: 0.2676 data_time: 0.0074 memory: 5828 grad_norm: 3.2038 loss: 2.4357 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4357 2023/06/05 06:04:19 - mmengine - INFO - Epoch(train) [72][1660/2569] lr: 4.0000e-02 eta: 14:51:36 time: 0.2575 data_time: 0.0077 memory: 5828 grad_norm: 3.0546 loss: 2.6114 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6114 2023/06/05 06:04:24 - mmengine - INFO - Epoch(train) [72][1680/2569] lr: 4.0000e-02 eta: 14:51:31 time: 0.2645 data_time: 0.0075 memory: 5828 grad_norm: 3.1070 loss: 2.6571 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6571 2023/06/05 06:04:29 - mmengine - INFO - Epoch(train) [72][1700/2569] lr: 4.0000e-02 eta: 14:51:26 time: 0.2656 data_time: 0.0077 memory: 5828 grad_norm: 3.1462 loss: 2.6121 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6121 2023/06/05 06:04:35 - mmengine - INFO - Epoch(train) [72][1720/2569] lr: 4.0000e-02 eta: 14:51:20 time: 0.2638 data_time: 0.0070 memory: 5828 grad_norm: 3.1713 loss: 2.4823 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4823 2023/06/05 06:04:40 - mmengine - INFO - Epoch(train) [72][1740/2569] lr: 4.0000e-02 eta: 14:51:15 time: 0.2600 data_time: 0.0073 memory: 5828 grad_norm: 3.0649 loss: 2.5299 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5299 2023/06/05 06:04:45 - mmengine - INFO - Epoch(train) [72][1760/2569] lr: 4.0000e-02 eta: 14:51:10 time: 0.2715 data_time: 0.0075 memory: 5828 grad_norm: 3.1331 loss: 2.7700 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7700 2023/06/05 06:04:50 - mmengine - INFO - Epoch(train) [72][1780/2569] lr: 4.0000e-02 eta: 14:51:04 time: 0.2588 data_time: 0.0073 memory: 5828 grad_norm: 3.0731 loss: 2.3175 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3175 2023/06/05 06:04:56 - mmengine - INFO - Epoch(train) [72][1800/2569] lr: 4.0000e-02 eta: 14:50:59 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 3.1096 loss: 2.4487 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4487 2023/06/05 06:05:01 - mmengine - INFO - Epoch(train) [72][1820/2569] lr: 4.0000e-02 eta: 14:50:53 time: 0.2582 data_time: 0.0074 memory: 5828 grad_norm: 3.1398 loss: 2.4602 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4602 2023/06/05 06:05:06 - mmengine - INFO - Epoch(train) [72][1840/2569] lr: 4.0000e-02 eta: 14:50:48 time: 0.2727 data_time: 0.0069 memory: 5828 grad_norm: 3.1270 loss: 2.4711 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4711 2023/06/05 06:05:11 - mmengine - INFO - Epoch(train) [72][1860/2569] lr: 4.0000e-02 eta: 14:50:43 time: 0.2610 data_time: 0.0078 memory: 5828 grad_norm: 3.1127 loss: 2.6816 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.6816 2023/06/05 06:05:17 - mmengine - INFO - Epoch(train) [72][1880/2569] lr: 4.0000e-02 eta: 14:50:37 time: 0.2629 data_time: 0.0073 memory: 5828 grad_norm: 3.1255 loss: 2.8236 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.8236 2023/06/05 06:05:22 - mmengine - INFO - Epoch(train) [72][1900/2569] lr: 4.0000e-02 eta: 14:50:32 time: 0.2576 data_time: 0.0078 memory: 5828 grad_norm: 3.1339 loss: 2.7280 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7280 2023/06/05 06:05:27 - mmengine - INFO - Epoch(train) [72][1920/2569] lr: 4.0000e-02 eta: 14:50:26 time: 0.2590 data_time: 0.0074 memory: 5828 grad_norm: 3.0952 loss: 2.2066 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2066 2023/06/05 06:05:32 - mmengine - INFO - Epoch(train) [72][1940/2569] lr: 4.0000e-02 eta: 14:50:21 time: 0.2659 data_time: 0.0073 memory: 5828 grad_norm: 3.1227 loss: 2.5663 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5663 2023/06/05 06:05:38 - mmengine - INFO - Epoch(train) [72][1960/2569] lr: 4.0000e-02 eta: 14:50:16 time: 0.2620 data_time: 0.0074 memory: 5828 grad_norm: 3.1549 loss: 2.7641 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.7641 2023/06/05 06:05:43 - mmengine - INFO - Epoch(train) [72][1980/2569] lr: 4.0000e-02 eta: 14:50:11 time: 0.2772 data_time: 0.0071 memory: 5828 grad_norm: 3.1752 loss: 2.5410 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5410 2023/06/05 06:05:48 - mmengine - INFO - Epoch(train) [72][2000/2569] lr: 4.0000e-02 eta: 14:50:05 time: 0.2575 data_time: 0.0072 memory: 5828 grad_norm: 3.0859 loss: 2.1722 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1722 2023/06/05 06:05:54 - mmengine - INFO - Epoch(train) [72][2020/2569] lr: 4.0000e-02 eta: 14:50:00 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.1512 loss: 2.5741 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5741 2023/06/05 06:05:59 - mmengine - INFO - Epoch(train) [72][2040/2569] lr: 4.0000e-02 eta: 14:49:54 time: 0.2601 data_time: 0.0074 memory: 5828 grad_norm: 3.1920 loss: 2.5528 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5528 2023/06/05 06:06:04 - mmengine - INFO - Epoch(train) [72][2060/2569] lr: 4.0000e-02 eta: 14:49:49 time: 0.2646 data_time: 0.0072 memory: 5828 grad_norm: 3.1119 loss: 2.4987 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4987 2023/06/05 06:06:09 - mmengine - INFO - Epoch(train) [72][2080/2569] lr: 4.0000e-02 eta: 14:49:43 time: 0.2577 data_time: 0.0073 memory: 5828 grad_norm: 3.0625 loss: 2.3741 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3741 2023/06/05 06:06:15 - mmengine - INFO - Epoch(train) [72][2100/2569] lr: 4.0000e-02 eta: 14:49:38 time: 0.2720 data_time: 0.0074 memory: 5828 grad_norm: 3.1272 loss: 2.5812 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5812 2023/06/05 06:06:20 - mmengine - INFO - Epoch(train) [72][2120/2569] lr: 4.0000e-02 eta: 14:49:33 time: 0.2584 data_time: 0.0077 memory: 5828 grad_norm: 3.1366 loss: 2.7756 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7756 2023/06/05 06:06:25 - mmengine - INFO - Epoch(train) [72][2140/2569] lr: 4.0000e-02 eta: 14:49:27 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 3.1492 loss: 2.6597 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6597 2023/06/05 06:06:30 - mmengine - INFO - Epoch(train) [72][2160/2569] lr: 4.0000e-02 eta: 14:49:22 time: 0.2626 data_time: 0.0078 memory: 5828 grad_norm: 3.0957 loss: 2.6604 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6604 2023/06/05 06:06:36 - mmengine - INFO - Epoch(train) [72][2180/2569] lr: 4.0000e-02 eta: 14:49:17 time: 0.2610 data_time: 0.0072 memory: 5828 grad_norm: 3.0868 loss: 2.6573 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6573 2023/06/05 06:06:41 - mmengine - INFO - Epoch(train) [72][2200/2569] lr: 4.0000e-02 eta: 14:49:11 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.1125 loss: 2.4966 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4966 2023/06/05 06:06:46 - mmengine - INFO - Epoch(train) [72][2220/2569] lr: 4.0000e-02 eta: 14:49:06 time: 0.2659 data_time: 0.0079 memory: 5828 grad_norm: 3.1123 loss: 2.7140 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7140 2023/06/05 06:06:52 - mmengine - INFO - Epoch(train) [72][2240/2569] lr: 4.0000e-02 eta: 14:49:01 time: 0.2642 data_time: 0.0075 memory: 5828 grad_norm: 3.1712 loss: 2.4570 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4570 2023/06/05 06:06:57 - mmengine - INFO - Epoch(train) [72][2260/2569] lr: 4.0000e-02 eta: 14:48:55 time: 0.2696 data_time: 0.0073 memory: 5828 grad_norm: 3.1449 loss: 2.3753 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3753 2023/06/05 06:07:02 - mmengine - INFO - Epoch(train) [72][2280/2569] lr: 4.0000e-02 eta: 14:48:50 time: 0.2595 data_time: 0.0077 memory: 5828 grad_norm: 3.1685 loss: 2.5492 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5492 2023/06/05 06:07:07 - mmengine - INFO - Epoch(train) [72][2300/2569] lr: 4.0000e-02 eta: 14:48:44 time: 0.2640 data_time: 0.0072 memory: 5828 grad_norm: 3.1972 loss: 2.6701 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6701 2023/06/05 06:07:13 - mmengine - INFO - Epoch(train) [72][2320/2569] lr: 4.0000e-02 eta: 14:48:39 time: 0.2599 data_time: 0.0071 memory: 5828 grad_norm: 3.1470 loss: 2.5455 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5455 2023/06/05 06:07:18 - mmengine - INFO - Epoch(train) [72][2340/2569] lr: 4.0000e-02 eta: 14:48:34 time: 0.2623 data_time: 0.0082 memory: 5828 grad_norm: 3.1558 loss: 2.4708 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4708 2023/06/05 06:07:23 - mmengine - INFO - Epoch(train) [72][2360/2569] lr: 4.0000e-02 eta: 14:48:28 time: 0.2593 data_time: 0.0078 memory: 5828 grad_norm: 3.1278 loss: 2.4685 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4685 2023/06/05 06:07:28 - mmengine - INFO - Epoch(train) [72][2380/2569] lr: 4.0000e-02 eta: 14:48:23 time: 0.2601 data_time: 0.0082 memory: 5828 grad_norm: 3.1186 loss: 2.6394 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6394 2023/06/05 06:07:34 - mmengine - INFO - Epoch(train) [72][2400/2569] lr: 4.0000e-02 eta: 14:48:17 time: 0.2634 data_time: 0.0083 memory: 5828 grad_norm: 3.0807 loss: 2.6224 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6224 2023/06/05 06:07:39 - mmengine - INFO - Epoch(train) [72][2420/2569] lr: 4.0000e-02 eta: 14:48:12 time: 0.2694 data_time: 0.0081 memory: 5828 grad_norm: 3.1621 loss: 2.3134 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3134 2023/06/05 06:07:44 - mmengine - INFO - Epoch(train) [72][2440/2569] lr: 4.0000e-02 eta: 14:48:07 time: 0.2688 data_time: 0.0076 memory: 5828 grad_norm: 3.0932 loss: 2.2109 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2109 2023/06/05 06:07:50 - mmengine - INFO - Epoch(train) [72][2460/2569] lr: 4.0000e-02 eta: 14:48:02 time: 0.2796 data_time: 0.0073 memory: 5828 grad_norm: 3.2026 loss: 2.7108 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7108 2023/06/05 06:07:55 - mmengine - INFO - Epoch(train) [72][2480/2569] lr: 4.0000e-02 eta: 14:47:57 time: 0.2694 data_time: 0.0077 memory: 5828 grad_norm: 3.1508 loss: 2.5440 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5440 2023/06/05 06:08:01 - mmengine - INFO - Epoch(train) [72][2500/2569] lr: 4.0000e-02 eta: 14:47:51 time: 0.2635 data_time: 0.0079 memory: 5828 grad_norm: 3.1090 loss: 2.9212 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9212 2023/06/05 06:08:06 - mmengine - INFO - Epoch(train) [72][2520/2569] lr: 4.0000e-02 eta: 14:47:46 time: 0.2627 data_time: 0.0078 memory: 5828 grad_norm: 3.1051 loss: 2.5108 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5108 2023/06/05 06:08:11 - mmengine - INFO - Epoch(train) [72][2540/2569] lr: 4.0000e-02 eta: 14:47:41 time: 0.2685 data_time: 0.0086 memory: 5828 grad_norm: 3.1208 loss: 2.4555 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4555 2023/06/05 06:08:17 - mmengine - INFO - Epoch(train) [72][2560/2569] lr: 4.0000e-02 eta: 14:47:35 time: 0.2642 data_time: 0.0079 memory: 5828 grad_norm: 3.1728 loss: 2.4846 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4846 2023/06/05 06:08:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:08:19 - mmengine - INFO - Epoch(train) [72][2569/2569] lr: 4.0000e-02 eta: 14:47:33 time: 0.2589 data_time: 0.0076 memory: 5828 grad_norm: 3.1663 loss: 2.6411 top1_acc: 0.1667 top5_acc: 0.6667 loss_cls: 2.6411 2023/06/05 06:08:19 - mmengine - INFO - Saving checkpoint at 72 epochs 2023/06/05 06:08:27 - mmengine - INFO - Epoch(train) [73][ 20/2569] lr: 4.0000e-02 eta: 14:47:28 time: 0.3140 data_time: 0.0478 memory: 5828 grad_norm: 3.0968 loss: 2.4509 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.4509 2023/06/05 06:08:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:08:32 - mmengine - INFO - Epoch(train) [73][ 40/2569] lr: 4.0000e-02 eta: 14:47:23 time: 0.2602 data_time: 0.0080 memory: 5828 grad_norm: 3.0470 loss: 2.3845 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3845 2023/06/05 06:08:37 - mmengine - INFO - Epoch(train) [73][ 60/2569] lr: 4.0000e-02 eta: 14:47:18 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 3.0416 loss: 2.3225 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3225 2023/06/05 06:08:43 - mmengine - INFO - Epoch(train) [73][ 80/2569] lr: 4.0000e-02 eta: 14:47:12 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 3.1033 loss: 2.6604 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6604 2023/06/05 06:08:48 - mmengine - INFO - Epoch(train) [73][ 100/2569] lr: 4.0000e-02 eta: 14:47:07 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.0704 loss: 2.4847 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4847 2023/06/05 06:08:53 - mmengine - INFO - Epoch(train) [73][ 120/2569] lr: 4.0000e-02 eta: 14:47:02 time: 0.2693 data_time: 0.0078 memory: 5828 grad_norm: 3.1066 loss: 2.4155 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4155 2023/06/05 06:08:59 - mmengine - INFO - Epoch(train) [73][ 140/2569] lr: 4.0000e-02 eta: 14:46:56 time: 0.2574 data_time: 0.0073 memory: 5828 grad_norm: 3.0816 loss: 2.7566 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7566 2023/06/05 06:09:04 - mmengine - INFO - Epoch(train) [73][ 160/2569] lr: 4.0000e-02 eta: 14:46:51 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 3.1366 loss: 2.4444 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4444 2023/06/05 06:09:09 - mmengine - INFO - Epoch(train) [73][ 180/2569] lr: 4.0000e-02 eta: 14:46:45 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 3.1073 loss: 2.2888 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2888 2023/06/05 06:09:15 - mmengine - INFO - Epoch(train) [73][ 200/2569] lr: 4.0000e-02 eta: 14:46:40 time: 0.2676 data_time: 0.0075 memory: 5828 grad_norm: 3.1011 loss: 2.3067 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3067 2023/06/05 06:09:20 - mmengine - INFO - Epoch(train) [73][ 220/2569] lr: 4.0000e-02 eta: 14:46:35 time: 0.2638 data_time: 0.0075 memory: 5828 grad_norm: 3.0491 loss: 2.4700 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4700 2023/06/05 06:09:25 - mmengine - INFO - Epoch(train) [73][ 240/2569] lr: 4.0000e-02 eta: 14:46:30 time: 0.2666 data_time: 0.0085 memory: 5828 grad_norm: 3.1274 loss: 2.4266 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4266 2023/06/05 06:09:30 - mmengine - INFO - Epoch(train) [73][ 260/2569] lr: 4.0000e-02 eta: 14:46:24 time: 0.2680 data_time: 0.0078 memory: 5828 grad_norm: 3.0793 loss: 2.3531 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3531 2023/06/05 06:09:36 - mmengine - INFO - Epoch(train) [73][ 280/2569] lr: 4.0000e-02 eta: 14:46:19 time: 0.2581 data_time: 0.0074 memory: 5828 grad_norm: 3.1002 loss: 2.3659 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3659 2023/06/05 06:09:41 - mmengine - INFO - Epoch(train) [73][ 300/2569] lr: 4.0000e-02 eta: 14:46:13 time: 0.2591 data_time: 0.0076 memory: 5828 grad_norm: 3.1590 loss: 2.4977 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4977 2023/06/05 06:09:46 - mmengine - INFO - Epoch(train) [73][ 320/2569] lr: 4.0000e-02 eta: 14:46:08 time: 0.2684 data_time: 0.0070 memory: 5828 grad_norm: 3.0896 loss: 2.2525 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2525 2023/06/05 06:09:51 - mmengine - INFO - Epoch(train) [73][ 340/2569] lr: 4.0000e-02 eta: 14:46:03 time: 0.2572 data_time: 0.0074 memory: 5828 grad_norm: 3.1233 loss: 2.4131 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4131 2023/06/05 06:09:57 - mmengine - INFO - Epoch(train) [73][ 360/2569] lr: 4.0000e-02 eta: 14:45:57 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 3.0907 loss: 2.7528 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7528 2023/06/05 06:10:02 - mmengine - INFO - Epoch(train) [73][ 380/2569] lr: 4.0000e-02 eta: 14:45:52 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 3.1243 loss: 2.3020 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3020 2023/06/05 06:10:07 - mmengine - INFO - Epoch(train) [73][ 400/2569] lr: 4.0000e-02 eta: 14:45:46 time: 0.2578 data_time: 0.0075 memory: 5828 grad_norm: 3.1395 loss: 2.5306 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5306 2023/06/05 06:10:13 - mmengine - INFO - Epoch(train) [73][ 420/2569] lr: 4.0000e-02 eta: 14:45:41 time: 0.2777 data_time: 0.0074 memory: 5828 grad_norm: 3.0994 loss: 2.8126 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8126 2023/06/05 06:10:18 - mmengine - INFO - Epoch(train) [73][ 440/2569] lr: 4.0000e-02 eta: 14:45:36 time: 0.2594 data_time: 0.0081 memory: 5828 grad_norm: 3.1255 loss: 2.3371 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3371 2023/06/05 06:10:23 - mmengine - INFO - Epoch(train) [73][ 460/2569] lr: 4.0000e-02 eta: 14:45:31 time: 0.2749 data_time: 0.0073 memory: 5828 grad_norm: 3.1078 loss: 2.3158 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3158 2023/06/05 06:10:28 - mmengine - INFO - Epoch(train) [73][ 480/2569] lr: 4.0000e-02 eta: 14:45:25 time: 0.2579 data_time: 0.0079 memory: 5828 grad_norm: 3.1674 loss: 2.4431 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4431 2023/06/05 06:10:34 - mmengine - INFO - Epoch(train) [73][ 500/2569] lr: 4.0000e-02 eta: 14:45:20 time: 0.2712 data_time: 0.0089 memory: 5828 grad_norm: 3.1068 loss: 2.3584 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3584 2023/06/05 06:10:39 - mmengine - INFO - Epoch(train) [73][ 520/2569] lr: 4.0000e-02 eta: 14:45:15 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 3.1185 loss: 2.5922 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5922 2023/06/05 06:10:44 - mmengine - INFO - Epoch(train) [73][ 540/2569] lr: 4.0000e-02 eta: 14:45:09 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 3.1003 loss: 2.1741 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1741 2023/06/05 06:10:50 - mmengine - INFO - Epoch(train) [73][ 560/2569] lr: 4.0000e-02 eta: 14:45:04 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 3.0267 loss: 2.5856 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5856 2023/06/05 06:10:55 - mmengine - INFO - Epoch(train) [73][ 580/2569] lr: 4.0000e-02 eta: 14:44:58 time: 0.2588 data_time: 0.0075 memory: 5828 grad_norm: 3.1098 loss: 2.3919 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3919 2023/06/05 06:11:00 - mmengine - INFO - Epoch(train) [73][ 600/2569] lr: 4.0000e-02 eta: 14:44:53 time: 0.2716 data_time: 0.0070 memory: 5828 grad_norm: 3.1890 loss: 2.4218 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4218 2023/06/05 06:11:06 - mmengine - INFO - Epoch(train) [73][ 620/2569] lr: 4.0000e-02 eta: 14:44:48 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 3.0878 loss: 2.4017 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4017 2023/06/05 06:11:11 - mmengine - INFO - Epoch(train) [73][ 640/2569] lr: 4.0000e-02 eta: 14:44:43 time: 0.2642 data_time: 0.0071 memory: 5828 grad_norm: 3.1481 loss: 2.5644 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5644 2023/06/05 06:11:16 - mmengine - INFO - Epoch(train) [73][ 660/2569] lr: 4.0000e-02 eta: 14:44:37 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 3.1337 loss: 2.0573 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0573 2023/06/05 06:11:22 - mmengine - INFO - Epoch(train) [73][ 680/2569] lr: 4.0000e-02 eta: 14:44:32 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 3.1418 loss: 2.6175 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6175 2023/06/05 06:11:27 - mmengine - INFO - Epoch(train) [73][ 700/2569] lr: 4.0000e-02 eta: 14:44:27 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 3.0285 loss: 2.1789 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1789 2023/06/05 06:11:32 - mmengine - INFO - Epoch(train) [73][ 720/2569] lr: 4.0000e-02 eta: 14:44:21 time: 0.2590 data_time: 0.0078 memory: 5828 grad_norm: 3.2179 loss: 2.9072 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.9072 2023/06/05 06:11:37 - mmengine - INFO - Epoch(train) [73][ 740/2569] lr: 4.0000e-02 eta: 14:44:16 time: 0.2675 data_time: 0.0081 memory: 5828 grad_norm: 3.1081 loss: 2.5636 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5636 2023/06/05 06:11:43 - mmengine - INFO - Epoch(train) [73][ 760/2569] lr: 4.0000e-02 eta: 14:44:11 time: 0.2728 data_time: 0.0077 memory: 5828 grad_norm: 3.1151 loss: 2.3687 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3687 2023/06/05 06:11:48 - mmengine - INFO - Epoch(train) [73][ 780/2569] lr: 4.0000e-02 eta: 14:44:05 time: 0.2577 data_time: 0.0075 memory: 5828 grad_norm: 3.1170 loss: 2.5956 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5956 2023/06/05 06:11:53 - mmengine - INFO - Epoch(train) [73][ 800/2569] lr: 4.0000e-02 eta: 14:44:00 time: 0.2641 data_time: 0.0078 memory: 5828 grad_norm: 3.0949 loss: 2.6932 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6932 2023/06/05 06:11:59 - mmengine - INFO - Epoch(train) [73][ 820/2569] lr: 4.0000e-02 eta: 14:43:55 time: 0.2714 data_time: 0.0075 memory: 5828 grad_norm: 3.0868 loss: 2.3553 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3553 2023/06/05 06:12:04 - mmengine - INFO - Epoch(train) [73][ 840/2569] lr: 4.0000e-02 eta: 14:43:49 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 3.1029 loss: 2.4912 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4912 2023/06/05 06:12:09 - mmengine - INFO - Epoch(train) [73][ 860/2569] lr: 4.0000e-02 eta: 14:43:44 time: 0.2636 data_time: 0.0072 memory: 5828 grad_norm: 3.1444 loss: 2.4063 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4063 2023/06/05 06:12:15 - mmengine - INFO - Epoch(train) [73][ 880/2569] lr: 4.0000e-02 eta: 14:43:39 time: 0.2580 data_time: 0.0073 memory: 5828 grad_norm: 3.1303 loss: 2.3794 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3794 2023/06/05 06:12:20 - mmengine - INFO - Epoch(train) [73][ 900/2569] lr: 4.0000e-02 eta: 14:43:33 time: 0.2622 data_time: 0.0074 memory: 5828 grad_norm: 3.1440 loss: 2.5273 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5273 2023/06/05 06:12:25 - mmengine - INFO - Epoch(train) [73][ 920/2569] lr: 4.0000e-02 eta: 14:43:28 time: 0.2694 data_time: 0.0074 memory: 5828 grad_norm: 3.1089 loss: 2.3842 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3842 2023/06/05 06:12:30 - mmengine - INFO - Epoch(train) [73][ 940/2569] lr: 4.0000e-02 eta: 14:43:22 time: 0.2601 data_time: 0.0076 memory: 5828 grad_norm: 3.1219 loss: 2.5229 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5229 2023/06/05 06:12:36 - mmengine - INFO - Epoch(train) [73][ 960/2569] lr: 4.0000e-02 eta: 14:43:17 time: 0.2759 data_time: 0.0076 memory: 5828 grad_norm: 3.1419 loss: 2.7456 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7456 2023/06/05 06:12:41 - mmengine - INFO - Epoch(train) [73][ 980/2569] lr: 4.0000e-02 eta: 14:43:12 time: 0.2668 data_time: 0.0075 memory: 5828 grad_norm: 3.1218 loss: 2.9342 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9342 2023/06/05 06:12:47 - mmengine - INFO - Epoch(train) [73][1000/2569] lr: 4.0000e-02 eta: 14:43:07 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 3.1018 loss: 2.6855 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6855 2023/06/05 06:12:52 - mmengine - INFO - Epoch(train) [73][1020/2569] lr: 4.0000e-02 eta: 14:43:01 time: 0.2652 data_time: 0.0073 memory: 5828 grad_norm: 3.1309 loss: 2.3745 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3745 2023/06/05 06:12:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:12:57 - mmengine - INFO - Epoch(train) [73][1040/2569] lr: 4.0000e-02 eta: 14:42:56 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 3.1597 loss: 2.2201 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2201 2023/06/05 06:13:03 - mmengine - INFO - Epoch(train) [73][1060/2569] lr: 4.0000e-02 eta: 14:42:51 time: 0.2767 data_time: 0.0081 memory: 5828 grad_norm: 3.0756 loss: 2.4420 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4420 2023/06/05 06:13:08 - mmengine - INFO - Epoch(train) [73][1080/2569] lr: 4.0000e-02 eta: 14:42:46 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 3.2059 loss: 2.5884 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5884 2023/06/05 06:13:13 - mmengine - INFO - Epoch(train) [73][1100/2569] lr: 4.0000e-02 eta: 14:42:40 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 3.1755 loss: 2.0793 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0793 2023/06/05 06:13:19 - mmengine - INFO - Epoch(train) [73][1120/2569] lr: 4.0000e-02 eta: 14:42:35 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.1081 loss: 2.5500 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5500 2023/06/05 06:13:24 - mmengine - INFO - Epoch(train) [73][1140/2569] lr: 4.0000e-02 eta: 14:42:30 time: 0.2637 data_time: 0.0071 memory: 5828 grad_norm: 3.1169 loss: 2.4464 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4464 2023/06/05 06:13:29 - mmengine - INFO - Epoch(train) [73][1160/2569] lr: 4.0000e-02 eta: 14:42:24 time: 0.2687 data_time: 0.0076 memory: 5828 grad_norm: 3.1224 loss: 2.5459 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5459 2023/06/05 06:13:35 - mmengine - INFO - Epoch(train) [73][1180/2569] lr: 4.0000e-02 eta: 14:42:19 time: 0.2686 data_time: 0.0076 memory: 5828 grad_norm: 3.1444 loss: 2.3937 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3937 2023/06/05 06:13:40 - mmengine - INFO - Epoch(train) [73][1200/2569] lr: 4.0000e-02 eta: 14:42:14 time: 0.2612 data_time: 0.0075 memory: 5828 grad_norm: 3.1833 loss: 2.8247 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8247 2023/06/05 06:13:45 - mmengine - INFO - Epoch(train) [73][1220/2569] lr: 4.0000e-02 eta: 14:42:08 time: 0.2724 data_time: 0.0077 memory: 5828 grad_norm: 3.1069 loss: 2.7336 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7336 2023/06/05 06:13:51 - mmengine - INFO - Epoch(train) [73][1240/2569] lr: 4.0000e-02 eta: 14:42:03 time: 0.2612 data_time: 0.0075 memory: 5828 grad_norm: 3.1534 loss: 2.6579 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6579 2023/06/05 06:13:56 - mmengine - INFO - Epoch(train) [73][1260/2569] lr: 4.0000e-02 eta: 14:41:58 time: 0.2641 data_time: 0.0077 memory: 5828 grad_norm: 3.1344 loss: 2.7213 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7213 2023/06/05 06:14:01 - mmengine - INFO - Epoch(train) [73][1280/2569] lr: 4.0000e-02 eta: 14:41:52 time: 0.2618 data_time: 0.0078 memory: 5828 grad_norm: 3.1401 loss: 2.4935 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4935 2023/06/05 06:14:06 - mmengine - INFO - Epoch(train) [73][1300/2569] lr: 4.0000e-02 eta: 14:41:47 time: 0.2661 data_time: 0.0074 memory: 5828 grad_norm: 3.1394 loss: 2.3749 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3749 2023/06/05 06:14:12 - mmengine - INFO - Epoch(train) [73][1320/2569] lr: 4.0000e-02 eta: 14:41:42 time: 0.2653 data_time: 0.0075 memory: 5828 grad_norm: 3.1437 loss: 2.6088 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6088 2023/06/05 06:14:17 - mmengine - INFO - Epoch(train) [73][1340/2569] lr: 4.0000e-02 eta: 14:41:36 time: 0.2656 data_time: 0.0075 memory: 5828 grad_norm: 3.1190 loss: 2.3618 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3618 2023/06/05 06:14:22 - mmengine - INFO - Epoch(train) [73][1360/2569] lr: 4.0000e-02 eta: 14:41:31 time: 0.2595 data_time: 0.0082 memory: 5828 grad_norm: 3.1770 loss: 2.3654 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3654 2023/06/05 06:14:27 - mmengine - INFO - Epoch(train) [73][1380/2569] lr: 4.0000e-02 eta: 14:41:25 time: 0.2587 data_time: 0.0074 memory: 5828 grad_norm: 3.1894 loss: 2.5133 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5133 2023/06/05 06:14:33 - mmengine - INFO - Epoch(train) [73][1400/2569] lr: 4.0000e-02 eta: 14:41:20 time: 0.2765 data_time: 0.0075 memory: 5828 grad_norm: 3.1774 loss: 2.3962 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3962 2023/06/05 06:14:38 - mmengine - INFO - Epoch(train) [73][1420/2569] lr: 4.0000e-02 eta: 14:41:15 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 3.1560 loss: 1.9297 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9297 2023/06/05 06:14:44 - mmengine - INFO - Epoch(train) [73][1440/2569] lr: 4.0000e-02 eta: 14:41:10 time: 0.2723 data_time: 0.0074 memory: 5828 grad_norm: 3.1970 loss: 2.3482 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3482 2023/06/05 06:14:50 - mmengine - INFO - Epoch(train) [73][1460/2569] lr: 4.0000e-02 eta: 14:41:06 time: 0.3282 data_time: 0.0075 memory: 5828 grad_norm: 3.1662 loss: 2.6269 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6269 2023/06/05 06:14:55 - mmengine - INFO - Epoch(train) [73][1480/2569] lr: 4.0000e-02 eta: 14:41:00 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 3.1530 loss: 2.4401 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4401 2023/06/05 06:15:01 - mmengine - INFO - Epoch(train) [73][1500/2569] lr: 4.0000e-02 eta: 14:40:55 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 3.1147 loss: 2.6819 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6819 2023/06/05 06:15:06 - mmengine - INFO - Epoch(train) [73][1520/2569] lr: 4.0000e-02 eta: 14:40:50 time: 0.2693 data_time: 0.0074 memory: 5828 grad_norm: 3.1166 loss: 2.3052 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3052 2023/06/05 06:15:11 - mmengine - INFO - Epoch(train) [73][1540/2569] lr: 4.0000e-02 eta: 14:40:44 time: 0.2575 data_time: 0.0080 memory: 5828 grad_norm: 3.1565 loss: 2.3032 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3032 2023/06/05 06:15:17 - mmengine - INFO - Epoch(train) [73][1560/2569] lr: 4.0000e-02 eta: 14:40:39 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 3.1105 loss: 2.6889 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6889 2023/06/05 06:15:22 - mmengine - INFO - Epoch(train) [73][1580/2569] lr: 4.0000e-02 eta: 14:40:34 time: 0.2647 data_time: 0.0075 memory: 5828 grad_norm: 3.1001 loss: 2.8134 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8134 2023/06/05 06:15:27 - mmengine - INFO - Epoch(train) [73][1600/2569] lr: 4.0000e-02 eta: 14:40:28 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 3.1846 loss: 2.2545 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2545 2023/06/05 06:15:33 - mmengine - INFO - Epoch(train) [73][1620/2569] lr: 4.0000e-02 eta: 14:40:23 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 3.0697 loss: 2.7376 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7376 2023/06/05 06:15:38 - mmengine - INFO - Epoch(train) [73][1640/2569] lr: 4.0000e-02 eta: 14:40:18 time: 0.2648 data_time: 0.0076 memory: 5828 grad_norm: 3.1274 loss: 2.3818 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3818 2023/06/05 06:15:43 - mmengine - INFO - Epoch(train) [73][1660/2569] lr: 4.0000e-02 eta: 14:40:12 time: 0.2635 data_time: 0.0079 memory: 5828 grad_norm: 3.1194 loss: 2.3063 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3063 2023/06/05 06:15:49 - mmengine - INFO - Epoch(train) [73][1680/2569] lr: 4.0000e-02 eta: 14:40:07 time: 0.2676 data_time: 0.0077 memory: 5828 grad_norm: 3.1247 loss: 2.6845 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6845 2023/06/05 06:15:54 - mmengine - INFO - Epoch(train) [73][1700/2569] lr: 4.0000e-02 eta: 14:40:02 time: 0.2581 data_time: 0.0074 memory: 5828 grad_norm: 3.2021 loss: 2.5116 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5116 2023/06/05 06:15:59 - mmengine - INFO - Epoch(train) [73][1720/2569] lr: 4.0000e-02 eta: 14:39:56 time: 0.2673 data_time: 0.0076 memory: 5828 grad_norm: 3.0939 loss: 2.5072 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5072 2023/06/05 06:16:04 - mmengine - INFO - Epoch(train) [73][1740/2569] lr: 4.0000e-02 eta: 14:39:51 time: 0.2583 data_time: 0.0075 memory: 5828 grad_norm: 3.1684 loss: 2.6051 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6051 2023/06/05 06:16:10 - mmengine - INFO - Epoch(train) [73][1760/2569] lr: 4.0000e-02 eta: 14:39:46 time: 0.2696 data_time: 0.0074 memory: 5828 grad_norm: 3.1039 loss: 2.6132 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6132 2023/06/05 06:16:15 - mmengine - INFO - Epoch(train) [73][1780/2569] lr: 4.0000e-02 eta: 14:39:40 time: 0.2575 data_time: 0.0071 memory: 5828 grad_norm: 3.1555 loss: 2.9218 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9218 2023/06/05 06:16:20 - mmengine - INFO - Epoch(train) [73][1800/2569] lr: 4.0000e-02 eta: 14:39:35 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.1024 loss: 2.3188 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.3188 2023/06/05 06:16:25 - mmengine - INFO - Epoch(train) [73][1820/2569] lr: 4.0000e-02 eta: 14:39:29 time: 0.2587 data_time: 0.0085 memory: 5828 grad_norm: 3.0773 loss: 2.6114 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6114 2023/06/05 06:16:30 - mmengine - INFO - Epoch(train) [73][1840/2569] lr: 4.0000e-02 eta: 14:39:24 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 3.0825 loss: 2.2369 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2369 2023/06/05 06:16:36 - mmengine - INFO - Epoch(train) [73][1860/2569] lr: 4.0000e-02 eta: 14:39:18 time: 0.2585 data_time: 0.0070 memory: 5828 grad_norm: 3.1723 loss: 2.7832 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7832 2023/06/05 06:16:41 - mmengine - INFO - Epoch(train) [73][1880/2569] lr: 4.0000e-02 eta: 14:39:13 time: 0.2762 data_time: 0.0074 memory: 5828 grad_norm: 3.1475 loss: 2.3987 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3987 2023/06/05 06:16:46 - mmengine - INFO - Epoch(train) [73][1900/2569] lr: 4.0000e-02 eta: 14:39:08 time: 0.2594 data_time: 0.0072 memory: 5828 grad_norm: 3.1185 loss: 2.3190 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.3190 2023/06/05 06:16:52 - mmengine - INFO - Epoch(train) [73][1920/2569] lr: 4.0000e-02 eta: 14:39:02 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 3.1217 loss: 2.6343 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6343 2023/06/05 06:16:57 - mmengine - INFO - Epoch(train) [73][1940/2569] lr: 4.0000e-02 eta: 14:38:57 time: 0.2617 data_time: 0.0076 memory: 5828 grad_norm: 3.1780 loss: 2.3418 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3418 2023/06/05 06:17:02 - mmengine - INFO - Epoch(train) [73][1960/2569] lr: 4.0000e-02 eta: 14:38:52 time: 0.2667 data_time: 0.0080 memory: 5828 grad_norm: 3.1222 loss: 2.3455 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3455 2023/06/05 06:17:07 - mmengine - INFO - Epoch(train) [73][1980/2569] lr: 4.0000e-02 eta: 14:38:46 time: 0.2619 data_time: 0.0071 memory: 5828 grad_norm: 3.2093 loss: 2.7868 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.7868 2023/06/05 06:17:13 - mmengine - INFO - Epoch(train) [73][2000/2569] lr: 4.0000e-02 eta: 14:38:41 time: 0.2692 data_time: 0.0081 memory: 5828 grad_norm: 3.1683 loss: 2.3847 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3847 2023/06/05 06:17:18 - mmengine - INFO - Epoch(train) [73][2020/2569] lr: 4.0000e-02 eta: 14:38:36 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 3.0626 loss: 2.7138 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7138 2023/06/05 06:17:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:17:24 - mmengine - INFO - Epoch(train) [73][2040/2569] lr: 4.0000e-02 eta: 14:38:31 time: 0.2714 data_time: 0.0077 memory: 5828 grad_norm: 3.1069 loss: 2.3682 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3682 2023/06/05 06:17:29 - mmengine - INFO - Epoch(train) [73][2060/2569] lr: 4.0000e-02 eta: 14:38:25 time: 0.2585 data_time: 0.0076 memory: 5828 grad_norm: 3.1361 loss: 2.5392 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5392 2023/06/05 06:17:34 - mmengine - INFO - Epoch(train) [73][2080/2569] lr: 4.0000e-02 eta: 14:38:20 time: 0.2661 data_time: 0.0079 memory: 5828 grad_norm: 3.0726 loss: 2.7289 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7289 2023/06/05 06:17:39 - mmengine - INFO - Epoch(train) [73][2100/2569] lr: 4.0000e-02 eta: 14:38:14 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 3.1579 loss: 2.9175 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.9175 2023/06/05 06:17:45 - mmengine - INFO - Epoch(train) [73][2120/2569] lr: 4.0000e-02 eta: 14:38:09 time: 0.2594 data_time: 0.0075 memory: 5828 grad_norm: 3.1340 loss: 2.6940 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6940 2023/06/05 06:17:50 - mmengine - INFO - Epoch(train) [73][2140/2569] lr: 4.0000e-02 eta: 14:38:04 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 3.1274 loss: 2.4923 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4923 2023/06/05 06:17:55 - mmengine - INFO - Epoch(train) [73][2160/2569] lr: 4.0000e-02 eta: 14:37:58 time: 0.2699 data_time: 0.0076 memory: 5828 grad_norm: 3.1054 loss: 2.5262 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5262 2023/06/05 06:18:00 - mmengine - INFO - Epoch(train) [73][2180/2569] lr: 4.0000e-02 eta: 14:37:53 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 3.1422 loss: 2.6936 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6936 2023/06/05 06:18:06 - mmengine - INFO - Epoch(train) [73][2200/2569] lr: 4.0000e-02 eta: 14:37:48 time: 0.2719 data_time: 0.0077 memory: 5828 grad_norm: 3.0829 loss: 2.4952 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4952 2023/06/05 06:18:11 - mmengine - INFO - Epoch(train) [73][2220/2569] lr: 4.0000e-02 eta: 14:37:42 time: 0.2597 data_time: 0.0077 memory: 5828 grad_norm: 3.2053 loss: 2.6306 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6306 2023/06/05 06:18:17 - mmengine - INFO - Epoch(train) [73][2240/2569] lr: 4.0000e-02 eta: 14:37:37 time: 0.2705 data_time: 0.0078 memory: 5828 grad_norm: 3.0820 loss: 2.4807 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4807 2023/06/05 06:18:22 - mmengine - INFO - Epoch(train) [73][2260/2569] lr: 4.0000e-02 eta: 14:37:32 time: 0.2644 data_time: 0.0069 memory: 5828 grad_norm: 3.0821 loss: 2.4327 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4327 2023/06/05 06:18:27 - mmengine - INFO - Epoch(train) [73][2280/2569] lr: 4.0000e-02 eta: 14:37:27 time: 0.2694 data_time: 0.0075 memory: 5828 grad_norm: 3.1660 loss: 2.8684 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.8684 2023/06/05 06:18:33 - mmengine - INFO - Epoch(train) [73][2300/2569] lr: 4.0000e-02 eta: 14:37:21 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 3.1469 loss: 2.5382 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5382 2023/06/05 06:18:38 - mmengine - INFO - Epoch(train) [73][2320/2569] lr: 4.0000e-02 eta: 14:37:16 time: 0.2606 data_time: 0.0075 memory: 5828 grad_norm: 3.1484 loss: 2.5801 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5801 2023/06/05 06:18:43 - mmengine - INFO - Epoch(train) [73][2340/2569] lr: 4.0000e-02 eta: 14:37:10 time: 0.2578 data_time: 0.0072 memory: 5828 grad_norm: 3.1504 loss: 2.7714 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7714 2023/06/05 06:18:48 - mmengine - INFO - Epoch(train) [73][2360/2569] lr: 4.0000e-02 eta: 14:37:05 time: 0.2607 data_time: 0.0073 memory: 5828 grad_norm: 3.0580 loss: 2.7164 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7164 2023/06/05 06:18:54 - mmengine - INFO - Epoch(train) [73][2380/2569] lr: 4.0000e-02 eta: 14:37:00 time: 0.2743 data_time: 0.0075 memory: 5828 grad_norm: 3.0902 loss: 2.3033 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3033 2023/06/05 06:18:59 - mmengine - INFO - Epoch(train) [73][2400/2569] lr: 4.0000e-02 eta: 14:36:55 time: 0.2685 data_time: 0.0076 memory: 5828 grad_norm: 3.2018 loss: 2.5792 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5792 2023/06/05 06:19:04 - mmengine - INFO - Epoch(train) [73][2420/2569] lr: 4.0000e-02 eta: 14:36:49 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 3.1739 loss: 2.6534 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6534 2023/06/05 06:19:10 - mmengine - INFO - Epoch(train) [73][2440/2569] lr: 4.0000e-02 eta: 14:36:44 time: 0.2703 data_time: 0.0075 memory: 5828 grad_norm: 3.1934 loss: 2.3895 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3895 2023/06/05 06:19:15 - mmengine - INFO - Epoch(train) [73][2460/2569] lr: 4.0000e-02 eta: 14:36:39 time: 0.2603 data_time: 0.0076 memory: 5828 grad_norm: 3.1309 loss: 2.5453 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5453 2023/06/05 06:19:20 - mmengine - INFO - Epoch(train) [73][2480/2569] lr: 4.0000e-02 eta: 14:36:33 time: 0.2736 data_time: 0.0072 memory: 5828 grad_norm: 3.0917 loss: 2.7287 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7287 2023/06/05 06:19:26 - mmengine - INFO - Epoch(train) [73][2500/2569] lr: 4.0000e-02 eta: 14:36:28 time: 0.2688 data_time: 0.0076 memory: 5828 grad_norm: 3.0974 loss: 2.4490 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4490 2023/06/05 06:19:31 - mmengine - INFO - Epoch(train) [73][2520/2569] lr: 4.0000e-02 eta: 14:36:23 time: 0.2653 data_time: 0.0078 memory: 5828 grad_norm: 3.1426 loss: 2.4445 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4445 2023/06/05 06:19:36 - mmengine - INFO - Epoch(train) [73][2540/2569] lr: 4.0000e-02 eta: 14:36:17 time: 0.2577 data_time: 0.0077 memory: 5828 grad_norm: 3.0368 loss: 2.5239 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5239 2023/06/05 06:19:42 - mmengine - INFO - Epoch(train) [73][2560/2569] lr: 4.0000e-02 eta: 14:36:12 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 3.1272 loss: 2.4000 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4000 2023/06/05 06:19:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:19:44 - mmengine - INFO - Epoch(train) [73][2569/2569] lr: 4.0000e-02 eta: 14:36:09 time: 0.2562 data_time: 0.0073 memory: 5828 grad_norm: 3.1984 loss: 2.3570 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3570 2023/06/05 06:19:51 - mmengine - INFO - Epoch(train) [74][ 20/2569] lr: 4.0000e-02 eta: 14:36:06 time: 0.3454 data_time: 0.0588 memory: 5828 grad_norm: 3.1741 loss: 2.5714 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.5714 2023/06/05 06:19:56 - mmengine - INFO - Epoch(train) [74][ 40/2569] lr: 4.0000e-02 eta: 14:36:01 time: 0.2753 data_time: 0.0074 memory: 5828 grad_norm: 3.0960 loss: 2.4716 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.4716 2023/06/05 06:20:02 - mmengine - INFO - Epoch(train) [74][ 60/2569] lr: 4.0000e-02 eta: 14:35:55 time: 0.2607 data_time: 0.0075 memory: 5828 grad_norm: 3.1629 loss: 2.5488 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5488 2023/06/05 06:20:07 - mmengine - INFO - Epoch(train) [74][ 80/2569] lr: 4.0000e-02 eta: 14:35:50 time: 0.2889 data_time: 0.0076 memory: 5828 grad_norm: 3.1200 loss: 2.4842 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4842 2023/06/05 06:20:12 - mmengine - INFO - Epoch(train) [74][ 100/2569] lr: 4.0000e-02 eta: 14:35:45 time: 0.2582 data_time: 0.0074 memory: 5828 grad_norm: 3.1286 loss: 2.7909 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7909 2023/06/05 06:20:18 - mmengine - INFO - Epoch(train) [74][ 120/2569] lr: 4.0000e-02 eta: 14:35:40 time: 0.2745 data_time: 0.0077 memory: 5828 grad_norm: 3.1836 loss: 2.6539 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6539 2023/06/05 06:20:23 - mmengine - INFO - Epoch(train) [74][ 140/2569] lr: 4.0000e-02 eta: 14:35:35 time: 0.2702 data_time: 0.0075 memory: 5828 grad_norm: 3.1893 loss: 2.4670 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4670 2023/06/05 06:20:29 - mmengine - INFO - Epoch(train) [74][ 160/2569] lr: 4.0000e-02 eta: 14:35:30 time: 0.2736 data_time: 0.0073 memory: 5828 grad_norm: 3.1066 loss: 2.6492 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6492 2023/06/05 06:20:34 - mmengine - INFO - Epoch(train) [74][ 180/2569] lr: 4.0000e-02 eta: 14:35:24 time: 0.2596 data_time: 0.0076 memory: 5828 grad_norm: 3.1448 loss: 2.3332 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3332 2023/06/05 06:20:39 - mmengine - INFO - Epoch(train) [74][ 200/2569] lr: 4.0000e-02 eta: 14:35:19 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 3.1634 loss: 2.6182 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6182 2023/06/05 06:20:45 - mmengine - INFO - Epoch(train) [74][ 220/2569] lr: 4.0000e-02 eta: 14:35:13 time: 0.2607 data_time: 0.0073 memory: 5828 grad_norm: 3.1693 loss: 2.1161 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1161 2023/06/05 06:20:50 - mmengine - INFO - Epoch(train) [74][ 240/2569] lr: 4.0000e-02 eta: 14:35:08 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 3.1508 loss: 2.6125 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6125 2023/06/05 06:20:55 - mmengine - INFO - Epoch(train) [74][ 260/2569] lr: 4.0000e-02 eta: 14:35:03 time: 0.2615 data_time: 0.0074 memory: 5828 grad_norm: 3.1605 loss: 2.3919 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3919 2023/06/05 06:21:01 - mmengine - INFO - Epoch(train) [74][ 280/2569] lr: 4.0000e-02 eta: 14:34:57 time: 0.2761 data_time: 0.0073 memory: 5828 grad_norm: 3.1634 loss: 2.6101 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6101 2023/06/05 06:21:06 - mmengine - INFO - Epoch(train) [74][ 300/2569] lr: 4.0000e-02 eta: 14:34:52 time: 0.2690 data_time: 0.0069 memory: 5828 grad_norm: 3.0805 loss: 2.5973 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5973 2023/06/05 06:21:11 - mmengine - INFO - Epoch(train) [74][ 320/2569] lr: 4.0000e-02 eta: 14:34:47 time: 0.2676 data_time: 0.0075 memory: 5828 grad_norm: 3.0734 loss: 2.4139 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4139 2023/06/05 06:21:17 - mmengine - INFO - Epoch(train) [74][ 340/2569] lr: 4.0000e-02 eta: 14:34:42 time: 0.2637 data_time: 0.0074 memory: 5828 grad_norm: 3.0924 loss: 2.5917 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5917 2023/06/05 06:21:22 - mmengine - INFO - Epoch(train) [74][ 360/2569] lr: 4.0000e-02 eta: 14:34:36 time: 0.2647 data_time: 0.0077 memory: 5828 grad_norm: 3.1008 loss: 2.5496 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5496 2023/06/05 06:21:27 - mmengine - INFO - Epoch(train) [74][ 380/2569] lr: 4.0000e-02 eta: 14:34:31 time: 0.2636 data_time: 0.0076 memory: 5828 grad_norm: 3.1025 loss: 2.5131 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5131 2023/06/05 06:21:32 - mmengine - INFO - Epoch(train) [74][ 400/2569] lr: 4.0000e-02 eta: 14:34:25 time: 0.2595 data_time: 0.0074 memory: 5828 grad_norm: 3.1457 loss: 2.8521 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8521 2023/06/05 06:21:38 - mmengine - INFO - Epoch(train) [74][ 420/2569] lr: 4.0000e-02 eta: 14:34:20 time: 0.2750 data_time: 0.0075 memory: 5828 grad_norm: 3.1545 loss: 2.4749 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4749 2023/06/05 06:21:43 - mmengine - INFO - Epoch(train) [74][ 440/2569] lr: 4.0000e-02 eta: 14:34:15 time: 0.2699 data_time: 0.0079 memory: 5828 grad_norm: 3.1352 loss: 2.3118 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3118 2023/06/05 06:21:49 - mmengine - INFO - Epoch(train) [74][ 460/2569] lr: 4.0000e-02 eta: 14:34:10 time: 0.2700 data_time: 0.0073 memory: 5828 grad_norm: 3.1377 loss: 2.3057 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3057 2023/06/05 06:21:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:21:54 - mmengine - INFO - Epoch(train) [74][ 480/2569] lr: 4.0000e-02 eta: 14:34:04 time: 0.2614 data_time: 0.0075 memory: 5828 grad_norm: 3.1937 loss: 2.3789 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3789 2023/06/05 06:21:59 - mmengine - INFO - Epoch(train) [74][ 500/2569] lr: 4.0000e-02 eta: 14:33:59 time: 0.2671 data_time: 0.0083 memory: 5828 grad_norm: 3.1985 loss: 2.6310 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6310 2023/06/05 06:22:05 - mmengine - INFO - Epoch(train) [74][ 520/2569] lr: 4.0000e-02 eta: 14:33:54 time: 0.2643 data_time: 0.0075 memory: 5828 grad_norm: 3.1449 loss: 2.4849 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4849 2023/06/05 06:22:10 - mmengine - INFO - Epoch(train) [74][ 540/2569] lr: 4.0000e-02 eta: 14:33:49 time: 0.2667 data_time: 0.0075 memory: 5828 grad_norm: 3.1304 loss: 2.4738 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4738 2023/06/05 06:22:15 - mmengine - INFO - Epoch(train) [74][ 560/2569] lr: 4.0000e-02 eta: 14:33:43 time: 0.2675 data_time: 0.0075 memory: 5828 grad_norm: 3.4285 loss: 2.5385 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5385 2023/06/05 06:22:21 - mmengine - INFO - Epoch(train) [74][ 580/2569] lr: 4.0000e-02 eta: 14:33:38 time: 0.2609 data_time: 0.0072 memory: 5828 grad_norm: 3.2000 loss: 2.2118 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.2118 2023/06/05 06:22:26 - mmengine - INFO - Epoch(train) [74][ 600/2569] lr: 4.0000e-02 eta: 14:33:33 time: 0.2658 data_time: 0.0071 memory: 5828 grad_norm: 3.1562 loss: 2.1745 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1745 2023/06/05 06:22:31 - mmengine - INFO - Epoch(train) [74][ 620/2569] lr: 4.0000e-02 eta: 14:33:27 time: 0.2582 data_time: 0.0073 memory: 5828 grad_norm: 3.1148 loss: 2.6313 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6313 2023/06/05 06:22:36 - mmengine - INFO - Epoch(train) [74][ 640/2569] lr: 4.0000e-02 eta: 14:33:22 time: 0.2688 data_time: 0.0071 memory: 5828 grad_norm: 3.1064 loss: 3.0001 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0001 2023/06/05 06:22:42 - mmengine - INFO - Epoch(train) [74][ 660/2569] lr: 4.0000e-02 eta: 14:33:16 time: 0.2590 data_time: 0.0075 memory: 5828 grad_norm: 3.0802 loss: 2.5648 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5648 2023/06/05 06:22:47 - mmengine - INFO - Epoch(train) [74][ 680/2569] lr: 4.0000e-02 eta: 14:33:11 time: 0.2630 data_time: 0.0071 memory: 5828 grad_norm: 3.1606 loss: 2.3168 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3168 2023/06/05 06:22:52 - mmengine - INFO - Epoch(train) [74][ 700/2569] lr: 4.0000e-02 eta: 14:33:06 time: 0.2600 data_time: 0.0072 memory: 5828 grad_norm: 3.1026 loss: 2.4497 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4497 2023/06/05 06:22:57 - mmengine - INFO - Epoch(train) [74][ 720/2569] lr: 4.0000e-02 eta: 14:33:00 time: 0.2607 data_time: 0.0072 memory: 5828 grad_norm: 3.1102 loss: 2.2758 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2758 2023/06/05 06:23:03 - mmengine - INFO - Epoch(train) [74][ 740/2569] lr: 4.0000e-02 eta: 14:32:55 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 3.1652 loss: 2.6695 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6695 2023/06/05 06:23:08 - mmengine - INFO - Epoch(train) [74][ 760/2569] lr: 4.0000e-02 eta: 14:32:49 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 3.1395 loss: 2.5954 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5954 2023/06/05 06:23:13 - mmengine - INFO - Epoch(train) [74][ 780/2569] lr: 4.0000e-02 eta: 14:32:44 time: 0.2649 data_time: 0.0072 memory: 5828 grad_norm: 3.0718 loss: 2.7462 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7462 2023/06/05 06:23:18 - mmengine - INFO - Epoch(train) [74][ 800/2569] lr: 4.0000e-02 eta: 14:32:39 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 3.0902 loss: 2.4325 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4325 2023/06/05 06:23:24 - mmengine - INFO - Epoch(train) [74][ 820/2569] lr: 4.0000e-02 eta: 14:32:33 time: 0.2717 data_time: 0.0076 memory: 5828 grad_norm: 3.1854 loss: 2.6153 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6153 2023/06/05 06:23:29 - mmengine - INFO - Epoch(train) [74][ 840/2569] lr: 4.0000e-02 eta: 14:32:28 time: 0.2641 data_time: 0.0076 memory: 5828 grad_norm: 3.1639 loss: 2.4096 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4096 2023/06/05 06:23:34 - mmengine - INFO - Epoch(train) [74][ 860/2569] lr: 4.0000e-02 eta: 14:32:23 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.1230 loss: 2.6501 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6501 2023/06/05 06:23:40 - mmengine - INFO - Epoch(train) [74][ 880/2569] lr: 4.0000e-02 eta: 14:32:17 time: 0.2597 data_time: 0.0076 memory: 5828 grad_norm: 3.1101 loss: 2.5028 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5028 2023/06/05 06:23:45 - mmengine - INFO - Epoch(train) [74][ 900/2569] lr: 4.0000e-02 eta: 14:32:12 time: 0.2721 data_time: 0.0072 memory: 5828 grad_norm: 3.1495 loss: 2.4211 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4211 2023/06/05 06:23:50 - mmengine - INFO - Epoch(train) [74][ 920/2569] lr: 4.0000e-02 eta: 14:32:07 time: 0.2681 data_time: 0.0078 memory: 5828 grad_norm: 3.0754 loss: 2.3590 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3590 2023/06/05 06:23:56 - mmengine - INFO - Epoch(train) [74][ 940/2569] lr: 4.0000e-02 eta: 14:32:01 time: 0.2648 data_time: 0.0075 memory: 5828 grad_norm: 3.1486 loss: 2.3764 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3764 2023/06/05 06:24:01 - mmengine - INFO - Epoch(train) [74][ 960/2569] lr: 4.0000e-02 eta: 14:31:56 time: 0.2626 data_time: 0.0075 memory: 5828 grad_norm: 3.1729 loss: 2.4008 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4008 2023/06/05 06:24:06 - mmengine - INFO - Epoch(train) [74][ 980/2569] lr: 4.0000e-02 eta: 14:31:51 time: 0.2653 data_time: 0.0076 memory: 5828 grad_norm: 3.1484 loss: 2.1726 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1726 2023/06/05 06:24:12 - mmengine - INFO - Epoch(train) [74][1000/2569] lr: 4.0000e-02 eta: 14:31:46 time: 0.2695 data_time: 0.0076 memory: 5828 grad_norm: 3.0937 loss: 2.5212 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5212 2023/06/05 06:24:17 - mmengine - INFO - Epoch(train) [74][1020/2569] lr: 4.0000e-02 eta: 14:31:40 time: 0.2644 data_time: 0.0077 memory: 5828 grad_norm: 3.1075 loss: 2.6030 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6030 2023/06/05 06:24:22 - mmengine - INFO - Epoch(train) [74][1040/2569] lr: 4.0000e-02 eta: 14:31:35 time: 0.2702 data_time: 0.0075 memory: 5828 grad_norm: 3.0443 loss: 2.6667 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6667 2023/06/05 06:24:28 - mmengine - INFO - Epoch(train) [74][1060/2569] lr: 4.0000e-02 eta: 14:31:30 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 3.1576 loss: 2.7293 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7293 2023/06/05 06:24:33 - mmengine - INFO - Epoch(train) [74][1080/2569] lr: 4.0000e-02 eta: 14:31:25 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 3.1718 loss: 2.5202 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5202 2023/06/05 06:24:39 - mmengine - INFO - Epoch(train) [74][1100/2569] lr: 4.0000e-02 eta: 14:31:19 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 3.1092 loss: 2.1876 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1876 2023/06/05 06:24:44 - mmengine - INFO - Epoch(train) [74][1120/2569] lr: 4.0000e-02 eta: 14:31:14 time: 0.2584 data_time: 0.0073 memory: 5828 grad_norm: 3.0929 loss: 2.5927 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5927 2023/06/05 06:24:49 - mmengine - INFO - Epoch(train) [74][1140/2569] lr: 4.0000e-02 eta: 14:31:08 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 3.0752 loss: 2.6786 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6786 2023/06/05 06:24:54 - mmengine - INFO - Epoch(train) [74][1160/2569] lr: 4.0000e-02 eta: 14:31:03 time: 0.2588 data_time: 0.0078 memory: 5828 grad_norm: 3.2251 loss: 2.5759 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5759 2023/06/05 06:25:00 - mmengine - INFO - Epoch(train) [74][1180/2569] lr: 4.0000e-02 eta: 14:30:58 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 3.0774 loss: 2.3228 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3228 2023/06/05 06:25:05 - mmengine - INFO - Epoch(train) [74][1200/2569] lr: 4.0000e-02 eta: 14:30:52 time: 0.2607 data_time: 0.0074 memory: 5828 grad_norm: 3.1370 loss: 2.4313 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4313 2023/06/05 06:25:10 - mmengine - INFO - Epoch(train) [74][1220/2569] lr: 4.0000e-02 eta: 14:30:47 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.0877 loss: 2.8354 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8354 2023/06/05 06:25:15 - mmengine - INFO - Epoch(train) [74][1240/2569] lr: 4.0000e-02 eta: 14:30:41 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 3.1620 loss: 2.2840 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2840 2023/06/05 06:25:20 - mmengine - INFO - Epoch(train) [74][1260/2569] lr: 4.0000e-02 eta: 14:30:36 time: 0.2591 data_time: 0.0071 memory: 5828 grad_norm: 3.1328 loss: 2.5726 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5726 2023/06/05 06:25:26 - mmengine - INFO - Epoch(train) [74][1280/2569] lr: 4.0000e-02 eta: 14:30:31 time: 0.2628 data_time: 0.0073 memory: 5828 grad_norm: 3.1507 loss: 2.4631 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4631 2023/06/05 06:25:31 - mmengine - INFO - Epoch(train) [74][1300/2569] lr: 4.0000e-02 eta: 14:30:25 time: 0.2673 data_time: 0.0076 memory: 5828 grad_norm: 3.1660 loss: 2.4740 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4740 2023/06/05 06:25:36 - mmengine - INFO - Epoch(train) [74][1320/2569] lr: 4.0000e-02 eta: 14:30:20 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 3.1172 loss: 2.4238 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4238 2023/06/05 06:25:42 - mmengine - INFO - Epoch(train) [74][1340/2569] lr: 4.0000e-02 eta: 14:30:15 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 3.1210 loss: 2.6862 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6862 2023/06/05 06:25:47 - mmengine - INFO - Epoch(train) [74][1360/2569] lr: 4.0000e-02 eta: 14:30:09 time: 0.2647 data_time: 0.0071 memory: 5828 grad_norm: 3.1419 loss: 2.5622 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5622 2023/06/05 06:25:52 - mmengine - INFO - Epoch(train) [74][1380/2569] lr: 4.0000e-02 eta: 14:30:04 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 3.0970 loss: 2.6877 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6877 2023/06/05 06:25:57 - mmengine - INFO - Epoch(train) [74][1400/2569] lr: 4.0000e-02 eta: 14:29:58 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 3.0934 loss: 2.4000 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4000 2023/06/05 06:26:03 - mmengine - INFO - Epoch(train) [74][1420/2569] lr: 4.0000e-02 eta: 14:29:53 time: 0.2596 data_time: 0.0072 memory: 5828 grad_norm: 3.1563 loss: 2.8998 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8998 2023/06/05 06:26:08 - mmengine - INFO - Epoch(train) [74][1440/2569] lr: 4.0000e-02 eta: 14:29:48 time: 0.2587 data_time: 0.0071 memory: 5828 grad_norm: 3.1807 loss: 2.9557 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9557 2023/06/05 06:26:13 - mmengine - INFO - Epoch(train) [74][1460/2569] lr: 4.0000e-02 eta: 14:29:42 time: 0.2695 data_time: 0.0074 memory: 5828 grad_norm: 3.0754 loss: 2.5304 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5304 2023/06/05 06:26:14 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:26:18 - mmengine - INFO - Epoch(train) [74][1480/2569] lr: 4.0000e-02 eta: 14:29:37 time: 0.2627 data_time: 0.0079 memory: 5828 grad_norm: 3.0450 loss: 2.7263 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7263 2023/06/05 06:26:24 - mmengine - INFO - Epoch(train) [74][1500/2569] lr: 4.0000e-02 eta: 14:29:32 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 3.0828 loss: 2.2520 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2520 2023/06/05 06:26:29 - mmengine - INFO - Epoch(train) [74][1520/2569] lr: 4.0000e-02 eta: 14:29:26 time: 0.2593 data_time: 0.0074 memory: 5828 grad_norm: 3.0690 loss: 2.5095 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5095 2023/06/05 06:26:34 - mmengine - INFO - Epoch(train) [74][1540/2569] lr: 4.0000e-02 eta: 14:29:21 time: 0.2641 data_time: 0.0071 memory: 5828 grad_norm: 3.1495 loss: 2.9128 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9128 2023/06/05 06:26:40 - mmengine - INFO - Epoch(train) [74][1560/2569] lr: 4.0000e-02 eta: 14:29:16 time: 0.2685 data_time: 0.0074 memory: 5828 grad_norm: 3.1168 loss: 2.8609 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8609 2023/06/05 06:26:45 - mmengine - INFO - Epoch(train) [74][1580/2569] lr: 4.0000e-02 eta: 14:29:10 time: 0.2696 data_time: 0.0072 memory: 5828 grad_norm: 3.0636 loss: 2.3706 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3706 2023/06/05 06:26:50 - mmengine - INFO - Epoch(train) [74][1600/2569] lr: 4.0000e-02 eta: 14:29:05 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.0649 loss: 2.7128 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7128 2023/06/05 06:26:55 - mmengine - INFO - Epoch(train) [74][1620/2569] lr: 4.0000e-02 eta: 14:29:00 time: 0.2587 data_time: 0.0073 memory: 5828 grad_norm: 3.1679 loss: 2.3899 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3899 2023/06/05 06:27:01 - mmengine - INFO - Epoch(train) [74][1640/2569] lr: 4.0000e-02 eta: 14:28:54 time: 0.2694 data_time: 0.0071 memory: 5828 grad_norm: 3.0325 loss: 2.4949 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4949 2023/06/05 06:27:06 - mmengine - INFO - Epoch(train) [74][1660/2569] lr: 4.0000e-02 eta: 14:28:49 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 3.1312 loss: 2.4129 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4129 2023/06/05 06:27:11 - mmengine - INFO - Epoch(train) [74][1680/2569] lr: 4.0000e-02 eta: 14:28:43 time: 0.2575 data_time: 0.0072 memory: 5828 grad_norm: 3.1126 loss: 2.3149 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3149 2023/06/05 06:27:17 - mmengine - INFO - Epoch(train) [74][1700/2569] lr: 4.0000e-02 eta: 14:28:38 time: 0.2615 data_time: 0.0069 memory: 5828 grad_norm: 3.0974 loss: 2.3990 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3990 2023/06/05 06:27:22 - mmengine - INFO - Epoch(train) [74][1720/2569] lr: 4.0000e-02 eta: 14:28:33 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.0704 loss: 2.6245 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6245 2023/06/05 06:27:27 - mmengine - INFO - Epoch(train) [74][1740/2569] lr: 4.0000e-02 eta: 14:28:27 time: 0.2631 data_time: 0.0071 memory: 5828 grad_norm: 3.0979 loss: 2.2200 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2200 2023/06/05 06:27:32 - mmengine - INFO - Epoch(train) [74][1760/2569] lr: 4.0000e-02 eta: 14:28:22 time: 0.2574 data_time: 0.0075 memory: 5828 grad_norm: 3.0841 loss: 2.6653 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6653 2023/06/05 06:27:38 - mmengine - INFO - Epoch(train) [74][1780/2569] lr: 4.0000e-02 eta: 14:28:17 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 3.1337 loss: 3.0575 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.0575 2023/06/05 06:27:43 - mmengine - INFO - Epoch(train) [74][1800/2569] lr: 4.0000e-02 eta: 14:28:11 time: 0.2641 data_time: 0.0069 memory: 5828 grad_norm: 3.1083 loss: 2.3440 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3440 2023/06/05 06:27:48 - mmengine - INFO - Epoch(train) [74][1820/2569] lr: 4.0000e-02 eta: 14:28:06 time: 0.2598 data_time: 0.0071 memory: 5828 grad_norm: 3.0705 loss: 2.7186 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7186 2023/06/05 06:27:53 - mmengine - INFO - Epoch(train) [74][1840/2569] lr: 4.0000e-02 eta: 14:28:00 time: 0.2666 data_time: 0.0074 memory: 5828 grad_norm: 3.1306 loss: 2.6979 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6979 2023/06/05 06:27:59 - mmengine - INFO - Epoch(train) [74][1860/2569] lr: 4.0000e-02 eta: 14:27:55 time: 0.2755 data_time: 0.0071 memory: 5828 grad_norm: 3.1463 loss: 2.0923 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0923 2023/06/05 06:28:04 - mmengine - INFO - Epoch(train) [74][1880/2569] lr: 4.0000e-02 eta: 14:27:50 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 3.1769 loss: 2.4009 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4009 2023/06/05 06:28:10 - mmengine - INFO - Epoch(train) [74][1900/2569] lr: 4.0000e-02 eta: 14:27:45 time: 0.2809 data_time: 0.0072 memory: 5828 grad_norm: 3.1364 loss: 2.7190 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7190 2023/06/05 06:28:15 - mmengine - INFO - Epoch(train) [74][1920/2569] lr: 4.0000e-02 eta: 14:27:40 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.0433 loss: 2.6808 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6808 2023/06/05 06:28:20 - mmengine - INFO - Epoch(train) [74][1940/2569] lr: 4.0000e-02 eta: 14:27:34 time: 0.2611 data_time: 0.0071 memory: 5828 grad_norm: 3.0692 loss: 2.6234 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6234 2023/06/05 06:28:26 - mmengine - INFO - Epoch(train) [74][1960/2569] lr: 4.0000e-02 eta: 14:27:29 time: 0.2629 data_time: 0.0074 memory: 5828 grad_norm: 3.1183 loss: 2.1923 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1923 2023/06/05 06:28:31 - mmengine - INFO - Epoch(train) [74][1980/2569] lr: 4.0000e-02 eta: 14:27:23 time: 0.2593 data_time: 0.0077 memory: 5828 grad_norm: 3.1428 loss: 2.5376 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5376 2023/06/05 06:28:36 - mmengine - INFO - Epoch(train) [74][2000/2569] lr: 4.0000e-02 eta: 14:27:18 time: 0.2595 data_time: 0.0073 memory: 5828 grad_norm: 3.0728 loss: 2.4859 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4859 2023/06/05 06:28:41 - mmengine - INFO - Epoch(train) [74][2020/2569] lr: 4.0000e-02 eta: 14:27:13 time: 0.2719 data_time: 0.0076 memory: 5828 grad_norm: 3.1337 loss: 2.5570 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5570 2023/06/05 06:28:47 - mmengine - INFO - Epoch(train) [74][2040/2569] lr: 4.0000e-02 eta: 14:27:07 time: 0.2624 data_time: 0.0074 memory: 5828 grad_norm: 3.0840 loss: 2.4609 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4609 2023/06/05 06:28:52 - mmengine - INFO - Epoch(train) [74][2060/2569] lr: 4.0000e-02 eta: 14:27:02 time: 0.2724 data_time: 0.0071 memory: 5828 grad_norm: 3.0802 loss: 2.6484 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.6484 2023/06/05 06:28:57 - mmengine - INFO - Epoch(train) [74][2080/2569] lr: 4.0000e-02 eta: 14:26:57 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 3.1416 loss: 2.8094 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8094 2023/06/05 06:29:03 - mmengine - INFO - Epoch(train) [74][2100/2569] lr: 4.0000e-02 eta: 14:26:52 time: 0.2680 data_time: 0.0077 memory: 5828 grad_norm: 3.1448 loss: 2.6515 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6515 2023/06/05 06:29:08 - mmengine - INFO - Epoch(train) [74][2120/2569] lr: 4.0000e-02 eta: 14:26:46 time: 0.2681 data_time: 0.0073 memory: 5828 grad_norm: 3.0829 loss: 2.3131 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3131 2023/06/05 06:29:14 - mmengine - INFO - Epoch(train) [74][2140/2569] lr: 4.0000e-02 eta: 14:26:41 time: 0.2676 data_time: 0.0075 memory: 5828 grad_norm: 3.1359 loss: 2.2754 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2754 2023/06/05 06:29:19 - mmengine - INFO - Epoch(train) [74][2160/2569] lr: 4.0000e-02 eta: 14:26:36 time: 0.2703 data_time: 0.0075 memory: 5828 grad_norm: 3.1278 loss: 2.6657 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6657 2023/06/05 06:29:24 - mmengine - INFO - Epoch(train) [74][2180/2569] lr: 4.0000e-02 eta: 14:26:31 time: 0.2694 data_time: 0.0082 memory: 5828 grad_norm: 3.1166 loss: 2.1960 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1960 2023/06/05 06:29:30 - mmengine - INFO - Epoch(train) [74][2200/2569] lr: 4.0000e-02 eta: 14:26:25 time: 0.2581 data_time: 0.0082 memory: 5828 grad_norm: 3.1222 loss: 2.5971 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5971 2023/06/05 06:29:35 - mmengine - INFO - Epoch(train) [74][2220/2569] lr: 4.0000e-02 eta: 14:26:20 time: 0.2589 data_time: 0.0075 memory: 5828 grad_norm: 3.1507 loss: 2.3254 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3254 2023/06/05 06:29:40 - mmengine - INFO - Epoch(train) [74][2240/2569] lr: 4.0000e-02 eta: 14:26:14 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 3.1337 loss: 2.5138 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5138 2023/06/05 06:29:45 - mmengine - INFO - Epoch(train) [74][2260/2569] lr: 4.0000e-02 eta: 14:26:09 time: 0.2648 data_time: 0.0078 memory: 5828 grad_norm: 3.0993 loss: 2.5050 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5050 2023/06/05 06:29:50 - mmengine - INFO - Epoch(train) [74][2280/2569] lr: 4.0000e-02 eta: 14:26:03 time: 0.2588 data_time: 0.0077 memory: 5828 grad_norm: 3.1590 loss: 2.3923 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3923 2023/06/05 06:29:56 - mmengine - INFO - Epoch(train) [74][2300/2569] lr: 4.0000e-02 eta: 14:25:58 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 3.1284 loss: 2.7145 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7145 2023/06/05 06:30:01 - mmengine - INFO - Epoch(train) [74][2320/2569] lr: 4.0000e-02 eta: 14:25:53 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 3.1276 loss: 2.3341 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3341 2023/06/05 06:30:06 - mmengine - INFO - Epoch(train) [74][2340/2569] lr: 4.0000e-02 eta: 14:25:47 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 3.1171 loss: 2.1537 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1537 2023/06/05 06:30:12 - mmengine - INFO - Epoch(train) [74][2360/2569] lr: 4.0000e-02 eta: 14:25:42 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.1233 loss: 2.3479 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3479 2023/06/05 06:30:17 - mmengine - INFO - Epoch(train) [74][2380/2569] lr: 4.0000e-02 eta: 14:25:37 time: 0.2611 data_time: 0.0073 memory: 5828 grad_norm: 3.1213 loss: 2.7066 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7066 2023/06/05 06:30:22 - mmengine - INFO - Epoch(train) [74][2400/2569] lr: 4.0000e-02 eta: 14:25:31 time: 0.2582 data_time: 0.0075 memory: 5828 grad_norm: 3.1175 loss: 2.7097 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7097 2023/06/05 06:30:27 - mmengine - INFO - Epoch(train) [74][2420/2569] lr: 4.0000e-02 eta: 14:25:26 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 3.0962 loss: 2.2270 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2270 2023/06/05 06:30:33 - mmengine - INFO - Epoch(train) [74][2440/2569] lr: 4.0000e-02 eta: 14:25:21 time: 0.2722 data_time: 0.0071 memory: 5828 grad_norm: 3.1592 loss: 2.3518 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3518 2023/06/05 06:30:38 - mmengine - INFO - Epoch(train) [74][2460/2569] lr: 4.0000e-02 eta: 14:25:15 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 3.1213 loss: 2.4109 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4109 2023/06/05 06:30:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:30:43 - mmengine - INFO - Epoch(train) [74][2480/2569] lr: 4.0000e-02 eta: 14:25:10 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 3.1539 loss: 2.5754 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5754 2023/06/05 06:30:49 - mmengine - INFO - Epoch(train) [74][2500/2569] lr: 4.0000e-02 eta: 14:25:05 time: 0.2811 data_time: 0.0072 memory: 5828 grad_norm: 3.1380 loss: 2.7810 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7810 2023/06/05 06:30:54 - mmengine - INFO - Epoch(train) [74][2520/2569] lr: 4.0000e-02 eta: 14:24:59 time: 0.2640 data_time: 0.0078 memory: 5828 grad_norm: 3.1053 loss: 2.9715 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9715 2023/06/05 06:30:59 - mmengine - INFO - Epoch(train) [74][2540/2569] lr: 4.0000e-02 eta: 14:24:54 time: 0.2660 data_time: 0.0072 memory: 5828 grad_norm: 3.1517 loss: 2.8598 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8598 2023/06/05 06:31:05 - mmengine - INFO - Epoch(train) [74][2560/2569] lr: 4.0000e-02 eta: 14:24:49 time: 0.2566 data_time: 0.0076 memory: 5828 grad_norm: 3.0922 loss: 2.7907 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7907 2023/06/05 06:31:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:31:07 - mmengine - INFO - Epoch(train) [74][2569/2569] lr: 4.0000e-02 eta: 14:24:46 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 3.1195 loss: 3.0290 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 3.0290 2023/06/05 06:31:14 - mmengine - INFO - Epoch(train) [75][ 20/2569] lr: 4.0000e-02 eta: 14:24:43 time: 0.3427 data_time: 0.0489 memory: 5828 grad_norm: 3.1039 loss: 2.4072 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4072 2023/06/05 06:31:19 - mmengine - INFO - Epoch(train) [75][ 40/2569] lr: 4.0000e-02 eta: 14:24:37 time: 0.2673 data_time: 0.0077 memory: 5828 grad_norm: 3.0994 loss: 2.6856 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6856 2023/06/05 06:31:24 - mmengine - INFO - Epoch(train) [75][ 60/2569] lr: 4.0000e-02 eta: 14:24:32 time: 0.2585 data_time: 0.0077 memory: 5828 grad_norm: 3.0289 loss: 2.6098 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6098 2023/06/05 06:31:30 - mmengine - INFO - Epoch(train) [75][ 80/2569] lr: 4.0000e-02 eta: 14:24:27 time: 0.2731 data_time: 0.0081 memory: 5828 grad_norm: 3.1128 loss: 2.4650 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4650 2023/06/05 06:31:35 - mmengine - INFO - Epoch(train) [75][ 100/2569] lr: 4.0000e-02 eta: 14:24:21 time: 0.2582 data_time: 0.0075 memory: 5828 grad_norm: 3.0954 loss: 2.9389 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9389 2023/06/05 06:31:40 - mmengine - INFO - Epoch(train) [75][ 120/2569] lr: 4.0000e-02 eta: 14:24:16 time: 0.2617 data_time: 0.0080 memory: 5828 grad_norm: 3.1476 loss: 2.3451 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3451 2023/06/05 06:31:46 - mmengine - INFO - Epoch(train) [75][ 140/2569] lr: 4.0000e-02 eta: 14:24:10 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.1027 loss: 2.4851 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4851 2023/06/05 06:31:51 - mmengine - INFO - Epoch(train) [75][ 160/2569] lr: 4.0000e-02 eta: 14:24:05 time: 0.2635 data_time: 0.0075 memory: 5828 grad_norm: 3.0677 loss: 2.6293 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6293 2023/06/05 06:31:56 - mmengine - INFO - Epoch(train) [75][ 180/2569] lr: 4.0000e-02 eta: 14:24:00 time: 0.2650 data_time: 0.0078 memory: 5828 grad_norm: 3.1067 loss: 2.4083 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4083 2023/06/05 06:32:01 - mmengine - INFO - Epoch(train) [75][ 200/2569] lr: 4.0000e-02 eta: 14:23:54 time: 0.2665 data_time: 0.0076 memory: 5828 grad_norm: 3.0705 loss: 2.6494 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6494 2023/06/05 06:32:07 - mmengine - INFO - Epoch(train) [75][ 220/2569] lr: 4.0000e-02 eta: 14:23:49 time: 0.2694 data_time: 0.0075 memory: 5828 grad_norm: 3.1267 loss: 2.6267 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6267 2023/06/05 06:32:12 - mmengine - INFO - Epoch(train) [75][ 240/2569] lr: 4.0000e-02 eta: 14:23:44 time: 0.2601 data_time: 0.0072 memory: 5828 grad_norm: 3.1296 loss: 2.6568 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6568 2023/06/05 06:32:18 - mmengine - INFO - Epoch(train) [75][ 260/2569] lr: 4.0000e-02 eta: 14:23:39 time: 0.2740 data_time: 0.0076 memory: 5828 grad_norm: 3.1236 loss: 2.4414 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4414 2023/06/05 06:32:23 - mmengine - INFO - Epoch(train) [75][ 280/2569] lr: 4.0000e-02 eta: 14:23:33 time: 0.2592 data_time: 0.0076 memory: 5828 grad_norm: 3.1349 loss: 2.3731 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.3731 2023/06/05 06:32:28 - mmengine - INFO - Epoch(train) [75][ 300/2569] lr: 4.0000e-02 eta: 14:23:28 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 3.1070 loss: 2.6155 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6155 2023/06/05 06:32:33 - mmengine - INFO - Epoch(train) [75][ 320/2569] lr: 4.0000e-02 eta: 14:23:22 time: 0.2593 data_time: 0.0075 memory: 5828 grad_norm: 3.1417 loss: 2.3251 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3251 2023/06/05 06:32:39 - mmengine - INFO - Epoch(train) [75][ 340/2569] lr: 4.0000e-02 eta: 14:23:17 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 3.1206 loss: 2.5302 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5302 2023/06/05 06:32:44 - mmengine - INFO - Epoch(train) [75][ 360/2569] lr: 4.0000e-02 eta: 14:23:12 time: 0.2587 data_time: 0.0079 memory: 5828 grad_norm: 3.1554 loss: 2.6168 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6168 2023/06/05 06:32:49 - mmengine - INFO - Epoch(train) [75][ 380/2569] lr: 4.0000e-02 eta: 14:23:06 time: 0.2678 data_time: 0.0071 memory: 5828 grad_norm: 3.0913 loss: 2.4436 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4436 2023/06/05 06:32:55 - mmengine - INFO - Epoch(train) [75][ 400/2569] lr: 4.0000e-02 eta: 14:23:01 time: 0.2738 data_time: 0.0073 memory: 5828 grad_norm: 3.1407 loss: 2.3887 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3887 2023/06/05 06:33:00 - mmengine - INFO - Epoch(train) [75][ 420/2569] lr: 4.0000e-02 eta: 14:22:56 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 3.1818 loss: 2.5858 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5858 2023/06/05 06:33:05 - mmengine - INFO - Epoch(train) [75][ 440/2569] lr: 4.0000e-02 eta: 14:22:50 time: 0.2640 data_time: 0.0076 memory: 5828 grad_norm: 3.1315 loss: 2.5754 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5754 2023/06/05 06:33:11 - mmengine - INFO - Epoch(train) [75][ 460/2569] lr: 4.0000e-02 eta: 14:22:45 time: 0.2711 data_time: 0.0072 memory: 5828 grad_norm: 3.0843 loss: 2.1395 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1395 2023/06/05 06:33:16 - mmengine - INFO - Epoch(train) [75][ 480/2569] lr: 4.0000e-02 eta: 14:22:40 time: 0.2581 data_time: 0.0075 memory: 5828 grad_norm: 3.2236 loss: 2.7631 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7631 2023/06/05 06:33:21 - mmengine - INFO - Epoch(train) [75][ 500/2569] lr: 4.0000e-02 eta: 14:22:34 time: 0.2652 data_time: 0.0071 memory: 5828 grad_norm: 3.0818 loss: 2.6183 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6183 2023/06/05 06:33:26 - mmengine - INFO - Epoch(train) [75][ 520/2569] lr: 4.0000e-02 eta: 14:22:29 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 3.0778 loss: 2.2941 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2941 2023/06/05 06:33:32 - mmengine - INFO - Epoch(train) [75][ 540/2569] lr: 4.0000e-02 eta: 14:22:24 time: 0.2629 data_time: 0.0076 memory: 5828 grad_norm: 3.1246 loss: 2.5916 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5916 2023/06/05 06:33:37 - mmengine - INFO - Epoch(train) [75][ 560/2569] lr: 4.0000e-02 eta: 14:22:18 time: 0.2681 data_time: 0.0081 memory: 5828 grad_norm: 3.1290 loss: 2.6421 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6421 2023/06/05 06:33:42 - mmengine - INFO - Epoch(train) [75][ 580/2569] lr: 4.0000e-02 eta: 14:22:13 time: 0.2631 data_time: 0.0070 memory: 5828 grad_norm: 3.1430 loss: 2.5571 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5571 2023/06/05 06:33:48 - mmengine - INFO - Epoch(train) [75][ 600/2569] lr: 4.0000e-02 eta: 14:22:08 time: 0.2700 data_time: 0.0073 memory: 5828 grad_norm: 3.2008 loss: 2.6724 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6724 2023/06/05 06:33:53 - mmengine - INFO - Epoch(train) [75][ 620/2569] lr: 4.0000e-02 eta: 14:22:02 time: 0.2621 data_time: 0.0076 memory: 5828 grad_norm: 3.1599 loss: 2.6733 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6733 2023/06/05 06:33:58 - mmengine - INFO - Epoch(train) [75][ 640/2569] lr: 4.0000e-02 eta: 14:21:57 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 3.1375 loss: 2.4236 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4236 2023/06/05 06:34:04 - mmengine - INFO - Epoch(train) [75][ 660/2569] lr: 4.0000e-02 eta: 14:21:52 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 3.1353 loss: 2.2301 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2301 2023/06/05 06:34:09 - mmengine - INFO - Epoch(train) [75][ 680/2569] lr: 4.0000e-02 eta: 14:21:46 time: 0.2572 data_time: 0.0076 memory: 5828 grad_norm: 3.1470 loss: 2.4851 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4851 2023/06/05 06:34:14 - mmengine - INFO - Epoch(train) [75][ 700/2569] lr: 4.0000e-02 eta: 14:21:41 time: 0.2633 data_time: 0.0076 memory: 5828 grad_norm: 3.1195 loss: 2.7347 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7347 2023/06/05 06:34:19 - mmengine - INFO - Epoch(train) [75][ 720/2569] lr: 4.0000e-02 eta: 14:21:36 time: 0.2596 data_time: 0.0075 memory: 5828 grad_norm: 3.1455 loss: 2.7049 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7049 2023/06/05 06:34:24 - mmengine - INFO - Epoch(train) [75][ 740/2569] lr: 4.0000e-02 eta: 14:21:30 time: 0.2630 data_time: 0.0072 memory: 5828 grad_norm: 3.1121 loss: 2.3754 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3754 2023/06/05 06:34:30 - mmengine - INFO - Epoch(train) [75][ 760/2569] lr: 4.0000e-02 eta: 14:21:25 time: 0.2644 data_time: 0.0075 memory: 5828 grad_norm: 3.1547 loss: 2.4740 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4740 2023/06/05 06:34:35 - mmengine - INFO - Epoch(train) [75][ 780/2569] lr: 4.0000e-02 eta: 14:21:19 time: 0.2663 data_time: 0.0071 memory: 5828 grad_norm: 3.1113 loss: 2.0171 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0171 2023/06/05 06:34:40 - mmengine - INFO - Epoch(train) [75][ 800/2569] lr: 4.0000e-02 eta: 14:21:14 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 3.1155 loss: 2.5411 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5411 2023/06/05 06:34:46 - mmengine - INFO - Epoch(train) [75][ 820/2569] lr: 4.0000e-02 eta: 14:21:09 time: 0.2736 data_time: 0.0074 memory: 5828 grad_norm: 3.1154 loss: 2.2541 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2541 2023/06/05 06:34:51 - mmengine - INFO - Epoch(train) [75][ 840/2569] lr: 4.0000e-02 eta: 14:21:03 time: 0.2571 data_time: 0.0073 memory: 5828 grad_norm: 3.1174 loss: 2.4001 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4001 2023/06/05 06:34:56 - mmengine - INFO - Epoch(train) [75][ 860/2569] lr: 4.0000e-02 eta: 14:20:58 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.1473 loss: 2.6249 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6249 2023/06/05 06:35:01 - mmengine - INFO - Epoch(train) [75][ 880/2569] lr: 4.0000e-02 eta: 14:20:53 time: 0.2602 data_time: 0.0078 memory: 5828 grad_norm: 3.1090 loss: 2.5613 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5613 2023/06/05 06:35:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:35:07 - mmengine - INFO - Epoch(train) [75][ 900/2569] lr: 4.0000e-02 eta: 14:20:47 time: 0.2654 data_time: 0.0070 memory: 5828 grad_norm: 3.1403 loss: 2.2633 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2633 2023/06/05 06:35:12 - mmengine - INFO - Epoch(train) [75][ 920/2569] lr: 4.0000e-02 eta: 14:20:42 time: 0.2664 data_time: 0.0071 memory: 5828 grad_norm: 3.1377 loss: 2.4395 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4395 2023/06/05 06:35:17 - mmengine - INFO - Epoch(train) [75][ 940/2569] lr: 4.0000e-02 eta: 14:20:37 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 3.1215 loss: 2.7254 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7254 2023/06/05 06:35:23 - mmengine - INFO - Epoch(train) [75][ 960/2569] lr: 4.0000e-02 eta: 14:20:31 time: 0.2654 data_time: 0.0074 memory: 5828 grad_norm: 3.0810 loss: 2.7908 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7908 2023/06/05 06:35:28 - mmengine - INFO - Epoch(train) [75][ 980/2569] lr: 4.0000e-02 eta: 14:20:26 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 3.1758 loss: 2.9050 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9050 2023/06/05 06:35:33 - mmengine - INFO - Epoch(train) [75][1000/2569] lr: 4.0000e-02 eta: 14:20:21 time: 0.2605 data_time: 0.0073 memory: 5828 grad_norm: 3.1391 loss: 2.5114 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5114 2023/06/05 06:35:38 - mmengine - INFO - Epoch(train) [75][1020/2569] lr: 4.0000e-02 eta: 14:20:15 time: 0.2605 data_time: 0.0073 memory: 5828 grad_norm: 3.0964 loss: 2.5209 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5209 2023/06/05 06:35:44 - mmengine - INFO - Epoch(train) [75][1040/2569] lr: 4.0000e-02 eta: 14:20:10 time: 0.2593 data_time: 0.0073 memory: 5828 grad_norm: 3.0942 loss: 2.3715 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3715 2023/06/05 06:35:49 - mmengine - INFO - Epoch(train) [75][1060/2569] lr: 4.0000e-02 eta: 14:20:04 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 3.1542 loss: 2.3310 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3310 2023/06/05 06:35:54 - mmengine - INFO - Epoch(train) [75][1080/2569] lr: 4.0000e-02 eta: 14:19:59 time: 0.2772 data_time: 0.0074 memory: 5828 grad_norm: 3.1337 loss: 2.9668 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9668 2023/06/05 06:36:00 - mmengine - INFO - Epoch(train) [75][1100/2569] lr: 4.0000e-02 eta: 14:19:54 time: 0.2658 data_time: 0.0085 memory: 5828 grad_norm: 3.1597 loss: 2.4745 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4745 2023/06/05 06:36:05 - mmengine - INFO - Epoch(train) [75][1120/2569] lr: 4.0000e-02 eta: 14:19:48 time: 0.2584 data_time: 0.0078 memory: 5828 grad_norm: 3.1279 loss: 2.7158 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7158 2023/06/05 06:36:10 - mmengine - INFO - Epoch(train) [75][1140/2569] lr: 4.0000e-02 eta: 14:19:43 time: 0.2697 data_time: 0.0078 memory: 5828 grad_norm: 3.1438 loss: 2.4859 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4859 2023/06/05 06:36:15 - mmengine - INFO - Epoch(train) [75][1160/2569] lr: 4.0000e-02 eta: 14:19:38 time: 0.2589 data_time: 0.0081 memory: 5828 grad_norm: 3.1159 loss: 2.3672 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3672 2023/06/05 06:36:21 - mmengine - INFO - Epoch(train) [75][1180/2569] lr: 4.0000e-02 eta: 14:19:32 time: 0.2637 data_time: 0.0077 memory: 5828 grad_norm: 3.1768 loss: 2.7670 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7670 2023/06/05 06:36:26 - mmengine - INFO - Epoch(train) [75][1200/2569] lr: 4.0000e-02 eta: 14:19:27 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 3.1388 loss: 2.8314 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8314 2023/06/05 06:36:31 - mmengine - INFO - Epoch(train) [75][1220/2569] lr: 4.0000e-02 eta: 14:19:22 time: 0.2708 data_time: 0.0072 memory: 5828 grad_norm: 3.1500 loss: 2.6441 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6441 2023/06/05 06:36:37 - mmengine - INFO - Epoch(train) [75][1240/2569] lr: 4.0000e-02 eta: 14:19:16 time: 0.2588 data_time: 0.0073 memory: 5828 grad_norm: 3.1387 loss: 2.5738 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5738 2023/06/05 06:36:42 - mmengine - INFO - Epoch(train) [75][1260/2569] lr: 4.0000e-02 eta: 14:19:11 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 3.1055 loss: 2.4195 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4195 2023/06/05 06:36:47 - mmengine - INFO - Epoch(train) [75][1280/2569] lr: 4.0000e-02 eta: 14:19:06 time: 0.2608 data_time: 0.0074 memory: 5828 grad_norm: 3.2054 loss: 2.6936 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6936 2023/06/05 06:36:53 - mmengine - INFO - Epoch(train) [75][1300/2569] lr: 4.0000e-02 eta: 14:19:00 time: 0.2693 data_time: 0.0074 memory: 5828 grad_norm: 3.1254 loss: 2.1285 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1285 2023/06/05 06:36:58 - mmengine - INFO - Epoch(train) [75][1320/2569] lr: 4.0000e-02 eta: 14:18:55 time: 0.2607 data_time: 0.0076 memory: 5828 grad_norm: 3.1547 loss: 2.9956 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9956 2023/06/05 06:37:03 - mmengine - INFO - Epoch(train) [75][1340/2569] lr: 4.0000e-02 eta: 14:18:50 time: 0.2589 data_time: 0.0075 memory: 5828 grad_norm: 3.1020 loss: 2.1806 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1806 2023/06/05 06:37:09 - mmengine - INFO - Epoch(train) [75][1360/2569] lr: 4.0000e-02 eta: 14:18:44 time: 0.2792 data_time: 0.0075 memory: 5828 grad_norm: 3.1219 loss: 2.5258 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5258 2023/06/05 06:37:14 - mmengine - INFO - Epoch(train) [75][1380/2569] lr: 4.0000e-02 eta: 14:18:39 time: 0.2635 data_time: 0.0081 memory: 5828 grad_norm: 3.1464 loss: 2.7474 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7474 2023/06/05 06:37:19 - mmengine - INFO - Epoch(train) [75][1400/2569] lr: 4.0000e-02 eta: 14:18:34 time: 0.2657 data_time: 0.0075 memory: 5828 grad_norm: 3.0702 loss: 2.8233 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8233 2023/06/05 06:37:25 - mmengine - INFO - Epoch(train) [75][1420/2569] lr: 4.0000e-02 eta: 14:18:29 time: 0.2698 data_time: 0.0075 memory: 5828 grad_norm: 3.1060 loss: 2.6348 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6348 2023/06/05 06:37:30 - mmengine - INFO - Epoch(train) [75][1440/2569] lr: 4.0000e-02 eta: 14:18:23 time: 0.2607 data_time: 0.0077 memory: 5828 grad_norm: 3.2098 loss: 2.7176 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7176 2023/06/05 06:37:35 - mmengine - INFO - Epoch(train) [75][1460/2569] lr: 4.0000e-02 eta: 14:18:18 time: 0.2682 data_time: 0.0074 memory: 5828 grad_norm: 3.0767 loss: 2.4772 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4772 2023/06/05 06:37:40 - mmengine - INFO - Epoch(train) [75][1480/2569] lr: 4.0000e-02 eta: 14:18:12 time: 0.2581 data_time: 0.0072 memory: 5828 grad_norm: 3.1211 loss: 2.6531 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6531 2023/06/05 06:37:45 - mmengine - INFO - Epoch(train) [75][1500/2569] lr: 4.0000e-02 eta: 14:18:07 time: 0.2577 data_time: 0.0074 memory: 5828 grad_norm: 3.1733 loss: 2.7985 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7985 2023/06/05 06:37:51 - mmengine - INFO - Epoch(train) [75][1520/2569] lr: 4.0000e-02 eta: 14:18:01 time: 0.2582 data_time: 0.0073 memory: 5828 grad_norm: 3.1174 loss: 2.5627 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5627 2023/06/05 06:37:56 - mmengine - INFO - Epoch(train) [75][1540/2569] lr: 4.0000e-02 eta: 14:17:56 time: 0.2726 data_time: 0.0075 memory: 5828 grad_norm: 3.1684 loss: 2.5186 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5186 2023/06/05 06:38:02 - mmengine - INFO - Epoch(train) [75][1560/2569] lr: 4.0000e-02 eta: 14:17:51 time: 0.2742 data_time: 0.0079 memory: 5828 grad_norm: 3.0779 loss: 2.9080 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9080 2023/06/05 06:38:07 - mmengine - INFO - Epoch(train) [75][1580/2569] lr: 4.0000e-02 eta: 14:17:46 time: 0.2587 data_time: 0.0074 memory: 5828 grad_norm: 3.0916 loss: 2.5861 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5861 2023/06/05 06:38:12 - mmengine - INFO - Epoch(train) [75][1600/2569] lr: 4.0000e-02 eta: 14:17:40 time: 0.2634 data_time: 0.0077 memory: 5828 grad_norm: 3.0634 loss: 2.7599 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7599 2023/06/05 06:38:18 - mmengine - INFO - Epoch(train) [75][1620/2569] lr: 4.0000e-02 eta: 14:17:35 time: 0.2748 data_time: 0.0075 memory: 5828 grad_norm: 3.1458 loss: 2.7852 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7852 2023/06/05 06:38:23 - mmengine - INFO - Epoch(train) [75][1640/2569] lr: 4.0000e-02 eta: 14:17:30 time: 0.2715 data_time: 0.0079 memory: 5828 grad_norm: 3.1709 loss: 2.3883 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.3883 2023/06/05 06:38:28 - mmengine - INFO - Epoch(train) [75][1660/2569] lr: 4.0000e-02 eta: 14:17:25 time: 0.2691 data_time: 0.0078 memory: 5828 grad_norm: 3.1455 loss: 2.6166 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6166 2023/06/05 06:38:34 - mmengine - INFO - Epoch(train) [75][1680/2569] lr: 4.0000e-02 eta: 14:17:19 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 3.0658 loss: 2.5359 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5359 2023/06/05 06:38:39 - mmengine - INFO - Epoch(train) [75][1700/2569] lr: 4.0000e-02 eta: 14:17:14 time: 0.2690 data_time: 0.0077 memory: 5828 grad_norm: 3.0771 loss: 2.6541 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.6541 2023/06/05 06:38:44 - mmengine - INFO - Epoch(train) [75][1720/2569] lr: 4.0000e-02 eta: 14:17:09 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 3.1190 loss: 2.6356 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6356 2023/06/05 06:38:50 - mmengine - INFO - Epoch(train) [75][1740/2569] lr: 4.0000e-02 eta: 14:17:04 time: 0.2673 data_time: 0.0077 memory: 5828 grad_norm: 3.1189 loss: 2.5029 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5029 2023/06/05 06:38:55 - mmengine - INFO - Epoch(train) [75][1760/2569] lr: 4.0000e-02 eta: 14:16:58 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 3.0876 loss: 2.6010 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6010 2023/06/05 06:39:00 - mmengine - INFO - Epoch(train) [75][1780/2569] lr: 4.0000e-02 eta: 14:16:53 time: 0.2575 data_time: 0.0077 memory: 5828 grad_norm: 3.1648 loss: 2.3450 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3450 2023/06/05 06:39:06 - mmengine - INFO - Epoch(train) [75][1800/2569] lr: 4.0000e-02 eta: 14:16:48 time: 0.2822 data_time: 0.0075 memory: 5828 grad_norm: 3.1332 loss: 2.5123 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5123 2023/06/05 06:39:11 - mmengine - INFO - Epoch(train) [75][1820/2569] lr: 4.0000e-02 eta: 14:16:42 time: 0.2566 data_time: 0.0080 memory: 5828 grad_norm: 3.1181 loss: 2.4906 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4906 2023/06/05 06:39:17 - mmengine - INFO - Epoch(train) [75][1840/2569] lr: 4.0000e-02 eta: 14:16:37 time: 0.2782 data_time: 0.0075 memory: 5828 grad_norm: 3.2005 loss: 2.1733 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1733 2023/06/05 06:39:22 - mmengine - INFO - Epoch(train) [75][1860/2569] lr: 4.0000e-02 eta: 14:16:32 time: 0.2622 data_time: 0.0081 memory: 5828 grad_norm: 3.0484 loss: 2.6219 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6219 2023/06/05 06:39:27 - mmengine - INFO - Epoch(train) [75][1880/2569] lr: 4.0000e-02 eta: 14:16:27 time: 0.2676 data_time: 0.0073 memory: 5828 grad_norm: 3.1299 loss: 2.5473 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5473 2023/06/05 06:39:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:39:32 - mmengine - INFO - Epoch(train) [75][1900/2569] lr: 4.0000e-02 eta: 14:16:21 time: 0.2600 data_time: 0.0075 memory: 5828 grad_norm: 3.1472 loss: 2.5451 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5451 2023/06/05 06:39:38 - mmengine - INFO - Epoch(train) [75][1920/2569] lr: 4.0000e-02 eta: 14:16:16 time: 0.2724 data_time: 0.0075 memory: 5828 grad_norm: 3.1295 loss: 2.7353 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7353 2023/06/05 06:39:43 - mmengine - INFO - Epoch(train) [75][1940/2569] lr: 4.0000e-02 eta: 14:16:11 time: 0.2616 data_time: 0.0077 memory: 5828 grad_norm: 3.0767 loss: 2.5374 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5374 2023/06/05 06:39:48 - mmengine - INFO - Epoch(train) [75][1960/2569] lr: 4.0000e-02 eta: 14:16:05 time: 0.2661 data_time: 0.0077 memory: 5828 grad_norm: 3.0742 loss: 2.4518 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4518 2023/06/05 06:39:54 - mmengine - INFO - Epoch(train) [75][1980/2569] lr: 4.0000e-02 eta: 14:16:00 time: 0.2574 data_time: 0.0076 memory: 5828 grad_norm: 3.2166 loss: 2.3126 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3126 2023/06/05 06:39:59 - mmengine - INFO - Epoch(train) [75][2000/2569] lr: 4.0000e-02 eta: 14:15:54 time: 0.2569 data_time: 0.0075 memory: 5828 grad_norm: 3.1869 loss: 2.4643 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4643 2023/06/05 06:40:04 - mmengine - INFO - Epoch(train) [75][2020/2569] lr: 4.0000e-02 eta: 14:15:49 time: 0.2868 data_time: 0.0075 memory: 5828 grad_norm: 3.1120 loss: 2.6433 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6433 2023/06/05 06:40:10 - mmengine - INFO - Epoch(train) [75][2040/2569] lr: 4.0000e-02 eta: 14:15:44 time: 0.2594 data_time: 0.0079 memory: 5828 grad_norm: 3.1893 loss: 2.8332 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8332 2023/06/05 06:40:15 - mmengine - INFO - Epoch(train) [75][2060/2569] lr: 4.0000e-02 eta: 14:15:39 time: 0.2757 data_time: 0.0074 memory: 5828 grad_norm: 3.1536 loss: 2.3909 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3909 2023/06/05 06:40:21 - mmengine - INFO - Epoch(train) [75][2080/2569] lr: 4.0000e-02 eta: 14:15:34 time: 0.2714 data_time: 0.0075 memory: 5828 grad_norm: 3.1318 loss: 2.3407 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3407 2023/06/05 06:40:26 - mmengine - INFO - Epoch(train) [75][2100/2569] lr: 4.0000e-02 eta: 14:15:28 time: 0.2675 data_time: 0.0078 memory: 5828 grad_norm: 3.0904 loss: 2.2648 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2648 2023/06/05 06:40:31 - mmengine - INFO - Epoch(train) [75][2120/2569] lr: 4.0000e-02 eta: 14:15:23 time: 0.2759 data_time: 0.0077 memory: 5828 grad_norm: 3.0940 loss: 2.2963 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2963 2023/06/05 06:40:37 - mmengine - INFO - Epoch(train) [75][2140/2569] lr: 4.0000e-02 eta: 14:15:18 time: 0.2640 data_time: 0.0075 memory: 5828 grad_norm: 3.1022 loss: 2.6810 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6810 2023/06/05 06:40:42 - mmengine - INFO - Epoch(train) [75][2160/2569] lr: 4.0000e-02 eta: 14:15:13 time: 0.2708 data_time: 0.0073 memory: 5828 grad_norm: 3.0945 loss: 2.2772 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2772 2023/06/05 06:40:47 - mmengine - INFO - Epoch(train) [75][2180/2569] lr: 4.0000e-02 eta: 14:15:07 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 3.0741 loss: 2.5975 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5975 2023/06/05 06:40:53 - mmengine - INFO - Epoch(train) [75][2200/2569] lr: 4.0000e-02 eta: 14:15:02 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 3.1716 loss: 2.4650 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4650 2023/06/05 06:40:58 - mmengine - INFO - Epoch(train) [75][2220/2569] lr: 4.0000e-02 eta: 14:14:57 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 3.1187 loss: 2.9840 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9840 2023/06/05 06:41:03 - mmengine - INFO - Epoch(train) [75][2240/2569] lr: 4.0000e-02 eta: 14:14:51 time: 0.2690 data_time: 0.0073 memory: 5828 grad_norm: 3.1152 loss: 2.5459 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5459 2023/06/05 06:41:09 - mmengine - INFO - Epoch(train) [75][2260/2569] lr: 4.0000e-02 eta: 14:14:46 time: 0.2689 data_time: 0.0072 memory: 5828 grad_norm: 3.1634 loss: 2.2075 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2075 2023/06/05 06:41:14 - mmengine - INFO - Epoch(train) [75][2280/2569] lr: 4.0000e-02 eta: 14:14:41 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.0453 loss: 2.4654 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4654 2023/06/05 06:41:20 - mmengine - INFO - Epoch(train) [75][2300/2569] lr: 4.0000e-02 eta: 14:14:36 time: 0.2814 data_time: 0.0076 memory: 5828 grad_norm: 3.1685 loss: 2.3964 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3964 2023/06/05 06:41:25 - mmengine - INFO - Epoch(train) [75][2320/2569] lr: 4.0000e-02 eta: 14:14:30 time: 0.2575 data_time: 0.0079 memory: 5828 grad_norm: 3.1158 loss: 2.8662 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8662 2023/06/05 06:41:30 - mmengine - INFO - Epoch(train) [75][2340/2569] lr: 4.0000e-02 eta: 14:14:25 time: 0.2780 data_time: 0.0073 memory: 5828 grad_norm: 3.1578 loss: 2.5157 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5157 2023/06/05 06:41:36 - mmengine - INFO - Epoch(train) [75][2360/2569] lr: 4.0000e-02 eta: 14:14:20 time: 0.2729 data_time: 0.0078 memory: 5828 grad_norm: 3.1133 loss: 2.4214 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4214 2023/06/05 06:41:41 - mmengine - INFO - Epoch(train) [75][2380/2569] lr: 4.0000e-02 eta: 14:14:15 time: 0.2628 data_time: 0.0077 memory: 5828 grad_norm: 3.1778 loss: 2.6079 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6079 2023/06/05 06:41:46 - mmengine - INFO - Epoch(train) [75][2400/2569] lr: 4.0000e-02 eta: 14:14:09 time: 0.2641 data_time: 0.0076 memory: 5828 grad_norm: 3.0452 loss: 2.4850 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4850 2023/06/05 06:41:52 - mmengine - INFO - Epoch(train) [75][2420/2569] lr: 4.0000e-02 eta: 14:14:04 time: 0.2586 data_time: 0.0076 memory: 5828 grad_norm: 3.1422 loss: 2.3400 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3400 2023/06/05 06:41:57 - mmengine - INFO - Epoch(train) [75][2440/2569] lr: 4.0000e-02 eta: 14:13:59 time: 0.2685 data_time: 0.0071 memory: 5828 grad_norm: 3.0952 loss: 2.2501 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2501 2023/06/05 06:42:02 - mmengine - INFO - Epoch(train) [75][2460/2569] lr: 4.0000e-02 eta: 14:13:53 time: 0.2589 data_time: 0.0072 memory: 5828 grad_norm: 3.1742 loss: 2.7577 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7577 2023/06/05 06:42:07 - mmengine - INFO - Epoch(train) [75][2480/2569] lr: 4.0000e-02 eta: 14:13:48 time: 0.2615 data_time: 0.0078 memory: 5828 grad_norm: 3.1446 loss: 2.2775 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2775 2023/06/05 06:42:13 - mmengine - INFO - Epoch(train) [75][2500/2569] lr: 4.0000e-02 eta: 14:13:42 time: 0.2575 data_time: 0.0076 memory: 5828 grad_norm: 3.1530 loss: 2.3924 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3924 2023/06/05 06:42:18 - mmengine - INFO - Epoch(train) [75][2520/2569] lr: 4.0000e-02 eta: 14:13:37 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 3.1473 loss: 2.5101 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5101 2023/06/05 06:42:23 - mmengine - INFO - Epoch(train) [75][2540/2569] lr: 4.0000e-02 eta: 14:13:32 time: 0.2702 data_time: 0.0075 memory: 5828 grad_norm: 3.1287 loss: 2.2921 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2921 2023/06/05 06:42:29 - mmengine - INFO - Epoch(train) [75][2560/2569] lr: 4.0000e-02 eta: 14:13:26 time: 0.2615 data_time: 0.0076 memory: 5828 grad_norm: 3.1280 loss: 2.5624 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5624 2023/06/05 06:42:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:42:31 - mmengine - INFO - Epoch(train) [75][2569/2569] lr: 4.0000e-02 eta: 14:13:24 time: 0.2608 data_time: 0.0072 memory: 5828 grad_norm: 3.1149 loss: 2.3933 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3933 2023/06/05 06:42:34 - mmengine - INFO - Epoch(val) [75][ 20/260] eta: 0:00:42 time: 0.1769 data_time: 0.1181 memory: 1238 2023/06/05 06:42:37 - mmengine - INFO - Epoch(val) [75][ 40/260] eta: 0:00:33 time: 0.1239 data_time: 0.0650 memory: 1238 2023/06/05 06:42:40 - mmengine - INFO - Epoch(val) [75][ 60/260] eta: 0:00:30 time: 0.1620 data_time: 0.1033 memory: 1238 2023/06/05 06:42:43 - mmengine - INFO - Epoch(val) [75][ 80/260] eta: 0:00:26 time: 0.1345 data_time: 0.0758 memory: 1238 2023/06/05 06:42:46 - mmengine - INFO - Epoch(val) [75][100/260] eta: 0:00:24 time: 0.1545 data_time: 0.0956 memory: 1238 2023/06/05 06:42:48 - mmengine - INFO - Epoch(val) [75][120/260] eta: 0:00:20 time: 0.1173 data_time: 0.0588 memory: 1238 2023/06/05 06:42:51 - mmengine - INFO - Epoch(val) [75][140/260] eta: 0:00:17 time: 0.1412 data_time: 0.0827 memory: 1238 2023/06/05 06:42:54 - mmengine - INFO - Epoch(val) [75][160/260] eta: 0:00:14 time: 0.1464 data_time: 0.0880 memory: 1238 2023/06/05 06:42:57 - mmengine - INFO - Epoch(val) [75][180/260] eta: 0:00:11 time: 0.1403 data_time: 0.0820 memory: 1238 2023/06/05 06:43:00 - mmengine - INFO - Epoch(val) [75][200/260] eta: 0:00:08 time: 0.1483 data_time: 0.0897 memory: 1238 2023/06/05 06:43:03 - mmengine - INFO - Epoch(val) [75][220/260] eta: 0:00:05 time: 0.1455 data_time: 0.0870 memory: 1238 2023/06/05 06:43:05 - mmengine - INFO - Epoch(val) [75][240/260] eta: 0:00:02 time: 0.1310 data_time: 0.0727 memory: 1238 2023/06/05 06:43:08 - mmengine - INFO - Epoch(val) [75][260/260] eta: 0:00:00 time: 0.1343 data_time: 0.0774 memory: 1238 2023/06/05 06:43:15 - mmengine - INFO - Epoch(val) [75][260/260] acc/top1: 0.4840 acc/top5: 0.7248 acc/mean1: 0.4749 data_time: 0.0840 time: 0.1424 2023/06/05 06:43:22 - mmengine - INFO - Epoch(train) [76][ 20/2569] lr: 4.0000e-02 eta: 14:13:20 time: 0.3277 data_time: 0.0514 memory: 5828 grad_norm: 3.1413 loss: 2.2853 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2853 2023/06/05 06:43:27 - mmengine - INFO - Epoch(train) [76][ 40/2569] lr: 4.0000e-02 eta: 14:13:14 time: 0.2581 data_time: 0.0075 memory: 5828 grad_norm: 3.0847 loss: 2.0615 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0615 2023/06/05 06:43:32 - mmengine - INFO - Epoch(train) [76][ 60/2569] lr: 4.0000e-02 eta: 14:13:09 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 3.1211 loss: 2.4079 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4079 2023/06/05 06:43:38 - mmengine - INFO - Epoch(train) [76][ 80/2569] lr: 4.0000e-02 eta: 14:13:04 time: 0.2658 data_time: 0.0076 memory: 5828 grad_norm: 3.1660 loss: 2.2840 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2840 2023/06/05 06:43:43 - mmengine - INFO - Epoch(train) [76][ 100/2569] lr: 4.0000e-02 eta: 14:12:58 time: 0.2698 data_time: 0.0072 memory: 5828 grad_norm: 3.1166 loss: 2.5144 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5144 2023/06/05 06:43:48 - mmengine - INFO - Epoch(train) [76][ 120/2569] lr: 4.0000e-02 eta: 14:12:53 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 3.1719 loss: 2.4626 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4626 2023/06/05 06:43:54 - mmengine - INFO - Epoch(train) [76][ 140/2569] lr: 4.0000e-02 eta: 14:12:48 time: 0.2637 data_time: 0.0072 memory: 5828 grad_norm: 3.1130 loss: 2.3227 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3227 2023/06/05 06:43:59 - mmengine - INFO - Epoch(train) [76][ 160/2569] lr: 4.0000e-02 eta: 14:12:42 time: 0.2691 data_time: 0.0076 memory: 5828 grad_norm: 3.1424 loss: 2.9313 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.9313 2023/06/05 06:44:04 - mmengine - INFO - Epoch(train) [76][ 180/2569] lr: 4.0000e-02 eta: 14:12:37 time: 0.2674 data_time: 0.0076 memory: 5828 grad_norm: 3.1348 loss: 2.5137 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5137 2023/06/05 06:44:10 - mmengine - INFO - Epoch(train) [76][ 200/2569] lr: 4.0000e-02 eta: 14:12:32 time: 0.2703 data_time: 0.0074 memory: 5828 grad_norm: 3.1087 loss: 2.4632 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4632 2023/06/05 06:44:15 - mmengine - INFO - Epoch(train) [76][ 220/2569] lr: 4.0000e-02 eta: 14:12:27 time: 0.2633 data_time: 0.0068 memory: 5828 grad_norm: 3.1047 loss: 2.8607 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8607 2023/06/05 06:44:21 - mmengine - INFO - Epoch(train) [76][ 240/2569] lr: 4.0000e-02 eta: 14:12:21 time: 0.2749 data_time: 0.0075 memory: 5828 grad_norm: 3.0735 loss: 2.6000 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6000 2023/06/05 06:44:26 - mmengine - INFO - Epoch(train) [76][ 260/2569] lr: 4.0000e-02 eta: 14:12:16 time: 0.2594 data_time: 0.0069 memory: 5828 grad_norm: 3.1691 loss: 2.3314 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3314 2023/06/05 06:44:31 - mmengine - INFO - Epoch(train) [76][ 280/2569] lr: 4.0000e-02 eta: 14:12:11 time: 0.2595 data_time: 0.0077 memory: 5828 grad_norm: 3.1341 loss: 2.4142 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4142 2023/06/05 06:44:36 - mmengine - INFO - Epoch(train) [76][ 300/2569] lr: 4.0000e-02 eta: 14:12:05 time: 0.2574 data_time: 0.0076 memory: 5828 grad_norm: 3.1576 loss: 2.4930 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4930 2023/06/05 06:44:41 - mmengine - INFO - Epoch(train) [76][ 320/2569] lr: 4.0000e-02 eta: 14:12:00 time: 0.2583 data_time: 0.0080 memory: 5828 grad_norm: 3.1018 loss: 2.1684 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1684 2023/06/05 06:44:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:44:47 - mmengine - INFO - Epoch(train) [76][ 340/2569] lr: 4.0000e-02 eta: 14:11:54 time: 0.2611 data_time: 0.0073 memory: 5828 grad_norm: 3.1147 loss: 2.5375 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5375 2023/06/05 06:44:52 - mmengine - INFO - Epoch(train) [76][ 360/2569] lr: 4.0000e-02 eta: 14:11:49 time: 0.2689 data_time: 0.0072 memory: 5828 grad_norm: 3.0719 loss: 2.8796 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8796 2023/06/05 06:44:57 - mmengine - INFO - Epoch(train) [76][ 380/2569] lr: 4.0000e-02 eta: 14:11:44 time: 0.2602 data_time: 0.0076 memory: 5828 grad_norm: 3.1792 loss: 2.2603 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2603 2023/06/05 06:45:02 - mmengine - INFO - Epoch(train) [76][ 400/2569] lr: 4.0000e-02 eta: 14:11:38 time: 0.2584 data_time: 0.0073 memory: 5828 grad_norm: 3.1247 loss: 2.7803 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7803 2023/06/05 06:45:08 - mmengine - INFO - Epoch(train) [76][ 420/2569] lr: 4.0000e-02 eta: 14:11:33 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 3.1310 loss: 2.4198 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4198 2023/06/05 06:45:13 - mmengine - INFO - Epoch(train) [76][ 440/2569] lr: 4.0000e-02 eta: 14:11:27 time: 0.2650 data_time: 0.0073 memory: 5828 grad_norm: 3.1472 loss: 2.3657 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3657 2023/06/05 06:45:18 - mmengine - INFO - Epoch(train) [76][ 460/2569] lr: 4.0000e-02 eta: 14:11:22 time: 0.2621 data_time: 0.0072 memory: 5828 grad_norm: 3.0885 loss: 2.6423 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6423 2023/06/05 06:45:24 - mmengine - INFO - Epoch(train) [76][ 480/2569] lr: 4.0000e-02 eta: 14:11:17 time: 0.2672 data_time: 0.0072 memory: 5828 grad_norm: 3.1145 loss: 2.5543 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5543 2023/06/05 06:45:29 - mmengine - INFO - Epoch(train) [76][ 500/2569] lr: 4.0000e-02 eta: 14:11:12 time: 0.2692 data_time: 0.0072 memory: 5828 grad_norm: 3.1289 loss: 2.5496 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5496 2023/06/05 06:45:34 - mmengine - INFO - Epoch(train) [76][ 520/2569] lr: 4.0000e-02 eta: 14:11:06 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 3.1322 loss: 2.6769 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6769 2023/06/05 06:45:39 - mmengine - INFO - Epoch(train) [76][ 540/2569] lr: 4.0000e-02 eta: 14:11:01 time: 0.2626 data_time: 0.0073 memory: 5828 grad_norm: 3.1104 loss: 2.4272 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4272 2023/06/05 06:45:45 - mmengine - INFO - Epoch(train) [76][ 560/2569] lr: 4.0000e-02 eta: 14:10:55 time: 0.2632 data_time: 0.0076 memory: 5828 grad_norm: 3.0925 loss: 2.5444 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5444 2023/06/05 06:45:50 - mmengine - INFO - Epoch(train) [76][ 580/2569] lr: 4.0000e-02 eta: 14:10:50 time: 0.2610 data_time: 0.0072 memory: 5828 grad_norm: 3.1219 loss: 2.5964 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5964 2023/06/05 06:45:55 - mmengine - INFO - Epoch(train) [76][ 600/2569] lr: 4.0000e-02 eta: 14:10:45 time: 0.2713 data_time: 0.0075 memory: 5828 grad_norm: 3.1696 loss: 2.2289 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2289 2023/06/05 06:46:01 - mmengine - INFO - Epoch(train) [76][ 620/2569] lr: 4.0000e-02 eta: 14:10:39 time: 0.2589 data_time: 0.0071 memory: 5828 grad_norm: 3.1815 loss: 2.4023 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4023 2023/06/05 06:46:06 - mmengine - INFO - Epoch(train) [76][ 640/2569] lr: 4.0000e-02 eta: 14:10:34 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 3.1552 loss: 2.2604 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2604 2023/06/05 06:46:11 - mmengine - INFO - Epoch(train) [76][ 660/2569] lr: 4.0000e-02 eta: 14:10:29 time: 0.2587 data_time: 0.0070 memory: 5828 grad_norm: 3.1593 loss: 2.3583 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3583 2023/06/05 06:46:16 - mmengine - INFO - Epoch(train) [76][ 680/2569] lr: 4.0000e-02 eta: 14:10:23 time: 0.2610 data_time: 0.0071 memory: 5828 grad_norm: 3.1488 loss: 2.0368 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0368 2023/06/05 06:46:22 - mmengine - INFO - Epoch(train) [76][ 700/2569] lr: 4.0000e-02 eta: 14:10:18 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 3.1833 loss: 2.9063 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.9063 2023/06/05 06:46:27 - mmengine - INFO - Epoch(train) [76][ 720/2569] lr: 4.0000e-02 eta: 14:10:12 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 3.1040 loss: 2.6986 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6986 2023/06/05 06:46:32 - mmengine - INFO - Epoch(train) [76][ 740/2569] lr: 4.0000e-02 eta: 14:10:07 time: 0.2611 data_time: 0.0073 memory: 5828 grad_norm: 3.1592 loss: 2.2789 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2789 2023/06/05 06:46:37 - mmengine - INFO - Epoch(train) [76][ 760/2569] lr: 4.0000e-02 eta: 14:10:02 time: 0.2594 data_time: 0.0072 memory: 5828 grad_norm: 3.1553 loss: 2.3847 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3847 2023/06/05 06:46:43 - mmengine - INFO - Epoch(train) [76][ 780/2569] lr: 4.0000e-02 eta: 14:09:56 time: 0.2683 data_time: 0.0074 memory: 5828 grad_norm: 3.1554 loss: 3.0682 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 3.0682 2023/06/05 06:46:48 - mmengine - INFO - Epoch(train) [76][ 800/2569] lr: 4.0000e-02 eta: 14:09:51 time: 0.2605 data_time: 0.0071 memory: 5828 grad_norm: 3.1572 loss: 2.4976 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4976 2023/06/05 06:46:53 - mmengine - INFO - Epoch(train) [76][ 820/2569] lr: 4.0000e-02 eta: 14:09:46 time: 0.2655 data_time: 0.0073 memory: 5828 grad_norm: 3.1006 loss: 2.6014 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6014 2023/06/05 06:46:58 - mmengine - INFO - Epoch(train) [76][ 840/2569] lr: 4.0000e-02 eta: 14:09:40 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.1258 loss: 2.4407 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4407 2023/06/05 06:47:04 - mmengine - INFO - Epoch(train) [76][ 860/2569] lr: 4.0000e-02 eta: 14:09:35 time: 0.2659 data_time: 0.0073 memory: 5828 grad_norm: 3.1495 loss: 2.6104 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6104 2023/06/05 06:47:09 - mmengine - INFO - Epoch(train) [76][ 880/2569] lr: 4.0000e-02 eta: 14:09:29 time: 0.2616 data_time: 0.0075 memory: 5828 grad_norm: 3.0605 loss: 2.5732 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5732 2023/06/05 06:47:14 - mmengine - INFO - Epoch(train) [76][ 900/2569] lr: 4.0000e-02 eta: 14:09:24 time: 0.2680 data_time: 0.0076 memory: 5828 grad_norm: 3.1209 loss: 2.6305 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.6305 2023/06/05 06:47:20 - mmengine - INFO - Epoch(train) [76][ 920/2569] lr: 4.0000e-02 eta: 14:09:19 time: 0.2625 data_time: 0.0076 memory: 5828 grad_norm: 3.1636 loss: 2.7111 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7111 2023/06/05 06:47:25 - mmengine - INFO - Epoch(train) [76][ 940/2569] lr: 4.0000e-02 eta: 14:09:13 time: 0.2622 data_time: 0.0070 memory: 5828 grad_norm: 3.1050 loss: 2.3369 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3369 2023/06/05 06:47:30 - mmengine - INFO - Epoch(train) [76][ 960/2569] lr: 4.0000e-02 eta: 14:09:08 time: 0.2649 data_time: 0.0072 memory: 5828 grad_norm: 3.1978 loss: 2.5330 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5330 2023/06/05 06:47:35 - mmengine - INFO - Epoch(train) [76][ 980/2569] lr: 4.0000e-02 eta: 14:09:03 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 3.1299 loss: 2.6176 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6176 2023/06/05 06:47:41 - mmengine - INFO - Epoch(train) [76][1000/2569] lr: 4.0000e-02 eta: 14:08:57 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 3.1721 loss: 2.7990 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7990 2023/06/05 06:47:46 - mmengine - INFO - Epoch(train) [76][1020/2569] lr: 4.0000e-02 eta: 14:08:52 time: 0.2582 data_time: 0.0082 memory: 5828 grad_norm: 3.1519 loss: 2.7175 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7175 2023/06/05 06:47:51 - mmengine - INFO - Epoch(train) [76][1040/2569] lr: 4.0000e-02 eta: 14:08:47 time: 0.2634 data_time: 0.0073 memory: 5828 grad_norm: 3.1147 loss: 2.4146 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4146 2023/06/05 06:47:56 - mmengine - INFO - Epoch(train) [76][1060/2569] lr: 4.0000e-02 eta: 14:08:41 time: 0.2665 data_time: 0.0074 memory: 5828 grad_norm: 3.0958 loss: 2.3572 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3572 2023/06/05 06:48:02 - mmengine - INFO - Epoch(train) [76][1080/2569] lr: 4.0000e-02 eta: 14:08:36 time: 0.2590 data_time: 0.0072 memory: 5828 grad_norm: 3.1769 loss: 2.5285 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5285 2023/06/05 06:48:07 - mmengine - INFO - Epoch(train) [76][1100/2569] lr: 4.0000e-02 eta: 14:08:30 time: 0.2635 data_time: 0.0071 memory: 5828 grad_norm: 3.1090 loss: 2.5634 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5634 2023/06/05 06:48:12 - mmengine - INFO - Epoch(train) [76][1120/2569] lr: 4.0000e-02 eta: 14:08:25 time: 0.2640 data_time: 0.0069 memory: 5828 grad_norm: 3.1405 loss: 2.1187 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1187 2023/06/05 06:48:18 - mmengine - INFO - Epoch(train) [76][1140/2569] lr: 4.0000e-02 eta: 14:08:20 time: 0.2706 data_time: 0.0073 memory: 5828 grad_norm: 3.1494 loss: 2.3993 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3993 2023/06/05 06:48:23 - mmengine - INFO - Epoch(train) [76][1160/2569] lr: 4.0000e-02 eta: 14:08:14 time: 0.2635 data_time: 0.0074 memory: 5828 grad_norm: 3.1642 loss: 2.7618 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7618 2023/06/05 06:48:28 - mmengine - INFO - Epoch(train) [76][1180/2569] lr: 4.0000e-02 eta: 14:08:09 time: 0.2602 data_time: 0.0076 memory: 5828 grad_norm: 3.1304 loss: 2.4215 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4215 2023/06/05 06:48:33 - mmengine - INFO - Epoch(train) [76][1200/2569] lr: 4.0000e-02 eta: 14:08:04 time: 0.2646 data_time: 0.0077 memory: 5828 grad_norm: 3.1603 loss: 2.6439 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6439 2023/06/05 06:48:39 - mmengine - INFO - Epoch(train) [76][1220/2569] lr: 4.0000e-02 eta: 14:07:59 time: 0.2738 data_time: 0.0072 memory: 5828 grad_norm: 3.0319 loss: 2.4714 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4714 2023/06/05 06:48:44 - mmengine - INFO - Epoch(train) [76][1240/2569] lr: 4.0000e-02 eta: 14:07:53 time: 0.2712 data_time: 0.0075 memory: 5828 grad_norm: 3.2189 loss: 2.7138 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7138 2023/06/05 06:48:50 - mmengine - INFO - Epoch(train) [76][1260/2569] lr: 4.0000e-02 eta: 14:07:48 time: 0.2676 data_time: 0.0077 memory: 5828 grad_norm: 3.1206 loss: 2.6931 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6931 2023/06/05 06:48:55 - mmengine - INFO - Epoch(train) [76][1280/2569] lr: 4.0000e-02 eta: 14:07:43 time: 0.2663 data_time: 0.0070 memory: 5828 grad_norm: 3.1038 loss: 2.5433 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5433 2023/06/05 06:49:00 - mmengine - INFO - Epoch(train) [76][1300/2569] lr: 4.0000e-02 eta: 14:07:37 time: 0.2582 data_time: 0.0074 memory: 5828 grad_norm: 3.2451 loss: 2.5888 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5888 2023/06/05 06:49:06 - mmengine - INFO - Epoch(train) [76][1320/2569] lr: 4.0000e-02 eta: 14:07:32 time: 0.2682 data_time: 0.0077 memory: 5828 grad_norm: 3.1321 loss: 2.5369 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5369 2023/06/05 06:49:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:49:11 - mmengine - INFO - Epoch(train) [76][1340/2569] lr: 4.0000e-02 eta: 14:07:27 time: 0.2706 data_time: 0.0074 memory: 5828 grad_norm: 3.0546 loss: 2.7237 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7237 2023/06/05 06:49:16 - mmengine - INFO - Epoch(train) [76][1360/2569] lr: 4.0000e-02 eta: 14:07:22 time: 0.2647 data_time: 0.0079 memory: 5828 grad_norm: 3.1602 loss: 2.4056 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4056 2023/06/05 06:49:22 - mmengine - INFO - Epoch(train) [76][1380/2569] lr: 4.0000e-02 eta: 14:07:16 time: 0.2679 data_time: 0.0076 memory: 5828 grad_norm: 3.1561 loss: 2.5768 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5768 2023/06/05 06:49:27 - mmengine - INFO - Epoch(train) [76][1400/2569] lr: 4.0000e-02 eta: 14:07:11 time: 0.2657 data_time: 0.0073 memory: 5828 grad_norm: 3.1093 loss: 2.9439 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9439 2023/06/05 06:49:32 - mmengine - INFO - Epoch(train) [76][1420/2569] lr: 4.0000e-02 eta: 14:07:06 time: 0.2627 data_time: 0.0070 memory: 5828 grad_norm: 3.1337 loss: 2.3786 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3786 2023/06/05 06:49:37 - mmengine - INFO - Epoch(train) [76][1440/2569] lr: 4.0000e-02 eta: 14:07:00 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 3.1554 loss: 2.5104 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5104 2023/06/05 06:49:43 - mmengine - INFO - Epoch(train) [76][1460/2569] lr: 4.0000e-02 eta: 14:06:55 time: 0.2607 data_time: 0.0076 memory: 5828 grad_norm: 3.1044 loss: 2.5438 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5438 2023/06/05 06:49:48 - mmengine - INFO - Epoch(train) [76][1480/2569] lr: 4.0000e-02 eta: 14:06:50 time: 0.2730 data_time: 0.0081 memory: 5828 grad_norm: 3.1153 loss: 2.6194 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6194 2023/06/05 06:49:53 - mmengine - INFO - Epoch(train) [76][1500/2569] lr: 4.0000e-02 eta: 14:06:44 time: 0.2633 data_time: 0.0078 memory: 5828 grad_norm: 3.1320 loss: 2.7060 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7060 2023/06/05 06:49:59 - mmengine - INFO - Epoch(train) [76][1520/2569] lr: 4.0000e-02 eta: 14:06:39 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 3.0399 loss: 2.3275 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3275 2023/06/05 06:50:04 - mmengine - INFO - Epoch(train) [76][1540/2569] lr: 4.0000e-02 eta: 14:06:33 time: 0.2613 data_time: 0.0076 memory: 5828 grad_norm: 3.1003 loss: 2.2427 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2427 2023/06/05 06:50:09 - mmengine - INFO - Epoch(train) [76][1560/2569] lr: 4.0000e-02 eta: 14:06:28 time: 0.2643 data_time: 0.0071 memory: 5828 grad_norm: 3.1533 loss: 2.4059 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4059 2023/06/05 06:50:15 - mmengine - INFO - Epoch(train) [76][1580/2569] lr: 4.0000e-02 eta: 14:06:23 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 3.1267 loss: 2.6781 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6781 2023/06/05 06:50:20 - mmengine - INFO - Epoch(train) [76][1600/2569] lr: 4.0000e-02 eta: 14:06:17 time: 0.2572 data_time: 0.0074 memory: 5828 grad_norm: 3.1641 loss: 3.0001 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0001 2023/06/05 06:50:25 - mmengine - INFO - Epoch(train) [76][1620/2569] lr: 4.0000e-02 eta: 14:06:12 time: 0.2630 data_time: 0.0074 memory: 5828 grad_norm: 3.1708 loss: 2.5105 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5105 2023/06/05 06:50:30 - mmengine - INFO - Epoch(train) [76][1640/2569] lr: 4.0000e-02 eta: 14:06:07 time: 0.2619 data_time: 0.0075 memory: 5828 grad_norm: 3.1379 loss: 2.5707 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5707 2023/06/05 06:50:36 - mmengine - INFO - Epoch(train) [76][1660/2569] lr: 4.0000e-02 eta: 14:06:01 time: 0.2622 data_time: 0.0076 memory: 5828 grad_norm: 3.1071 loss: 2.8609 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8609 2023/06/05 06:50:41 - mmengine - INFO - Epoch(train) [76][1680/2569] lr: 4.0000e-02 eta: 14:05:56 time: 0.2630 data_time: 0.0075 memory: 5828 grad_norm: 3.0762 loss: 2.2362 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2362 2023/06/05 06:50:46 - mmengine - INFO - Epoch(train) [76][1700/2569] lr: 4.0000e-02 eta: 14:05:51 time: 0.2672 data_time: 0.0080 memory: 5828 grad_norm: 3.1666 loss: 2.6781 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6781 2023/06/05 06:50:52 - mmengine - INFO - Epoch(train) [76][1720/2569] lr: 4.0000e-02 eta: 14:05:45 time: 0.2729 data_time: 0.0080 memory: 5828 grad_norm: 3.1099 loss: 2.5579 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5579 2023/06/05 06:50:57 - mmengine - INFO - Epoch(train) [76][1740/2569] lr: 4.0000e-02 eta: 14:05:40 time: 0.2617 data_time: 0.0075 memory: 5828 grad_norm: 3.1490 loss: 2.5596 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5596 2023/06/05 06:51:02 - mmengine - INFO - Epoch(train) [76][1760/2569] lr: 4.0000e-02 eta: 14:05:35 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.1270 loss: 2.7182 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7182 2023/06/05 06:51:07 - mmengine - INFO - Epoch(train) [76][1780/2569] lr: 4.0000e-02 eta: 14:05:29 time: 0.2632 data_time: 0.0076 memory: 5828 grad_norm: 3.1578 loss: 2.5237 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5237 2023/06/05 06:51:13 - mmengine - INFO - Epoch(train) [76][1800/2569] lr: 4.0000e-02 eta: 14:05:24 time: 0.2582 data_time: 0.0075 memory: 5828 grad_norm: 3.1273 loss: 2.7224 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7224 2023/06/05 06:51:18 - mmengine - INFO - Epoch(train) [76][1820/2569] lr: 4.0000e-02 eta: 14:05:18 time: 0.2622 data_time: 0.0074 memory: 5828 grad_norm: 3.1119 loss: 2.3020 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3020 2023/06/05 06:51:23 - mmengine - INFO - Epoch(train) [76][1840/2569] lr: 4.0000e-02 eta: 14:05:13 time: 0.2599 data_time: 0.0072 memory: 5828 grad_norm: 3.1243 loss: 2.5856 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5856 2023/06/05 06:51:28 - mmengine - INFO - Epoch(train) [76][1860/2569] lr: 4.0000e-02 eta: 14:05:08 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.1293 loss: 2.8856 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8856 2023/06/05 06:51:33 - mmengine - INFO - Epoch(train) [76][1880/2569] lr: 4.0000e-02 eta: 14:05:02 time: 0.2580 data_time: 0.0076 memory: 5828 grad_norm: 3.0918 loss: 2.5297 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5297 2023/06/05 06:51:39 - mmengine - INFO - Epoch(train) [76][1900/2569] lr: 4.0000e-02 eta: 14:04:57 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 3.1284 loss: 2.3342 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.3342 2023/06/05 06:51:44 - mmengine - INFO - Epoch(train) [76][1920/2569] lr: 4.0000e-02 eta: 14:04:51 time: 0.2594 data_time: 0.0074 memory: 5828 grad_norm: 3.1449 loss: 2.6840 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6840 2023/06/05 06:51:49 - mmengine - INFO - Epoch(train) [76][1940/2569] lr: 4.0000e-02 eta: 14:04:46 time: 0.2739 data_time: 0.0073 memory: 5828 grad_norm: 3.1324 loss: 2.8118 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8118 2023/06/05 06:51:55 - mmengine - INFO - Epoch(train) [76][1960/2569] lr: 4.0000e-02 eta: 14:04:41 time: 0.2624 data_time: 0.0077 memory: 5828 grad_norm: 3.1024 loss: 2.4109 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4109 2023/06/05 06:52:00 - mmengine - INFO - Epoch(train) [76][1980/2569] lr: 4.0000e-02 eta: 14:04:35 time: 0.2618 data_time: 0.0076 memory: 5828 grad_norm: 3.1311 loss: 2.4725 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4725 2023/06/05 06:52:05 - mmengine - INFO - Epoch(train) [76][2000/2569] lr: 4.0000e-02 eta: 14:04:30 time: 0.2613 data_time: 0.0077 memory: 5828 grad_norm: 3.1861 loss: 2.5681 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5681 2023/06/05 06:52:10 - mmengine - INFO - Epoch(train) [76][2020/2569] lr: 4.0000e-02 eta: 14:04:25 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 3.1208 loss: 2.5190 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5190 2023/06/05 06:52:16 - mmengine - INFO - Epoch(train) [76][2040/2569] lr: 4.0000e-02 eta: 14:04:19 time: 0.2618 data_time: 0.0078 memory: 5828 grad_norm: 3.0658 loss: 2.1440 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1440 2023/06/05 06:52:21 - mmengine - INFO - Epoch(train) [76][2060/2569] lr: 4.0000e-02 eta: 14:04:14 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 3.1086 loss: 2.5771 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5771 2023/06/05 06:52:26 - mmengine - INFO - Epoch(train) [76][2080/2569] lr: 4.0000e-02 eta: 14:04:09 time: 0.2631 data_time: 0.0075 memory: 5828 grad_norm: 3.0907 loss: 2.6588 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6588 2023/06/05 06:52:32 - mmengine - INFO - Epoch(train) [76][2100/2569] lr: 4.0000e-02 eta: 14:04:03 time: 0.2716 data_time: 0.0075 memory: 5828 grad_norm: 3.1285 loss: 2.4520 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4520 2023/06/05 06:52:37 - mmengine - INFO - Epoch(train) [76][2120/2569] lr: 4.0000e-02 eta: 14:03:58 time: 0.2644 data_time: 0.0076 memory: 5828 grad_norm: 3.0929 loss: 2.5975 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5975 2023/06/05 06:52:42 - mmengine - INFO - Epoch(train) [76][2140/2569] lr: 4.0000e-02 eta: 14:03:53 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 3.0830 loss: 2.5017 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5017 2023/06/05 06:52:48 - mmengine - INFO - Epoch(train) [76][2160/2569] lr: 4.0000e-02 eta: 14:03:47 time: 0.2636 data_time: 0.0072 memory: 5828 grad_norm: 3.1941 loss: 2.3842 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3842 2023/06/05 06:52:53 - mmengine - INFO - Epoch(train) [76][2180/2569] lr: 4.0000e-02 eta: 14:03:42 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 3.1048 loss: 2.5012 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5012 2023/06/05 06:52:58 - mmengine - INFO - Epoch(train) [76][2200/2569] lr: 4.0000e-02 eta: 14:03:37 time: 0.2585 data_time: 0.0075 memory: 5828 grad_norm: 3.1511 loss: 2.3666 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3666 2023/06/05 06:53:03 - mmengine - INFO - Epoch(train) [76][2220/2569] lr: 4.0000e-02 eta: 14:03:31 time: 0.2579 data_time: 0.0072 memory: 5828 grad_norm: 3.1713 loss: 2.3445 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3445 2023/06/05 06:53:09 - mmengine - INFO - Epoch(train) [76][2240/2569] lr: 4.0000e-02 eta: 14:03:26 time: 0.2639 data_time: 0.0071 memory: 5828 grad_norm: 3.0866 loss: 2.7612 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7612 2023/06/05 06:53:14 - mmengine - INFO - Epoch(train) [76][2260/2569] lr: 4.0000e-02 eta: 14:03:21 time: 0.2739 data_time: 0.0071 memory: 5828 grad_norm: 3.1052 loss: 2.6758 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6758 2023/06/05 06:53:19 - mmengine - INFO - Epoch(train) [76][2280/2569] lr: 4.0000e-02 eta: 14:03:15 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 3.0572 loss: 2.7165 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7165 2023/06/05 06:53:25 - mmengine - INFO - Epoch(train) [76][2300/2569] lr: 4.0000e-02 eta: 14:03:10 time: 0.2718 data_time: 0.0071 memory: 5828 grad_norm: 3.1433 loss: 2.5037 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5037 2023/06/05 06:53:30 - mmengine - INFO - Epoch(train) [76][2320/2569] lr: 4.0000e-02 eta: 14:03:05 time: 0.2580 data_time: 0.0073 memory: 5828 grad_norm: 3.1374 loss: 2.9200 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9200 2023/06/05 06:53:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:53:35 - mmengine - INFO - Epoch(train) [76][2340/2569] lr: 4.0000e-02 eta: 14:02:59 time: 0.2635 data_time: 0.0078 memory: 5828 grad_norm: 3.1223 loss: 2.6059 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6059 2023/06/05 06:53:40 - mmengine - INFO - Epoch(train) [76][2360/2569] lr: 4.0000e-02 eta: 14:02:54 time: 0.2589 data_time: 0.0075 memory: 5828 grad_norm: 3.1161 loss: 2.8554 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.8554 2023/06/05 06:53:46 - mmengine - INFO - Epoch(train) [76][2380/2569] lr: 4.0000e-02 eta: 14:02:48 time: 0.2649 data_time: 0.0070 memory: 5828 grad_norm: 3.2041 loss: 2.5509 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5509 2023/06/05 06:53:51 - mmengine - INFO - Epoch(train) [76][2400/2569] lr: 4.0000e-02 eta: 14:02:43 time: 0.2599 data_time: 0.0073 memory: 5828 grad_norm: 3.0524 loss: 2.5906 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5906 2023/06/05 06:53:56 - mmengine - INFO - Epoch(train) [76][2420/2569] lr: 4.0000e-02 eta: 14:02:38 time: 0.2700 data_time: 0.0073 memory: 5828 grad_norm: 3.1595 loss: 2.5594 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5594 2023/06/05 06:54:01 - mmengine - INFO - Epoch(train) [76][2440/2569] lr: 4.0000e-02 eta: 14:02:32 time: 0.2582 data_time: 0.0074 memory: 5828 grad_norm: 3.0929 loss: 2.4911 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4911 2023/06/05 06:54:07 - mmengine - INFO - Epoch(train) [76][2460/2569] lr: 4.0000e-02 eta: 14:02:27 time: 0.2616 data_time: 0.0071 memory: 5828 grad_norm: 3.0455 loss: 2.6844 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6844 2023/06/05 06:54:12 - mmengine - INFO - Epoch(train) [76][2480/2569] lr: 4.0000e-02 eta: 14:02:21 time: 0.2590 data_time: 0.0075 memory: 5828 grad_norm: 3.0704 loss: 2.4662 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4662 2023/06/05 06:54:17 - mmengine - INFO - Epoch(train) [76][2500/2569] lr: 4.0000e-02 eta: 14:02:16 time: 0.2666 data_time: 0.0072 memory: 5828 grad_norm: 3.1037 loss: 2.4490 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4490 2023/06/05 06:54:22 - mmengine - INFO - Epoch(train) [76][2520/2569] lr: 4.0000e-02 eta: 14:02:11 time: 0.2611 data_time: 0.0071 memory: 5828 grad_norm: 3.1557 loss: 2.4088 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4088 2023/06/05 06:54:28 - mmengine - INFO - Epoch(train) [76][2540/2569] lr: 4.0000e-02 eta: 14:02:06 time: 0.2743 data_time: 0.0073 memory: 5828 grad_norm: 3.1112 loss: 2.6212 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6212 2023/06/05 06:54:33 - mmengine - INFO - Epoch(train) [76][2560/2569] lr: 4.0000e-02 eta: 14:02:00 time: 0.2567 data_time: 0.0080 memory: 5828 grad_norm: 3.0895 loss: 2.5812 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5812 2023/06/05 06:54:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:54:35 - mmengine - INFO - Epoch(train) [76][2569/2569] lr: 4.0000e-02 eta: 14:01:58 time: 0.2499 data_time: 0.0075 memory: 5828 grad_norm: 3.1265 loss: 2.5995 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.5995 2023/06/05 06:54:35 - mmengine - INFO - Saving checkpoint at 76 epochs 2023/06/05 06:54:43 - mmengine - INFO - Epoch(train) [77][ 20/2569] lr: 4.0000e-02 eta: 14:01:53 time: 0.3000 data_time: 0.0433 memory: 5828 grad_norm: 3.0981 loss: 2.7267 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7267 2023/06/05 06:54:48 - mmengine - INFO - Epoch(train) [77][ 40/2569] lr: 4.0000e-02 eta: 14:01:48 time: 0.2678 data_time: 0.0076 memory: 5828 grad_norm: 3.0340 loss: 2.2314 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2314 2023/06/05 06:54:54 - mmengine - INFO - Epoch(train) [77][ 60/2569] lr: 4.0000e-02 eta: 14:01:42 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 3.1462 loss: 2.6789 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6789 2023/06/05 06:54:59 - mmengine - INFO - Epoch(train) [77][ 80/2569] lr: 4.0000e-02 eta: 14:01:37 time: 0.2854 data_time: 0.0073 memory: 5828 grad_norm: 3.1560 loss: 2.7180 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.7180 2023/06/05 06:55:05 - mmengine - INFO - Epoch(train) [77][ 100/2569] lr: 4.0000e-02 eta: 14:01:32 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 3.0971 loss: 2.7683 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7683 2023/06/05 06:55:10 - mmengine - INFO - Epoch(train) [77][ 120/2569] lr: 4.0000e-02 eta: 14:01:27 time: 0.2701 data_time: 0.0069 memory: 5828 grad_norm: 3.1610 loss: 2.9922 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9922 2023/06/05 06:55:15 - mmengine - INFO - Epoch(train) [77][ 140/2569] lr: 4.0000e-02 eta: 14:01:22 time: 0.2627 data_time: 0.0077 memory: 5828 grad_norm: 3.1852 loss: 2.3441 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3441 2023/06/05 06:55:21 - mmengine - INFO - Epoch(train) [77][ 160/2569] lr: 4.0000e-02 eta: 14:01:16 time: 0.2645 data_time: 0.0078 memory: 5828 grad_norm: 3.1077 loss: 2.4383 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4383 2023/06/05 06:55:26 - mmengine - INFO - Epoch(train) [77][ 180/2569] lr: 4.0000e-02 eta: 14:01:11 time: 0.2628 data_time: 0.0073 memory: 5828 grad_norm: 3.1143 loss: 2.3368 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3368 2023/06/05 06:55:31 - mmengine - INFO - Epoch(train) [77][ 200/2569] lr: 4.0000e-02 eta: 14:01:05 time: 0.2575 data_time: 0.0079 memory: 5828 grad_norm: 3.1272 loss: 2.4922 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.4922 2023/06/05 06:55:36 - mmengine - INFO - Epoch(train) [77][ 220/2569] lr: 4.0000e-02 eta: 14:01:00 time: 0.2638 data_time: 0.0076 memory: 5828 grad_norm: 3.0871 loss: 2.7621 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7621 2023/06/05 06:55:42 - mmengine - INFO - Epoch(train) [77][ 240/2569] lr: 4.0000e-02 eta: 14:00:55 time: 0.2704 data_time: 0.0074 memory: 5828 grad_norm: 3.1491 loss: 2.3529 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3529 2023/06/05 06:55:47 - mmengine - INFO - Epoch(train) [77][ 260/2569] lr: 4.0000e-02 eta: 14:00:49 time: 0.2611 data_time: 0.0071 memory: 5828 grad_norm: 3.0688 loss: 2.2953 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.2953 2023/06/05 06:55:52 - mmengine - INFO - Epoch(train) [77][ 280/2569] lr: 4.0000e-02 eta: 14:00:44 time: 0.2658 data_time: 0.0077 memory: 5828 grad_norm: 3.0950 loss: 2.4339 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4339 2023/06/05 06:55:58 - mmengine - INFO - Epoch(train) [77][ 300/2569] lr: 4.0000e-02 eta: 14:00:39 time: 0.2699 data_time: 0.0077 memory: 5828 grad_norm: 3.1235 loss: 2.1051 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1051 2023/06/05 06:56:03 - mmengine - INFO - Epoch(train) [77][ 320/2569] lr: 4.0000e-02 eta: 14:00:33 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 3.1398 loss: 2.5068 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5068 2023/06/05 06:56:08 - mmengine - INFO - Epoch(train) [77][ 340/2569] lr: 4.0000e-02 eta: 14:00:28 time: 0.2645 data_time: 0.0076 memory: 5828 grad_norm: 3.1281 loss: 2.3020 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3020 2023/06/05 06:56:14 - mmengine - INFO - Epoch(train) [77][ 360/2569] lr: 4.0000e-02 eta: 14:00:23 time: 0.2717 data_time: 0.0076 memory: 5828 grad_norm: 3.0540 loss: 2.3886 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3886 2023/06/05 06:56:19 - mmengine - INFO - Epoch(train) [77][ 380/2569] lr: 4.0000e-02 eta: 14:00:18 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.1017 loss: 2.8450 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8450 2023/06/05 06:56:24 - mmengine - INFO - Epoch(train) [77][ 400/2569] lr: 4.0000e-02 eta: 14:00:12 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 3.1069 loss: 2.3541 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3541 2023/06/05 06:56:30 - mmengine - INFO - Epoch(train) [77][ 420/2569] lr: 4.0000e-02 eta: 14:00:07 time: 0.2579 data_time: 0.0071 memory: 5828 grad_norm: 3.1432 loss: 2.0699 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0699 2023/06/05 06:56:35 - mmengine - INFO - Epoch(train) [77][ 440/2569] lr: 4.0000e-02 eta: 14:00:01 time: 0.2615 data_time: 0.0076 memory: 5828 grad_norm: 3.0836 loss: 2.5874 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5874 2023/06/05 06:56:40 - mmengine - INFO - Epoch(train) [77][ 460/2569] lr: 4.0000e-02 eta: 13:59:56 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 3.0589 loss: 2.7946 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7946 2023/06/05 06:56:45 - mmengine - INFO - Epoch(train) [77][ 480/2569] lr: 4.0000e-02 eta: 13:59:51 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 3.1266 loss: 2.1532 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1532 2023/06/05 06:56:51 - mmengine - INFO - Epoch(train) [77][ 500/2569] lr: 4.0000e-02 eta: 13:59:45 time: 0.2594 data_time: 0.0074 memory: 5828 grad_norm: 3.1222 loss: 2.7053 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7053 2023/06/05 06:56:56 - mmengine - INFO - Epoch(train) [77][ 520/2569] lr: 4.0000e-02 eta: 13:59:40 time: 0.2583 data_time: 0.0075 memory: 5828 grad_norm: 3.0760 loss: 2.2996 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2996 2023/06/05 06:57:01 - mmengine - INFO - Epoch(train) [77][ 540/2569] lr: 4.0000e-02 eta: 13:59:34 time: 0.2623 data_time: 0.0081 memory: 5828 grad_norm: 3.1199 loss: 2.5780 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5780 2023/06/05 06:57:06 - mmengine - INFO - Epoch(train) [77][ 560/2569] lr: 4.0000e-02 eta: 13:59:29 time: 0.2607 data_time: 0.0080 memory: 5828 grad_norm: 3.1252 loss: 2.3798 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3798 2023/06/05 06:57:12 - mmengine - INFO - Epoch(train) [77][ 580/2569] lr: 4.0000e-02 eta: 13:59:24 time: 0.2721 data_time: 0.0077 memory: 5828 grad_norm: 3.0883 loss: 2.3334 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3334 2023/06/05 06:57:17 - mmengine - INFO - Epoch(train) [77][ 600/2569] lr: 4.0000e-02 eta: 13:59:18 time: 0.2606 data_time: 0.0076 memory: 5828 grad_norm: 3.1020 loss: 2.5546 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5546 2023/06/05 06:57:22 - mmengine - INFO - Epoch(train) [77][ 620/2569] lr: 4.0000e-02 eta: 13:59:13 time: 0.2678 data_time: 0.0074 memory: 5828 grad_norm: 3.1601 loss: 2.6710 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6710 2023/06/05 06:57:28 - mmengine - INFO - Epoch(train) [77][ 640/2569] lr: 4.0000e-02 eta: 13:59:08 time: 0.2689 data_time: 0.0076 memory: 5828 grad_norm: 3.1212 loss: 2.6593 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6593 2023/06/05 06:57:33 - mmengine - INFO - Epoch(train) [77][ 660/2569] lr: 4.0000e-02 eta: 13:59:02 time: 0.2651 data_time: 0.0072 memory: 5828 grad_norm: 3.1249 loss: 2.7425 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7425 2023/06/05 06:57:38 - mmengine - INFO - Epoch(train) [77][ 680/2569] lr: 4.0000e-02 eta: 13:58:57 time: 0.2602 data_time: 0.0078 memory: 5828 grad_norm: 3.1515 loss: 2.6128 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6128 2023/06/05 06:57:44 - mmengine - INFO - Epoch(train) [77][ 700/2569] lr: 4.0000e-02 eta: 13:58:52 time: 0.2841 data_time: 0.0073 memory: 5828 grad_norm: 3.1350 loss: 2.5301 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5301 2023/06/05 06:57:49 - mmengine - INFO - Epoch(train) [77][ 720/2569] lr: 4.0000e-02 eta: 13:58:47 time: 0.2606 data_time: 0.0077 memory: 5828 grad_norm: 3.1604 loss: 2.6754 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6754 2023/06/05 06:57:55 - mmengine - INFO - Epoch(train) [77][ 740/2569] lr: 4.0000e-02 eta: 13:58:42 time: 0.2805 data_time: 0.0082 memory: 5828 grad_norm: 3.1482 loss: 2.2639 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2639 2023/06/05 06:57:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 06:58:00 - mmengine - INFO - Epoch(train) [77][ 760/2569] lr: 4.0000e-02 eta: 13:58:36 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 3.1834 loss: 2.7515 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7515 2023/06/05 06:58:05 - mmengine - INFO - Epoch(train) [77][ 780/2569] lr: 4.0000e-02 eta: 13:58:31 time: 0.2725 data_time: 0.0074 memory: 5828 grad_norm: 3.1385 loss: 2.3426 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3426 2023/06/05 06:58:11 - mmengine - INFO - Epoch(train) [77][ 800/2569] lr: 4.0000e-02 eta: 13:58:26 time: 0.2664 data_time: 0.0080 memory: 5828 grad_norm: 3.1481 loss: 2.6219 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6219 2023/06/05 06:58:16 - mmengine - INFO - Epoch(train) [77][ 820/2569] lr: 4.0000e-02 eta: 13:58:20 time: 0.2606 data_time: 0.0071 memory: 5828 grad_norm: 3.1227 loss: 2.4474 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4474 2023/06/05 06:58:21 - mmengine - INFO - Epoch(train) [77][ 840/2569] lr: 4.0000e-02 eta: 13:58:15 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 3.0785 loss: 2.3443 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3443 2023/06/05 06:58:27 - mmengine - INFO - Epoch(train) [77][ 860/2569] lr: 4.0000e-02 eta: 13:58:10 time: 0.2761 data_time: 0.0068 memory: 5828 grad_norm: 3.1361 loss: 2.4884 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4884 2023/06/05 06:58:32 - mmengine - INFO - Epoch(train) [77][ 880/2569] lr: 4.0000e-02 eta: 13:58:04 time: 0.2578 data_time: 0.0077 memory: 5828 grad_norm: 3.0951 loss: 2.6632 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6632 2023/06/05 06:58:38 - mmengine - INFO - Epoch(train) [77][ 900/2569] lr: 4.0000e-02 eta: 13:57:59 time: 0.2808 data_time: 0.0074 memory: 5828 grad_norm: 3.1530 loss: 2.5890 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5890 2023/06/05 06:58:43 - mmengine - INFO - Epoch(train) [77][ 920/2569] lr: 4.0000e-02 eta: 13:57:54 time: 0.2568 data_time: 0.0080 memory: 5828 grad_norm: 3.1606 loss: 2.5212 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5212 2023/06/05 06:58:48 - mmengine - INFO - Epoch(train) [77][ 940/2569] lr: 4.0000e-02 eta: 13:57:49 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 3.1117 loss: 2.7489 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7489 2023/06/05 06:58:53 - mmengine - INFO - Epoch(train) [77][ 960/2569] lr: 4.0000e-02 eta: 13:57:43 time: 0.2579 data_time: 0.0075 memory: 5828 grad_norm: 3.1483 loss: 2.4758 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4758 2023/06/05 06:58:59 - mmengine - INFO - Epoch(train) [77][ 980/2569] lr: 4.0000e-02 eta: 13:57:38 time: 0.2642 data_time: 0.0075 memory: 5828 grad_norm: 3.0961 loss: 2.4468 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4468 2023/06/05 06:59:04 - mmengine - INFO - Epoch(train) [77][1000/2569] lr: 4.0000e-02 eta: 13:57:32 time: 0.2635 data_time: 0.0080 memory: 5828 grad_norm: 3.0996 loss: 2.1788 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1788 2023/06/05 06:59:09 - mmengine - INFO - Epoch(train) [77][1020/2569] lr: 4.0000e-02 eta: 13:57:27 time: 0.2636 data_time: 0.0080 memory: 5828 grad_norm: 3.1287 loss: 2.7293 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7293 2023/06/05 06:59:15 - mmengine - INFO - Epoch(train) [77][1040/2569] lr: 4.0000e-02 eta: 13:57:22 time: 0.2721 data_time: 0.0075 memory: 5828 grad_norm: 3.1389 loss: 2.6071 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6071 2023/06/05 06:59:20 - mmengine - INFO - Epoch(train) [77][1060/2569] lr: 4.0000e-02 eta: 13:57:17 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 3.1142 loss: 2.6959 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6959 2023/06/05 06:59:25 - mmengine - INFO - Epoch(train) [77][1080/2569] lr: 4.0000e-02 eta: 13:57:11 time: 0.2642 data_time: 0.0077 memory: 5828 grad_norm: 3.1018 loss: 2.7245 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7245 2023/06/05 06:59:30 - mmengine - INFO - Epoch(train) [77][1100/2569] lr: 4.0000e-02 eta: 13:57:06 time: 0.2581 data_time: 0.0074 memory: 5828 grad_norm: 3.1391 loss: 2.4042 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4042 2023/06/05 06:59:36 - mmengine - INFO - Epoch(train) [77][1120/2569] lr: 4.0000e-02 eta: 13:57:01 time: 0.2729 data_time: 0.0071 memory: 5828 grad_norm: 3.1415 loss: 2.4782 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4782 2023/06/05 06:59:41 - mmengine - INFO - Epoch(train) [77][1140/2569] lr: 4.0000e-02 eta: 13:56:55 time: 0.2713 data_time: 0.0071 memory: 5828 grad_norm: 3.0913 loss: 2.8874 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8874 2023/06/05 06:59:46 - mmengine - INFO - Epoch(train) [77][1160/2569] lr: 4.0000e-02 eta: 13:56:50 time: 0.2581 data_time: 0.0083 memory: 5828 grad_norm: 3.1192 loss: 2.8041 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8041 2023/06/05 06:59:52 - mmengine - INFO - Epoch(train) [77][1180/2569] lr: 4.0000e-02 eta: 13:56:45 time: 0.2718 data_time: 0.0073 memory: 5828 grad_norm: 3.0795 loss: 2.3360 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3360 2023/06/05 06:59:57 - mmengine - INFO - Epoch(train) [77][1200/2569] lr: 4.0000e-02 eta: 13:56:39 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 3.0779 loss: 2.4393 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4393 2023/06/05 07:00:02 - mmengine - INFO - Epoch(train) [77][1220/2569] lr: 4.0000e-02 eta: 13:56:34 time: 0.2592 data_time: 0.0076 memory: 5828 grad_norm: 3.1165 loss: 2.4906 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4906 2023/06/05 07:00:07 - mmengine - INFO - Epoch(train) [77][1240/2569] lr: 4.0000e-02 eta: 13:56:29 time: 0.2643 data_time: 0.0077 memory: 5828 grad_norm: 3.0985 loss: 2.5252 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5252 2023/06/05 07:00:13 - mmengine - INFO - Epoch(train) [77][1260/2569] lr: 4.0000e-02 eta: 13:56:23 time: 0.2591 data_time: 0.0071 memory: 5828 grad_norm: 3.1352 loss: 2.4088 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 2.4088 2023/06/05 07:00:18 - mmengine - INFO - Epoch(train) [77][1280/2569] lr: 4.0000e-02 eta: 13:56:18 time: 0.2646 data_time: 0.0076 memory: 5828 grad_norm: 3.0993 loss: 2.5397 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5397 2023/06/05 07:00:23 - mmengine - INFO - Epoch(train) [77][1300/2569] lr: 4.0000e-02 eta: 13:56:12 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 3.2088 loss: 2.6059 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6059 2023/06/05 07:00:29 - mmengine - INFO - Epoch(train) [77][1320/2569] lr: 4.0000e-02 eta: 13:56:07 time: 0.2640 data_time: 0.0070 memory: 5828 grad_norm: 3.1203 loss: 2.7146 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7146 2023/06/05 07:00:34 - mmengine - INFO - Epoch(train) [77][1340/2569] lr: 4.0000e-02 eta: 13:56:02 time: 0.2597 data_time: 0.0077 memory: 5828 grad_norm: 3.1648 loss: 2.5368 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5368 2023/06/05 07:00:39 - mmengine - INFO - Epoch(train) [77][1360/2569] lr: 4.0000e-02 eta: 13:55:56 time: 0.2676 data_time: 0.0074 memory: 5828 grad_norm: 3.0969 loss: 2.7656 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7656 2023/06/05 07:00:44 - mmengine - INFO - Epoch(train) [77][1380/2569] lr: 4.0000e-02 eta: 13:55:51 time: 0.2584 data_time: 0.0079 memory: 5828 grad_norm: 3.0645 loss: 2.2422 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2422 2023/06/05 07:00:50 - mmengine - INFO - Epoch(train) [77][1400/2569] lr: 4.0000e-02 eta: 13:55:45 time: 0.2643 data_time: 0.0079 memory: 5828 grad_norm: 3.1075 loss: 2.7897 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7897 2023/06/05 07:00:55 - mmengine - INFO - Epoch(train) [77][1420/2569] lr: 4.0000e-02 eta: 13:55:40 time: 0.2574 data_time: 0.0078 memory: 5828 grad_norm: 3.1317 loss: 2.6347 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6347 2023/06/05 07:01:00 - mmengine - INFO - Epoch(train) [77][1440/2569] lr: 4.0000e-02 eta: 13:55:35 time: 0.2577 data_time: 0.0078 memory: 5828 grad_norm: 3.1381 loss: 2.3746 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3746 2023/06/05 07:01:05 - mmengine - INFO - Epoch(train) [77][1460/2569] lr: 4.0000e-02 eta: 13:55:29 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 3.1266 loss: 2.6753 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6753 2023/06/05 07:01:10 - mmengine - INFO - Epoch(train) [77][1480/2569] lr: 4.0000e-02 eta: 13:55:24 time: 0.2608 data_time: 0.0077 memory: 5828 grad_norm: 3.1843 loss: 2.8327 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8327 2023/06/05 07:01:16 - mmengine - INFO - Epoch(train) [77][1500/2569] lr: 4.0000e-02 eta: 13:55:18 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 3.1645 loss: 2.7958 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7958 2023/06/05 07:01:21 - mmengine - INFO - Epoch(train) [77][1520/2569] lr: 4.0000e-02 eta: 13:55:13 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 3.1577 loss: 2.6046 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6046 2023/06/05 07:01:26 - mmengine - INFO - Epoch(train) [77][1540/2569] lr: 4.0000e-02 eta: 13:55:08 time: 0.2690 data_time: 0.0078 memory: 5828 grad_norm: 3.1187 loss: 2.5622 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5622 2023/06/05 07:01:32 - mmengine - INFO - Epoch(train) [77][1560/2569] lr: 4.0000e-02 eta: 13:55:03 time: 0.2734 data_time: 0.0078 memory: 5828 grad_norm: 3.1233 loss: 2.6030 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6030 2023/06/05 07:01:37 - mmengine - INFO - Epoch(train) [77][1580/2569] lr: 4.0000e-02 eta: 13:54:57 time: 0.2637 data_time: 0.0071 memory: 5828 grad_norm: 3.1229 loss: 2.2201 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2201 2023/06/05 07:01:42 - mmengine - INFO - Epoch(train) [77][1600/2569] lr: 4.0000e-02 eta: 13:54:52 time: 0.2622 data_time: 0.0078 memory: 5828 grad_norm: 3.0823 loss: 2.5169 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5169 2023/06/05 07:01:48 - mmengine - INFO - Epoch(train) [77][1620/2569] lr: 4.0000e-02 eta: 13:54:47 time: 0.2569 data_time: 0.0071 memory: 5828 grad_norm: 3.1757 loss: 2.3143 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3143 2023/06/05 07:01:53 - mmengine - INFO - Epoch(train) [77][1640/2569] lr: 4.0000e-02 eta: 13:54:41 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 3.1025 loss: 2.5914 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5914 2023/06/05 07:01:58 - mmengine - INFO - Epoch(train) [77][1660/2569] lr: 4.0000e-02 eta: 13:54:36 time: 0.2631 data_time: 0.0076 memory: 5828 grad_norm: 3.1141 loss: 2.4471 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4471 2023/06/05 07:02:03 - mmengine - INFO - Epoch(train) [77][1680/2569] lr: 4.0000e-02 eta: 13:54:30 time: 0.2644 data_time: 0.0076 memory: 5828 grad_norm: 3.1042 loss: 2.5724 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5724 2023/06/05 07:02:09 - mmengine - INFO - Epoch(train) [77][1700/2569] lr: 4.0000e-02 eta: 13:54:25 time: 0.2628 data_time: 0.0068 memory: 5828 grad_norm: 3.1272 loss: 2.2666 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2666 2023/06/05 07:02:14 - mmengine - INFO - Epoch(train) [77][1720/2569] lr: 4.0000e-02 eta: 13:54:20 time: 0.2719 data_time: 0.0074 memory: 5828 grad_norm: 3.1348 loss: 2.4411 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4411 2023/06/05 07:02:19 - mmengine - INFO - Epoch(train) [77][1740/2569] lr: 4.0000e-02 eta: 13:54:15 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 3.1722 loss: 2.2168 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2168 2023/06/05 07:02:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:02:25 - mmengine - INFO - Epoch(train) [77][1760/2569] lr: 4.0000e-02 eta: 13:54:10 time: 0.2837 data_time: 0.0074 memory: 5828 grad_norm: 3.1744 loss: 2.7512 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7512 2023/06/05 07:02:31 - mmengine - INFO - Epoch(train) [77][1780/2569] lr: 4.0000e-02 eta: 13:54:05 time: 0.2768 data_time: 0.0074 memory: 5828 grad_norm: 3.1827 loss: 2.2756 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2756 2023/06/05 07:02:36 - mmengine - INFO - Epoch(train) [77][1800/2569] lr: 4.0000e-02 eta: 13:53:59 time: 0.2585 data_time: 0.0076 memory: 5828 grad_norm: 3.1457 loss: 2.4326 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4326 2023/06/05 07:02:41 - mmengine - INFO - Epoch(train) [77][1820/2569] lr: 4.0000e-02 eta: 13:53:54 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 3.1480 loss: 2.5977 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5977 2023/06/05 07:02:46 - mmengine - INFO - Epoch(train) [77][1840/2569] lr: 4.0000e-02 eta: 13:53:48 time: 0.2589 data_time: 0.0073 memory: 5828 grad_norm: 3.1446 loss: 2.5556 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5556 2023/06/05 07:02:51 - mmengine - INFO - Epoch(train) [77][1860/2569] lr: 4.0000e-02 eta: 13:53:43 time: 0.2575 data_time: 0.0077 memory: 5828 grad_norm: 3.1640 loss: 2.5287 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5287 2023/06/05 07:02:57 - mmengine - INFO - Epoch(train) [77][1880/2569] lr: 4.0000e-02 eta: 13:53:38 time: 0.2698 data_time: 0.0076 memory: 5828 grad_norm: 3.1517 loss: 2.6196 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6196 2023/06/05 07:03:02 - mmengine - INFO - Epoch(train) [77][1900/2569] lr: 4.0000e-02 eta: 13:53:32 time: 0.2599 data_time: 0.0079 memory: 5828 grad_norm: 3.1294 loss: 2.4840 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4840 2023/06/05 07:03:07 - mmengine - INFO - Epoch(train) [77][1920/2569] lr: 4.0000e-02 eta: 13:53:27 time: 0.2629 data_time: 0.0076 memory: 5828 grad_norm: 3.1945 loss: 2.6240 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6240 2023/06/05 07:03:12 - mmengine - INFO - Epoch(train) [77][1940/2569] lr: 4.0000e-02 eta: 13:53:21 time: 0.2585 data_time: 0.0076 memory: 5828 grad_norm: 3.1268 loss: 2.6643 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.6643 2023/06/05 07:03:18 - mmengine - INFO - Epoch(train) [77][1960/2569] lr: 4.0000e-02 eta: 13:53:16 time: 0.2767 data_time: 0.0076 memory: 5828 grad_norm: 3.1089 loss: 2.7382 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7382 2023/06/05 07:03:23 - mmengine - INFO - Epoch(train) [77][1980/2569] lr: 4.0000e-02 eta: 13:53:11 time: 0.2585 data_time: 0.0078 memory: 5828 grad_norm: 3.1301 loss: 2.5626 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5626 2023/06/05 07:03:28 - mmengine - INFO - Epoch(train) [77][2000/2569] lr: 4.0000e-02 eta: 13:53:05 time: 0.2614 data_time: 0.0075 memory: 5828 grad_norm: 3.1500 loss: 2.5017 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5017 2023/06/05 07:03:34 - mmengine - INFO - Epoch(train) [77][2020/2569] lr: 4.0000e-02 eta: 13:53:00 time: 0.2571 data_time: 0.0073 memory: 5828 grad_norm: 3.1846 loss: 2.2653 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2653 2023/06/05 07:03:39 - mmengine - INFO - Epoch(train) [77][2040/2569] lr: 4.0000e-02 eta: 13:52:54 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 3.1750 loss: 2.3708 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3708 2023/06/05 07:03:44 - mmengine - INFO - Epoch(train) [77][2060/2569] lr: 4.0000e-02 eta: 13:52:49 time: 0.2612 data_time: 0.0074 memory: 5828 grad_norm: 3.1156 loss: 2.6575 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6575 2023/06/05 07:03:50 - mmengine - INFO - Epoch(train) [77][2080/2569] lr: 4.0000e-02 eta: 13:52:44 time: 0.2737 data_time: 0.0075 memory: 5828 grad_norm: 3.1017 loss: 2.3235 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3235 2023/06/05 07:03:55 - mmengine - INFO - Epoch(train) [77][2100/2569] lr: 4.0000e-02 eta: 13:52:38 time: 0.2593 data_time: 0.0079 memory: 5828 grad_norm: 3.1222 loss: 2.4694 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4694 2023/06/05 07:04:00 - mmengine - INFO - Epoch(train) [77][2120/2569] lr: 4.0000e-02 eta: 13:52:33 time: 0.2649 data_time: 0.0077 memory: 5828 grad_norm: 3.0953 loss: 2.4484 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4484 2023/06/05 07:04:05 - mmengine - INFO - Epoch(train) [77][2140/2569] lr: 4.0000e-02 eta: 13:52:28 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 3.1482 loss: 2.3903 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3903 2023/06/05 07:04:11 - mmengine - INFO - Epoch(train) [77][2160/2569] lr: 4.0000e-02 eta: 13:52:23 time: 0.2750 data_time: 0.0075 memory: 5828 grad_norm: 3.1007 loss: 2.3148 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3148 2023/06/05 07:04:16 - mmengine - INFO - Epoch(train) [77][2180/2569] lr: 4.0000e-02 eta: 13:52:17 time: 0.2651 data_time: 0.0067 memory: 5828 grad_norm: 3.1463 loss: 2.3781 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3781 2023/06/05 07:04:21 - mmengine - INFO - Epoch(train) [77][2200/2569] lr: 4.0000e-02 eta: 13:52:12 time: 0.2637 data_time: 0.0075 memory: 5828 grad_norm: 3.0943 loss: 2.4286 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4286 2023/06/05 07:04:27 - mmengine - INFO - Epoch(train) [77][2220/2569] lr: 4.0000e-02 eta: 13:52:06 time: 0.2593 data_time: 0.0073 memory: 5828 grad_norm: 3.0814 loss: 2.3725 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3725 2023/06/05 07:04:32 - mmengine - INFO - Epoch(train) [77][2240/2569] lr: 4.0000e-02 eta: 13:52:01 time: 0.2628 data_time: 0.0077 memory: 5828 grad_norm: 3.2019 loss: 2.5362 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5362 2023/06/05 07:04:37 - mmengine - INFO - Epoch(train) [77][2260/2569] lr: 4.0000e-02 eta: 13:51:56 time: 0.2578 data_time: 0.0078 memory: 5828 grad_norm: 3.1158 loss: 2.2121 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2121 2023/06/05 07:04:42 - mmengine - INFO - Epoch(train) [77][2280/2569] lr: 4.0000e-02 eta: 13:51:50 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 3.2023 loss: 2.4642 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4642 2023/06/05 07:04:48 - mmengine - INFO - Epoch(train) [77][2300/2569] lr: 4.0000e-02 eta: 13:51:45 time: 0.2643 data_time: 0.0075 memory: 5828 grad_norm: 3.1911 loss: 2.4888 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4888 2023/06/05 07:04:53 - mmengine - INFO - Epoch(train) [77][2320/2569] lr: 4.0000e-02 eta: 13:51:40 time: 0.2755 data_time: 0.0073 memory: 5828 grad_norm: 3.0894 loss: 2.6817 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6817 2023/06/05 07:04:58 - mmengine - INFO - Epoch(train) [77][2340/2569] lr: 4.0000e-02 eta: 13:51:34 time: 0.2593 data_time: 0.0075 memory: 5828 grad_norm: 3.1273 loss: 2.6202 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6202 2023/06/05 07:05:04 - mmengine - INFO - Epoch(train) [77][2360/2569] lr: 4.0000e-02 eta: 13:51:29 time: 0.2751 data_time: 0.0075 memory: 5828 grad_norm: 3.1246 loss: 2.7151 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7151 2023/06/05 07:05:09 - mmengine - INFO - Epoch(train) [77][2380/2569] lr: 4.0000e-02 eta: 13:51:24 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 3.1595 loss: 2.1785 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1785 2023/06/05 07:05:15 - mmengine - INFO - Epoch(train) [77][2400/2569] lr: 4.0000e-02 eta: 13:51:19 time: 0.2765 data_time: 0.0074 memory: 5828 grad_norm: 3.1103 loss: 2.6235 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6235 2023/06/05 07:05:20 - mmengine - INFO - Epoch(train) [77][2420/2569] lr: 4.0000e-02 eta: 13:51:13 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 3.1684 loss: 2.1819 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.1819 2023/06/05 07:05:25 - mmengine - INFO - Epoch(train) [77][2440/2569] lr: 4.0000e-02 eta: 13:51:08 time: 0.2702 data_time: 0.0074 memory: 5828 grad_norm: 3.0826 loss: 2.2887 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.2887 2023/06/05 07:05:31 - mmengine - INFO - Epoch(train) [77][2460/2569] lr: 4.0000e-02 eta: 13:51:03 time: 0.2644 data_time: 0.0077 memory: 5828 grad_norm: 3.1475 loss: 2.3097 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.3097 2023/06/05 07:05:36 - mmengine - INFO - Epoch(train) [77][2480/2569] lr: 4.0000e-02 eta: 13:50:58 time: 0.2686 data_time: 0.0080 memory: 5828 grad_norm: 3.1687 loss: 2.6194 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6194 2023/06/05 07:05:41 - mmengine - INFO - Epoch(train) [77][2500/2569] lr: 4.0000e-02 eta: 13:50:52 time: 0.2668 data_time: 0.0075 memory: 5828 grad_norm: 3.1448 loss: 2.3042 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3042 2023/06/05 07:05:47 - mmengine - INFO - Epoch(train) [77][2520/2569] lr: 4.0000e-02 eta: 13:50:47 time: 0.2576 data_time: 0.0076 memory: 5828 grad_norm: 3.0513 loss: 2.2360 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2360 2023/06/05 07:05:52 - mmengine - INFO - Epoch(train) [77][2540/2569] lr: 4.0000e-02 eta: 13:50:42 time: 0.2782 data_time: 0.0071 memory: 5828 grad_norm: 3.0837 loss: 2.5987 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5987 2023/06/05 07:05:57 - mmengine - INFO - Epoch(train) [77][2560/2569] lr: 4.0000e-02 eta: 13:50:36 time: 0.2624 data_time: 0.0077 memory: 5828 grad_norm: 3.0885 loss: 2.6109 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6109 2023/06/05 07:06:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:06:00 - mmengine - INFO - Epoch(train) [77][2569/2569] lr: 4.0000e-02 eta: 13:50:34 time: 0.2570 data_time: 0.0072 memory: 5828 grad_norm: 3.0816 loss: 2.4308 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4308 2023/06/05 07:06:07 - mmengine - INFO - Epoch(train) [78][ 20/2569] lr: 4.0000e-02 eta: 13:50:30 time: 0.3420 data_time: 0.0501 memory: 5828 grad_norm: 3.0940 loss: 2.7935 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7935 2023/06/05 07:06:12 - mmengine - INFO - Epoch(train) [78][ 40/2569] lr: 4.0000e-02 eta: 13:50:25 time: 0.2591 data_time: 0.0077 memory: 5828 grad_norm: 3.0872 loss: 2.4215 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4215 2023/06/05 07:06:17 - mmengine - INFO - Epoch(train) [78][ 60/2569] lr: 4.0000e-02 eta: 13:50:19 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 3.1104 loss: 2.4310 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4310 2023/06/05 07:06:22 - mmengine - INFO - Epoch(train) [78][ 80/2569] lr: 4.0000e-02 eta: 13:50:14 time: 0.2595 data_time: 0.0072 memory: 5828 grad_norm: 3.1238 loss: 2.1435 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.1435 2023/06/05 07:06:28 - mmengine - INFO - Epoch(train) [78][ 100/2569] lr: 4.0000e-02 eta: 13:50:09 time: 0.2675 data_time: 0.0078 memory: 5828 grad_norm: 3.1339 loss: 2.5619 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5619 2023/06/05 07:06:33 - mmengine - INFO - Epoch(train) [78][ 120/2569] lr: 4.0000e-02 eta: 13:50:03 time: 0.2584 data_time: 0.0075 memory: 5828 grad_norm: 3.0836 loss: 2.6816 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6816 2023/06/05 07:06:38 - mmengine - INFO - Epoch(train) [78][ 140/2569] lr: 4.0000e-02 eta: 13:49:58 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 3.1618 loss: 2.4820 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4820 2023/06/05 07:06:43 - mmengine - INFO - Epoch(train) [78][ 160/2569] lr: 4.0000e-02 eta: 13:49:52 time: 0.2607 data_time: 0.0073 memory: 5828 grad_norm: 3.0992 loss: 2.4169 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4169 2023/06/05 07:06:49 - mmengine - INFO - Epoch(train) [78][ 180/2569] lr: 4.0000e-02 eta: 13:49:47 time: 0.2657 data_time: 0.0073 memory: 5828 grad_norm: 3.1393 loss: 2.3250 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3250 2023/06/05 07:06:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:06:54 - mmengine - INFO - Epoch(train) [78][ 200/2569] lr: 4.0000e-02 eta: 13:49:42 time: 0.2578 data_time: 0.0075 memory: 5828 grad_norm: 3.1155 loss: 2.5079 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5079 2023/06/05 07:06:59 - mmengine - INFO - Epoch(train) [78][ 220/2569] lr: 4.0000e-02 eta: 13:49:36 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 3.1418 loss: 2.4892 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4892 2023/06/05 07:07:05 - mmengine - INFO - Epoch(train) [78][ 240/2569] lr: 4.0000e-02 eta: 13:49:31 time: 0.2700 data_time: 0.0074 memory: 5828 grad_norm: 3.1245 loss: 2.2877 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2877 2023/06/05 07:07:10 - mmengine - INFO - Epoch(train) [78][ 260/2569] lr: 4.0000e-02 eta: 13:49:26 time: 0.2681 data_time: 0.0076 memory: 5828 grad_norm: 3.1014 loss: 2.3912 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3912 2023/06/05 07:07:15 - mmengine - INFO - Epoch(train) [78][ 280/2569] lr: 4.0000e-02 eta: 13:49:21 time: 0.2710 data_time: 0.0074 memory: 5828 grad_norm: 3.0859 loss: 2.4647 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4647 2023/06/05 07:07:21 - mmengine - INFO - Epoch(train) [78][ 300/2569] lr: 4.0000e-02 eta: 13:49:15 time: 0.2741 data_time: 0.0079 memory: 5828 grad_norm: 3.1355 loss: 2.5266 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5266 2023/06/05 07:07:26 - mmengine - INFO - Epoch(train) [78][ 320/2569] lr: 4.0000e-02 eta: 13:49:10 time: 0.2676 data_time: 0.0076 memory: 5828 grad_norm: 3.1272 loss: 2.4439 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4439 2023/06/05 07:07:32 - mmengine - INFO - Epoch(train) [78][ 340/2569] lr: 4.0000e-02 eta: 13:49:05 time: 0.2701 data_time: 0.0074 memory: 5828 grad_norm: 3.0992 loss: 2.5771 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5771 2023/06/05 07:07:37 - mmengine - INFO - Epoch(train) [78][ 360/2569] lr: 4.0000e-02 eta: 13:49:00 time: 0.2607 data_time: 0.0079 memory: 5828 grad_norm: 3.0882 loss: 2.6721 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6721 2023/06/05 07:07:42 - mmengine - INFO - Epoch(train) [78][ 380/2569] lr: 4.0000e-02 eta: 13:48:54 time: 0.2619 data_time: 0.0076 memory: 5828 grad_norm: 3.0416 loss: 2.6549 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6549 2023/06/05 07:07:47 - mmengine - INFO - Epoch(train) [78][ 400/2569] lr: 4.0000e-02 eta: 13:48:49 time: 0.2669 data_time: 0.0076 memory: 5828 grad_norm: 3.0719 loss: 2.6652 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6652 2023/06/05 07:07:53 - mmengine - INFO - Epoch(train) [78][ 420/2569] lr: 4.0000e-02 eta: 13:48:44 time: 0.2698 data_time: 0.0072 memory: 5828 grad_norm: 3.1144 loss: 2.6320 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6320 2023/06/05 07:07:58 - mmengine - INFO - Epoch(train) [78][ 440/2569] lr: 4.0000e-02 eta: 13:48:38 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 3.1629 loss: 2.3118 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3118 2023/06/05 07:08:03 - mmengine - INFO - Epoch(train) [78][ 460/2569] lr: 4.0000e-02 eta: 13:48:33 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 3.1014 loss: 2.5101 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5101 2023/06/05 07:08:09 - mmengine - INFO - Epoch(train) [78][ 480/2569] lr: 4.0000e-02 eta: 13:48:28 time: 0.2643 data_time: 0.0078 memory: 5828 grad_norm: 3.1320 loss: 2.3642 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3642 2023/06/05 07:08:14 - mmengine - INFO - Epoch(train) [78][ 500/2569] lr: 4.0000e-02 eta: 13:48:22 time: 0.2566 data_time: 0.0078 memory: 5828 grad_norm: 3.1255 loss: 2.7125 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7125 2023/06/05 07:08:19 - mmengine - INFO - Epoch(train) [78][ 520/2569] lr: 4.0000e-02 eta: 13:48:17 time: 0.2716 data_time: 0.0070 memory: 5828 grad_norm: 3.0812 loss: 2.5332 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5332 2023/06/05 07:08:25 - mmengine - INFO - Epoch(train) [78][ 540/2569] lr: 4.0000e-02 eta: 13:48:12 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 3.2223 loss: 2.8113 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8113 2023/06/05 07:08:30 - mmengine - INFO - Epoch(train) [78][ 560/2569] lr: 4.0000e-02 eta: 13:48:06 time: 0.2621 data_time: 0.0066 memory: 5828 grad_norm: 3.1464 loss: 2.4728 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4728 2023/06/05 07:08:35 - mmengine - INFO - Epoch(train) [78][ 580/2569] lr: 4.0000e-02 eta: 13:48:01 time: 0.2634 data_time: 0.0071 memory: 5828 grad_norm: 3.1247 loss: 2.3499 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3499 2023/06/05 07:08:40 - mmengine - INFO - Epoch(train) [78][ 600/2569] lr: 4.0000e-02 eta: 13:47:55 time: 0.2628 data_time: 0.0074 memory: 5828 grad_norm: 3.1440 loss: 2.5710 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5710 2023/06/05 07:08:46 - mmengine - INFO - Epoch(train) [78][ 620/2569] lr: 4.0000e-02 eta: 13:47:50 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.1694 loss: 2.5083 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5083 2023/06/05 07:08:51 - mmengine - INFO - Epoch(train) [78][ 640/2569] lr: 4.0000e-02 eta: 13:47:45 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 3.1757 loss: 2.4541 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4541 2023/06/05 07:08:56 - mmengine - INFO - Epoch(train) [78][ 660/2569] lr: 4.0000e-02 eta: 13:47:39 time: 0.2639 data_time: 0.0078 memory: 5828 grad_norm: 3.1598 loss: 2.5697 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5697 2023/06/05 07:09:01 - mmengine - INFO - Epoch(train) [78][ 680/2569] lr: 4.0000e-02 eta: 13:47:34 time: 0.2635 data_time: 0.0069 memory: 5828 grad_norm: 3.1674 loss: 2.3880 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3880 2023/06/05 07:09:07 - mmengine - INFO - Epoch(train) [78][ 700/2569] lr: 4.0000e-02 eta: 13:47:29 time: 0.2587 data_time: 0.0075 memory: 5828 grad_norm: 3.1522 loss: 2.8793 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8793 2023/06/05 07:09:12 - mmengine - INFO - Epoch(train) [78][ 720/2569] lr: 4.0000e-02 eta: 13:47:23 time: 0.2753 data_time: 0.0076 memory: 5828 grad_norm: 3.2457 loss: 2.7763 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7763 2023/06/05 07:09:17 - mmengine - INFO - Epoch(train) [78][ 740/2569] lr: 4.0000e-02 eta: 13:47:18 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.1463 loss: 2.3744 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3744 2023/06/05 07:09:23 - mmengine - INFO - Epoch(train) [78][ 760/2569] lr: 4.0000e-02 eta: 13:47:13 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 3.1555 loss: 2.5345 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5345 2023/06/05 07:09:28 - mmengine - INFO - Epoch(train) [78][ 780/2569] lr: 4.0000e-02 eta: 13:47:07 time: 0.2570 data_time: 0.0078 memory: 5828 grad_norm: 3.1607 loss: 2.6259 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6259 2023/06/05 07:09:33 - mmengine - INFO - Epoch(train) [78][ 800/2569] lr: 4.0000e-02 eta: 13:47:02 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 3.1462 loss: 2.3778 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3778 2023/06/05 07:09:39 - mmengine - INFO - Epoch(train) [78][ 820/2569] lr: 4.0000e-02 eta: 13:46:57 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 3.1722 loss: 2.4984 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4984 2023/06/05 07:09:44 - mmengine - INFO - Epoch(train) [78][ 840/2569] lr: 4.0000e-02 eta: 13:46:51 time: 0.2595 data_time: 0.0072 memory: 5828 grad_norm: 3.1438 loss: 2.6069 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6069 2023/06/05 07:09:49 - mmengine - INFO - Epoch(train) [78][ 860/2569] lr: 4.0000e-02 eta: 13:46:46 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 3.1298 loss: 2.4840 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.4840 2023/06/05 07:09:54 - mmengine - INFO - Epoch(train) [78][ 880/2569] lr: 4.0000e-02 eta: 13:46:41 time: 0.2598 data_time: 0.0075 memory: 5828 grad_norm: 3.0886 loss: 2.8803 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8803 2023/06/05 07:10:00 - mmengine - INFO - Epoch(train) [78][ 900/2569] lr: 4.0000e-02 eta: 13:46:35 time: 0.2660 data_time: 0.0072 memory: 5828 grad_norm: 3.1488 loss: 2.6798 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6798 2023/06/05 07:10:05 - mmengine - INFO - Epoch(train) [78][ 920/2569] lr: 4.0000e-02 eta: 13:46:30 time: 0.2699 data_time: 0.0075 memory: 5828 grad_norm: 3.0902 loss: 2.7127 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7127 2023/06/05 07:10:10 - mmengine - INFO - Epoch(train) [78][ 940/2569] lr: 4.0000e-02 eta: 13:46:25 time: 0.2573 data_time: 0.0076 memory: 5828 grad_norm: 3.0744 loss: 2.6114 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6114 2023/06/05 07:10:16 - mmengine - INFO - Epoch(train) [78][ 960/2569] lr: 4.0000e-02 eta: 13:46:19 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 3.1816 loss: 2.4970 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4970 2023/06/05 07:10:21 - mmengine - INFO - Epoch(train) [78][ 980/2569] lr: 4.0000e-02 eta: 13:46:14 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 3.1623 loss: 2.3155 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3155 2023/06/05 07:10:26 - mmengine - INFO - Epoch(train) [78][1000/2569] lr: 4.0000e-02 eta: 13:46:09 time: 0.2673 data_time: 0.0077 memory: 5828 grad_norm: 3.1669 loss: 2.3665 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3665 2023/06/05 07:10:31 - mmengine - INFO - Epoch(train) [78][1020/2569] lr: 4.0000e-02 eta: 13:46:03 time: 0.2629 data_time: 0.0077 memory: 5828 grad_norm: 3.1651 loss: 2.5222 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5222 2023/06/05 07:10:37 - mmengine - INFO - Epoch(train) [78][1040/2569] lr: 4.0000e-02 eta: 13:45:58 time: 0.2804 data_time: 0.0070 memory: 5828 grad_norm: 3.1279 loss: 2.2909 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2909 2023/06/05 07:10:42 - mmengine - INFO - Epoch(train) [78][1060/2569] lr: 4.0000e-02 eta: 13:45:53 time: 0.2591 data_time: 0.0075 memory: 5828 grad_norm: 3.1953 loss: 2.7764 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7764 2023/06/05 07:10:48 - mmengine - INFO - Epoch(train) [78][1080/2569] lr: 4.0000e-02 eta: 13:45:48 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 3.0933 loss: 2.5049 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5049 2023/06/05 07:10:53 - mmengine - INFO - Epoch(train) [78][1100/2569] lr: 4.0000e-02 eta: 13:45:42 time: 0.2689 data_time: 0.0074 memory: 5828 grad_norm: 3.1150 loss: 2.6093 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6093 2023/06/05 07:10:58 - mmengine - INFO - Epoch(train) [78][1120/2569] lr: 4.0000e-02 eta: 13:45:37 time: 0.2579 data_time: 0.0076 memory: 5828 grad_norm: 3.1615 loss: 2.3875 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.3875 2023/06/05 07:11:03 - mmengine - INFO - Epoch(train) [78][1140/2569] lr: 4.0000e-02 eta: 13:45:31 time: 0.2644 data_time: 0.0073 memory: 5828 grad_norm: 3.1180 loss: 2.3019 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3019 2023/06/05 07:11:09 - mmengine - INFO - Epoch(train) [78][1160/2569] lr: 4.0000e-02 eta: 13:45:26 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 3.0937 loss: 2.5888 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5888 2023/06/05 07:11:14 - mmengine - INFO - Epoch(train) [78][1180/2569] lr: 4.0000e-02 eta: 13:45:21 time: 0.2589 data_time: 0.0074 memory: 5828 grad_norm: 3.1382 loss: 2.7548 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7548 2023/06/05 07:11:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:11:19 - mmengine - INFO - Epoch(train) [78][1200/2569] lr: 4.0000e-02 eta: 13:45:15 time: 0.2640 data_time: 0.0076 memory: 5828 grad_norm: 3.1738 loss: 2.3736 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3736 2023/06/05 07:11:25 - mmengine - INFO - Epoch(train) [78][1220/2569] lr: 4.0000e-02 eta: 13:45:10 time: 0.2684 data_time: 0.0076 memory: 5828 grad_norm: 3.1318 loss: 2.3274 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3274 2023/06/05 07:11:30 - mmengine - INFO - Epoch(train) [78][1240/2569] lr: 4.0000e-02 eta: 13:45:05 time: 0.2694 data_time: 0.0071 memory: 5828 grad_norm: 3.0916 loss: 2.4560 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4560 2023/06/05 07:11:35 - mmengine - INFO - Epoch(train) [78][1260/2569] lr: 4.0000e-02 eta: 13:44:59 time: 0.2584 data_time: 0.0075 memory: 5828 grad_norm: 3.1809 loss: 2.5053 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5053 2023/06/05 07:11:41 - mmengine - INFO - Epoch(train) [78][1280/2569] lr: 4.0000e-02 eta: 13:44:54 time: 0.2775 data_time: 0.0073 memory: 5828 grad_norm: 3.1650 loss: 2.5166 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5166 2023/06/05 07:11:46 - mmengine - INFO - Epoch(train) [78][1300/2569] lr: 4.0000e-02 eta: 13:44:49 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 3.1091 loss: 2.4400 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4400 2023/06/05 07:11:52 - mmengine - INFO - Epoch(train) [78][1320/2569] lr: 4.0000e-02 eta: 13:44:44 time: 0.2846 data_time: 0.0076 memory: 5828 grad_norm: 3.1561 loss: 2.4618 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4618 2023/06/05 07:11:57 - mmengine - INFO - Epoch(train) [78][1340/2569] lr: 4.0000e-02 eta: 13:44:38 time: 0.2589 data_time: 0.0076 memory: 5828 grad_norm: 3.2000 loss: 2.4797 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4797 2023/06/05 07:12:02 - mmengine - INFO - Epoch(train) [78][1360/2569] lr: 4.0000e-02 eta: 13:44:33 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 3.1368 loss: 2.3431 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3431 2023/06/05 07:12:08 - mmengine - INFO - Epoch(train) [78][1380/2569] lr: 4.0000e-02 eta: 13:44:28 time: 0.2708 data_time: 0.0077 memory: 5828 grad_norm: 3.1649 loss: 2.3737 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3737 2023/06/05 07:12:13 - mmengine - INFO - Epoch(train) [78][1400/2569] lr: 4.0000e-02 eta: 13:44:23 time: 0.2703 data_time: 0.0071 memory: 5828 grad_norm: 3.0885 loss: 2.2759 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2759 2023/06/05 07:12:18 - mmengine - INFO - Epoch(train) [78][1420/2569] lr: 4.0000e-02 eta: 13:44:17 time: 0.2567 data_time: 0.0081 memory: 5828 grad_norm: 3.1718 loss: 2.7611 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7611 2023/06/05 07:12:23 - mmengine - INFO - Epoch(train) [78][1440/2569] lr: 4.0000e-02 eta: 13:44:12 time: 0.2646 data_time: 0.0081 memory: 5828 grad_norm: 3.1102 loss: 2.5511 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5511 2023/06/05 07:12:29 - mmengine - INFO - Epoch(train) [78][1460/2569] lr: 4.0000e-02 eta: 13:44:07 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 3.0990 loss: 2.7308 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7308 2023/06/05 07:12:34 - mmengine - INFO - Epoch(train) [78][1480/2569] lr: 4.0000e-02 eta: 13:44:01 time: 0.2688 data_time: 0.0082 memory: 5828 grad_norm: 3.2124 loss: 2.3991 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3991 2023/06/05 07:12:40 - mmengine - INFO - Epoch(train) [78][1500/2569] lr: 4.0000e-02 eta: 13:43:56 time: 0.2687 data_time: 0.0077 memory: 5828 grad_norm: 3.0862 loss: 2.4456 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4456 2023/06/05 07:12:45 - mmengine - INFO - Epoch(train) [78][1520/2569] lr: 4.0000e-02 eta: 13:43:51 time: 0.2638 data_time: 0.0084 memory: 5828 grad_norm: 3.1764 loss: 2.4968 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4968 2023/06/05 07:12:50 - mmengine - INFO - Epoch(train) [78][1540/2569] lr: 4.0000e-02 eta: 13:43:45 time: 0.2710 data_time: 0.0079 memory: 5828 grad_norm: 3.1096 loss: 2.3870 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3870 2023/06/05 07:12:56 - mmengine - INFO - Epoch(train) [78][1560/2569] lr: 4.0000e-02 eta: 13:43:40 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 3.1889 loss: 2.4412 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4412 2023/06/05 07:13:01 - mmengine - INFO - Epoch(train) [78][1580/2569] lr: 4.0000e-02 eta: 13:43:35 time: 0.2666 data_time: 0.0074 memory: 5828 grad_norm: 3.1494 loss: 2.2689 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2689 2023/06/05 07:13:06 - mmengine - INFO - Epoch(train) [78][1600/2569] lr: 4.0000e-02 eta: 13:43:29 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 3.1629 loss: 2.9082 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.9082 2023/06/05 07:13:11 - mmengine - INFO - Epoch(train) [78][1620/2569] lr: 4.0000e-02 eta: 13:43:24 time: 0.2690 data_time: 0.0072 memory: 5828 grad_norm: 3.1250 loss: 2.7486 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7486 2023/06/05 07:13:17 - mmengine - INFO - Epoch(train) [78][1640/2569] lr: 4.0000e-02 eta: 13:43:19 time: 0.2637 data_time: 0.0074 memory: 5828 grad_norm: 3.0549 loss: 2.6540 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6540 2023/06/05 07:13:22 - mmengine - INFO - Epoch(train) [78][1660/2569] lr: 4.0000e-02 eta: 13:43:14 time: 0.2713 data_time: 0.0073 memory: 5828 grad_norm: 3.0772 loss: 2.4319 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4319 2023/06/05 07:13:27 - mmengine - INFO - Epoch(train) [78][1680/2569] lr: 4.0000e-02 eta: 13:43:08 time: 0.2644 data_time: 0.0075 memory: 5828 grad_norm: 3.1316 loss: 2.8461 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.8461 2023/06/05 07:13:33 - mmengine - INFO - Epoch(train) [78][1700/2569] lr: 4.0000e-02 eta: 13:43:03 time: 0.2587 data_time: 0.0071 memory: 5828 grad_norm: 3.1186 loss: 2.4593 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4593 2023/06/05 07:13:38 - mmengine - INFO - Epoch(train) [78][1720/2569] lr: 4.0000e-02 eta: 13:42:57 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.0615 loss: 2.5317 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5317 2023/06/05 07:13:43 - mmengine - INFO - Epoch(train) [78][1740/2569] lr: 4.0000e-02 eta: 13:42:52 time: 0.2597 data_time: 0.0069 memory: 5828 grad_norm: 3.1237 loss: 2.1534 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1534 2023/06/05 07:13:49 - mmengine - INFO - Epoch(train) [78][1760/2569] lr: 4.0000e-02 eta: 13:42:47 time: 0.2732 data_time: 0.0076 memory: 5828 grad_norm: 3.1202 loss: 2.6301 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6301 2023/06/05 07:13:54 - mmengine - INFO - Epoch(train) [78][1780/2569] lr: 4.0000e-02 eta: 13:42:41 time: 0.2634 data_time: 0.0077 memory: 5828 grad_norm: 3.1633 loss: 2.8470 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8470 2023/06/05 07:13:59 - mmengine - INFO - Epoch(train) [78][1800/2569] lr: 4.0000e-02 eta: 13:42:36 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 3.1115 loss: 2.5112 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5112 2023/06/05 07:14:04 - mmengine - INFO - Epoch(train) [78][1820/2569] lr: 4.0000e-02 eta: 13:42:31 time: 0.2578 data_time: 0.0070 memory: 5828 grad_norm: 3.1158 loss: 2.7882 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7882 2023/06/05 07:14:10 - mmengine - INFO - Epoch(train) [78][1840/2569] lr: 4.0000e-02 eta: 13:42:25 time: 0.2639 data_time: 0.0071 memory: 5828 grad_norm: 3.1303 loss: 2.3498 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3498 2023/06/05 07:14:15 - mmengine - INFO - Epoch(train) [78][1860/2569] lr: 4.0000e-02 eta: 13:42:20 time: 0.2583 data_time: 0.0074 memory: 5828 grad_norm: 3.1096 loss: 2.7381 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7381 2023/06/05 07:14:20 - mmengine - INFO - Epoch(train) [78][1880/2569] lr: 4.0000e-02 eta: 13:42:15 time: 0.2802 data_time: 0.0073 memory: 5828 grad_norm: 3.0749 loss: 2.4403 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4403 2023/06/05 07:14:26 - mmengine - INFO - Epoch(train) [78][1900/2569] lr: 4.0000e-02 eta: 13:42:10 time: 0.2770 data_time: 0.0072 memory: 5828 grad_norm: 3.1589 loss: 2.3791 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3791 2023/06/05 07:14:31 - mmengine - INFO - Epoch(train) [78][1920/2569] lr: 4.0000e-02 eta: 13:42:04 time: 0.2601 data_time: 0.0075 memory: 5828 grad_norm: 3.0922 loss: 2.4591 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4591 2023/06/05 07:14:36 - mmengine - INFO - Epoch(train) [78][1940/2569] lr: 4.0000e-02 eta: 13:41:59 time: 0.2644 data_time: 0.0073 memory: 5828 grad_norm: 3.1520 loss: 2.8943 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8943 2023/06/05 07:14:42 - mmengine - INFO - Epoch(train) [78][1960/2569] lr: 4.0000e-02 eta: 13:41:53 time: 0.2580 data_time: 0.0076 memory: 5828 grad_norm: 3.1130 loss: 2.8362 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8362 2023/06/05 07:14:47 - mmengine - INFO - Epoch(train) [78][1980/2569] lr: 4.0000e-02 eta: 13:41:48 time: 0.2704 data_time: 0.0073 memory: 5828 grad_norm: 3.1026 loss: 2.5495 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5495 2023/06/05 07:14:52 - mmengine - INFO - Epoch(train) [78][2000/2569] lr: 4.0000e-02 eta: 13:41:43 time: 0.2581 data_time: 0.0074 memory: 5828 grad_norm: 3.1091 loss: 2.3462 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3462 2023/06/05 07:14:58 - mmengine - INFO - Epoch(train) [78][2020/2569] lr: 4.0000e-02 eta: 13:41:37 time: 0.2659 data_time: 0.0073 memory: 5828 grad_norm: 3.1220 loss: 2.3625 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3625 2023/06/05 07:15:03 - mmengine - INFO - Epoch(train) [78][2040/2569] lr: 4.0000e-02 eta: 13:41:32 time: 0.2722 data_time: 0.0073 memory: 5828 grad_norm: 3.0964 loss: 2.3379 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3379 2023/06/05 07:15:08 - mmengine - INFO - Epoch(train) [78][2060/2569] lr: 4.0000e-02 eta: 13:41:27 time: 0.2600 data_time: 0.0072 memory: 5828 grad_norm: 3.1982 loss: 2.4234 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4234 2023/06/05 07:15:14 - mmengine - INFO - Epoch(train) [78][2080/2569] lr: 4.0000e-02 eta: 13:41:22 time: 0.2741 data_time: 0.0069 memory: 5828 grad_norm: 3.0966 loss: 2.5880 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5880 2023/06/05 07:15:19 - mmengine - INFO - Epoch(train) [78][2100/2569] lr: 4.0000e-02 eta: 13:41:17 time: 0.2747 data_time: 0.0076 memory: 5828 grad_norm: 3.1411 loss: 2.7847 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7847 2023/06/05 07:15:24 - mmengine - INFO - Epoch(train) [78][2120/2569] lr: 4.0000e-02 eta: 13:41:11 time: 0.2606 data_time: 0.0077 memory: 5828 grad_norm: 3.1470 loss: 2.7187 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7187 2023/06/05 07:15:30 - mmengine - INFO - Epoch(train) [78][2140/2569] lr: 4.0000e-02 eta: 13:41:06 time: 0.2584 data_time: 0.0080 memory: 5828 grad_norm: 3.1493 loss: 2.2722 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2722 2023/06/05 07:15:35 - mmengine - INFO - Epoch(train) [78][2160/2569] lr: 4.0000e-02 eta: 13:41:00 time: 0.2587 data_time: 0.0076 memory: 5828 grad_norm: 3.1828 loss: 2.8677 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8677 2023/06/05 07:15:40 - mmengine - INFO - Epoch(train) [78][2180/2569] lr: 4.0000e-02 eta: 13:40:55 time: 0.2585 data_time: 0.0077 memory: 5828 grad_norm: 3.1323 loss: 2.1541 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1541 2023/06/05 07:15:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:15:45 - mmengine - INFO - Epoch(train) [78][2200/2569] lr: 4.0000e-02 eta: 13:40:50 time: 0.2698 data_time: 0.0075 memory: 5828 grad_norm: 3.1216 loss: 2.5116 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5116 2023/06/05 07:15:51 - mmengine - INFO - Epoch(train) [78][2220/2569] lr: 4.0000e-02 eta: 13:40:44 time: 0.2589 data_time: 0.0079 memory: 5828 grad_norm: 3.0694 loss: 2.7890 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7890 2023/06/05 07:15:56 - mmengine - INFO - Epoch(train) [78][2240/2569] lr: 4.0000e-02 eta: 13:40:39 time: 0.2615 data_time: 0.0071 memory: 5828 grad_norm: 3.1222 loss: 2.3315 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3315 2023/06/05 07:16:01 - mmengine - INFO - Epoch(train) [78][2260/2569] lr: 4.0000e-02 eta: 13:40:33 time: 0.2584 data_time: 0.0073 memory: 5828 grad_norm: 3.1692 loss: 2.4450 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4450 2023/06/05 07:16:06 - mmengine - INFO - Epoch(train) [78][2280/2569] lr: 4.0000e-02 eta: 13:40:28 time: 0.2615 data_time: 0.0069 memory: 5828 grad_norm: 3.1031 loss: 2.4432 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4432 2023/06/05 07:16:11 - mmengine - INFO - Epoch(train) [78][2300/2569] lr: 4.0000e-02 eta: 13:40:22 time: 0.2593 data_time: 0.0074 memory: 5828 grad_norm: 3.1097 loss: 2.9441 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9441 2023/06/05 07:16:17 - mmengine - INFO - Epoch(train) [78][2320/2569] lr: 4.0000e-02 eta: 13:40:17 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.2227 loss: 2.6908 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6908 2023/06/05 07:16:22 - mmengine - INFO - Epoch(train) [78][2340/2569] lr: 4.0000e-02 eta: 13:40:12 time: 0.2711 data_time: 0.0077 memory: 5828 grad_norm: 3.2085 loss: 2.4010 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4010 2023/06/05 07:16:27 - mmengine - INFO - Epoch(train) [78][2360/2569] lr: 4.0000e-02 eta: 13:40:06 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 3.1789 loss: 2.2451 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2451 2023/06/05 07:16:33 - mmengine - INFO - Epoch(train) [78][2380/2569] lr: 4.0000e-02 eta: 13:40:01 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 3.1944 loss: 2.5962 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5962 2023/06/05 07:16:38 - mmengine - INFO - Epoch(train) [78][2400/2569] lr: 4.0000e-02 eta: 13:39:56 time: 0.2783 data_time: 0.0072 memory: 5828 grad_norm: 3.0814 loss: 2.7864 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7864 2023/06/05 07:16:43 - mmengine - INFO - Epoch(train) [78][2420/2569] lr: 4.0000e-02 eta: 13:39:51 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 3.1034 loss: 2.4218 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4218 2023/06/05 07:16:49 - mmengine - INFO - Epoch(train) [78][2440/2569] lr: 4.0000e-02 eta: 13:39:45 time: 0.2613 data_time: 0.0072 memory: 5828 grad_norm: 3.0989 loss: 2.5217 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5217 2023/06/05 07:16:54 - mmengine - INFO - Epoch(train) [78][2460/2569] lr: 4.0000e-02 eta: 13:39:40 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 3.1394 loss: 2.4907 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4907 2023/06/05 07:16:59 - mmengine - INFO - Epoch(train) [78][2480/2569] lr: 4.0000e-02 eta: 13:39:35 time: 0.2587 data_time: 0.0075 memory: 5828 grad_norm: 3.1347 loss: 2.4256 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4256 2023/06/05 07:17:05 - mmengine - INFO - Epoch(train) [78][2500/2569] lr: 4.0000e-02 eta: 13:39:29 time: 0.2743 data_time: 0.0071 memory: 5828 grad_norm: 3.1966 loss: 2.5842 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5842 2023/06/05 07:17:10 - mmengine - INFO - Epoch(train) [78][2520/2569] lr: 4.0000e-02 eta: 13:39:24 time: 0.2640 data_time: 0.0075 memory: 5828 grad_norm: 3.1290 loss: 2.6682 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6682 2023/06/05 07:17:15 - mmengine - INFO - Epoch(train) [78][2540/2569] lr: 4.0000e-02 eta: 13:39:19 time: 0.2588 data_time: 0.0072 memory: 5828 grad_norm: 3.1137 loss: 2.4769 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4769 2023/06/05 07:17:20 - mmengine - INFO - Epoch(train) [78][2560/2569] lr: 4.0000e-02 eta: 13:39:13 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 3.2036 loss: 2.4192 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4192 2023/06/05 07:17:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:17:23 - mmengine - INFO - Epoch(train) [78][2569/2569] lr: 4.0000e-02 eta: 13:39:11 time: 0.2493 data_time: 0.0073 memory: 5828 grad_norm: 3.1659 loss: 2.5736 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.5736 2023/06/05 07:17:29 - mmengine - INFO - Epoch(train) [79][ 20/2569] lr: 4.0000e-02 eta: 13:39:06 time: 0.3272 data_time: 0.0428 memory: 5828 grad_norm: 3.1574 loss: 2.5849 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5849 2023/06/05 07:17:35 - mmengine - INFO - Epoch(train) [79][ 40/2569] lr: 4.0000e-02 eta: 13:39:01 time: 0.2721 data_time: 0.0075 memory: 5828 grad_norm: 3.2195 loss: 2.4778 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4778 2023/06/05 07:17:40 - mmengine - INFO - Epoch(train) [79][ 60/2569] lr: 4.0000e-02 eta: 13:38:56 time: 0.2662 data_time: 0.0075 memory: 5828 grad_norm: 3.0798 loss: 2.8150 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8150 2023/06/05 07:17:45 - mmengine - INFO - Epoch(train) [79][ 80/2569] lr: 4.0000e-02 eta: 13:38:51 time: 0.2757 data_time: 0.0073 memory: 5828 grad_norm: 3.1585 loss: 2.6803 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6803 2023/06/05 07:17:51 - mmengine - INFO - Epoch(train) [79][ 100/2569] lr: 4.0000e-02 eta: 13:38:45 time: 0.2580 data_time: 0.0072 memory: 5828 grad_norm: 3.1160 loss: 2.5482 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5482 2023/06/05 07:17:56 - mmengine - INFO - Epoch(train) [79][ 120/2569] lr: 4.0000e-02 eta: 13:38:40 time: 0.2653 data_time: 0.0075 memory: 5828 grad_norm: 3.0519 loss: 2.6903 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6903 2023/06/05 07:18:01 - mmengine - INFO - Epoch(train) [79][ 140/2569] lr: 4.0000e-02 eta: 13:38:35 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 3.2083 loss: 2.2555 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2555 2023/06/05 07:18:06 - mmengine - INFO - Epoch(train) [79][ 160/2569] lr: 4.0000e-02 eta: 13:38:29 time: 0.2644 data_time: 0.0078 memory: 5828 grad_norm: 3.1482 loss: 2.5909 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5909 2023/06/05 07:18:12 - mmengine - INFO - Epoch(train) [79][ 180/2569] lr: 4.0000e-02 eta: 13:38:24 time: 0.2585 data_time: 0.0078 memory: 5828 grad_norm: 3.1421 loss: 2.4983 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4983 2023/06/05 07:18:17 - mmengine - INFO - Epoch(train) [79][ 200/2569] lr: 4.0000e-02 eta: 13:38:19 time: 0.2695 data_time: 0.0072 memory: 5828 grad_norm: 3.1738 loss: 2.4559 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4559 2023/06/05 07:18:22 - mmengine - INFO - Epoch(train) [79][ 220/2569] lr: 4.0000e-02 eta: 13:38:13 time: 0.2582 data_time: 0.0074 memory: 5828 grad_norm: 3.1363 loss: 2.5689 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5689 2023/06/05 07:18:28 - mmengine - INFO - Epoch(train) [79][ 240/2569] lr: 4.0000e-02 eta: 13:38:08 time: 0.2640 data_time: 0.0072 memory: 5828 grad_norm: 3.1790 loss: 2.7660 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7660 2023/06/05 07:18:33 - mmengine - INFO - Epoch(train) [79][ 260/2569] lr: 4.0000e-02 eta: 13:38:02 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 3.1676 loss: 2.5511 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5511 2023/06/05 07:18:38 - mmengine - INFO - Epoch(train) [79][ 280/2569] lr: 4.0000e-02 eta: 13:37:57 time: 0.2578 data_time: 0.0074 memory: 5828 grad_norm: 3.1771 loss: 2.3349 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3349 2023/06/05 07:18:43 - mmengine - INFO - Epoch(train) [79][ 300/2569] lr: 4.0000e-02 eta: 13:37:52 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.1330 loss: 2.4476 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4476 2023/06/05 07:18:48 - mmengine - INFO - Epoch(train) [79][ 320/2569] lr: 4.0000e-02 eta: 13:37:46 time: 0.2590 data_time: 0.0073 memory: 5828 grad_norm: 3.1099 loss: 2.6514 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6514 2023/06/05 07:18:54 - mmengine - INFO - Epoch(train) [79][ 340/2569] lr: 4.0000e-02 eta: 13:37:41 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 3.1242 loss: 2.6445 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6445 2023/06/05 07:18:59 - mmengine - INFO - Epoch(train) [79][ 360/2569] lr: 4.0000e-02 eta: 13:37:36 time: 0.2704 data_time: 0.0070 memory: 5828 grad_norm: 3.1378 loss: 2.3443 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3443 2023/06/05 07:19:05 - mmengine - INFO - Epoch(train) [79][ 380/2569] lr: 4.0000e-02 eta: 13:37:31 time: 0.2763 data_time: 0.0072 memory: 5828 grad_norm: 3.1245 loss: 2.3912 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3912 2023/06/05 07:19:10 - mmengine - INFO - Epoch(train) [79][ 400/2569] lr: 4.0000e-02 eta: 13:37:25 time: 0.2593 data_time: 0.0073 memory: 5828 grad_norm: 3.1316 loss: 2.4933 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4933 2023/06/05 07:19:15 - mmengine - INFO - Epoch(train) [79][ 420/2569] lr: 4.0000e-02 eta: 13:37:20 time: 0.2754 data_time: 0.0073 memory: 5828 grad_norm: 3.1801 loss: 2.5276 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5276 2023/06/05 07:19:21 - mmengine - INFO - Epoch(train) [79][ 440/2569] lr: 4.0000e-02 eta: 13:37:15 time: 0.2654 data_time: 0.0074 memory: 5828 grad_norm: 3.2138 loss: 2.2762 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.2762 2023/06/05 07:19:26 - mmengine - INFO - Epoch(train) [79][ 460/2569] lr: 4.0000e-02 eta: 13:37:09 time: 0.2710 data_time: 0.0072 memory: 5828 grad_norm: 3.1146 loss: 2.4814 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4814 2023/06/05 07:19:31 - mmengine - INFO - Epoch(train) [79][ 480/2569] lr: 4.0000e-02 eta: 13:37:04 time: 0.2582 data_time: 0.0070 memory: 5828 grad_norm: 3.1319 loss: 2.5383 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5383 2023/06/05 07:19:37 - mmengine - INFO - Epoch(train) [79][ 500/2569] lr: 4.0000e-02 eta: 13:36:59 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 3.1258 loss: 2.3989 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.3989 2023/06/05 07:19:42 - mmengine - INFO - Epoch(train) [79][ 520/2569] lr: 4.0000e-02 eta: 13:36:53 time: 0.2612 data_time: 0.0074 memory: 5828 grad_norm: 3.1882 loss: 2.5830 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5830 2023/06/05 07:19:47 - mmengine - INFO - Epoch(train) [79][ 540/2569] lr: 4.0000e-02 eta: 13:36:48 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 3.1227 loss: 2.4048 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4048 2023/06/05 07:19:53 - mmengine - INFO - Epoch(train) [79][ 560/2569] lr: 4.0000e-02 eta: 13:36:43 time: 0.2693 data_time: 0.0077 memory: 5828 grad_norm: 3.1472 loss: 2.3565 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3565 2023/06/05 07:19:58 - mmengine - INFO - Epoch(train) [79][ 580/2569] lr: 4.0000e-02 eta: 13:36:37 time: 0.2633 data_time: 0.0077 memory: 5828 grad_norm: 3.1518 loss: 2.4203 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4203 2023/06/05 07:20:03 - mmengine - INFO - Epoch(train) [79][ 600/2569] lr: 4.0000e-02 eta: 13:36:32 time: 0.2681 data_time: 0.0073 memory: 5828 grad_norm: 3.1304 loss: 2.3016 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3016 2023/06/05 07:20:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:20:09 - mmengine - INFO - Epoch(train) [79][ 620/2569] lr: 4.0000e-02 eta: 13:36:27 time: 0.2700 data_time: 0.0073 memory: 5828 grad_norm: 3.1927 loss: 3.0818 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 3.0818 2023/06/05 07:20:14 - mmengine - INFO - Epoch(train) [79][ 640/2569] lr: 4.0000e-02 eta: 13:36:21 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 3.1325 loss: 2.6533 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6533 2023/06/05 07:20:19 - mmengine - INFO - Epoch(train) [79][ 660/2569] lr: 4.0000e-02 eta: 13:36:16 time: 0.2667 data_time: 0.0071 memory: 5828 grad_norm: 3.1212 loss: 2.5892 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5892 2023/06/05 07:20:24 - mmengine - INFO - Epoch(train) [79][ 680/2569] lr: 4.0000e-02 eta: 13:36:11 time: 0.2624 data_time: 0.0080 memory: 5828 grad_norm: 3.1481 loss: 2.7704 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7704 2023/06/05 07:20:30 - mmengine - INFO - Epoch(train) [79][ 700/2569] lr: 4.0000e-02 eta: 13:36:06 time: 0.2665 data_time: 0.0072 memory: 5828 grad_norm: 3.0805 loss: 2.7731 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7731 2023/06/05 07:20:35 - mmengine - INFO - Epoch(train) [79][ 720/2569] lr: 4.0000e-02 eta: 13:36:00 time: 0.2709 data_time: 0.0095 memory: 5828 grad_norm: 3.1403 loss: 2.8095 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8095 2023/06/05 07:20:41 - mmengine - INFO - Epoch(train) [79][ 740/2569] lr: 4.0000e-02 eta: 13:35:55 time: 0.2635 data_time: 0.0075 memory: 5828 grad_norm: 3.1440 loss: 2.5193 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5193 2023/06/05 07:20:46 - mmengine - INFO - Epoch(train) [79][ 760/2569] lr: 4.0000e-02 eta: 13:35:49 time: 0.2588 data_time: 0.0076 memory: 5828 grad_norm: 3.1456 loss: 2.7591 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7591 2023/06/05 07:20:51 - mmengine - INFO - Epoch(train) [79][ 780/2569] lr: 4.0000e-02 eta: 13:35:44 time: 0.2695 data_time: 0.0085 memory: 5828 grad_norm: 3.1560 loss: 2.3727 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3727 2023/06/05 07:20:56 - mmengine - INFO - Epoch(train) [79][ 800/2569] lr: 4.0000e-02 eta: 13:35:39 time: 0.2597 data_time: 0.0073 memory: 5828 grad_norm: 3.0608 loss: 2.3035 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3035 2023/06/05 07:21:02 - mmengine - INFO - Epoch(train) [79][ 820/2569] lr: 4.0000e-02 eta: 13:35:34 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 3.1547 loss: 2.2550 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2550 2023/06/05 07:21:07 - mmengine - INFO - Epoch(train) [79][ 840/2569] lr: 4.0000e-02 eta: 13:35:28 time: 0.2598 data_time: 0.0074 memory: 5828 grad_norm: 3.1125 loss: 2.4436 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4436 2023/06/05 07:21:12 - mmengine - INFO - Epoch(train) [79][ 860/2569] lr: 4.0000e-02 eta: 13:35:23 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 3.1368 loss: 2.7221 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.7221 2023/06/05 07:21:17 - mmengine - INFO - Epoch(train) [79][ 880/2569] lr: 4.0000e-02 eta: 13:35:17 time: 0.2678 data_time: 0.0073 memory: 5828 grad_norm: 3.1147 loss: 2.3126 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3126 2023/06/05 07:21:23 - mmengine - INFO - Epoch(train) [79][ 900/2569] lr: 4.0000e-02 eta: 13:35:12 time: 0.2623 data_time: 0.0077 memory: 5828 grad_norm: 3.0695 loss: 2.1435 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1435 2023/06/05 07:21:28 - mmengine - INFO - Epoch(train) [79][ 920/2569] lr: 4.0000e-02 eta: 13:35:07 time: 0.2596 data_time: 0.0078 memory: 5828 grad_norm: 3.0522 loss: 2.2959 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2959 2023/06/05 07:21:33 - mmengine - INFO - Epoch(train) [79][ 940/2569] lr: 4.0000e-02 eta: 13:35:01 time: 0.2589 data_time: 0.0074 memory: 5828 grad_norm: 3.1592 loss: 2.5937 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5937 2023/06/05 07:21:38 - mmengine - INFO - Epoch(train) [79][ 960/2569] lr: 4.0000e-02 eta: 13:34:56 time: 0.2665 data_time: 0.0078 memory: 5828 grad_norm: 3.0632 loss: 2.5209 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5209 2023/06/05 07:21:44 - mmengine - INFO - Epoch(train) [79][ 980/2569] lr: 4.0000e-02 eta: 13:34:50 time: 0.2584 data_time: 0.0075 memory: 5828 grad_norm: 3.1366 loss: 2.2160 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.2160 2023/06/05 07:21:49 - mmengine - INFO - Epoch(train) [79][1000/2569] lr: 4.0000e-02 eta: 13:34:45 time: 0.2601 data_time: 0.0072 memory: 5828 grad_norm: 3.0975 loss: 2.5132 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5132 2023/06/05 07:21:54 - mmengine - INFO - Epoch(train) [79][1020/2569] lr: 4.0000e-02 eta: 13:34:40 time: 0.2696 data_time: 0.0076 memory: 5828 grad_norm: 3.0320 loss: 2.4014 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4014 2023/06/05 07:22:00 - mmengine - INFO - Epoch(train) [79][1040/2569] lr: 4.0000e-02 eta: 13:34:34 time: 0.2649 data_time: 0.0079 memory: 5828 grad_norm: 3.1533 loss: 2.5720 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5720 2023/06/05 07:22:05 - mmengine - INFO - Epoch(train) [79][1060/2569] lr: 4.0000e-02 eta: 13:34:29 time: 0.2685 data_time: 0.0070 memory: 5828 grad_norm: 3.1465 loss: 2.5225 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5225 2023/06/05 07:22:10 - mmengine - INFO - Epoch(train) [79][1080/2569] lr: 4.0000e-02 eta: 13:34:24 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 3.1546 loss: 2.6574 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6574 2023/06/05 07:22:16 - mmengine - INFO - Epoch(train) [79][1100/2569] lr: 4.0000e-02 eta: 13:34:19 time: 0.2749 data_time: 0.0074 memory: 5828 grad_norm: 3.1640 loss: 2.2393 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2393 2023/06/05 07:22:21 - mmengine - INFO - Epoch(train) [79][1120/2569] lr: 4.0000e-02 eta: 13:34:13 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.1289 loss: 2.4306 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4306 2023/06/05 07:22:26 - mmengine - INFO - Epoch(train) [79][1140/2569] lr: 4.0000e-02 eta: 13:34:08 time: 0.2714 data_time: 0.0077 memory: 5828 grad_norm: 3.1814 loss: 2.5111 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5111 2023/06/05 07:22:32 - mmengine - INFO - Epoch(train) [79][1160/2569] lr: 4.0000e-02 eta: 13:34:03 time: 0.2630 data_time: 0.0069 memory: 5828 grad_norm: 3.1101 loss: 2.2679 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2679 2023/06/05 07:22:37 - mmengine - INFO - Epoch(train) [79][1180/2569] lr: 4.0000e-02 eta: 13:33:58 time: 0.2720 data_time: 0.0072 memory: 5828 grad_norm: 3.1971 loss: 2.4274 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4274 2023/06/05 07:22:42 - mmengine - INFO - Epoch(train) [79][1200/2569] lr: 4.0000e-02 eta: 13:33:52 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 3.1454 loss: 2.4509 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4509 2023/06/05 07:22:48 - mmengine - INFO - Epoch(train) [79][1220/2569] lr: 4.0000e-02 eta: 13:33:47 time: 0.2593 data_time: 0.0071 memory: 5828 grad_norm: 3.1456 loss: 2.3824 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3824 2023/06/05 07:22:53 - mmengine - INFO - Epoch(train) [79][1240/2569] lr: 4.0000e-02 eta: 13:33:41 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 3.0922 loss: 2.8999 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8999 2023/06/05 07:22:58 - mmengine - INFO - Epoch(train) [79][1260/2569] lr: 4.0000e-02 eta: 13:33:36 time: 0.2644 data_time: 0.0073 memory: 5828 grad_norm: 3.1080 loss: 2.5959 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5959 2023/06/05 07:23:04 - mmengine - INFO - Epoch(train) [79][1280/2569] lr: 4.0000e-02 eta: 13:33:31 time: 0.2722 data_time: 0.0073 memory: 5828 grad_norm: 3.1223 loss: 2.5421 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5421 2023/06/05 07:23:09 - mmengine - INFO - Epoch(train) [79][1300/2569] lr: 4.0000e-02 eta: 13:33:26 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 3.1690 loss: 2.6259 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6259 2023/06/05 07:23:14 - mmengine - INFO - Epoch(train) [79][1320/2569] lr: 4.0000e-02 eta: 13:33:20 time: 0.2680 data_time: 0.0094 memory: 5828 grad_norm: 3.1342 loss: 2.6585 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6585 2023/06/05 07:23:19 - mmengine - INFO - Epoch(train) [79][1340/2569] lr: 4.0000e-02 eta: 13:33:15 time: 0.2606 data_time: 0.0080 memory: 5828 grad_norm: 3.1797 loss: 2.5395 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5395 2023/06/05 07:23:25 - mmengine - INFO - Epoch(train) [79][1360/2569] lr: 4.0000e-02 eta: 13:33:10 time: 0.2690 data_time: 0.0074 memory: 5828 grad_norm: 3.0961 loss: 2.4925 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4925 2023/06/05 07:23:30 - mmengine - INFO - Epoch(train) [79][1380/2569] lr: 4.0000e-02 eta: 13:33:04 time: 0.2742 data_time: 0.0072 memory: 5828 grad_norm: 3.0903 loss: 2.7966 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7966 2023/06/05 07:23:36 - mmengine - INFO - Epoch(train) [79][1400/2569] lr: 4.0000e-02 eta: 13:32:59 time: 0.2585 data_time: 0.0074 memory: 5828 grad_norm: 3.1181 loss: 2.5786 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5786 2023/06/05 07:23:41 - mmengine - INFO - Epoch(train) [79][1420/2569] lr: 4.0000e-02 eta: 13:32:54 time: 0.2570 data_time: 0.0071 memory: 5828 grad_norm: 3.0417 loss: 2.7048 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7048 2023/06/05 07:23:46 - mmengine - INFO - Epoch(train) [79][1440/2569] lr: 4.0000e-02 eta: 13:32:48 time: 0.2638 data_time: 0.0077 memory: 5828 grad_norm: 3.1046 loss: 2.5960 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5960 2023/06/05 07:23:51 - mmengine - INFO - Epoch(train) [79][1460/2569] lr: 4.0000e-02 eta: 13:32:43 time: 0.2576 data_time: 0.0074 memory: 5828 grad_norm: 3.1316 loss: 2.6987 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6987 2023/06/05 07:23:56 - mmengine - INFO - Epoch(train) [79][1480/2569] lr: 4.0000e-02 eta: 13:32:37 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 3.0762 loss: 2.5681 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5681 2023/06/05 07:24:02 - mmengine - INFO - Epoch(train) [79][1500/2569] lr: 4.0000e-02 eta: 13:32:32 time: 0.2585 data_time: 0.0073 memory: 5828 grad_norm: 3.1372 loss: 2.2840 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.2840 2023/06/05 07:24:07 - mmengine - INFO - Epoch(train) [79][1520/2569] lr: 4.0000e-02 eta: 13:32:26 time: 0.2592 data_time: 0.0075 memory: 5828 grad_norm: 3.1106 loss: 2.4129 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4129 2023/06/05 07:24:12 - mmengine - INFO - Epoch(train) [79][1540/2569] lr: 4.0000e-02 eta: 13:32:21 time: 0.2586 data_time: 0.0068 memory: 5828 grad_norm: 3.0989 loss: 2.5865 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5865 2023/06/05 07:24:18 - mmengine - INFO - Epoch(train) [79][1560/2569] lr: 4.0000e-02 eta: 13:32:16 time: 0.2830 data_time: 0.0073 memory: 5828 grad_norm: 3.1417 loss: 2.3445 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3445 2023/06/05 07:24:23 - mmengine - INFO - Epoch(train) [79][1580/2569] lr: 4.0000e-02 eta: 13:32:11 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 3.1359 loss: 2.4672 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4672 2023/06/05 07:24:28 - mmengine - INFO - Epoch(train) [79][1600/2569] lr: 4.0000e-02 eta: 13:32:05 time: 0.2753 data_time: 0.0075 memory: 5828 grad_norm: 3.1445 loss: 2.3083 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3083 2023/06/05 07:24:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:24:34 - mmengine - INFO - Epoch(train) [79][1620/2569] lr: 4.0000e-02 eta: 13:32:00 time: 0.2583 data_time: 0.0078 memory: 5828 grad_norm: 3.1568 loss: 2.6022 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6022 2023/06/05 07:24:39 - mmengine - INFO - Epoch(train) [79][1640/2569] lr: 4.0000e-02 eta: 13:31:55 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 3.1199 loss: 2.1897 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1897 2023/06/05 07:24:44 - mmengine - INFO - Epoch(train) [79][1660/2569] lr: 4.0000e-02 eta: 13:31:49 time: 0.2684 data_time: 0.0074 memory: 5828 grad_norm: 3.1514 loss: 2.5104 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5104 2023/06/05 07:24:49 - mmengine - INFO - Epoch(train) [79][1680/2569] lr: 4.0000e-02 eta: 13:31:44 time: 0.2622 data_time: 0.0078 memory: 5828 grad_norm: 3.1028 loss: 2.4551 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4551 2023/06/05 07:24:55 - mmengine - INFO - Epoch(train) [79][1700/2569] lr: 4.0000e-02 eta: 13:31:39 time: 0.2635 data_time: 0.0085 memory: 5828 grad_norm: 3.1184 loss: 2.6810 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6810 2023/06/05 07:25:00 - mmengine - INFO - Epoch(train) [79][1720/2569] lr: 4.0000e-02 eta: 13:31:33 time: 0.2690 data_time: 0.0072 memory: 5828 grad_norm: 3.1362 loss: 2.3488 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3488 2023/06/05 07:25:05 - mmengine - INFO - Epoch(train) [79][1740/2569] lr: 4.0000e-02 eta: 13:31:28 time: 0.2675 data_time: 0.0071 memory: 5828 grad_norm: 3.1921 loss: 2.5927 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5927 2023/06/05 07:25:11 - mmengine - INFO - Epoch(train) [79][1760/2569] lr: 4.0000e-02 eta: 13:31:23 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 3.1069 loss: 2.3278 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3278 2023/06/05 07:25:16 - mmengine - INFO - Epoch(train) [79][1780/2569] lr: 4.0000e-02 eta: 13:31:18 time: 0.2714 data_time: 0.0072 memory: 5828 grad_norm: 3.1496 loss: 2.7794 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7794 2023/06/05 07:25:22 - mmengine - INFO - Epoch(train) [79][1800/2569] lr: 4.0000e-02 eta: 13:31:12 time: 0.2729 data_time: 0.0073 memory: 5828 grad_norm: 3.0078 loss: 2.5515 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5515 2023/06/05 07:25:27 - mmengine - INFO - Epoch(train) [79][1820/2569] lr: 4.0000e-02 eta: 13:31:07 time: 0.2644 data_time: 0.0069 memory: 5828 grad_norm: 3.0948 loss: 2.6466 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6466 2023/06/05 07:25:32 - mmengine - INFO - Epoch(train) [79][1840/2569] lr: 4.0000e-02 eta: 13:31:02 time: 0.2734 data_time: 0.0072 memory: 5828 grad_norm: 3.1612 loss: 2.7415 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7415 2023/06/05 07:25:38 - mmengine - INFO - Epoch(train) [79][1860/2569] lr: 4.0000e-02 eta: 13:30:57 time: 0.2632 data_time: 0.0068 memory: 5828 grad_norm: 3.2373 loss: 2.6792 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6792 2023/06/05 07:25:43 - mmengine - INFO - Epoch(train) [79][1880/2569] lr: 4.0000e-02 eta: 13:30:51 time: 0.2688 data_time: 0.0072 memory: 5828 grad_norm: 3.0487 loss: 2.8152 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8152 2023/06/05 07:25:48 - mmengine - INFO - Epoch(train) [79][1900/2569] lr: 4.0000e-02 eta: 13:30:46 time: 0.2689 data_time: 0.0070 memory: 5828 grad_norm: 3.1203 loss: 2.5738 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5738 2023/06/05 07:25:54 - mmengine - INFO - Epoch(train) [79][1920/2569] lr: 4.0000e-02 eta: 13:30:41 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 3.1033 loss: 2.3895 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3895 2023/06/05 07:25:59 - mmengine - INFO - Epoch(train) [79][1940/2569] lr: 4.0000e-02 eta: 13:30:35 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.1177 loss: 2.1001 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1001 2023/06/05 07:26:04 - mmengine - INFO - Epoch(train) [79][1960/2569] lr: 4.0000e-02 eta: 13:30:30 time: 0.2628 data_time: 0.0074 memory: 5828 grad_norm: 3.1331 loss: 2.1659 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1659 2023/06/05 07:26:10 - mmengine - INFO - Epoch(train) [79][1980/2569] lr: 4.0000e-02 eta: 13:30:25 time: 0.2653 data_time: 0.0097 memory: 5828 grad_norm: 3.0665 loss: 2.4432 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4432 2023/06/05 07:26:15 - mmengine - INFO - Epoch(train) [79][2000/2569] lr: 4.0000e-02 eta: 13:30:19 time: 0.2667 data_time: 0.0086 memory: 5828 grad_norm: 3.1542 loss: 2.3580 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3580 2023/06/05 07:26:20 - mmengine - INFO - Epoch(train) [79][2020/2569] lr: 4.0000e-02 eta: 13:30:14 time: 0.2582 data_time: 0.0072 memory: 5828 grad_norm: 3.1694 loss: 2.3198 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3198 2023/06/05 07:26:25 - mmengine - INFO - Epoch(train) [79][2040/2569] lr: 4.0000e-02 eta: 13:30:09 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 3.2161 loss: 2.6165 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6165 2023/06/05 07:26:31 - mmengine - INFO - Epoch(train) [79][2060/2569] lr: 4.0000e-02 eta: 13:30:03 time: 0.2708 data_time: 0.0077 memory: 5828 grad_norm: 3.1074 loss: 2.2863 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2863 2023/06/05 07:26:36 - mmengine - INFO - Epoch(train) [79][2080/2569] lr: 4.0000e-02 eta: 13:29:58 time: 0.2691 data_time: 0.0073 memory: 5828 grad_norm: 3.0946 loss: 2.6476 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6476 2023/06/05 07:26:42 - mmengine - INFO - Epoch(train) [79][2100/2569] lr: 4.0000e-02 eta: 13:29:53 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 3.1216 loss: 2.5892 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5892 2023/06/05 07:26:47 - mmengine - INFO - Epoch(train) [79][2120/2569] lr: 4.0000e-02 eta: 13:29:48 time: 0.2720 data_time: 0.0077 memory: 5828 grad_norm: 3.1472 loss: 2.4763 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4763 2023/06/05 07:26:52 - mmengine - INFO - Epoch(train) [79][2140/2569] lr: 4.0000e-02 eta: 13:29:42 time: 0.2646 data_time: 0.0077 memory: 5828 grad_norm: 3.0933 loss: 2.3015 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3015 2023/06/05 07:26:58 - mmengine - INFO - Epoch(train) [79][2160/2569] lr: 4.0000e-02 eta: 13:29:37 time: 0.2592 data_time: 0.0076 memory: 5828 grad_norm: 3.1188 loss: 2.5386 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5386 2023/06/05 07:27:03 - mmengine - INFO - Epoch(train) [79][2180/2569] lr: 4.0000e-02 eta: 13:29:32 time: 0.2667 data_time: 0.0076 memory: 5828 grad_norm: 3.0956 loss: 2.4036 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4036 2023/06/05 07:27:08 - mmengine - INFO - Epoch(train) [79][2200/2569] lr: 4.0000e-02 eta: 13:29:26 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 3.1178 loss: 2.2935 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2935 2023/06/05 07:27:13 - mmengine - INFO - Epoch(train) [79][2220/2569] lr: 4.0000e-02 eta: 13:29:21 time: 0.2583 data_time: 0.0074 memory: 5828 grad_norm: 3.1583 loss: 2.5852 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5852 2023/06/05 07:27:19 - mmengine - INFO - Epoch(train) [79][2240/2569] lr: 4.0000e-02 eta: 13:29:16 time: 0.2741 data_time: 0.0070 memory: 5828 grad_norm: 3.1491 loss: 2.4802 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4802 2023/06/05 07:27:24 - mmengine - INFO - Epoch(train) [79][2260/2569] lr: 4.0000e-02 eta: 13:29:10 time: 0.2668 data_time: 0.0077 memory: 5828 grad_norm: 3.1250 loss: 2.3885 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3885 2023/06/05 07:27:30 - mmengine - INFO - Epoch(train) [79][2280/2569] lr: 4.0000e-02 eta: 13:29:05 time: 0.2699 data_time: 0.0074 memory: 5828 grad_norm: 3.0963 loss: 2.6881 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6881 2023/06/05 07:27:35 - mmengine - INFO - Epoch(train) [79][2300/2569] lr: 4.0000e-02 eta: 13:29:00 time: 0.2752 data_time: 0.0072 memory: 5828 grad_norm: 3.0960 loss: 2.4596 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4596 2023/06/05 07:27:40 - mmengine - INFO - Epoch(train) [79][2320/2569] lr: 4.0000e-02 eta: 13:28:54 time: 0.2579 data_time: 0.0073 memory: 5828 grad_norm: 3.1406 loss: 2.4100 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4100 2023/06/05 07:27:46 - mmengine - INFO - Epoch(train) [79][2340/2569] lr: 4.0000e-02 eta: 13:28:49 time: 0.2730 data_time: 0.0080 memory: 5828 grad_norm: 3.1714 loss: 2.4850 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4850 2023/06/05 07:27:51 - mmengine - INFO - Epoch(train) [79][2360/2569] lr: 4.0000e-02 eta: 13:28:44 time: 0.2586 data_time: 0.0080 memory: 5828 grad_norm: 3.1363 loss: 2.4907 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4907 2023/06/05 07:27:56 - mmengine - INFO - Epoch(train) [79][2380/2569] lr: 4.0000e-02 eta: 13:28:39 time: 0.2645 data_time: 0.0078 memory: 5828 grad_norm: 3.1339 loss: 2.7074 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7074 2023/06/05 07:28:02 - mmengine - INFO - Epoch(train) [79][2400/2569] lr: 4.0000e-02 eta: 13:28:33 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 3.1968 loss: 2.6345 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6345 2023/06/05 07:28:07 - mmengine - INFO - Epoch(train) [79][2420/2569] lr: 4.0000e-02 eta: 13:28:28 time: 0.2636 data_time: 0.0081 memory: 5828 grad_norm: 3.1080 loss: 2.5293 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5293 2023/06/05 07:28:12 - mmengine - INFO - Epoch(train) [79][2440/2569] lr: 4.0000e-02 eta: 13:28:23 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 3.0770 loss: 2.3196 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3196 2023/06/05 07:28:18 - mmengine - INFO - Epoch(train) [79][2460/2569] lr: 4.0000e-02 eta: 13:28:17 time: 0.2706 data_time: 0.0073 memory: 5828 grad_norm: 3.2195 loss: 2.4617 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4617 2023/06/05 07:28:23 - mmengine - INFO - Epoch(train) [79][2480/2569] lr: 4.0000e-02 eta: 13:28:12 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 3.0550 loss: 2.5004 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5004 2023/06/05 07:28:28 - mmengine - INFO - Epoch(train) [79][2500/2569] lr: 4.0000e-02 eta: 13:28:07 time: 0.2629 data_time: 0.0069 memory: 5828 grad_norm: 3.1548 loss: 2.6285 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6285 2023/06/05 07:28:33 - mmengine - INFO - Epoch(train) [79][2520/2569] lr: 4.0000e-02 eta: 13:28:01 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 3.1441 loss: 2.3279 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.3279 2023/06/05 07:28:39 - mmengine - INFO - Epoch(train) [79][2540/2569] lr: 4.0000e-02 eta: 13:27:56 time: 0.2607 data_time: 0.0074 memory: 5828 grad_norm: 3.1588 loss: 2.3622 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3622 2023/06/05 07:28:44 - mmengine - INFO - Epoch(train) [79][2560/2569] lr: 4.0000e-02 eta: 13:27:50 time: 0.2567 data_time: 0.0075 memory: 5828 grad_norm: 3.1320 loss: 2.1083 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1083 2023/06/05 07:28:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:28:46 - mmengine - INFO - Epoch(train) [79][2569/2569] lr: 4.0000e-02 eta: 13:27:48 time: 0.2569 data_time: 0.0072 memory: 5828 grad_norm: 3.1742 loss: 2.4867 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4867 2023/06/05 07:28:53 - mmengine - INFO - Epoch(train) [80][ 20/2569] lr: 4.0000e-02 eta: 13:27:44 time: 0.3412 data_time: 0.0539 memory: 5828 grad_norm: 3.1615 loss: 2.3498 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3498 2023/06/05 07:28:58 - mmengine - INFO - Epoch(train) [80][ 40/2569] lr: 4.0000e-02 eta: 13:27:39 time: 0.2711 data_time: 0.0074 memory: 5828 grad_norm: 3.0824 loss: 2.3694 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3694 2023/06/05 07:29:01 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:29:04 - mmengine - INFO - Epoch(train) [80][ 60/2569] lr: 4.0000e-02 eta: 13:27:33 time: 0.2597 data_time: 0.0072 memory: 5828 grad_norm: 3.1447 loss: 2.5070 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5070 2023/06/05 07:29:09 - mmengine - INFO - Epoch(train) [80][ 80/2569] lr: 4.0000e-02 eta: 13:27:28 time: 0.2769 data_time: 0.0075 memory: 5828 grad_norm: 3.1538 loss: 2.4540 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4540 2023/06/05 07:29:14 - mmengine - INFO - Epoch(train) [80][ 100/2569] lr: 4.0000e-02 eta: 13:27:23 time: 0.2645 data_time: 0.0080 memory: 5828 grad_norm: 3.1113 loss: 2.4405 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4405 2023/06/05 07:29:20 - mmengine - INFO - Epoch(train) [80][ 120/2569] lr: 4.0000e-02 eta: 13:27:17 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 3.1193 loss: 2.2736 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2736 2023/06/05 07:29:25 - mmengine - INFO - Epoch(train) [80][ 140/2569] lr: 4.0000e-02 eta: 13:27:12 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 3.1105 loss: 2.6557 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6557 2023/06/05 07:29:30 - mmengine - INFO - Epoch(train) [80][ 160/2569] lr: 4.0000e-02 eta: 13:27:07 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 3.2035 loss: 2.7735 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.7735 2023/06/05 07:29:36 - mmengine - INFO - Epoch(train) [80][ 180/2569] lr: 4.0000e-02 eta: 13:27:02 time: 0.2694 data_time: 0.0073 memory: 5828 grad_norm: 3.2139 loss: 2.6868 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6868 2023/06/05 07:29:41 - mmengine - INFO - Epoch(train) [80][ 200/2569] lr: 4.0000e-02 eta: 13:26:56 time: 0.2663 data_time: 0.0070 memory: 5828 grad_norm: 3.1762 loss: 2.4614 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4614 2023/06/05 07:29:46 - mmengine - INFO - Epoch(train) [80][ 220/2569] lr: 4.0000e-02 eta: 13:26:51 time: 0.2580 data_time: 0.0076 memory: 5828 grad_norm: 3.0854 loss: 2.4097 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4097 2023/06/05 07:29:52 - mmengine - INFO - Epoch(train) [80][ 240/2569] lr: 4.0000e-02 eta: 13:26:46 time: 0.2766 data_time: 0.0077 memory: 5828 grad_norm: 3.1369 loss: 2.5070 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5070 2023/06/05 07:29:57 - mmengine - INFO - Epoch(train) [80][ 260/2569] lr: 4.0000e-02 eta: 13:26:40 time: 0.2600 data_time: 0.0075 memory: 5828 grad_norm: 3.1408 loss: 2.6427 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6427 2023/06/05 07:30:02 - mmengine - INFO - Epoch(train) [80][ 280/2569] lr: 4.0000e-02 eta: 13:26:35 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 3.1329 loss: 2.3583 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3583 2023/06/05 07:30:08 - mmengine - INFO - Epoch(train) [80][ 300/2569] lr: 4.0000e-02 eta: 13:26:30 time: 0.2592 data_time: 0.0072 memory: 5828 grad_norm: 3.1157 loss: 2.3939 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3939 2023/06/05 07:30:13 - mmengine - INFO - Epoch(train) [80][ 320/2569] lr: 4.0000e-02 eta: 13:26:24 time: 0.2667 data_time: 0.0079 memory: 5828 grad_norm: 3.1779 loss: 2.5505 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5505 2023/06/05 07:30:18 - mmengine - INFO - Epoch(train) [80][ 340/2569] lr: 4.0000e-02 eta: 13:26:19 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 3.1305 loss: 2.7388 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7388 2023/06/05 07:30:24 - mmengine - INFO - Epoch(train) [80][ 360/2569] lr: 4.0000e-02 eta: 13:26:14 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 3.1029 loss: 2.2000 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2000 2023/06/05 07:30:29 - mmengine - INFO - Epoch(train) [80][ 380/2569] lr: 4.0000e-02 eta: 13:26:08 time: 0.2585 data_time: 0.0071 memory: 5828 grad_norm: 3.0989 loss: 2.4830 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4830 2023/06/05 07:30:34 - mmengine - INFO - Epoch(train) [80][ 400/2569] lr: 4.0000e-02 eta: 13:26:03 time: 0.2738 data_time: 0.0072 memory: 5828 grad_norm: 3.0824 loss: 2.6407 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6407 2023/06/05 07:30:40 - mmengine - INFO - Epoch(train) [80][ 420/2569] lr: 4.0000e-02 eta: 13:25:58 time: 0.2665 data_time: 0.0078 memory: 5828 grad_norm: 3.2236 loss: 2.2182 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2182 2023/06/05 07:30:45 - mmengine - INFO - Epoch(train) [80][ 440/2569] lr: 4.0000e-02 eta: 13:25:52 time: 0.2608 data_time: 0.0075 memory: 5828 grad_norm: 3.1760 loss: 2.3034 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3034 2023/06/05 07:30:50 - mmengine - INFO - Epoch(train) [80][ 460/2569] lr: 4.0000e-02 eta: 13:25:47 time: 0.2653 data_time: 0.0078 memory: 5828 grad_norm: 3.1107 loss: 2.5092 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5092 2023/06/05 07:30:55 - mmengine - INFO - Epoch(train) [80][ 480/2569] lr: 4.0000e-02 eta: 13:25:42 time: 0.2633 data_time: 0.0072 memory: 5828 grad_norm: 3.1389 loss: 2.4129 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4129 2023/06/05 07:31:00 - mmengine - INFO - Epoch(train) [80][ 500/2569] lr: 4.0000e-02 eta: 13:25:36 time: 0.2584 data_time: 0.0075 memory: 5828 grad_norm: 3.1330 loss: 2.4537 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4537 2023/06/05 07:31:06 - mmengine - INFO - Epoch(train) [80][ 520/2569] lr: 4.0000e-02 eta: 13:25:31 time: 0.2647 data_time: 0.0076 memory: 5828 grad_norm: 3.2293 loss: 2.4953 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4953 2023/06/05 07:31:11 - mmengine - INFO - Epoch(train) [80][ 540/2569] lr: 4.0000e-02 eta: 13:25:26 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.1437 loss: 2.5325 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5325 2023/06/05 07:31:16 - mmengine - INFO - Epoch(train) [80][ 560/2569] lr: 4.0000e-02 eta: 13:25:20 time: 0.2704 data_time: 0.0073 memory: 5828 grad_norm: 3.1884 loss: 2.3025 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3025 2023/06/05 07:31:22 - mmengine - INFO - Epoch(train) [80][ 580/2569] lr: 4.0000e-02 eta: 13:25:15 time: 0.2689 data_time: 0.0071 memory: 5828 grad_norm: 3.1205 loss: 2.6481 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6481 2023/06/05 07:31:27 - mmengine - INFO - Epoch(train) [80][ 600/2569] lr: 4.0000e-02 eta: 13:25:10 time: 0.2640 data_time: 0.0072 memory: 5828 grad_norm: 3.1231 loss: 2.4573 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4573 2023/06/05 07:31:33 - mmengine - INFO - Epoch(train) [80][ 620/2569] lr: 4.0000e-02 eta: 13:25:04 time: 0.2701 data_time: 0.0069 memory: 5828 grad_norm: 3.1504 loss: 2.4072 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4072 2023/06/05 07:31:38 - mmengine - INFO - Epoch(train) [80][ 640/2569] lr: 4.0000e-02 eta: 13:24:59 time: 0.2627 data_time: 0.0075 memory: 5828 grad_norm: 3.1561 loss: 2.6262 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6262 2023/06/05 07:31:43 - mmengine - INFO - Epoch(train) [80][ 660/2569] lr: 4.0000e-02 eta: 13:24:54 time: 0.2652 data_time: 0.0070 memory: 5828 grad_norm: 3.1642 loss: 2.5317 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5317 2023/06/05 07:31:49 - mmengine - INFO - Epoch(train) [80][ 680/2569] lr: 4.0000e-02 eta: 13:24:48 time: 0.2687 data_time: 0.0078 memory: 5828 grad_norm: 3.1695 loss: 2.5277 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5277 2023/06/05 07:31:54 - mmengine - INFO - Epoch(train) [80][ 700/2569] lr: 4.0000e-02 eta: 13:24:43 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 3.1981 loss: 2.4584 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4584 2023/06/05 07:31:59 - mmengine - INFO - Epoch(train) [80][ 720/2569] lr: 4.0000e-02 eta: 13:24:38 time: 0.2638 data_time: 0.0077 memory: 5828 grad_norm: 3.1905 loss: 2.4118 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4118 2023/06/05 07:32:04 - mmengine - INFO - Epoch(train) [80][ 740/2569] lr: 4.0000e-02 eta: 13:24:32 time: 0.2638 data_time: 0.0082 memory: 5828 grad_norm: 3.1335 loss: 2.4229 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4229 2023/06/05 07:32:10 - mmengine - INFO - Epoch(train) [80][ 760/2569] lr: 4.0000e-02 eta: 13:24:27 time: 0.2670 data_time: 0.0079 memory: 5828 grad_norm: 3.1580 loss: 2.3039 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3039 2023/06/05 07:32:15 - mmengine - INFO - Epoch(train) [80][ 780/2569] lr: 4.0000e-02 eta: 13:24:22 time: 0.2678 data_time: 0.0076 memory: 5828 grad_norm: 3.1388 loss: 2.4811 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4811 2023/06/05 07:32:20 - mmengine - INFO - Epoch(train) [80][ 800/2569] lr: 4.0000e-02 eta: 13:24:17 time: 0.2716 data_time: 0.0075 memory: 5828 grad_norm: 3.1549 loss: 2.6601 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6601 2023/06/05 07:32:26 - mmengine - INFO - Epoch(train) [80][ 820/2569] lr: 4.0000e-02 eta: 13:24:11 time: 0.2698 data_time: 0.0071 memory: 5828 grad_norm: 3.1363 loss: 2.5296 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5296 2023/06/05 07:32:31 - mmengine - INFO - Epoch(train) [80][ 840/2569] lr: 4.0000e-02 eta: 13:24:06 time: 0.2651 data_time: 0.0071 memory: 5828 grad_norm: 3.0916 loss: 2.7934 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7934 2023/06/05 07:32:37 - mmengine - INFO - Epoch(train) [80][ 860/2569] lr: 4.0000e-02 eta: 13:24:01 time: 0.2687 data_time: 0.0072 memory: 5828 grad_norm: 3.0926 loss: 2.7708 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7708 2023/06/05 07:32:42 - mmengine - INFO - Epoch(train) [80][ 880/2569] lr: 4.0000e-02 eta: 13:23:56 time: 0.2735 data_time: 0.0074 memory: 5828 grad_norm: 3.1198 loss: 2.6336 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6336 2023/06/05 07:32:48 - mmengine - INFO - Epoch(train) [80][ 900/2569] lr: 4.0000e-02 eta: 13:23:50 time: 0.2718 data_time: 0.0082 memory: 5828 grad_norm: 3.1087 loss: 2.2333 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2333 2023/06/05 07:32:53 - mmengine - INFO - Epoch(train) [80][ 920/2569] lr: 4.0000e-02 eta: 13:23:45 time: 0.2626 data_time: 0.0070 memory: 5828 grad_norm: 3.1094 loss: 2.4461 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4461 2023/06/05 07:32:58 - mmengine - INFO - Epoch(train) [80][ 940/2569] lr: 4.0000e-02 eta: 13:23:40 time: 0.2650 data_time: 0.0079 memory: 5828 grad_norm: 3.1455 loss: 2.5442 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5442 2023/06/05 07:33:03 - mmengine - INFO - Epoch(train) [80][ 960/2569] lr: 4.0000e-02 eta: 13:23:34 time: 0.2637 data_time: 0.0077 memory: 5828 grad_norm: 3.1509 loss: 2.4309 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.4309 2023/06/05 07:33:09 - mmengine - INFO - Epoch(train) [80][ 980/2569] lr: 4.0000e-02 eta: 13:23:29 time: 0.2638 data_time: 0.0070 memory: 5828 grad_norm: 3.1293 loss: 2.7234 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7234 2023/06/05 07:33:14 - mmengine - INFO - Epoch(train) [80][1000/2569] lr: 4.0000e-02 eta: 13:23:24 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 3.1469 loss: 2.6379 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6379 2023/06/05 07:33:19 - mmengine - INFO - Epoch(train) [80][1020/2569] lr: 4.0000e-02 eta: 13:23:19 time: 0.2731 data_time: 0.0072 memory: 5828 grad_norm: 3.1129 loss: 2.5713 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5713 2023/06/05 07:33:25 - mmengine - INFO - Epoch(train) [80][1040/2569] lr: 4.0000e-02 eta: 13:23:13 time: 0.2593 data_time: 0.0072 memory: 5828 grad_norm: 3.1863 loss: 2.6568 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6568 2023/06/05 07:33:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:33:30 - mmengine - INFO - Epoch(train) [80][1060/2569] lr: 4.0000e-02 eta: 13:23:08 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 3.1241 loss: 2.5817 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5817 2023/06/05 07:33:35 - mmengine - INFO - Epoch(train) [80][1080/2569] lr: 4.0000e-02 eta: 13:23:02 time: 0.2601 data_time: 0.0073 memory: 5828 grad_norm: 3.1302 loss: 2.6527 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6527 2023/06/05 07:33:40 - mmengine - INFO - Epoch(train) [80][1100/2569] lr: 4.0000e-02 eta: 13:22:57 time: 0.2643 data_time: 0.0070 memory: 5828 grad_norm: 3.1399 loss: 2.6753 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6753 2023/06/05 07:33:46 - mmengine - INFO - Epoch(train) [80][1120/2569] lr: 4.0000e-02 eta: 13:22:52 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 3.1303 loss: 2.4370 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4370 2023/06/05 07:33:51 - mmengine - INFO - Epoch(train) [80][1140/2569] lr: 4.0000e-02 eta: 13:22:46 time: 0.2582 data_time: 0.0073 memory: 5828 grad_norm: 3.2252 loss: 2.7239 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7239 2023/06/05 07:33:56 - mmengine - INFO - Epoch(train) [80][1160/2569] lr: 4.0000e-02 eta: 13:22:41 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.2015 loss: 2.6396 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6396 2023/06/05 07:34:01 - mmengine - INFO - Epoch(train) [80][1180/2569] lr: 4.0000e-02 eta: 13:22:36 time: 0.2609 data_time: 0.0070 memory: 5828 grad_norm: 3.0916 loss: 2.7045 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7045 2023/06/05 07:34:07 - mmengine - INFO - Epoch(train) [80][1200/2569] lr: 4.0000e-02 eta: 13:22:30 time: 0.2581 data_time: 0.0074 memory: 5828 grad_norm: 3.1454 loss: 2.4872 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4872 2023/06/05 07:34:12 - mmengine - INFO - Epoch(train) [80][1220/2569] lr: 4.0000e-02 eta: 13:22:25 time: 0.2639 data_time: 0.0071 memory: 5828 grad_norm: 3.0987 loss: 2.5610 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5610 2023/06/05 07:34:17 - mmengine - INFO - Epoch(train) [80][1240/2569] lr: 4.0000e-02 eta: 13:22:19 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 3.1975 loss: 2.5068 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5068 2023/06/05 07:34:23 - mmengine - INFO - Epoch(train) [80][1260/2569] lr: 4.0000e-02 eta: 13:22:14 time: 0.2685 data_time: 0.0074 memory: 5828 grad_norm: 3.1601 loss: 2.3243 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3243 2023/06/05 07:34:28 - mmengine - INFO - Epoch(train) [80][1280/2569] lr: 4.0000e-02 eta: 13:22:09 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 3.1952 loss: 2.5496 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5496 2023/06/05 07:34:33 - mmengine - INFO - Epoch(train) [80][1300/2569] lr: 4.0000e-02 eta: 13:22:03 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 3.1070 loss: 2.6735 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6735 2023/06/05 07:34:39 - mmengine - INFO - Epoch(train) [80][1320/2569] lr: 4.0000e-02 eta: 13:21:58 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 3.1752 loss: 2.4479 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4479 2023/06/05 07:34:44 - mmengine - INFO - Epoch(train) [80][1340/2569] lr: 4.0000e-02 eta: 13:21:53 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 3.1444 loss: 2.3708 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3708 2023/06/05 07:34:49 - mmengine - INFO - Epoch(train) [80][1360/2569] lr: 4.0000e-02 eta: 13:21:48 time: 0.2667 data_time: 0.0076 memory: 5828 grad_norm: 3.1192 loss: 2.3899 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3899 2023/06/05 07:34:54 - mmengine - INFO - Epoch(train) [80][1380/2569] lr: 4.0000e-02 eta: 13:21:42 time: 0.2598 data_time: 0.0076 memory: 5828 grad_norm: 3.1439 loss: 2.8287 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8287 2023/06/05 07:35:00 - mmengine - INFO - Epoch(train) [80][1400/2569] lr: 4.0000e-02 eta: 13:21:37 time: 0.2682 data_time: 0.0074 memory: 5828 grad_norm: 3.1560 loss: 2.5896 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5896 2023/06/05 07:35:05 - mmengine - INFO - Epoch(train) [80][1420/2569] lr: 4.0000e-02 eta: 13:21:32 time: 0.2644 data_time: 0.0073 memory: 5828 grad_norm: 3.1717 loss: 2.7105 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7105 2023/06/05 07:35:11 - mmengine - INFO - Epoch(train) [80][1440/2569] lr: 4.0000e-02 eta: 13:21:26 time: 0.2712 data_time: 0.0078 memory: 5828 grad_norm: 3.1124 loss: 2.3931 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3931 2023/06/05 07:35:16 - mmengine - INFO - Epoch(train) [80][1460/2569] lr: 4.0000e-02 eta: 13:21:21 time: 0.2691 data_time: 0.0071 memory: 5828 grad_norm: 3.2033 loss: 2.3728 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3728 2023/06/05 07:35:21 - mmengine - INFO - Epoch(train) [80][1480/2569] lr: 4.0000e-02 eta: 13:21:16 time: 0.2628 data_time: 0.0073 memory: 5828 grad_norm: 3.1333 loss: 2.7283 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7283 2023/06/05 07:35:26 - mmengine - INFO - Epoch(train) [80][1500/2569] lr: 4.0000e-02 eta: 13:21:10 time: 0.2572 data_time: 0.0074 memory: 5828 grad_norm: 3.1828 loss: 2.0847 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0847 2023/06/05 07:35:32 - mmengine - INFO - Epoch(train) [80][1520/2569] lr: 4.0000e-02 eta: 13:21:05 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 3.1916 loss: 2.6332 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6332 2023/06/05 07:35:37 - mmengine - INFO - Epoch(train) [80][1540/2569] lr: 4.0000e-02 eta: 13:20:59 time: 0.2611 data_time: 0.0073 memory: 5828 grad_norm: 3.1639 loss: 2.6695 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6695 2023/06/05 07:35:42 - mmengine - INFO - Epoch(train) [80][1560/2569] lr: 4.0000e-02 eta: 13:20:54 time: 0.2649 data_time: 0.0071 memory: 5828 grad_norm: 3.1547 loss: 2.4184 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4184 2023/06/05 07:35:48 - mmengine - INFO - Epoch(train) [80][1580/2569] lr: 4.0000e-02 eta: 13:20:49 time: 0.2742 data_time: 0.0076 memory: 5828 grad_norm: 3.1051 loss: 2.4171 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4171 2023/06/05 07:35:53 - mmengine - INFO - Epoch(train) [80][1600/2569] lr: 4.0000e-02 eta: 13:20:44 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.1109 loss: 2.3847 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3847 2023/06/05 07:35:58 - mmengine - INFO - Epoch(train) [80][1620/2569] lr: 4.0000e-02 eta: 13:20:38 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 3.1042 loss: 2.3447 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3447 2023/06/05 07:36:03 - mmengine - INFO - Epoch(train) [80][1640/2569] lr: 4.0000e-02 eta: 13:20:33 time: 0.2604 data_time: 0.0075 memory: 5828 grad_norm: 3.0825 loss: 3.0053 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0053 2023/06/05 07:36:09 - mmengine - INFO - Epoch(train) [80][1660/2569] lr: 4.0000e-02 eta: 13:20:27 time: 0.2584 data_time: 0.0074 memory: 5828 grad_norm: 3.0728 loss: 2.6694 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6694 2023/06/05 07:36:14 - mmengine - INFO - Epoch(train) [80][1680/2569] lr: 4.0000e-02 eta: 13:20:22 time: 0.2740 data_time: 0.0074 memory: 5828 grad_norm: 3.1287 loss: 2.4810 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4810 2023/06/05 07:36:19 - mmengine - INFO - Epoch(train) [80][1700/2569] lr: 4.0000e-02 eta: 13:20:17 time: 0.2598 data_time: 0.0073 memory: 5828 grad_norm: 3.1373 loss: 2.5068 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5068 2023/06/05 07:36:25 - mmengine - INFO - Epoch(train) [80][1720/2569] lr: 4.0000e-02 eta: 13:20:12 time: 0.2693 data_time: 0.0073 memory: 5828 grad_norm: 3.1447 loss: 2.4579 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4579 2023/06/05 07:36:30 - mmengine - INFO - Epoch(train) [80][1740/2569] lr: 4.0000e-02 eta: 13:20:06 time: 0.2680 data_time: 0.0069 memory: 5828 grad_norm: 3.1904 loss: 2.3917 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3917 2023/06/05 07:36:35 - mmengine - INFO - Epoch(train) [80][1760/2569] lr: 4.0000e-02 eta: 13:20:01 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 3.1156 loss: 2.5167 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5167 2023/06/05 07:36:40 - mmengine - INFO - Epoch(train) [80][1780/2569] lr: 4.0000e-02 eta: 13:19:55 time: 0.2577 data_time: 0.0072 memory: 5828 grad_norm: 3.1862 loss: 2.4917 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4917 2023/06/05 07:36:46 - mmengine - INFO - Epoch(train) [80][1800/2569] lr: 4.0000e-02 eta: 13:19:50 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 3.0989 loss: 2.6010 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6010 2023/06/05 07:36:51 - mmengine - INFO - Epoch(train) [80][1820/2569] lr: 4.0000e-02 eta: 13:19:45 time: 0.2581 data_time: 0.0074 memory: 5828 grad_norm: 3.1214 loss: 2.6376 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6376 2023/06/05 07:36:56 - mmengine - INFO - Epoch(train) [80][1840/2569] lr: 4.0000e-02 eta: 13:19:39 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.1491 loss: 2.6917 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6917 2023/06/05 07:37:01 - mmengine - INFO - Epoch(train) [80][1860/2569] lr: 4.0000e-02 eta: 13:19:34 time: 0.2619 data_time: 0.0071 memory: 5828 grad_norm: 3.1075 loss: 2.6663 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6663 2023/06/05 07:37:07 - mmengine - INFO - Epoch(train) [80][1880/2569] lr: 4.0000e-02 eta: 13:19:29 time: 0.2602 data_time: 0.0077 memory: 5828 grad_norm: 3.0814 loss: 2.2655 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2655 2023/06/05 07:37:12 - mmengine - INFO - Epoch(train) [80][1900/2569] lr: 4.0000e-02 eta: 13:19:23 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 3.1594 loss: 2.3086 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3086 2023/06/05 07:37:17 - mmengine - INFO - Epoch(train) [80][1920/2569] lr: 4.0000e-02 eta: 13:19:18 time: 0.2692 data_time: 0.0072 memory: 5828 grad_norm: 3.1251 loss: 2.6071 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6071 2023/06/05 07:37:23 - mmengine - INFO - Epoch(train) [80][1940/2569] lr: 4.0000e-02 eta: 13:19:13 time: 0.2651 data_time: 0.0071 memory: 5828 grad_norm: 3.0798 loss: 2.2311 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2311 2023/06/05 07:37:28 - mmengine - INFO - Epoch(train) [80][1960/2569] lr: 4.0000e-02 eta: 13:19:07 time: 0.2709 data_time: 0.0076 memory: 5828 grad_norm: 3.1530 loss: 2.3305 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3305 2023/06/05 07:37:33 - mmengine - INFO - Epoch(train) [80][1980/2569] lr: 4.0000e-02 eta: 13:19:02 time: 0.2695 data_time: 0.0077 memory: 5828 grad_norm: 3.1570 loss: 2.7446 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7446 2023/06/05 07:37:39 - mmengine - INFO - Epoch(train) [80][2000/2569] lr: 4.0000e-02 eta: 13:18:57 time: 0.2732 data_time: 0.0075 memory: 5828 grad_norm: 3.0727 loss: 2.2008 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2008 2023/06/05 07:37:44 - mmengine - INFO - Epoch(train) [80][2020/2569] lr: 4.0000e-02 eta: 13:18:52 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 3.0845 loss: 2.3478 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3478 2023/06/05 07:37:50 - mmengine - INFO - Epoch(train) [80][2040/2569] lr: 4.0000e-02 eta: 13:18:46 time: 0.2690 data_time: 0.0073 memory: 5828 grad_norm: 3.1069 loss: 2.3284 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3284 2023/06/05 07:37:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:37:55 - mmengine - INFO - Epoch(train) [80][2060/2569] lr: 4.0000e-02 eta: 13:18:41 time: 0.2834 data_time: 0.0074 memory: 5828 grad_norm: 3.1583 loss: 2.6972 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6972 2023/06/05 07:38:01 - mmengine - INFO - Epoch(train) [80][2080/2569] lr: 4.0000e-02 eta: 13:18:36 time: 0.2639 data_time: 0.0072 memory: 5828 grad_norm: 3.1445 loss: 2.3382 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3382 2023/06/05 07:38:06 - mmengine - INFO - Epoch(train) [80][2100/2569] lr: 4.0000e-02 eta: 13:18:31 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 3.0933 loss: 2.3231 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3231 2023/06/05 07:38:11 - mmengine - INFO - Epoch(train) [80][2120/2569] lr: 4.0000e-02 eta: 13:18:25 time: 0.2706 data_time: 0.0074 memory: 5828 grad_norm: 3.1567 loss: 1.9983 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9983 2023/06/05 07:38:16 - mmengine - INFO - Epoch(train) [80][2140/2569] lr: 4.0000e-02 eta: 13:18:20 time: 0.2585 data_time: 0.0071 memory: 5828 grad_norm: 3.0501 loss: 2.5801 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5801 2023/06/05 07:38:22 - mmengine - INFO - Epoch(train) [80][2160/2569] lr: 4.0000e-02 eta: 13:18:15 time: 0.2642 data_time: 0.0077 memory: 5828 grad_norm: 3.1013 loss: 2.3213 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3213 2023/06/05 07:38:27 - mmengine - INFO - Epoch(train) [80][2180/2569] lr: 4.0000e-02 eta: 13:18:09 time: 0.2584 data_time: 0.0069 memory: 5828 grad_norm: 3.1366 loss: 2.6147 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6147 2023/06/05 07:38:32 - mmengine - INFO - Epoch(train) [80][2200/2569] lr: 4.0000e-02 eta: 13:18:04 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 3.1569 loss: 2.5216 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5216 2023/06/05 07:38:38 - mmengine - INFO - Epoch(train) [80][2220/2569] lr: 4.0000e-02 eta: 13:17:59 time: 0.2708 data_time: 0.0072 memory: 5828 grad_norm: 3.0977 loss: 2.4560 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.4560 2023/06/05 07:38:43 - mmengine - INFO - Epoch(train) [80][2240/2569] lr: 4.0000e-02 eta: 13:17:53 time: 0.2605 data_time: 0.0076 memory: 5828 grad_norm: 3.1782 loss: 3.0561 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 3.0561 2023/06/05 07:38:48 - mmengine - INFO - Epoch(train) [80][2260/2569] lr: 4.0000e-02 eta: 13:17:48 time: 0.2647 data_time: 0.0071 memory: 5828 grad_norm: 3.1796 loss: 2.6219 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6219 2023/06/05 07:38:53 - mmengine - INFO - Epoch(train) [80][2280/2569] lr: 4.0000e-02 eta: 13:17:42 time: 0.2585 data_time: 0.0074 memory: 5828 grad_norm: 3.1348 loss: 2.4513 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4513 2023/06/05 07:38:59 - mmengine - INFO - Epoch(train) [80][2300/2569] lr: 4.0000e-02 eta: 13:17:37 time: 0.2679 data_time: 0.0071 memory: 5828 grad_norm: 3.1686 loss: 2.5963 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5963 2023/06/05 07:39:04 - mmengine - INFO - Epoch(train) [80][2320/2569] lr: 4.0000e-02 eta: 13:17:32 time: 0.2620 data_time: 0.0070 memory: 5828 grad_norm: 3.1339 loss: 2.4170 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4170 2023/06/05 07:39:09 - mmengine - INFO - Epoch(train) [80][2340/2569] lr: 4.0000e-02 eta: 13:17:27 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 3.0737 loss: 2.6423 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6423 2023/06/05 07:39:15 - mmengine - INFO - Epoch(train) [80][2360/2569] lr: 4.0000e-02 eta: 13:17:21 time: 0.2616 data_time: 0.0075 memory: 5828 grad_norm: 3.1306 loss: 2.4594 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4594 2023/06/05 07:39:20 - mmengine - INFO - Epoch(train) [80][2380/2569] lr: 4.0000e-02 eta: 13:17:16 time: 0.2588 data_time: 0.0075 memory: 5828 grad_norm: 3.1345 loss: 2.6345 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6345 2023/06/05 07:39:25 - mmengine - INFO - Epoch(train) [80][2400/2569] lr: 4.0000e-02 eta: 13:17:10 time: 0.2600 data_time: 0.0071 memory: 5828 grad_norm: 3.1559 loss: 2.6689 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6689 2023/06/05 07:39:30 - mmengine - INFO - Epoch(train) [80][2420/2569] lr: 4.0000e-02 eta: 13:17:05 time: 0.2633 data_time: 0.0071 memory: 5828 grad_norm: 3.1807 loss: 2.3392 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.3392 2023/06/05 07:39:36 - mmengine - INFO - Epoch(train) [80][2440/2569] lr: 4.0000e-02 eta: 13:17:00 time: 0.2710 data_time: 0.0075 memory: 5828 grad_norm: 3.1855 loss: 2.2057 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2057 2023/06/05 07:39:41 - mmengine - INFO - Epoch(train) [80][2460/2569] lr: 4.0000e-02 eta: 13:16:54 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 3.0868 loss: 2.4591 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4591 2023/06/05 07:39:46 - mmengine - INFO - Epoch(train) [80][2480/2569] lr: 4.0000e-02 eta: 13:16:49 time: 0.2635 data_time: 0.0070 memory: 5828 grad_norm: 3.1752 loss: 2.6727 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6727 2023/06/05 07:39:51 - mmengine - INFO - Epoch(train) [80][2500/2569] lr: 4.0000e-02 eta: 13:16:44 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.1886 loss: 2.2684 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2684 2023/06/05 07:39:57 - mmengine - INFO - Epoch(train) [80][2520/2569] lr: 4.0000e-02 eta: 13:16:38 time: 0.2589 data_time: 0.0077 memory: 5828 grad_norm: 3.1460 loss: 3.0321 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0321 2023/06/05 07:40:02 - mmengine - INFO - Epoch(train) [80][2540/2569] lr: 4.0000e-02 eta: 13:16:33 time: 0.2683 data_time: 0.0070 memory: 5828 grad_norm: 3.1499 loss: 2.5014 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5014 2023/06/05 07:40:07 - mmengine - INFO - Epoch(train) [80][2560/2569] lr: 4.0000e-02 eta: 13:16:28 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 3.1331 loss: 2.7257 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7257 2023/06/05 07:40:10 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:40:10 - mmengine - INFO - Epoch(train) [80][2569/2569] lr: 4.0000e-02 eta: 13:16:25 time: 0.2678 data_time: 0.0069 memory: 5828 grad_norm: 3.1212 loss: 2.4802 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.4802 2023/06/05 07:40:10 - mmengine - INFO - Saving checkpoint at 80 epochs 2023/06/05 07:40:16 - mmengine - INFO - Epoch(val) [80][ 20/260] eta: 0:00:42 time: 0.1787 data_time: 0.1197 memory: 1238 2023/06/05 07:40:19 - mmengine - INFO - Epoch(val) [80][ 40/260] eta: 0:00:35 time: 0.1414 data_time: 0.0826 memory: 1238 2023/06/05 07:40:22 - mmengine - INFO - Epoch(val) [80][ 60/260] eta: 0:00:31 time: 0.1581 data_time: 0.0997 memory: 1238 2023/06/05 07:40:24 - mmengine - INFO - Epoch(val) [80][ 80/260] eta: 0:00:27 time: 0.1347 data_time: 0.0756 memory: 1238 2023/06/05 07:40:27 - mmengine - INFO - Epoch(val) [80][100/260] eta: 0:00:24 time: 0.1531 data_time: 0.0944 memory: 1238 2023/06/05 07:40:30 - mmengine - INFO - Epoch(val) [80][120/260] eta: 0:00:20 time: 0.1226 data_time: 0.0640 memory: 1238 2023/06/05 07:40:33 - mmengine - INFO - Epoch(val) [80][140/260] eta: 0:00:17 time: 0.1486 data_time: 0.0899 memory: 1238 2023/06/05 07:40:35 - mmengine - INFO - Epoch(val) [80][160/260] eta: 0:00:14 time: 0.1163 data_time: 0.0578 memory: 1238 2023/06/05 07:40:38 - mmengine - INFO - Epoch(val) [80][180/260] eta: 0:00:11 time: 0.1484 data_time: 0.0901 memory: 1238 2023/06/05 07:40:41 - mmengine - INFO - Epoch(val) [80][200/260] eta: 0:00:08 time: 0.1292 data_time: 0.0703 memory: 1238 2023/06/05 07:40:44 - mmengine - INFO - Epoch(val) [80][220/260] eta: 0:00:05 time: 0.1602 data_time: 0.1014 memory: 1238 2023/06/05 07:40:46 - mmengine - INFO - Epoch(val) [80][240/260] eta: 0:00:02 time: 0.1201 data_time: 0.0620 memory: 1238 2023/06/05 07:40:49 - mmengine - INFO - Epoch(val) [80][260/260] eta: 0:00:00 time: 0.1135 data_time: 0.0577 memory: 1238 2023/06/05 07:40:55 - mmengine - INFO - Epoch(val) [80][260/260] acc/top1: 0.5042 acc/top5: 0.7484 acc/mean1: 0.4959 data_time: 0.0816 time: 0.1400 2023/06/05 07:40:55 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_65.pth is removed 2023/06/05 07:40:57 - mmengine - INFO - The best checkpoint with 0.5042 acc/top1 at 80 epoch is saved to best_acc_top1_epoch_80.pth. 2023/06/05 07:41:03 - mmengine - INFO - Epoch(train) [81][ 20/2569] lr: 4.0000e-02 eta: 13:16:21 time: 0.3162 data_time: 0.0621 memory: 5828 grad_norm: 3.0885 loss: 2.4638 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4638 2023/06/05 07:41:08 - mmengine - INFO - Epoch(train) [81][ 40/2569] lr: 4.0000e-02 eta: 13:16:15 time: 0.2585 data_time: 0.0073 memory: 5828 grad_norm: 3.1347 loss: 2.7085 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7085 2023/06/05 07:41:14 - mmengine - INFO - Epoch(train) [81][ 60/2569] lr: 4.0000e-02 eta: 13:16:10 time: 0.2580 data_time: 0.0077 memory: 5828 grad_norm: 3.0794 loss: 2.2691 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2691 2023/06/05 07:41:19 - mmengine - INFO - Epoch(train) [81][ 80/2569] lr: 4.0000e-02 eta: 13:16:05 time: 0.2679 data_time: 0.0075 memory: 5828 grad_norm: 3.1248 loss: 2.5858 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5858 2023/06/05 07:41:24 - mmengine - INFO - Epoch(train) [81][ 100/2569] lr: 4.0000e-02 eta: 13:15:59 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.1502 loss: 2.5060 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5060 2023/06/05 07:41:30 - mmengine - INFO - Epoch(train) [81][ 120/2569] lr: 4.0000e-02 eta: 13:15:54 time: 0.2760 data_time: 0.0075 memory: 5828 grad_norm: 3.1487 loss: 2.5352 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5352 2023/06/05 07:41:35 - mmengine - INFO - Epoch(train) [81][ 140/2569] lr: 4.0000e-02 eta: 13:15:49 time: 0.2641 data_time: 0.0076 memory: 5828 grad_norm: 3.0667 loss: 2.6007 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6007 2023/06/05 07:41:40 - mmengine - INFO - Epoch(train) [81][ 160/2569] lr: 4.0000e-02 eta: 13:15:44 time: 0.2653 data_time: 0.0073 memory: 5828 grad_norm: 3.1591 loss: 2.4677 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4677 2023/06/05 07:41:46 - mmengine - INFO - Epoch(train) [81][ 180/2569] lr: 4.0000e-02 eta: 13:15:38 time: 0.2766 data_time: 0.0073 memory: 5828 grad_norm: 3.1851 loss: 2.2177 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2177 2023/06/05 07:41:51 - mmengine - INFO - Epoch(train) [81][ 200/2569] lr: 4.0000e-02 eta: 13:15:33 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 3.1713 loss: 2.6349 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6349 2023/06/05 07:41:56 - mmengine - INFO - Epoch(train) [81][ 220/2569] lr: 4.0000e-02 eta: 13:15:28 time: 0.2584 data_time: 0.0071 memory: 5828 grad_norm: 3.0931 loss: 2.7308 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7308 2023/06/05 07:42:02 - mmengine - INFO - Epoch(train) [81][ 240/2569] lr: 4.0000e-02 eta: 13:15:22 time: 0.2596 data_time: 0.0073 memory: 5828 grad_norm: 3.1099 loss: 2.5715 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5715 2023/06/05 07:42:07 - mmengine - INFO - Epoch(train) [81][ 260/2569] lr: 4.0000e-02 eta: 13:15:17 time: 0.2775 data_time: 0.0071 memory: 5828 grad_norm: 3.1146 loss: 2.6292 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6292 2023/06/05 07:42:12 - mmengine - INFO - Epoch(train) [81][ 280/2569] lr: 4.0000e-02 eta: 13:15:12 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 3.0829 loss: 2.1731 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1731 2023/06/05 07:42:18 - mmengine - INFO - Epoch(train) [81][ 300/2569] lr: 4.0000e-02 eta: 13:15:06 time: 0.2655 data_time: 0.0072 memory: 5828 grad_norm: 3.1025 loss: 2.6898 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6898 2023/06/05 07:42:23 - mmengine - INFO - Epoch(train) [81][ 320/2569] lr: 4.0000e-02 eta: 13:15:01 time: 0.2725 data_time: 0.0070 memory: 5828 grad_norm: 3.1552 loss: 2.4154 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.4154 2023/06/05 07:42:29 - mmengine - INFO - Epoch(train) [81][ 340/2569] lr: 4.0000e-02 eta: 13:14:56 time: 0.2687 data_time: 0.0070 memory: 5828 grad_norm: 3.1528 loss: 3.0821 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0821 2023/06/05 07:42:34 - mmengine - INFO - Epoch(train) [81][ 360/2569] lr: 4.0000e-02 eta: 13:14:51 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 3.1807 loss: 2.3509 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3509 2023/06/05 07:42:39 - mmengine - INFO - Epoch(train) [81][ 380/2569] lr: 4.0000e-02 eta: 13:14:45 time: 0.2695 data_time: 0.0070 memory: 5828 grad_norm: 3.0610 loss: 2.4084 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4084 2023/06/05 07:42:45 - mmengine - INFO - Epoch(train) [81][ 400/2569] lr: 4.0000e-02 eta: 13:14:40 time: 0.2586 data_time: 0.0075 memory: 5828 grad_norm: 3.1335 loss: 2.3873 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.3873 2023/06/05 07:42:50 - mmengine - INFO - Epoch(train) [81][ 420/2569] lr: 4.0000e-02 eta: 13:14:35 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 3.0938 loss: 2.7141 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7141 2023/06/05 07:42:55 - mmengine - INFO - Epoch(train) [81][ 440/2569] lr: 4.0000e-02 eta: 13:14:29 time: 0.2751 data_time: 0.0077 memory: 5828 grad_norm: 3.0949 loss: 2.4586 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4586 2023/06/05 07:43:01 - mmengine - INFO - Epoch(train) [81][ 460/2569] lr: 4.0000e-02 eta: 13:14:24 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.1332 loss: 2.2454 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2454 2023/06/05 07:43:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:43:06 - mmengine - INFO - Epoch(train) [81][ 480/2569] lr: 4.0000e-02 eta: 13:14:19 time: 0.2608 data_time: 0.0080 memory: 5828 grad_norm: 3.0842 loss: 2.9128 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9128 2023/06/05 07:43:11 - mmengine - INFO - Epoch(train) [81][ 500/2569] lr: 4.0000e-02 eta: 13:14:13 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 3.1462 loss: 2.5172 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5172 2023/06/05 07:43:16 - mmengine - INFO - Epoch(train) [81][ 520/2569] lr: 4.0000e-02 eta: 13:14:08 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 3.1389 loss: 2.1440 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1440 2023/06/05 07:43:22 - mmengine - INFO - Epoch(train) [81][ 540/2569] lr: 4.0000e-02 eta: 13:14:03 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 3.1480 loss: 2.3958 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3958 2023/06/05 07:43:27 - mmengine - INFO - Epoch(train) [81][ 560/2569] lr: 4.0000e-02 eta: 13:13:57 time: 0.2712 data_time: 0.0074 memory: 5828 grad_norm: 3.1042 loss: 2.3939 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3939 2023/06/05 07:43:32 - mmengine - INFO - Epoch(train) [81][ 580/2569] lr: 4.0000e-02 eta: 13:13:52 time: 0.2684 data_time: 0.0075 memory: 5828 grad_norm: 3.0929 loss: 2.4537 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4537 2023/06/05 07:43:38 - mmengine - INFO - Epoch(train) [81][ 600/2569] lr: 4.0000e-02 eta: 13:13:47 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 3.1278 loss: 2.3492 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3492 2023/06/05 07:43:43 - mmengine - INFO - Epoch(train) [81][ 620/2569] lr: 4.0000e-02 eta: 13:13:42 time: 0.2678 data_time: 0.0074 memory: 5828 grad_norm: 3.1851 loss: 2.6001 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6001 2023/06/05 07:43:48 - mmengine - INFO - Epoch(train) [81][ 640/2569] lr: 4.0000e-02 eta: 13:13:36 time: 0.2635 data_time: 0.0072 memory: 5828 grad_norm: 3.0701 loss: 2.7813 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7813 2023/06/05 07:43:54 - mmengine - INFO - Epoch(train) [81][ 660/2569] lr: 4.0000e-02 eta: 13:13:31 time: 0.2570 data_time: 0.0069 memory: 5828 grad_norm: 3.1112 loss: 2.6924 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6924 2023/06/05 07:43:59 - mmengine - INFO - Epoch(train) [81][ 680/2569] lr: 4.0000e-02 eta: 13:13:25 time: 0.2582 data_time: 0.0074 memory: 5828 grad_norm: 3.1085 loss: 2.5972 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5972 2023/06/05 07:44:04 - mmengine - INFO - Epoch(train) [81][ 700/2569] lr: 4.0000e-02 eta: 13:13:20 time: 0.2570 data_time: 0.0073 memory: 5828 grad_norm: 3.2016 loss: 2.6982 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6982 2023/06/05 07:44:09 - mmengine - INFO - Epoch(train) [81][ 720/2569] lr: 4.0000e-02 eta: 13:13:15 time: 0.2691 data_time: 0.0073 memory: 5828 grad_norm: 3.1444 loss: 2.4542 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4542 2023/06/05 07:44:14 - mmengine - INFO - Epoch(train) [81][ 740/2569] lr: 4.0000e-02 eta: 13:13:09 time: 0.2594 data_time: 0.0072 memory: 5828 grad_norm: 3.1485 loss: 2.5683 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5683 2023/06/05 07:44:20 - mmengine - INFO - Epoch(train) [81][ 760/2569] lr: 4.0000e-02 eta: 13:13:04 time: 0.2638 data_time: 0.0077 memory: 5828 grad_norm: 3.1400 loss: 2.4642 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4642 2023/06/05 07:44:25 - mmengine - INFO - Epoch(train) [81][ 780/2569] lr: 4.0000e-02 eta: 13:12:58 time: 0.2651 data_time: 0.0078 memory: 5828 grad_norm: 3.1653 loss: 2.5543 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5543 2023/06/05 07:44:30 - mmengine - INFO - Epoch(train) [81][ 800/2569] lr: 4.0000e-02 eta: 13:12:53 time: 0.2573 data_time: 0.0078 memory: 5828 grad_norm: 3.1832 loss: 2.3592 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3592 2023/06/05 07:44:36 - mmengine - INFO - Epoch(train) [81][ 820/2569] lr: 4.0000e-02 eta: 13:12:48 time: 0.2678 data_time: 0.0081 memory: 5828 grad_norm: 3.1119 loss: 2.4998 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4998 2023/06/05 07:44:41 - mmengine - INFO - Epoch(train) [81][ 840/2569] lr: 4.0000e-02 eta: 13:12:42 time: 0.2700 data_time: 0.0073 memory: 5828 grad_norm: 3.1194 loss: 2.2035 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2035 2023/06/05 07:44:46 - mmengine - INFO - Epoch(train) [81][ 860/2569] lr: 4.0000e-02 eta: 13:12:37 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 3.1478 loss: 2.4937 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4937 2023/06/05 07:44:52 - mmengine - INFO - Epoch(train) [81][ 880/2569] lr: 4.0000e-02 eta: 13:12:32 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 3.1646 loss: 2.2536 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2536 2023/06/05 07:44:57 - mmengine - INFO - Epoch(train) [81][ 900/2569] lr: 4.0000e-02 eta: 13:12:26 time: 0.2630 data_time: 0.0071 memory: 5828 grad_norm: 3.1217 loss: 2.2225 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2225 2023/06/05 07:45:02 - mmengine - INFO - Epoch(train) [81][ 920/2569] lr: 4.0000e-02 eta: 13:12:21 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 3.1166 loss: 2.6389 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6389 2023/06/05 07:45:08 - mmengine - INFO - Epoch(train) [81][ 940/2569] lr: 4.0000e-02 eta: 13:12:16 time: 0.2646 data_time: 0.0070 memory: 5828 grad_norm: 3.1123 loss: 2.6171 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6171 2023/06/05 07:45:13 - mmengine - INFO - Epoch(train) [81][ 960/2569] lr: 4.0000e-02 eta: 13:12:11 time: 0.2594 data_time: 0.0071 memory: 5828 grad_norm: 3.1882 loss: 2.7823 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7823 2023/06/05 07:45:18 - mmengine - INFO - Epoch(train) [81][ 980/2569] lr: 4.0000e-02 eta: 13:12:05 time: 0.2649 data_time: 0.0075 memory: 5828 grad_norm: 3.1865 loss: 2.3654 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3654 2023/06/05 07:45:23 - mmengine - INFO - Epoch(train) [81][1000/2569] lr: 4.0000e-02 eta: 13:12:00 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 3.0973 loss: 2.7171 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7171 2023/06/05 07:45:29 - mmengine - INFO - Epoch(train) [81][1020/2569] lr: 4.0000e-02 eta: 13:11:55 time: 0.2706 data_time: 0.0077 memory: 5828 grad_norm: 3.1663 loss: 2.2741 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2741 2023/06/05 07:45:34 - mmengine - INFO - Epoch(train) [81][1040/2569] lr: 4.0000e-02 eta: 13:11:49 time: 0.2592 data_time: 0.0090 memory: 5828 grad_norm: 3.1430 loss: 2.3015 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3015 2023/06/05 07:45:39 - mmengine - INFO - Epoch(train) [81][1060/2569] lr: 4.0000e-02 eta: 13:11:44 time: 0.2649 data_time: 0.0072 memory: 5828 grad_norm: 3.1678 loss: 2.5155 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5155 2023/06/05 07:45:45 - mmengine - INFO - Epoch(train) [81][1080/2569] lr: 4.0000e-02 eta: 13:11:39 time: 0.2647 data_time: 0.0081 memory: 5828 grad_norm: 3.1867 loss: 2.3650 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3650 2023/06/05 07:45:50 - mmengine - INFO - Epoch(train) [81][1100/2569] lr: 4.0000e-02 eta: 13:11:33 time: 0.2607 data_time: 0.0073 memory: 5828 grad_norm: 3.1541 loss: 2.8231 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8231 2023/06/05 07:45:55 - mmengine - INFO - Epoch(train) [81][1120/2569] lr: 4.0000e-02 eta: 13:11:28 time: 0.2699 data_time: 0.0074 memory: 5828 grad_norm: 3.0991 loss: 2.6879 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6879 2023/06/05 07:46:01 - mmengine - INFO - Epoch(train) [81][1140/2569] lr: 4.0000e-02 eta: 13:11:23 time: 0.2610 data_time: 0.0072 memory: 5828 grad_norm: 3.0974 loss: 2.6700 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6700 2023/06/05 07:46:06 - mmengine - INFO - Epoch(train) [81][1160/2569] lr: 4.0000e-02 eta: 13:11:17 time: 0.2821 data_time: 0.0074 memory: 5828 grad_norm: 3.1466 loss: 2.5449 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5449 2023/06/05 07:46:12 - mmengine - INFO - Epoch(train) [81][1180/2569] lr: 4.0000e-02 eta: 13:11:12 time: 0.2682 data_time: 0.0091 memory: 5828 grad_norm: 3.1719 loss: 2.4385 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4385 2023/06/05 07:46:17 - mmengine - INFO - Epoch(train) [81][1200/2569] lr: 4.0000e-02 eta: 13:11:07 time: 0.2649 data_time: 0.0086 memory: 5828 grad_norm: 3.1026 loss: 2.1950 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1950 2023/06/05 07:46:22 - mmengine - INFO - Epoch(train) [81][1220/2569] lr: 4.0000e-02 eta: 13:11:01 time: 0.2581 data_time: 0.0072 memory: 5828 grad_norm: 3.1535 loss: 2.2308 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2308 2023/06/05 07:46:28 - mmengine - INFO - Epoch(train) [81][1240/2569] lr: 4.0000e-02 eta: 13:10:56 time: 0.2721 data_time: 0.0073 memory: 5828 grad_norm: 3.1334 loss: 2.4706 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4706 2023/06/05 07:46:33 - mmengine - INFO - Epoch(train) [81][1260/2569] lr: 4.0000e-02 eta: 13:10:51 time: 0.2649 data_time: 0.0078 memory: 5828 grad_norm: 3.1586 loss: 2.3851 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3851 2023/06/05 07:46:38 - mmengine - INFO - Epoch(train) [81][1280/2569] lr: 4.0000e-02 eta: 13:10:46 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 3.1329 loss: 2.4363 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4363 2023/06/05 07:46:44 - mmengine - INFO - Epoch(train) [81][1300/2569] lr: 4.0000e-02 eta: 13:10:40 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 3.1965 loss: 2.6261 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6261 2023/06/05 07:46:49 - mmengine - INFO - Epoch(train) [81][1320/2569] lr: 4.0000e-02 eta: 13:10:35 time: 0.2669 data_time: 0.0083 memory: 5828 grad_norm: 3.1704 loss: 2.3997 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3997 2023/06/05 07:46:54 - mmengine - INFO - Epoch(train) [81][1340/2569] lr: 4.0000e-02 eta: 13:10:30 time: 0.2667 data_time: 0.0077 memory: 5828 grad_norm: 3.1157 loss: 2.4847 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4847 2023/06/05 07:47:00 - mmengine - INFO - Epoch(train) [81][1360/2569] lr: 4.0000e-02 eta: 13:10:25 time: 0.2697 data_time: 0.0074 memory: 5828 grad_norm: 3.1371 loss: 2.6894 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6894 2023/06/05 07:47:05 - mmengine - INFO - Epoch(train) [81][1380/2569] lr: 4.0000e-02 eta: 13:10:19 time: 0.2587 data_time: 0.0077 memory: 5828 grad_norm: 3.0935 loss: 2.4074 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4074 2023/06/05 07:47:10 - mmengine - INFO - Epoch(train) [81][1400/2569] lr: 4.0000e-02 eta: 13:10:14 time: 0.2699 data_time: 0.0078 memory: 5828 grad_norm: 3.1065 loss: 2.5899 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5899 2023/06/05 07:47:15 - mmengine - INFO - Epoch(train) [81][1420/2569] lr: 4.0000e-02 eta: 13:10:08 time: 0.2579 data_time: 0.0070 memory: 5828 grad_norm: 3.1803 loss: 2.5872 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5872 2023/06/05 07:47:21 - mmengine - INFO - Epoch(train) [81][1440/2569] lr: 4.0000e-02 eta: 13:10:03 time: 0.2700 data_time: 0.0077 memory: 5828 grad_norm: 3.1307 loss: 2.9352 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9352 2023/06/05 07:47:26 - mmengine - INFO - Epoch(train) [81][1460/2569] lr: 4.0000e-02 eta: 13:09:58 time: 0.2597 data_time: 0.0085 memory: 5828 grad_norm: 3.1468 loss: 2.5700 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5700 2023/06/05 07:47:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:47:31 - mmengine - INFO - Epoch(train) [81][1480/2569] lr: 4.0000e-02 eta: 13:09:52 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 3.0439 loss: 2.4771 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4771 2023/06/05 07:47:37 - mmengine - INFO - Epoch(train) [81][1500/2569] lr: 4.0000e-02 eta: 13:09:47 time: 0.2717 data_time: 0.0072 memory: 5828 grad_norm: 3.0848 loss: 2.4403 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4403 2023/06/05 07:47:42 - mmengine - INFO - Epoch(train) [81][1520/2569] lr: 4.0000e-02 eta: 13:09:42 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 3.1144 loss: 2.6591 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 2.6591 2023/06/05 07:47:47 - mmengine - INFO - Epoch(train) [81][1540/2569] lr: 4.0000e-02 eta: 13:09:37 time: 0.2660 data_time: 0.0072 memory: 5828 grad_norm: 3.1694 loss: 2.5145 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5145 2023/06/05 07:47:53 - mmengine - INFO - Epoch(train) [81][1560/2569] lr: 4.0000e-02 eta: 13:09:31 time: 0.2590 data_time: 0.0072 memory: 5828 grad_norm: 3.1665 loss: 2.6580 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6580 2023/06/05 07:47:58 - mmengine - INFO - Epoch(train) [81][1580/2569] lr: 4.0000e-02 eta: 13:09:26 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 3.1598 loss: 2.4104 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4104 2023/06/05 07:48:03 - mmengine - INFO - Epoch(train) [81][1600/2569] lr: 4.0000e-02 eta: 13:09:20 time: 0.2588 data_time: 0.0082 memory: 5828 grad_norm: 3.1652 loss: 2.1404 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1404 2023/06/05 07:48:08 - mmengine - INFO - Epoch(train) [81][1620/2569] lr: 4.0000e-02 eta: 13:09:15 time: 0.2690 data_time: 0.0072 memory: 5828 grad_norm: 3.1441 loss: 2.5244 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5244 2023/06/05 07:48:14 - mmengine - INFO - Epoch(train) [81][1640/2569] lr: 4.0000e-02 eta: 13:09:10 time: 0.2569 data_time: 0.0080 memory: 5828 grad_norm: 3.1567 loss: 2.5915 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5915 2023/06/05 07:48:19 - mmengine - INFO - Epoch(train) [81][1660/2569] lr: 4.0000e-02 eta: 13:09:04 time: 0.2577 data_time: 0.0077 memory: 5828 grad_norm: 3.0837 loss: 2.3660 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3660 2023/06/05 07:48:24 - mmengine - INFO - Epoch(train) [81][1680/2569] lr: 4.0000e-02 eta: 13:08:59 time: 0.2653 data_time: 0.0079 memory: 5828 grad_norm: 3.1676 loss: 2.4563 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4563 2023/06/05 07:48:29 - mmengine - INFO - Epoch(train) [81][1700/2569] lr: 4.0000e-02 eta: 13:08:53 time: 0.2589 data_time: 0.0082 memory: 5828 grad_norm: 3.1021 loss: 2.4348 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4348 2023/06/05 07:48:35 - mmengine - INFO - Epoch(train) [81][1720/2569] lr: 4.0000e-02 eta: 13:08:48 time: 0.2647 data_time: 0.0080 memory: 5828 grad_norm: 3.1624 loss: 2.2323 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2323 2023/06/05 07:48:40 - mmengine - INFO - Epoch(train) [81][1740/2569] lr: 4.0000e-02 eta: 13:08:43 time: 0.2737 data_time: 0.0074 memory: 5828 grad_norm: 3.1431 loss: 2.5878 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5878 2023/06/05 07:48:45 - mmengine - INFO - Epoch(train) [81][1760/2569] lr: 4.0000e-02 eta: 13:08:38 time: 0.2640 data_time: 0.0078 memory: 5828 grad_norm: 3.0513 loss: 2.4753 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4753 2023/06/05 07:48:51 - mmengine - INFO - Epoch(train) [81][1780/2569] lr: 4.0000e-02 eta: 13:08:32 time: 0.2638 data_time: 0.0079 memory: 5828 grad_norm: 3.1052 loss: 2.4267 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4267 2023/06/05 07:48:56 - mmengine - INFO - Epoch(train) [81][1800/2569] lr: 4.0000e-02 eta: 13:08:27 time: 0.2642 data_time: 0.0091 memory: 5828 grad_norm: 3.1239 loss: 2.5839 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5839 2023/06/05 07:49:01 - mmengine - INFO - Epoch(train) [81][1820/2569] lr: 4.0000e-02 eta: 13:08:22 time: 0.2730 data_time: 0.0073 memory: 5828 grad_norm: 3.1115 loss: 2.1384 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.1384 2023/06/05 07:49:07 - mmengine - INFO - Epoch(train) [81][1840/2569] lr: 4.0000e-02 eta: 13:08:16 time: 0.2606 data_time: 0.0080 memory: 5828 grad_norm: 3.1457 loss: 2.6438 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6438 2023/06/05 07:49:12 - mmengine - INFO - Epoch(train) [81][1860/2569] lr: 4.0000e-02 eta: 13:08:11 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 3.0945 loss: 2.6248 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6248 2023/06/05 07:49:17 - mmengine - INFO - Epoch(train) [81][1880/2569] lr: 4.0000e-02 eta: 13:08:06 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 3.1479 loss: 2.2590 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2590 2023/06/05 07:49:23 - mmengine - INFO - Epoch(train) [81][1900/2569] lr: 4.0000e-02 eta: 13:08:00 time: 0.2688 data_time: 0.0076 memory: 5828 grad_norm: 3.1791 loss: 2.9571 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9571 2023/06/05 07:49:28 - mmengine - INFO - Epoch(train) [81][1920/2569] lr: 4.0000e-02 eta: 13:07:55 time: 0.2664 data_time: 0.0078 memory: 5828 grad_norm: 3.1318 loss: 2.5753 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5753 2023/06/05 07:49:33 - mmengine - INFO - Epoch(train) [81][1940/2569] lr: 4.0000e-02 eta: 13:07:50 time: 0.2695 data_time: 0.0076 memory: 5828 grad_norm: 3.1124 loss: 2.7957 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7957 2023/06/05 07:49:39 - mmengine - INFO - Epoch(train) [81][1960/2569] lr: 4.0000e-02 eta: 13:07:44 time: 0.2614 data_time: 0.0076 memory: 5828 grad_norm: 3.1460 loss: 2.5217 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5217 2023/06/05 07:49:44 - mmengine - INFO - Epoch(train) [81][1980/2569] lr: 4.0000e-02 eta: 13:07:39 time: 0.2746 data_time: 0.0073 memory: 5828 grad_norm: 3.1091 loss: 2.2998 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2998 2023/06/05 07:49:49 - mmengine - INFO - Epoch(train) [81][2000/2569] lr: 4.0000e-02 eta: 13:07:34 time: 0.2636 data_time: 0.0078 memory: 5828 grad_norm: 3.1905 loss: 2.7642 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7642 2023/06/05 07:49:54 - mmengine - INFO - Epoch(train) [81][2020/2569] lr: 4.0000e-02 eta: 13:07:28 time: 0.2584 data_time: 0.0081 memory: 5828 grad_norm: 3.1800 loss: 2.5578 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5578 2023/06/05 07:50:00 - mmengine - INFO - Epoch(train) [81][2040/2569] lr: 4.0000e-02 eta: 13:07:23 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 3.1491 loss: 2.3131 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3131 2023/06/05 07:50:05 - mmengine - INFO - Epoch(train) [81][2060/2569] lr: 4.0000e-02 eta: 13:07:18 time: 0.2690 data_time: 0.0070 memory: 5828 grad_norm: 3.1808 loss: 2.4523 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4523 2023/06/05 07:50:11 - mmengine - INFO - Epoch(train) [81][2080/2569] lr: 4.0000e-02 eta: 13:07:13 time: 0.2678 data_time: 0.0074 memory: 5828 grad_norm: 3.1868 loss: 2.6450 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6450 2023/06/05 07:50:16 - mmengine - INFO - Epoch(train) [81][2100/2569] lr: 4.0000e-02 eta: 13:07:07 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.1650 loss: 2.5982 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5982 2023/06/05 07:50:21 - mmengine - INFO - Epoch(train) [81][2120/2569] lr: 4.0000e-02 eta: 13:07:02 time: 0.2691 data_time: 0.0075 memory: 5828 grad_norm: 3.2169 loss: 2.7673 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7673 2023/06/05 07:50:27 - mmengine - INFO - Epoch(train) [81][2140/2569] lr: 4.0000e-02 eta: 13:06:57 time: 0.2683 data_time: 0.0076 memory: 5828 grad_norm: 3.1019 loss: 2.5889 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5889 2023/06/05 07:50:32 - mmengine - INFO - Epoch(train) [81][2160/2569] lr: 4.0000e-02 eta: 13:06:51 time: 0.2578 data_time: 0.0079 memory: 5828 grad_norm: 3.1082 loss: 2.4451 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4451 2023/06/05 07:50:37 - mmengine - INFO - Epoch(train) [81][2180/2569] lr: 4.0000e-02 eta: 13:06:46 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 3.1240 loss: 2.4377 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4377 2023/06/05 07:50:43 - mmengine - INFO - Epoch(train) [81][2200/2569] lr: 4.0000e-02 eta: 13:06:41 time: 0.2711 data_time: 0.0075 memory: 5828 grad_norm: 3.0927 loss: 2.7026 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7026 2023/06/05 07:50:48 - mmengine - INFO - Epoch(train) [81][2220/2569] lr: 4.0000e-02 eta: 13:06:35 time: 0.2605 data_time: 0.0071 memory: 5828 grad_norm: 3.0664 loss: 2.4879 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4879 2023/06/05 07:50:53 - mmengine - INFO - Epoch(train) [81][2240/2569] lr: 4.0000e-02 eta: 13:06:30 time: 0.2728 data_time: 0.0075 memory: 5828 grad_norm: 3.1178 loss: 2.5442 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5442 2023/06/05 07:50:58 - mmengine - INFO - Epoch(train) [81][2260/2569] lr: 4.0000e-02 eta: 13:06:25 time: 0.2604 data_time: 0.0074 memory: 5828 grad_norm: 3.1373 loss: 2.6079 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6079 2023/06/05 07:51:04 - mmengine - INFO - Epoch(train) [81][2280/2569] lr: 4.0000e-02 eta: 13:06:20 time: 0.2680 data_time: 0.0081 memory: 5828 grad_norm: 3.0337 loss: 2.4601 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4601 2023/06/05 07:51:09 - mmengine - INFO - Epoch(train) [81][2300/2569] lr: 4.0000e-02 eta: 13:06:14 time: 0.2577 data_time: 0.0077 memory: 5828 grad_norm: 3.1157 loss: 2.6844 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6844 2023/06/05 07:51:14 - mmengine - INFO - Epoch(train) [81][2320/2569] lr: 4.0000e-02 eta: 13:06:09 time: 0.2657 data_time: 0.0077 memory: 5828 grad_norm: 3.0979 loss: 2.8395 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8395 2023/06/05 07:51:20 - mmengine - INFO - Epoch(train) [81][2340/2569] lr: 4.0000e-02 eta: 13:06:03 time: 0.2630 data_time: 0.0085 memory: 5828 grad_norm: 3.1462 loss: 2.6509 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6509 2023/06/05 07:51:25 - mmengine - INFO - Epoch(train) [81][2360/2569] lr: 4.0000e-02 eta: 13:05:58 time: 0.2649 data_time: 0.0078 memory: 5828 grad_norm: 3.1095 loss: 2.6804 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6804 2023/06/05 07:51:30 - mmengine - INFO - Epoch(train) [81][2380/2569] lr: 4.0000e-02 eta: 13:05:53 time: 0.2600 data_time: 0.0077 memory: 5828 grad_norm: 3.2071 loss: 2.6776 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6776 2023/06/05 07:51:36 - mmengine - INFO - Epoch(train) [81][2400/2569] lr: 4.0000e-02 eta: 13:05:48 time: 0.2825 data_time: 0.0076 memory: 5828 grad_norm: 3.1683 loss: 2.7901 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7901 2023/06/05 07:51:41 - mmengine - INFO - Epoch(train) [81][2420/2569] lr: 4.0000e-02 eta: 13:05:42 time: 0.2605 data_time: 0.0079 memory: 5828 grad_norm: 3.1654 loss: 2.6487 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6487 2023/06/05 07:51:46 - mmengine - INFO - Epoch(train) [81][2440/2569] lr: 4.0000e-02 eta: 13:05:37 time: 0.2620 data_time: 0.0074 memory: 5828 grad_norm: 3.1148 loss: 2.5839 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5839 2023/06/05 07:51:51 - mmengine - INFO - Epoch(train) [81][2460/2569] lr: 4.0000e-02 eta: 13:05:31 time: 0.2580 data_time: 0.0073 memory: 5828 grad_norm: 3.1306 loss: 2.7305 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7305 2023/06/05 07:51:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:51:57 - mmengine - INFO - Epoch(train) [81][2480/2569] lr: 4.0000e-02 eta: 13:05:26 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 3.0860 loss: 2.1596 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1596 2023/06/05 07:52:02 - mmengine - INFO - Epoch(train) [81][2500/2569] lr: 4.0000e-02 eta: 13:05:21 time: 0.2674 data_time: 0.0070 memory: 5828 grad_norm: 3.2048 loss: 2.5146 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5146 2023/06/05 07:52:07 - mmengine - INFO - Epoch(train) [81][2520/2569] lr: 4.0000e-02 eta: 13:05:16 time: 0.2671 data_time: 0.0075 memory: 5828 grad_norm: 3.1558 loss: 2.4305 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4305 2023/06/05 07:52:13 - mmengine - INFO - Epoch(train) [81][2540/2569] lr: 4.0000e-02 eta: 13:05:10 time: 0.2731 data_time: 0.0073 memory: 5828 grad_norm: 3.0948 loss: 2.4268 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4268 2023/06/05 07:52:18 - mmengine - INFO - Epoch(train) [81][2560/2569] lr: 4.0000e-02 eta: 13:05:05 time: 0.2579 data_time: 0.0077 memory: 5828 grad_norm: 3.1675 loss: 2.5155 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5155 2023/06/05 07:52:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:52:20 - mmengine - INFO - Epoch(train) [81][2569/2569] lr: 4.0000e-02 eta: 13:05:02 time: 0.2509 data_time: 0.0071 memory: 5828 grad_norm: 3.1150 loss: 2.6994 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 2.6994 2023/06/05 07:52:27 - mmengine - INFO - Epoch(train) [82][ 20/2569] lr: 4.0000e-02 eta: 13:04:58 time: 0.3368 data_time: 0.0485 memory: 5828 grad_norm: 3.0724 loss: 2.3687 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3687 2023/06/05 07:52:32 - mmengine - INFO - Epoch(train) [82][ 40/2569] lr: 4.0000e-02 eta: 13:04:53 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 3.1485 loss: 2.5934 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5934 2023/06/05 07:52:38 - mmengine - INFO - Epoch(train) [82][ 60/2569] lr: 4.0000e-02 eta: 13:04:47 time: 0.2604 data_time: 0.0073 memory: 5828 grad_norm: 3.1668 loss: 2.5112 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5112 2023/06/05 07:52:43 - mmengine - INFO - Epoch(train) [82][ 80/2569] lr: 4.0000e-02 eta: 13:04:42 time: 0.2609 data_time: 0.0071 memory: 5828 grad_norm: 3.2600 loss: 2.5328 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5328 2023/06/05 07:52:48 - mmengine - INFO - Epoch(train) [82][ 100/2569] lr: 4.0000e-02 eta: 13:04:37 time: 0.2596 data_time: 0.0078 memory: 5828 grad_norm: 3.0791 loss: 2.6219 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6219 2023/06/05 07:52:53 - mmengine - INFO - Epoch(train) [82][ 120/2569] lr: 4.0000e-02 eta: 13:04:31 time: 0.2590 data_time: 0.0076 memory: 5828 grad_norm: 3.0975 loss: 2.3903 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3903 2023/06/05 07:52:58 - mmengine - INFO - Epoch(train) [82][ 140/2569] lr: 4.0000e-02 eta: 13:04:26 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 3.1175 loss: 2.3816 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3816 2023/06/05 07:53:04 - mmengine - INFO - Epoch(train) [82][ 160/2569] lr: 4.0000e-02 eta: 13:04:20 time: 0.2596 data_time: 0.0075 memory: 5828 grad_norm: 3.1221 loss: 2.6662 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6662 2023/06/05 07:53:09 - mmengine - INFO - Epoch(train) [82][ 180/2569] lr: 4.0000e-02 eta: 13:04:15 time: 0.2811 data_time: 0.0071 memory: 5828 grad_norm: 3.0621 loss: 2.2657 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2657 2023/06/05 07:53:14 - mmengine - INFO - Epoch(train) [82][ 200/2569] lr: 4.0000e-02 eta: 13:04:10 time: 0.2584 data_time: 0.0081 memory: 5828 grad_norm: 3.1137 loss: 2.6932 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6932 2023/06/05 07:53:20 - mmengine - INFO - Epoch(train) [82][ 220/2569] lr: 4.0000e-02 eta: 13:04:05 time: 0.2588 data_time: 0.0072 memory: 5828 grad_norm: 3.1555 loss: 2.4377 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4377 2023/06/05 07:53:25 - mmengine - INFO - Epoch(train) [82][ 240/2569] lr: 4.0000e-02 eta: 13:03:59 time: 0.2693 data_time: 0.0073 memory: 5828 grad_norm: 3.1107 loss: 2.5471 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5471 2023/06/05 07:53:30 - mmengine - INFO - Epoch(train) [82][ 260/2569] lr: 4.0000e-02 eta: 13:03:54 time: 0.2581 data_time: 0.0076 memory: 5828 grad_norm: 3.1495 loss: 2.4527 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4527 2023/06/05 07:53:36 - mmengine - INFO - Epoch(train) [82][ 280/2569] lr: 4.0000e-02 eta: 13:03:49 time: 0.2778 data_time: 0.0074 memory: 5828 grad_norm: 3.1045 loss: 2.6195 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6195 2023/06/05 07:53:41 - mmengine - INFO - Epoch(train) [82][ 300/2569] lr: 4.0000e-02 eta: 13:03:43 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 3.1016 loss: 2.6644 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6644 2023/06/05 07:53:46 - mmengine - INFO - Epoch(train) [82][ 320/2569] lr: 4.0000e-02 eta: 13:03:38 time: 0.2727 data_time: 0.0075 memory: 5828 grad_norm: 3.1979 loss: 2.7285 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7285 2023/06/05 07:53:52 - mmengine - INFO - Epoch(train) [82][ 340/2569] lr: 4.0000e-02 eta: 13:03:33 time: 0.2591 data_time: 0.0071 memory: 5828 grad_norm: 3.1018 loss: 2.5137 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5137 2023/06/05 07:53:57 - mmengine - INFO - Epoch(train) [82][ 360/2569] lr: 4.0000e-02 eta: 13:03:27 time: 0.2585 data_time: 0.0072 memory: 5828 grad_norm: 3.1913 loss: 2.5305 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5305 2023/06/05 07:54:02 - mmengine - INFO - Epoch(train) [82][ 380/2569] lr: 4.0000e-02 eta: 13:03:22 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 3.0747 loss: 2.2688 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2688 2023/06/05 07:54:08 - mmengine - INFO - Epoch(train) [82][ 400/2569] lr: 4.0000e-02 eta: 13:03:17 time: 0.2766 data_time: 0.0074 memory: 5828 grad_norm: 3.1335 loss: 2.6458 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6458 2023/06/05 07:54:13 - mmengine - INFO - Epoch(train) [82][ 420/2569] lr: 4.0000e-02 eta: 13:03:12 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 3.1684 loss: 2.1815 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1815 2023/06/05 07:54:18 - mmengine - INFO - Epoch(train) [82][ 440/2569] lr: 4.0000e-02 eta: 13:03:06 time: 0.2593 data_time: 0.0075 memory: 5828 grad_norm: 3.1559 loss: 2.2837 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2837 2023/06/05 07:54:24 - mmengine - INFO - Epoch(train) [82][ 460/2569] lr: 4.0000e-02 eta: 13:03:01 time: 0.2669 data_time: 0.0083 memory: 5828 grad_norm: 3.0803 loss: 2.5785 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5785 2023/06/05 07:54:29 - mmengine - INFO - Epoch(train) [82][ 480/2569] lr: 4.0000e-02 eta: 13:02:56 time: 0.2698 data_time: 0.0072 memory: 5828 grad_norm: 3.1458 loss: 2.5647 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5647 2023/06/05 07:54:34 - mmengine - INFO - Epoch(train) [82][ 500/2569] lr: 4.0000e-02 eta: 13:02:50 time: 0.2766 data_time: 0.0074 memory: 5828 grad_norm: 3.1605 loss: 2.5763 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5763 2023/06/05 07:54:40 - mmengine - INFO - Epoch(train) [82][ 520/2569] lr: 4.0000e-02 eta: 13:02:45 time: 0.2701 data_time: 0.0072 memory: 5828 grad_norm: 3.1663 loss: 2.1266 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1266 2023/06/05 07:54:45 - mmengine - INFO - Epoch(train) [82][ 540/2569] lr: 4.0000e-02 eta: 13:02:40 time: 0.2695 data_time: 0.0083 memory: 5828 grad_norm: 3.0776 loss: 2.5766 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5766 2023/06/05 07:54:51 - mmengine - INFO - Epoch(train) [82][ 560/2569] lr: 4.0000e-02 eta: 13:02:35 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 3.1425 loss: 2.5631 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5631 2023/06/05 07:54:56 - mmengine - INFO - Epoch(train) [82][ 580/2569] lr: 4.0000e-02 eta: 13:02:29 time: 0.2598 data_time: 0.0076 memory: 5828 grad_norm: 3.0770 loss: 2.2933 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2933 2023/06/05 07:55:01 - mmengine - INFO - Epoch(train) [82][ 600/2569] lr: 4.0000e-02 eta: 13:02:24 time: 0.2612 data_time: 0.0077 memory: 5828 grad_norm: 3.1911 loss: 2.0236 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0236 2023/06/05 07:55:06 - mmengine - INFO - Epoch(train) [82][ 620/2569] lr: 4.0000e-02 eta: 13:02:18 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 3.1879 loss: 2.4654 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4654 2023/06/05 07:55:11 - mmengine - INFO - Epoch(train) [82][ 640/2569] lr: 4.0000e-02 eta: 13:02:13 time: 0.2595 data_time: 0.0074 memory: 5828 grad_norm: 3.1183 loss: 2.3578 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3578 2023/06/05 07:55:17 - mmengine - INFO - Epoch(train) [82][ 660/2569] lr: 4.0000e-02 eta: 13:02:08 time: 0.2584 data_time: 0.0074 memory: 5828 grad_norm: 3.1715 loss: 2.2862 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2862 2023/06/05 07:55:22 - mmengine - INFO - Epoch(train) [82][ 680/2569] lr: 4.0000e-02 eta: 13:02:02 time: 0.2596 data_time: 0.0078 memory: 5828 grad_norm: 3.1491 loss: 2.3295 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3295 2023/06/05 07:55:27 - mmengine - INFO - Epoch(train) [82][ 700/2569] lr: 4.0000e-02 eta: 13:01:57 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 3.1239 loss: 2.6677 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6677 2023/06/05 07:55:32 - mmengine - INFO - Epoch(train) [82][ 720/2569] lr: 4.0000e-02 eta: 13:01:51 time: 0.2590 data_time: 0.0073 memory: 5828 grad_norm: 3.1321 loss: 2.5899 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5899 2023/06/05 07:55:38 - mmengine - INFO - Epoch(train) [82][ 740/2569] lr: 4.0000e-02 eta: 13:01:46 time: 0.2749 data_time: 0.0075 memory: 5828 grad_norm: 3.1388 loss: 2.4224 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4224 2023/06/05 07:55:43 - mmengine - INFO - Epoch(train) [82][ 760/2569] lr: 4.0000e-02 eta: 13:01:41 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 3.1330 loss: 2.7027 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7027 2023/06/05 07:55:49 - mmengine - INFO - Epoch(train) [82][ 780/2569] lr: 4.0000e-02 eta: 13:01:36 time: 0.2684 data_time: 0.0076 memory: 5828 grad_norm: 3.2102 loss: 2.6388 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6388 2023/06/05 07:55:54 - mmengine - INFO - Epoch(train) [82][ 800/2569] lr: 4.0000e-02 eta: 13:01:30 time: 0.2584 data_time: 0.0077 memory: 5828 grad_norm: 3.1362 loss: 2.3507 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3507 2023/06/05 07:55:59 - mmengine - INFO - Epoch(train) [82][ 820/2569] lr: 4.0000e-02 eta: 13:01:25 time: 0.2668 data_time: 0.0069 memory: 5828 grad_norm: 3.1104 loss: 2.5898 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5898 2023/06/05 07:56:04 - mmengine - INFO - Epoch(train) [82][ 840/2569] lr: 4.0000e-02 eta: 13:01:19 time: 0.2577 data_time: 0.0079 memory: 5828 grad_norm: 3.1287 loss: 2.5066 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5066 2023/06/05 07:56:10 - mmengine - INFO - Epoch(train) [82][ 860/2569] lr: 4.0000e-02 eta: 13:01:14 time: 0.2709 data_time: 0.0072 memory: 5828 grad_norm: 3.1863 loss: 2.3957 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3957 2023/06/05 07:56:15 - mmengine - INFO - Epoch(train) [82][ 880/2569] lr: 4.0000e-02 eta: 13:01:09 time: 0.2629 data_time: 0.0080 memory: 5828 grad_norm: 3.2105 loss: 2.4366 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4366 2023/06/05 07:56:20 - mmengine - INFO - Epoch(train) [82][ 900/2569] lr: 4.0000e-02 eta: 13:01:03 time: 0.2583 data_time: 0.0081 memory: 5828 grad_norm: 3.1530 loss: 2.7341 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7341 2023/06/05 07:56:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 07:56:25 - mmengine - INFO - Epoch(train) [82][ 920/2569] lr: 4.0000e-02 eta: 13:00:58 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 3.2019 loss: 2.6247 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6247 2023/06/05 07:56:31 - mmengine - INFO - Epoch(train) [82][ 940/2569] lr: 4.0000e-02 eta: 13:00:53 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 3.0923 loss: 2.1398 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.1398 2023/06/05 07:56:36 - mmengine - INFO - Epoch(train) [82][ 960/2569] lr: 4.0000e-02 eta: 13:00:47 time: 0.2603 data_time: 0.0077 memory: 5828 grad_norm: 3.0407 loss: 2.6042 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6042 2023/06/05 07:56:41 - mmengine - INFO - Epoch(train) [82][ 980/2569] lr: 4.0000e-02 eta: 13:00:42 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 3.1782 loss: 2.4588 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4588 2023/06/05 07:56:46 - mmengine - INFO - Epoch(train) [82][1000/2569] lr: 4.0000e-02 eta: 13:00:37 time: 0.2621 data_time: 0.0072 memory: 5828 grad_norm: 3.0515 loss: 2.4074 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4074 2023/06/05 07:56:52 - mmengine - INFO - Epoch(train) [82][1020/2569] lr: 4.0000e-02 eta: 13:00:31 time: 0.2601 data_time: 0.0072 memory: 5828 grad_norm: 3.1716 loss: 2.6304 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6304 2023/06/05 07:56:57 - mmengine - INFO - Epoch(train) [82][1040/2569] lr: 4.0000e-02 eta: 13:00:26 time: 0.2600 data_time: 0.0074 memory: 5828 grad_norm: 3.1303 loss: 2.1960 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1960 2023/06/05 07:57:02 - mmengine - INFO - Epoch(train) [82][1060/2569] lr: 4.0000e-02 eta: 13:00:20 time: 0.2597 data_time: 0.0070 memory: 5828 grad_norm: 3.1002 loss: 2.5620 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5620 2023/06/05 07:57:08 - mmengine - INFO - Epoch(train) [82][1080/2569] lr: 4.0000e-02 eta: 13:00:15 time: 0.2817 data_time: 0.0080 memory: 5828 grad_norm: 3.0822 loss: 2.2716 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2716 2023/06/05 07:57:13 - mmengine - INFO - Epoch(train) [82][1100/2569] lr: 4.0000e-02 eta: 13:00:10 time: 0.2730 data_time: 0.0072 memory: 5828 grad_norm: 3.0871 loss: 2.7982 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7982 2023/06/05 07:57:18 - mmengine - INFO - Epoch(train) [82][1120/2569] lr: 4.0000e-02 eta: 13:00:05 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.1222 loss: 2.3749 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.3749 2023/06/05 07:57:24 - mmengine - INFO - Epoch(train) [82][1140/2569] lr: 4.0000e-02 eta: 12:59:59 time: 0.2692 data_time: 0.0074 memory: 5828 grad_norm: 3.1890 loss: 2.5425 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5425 2023/06/05 07:57:29 - mmengine - INFO - Epoch(train) [82][1160/2569] lr: 4.0000e-02 eta: 12:59:54 time: 0.2584 data_time: 0.0072 memory: 5828 grad_norm: 3.1504 loss: 2.5756 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5756 2023/06/05 07:57:34 - mmengine - INFO - Epoch(train) [82][1180/2569] lr: 4.0000e-02 eta: 12:59:49 time: 0.2625 data_time: 0.0070 memory: 5828 grad_norm: 3.2370 loss: 2.8541 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8541 2023/06/05 07:57:39 - mmengine - INFO - Epoch(train) [82][1200/2569] lr: 4.0000e-02 eta: 12:59:43 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 3.1039 loss: 2.6059 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6059 2023/06/05 07:57:45 - mmengine - INFO - Epoch(train) [82][1220/2569] lr: 4.0000e-02 eta: 12:59:38 time: 0.2725 data_time: 0.0072 memory: 5828 grad_norm: 3.0832 loss: 2.2901 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2901 2023/06/05 07:57:50 - mmengine - INFO - Epoch(train) [82][1240/2569] lr: 4.0000e-02 eta: 12:59:33 time: 0.2592 data_time: 0.0073 memory: 5828 grad_norm: 3.1924 loss: 2.6883 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6883 2023/06/05 07:57:55 - mmengine - INFO - Epoch(train) [82][1260/2569] lr: 4.0000e-02 eta: 12:59:27 time: 0.2590 data_time: 0.0070 memory: 5828 grad_norm: 3.0868 loss: 2.6652 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6652 2023/06/05 07:58:00 - mmengine - INFO - Epoch(train) [82][1280/2569] lr: 4.0000e-02 eta: 12:59:22 time: 0.2616 data_time: 0.0080 memory: 5828 grad_norm: 3.2104 loss: 2.5889 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5889 2023/06/05 07:58:06 - mmengine - INFO - Epoch(train) [82][1300/2569] lr: 4.0000e-02 eta: 12:59:16 time: 0.2594 data_time: 0.0074 memory: 5828 grad_norm: 3.1117 loss: 2.3750 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.3750 2023/06/05 07:58:11 - mmengine - INFO - Epoch(train) [82][1320/2569] lr: 4.0000e-02 eta: 12:59:11 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 3.1653 loss: 2.6657 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6657 2023/06/05 07:58:16 - mmengine - INFO - Epoch(train) [82][1340/2569] lr: 4.0000e-02 eta: 12:59:06 time: 0.2588 data_time: 0.0074 memory: 5828 grad_norm: 3.1391 loss: 2.2566 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2566 2023/06/05 07:58:21 - mmengine - INFO - Epoch(train) [82][1360/2569] lr: 4.0000e-02 eta: 12:59:00 time: 0.2654 data_time: 0.0071 memory: 5828 grad_norm: 3.1746 loss: 2.4478 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4478 2023/06/05 07:58:27 - mmengine - INFO - Epoch(train) [82][1380/2569] lr: 4.0000e-02 eta: 12:58:55 time: 0.2715 data_time: 0.0078 memory: 5828 grad_norm: 3.1875 loss: 2.3722 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3722 2023/06/05 07:58:32 - mmengine - INFO - Epoch(train) [82][1400/2569] lr: 4.0000e-02 eta: 12:58:50 time: 0.2630 data_time: 0.0075 memory: 5828 grad_norm: 3.1617 loss: 2.6587 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6587 2023/06/05 07:58:37 - mmengine - INFO - Epoch(train) [82][1420/2569] lr: 4.0000e-02 eta: 12:58:44 time: 0.2599 data_time: 0.0078 memory: 5828 grad_norm: 3.1653 loss: 2.5485 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5485 2023/06/05 07:58:43 - mmengine - INFO - Epoch(train) [82][1440/2569] lr: 4.0000e-02 eta: 12:58:39 time: 0.2644 data_time: 0.0077 memory: 5828 grad_norm: 3.1187 loss: 2.8503 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8503 2023/06/05 07:58:48 - mmengine - INFO - Epoch(train) [82][1460/2569] lr: 4.0000e-02 eta: 12:58:34 time: 0.2576 data_time: 0.0076 memory: 5828 grad_norm: 3.1331 loss: 2.6691 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6691 2023/06/05 07:58:53 - mmengine - INFO - Epoch(train) [82][1480/2569] lr: 4.0000e-02 eta: 12:58:28 time: 0.2633 data_time: 0.0077 memory: 5828 grad_norm: 3.1751 loss: 2.7648 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7648 2023/06/05 07:58:58 - mmengine - INFO - Epoch(train) [82][1500/2569] lr: 4.0000e-02 eta: 12:58:23 time: 0.2592 data_time: 0.0071 memory: 5828 grad_norm: 3.1389 loss: 2.5937 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5937 2023/06/05 07:59:04 - mmengine - INFO - Epoch(train) [82][1520/2569] lr: 4.0000e-02 eta: 12:58:17 time: 0.2695 data_time: 0.0072 memory: 5828 grad_norm: 3.1324 loss: 2.6313 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6313 2023/06/05 07:59:09 - mmengine - INFO - Epoch(train) [82][1540/2569] lr: 4.0000e-02 eta: 12:58:12 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 3.0907 loss: 2.4981 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4981 2023/06/05 07:59:15 - mmengine - INFO - Epoch(train) [82][1560/2569] lr: 4.0000e-02 eta: 12:58:07 time: 0.2756 data_time: 0.0074 memory: 5828 grad_norm: 3.0789 loss: 2.8835 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8835 2023/06/05 07:59:20 - mmengine - INFO - Epoch(train) [82][1580/2569] lr: 4.0000e-02 eta: 12:58:02 time: 0.2733 data_time: 0.0076 memory: 5828 grad_norm: 3.0945 loss: 2.5942 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5942 2023/06/05 07:59:25 - mmengine - INFO - Epoch(train) [82][1600/2569] lr: 4.0000e-02 eta: 12:57:57 time: 0.2702 data_time: 0.0069 memory: 5828 grad_norm: 3.1350 loss: 2.6011 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6011 2023/06/05 07:59:31 - mmengine - INFO - Epoch(train) [82][1620/2569] lr: 4.0000e-02 eta: 12:57:51 time: 0.2588 data_time: 0.0074 memory: 5828 grad_norm: 3.1536 loss: 2.8640 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8640 2023/06/05 07:59:36 - mmengine - INFO - Epoch(train) [82][1640/2569] lr: 4.0000e-02 eta: 12:57:46 time: 0.2746 data_time: 0.0076 memory: 5828 grad_norm: 3.0349 loss: 2.4690 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4690 2023/06/05 07:59:41 - mmengine - INFO - Epoch(train) [82][1660/2569] lr: 4.0000e-02 eta: 12:57:41 time: 0.2668 data_time: 0.0074 memory: 5828 grad_norm: 3.1307 loss: 2.7450 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7450 2023/06/05 07:59:47 - mmengine - INFO - Epoch(train) [82][1680/2569] lr: 4.0000e-02 eta: 12:57:35 time: 0.2628 data_time: 0.0083 memory: 5828 grad_norm: 3.0803 loss: 2.3404 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3404 2023/06/05 07:59:52 - mmengine - INFO - Epoch(train) [82][1700/2569] lr: 4.0000e-02 eta: 12:57:30 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 3.1596 loss: 2.4744 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4744 2023/06/05 07:59:57 - mmengine - INFO - Epoch(train) [82][1720/2569] lr: 4.0000e-02 eta: 12:57:25 time: 0.2575 data_time: 0.0078 memory: 5828 grad_norm: 3.0723 loss: 2.5859 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5859 2023/06/05 08:00:02 - mmengine - INFO - Epoch(train) [82][1740/2569] lr: 4.0000e-02 eta: 12:57:19 time: 0.2656 data_time: 0.0070 memory: 5828 grad_norm: 3.1082 loss: 2.5097 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5097 2023/06/05 08:00:08 - mmengine - INFO - Epoch(train) [82][1760/2569] lr: 4.0000e-02 eta: 12:57:14 time: 0.2582 data_time: 0.0075 memory: 5828 grad_norm: 3.1138 loss: 2.4571 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4571 2023/06/05 08:00:13 - mmengine - INFO - Epoch(train) [82][1780/2569] lr: 4.0000e-02 eta: 12:57:08 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 3.1576 loss: 2.5020 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5020 2023/06/05 08:00:18 - mmengine - INFO - Epoch(train) [82][1800/2569] lr: 4.0000e-02 eta: 12:57:03 time: 0.2677 data_time: 0.0075 memory: 5828 grad_norm: 3.1196 loss: 2.5407 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5407 2023/06/05 08:00:24 - mmengine - INFO - Epoch(train) [82][1820/2569] lr: 4.0000e-02 eta: 12:56:58 time: 0.2665 data_time: 0.0070 memory: 5828 grad_norm: 3.0804 loss: 2.7351 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7351 2023/06/05 08:00:29 - mmengine - INFO - Epoch(train) [82][1840/2569] lr: 4.0000e-02 eta: 12:56:53 time: 0.2690 data_time: 0.0074 memory: 5828 grad_norm: 3.0873 loss: 2.6392 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6392 2023/06/05 08:00:34 - mmengine - INFO - Epoch(train) [82][1860/2569] lr: 4.0000e-02 eta: 12:56:47 time: 0.2586 data_time: 0.0075 memory: 5828 grad_norm: 3.1969 loss: 2.8682 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.8682 2023/06/05 08:00:40 - mmengine - INFO - Epoch(train) [82][1880/2569] lr: 4.0000e-02 eta: 12:56:42 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 3.1471 loss: 2.5456 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5456 2023/06/05 08:00:45 - mmengine - INFO - Epoch(train) [82][1900/2569] lr: 4.0000e-02 eta: 12:56:37 time: 0.2646 data_time: 0.0070 memory: 5828 grad_norm: 3.0960 loss: 2.6422 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6422 2023/06/05 08:00:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:00:50 - mmengine - INFO - Epoch(train) [82][1920/2569] lr: 4.0000e-02 eta: 12:56:31 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.1284 loss: 2.4250 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4250 2023/06/05 08:00:56 - mmengine - INFO - Epoch(train) [82][1940/2569] lr: 4.0000e-02 eta: 12:56:26 time: 0.2698 data_time: 0.0073 memory: 5828 grad_norm: 3.0970 loss: 2.5560 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5560 2023/06/05 08:01:01 - mmengine - INFO - Epoch(train) [82][1960/2569] lr: 4.0000e-02 eta: 12:56:21 time: 0.2642 data_time: 0.0075 memory: 5828 grad_norm: 3.0943 loss: 2.4577 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4577 2023/06/05 08:01:06 - mmengine - INFO - Epoch(train) [82][1980/2569] lr: 4.0000e-02 eta: 12:56:15 time: 0.2735 data_time: 0.0072 memory: 5828 grad_norm: 3.0737 loss: 2.5166 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5166 2023/06/05 08:01:12 - mmengine - INFO - Epoch(train) [82][2000/2569] lr: 4.0000e-02 eta: 12:56:10 time: 0.2716 data_time: 0.0077 memory: 5828 grad_norm: 3.1392 loss: 2.5675 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5675 2023/06/05 08:01:17 - mmengine - INFO - Epoch(train) [82][2020/2569] lr: 4.0000e-02 eta: 12:56:05 time: 0.2666 data_time: 0.0076 memory: 5828 grad_norm: 3.0282 loss: 2.5573 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5573 2023/06/05 08:01:23 - mmengine - INFO - Epoch(train) [82][2040/2569] lr: 4.0000e-02 eta: 12:56:00 time: 0.2725 data_time: 0.0072 memory: 5828 grad_norm: 3.1630 loss: 2.2122 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2122 2023/06/05 08:01:28 - mmengine - INFO - Epoch(train) [82][2060/2569] lr: 4.0000e-02 eta: 12:55:54 time: 0.2628 data_time: 0.0077 memory: 5828 grad_norm: 3.0606 loss: 2.5589 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5589 2023/06/05 08:01:33 - mmengine - INFO - Epoch(train) [82][2080/2569] lr: 4.0000e-02 eta: 12:55:49 time: 0.2674 data_time: 0.0077 memory: 5828 grad_norm: 3.1868 loss: 2.7477 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7477 2023/06/05 08:01:39 - mmengine - INFO - Epoch(train) [82][2100/2569] lr: 4.0000e-02 eta: 12:55:44 time: 0.2761 data_time: 0.0072 memory: 5828 grad_norm: 3.1067 loss: 2.7563 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7563 2023/06/05 08:01:44 - mmengine - INFO - Epoch(train) [82][2120/2569] lr: 4.0000e-02 eta: 12:55:39 time: 0.2586 data_time: 0.0075 memory: 5828 grad_norm: 3.1082 loss: 2.4876 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4876 2023/06/05 08:01:49 - mmengine - INFO - Epoch(train) [82][2140/2569] lr: 4.0000e-02 eta: 12:55:33 time: 0.2716 data_time: 0.0073 memory: 5828 grad_norm: 3.1434 loss: 2.4208 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4208 2023/06/05 08:01:55 - mmengine - INFO - Epoch(train) [82][2160/2569] lr: 4.0000e-02 eta: 12:55:28 time: 0.2699 data_time: 0.0075 memory: 5828 grad_norm: 3.1438 loss: 2.7065 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7065 2023/06/05 08:02:00 - mmengine - INFO - Epoch(train) [82][2180/2569] lr: 4.0000e-02 eta: 12:55:23 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 3.1523 loss: 2.6038 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6038 2023/06/05 08:02:05 - mmengine - INFO - Epoch(train) [82][2200/2569] lr: 4.0000e-02 eta: 12:55:17 time: 0.2629 data_time: 0.0071 memory: 5828 grad_norm: 3.1537 loss: 2.3365 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3365 2023/06/05 08:02:11 - mmengine - INFO - Epoch(train) [82][2220/2569] lr: 4.0000e-02 eta: 12:55:12 time: 0.2674 data_time: 0.0074 memory: 5828 grad_norm: 3.0834 loss: 2.4508 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4508 2023/06/05 08:02:16 - mmengine - INFO - Epoch(train) [82][2240/2569] lr: 4.0000e-02 eta: 12:55:07 time: 0.2684 data_time: 0.0075 memory: 5828 grad_norm: 3.1190 loss: 2.6446 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6446 2023/06/05 08:02:21 - mmengine - INFO - Epoch(train) [82][2260/2569] lr: 4.0000e-02 eta: 12:55:01 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 3.0845 loss: 2.4501 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4501 2023/06/05 08:02:27 - mmengine - INFO - Epoch(train) [82][2280/2569] lr: 4.0000e-02 eta: 12:54:56 time: 0.2646 data_time: 0.0078 memory: 5828 grad_norm: 3.1616 loss: 2.5483 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5483 2023/06/05 08:02:32 - mmengine - INFO - Epoch(train) [82][2300/2569] lr: 4.0000e-02 eta: 12:54:51 time: 0.2642 data_time: 0.0075 memory: 5828 grad_norm: 3.1206 loss: 2.6150 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6150 2023/06/05 08:02:37 - mmengine - INFO - Epoch(train) [82][2320/2569] lr: 4.0000e-02 eta: 12:54:45 time: 0.2705 data_time: 0.0083 memory: 5828 grad_norm: 3.0375 loss: 2.7365 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7365 2023/06/05 08:02:43 - mmengine - INFO - Epoch(train) [82][2340/2569] lr: 4.0000e-02 eta: 12:54:40 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.1188 loss: 2.4347 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4347 2023/06/05 08:02:48 - mmengine - INFO - Epoch(train) [82][2360/2569] lr: 4.0000e-02 eta: 12:54:35 time: 0.2619 data_time: 0.0071 memory: 5828 grad_norm: 3.1098 loss: 2.3775 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3775 2023/06/05 08:02:53 - mmengine - INFO - Epoch(train) [82][2380/2569] lr: 4.0000e-02 eta: 12:54:29 time: 0.2647 data_time: 0.0072 memory: 5828 grad_norm: 3.0817 loss: 2.8044 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8044 2023/06/05 08:02:59 - mmengine - INFO - Epoch(train) [82][2400/2569] lr: 4.0000e-02 eta: 12:54:24 time: 0.2744 data_time: 0.0073 memory: 5828 grad_norm: 3.1098 loss: 2.4571 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4571 2023/06/05 08:03:04 - mmengine - INFO - Epoch(train) [82][2420/2569] lr: 4.0000e-02 eta: 12:54:19 time: 0.2641 data_time: 0.0079 memory: 5828 grad_norm: 3.2017 loss: 2.7391 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7391 2023/06/05 08:03:09 - mmengine - INFO - Epoch(train) [82][2440/2569] lr: 4.0000e-02 eta: 12:54:14 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 3.0873 loss: 2.3058 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3058 2023/06/05 08:03:15 - mmengine - INFO - Epoch(train) [82][2460/2569] lr: 4.0000e-02 eta: 12:54:08 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 3.1377 loss: 2.2119 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2119 2023/06/05 08:03:20 - mmengine - INFO - Epoch(train) [82][2480/2569] lr: 4.0000e-02 eta: 12:54:03 time: 0.2746 data_time: 0.0076 memory: 5828 grad_norm: 3.1578 loss: 2.5128 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5128 2023/06/05 08:03:25 - mmengine - INFO - Epoch(train) [82][2500/2569] lr: 4.0000e-02 eta: 12:53:58 time: 0.2632 data_time: 0.0082 memory: 5828 grad_norm: 3.1749 loss: 2.6318 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6318 2023/06/05 08:03:30 - mmengine - INFO - Epoch(train) [82][2520/2569] lr: 4.0000e-02 eta: 12:53:52 time: 0.2600 data_time: 0.0081 memory: 5828 grad_norm: 3.0758 loss: 2.6414 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6414 2023/06/05 08:03:36 - mmengine - INFO - Epoch(train) [82][2540/2569] lr: 4.0000e-02 eta: 12:53:47 time: 0.2631 data_time: 0.0075 memory: 5828 grad_norm: 3.1138 loss: 2.2084 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2084 2023/06/05 08:03:41 - mmengine - INFO - Epoch(train) [82][2560/2569] lr: 4.0000e-02 eta: 12:53:42 time: 0.2615 data_time: 0.0070 memory: 5828 grad_norm: 3.0766 loss: 2.6644 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6644 2023/06/05 08:03:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:03:43 - mmengine - INFO - Epoch(train) [82][2569/2569] lr: 4.0000e-02 eta: 12:53:39 time: 0.2558 data_time: 0.0070 memory: 5828 grad_norm: 3.0928 loss: 2.2834 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.2834 2023/06/05 08:03:50 - mmengine - INFO - Epoch(train) [83][ 20/2569] lr: 4.0000e-02 eta: 12:53:35 time: 0.3444 data_time: 0.0531 memory: 5828 grad_norm: 3.2017 loss: 2.6833 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6833 2023/06/05 08:03:56 - mmengine - INFO - Epoch(train) [83][ 40/2569] lr: 4.0000e-02 eta: 12:53:30 time: 0.2694 data_time: 0.0077 memory: 5828 grad_norm: 3.1112 loss: 2.2921 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2921 2023/06/05 08:04:01 - mmengine - INFO - Epoch(train) [83][ 60/2569] lr: 4.0000e-02 eta: 12:53:25 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 3.1409 loss: 2.3812 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3812 2023/06/05 08:04:06 - mmengine - INFO - Epoch(train) [83][ 80/2569] lr: 4.0000e-02 eta: 12:53:19 time: 0.2699 data_time: 0.0071 memory: 5828 grad_norm: 3.1932 loss: 2.4380 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4380 2023/06/05 08:04:12 - mmengine - INFO - Epoch(train) [83][ 100/2569] lr: 4.0000e-02 eta: 12:53:14 time: 0.2732 data_time: 0.0073 memory: 5828 grad_norm: 3.1156 loss: 2.5903 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5903 2023/06/05 08:04:17 - mmengine - INFO - Epoch(train) [83][ 120/2569] lr: 4.0000e-02 eta: 12:53:09 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 3.1491 loss: 2.5740 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5740 2023/06/05 08:04:22 - mmengine - INFO - Epoch(train) [83][ 140/2569] lr: 4.0000e-02 eta: 12:53:03 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 3.1145 loss: 2.7167 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7167 2023/06/05 08:04:27 - mmengine - INFO - Epoch(train) [83][ 160/2569] lr: 4.0000e-02 eta: 12:52:58 time: 0.2582 data_time: 0.0081 memory: 5828 grad_norm: 3.0969 loss: 2.3467 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3467 2023/06/05 08:04:33 - mmengine - INFO - Epoch(train) [83][ 180/2569] lr: 4.0000e-02 eta: 12:52:53 time: 0.2587 data_time: 0.0070 memory: 5828 grad_norm: 3.0925 loss: 2.6234 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6234 2023/06/05 08:04:38 - mmengine - INFO - Epoch(train) [83][ 200/2569] lr: 4.0000e-02 eta: 12:52:47 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 3.1649 loss: 2.4298 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4298 2023/06/05 08:04:43 - mmengine - INFO - Epoch(train) [83][ 220/2569] lr: 4.0000e-02 eta: 12:52:42 time: 0.2698 data_time: 0.0076 memory: 5828 grad_norm: 3.1432 loss: 2.4107 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4107 2023/06/05 08:04:49 - mmengine - INFO - Epoch(train) [83][ 240/2569] lr: 4.0000e-02 eta: 12:52:37 time: 0.2706 data_time: 0.0069 memory: 5828 grad_norm: 3.0949 loss: 2.4121 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4121 2023/06/05 08:04:54 - mmengine - INFO - Epoch(train) [83][ 260/2569] lr: 4.0000e-02 eta: 12:52:31 time: 0.2628 data_time: 0.0082 memory: 5828 grad_norm: 3.1186 loss: 2.2377 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2377 2023/06/05 08:04:59 - mmengine - INFO - Epoch(train) [83][ 280/2569] lr: 4.0000e-02 eta: 12:52:26 time: 0.2706 data_time: 0.0076 memory: 5828 grad_norm: 3.1346 loss: 2.7463 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7463 2023/06/05 08:05:05 - mmengine - INFO - Epoch(train) [83][ 300/2569] lr: 4.0000e-02 eta: 12:52:21 time: 0.2635 data_time: 0.0089 memory: 5828 grad_norm: 3.1340 loss: 2.5157 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5157 2023/06/05 08:05:10 - mmengine - INFO - Epoch(train) [83][ 320/2569] lr: 4.0000e-02 eta: 12:52:15 time: 0.2615 data_time: 0.0083 memory: 5828 grad_norm: 3.1036 loss: 2.4870 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4870 2023/06/05 08:05:15 - mmengine - INFO - Epoch(train) [83][ 340/2569] lr: 4.0000e-02 eta: 12:52:10 time: 0.2650 data_time: 0.0077 memory: 5828 grad_norm: 3.1541 loss: 2.3261 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3261 2023/06/05 08:05:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:05:20 - mmengine - INFO - Epoch(train) [83][ 360/2569] lr: 4.0000e-02 eta: 12:52:05 time: 0.2617 data_time: 0.0083 memory: 5828 grad_norm: 3.1327 loss: 2.4311 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4311 2023/06/05 08:05:26 - mmengine - INFO - Epoch(train) [83][ 380/2569] lr: 4.0000e-02 eta: 12:51:59 time: 0.2583 data_time: 0.0075 memory: 5828 grad_norm: 3.1674 loss: 2.3356 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3356 2023/06/05 08:05:31 - mmengine - INFO - Epoch(train) [83][ 400/2569] lr: 4.0000e-02 eta: 12:51:54 time: 0.2607 data_time: 0.0121 memory: 5828 grad_norm: 3.1860 loss: 2.5583 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5583 2023/06/05 08:05:36 - mmengine - INFO - Epoch(train) [83][ 420/2569] lr: 4.0000e-02 eta: 12:51:48 time: 0.2601 data_time: 0.0073 memory: 5828 grad_norm: 3.1064 loss: 2.5530 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5530 2023/06/05 08:05:41 - mmengine - INFO - Epoch(train) [83][ 440/2569] lr: 4.0000e-02 eta: 12:51:43 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 3.1395 loss: 2.5827 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5827 2023/06/05 08:05:47 - mmengine - INFO - Epoch(train) [83][ 460/2569] lr: 4.0000e-02 eta: 12:51:38 time: 0.2717 data_time: 0.0071 memory: 5828 grad_norm: 3.1185 loss: 2.8002 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8002 2023/06/05 08:05:52 - mmengine - INFO - Epoch(train) [83][ 480/2569] lr: 4.0000e-02 eta: 12:51:33 time: 0.2647 data_time: 0.0076 memory: 5828 grad_norm: 3.1128 loss: 2.3515 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3515 2023/06/05 08:05:58 - mmengine - INFO - Epoch(train) [83][ 500/2569] lr: 4.0000e-02 eta: 12:51:27 time: 0.2783 data_time: 0.0075 memory: 5828 grad_norm: 3.1359 loss: 2.4574 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4574 2023/06/05 08:06:03 - mmengine - INFO - Epoch(train) [83][ 520/2569] lr: 4.0000e-02 eta: 12:51:22 time: 0.2690 data_time: 0.0074 memory: 5828 grad_norm: 3.1434 loss: 2.7722 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7722 2023/06/05 08:06:08 - mmengine - INFO - Epoch(train) [83][ 540/2569] lr: 4.0000e-02 eta: 12:51:17 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 3.0993 loss: 2.6672 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6672 2023/06/05 08:06:14 - mmengine - INFO - Epoch(train) [83][ 560/2569] lr: 4.0000e-02 eta: 12:51:12 time: 0.2702 data_time: 0.0075 memory: 5828 grad_norm: 3.0155 loss: 2.1527 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1527 2023/06/05 08:06:19 - mmengine - INFO - Epoch(train) [83][ 580/2569] lr: 4.0000e-02 eta: 12:51:06 time: 0.2661 data_time: 0.0083 memory: 5828 grad_norm: 3.1129 loss: 2.7099 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7099 2023/06/05 08:06:25 - mmengine - INFO - Epoch(train) [83][ 600/2569] lr: 4.0000e-02 eta: 12:51:01 time: 0.2714 data_time: 0.0073 memory: 5828 grad_norm: 3.0819 loss: 2.1676 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1676 2023/06/05 08:06:30 - mmengine - INFO - Epoch(train) [83][ 620/2569] lr: 4.0000e-02 eta: 12:50:56 time: 0.2594 data_time: 0.0073 memory: 5828 grad_norm: 3.0862 loss: 2.3052 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3052 2023/06/05 08:06:35 - mmengine - INFO - Epoch(train) [83][ 640/2569] lr: 4.0000e-02 eta: 12:50:50 time: 0.2644 data_time: 0.0073 memory: 5828 grad_norm: 3.1098 loss: 2.4010 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4010 2023/06/05 08:06:40 - mmengine - INFO - Epoch(train) [83][ 660/2569] lr: 4.0000e-02 eta: 12:50:45 time: 0.2679 data_time: 0.0075 memory: 5828 grad_norm: 3.0976 loss: 2.6128 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6128 2023/06/05 08:06:46 - mmengine - INFO - Epoch(train) [83][ 680/2569] lr: 4.0000e-02 eta: 12:50:40 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.1517 loss: 2.6346 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6346 2023/06/05 08:06:51 - mmengine - INFO - Epoch(train) [83][ 700/2569] lr: 4.0000e-02 eta: 12:50:34 time: 0.2620 data_time: 0.0075 memory: 5828 grad_norm: 3.1312 loss: 2.4946 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4946 2023/06/05 08:06:56 - mmengine - INFO - Epoch(train) [83][ 720/2569] lr: 4.0000e-02 eta: 12:50:29 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 3.1818 loss: 2.7301 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7301 2023/06/05 08:07:01 - mmengine - INFO - Epoch(train) [83][ 740/2569] lr: 4.0000e-02 eta: 12:50:24 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.1302 loss: 2.4771 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4771 2023/06/05 08:07:07 - mmengine - INFO - Epoch(train) [83][ 760/2569] lr: 4.0000e-02 eta: 12:50:18 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 3.1573 loss: 2.4516 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4516 2023/06/05 08:07:12 - mmengine - INFO - Epoch(train) [83][ 780/2569] lr: 4.0000e-02 eta: 12:50:13 time: 0.2584 data_time: 0.0073 memory: 5828 grad_norm: 3.1385 loss: 2.4168 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4168 2023/06/05 08:07:17 - mmengine - INFO - Epoch(train) [83][ 800/2569] lr: 4.0000e-02 eta: 12:50:07 time: 0.2584 data_time: 0.0072 memory: 5828 grad_norm: 3.1897 loss: 2.5269 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5269 2023/06/05 08:07:22 - mmengine - INFO - Epoch(train) [83][ 820/2569] lr: 4.0000e-02 eta: 12:50:02 time: 0.2629 data_time: 0.0070 memory: 5828 grad_norm: 3.1348 loss: 2.6254 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6254 2023/06/05 08:07:28 - mmengine - INFO - Epoch(train) [83][ 840/2569] lr: 4.0000e-02 eta: 12:49:57 time: 0.2601 data_time: 0.0075 memory: 5828 grad_norm: 3.1415 loss: 2.1206 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1206 2023/06/05 08:07:33 - mmengine - INFO - Epoch(train) [83][ 860/2569] lr: 4.0000e-02 eta: 12:49:51 time: 0.2742 data_time: 0.0072 memory: 5828 grad_norm: 3.1462 loss: 2.8542 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8542 2023/06/05 08:07:38 - mmengine - INFO - Epoch(train) [83][ 880/2569] lr: 4.0000e-02 eta: 12:49:46 time: 0.2586 data_time: 0.0076 memory: 5828 grad_norm: 3.1140 loss: 2.6872 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6872 2023/06/05 08:07:43 - mmengine - INFO - Epoch(train) [83][ 900/2569] lr: 4.0000e-02 eta: 12:49:41 time: 0.2585 data_time: 0.0070 memory: 5828 grad_norm: 3.1656 loss: 2.4366 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4366 2023/06/05 08:07:49 - mmengine - INFO - Epoch(train) [83][ 920/2569] lr: 4.0000e-02 eta: 12:49:35 time: 0.2688 data_time: 0.0075 memory: 5828 grad_norm: 3.1442 loss: 2.2973 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2973 2023/06/05 08:07:54 - mmengine - INFO - Epoch(train) [83][ 940/2569] lr: 4.0000e-02 eta: 12:49:30 time: 0.2582 data_time: 0.0079 memory: 5828 grad_norm: 3.1004 loss: 2.3217 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3217 2023/06/05 08:07:59 - mmengine - INFO - Epoch(train) [83][ 960/2569] lr: 4.0000e-02 eta: 12:49:25 time: 0.2660 data_time: 0.0071 memory: 5828 grad_norm: 3.1481 loss: 2.3623 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3623 2023/06/05 08:08:05 - mmengine - INFO - Epoch(train) [83][ 980/2569] lr: 4.0000e-02 eta: 12:49:19 time: 0.2593 data_time: 0.0080 memory: 5828 grad_norm: 3.1405 loss: 2.3306 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3306 2023/06/05 08:08:10 - mmengine - INFO - Epoch(train) [83][1000/2569] lr: 4.0000e-02 eta: 12:49:14 time: 0.2646 data_time: 0.0076 memory: 5828 grad_norm: 3.1430 loss: 2.3657 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3657 2023/06/05 08:08:15 - mmengine - INFO - Epoch(train) [83][1020/2569] lr: 4.0000e-02 eta: 12:49:09 time: 0.2722 data_time: 0.0073 memory: 5828 grad_norm: 3.1566 loss: 2.4587 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4587 2023/06/05 08:08:21 - mmengine - INFO - Epoch(train) [83][1040/2569] lr: 4.0000e-02 eta: 12:49:03 time: 0.2615 data_time: 0.0076 memory: 5828 grad_norm: 3.1471 loss: 2.5523 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5523 2023/06/05 08:08:26 - mmengine - INFO - Epoch(train) [83][1060/2569] lr: 4.0000e-02 eta: 12:48:58 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 3.1335 loss: 2.3916 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3916 2023/06/05 08:08:31 - mmengine - INFO - Epoch(train) [83][1080/2569] lr: 4.0000e-02 eta: 12:48:52 time: 0.2592 data_time: 0.0075 memory: 5828 grad_norm: 3.0851 loss: 2.5277 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5277 2023/06/05 08:08:36 - mmengine - INFO - Epoch(train) [83][1100/2569] lr: 4.0000e-02 eta: 12:48:47 time: 0.2702 data_time: 0.0074 memory: 5828 grad_norm: 3.1485 loss: 2.4215 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4215 2023/06/05 08:08:42 - mmengine - INFO - Epoch(train) [83][1120/2569] lr: 4.0000e-02 eta: 12:48:42 time: 0.2590 data_time: 0.0075 memory: 5828 grad_norm: 3.1694 loss: 2.6008 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6008 2023/06/05 08:08:47 - mmengine - INFO - Epoch(train) [83][1140/2569] lr: 4.0000e-02 eta: 12:48:36 time: 0.2734 data_time: 0.0070 memory: 5828 grad_norm: 3.0951 loss: 2.6920 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6920 2023/06/05 08:08:52 - mmengine - INFO - Epoch(train) [83][1160/2569] lr: 4.0000e-02 eta: 12:48:31 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 3.0905 loss: 2.2765 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2765 2023/06/05 08:08:58 - mmengine - INFO - Epoch(train) [83][1180/2569] lr: 4.0000e-02 eta: 12:48:26 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.1274 loss: 2.4437 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4437 2023/06/05 08:09:03 - mmengine - INFO - Epoch(train) [83][1200/2569] lr: 4.0000e-02 eta: 12:48:20 time: 0.2641 data_time: 0.0071 memory: 5828 grad_norm: 3.1943 loss: 2.4716 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4716 2023/06/05 08:09:08 - mmengine - INFO - Epoch(train) [83][1220/2569] lr: 4.0000e-02 eta: 12:48:15 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 3.1295 loss: 2.1827 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.1827 2023/06/05 08:09:13 - mmengine - INFO - Epoch(train) [83][1240/2569] lr: 4.0000e-02 eta: 12:48:10 time: 0.2607 data_time: 0.0079 memory: 5828 grad_norm: 3.1317 loss: 2.1881 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1881 2023/06/05 08:09:19 - mmengine - INFO - Epoch(train) [83][1260/2569] lr: 4.0000e-02 eta: 12:48:04 time: 0.2589 data_time: 0.0080 memory: 5828 grad_norm: 3.1364 loss: 2.3728 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3728 2023/06/05 08:09:24 - mmengine - INFO - Epoch(train) [83][1280/2569] lr: 4.0000e-02 eta: 12:47:59 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 3.0968 loss: 2.4238 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4238 2023/06/05 08:09:29 - mmengine - INFO - Epoch(train) [83][1300/2569] lr: 4.0000e-02 eta: 12:47:54 time: 0.2659 data_time: 0.0076 memory: 5828 grad_norm: 3.1339 loss: 2.3490 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3490 2023/06/05 08:09:34 - mmengine - INFO - Epoch(train) [83][1320/2569] lr: 4.0000e-02 eta: 12:47:48 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 3.0985 loss: 2.3157 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3157 2023/06/05 08:09:40 - mmengine - INFO - Epoch(train) [83][1340/2569] lr: 4.0000e-02 eta: 12:47:43 time: 0.2741 data_time: 0.0074 memory: 5828 grad_norm: 3.1308 loss: 2.5690 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5690 2023/06/05 08:09:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:09:45 - mmengine - INFO - Epoch(train) [83][1360/2569] lr: 4.0000e-02 eta: 12:47:38 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 3.1123 loss: 2.4312 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4312 2023/06/05 08:09:50 - mmengine - INFO - Epoch(train) [83][1380/2569] lr: 4.0000e-02 eta: 12:47:32 time: 0.2598 data_time: 0.0074 memory: 5828 grad_norm: 3.1363 loss: 2.5779 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5779 2023/06/05 08:09:55 - mmengine - INFO - Epoch(train) [83][1400/2569] lr: 4.0000e-02 eta: 12:47:27 time: 0.2592 data_time: 0.0076 memory: 5828 grad_norm: 3.1778 loss: 2.6947 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6947 2023/06/05 08:10:01 - mmengine - INFO - Epoch(train) [83][1420/2569] lr: 4.0000e-02 eta: 12:47:22 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 3.1148 loss: 2.6665 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6665 2023/06/05 08:10:06 - mmengine - INFO - Epoch(train) [83][1440/2569] lr: 4.0000e-02 eta: 12:47:16 time: 0.2750 data_time: 0.0074 memory: 5828 grad_norm: 3.1734 loss: 2.6643 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.6643 2023/06/05 08:10:12 - mmengine - INFO - Epoch(train) [83][1460/2569] lr: 4.0000e-02 eta: 12:47:11 time: 0.2649 data_time: 0.0075 memory: 5828 grad_norm: 3.1168 loss: 2.5268 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5268 2023/06/05 08:10:17 - mmengine - INFO - Epoch(train) [83][1480/2569] lr: 4.0000e-02 eta: 12:47:06 time: 0.2597 data_time: 0.0075 memory: 5828 grad_norm: 3.1633 loss: 2.7294 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7294 2023/06/05 08:10:22 - mmengine - INFO - Epoch(train) [83][1500/2569] lr: 4.0000e-02 eta: 12:47:00 time: 0.2743 data_time: 0.0075 memory: 5828 grad_norm: 3.1092 loss: 2.3716 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3716 2023/06/05 08:10:28 - mmengine - INFO - Epoch(train) [83][1520/2569] lr: 4.0000e-02 eta: 12:46:55 time: 0.2585 data_time: 0.0076 memory: 5828 grad_norm: 3.1333 loss: 2.5083 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5083 2023/06/05 08:10:33 - mmengine - INFO - Epoch(train) [83][1540/2569] lr: 4.0000e-02 eta: 12:46:50 time: 0.2741 data_time: 0.0075 memory: 5828 grad_norm: 3.1068 loss: 2.2964 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2964 2023/06/05 08:10:38 - mmengine - INFO - Epoch(train) [83][1560/2569] lr: 4.0000e-02 eta: 12:46:44 time: 0.2598 data_time: 0.0074 memory: 5828 grad_norm: 3.1219 loss: 2.4708 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4708 2023/06/05 08:10:44 - mmengine - INFO - Epoch(train) [83][1580/2569] lr: 4.0000e-02 eta: 12:46:39 time: 0.2738 data_time: 0.0097 memory: 5828 grad_norm: 3.1043 loss: 2.3463 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3463 2023/06/05 08:10:49 - mmengine - INFO - Epoch(train) [83][1600/2569] lr: 4.0000e-02 eta: 12:46:34 time: 0.2582 data_time: 0.0074 memory: 5828 grad_norm: 3.1693 loss: 2.5762 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5762 2023/06/05 08:10:54 - mmengine - INFO - Epoch(train) [83][1620/2569] lr: 4.0000e-02 eta: 12:46:28 time: 0.2600 data_time: 0.0081 memory: 5828 grad_norm: 3.1357 loss: 2.4454 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4454 2023/06/05 08:10:59 - mmengine - INFO - Epoch(train) [83][1640/2569] lr: 4.0000e-02 eta: 12:46:23 time: 0.2696 data_time: 0.0082 memory: 5828 grad_norm: 3.0640 loss: 2.6466 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6466 2023/06/05 08:11:05 - mmengine - INFO - Epoch(train) [83][1660/2569] lr: 4.0000e-02 eta: 12:46:18 time: 0.2637 data_time: 0.0078 memory: 5828 grad_norm: 3.1012 loss: 2.8498 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8498 2023/06/05 08:11:10 - mmengine - INFO - Epoch(train) [83][1680/2569] lr: 4.0000e-02 eta: 12:46:13 time: 0.2720 data_time: 0.0071 memory: 5828 grad_norm: 3.2073 loss: 2.4400 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4400 2023/06/05 08:11:15 - mmengine - INFO - Epoch(train) [83][1700/2569] lr: 4.0000e-02 eta: 12:46:07 time: 0.2642 data_time: 0.0088 memory: 5828 grad_norm: 3.1450 loss: 2.5444 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5444 2023/06/05 08:11:21 - mmengine - INFO - Epoch(train) [83][1720/2569] lr: 4.0000e-02 eta: 12:46:02 time: 0.2661 data_time: 0.0074 memory: 5828 grad_norm: 3.1536 loss: 2.0723 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0723 2023/06/05 08:11:26 - mmengine - INFO - Epoch(train) [83][1740/2569] lr: 4.0000e-02 eta: 12:45:57 time: 0.2652 data_time: 0.0079 memory: 5828 grad_norm: 3.1226 loss: 2.7107 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7107 2023/06/05 08:11:32 - mmengine - INFO - Epoch(train) [83][1760/2569] lr: 4.0000e-02 eta: 12:45:51 time: 0.2755 data_time: 0.0069 memory: 5828 grad_norm: 3.1480 loss: 2.3886 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3886 2023/06/05 08:11:37 - mmengine - INFO - Epoch(train) [83][1780/2569] lr: 4.0000e-02 eta: 12:45:46 time: 0.2584 data_time: 0.0076 memory: 5828 grad_norm: 3.1680 loss: 2.5644 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.5644 2023/06/05 08:11:42 - mmengine - INFO - Epoch(train) [83][1800/2569] lr: 4.0000e-02 eta: 12:45:41 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 3.1025 loss: 2.6514 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6514 2023/06/05 08:11:47 - mmengine - INFO - Epoch(train) [83][1820/2569] lr: 4.0000e-02 eta: 12:45:35 time: 0.2587 data_time: 0.0073 memory: 5828 grad_norm: 3.1290 loss: 2.4166 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4166 2023/06/05 08:11:53 - mmengine - INFO - Epoch(train) [83][1840/2569] lr: 4.0000e-02 eta: 12:45:30 time: 0.2647 data_time: 0.0078 memory: 5828 grad_norm: 3.1222 loss: 2.6215 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6215 2023/06/05 08:11:58 - mmengine - INFO - Epoch(train) [83][1860/2569] lr: 4.0000e-02 eta: 12:45:25 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 3.1227 loss: 2.7217 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7217 2023/06/05 08:12:03 - mmengine - INFO - Epoch(train) [83][1880/2569] lr: 4.0000e-02 eta: 12:45:19 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 3.1298 loss: 2.6292 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6292 2023/06/05 08:12:08 - mmengine - INFO - Epoch(train) [83][1900/2569] lr: 4.0000e-02 eta: 12:45:14 time: 0.2577 data_time: 0.0075 memory: 5828 grad_norm: 3.1000 loss: 2.6417 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6417 2023/06/05 08:12:14 - mmengine - INFO - Epoch(train) [83][1920/2569] lr: 4.0000e-02 eta: 12:45:08 time: 0.2639 data_time: 0.0072 memory: 5828 grad_norm: 3.1194 loss: 2.2401 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2401 2023/06/05 08:12:19 - mmengine - INFO - Epoch(train) [83][1940/2569] lr: 4.0000e-02 eta: 12:45:03 time: 0.2591 data_time: 0.0075 memory: 5828 grad_norm: 3.1298 loss: 2.3035 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3035 2023/06/05 08:12:24 - mmengine - INFO - Epoch(train) [83][1960/2569] lr: 4.0000e-02 eta: 12:44:58 time: 0.2697 data_time: 0.0075 memory: 5828 grad_norm: 3.1617 loss: 2.4164 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4164 2023/06/05 08:12:30 - mmengine - INFO - Epoch(train) [83][1980/2569] lr: 4.0000e-02 eta: 12:44:52 time: 0.2692 data_time: 0.0075 memory: 5828 grad_norm: 3.1819 loss: 2.3066 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3066 2023/06/05 08:12:35 - mmengine - INFO - Epoch(train) [83][2000/2569] lr: 4.0000e-02 eta: 12:44:47 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 3.1084 loss: 2.5333 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5333 2023/06/05 08:12:40 - mmengine - INFO - Epoch(train) [83][2020/2569] lr: 4.0000e-02 eta: 12:44:42 time: 0.2752 data_time: 0.0074 memory: 5828 grad_norm: 3.1438 loss: 2.3330 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3330 2023/06/05 08:12:46 - mmengine - INFO - Epoch(train) [83][2040/2569] lr: 4.0000e-02 eta: 12:44:37 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 3.1616 loss: 2.5905 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5905 2023/06/05 08:12:51 - mmengine - INFO - Epoch(train) [83][2060/2569] lr: 4.0000e-02 eta: 12:44:31 time: 0.2624 data_time: 0.0074 memory: 5828 grad_norm: 3.1912 loss: 2.5120 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5120 2023/06/05 08:12:56 - mmengine - INFO - Epoch(train) [83][2080/2569] lr: 4.0000e-02 eta: 12:44:26 time: 0.2605 data_time: 0.0072 memory: 5828 grad_norm: 3.0937 loss: 2.7954 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7954 2023/06/05 08:13:02 - mmengine - INFO - Epoch(train) [83][2100/2569] lr: 4.0000e-02 eta: 12:44:21 time: 0.2632 data_time: 0.0071 memory: 5828 grad_norm: 3.0395 loss: 2.5723 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5723 2023/06/05 08:13:07 - mmengine - INFO - Epoch(train) [83][2120/2569] lr: 4.0000e-02 eta: 12:44:15 time: 0.2602 data_time: 0.0078 memory: 5828 grad_norm: 3.1976 loss: 2.5659 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5659 2023/06/05 08:13:12 - mmengine - INFO - Epoch(train) [83][2140/2569] lr: 4.0000e-02 eta: 12:44:10 time: 0.2598 data_time: 0.0070 memory: 5828 grad_norm: 3.0598 loss: 2.4320 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4320 2023/06/05 08:13:17 - mmengine - INFO - Epoch(train) [83][2160/2569] lr: 4.0000e-02 eta: 12:44:04 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 3.1774 loss: 2.4561 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4561 2023/06/05 08:13:22 - mmengine - INFO - Epoch(train) [83][2180/2569] lr: 4.0000e-02 eta: 12:43:59 time: 0.2588 data_time: 0.0073 memory: 5828 grad_norm: 3.1204 loss: 2.6133 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6133 2023/06/05 08:13:28 - mmengine - INFO - Epoch(train) [83][2200/2569] lr: 4.0000e-02 eta: 12:43:54 time: 0.2609 data_time: 0.0086 memory: 5828 grad_norm: 3.1599 loss: 2.5242 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5242 2023/06/05 08:13:33 - mmengine - INFO - Epoch(train) [83][2220/2569] lr: 4.0000e-02 eta: 12:43:48 time: 0.2579 data_time: 0.0074 memory: 5828 grad_norm: 3.0706 loss: 2.7372 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7372 2023/06/05 08:13:38 - mmengine - INFO - Epoch(train) [83][2240/2569] lr: 4.0000e-02 eta: 12:43:43 time: 0.2589 data_time: 0.0074 memory: 5828 grad_norm: 3.1902 loss: 2.6687 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6687 2023/06/05 08:13:43 - mmengine - INFO - Epoch(train) [83][2260/2569] lr: 4.0000e-02 eta: 12:43:37 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 3.2027 loss: 2.6801 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6801 2023/06/05 08:13:48 - mmengine - INFO - Epoch(train) [83][2280/2569] lr: 4.0000e-02 eta: 12:43:32 time: 0.2582 data_time: 0.0075 memory: 5828 grad_norm: 3.0904 loss: 2.7636 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7636 2023/06/05 08:13:54 - mmengine - INFO - Epoch(train) [83][2300/2569] lr: 4.0000e-02 eta: 12:43:27 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 3.1645 loss: 2.4454 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4454 2023/06/05 08:13:59 - mmengine - INFO - Epoch(train) [83][2320/2569] lr: 4.0000e-02 eta: 12:43:21 time: 0.2584 data_time: 0.0077 memory: 5828 grad_norm: 3.1812 loss: 2.8652 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8652 2023/06/05 08:14:04 - mmengine - INFO - Epoch(train) [83][2340/2569] lr: 4.0000e-02 eta: 12:43:16 time: 0.2600 data_time: 0.0074 memory: 5828 grad_norm: 3.1801 loss: 2.4823 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4823 2023/06/05 08:14:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:14:10 - mmengine - INFO - Epoch(train) [83][2360/2569] lr: 4.0000e-02 eta: 12:43:11 time: 0.2705 data_time: 0.0070 memory: 5828 grad_norm: 3.1570 loss: 2.7940 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7940 2023/06/05 08:14:15 - mmengine - INFO - Epoch(train) [83][2380/2569] lr: 4.0000e-02 eta: 12:43:05 time: 0.2598 data_time: 0.0073 memory: 5828 grad_norm: 3.1920 loss: 2.4416 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.4416 2023/06/05 08:14:20 - mmengine - INFO - Epoch(train) [83][2400/2569] lr: 4.0000e-02 eta: 12:43:00 time: 0.2715 data_time: 0.0075 memory: 5828 grad_norm: 3.1830 loss: 2.5715 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5715 2023/06/05 08:14:26 - mmengine - INFO - Epoch(train) [83][2420/2569] lr: 4.0000e-02 eta: 12:42:55 time: 0.2743 data_time: 0.0071 memory: 5828 grad_norm: 3.1475 loss: 2.5566 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5566 2023/06/05 08:14:31 - mmengine - INFO - Epoch(train) [83][2440/2569] lr: 4.0000e-02 eta: 12:42:49 time: 0.2607 data_time: 0.0074 memory: 5828 grad_norm: 3.1707 loss: 2.4735 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4735 2023/06/05 08:14:36 - mmengine - INFO - Epoch(train) [83][2460/2569] lr: 4.0000e-02 eta: 12:42:44 time: 0.2666 data_time: 0.0075 memory: 5828 grad_norm: 3.0702 loss: 2.4182 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4182 2023/06/05 08:14:42 - mmengine - INFO - Epoch(train) [83][2480/2569] lr: 4.0000e-02 eta: 12:42:39 time: 0.2642 data_time: 0.0075 memory: 5828 grad_norm: 3.1325 loss: 2.5506 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5506 2023/06/05 08:14:47 - mmengine - INFO - Epoch(train) [83][2500/2569] lr: 4.0000e-02 eta: 12:42:33 time: 0.2616 data_time: 0.0070 memory: 5828 grad_norm: 3.1629 loss: 2.3433 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3433 2023/06/05 08:14:52 - mmengine - INFO - Epoch(train) [83][2520/2569] lr: 4.0000e-02 eta: 12:42:28 time: 0.2593 data_time: 0.0073 memory: 5828 grad_norm: 3.1510 loss: 2.6387 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6387 2023/06/05 08:14:57 - mmengine - INFO - Epoch(train) [83][2540/2569] lr: 4.0000e-02 eta: 12:42:23 time: 0.2648 data_time: 0.0075 memory: 5828 grad_norm: 3.1394 loss: 2.5558 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5558 2023/06/05 08:15:03 - mmengine - INFO - Epoch(train) [83][2560/2569] lr: 4.0000e-02 eta: 12:42:17 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 3.0848 loss: 2.8680 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8680 2023/06/05 08:15:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:15:05 - mmengine - INFO - Epoch(train) [83][2569/2569] lr: 4.0000e-02 eta: 12:42:15 time: 0.2570 data_time: 0.0072 memory: 5828 grad_norm: 3.1816 loss: 2.4257 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.4257 2023/06/05 08:15:12 - mmengine - INFO - Epoch(train) [84][ 20/2569] lr: 4.0000e-02 eta: 12:42:11 time: 0.3414 data_time: 0.0518 memory: 5828 grad_norm: 3.0947 loss: 2.4629 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4629 2023/06/05 08:15:17 - mmengine - INFO - Epoch(train) [84][ 40/2569] lr: 4.0000e-02 eta: 12:42:05 time: 0.2711 data_time: 0.0079 memory: 5828 grad_norm: 3.1232 loss: 2.3393 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3393 2023/06/05 08:15:22 - mmengine - INFO - Epoch(train) [84][ 60/2569] lr: 4.0000e-02 eta: 12:42:00 time: 0.2695 data_time: 0.0072 memory: 5828 grad_norm: 3.1854 loss: 2.6000 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6000 2023/06/05 08:15:28 - mmengine - INFO - Epoch(train) [84][ 80/2569] lr: 4.0000e-02 eta: 12:41:55 time: 0.2662 data_time: 0.0075 memory: 5828 grad_norm: 3.0620 loss: 2.4811 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4811 2023/06/05 08:15:33 - mmengine - INFO - Epoch(train) [84][ 100/2569] lr: 4.0000e-02 eta: 12:41:50 time: 0.2698 data_time: 0.0076 memory: 5828 grad_norm: 3.1360 loss: 2.5615 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5615 2023/06/05 08:15:38 - mmengine - INFO - Epoch(train) [84][ 120/2569] lr: 4.0000e-02 eta: 12:41:44 time: 0.2579 data_time: 0.0077 memory: 5828 grad_norm: 3.0468 loss: 2.1179 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1179 2023/06/05 08:15:44 - mmengine - INFO - Epoch(train) [84][ 140/2569] lr: 4.0000e-02 eta: 12:41:39 time: 0.2621 data_time: 0.0078 memory: 5828 grad_norm: 3.1580 loss: 2.4311 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4311 2023/06/05 08:15:49 - mmengine - INFO - Epoch(train) [84][ 160/2569] lr: 4.0000e-02 eta: 12:41:34 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 3.1109 loss: 2.3661 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3661 2023/06/05 08:15:54 - mmengine - INFO - Epoch(train) [84][ 180/2569] lr: 4.0000e-02 eta: 12:41:28 time: 0.2628 data_time: 0.0073 memory: 5828 grad_norm: 3.1026 loss: 2.6306 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6306 2023/06/05 08:15:59 - mmengine - INFO - Epoch(train) [84][ 200/2569] lr: 4.0000e-02 eta: 12:41:23 time: 0.2566 data_time: 0.0074 memory: 5828 grad_norm: 3.1955 loss: 2.4810 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4810 2023/06/05 08:16:05 - mmengine - INFO - Epoch(train) [84][ 220/2569] lr: 4.0000e-02 eta: 12:41:17 time: 0.2632 data_time: 0.0070 memory: 5828 grad_norm: 3.1483 loss: 2.7518 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.7518 2023/06/05 08:16:10 - mmengine - INFO - Epoch(train) [84][ 240/2569] lr: 4.0000e-02 eta: 12:41:12 time: 0.2583 data_time: 0.0084 memory: 5828 grad_norm: 3.1214 loss: 2.8648 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8648 2023/06/05 08:16:15 - mmengine - INFO - Epoch(train) [84][ 260/2569] lr: 4.0000e-02 eta: 12:41:07 time: 0.2640 data_time: 0.0072 memory: 5828 grad_norm: 3.0659 loss: 2.6516 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6516 2023/06/05 08:16:21 - mmengine - INFO - Epoch(train) [84][ 280/2569] lr: 4.0000e-02 eta: 12:41:01 time: 0.2705 data_time: 0.0071 memory: 5828 grad_norm: 3.1198 loss: 2.4922 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4922 2023/06/05 08:16:26 - mmengine - INFO - Epoch(train) [84][ 300/2569] lr: 4.0000e-02 eta: 12:40:56 time: 0.2594 data_time: 0.0070 memory: 5828 grad_norm: 3.0951 loss: 2.6520 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6520 2023/06/05 08:16:31 - mmengine - INFO - Epoch(train) [84][ 320/2569] lr: 4.0000e-02 eta: 12:40:51 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 3.1621 loss: 2.3558 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3558 2023/06/05 08:16:36 - mmengine - INFO - Epoch(train) [84][ 340/2569] lr: 4.0000e-02 eta: 12:40:45 time: 0.2602 data_time: 0.0076 memory: 5828 grad_norm: 3.1703 loss: 2.5024 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5024 2023/06/05 08:16:42 - mmengine - INFO - Epoch(train) [84][ 360/2569] lr: 4.0000e-02 eta: 12:40:40 time: 0.2725 data_time: 0.0074 memory: 5828 grad_norm: 3.1505 loss: 2.4719 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4719 2023/06/05 08:16:47 - mmengine - INFO - Epoch(train) [84][ 380/2569] lr: 4.0000e-02 eta: 12:40:35 time: 0.2637 data_time: 0.0079 memory: 5828 grad_norm: 3.1516 loss: 2.8264 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8264 2023/06/05 08:16:52 - mmengine - INFO - Epoch(train) [84][ 400/2569] lr: 4.0000e-02 eta: 12:40:29 time: 0.2705 data_time: 0.0074 memory: 5828 grad_norm: 3.1801 loss: 2.6327 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6327 2023/06/05 08:16:58 - mmengine - INFO - Epoch(train) [84][ 420/2569] lr: 4.0000e-02 eta: 12:40:24 time: 0.2600 data_time: 0.0075 memory: 5828 grad_norm: 3.0303 loss: 2.6030 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6030 2023/06/05 08:17:03 - mmengine - INFO - Epoch(train) [84][ 440/2569] lr: 4.0000e-02 eta: 12:40:19 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 3.1752 loss: 2.4608 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4608 2023/06/05 08:17:08 - mmengine - INFO - Epoch(train) [84][ 460/2569] lr: 4.0000e-02 eta: 12:40:13 time: 0.2704 data_time: 0.0072 memory: 5828 grad_norm: 3.1810 loss: 2.9147 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9147 2023/06/05 08:17:14 - mmengine - INFO - Epoch(train) [84][ 480/2569] lr: 4.0000e-02 eta: 12:40:08 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 3.0959 loss: 2.6659 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6659 2023/06/05 08:17:19 - mmengine - INFO - Epoch(train) [84][ 500/2569] lr: 4.0000e-02 eta: 12:40:03 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 3.0960 loss: 2.3510 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3510 2023/06/05 08:17:24 - mmengine - INFO - Epoch(train) [84][ 520/2569] lr: 4.0000e-02 eta: 12:39:58 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 3.1383 loss: 2.6355 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6355 2023/06/05 08:17:30 - mmengine - INFO - Epoch(train) [84][ 540/2569] lr: 4.0000e-02 eta: 12:39:52 time: 0.2651 data_time: 0.0071 memory: 5828 grad_norm: 3.1444 loss: 2.2853 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2853 2023/06/05 08:17:35 - mmengine - INFO - Epoch(train) [84][ 560/2569] lr: 4.0000e-02 eta: 12:39:47 time: 0.2596 data_time: 0.0075 memory: 5828 grad_norm: 3.1275 loss: 2.2280 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2280 2023/06/05 08:17:40 - mmengine - INFO - Epoch(train) [84][ 580/2569] lr: 4.0000e-02 eta: 12:39:42 time: 0.2760 data_time: 0.0073 memory: 5828 grad_norm: 3.1464 loss: 2.2890 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2890 2023/06/05 08:17:46 - mmengine - INFO - Epoch(train) [84][ 600/2569] lr: 4.0000e-02 eta: 12:39:36 time: 0.2594 data_time: 0.0075 memory: 5828 grad_norm: 3.1399 loss: 2.5707 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5707 2023/06/05 08:17:51 - mmengine - INFO - Epoch(train) [84][ 620/2569] lr: 4.0000e-02 eta: 12:39:31 time: 0.2633 data_time: 0.0076 memory: 5828 grad_norm: 3.1452 loss: 2.4686 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4686 2023/06/05 08:17:56 - mmengine - INFO - Epoch(train) [84][ 640/2569] lr: 4.0000e-02 eta: 12:39:26 time: 0.2710 data_time: 0.0076 memory: 5828 grad_norm: 3.1556 loss: 2.3397 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3397 2023/06/05 08:18:02 - mmengine - INFO - Epoch(train) [84][ 660/2569] lr: 4.0000e-02 eta: 12:39:20 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.1505 loss: 2.6158 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.6158 2023/06/05 08:18:07 - mmengine - INFO - Epoch(train) [84][ 680/2569] lr: 4.0000e-02 eta: 12:39:15 time: 0.2715 data_time: 0.0077 memory: 5828 grad_norm: 3.0894 loss: 2.4085 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4085 2023/06/05 08:18:13 - mmengine - INFO - Epoch(train) [84][ 700/2569] lr: 4.0000e-02 eta: 12:39:10 time: 0.2812 data_time: 0.0071 memory: 5828 grad_norm: 3.1720 loss: 2.4031 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4031 2023/06/05 08:18:18 - mmengine - INFO - Epoch(train) [84][ 720/2569] lr: 4.0000e-02 eta: 12:39:05 time: 0.2599 data_time: 0.0074 memory: 5828 grad_norm: 3.1214 loss: 2.6561 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6561 2023/06/05 08:18:23 - mmengine - INFO - Epoch(train) [84][ 740/2569] lr: 4.0000e-02 eta: 12:38:59 time: 0.2662 data_time: 0.0072 memory: 5828 grad_norm: 3.1272 loss: 2.6501 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6501 2023/06/05 08:18:28 - mmengine - INFO - Epoch(train) [84][ 760/2569] lr: 4.0000e-02 eta: 12:38:54 time: 0.2585 data_time: 0.0074 memory: 5828 grad_norm: 3.0340 loss: 2.0819 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0819 2023/06/05 08:18:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:18:34 - mmengine - INFO - Epoch(train) [84][ 780/2569] lr: 4.0000e-02 eta: 12:38:49 time: 0.2647 data_time: 0.0071 memory: 5828 grad_norm: 3.1246 loss: 2.3101 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3101 2023/06/05 08:18:39 - mmengine - INFO - Epoch(train) [84][ 800/2569] lr: 4.0000e-02 eta: 12:38:43 time: 0.2702 data_time: 0.0074 memory: 5828 grad_norm: 3.1835 loss: 2.5930 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5930 2023/06/05 08:18:44 - mmengine - INFO - Epoch(train) [84][ 820/2569] lr: 4.0000e-02 eta: 12:38:38 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 3.1273 loss: 2.5054 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5054 2023/06/05 08:18:50 - mmengine - INFO - Epoch(train) [84][ 840/2569] lr: 4.0000e-02 eta: 12:38:33 time: 0.2683 data_time: 0.0077 memory: 5828 grad_norm: 3.1489 loss: 2.6480 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6480 2023/06/05 08:18:55 - mmengine - INFO - Epoch(train) [84][ 860/2569] lr: 4.0000e-02 eta: 12:38:27 time: 0.2666 data_time: 0.0078 memory: 5828 grad_norm: 3.1550 loss: 2.5815 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5815 2023/06/05 08:19:00 - mmengine - INFO - Epoch(train) [84][ 880/2569] lr: 4.0000e-02 eta: 12:38:22 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.1377 loss: 2.7463 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7463 2023/06/05 08:19:06 - mmengine - INFO - Epoch(train) [84][ 900/2569] lr: 4.0000e-02 eta: 12:38:17 time: 0.2678 data_time: 0.0072 memory: 5828 grad_norm: 3.1060 loss: 2.5068 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5068 2023/06/05 08:19:11 - mmengine - INFO - Epoch(train) [84][ 920/2569] lr: 4.0000e-02 eta: 12:38:11 time: 0.2613 data_time: 0.0071 memory: 5828 grad_norm: 3.0881 loss: 2.4818 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4818 2023/06/05 08:19:16 - mmengine - INFO - Epoch(train) [84][ 940/2569] lr: 4.0000e-02 eta: 12:38:06 time: 0.2616 data_time: 0.0072 memory: 5828 grad_norm: 3.0862 loss: 2.2675 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.2675 2023/06/05 08:19:22 - mmengine - INFO - Epoch(train) [84][ 960/2569] lr: 4.0000e-02 eta: 12:38:01 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 3.1309 loss: 2.5511 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5511 2023/06/05 08:19:27 - mmengine - INFO - Epoch(train) [84][ 980/2569] lr: 4.0000e-02 eta: 12:37:55 time: 0.2706 data_time: 0.0076 memory: 5828 grad_norm: 3.1222 loss: 2.6467 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6467 2023/06/05 08:19:32 - mmengine - INFO - Epoch(train) [84][1000/2569] lr: 4.0000e-02 eta: 12:37:50 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 3.1649 loss: 2.5817 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5817 2023/06/05 08:19:38 - mmengine - INFO - Epoch(train) [84][1020/2569] lr: 4.0000e-02 eta: 12:37:45 time: 0.2674 data_time: 0.0079 memory: 5828 grad_norm: 3.0633 loss: 2.1080 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1080 2023/06/05 08:19:43 - mmengine - INFO - Epoch(train) [84][1040/2569] lr: 4.0000e-02 eta: 12:37:39 time: 0.2593 data_time: 0.0073 memory: 5828 grad_norm: 3.1519 loss: 2.5926 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.5926 2023/06/05 08:19:48 - mmengine - INFO - Epoch(train) [84][1060/2569] lr: 4.0000e-02 eta: 12:37:34 time: 0.2584 data_time: 0.0079 memory: 5828 grad_norm: 3.1419 loss: 2.5883 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5883 2023/06/05 08:19:53 - mmengine - INFO - Epoch(train) [84][1080/2569] lr: 4.0000e-02 eta: 12:37:29 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 3.0058 loss: 2.5561 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5561 2023/06/05 08:19:59 - mmengine - INFO - Epoch(train) [84][1100/2569] lr: 4.0000e-02 eta: 12:37:23 time: 0.2663 data_time: 0.0075 memory: 5828 grad_norm: 3.1371 loss: 2.6288 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6288 2023/06/05 08:20:04 - mmengine - INFO - Epoch(train) [84][1120/2569] lr: 4.0000e-02 eta: 12:37:18 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 3.1404 loss: 2.2437 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2437 2023/06/05 08:20:09 - mmengine - INFO - Epoch(train) [84][1140/2569] lr: 4.0000e-02 eta: 12:37:13 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 3.1780 loss: 2.4692 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4692 2023/06/05 08:20:14 - mmengine - INFO - Epoch(train) [84][1160/2569] lr: 4.0000e-02 eta: 12:37:07 time: 0.2644 data_time: 0.0076 memory: 5828 grad_norm: 3.2047 loss: 2.6820 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6820 2023/06/05 08:20:20 - mmengine - INFO - Epoch(train) [84][1180/2569] lr: 4.0000e-02 eta: 12:37:02 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 3.1614 loss: 2.6304 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6304 2023/06/05 08:20:25 - mmengine - INFO - Epoch(train) [84][1200/2569] lr: 4.0000e-02 eta: 12:36:57 time: 0.2654 data_time: 0.0077 memory: 5828 grad_norm: 3.1197 loss: 2.3935 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3935 2023/06/05 08:20:30 - mmengine - INFO - Epoch(train) [84][1220/2569] lr: 4.0000e-02 eta: 12:36:51 time: 0.2628 data_time: 0.0069 memory: 5828 grad_norm: 3.1642 loss: 2.4163 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4163 2023/06/05 08:20:36 - mmengine - INFO - Epoch(train) [84][1240/2569] lr: 4.0000e-02 eta: 12:36:46 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.1109 loss: 2.9806 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.9806 2023/06/05 08:20:41 - mmengine - INFO - Epoch(train) [84][1260/2569] lr: 4.0000e-02 eta: 12:36:41 time: 0.2623 data_time: 0.0069 memory: 5828 grad_norm: 3.1509 loss: 2.3000 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3000 2023/06/05 08:20:46 - mmengine - INFO - Epoch(train) [84][1280/2569] lr: 4.0000e-02 eta: 12:36:35 time: 0.2646 data_time: 0.0077 memory: 5828 grad_norm: 3.1443 loss: 2.3365 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3365 2023/06/05 08:20:51 - mmengine - INFO - Epoch(train) [84][1300/2569] lr: 4.0000e-02 eta: 12:36:30 time: 0.2657 data_time: 0.0074 memory: 5828 grad_norm: 3.1768 loss: 2.5246 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5246 2023/06/05 08:20:57 - mmengine - INFO - Epoch(train) [84][1320/2569] lr: 4.0000e-02 eta: 12:36:24 time: 0.2591 data_time: 0.0072 memory: 5828 grad_norm: 3.1473 loss: 2.5796 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5796 2023/06/05 08:21:02 - mmengine - INFO - Epoch(train) [84][1340/2569] lr: 4.0000e-02 eta: 12:36:19 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 3.1211 loss: 2.6426 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6426 2023/06/05 08:21:07 - mmengine - INFO - Epoch(train) [84][1360/2569] lr: 4.0000e-02 eta: 12:36:14 time: 0.2752 data_time: 0.0075 memory: 5828 grad_norm: 3.1106 loss: 2.8189 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8189 2023/06/05 08:21:13 - mmengine - INFO - Epoch(train) [84][1380/2569] lr: 4.0000e-02 eta: 12:36:09 time: 0.2690 data_time: 0.0080 memory: 5828 grad_norm: 3.1641 loss: 2.5707 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5707 2023/06/05 08:21:18 - mmengine - INFO - Epoch(train) [84][1400/2569] lr: 4.0000e-02 eta: 12:36:03 time: 0.2657 data_time: 0.0077 memory: 5828 grad_norm: 3.1602 loss: 2.3633 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3633 2023/06/05 08:21:24 - mmengine - INFO - Epoch(train) [84][1420/2569] lr: 4.0000e-02 eta: 12:35:58 time: 0.2735 data_time: 0.0070 memory: 5828 grad_norm: 3.1351 loss: 2.5089 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5089 2023/06/05 08:21:29 - mmengine - INFO - Epoch(train) [84][1440/2569] lr: 4.0000e-02 eta: 12:35:53 time: 0.2671 data_time: 0.0077 memory: 5828 grad_norm: 3.1251 loss: 2.8395 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8395 2023/06/05 08:21:34 - mmengine - INFO - Epoch(train) [84][1460/2569] lr: 4.0000e-02 eta: 12:35:48 time: 0.2653 data_time: 0.0076 memory: 5828 grad_norm: 3.1879 loss: 2.3172 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3172 2023/06/05 08:21:40 - mmengine - INFO - Epoch(train) [84][1480/2569] lr: 4.0000e-02 eta: 12:35:42 time: 0.2645 data_time: 0.0082 memory: 5828 grad_norm: 3.1295 loss: 2.4484 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4484 2023/06/05 08:21:45 - mmengine - INFO - Epoch(train) [84][1500/2569] lr: 4.0000e-02 eta: 12:35:37 time: 0.2655 data_time: 0.0072 memory: 5828 grad_norm: 3.0683 loss: 2.4019 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4019 2023/06/05 08:21:50 - mmengine - INFO - Epoch(train) [84][1520/2569] lr: 4.0000e-02 eta: 12:35:32 time: 0.2655 data_time: 0.0072 memory: 5828 grad_norm: 3.1573 loss: 2.6801 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6801 2023/06/05 08:21:56 - mmengine - INFO - Epoch(train) [84][1540/2569] lr: 4.0000e-02 eta: 12:35:26 time: 0.2698 data_time: 0.0071 memory: 5828 grad_norm: 3.1428 loss: 2.8012 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8012 2023/06/05 08:22:01 - mmengine - INFO - Epoch(train) [84][1560/2569] lr: 4.0000e-02 eta: 12:35:21 time: 0.2689 data_time: 0.0074 memory: 5828 grad_norm: 3.1035 loss: 2.5530 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5530 2023/06/05 08:22:06 - mmengine - INFO - Epoch(train) [84][1580/2569] lr: 4.0000e-02 eta: 12:35:16 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.1124 loss: 2.7282 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7282 2023/06/05 08:22:12 - mmengine - INFO - Epoch(train) [84][1600/2569] lr: 4.0000e-02 eta: 12:35:10 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 3.2235 loss: 2.9500 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.9500 2023/06/05 08:22:17 - mmengine - INFO - Epoch(train) [84][1620/2569] lr: 4.0000e-02 eta: 12:35:05 time: 0.2586 data_time: 0.0072 memory: 5828 grad_norm: 3.1660 loss: 2.3417 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3417 2023/06/05 08:22:22 - mmengine - INFO - Epoch(train) [84][1640/2569] lr: 4.0000e-02 eta: 12:35:00 time: 0.2661 data_time: 0.0072 memory: 5828 grad_norm: 3.1272 loss: 2.6443 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6443 2023/06/05 08:22:27 - mmengine - INFO - Epoch(train) [84][1660/2569] lr: 4.0000e-02 eta: 12:34:54 time: 0.2596 data_time: 0.0072 memory: 5828 grad_norm: 3.1517 loss: 2.4759 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4759 2023/06/05 08:22:33 - mmengine - INFO - Epoch(train) [84][1680/2569] lr: 4.0000e-02 eta: 12:34:49 time: 0.2753 data_time: 0.0073 memory: 5828 grad_norm: 3.1493 loss: 2.3574 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3574 2023/06/05 08:22:38 - mmengine - INFO - Epoch(train) [84][1700/2569] lr: 4.0000e-02 eta: 12:34:44 time: 0.2761 data_time: 0.0069 memory: 5828 grad_norm: 3.1328 loss: 2.7922 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7922 2023/06/05 08:22:43 - mmengine - INFO - Epoch(train) [84][1720/2569] lr: 4.0000e-02 eta: 12:34:38 time: 0.2582 data_time: 0.0075 memory: 5828 grad_norm: 3.1509 loss: 2.1999 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1999 2023/06/05 08:22:49 - mmengine - INFO - Epoch(train) [84][1740/2569] lr: 4.0000e-02 eta: 12:34:33 time: 0.2655 data_time: 0.0076 memory: 5828 grad_norm: 3.1743 loss: 2.3419 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3419 2023/06/05 08:22:54 - mmengine - INFO - Epoch(train) [84][1760/2569] lr: 4.0000e-02 eta: 12:34:28 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 3.1079 loss: 2.2104 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2104 2023/06/05 08:22:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:22:59 - mmengine - INFO - Epoch(train) [84][1780/2569] lr: 4.0000e-02 eta: 12:34:22 time: 0.2651 data_time: 0.0070 memory: 5828 grad_norm: 3.1635 loss: 2.6921 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6921 2023/06/05 08:23:05 - mmengine - INFO - Epoch(train) [84][1800/2569] lr: 4.0000e-02 eta: 12:34:17 time: 0.2711 data_time: 0.0074 memory: 5828 grad_norm: 3.2084 loss: 2.5215 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5215 2023/06/05 08:23:10 - mmengine - INFO - Epoch(train) [84][1820/2569] lr: 4.0000e-02 eta: 12:34:12 time: 0.2809 data_time: 0.0071 memory: 5828 grad_norm: 3.1320 loss: 2.5233 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5233 2023/06/05 08:23:16 - mmengine - INFO - Epoch(train) [84][1840/2569] lr: 4.0000e-02 eta: 12:34:07 time: 0.2601 data_time: 0.0075 memory: 5828 grad_norm: 3.1292 loss: 2.4936 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4936 2023/06/05 08:23:21 - mmengine - INFO - Epoch(train) [84][1860/2569] lr: 4.0000e-02 eta: 12:34:01 time: 0.2639 data_time: 0.0076 memory: 5828 grad_norm: 3.1552 loss: 2.5761 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5761 2023/06/05 08:23:26 - mmengine - INFO - Epoch(train) [84][1880/2569] lr: 4.0000e-02 eta: 12:33:56 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 3.1315 loss: 2.3699 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.3699 2023/06/05 08:23:31 - mmengine - INFO - Epoch(train) [84][1900/2569] lr: 4.0000e-02 eta: 12:33:51 time: 0.2597 data_time: 0.0076 memory: 5828 grad_norm: 3.1546 loss: 2.8526 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8526 2023/06/05 08:23:37 - mmengine - INFO - Epoch(train) [84][1920/2569] lr: 4.0000e-02 eta: 12:33:45 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 3.1447 loss: 2.4447 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4447 2023/06/05 08:23:42 - mmengine - INFO - Epoch(train) [84][1940/2569] lr: 4.0000e-02 eta: 12:33:40 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 3.1294 loss: 2.2284 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2284 2023/06/05 08:23:47 - mmengine - INFO - Epoch(train) [84][1960/2569] lr: 4.0000e-02 eta: 12:33:35 time: 0.2642 data_time: 0.0072 memory: 5828 grad_norm: 3.1152 loss: 2.9496 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9496 2023/06/05 08:23:53 - mmengine - INFO - Epoch(train) [84][1980/2569] lr: 4.0000e-02 eta: 12:33:30 time: 0.2700 data_time: 0.0073 memory: 5828 grad_norm: 3.1504 loss: 2.2875 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2875 2023/06/05 08:23:58 - mmengine - INFO - Epoch(train) [84][2000/2569] lr: 4.0000e-02 eta: 12:33:24 time: 0.2647 data_time: 0.0076 memory: 5828 grad_norm: 3.1884 loss: 2.4910 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4910 2023/06/05 08:24:04 - mmengine - INFO - Epoch(train) [84][2020/2569] lr: 4.0000e-02 eta: 12:33:19 time: 0.2700 data_time: 0.0076 memory: 5828 grad_norm: 3.1602 loss: 2.7432 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7432 2023/06/05 08:24:09 - mmengine - INFO - Epoch(train) [84][2040/2569] lr: 4.0000e-02 eta: 12:33:14 time: 0.2588 data_time: 0.0071 memory: 5828 grad_norm: 3.1031 loss: 2.4638 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4638 2023/06/05 08:24:14 - mmengine - INFO - Epoch(train) [84][2060/2569] lr: 4.0000e-02 eta: 12:33:08 time: 0.2653 data_time: 0.0075 memory: 5828 grad_norm: 3.1594 loss: 2.7999 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7999 2023/06/05 08:24:19 - mmengine - INFO - Epoch(train) [84][2080/2569] lr: 4.0000e-02 eta: 12:33:03 time: 0.2626 data_time: 0.0076 memory: 5828 grad_norm: 3.1305 loss: 2.2536 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2536 2023/06/05 08:24:25 - mmengine - INFO - Epoch(train) [84][2100/2569] lr: 4.0000e-02 eta: 12:32:58 time: 0.2772 data_time: 0.0080 memory: 5828 grad_norm: 3.1189 loss: 2.7272 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7272 2023/06/05 08:24:30 - mmengine - INFO - Epoch(train) [84][2120/2569] lr: 4.0000e-02 eta: 12:32:52 time: 0.2688 data_time: 0.0075 memory: 5828 grad_norm: 3.1741 loss: 2.4519 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4519 2023/06/05 08:24:36 - mmengine - INFO - Epoch(train) [84][2140/2569] lr: 4.0000e-02 eta: 12:32:47 time: 0.2782 data_time: 0.0077 memory: 5828 grad_norm: 3.1690 loss: 2.0993 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0993 2023/06/05 08:24:41 - mmengine - INFO - Epoch(train) [84][2160/2569] lr: 4.0000e-02 eta: 12:32:42 time: 0.2597 data_time: 0.0074 memory: 5828 grad_norm: 3.1473 loss: 2.7172 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7172 2023/06/05 08:24:47 - mmengine - INFO - Epoch(train) [84][2180/2569] lr: 4.0000e-02 eta: 12:32:37 time: 0.2798 data_time: 0.0075 memory: 5828 grad_norm: 3.0719 loss: 2.4052 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4052 2023/06/05 08:24:52 - mmengine - INFO - Epoch(train) [84][2200/2569] lr: 4.0000e-02 eta: 12:32:31 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 3.1006 loss: 2.8389 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8389 2023/06/05 08:24:57 - mmengine - INFO - Epoch(train) [84][2220/2569] lr: 4.0000e-02 eta: 12:32:26 time: 0.2749 data_time: 0.0074 memory: 5828 grad_norm: 3.1514 loss: 2.5735 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5735 2023/06/05 08:25:03 - mmengine - INFO - Epoch(train) [84][2240/2569] lr: 4.0000e-02 eta: 12:32:21 time: 0.2603 data_time: 0.0078 memory: 5828 grad_norm: 3.1827 loss: 2.6582 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6582 2023/06/05 08:25:08 - mmengine - INFO - Epoch(train) [84][2260/2569] lr: 4.0000e-02 eta: 12:32:16 time: 0.2673 data_time: 0.0078 memory: 5828 grad_norm: 3.1316 loss: 2.5521 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5521 2023/06/05 08:25:13 - mmengine - INFO - Epoch(train) [84][2280/2569] lr: 4.0000e-02 eta: 12:32:10 time: 0.2602 data_time: 0.0079 memory: 5828 grad_norm: 3.1486 loss: 2.6084 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6084 2023/06/05 08:25:19 - mmengine - INFO - Epoch(train) [84][2300/2569] lr: 4.0000e-02 eta: 12:32:05 time: 0.2712 data_time: 0.0073 memory: 5828 grad_norm: 3.0979 loss: 2.3793 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3793 2023/06/05 08:25:24 - mmengine - INFO - Epoch(train) [84][2320/2569] lr: 4.0000e-02 eta: 12:32:00 time: 0.2588 data_time: 0.0081 memory: 5828 grad_norm: 3.1253 loss: 2.5303 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5303 2023/06/05 08:25:29 - mmengine - INFO - Epoch(train) [84][2340/2569] lr: 4.0000e-02 eta: 12:31:54 time: 0.2597 data_time: 0.0071 memory: 5828 grad_norm: 3.0768 loss: 2.4050 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4050 2023/06/05 08:25:34 - mmengine - INFO - Epoch(train) [84][2360/2569] lr: 4.0000e-02 eta: 12:31:49 time: 0.2699 data_time: 0.0071 memory: 5828 grad_norm: 3.1038 loss: 2.5359 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5359 2023/06/05 08:25:40 - mmengine - INFO - Epoch(train) [84][2380/2569] lr: 4.0000e-02 eta: 12:31:44 time: 0.2703 data_time: 0.0073 memory: 5828 grad_norm: 3.1116 loss: 2.4595 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4595 2023/06/05 08:25:45 - mmengine - INFO - Epoch(train) [84][2400/2569] lr: 4.0000e-02 eta: 12:31:38 time: 0.2716 data_time: 0.0080 memory: 5828 grad_norm: 3.0872 loss: 3.0843 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0843 2023/06/05 08:25:51 - mmengine - INFO - Epoch(train) [84][2420/2569] lr: 4.0000e-02 eta: 12:31:33 time: 0.2630 data_time: 0.0082 memory: 5828 grad_norm: 3.1552 loss: 2.7214 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7214 2023/06/05 08:25:56 - mmengine - INFO - Epoch(train) [84][2440/2569] lr: 4.0000e-02 eta: 12:31:28 time: 0.2698 data_time: 0.0071 memory: 5828 grad_norm: 3.1365 loss: 2.4481 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4481 2023/06/05 08:26:01 - mmengine - INFO - Epoch(train) [84][2460/2569] lr: 4.0000e-02 eta: 12:31:22 time: 0.2603 data_time: 0.0072 memory: 5828 grad_norm: 3.1041 loss: 2.2361 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2361 2023/06/05 08:26:06 - mmengine - INFO - Epoch(train) [84][2480/2569] lr: 4.0000e-02 eta: 12:31:17 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 3.1014 loss: 2.5469 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5469 2023/06/05 08:26:12 - mmengine - INFO - Epoch(train) [84][2500/2569] lr: 4.0000e-02 eta: 12:31:12 time: 0.2646 data_time: 0.0072 memory: 5828 grad_norm: 3.2189 loss: 2.7880 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7880 2023/06/05 08:26:17 - mmengine - INFO - Epoch(train) [84][2520/2569] lr: 4.0000e-02 eta: 12:31:06 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 3.1948 loss: 2.4729 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4729 2023/06/05 08:26:22 - mmengine - INFO - Epoch(train) [84][2540/2569] lr: 4.0000e-02 eta: 12:31:01 time: 0.2608 data_time: 0.0076 memory: 5828 grad_norm: 3.0943 loss: 2.6477 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6477 2023/06/05 08:26:27 - mmengine - INFO - Epoch(train) [84][2560/2569] lr: 4.0000e-02 eta: 12:30:56 time: 0.2607 data_time: 0.0076 memory: 5828 grad_norm: 3.1554 loss: 2.4274 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4274 2023/06/05 08:26:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:26:30 - mmengine - INFO - Epoch(train) [84][2569/2569] lr: 4.0000e-02 eta: 12:30:53 time: 0.2530 data_time: 0.0073 memory: 5828 grad_norm: 3.1780 loss: 2.3592 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3592 2023/06/05 08:26:30 - mmengine - INFO - Saving checkpoint at 84 epochs 2023/06/05 08:26:38 - mmengine - INFO - Epoch(train) [85][ 20/2569] lr: 4.0000e-02 eta: 12:30:49 time: 0.3168 data_time: 0.0539 memory: 5828 grad_norm: 3.1575 loss: 2.5044 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5044 2023/06/05 08:26:43 - mmengine - INFO - Epoch(train) [85][ 40/2569] lr: 4.0000e-02 eta: 12:30:43 time: 0.2683 data_time: 0.0074 memory: 5828 grad_norm: 3.1003 loss: 2.5141 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5141 2023/06/05 08:26:49 - mmengine - INFO - Epoch(train) [85][ 60/2569] lr: 4.0000e-02 eta: 12:30:38 time: 0.2637 data_time: 0.0076 memory: 5828 grad_norm: 3.1519 loss: 2.5422 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5422 2023/06/05 08:26:54 - mmengine - INFO - Epoch(train) [85][ 80/2569] lr: 4.0000e-02 eta: 12:30:33 time: 0.2635 data_time: 0.0077 memory: 5828 grad_norm: 3.1730 loss: 2.1820 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1820 2023/06/05 08:26:59 - mmengine - INFO - Epoch(train) [85][ 100/2569] lr: 4.0000e-02 eta: 12:30:27 time: 0.2688 data_time: 0.0072 memory: 5828 grad_norm: 3.1047 loss: 2.8303 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8303 2023/06/05 08:27:04 - mmengine - INFO - Epoch(train) [85][ 120/2569] lr: 4.0000e-02 eta: 12:30:22 time: 0.2602 data_time: 0.0076 memory: 5828 grad_norm: 3.1073 loss: 2.2558 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.2558 2023/06/05 08:27:10 - mmengine - INFO - Epoch(train) [85][ 140/2569] lr: 4.0000e-02 eta: 12:30:17 time: 0.2742 data_time: 0.0081 memory: 5828 grad_norm: 3.1582 loss: 2.7749 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7749 2023/06/05 08:27:15 - mmengine - INFO - Epoch(train) [85][ 160/2569] lr: 4.0000e-02 eta: 12:30:11 time: 0.2583 data_time: 0.0075 memory: 5828 grad_norm: 3.1231 loss: 2.2306 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2306 2023/06/05 08:27:20 - mmengine - INFO - Epoch(train) [85][ 180/2569] lr: 4.0000e-02 eta: 12:30:06 time: 0.2653 data_time: 0.0073 memory: 5828 grad_norm: 3.1917 loss: 2.3139 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3139 2023/06/05 08:27:26 - mmengine - INFO - Epoch(train) [85][ 200/2569] lr: 4.0000e-02 eta: 12:30:01 time: 0.2575 data_time: 0.0072 memory: 5828 grad_norm: 3.0744 loss: 2.7665 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7665 2023/06/05 08:27:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:27:31 - mmengine - INFO - Epoch(train) [85][ 220/2569] lr: 4.0000e-02 eta: 12:29:55 time: 0.2706 data_time: 0.0072 memory: 5828 grad_norm: 3.1236 loss: 2.4779 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4779 2023/06/05 08:27:36 - mmengine - INFO - Epoch(train) [85][ 240/2569] lr: 4.0000e-02 eta: 12:29:50 time: 0.2597 data_time: 0.0083 memory: 5828 grad_norm: 3.1048 loss: 2.5925 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5925 2023/06/05 08:27:42 - mmengine - INFO - Epoch(train) [85][ 260/2569] lr: 4.0000e-02 eta: 12:29:45 time: 0.2758 data_time: 0.0072 memory: 5828 grad_norm: 3.0921 loss: 2.7642 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7642 2023/06/05 08:27:47 - mmengine - INFO - Epoch(train) [85][ 280/2569] lr: 4.0000e-02 eta: 12:29:39 time: 0.2595 data_time: 0.0075 memory: 5828 grad_norm: 3.1378 loss: 2.9112 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9112 2023/06/05 08:27:52 - mmengine - INFO - Epoch(train) [85][ 300/2569] lr: 4.0000e-02 eta: 12:29:34 time: 0.2629 data_time: 0.0070 memory: 5828 grad_norm: 3.0932 loss: 2.7357 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7357 2023/06/05 08:27:58 - mmengine - INFO - Epoch(train) [85][ 320/2569] lr: 4.0000e-02 eta: 12:29:29 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.0769 loss: 2.4987 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4987 2023/06/05 08:28:03 - mmengine - INFO - Epoch(train) [85][ 340/2569] lr: 4.0000e-02 eta: 12:29:23 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 3.1168 loss: 2.4252 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4252 2023/06/05 08:28:08 - mmengine - INFO - Epoch(train) [85][ 360/2569] lr: 4.0000e-02 eta: 12:29:18 time: 0.2734 data_time: 0.0073 memory: 5828 grad_norm: 3.2026 loss: 2.3827 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3827 2023/06/05 08:28:14 - mmengine - INFO - Epoch(train) [85][ 380/2569] lr: 4.0000e-02 eta: 12:29:13 time: 0.2646 data_time: 0.0066 memory: 5828 grad_norm: 3.1537 loss: 2.4901 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4901 2023/06/05 08:28:19 - mmengine - INFO - Epoch(train) [85][ 400/2569] lr: 4.0000e-02 eta: 12:29:07 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 3.1375 loss: 2.1570 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.1570 2023/06/05 08:28:24 - mmengine - INFO - Epoch(train) [85][ 420/2569] lr: 4.0000e-02 eta: 12:29:02 time: 0.2600 data_time: 0.0072 memory: 5828 grad_norm: 3.0681 loss: 2.2392 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2392 2023/06/05 08:28:29 - mmengine - INFO - Epoch(train) [85][ 440/2569] lr: 4.0000e-02 eta: 12:28:57 time: 0.2634 data_time: 0.0073 memory: 5828 grad_norm: 3.1829 loss: 2.6065 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6065 2023/06/05 08:28:35 - mmengine - INFO - Epoch(train) [85][ 460/2569] lr: 4.0000e-02 eta: 12:28:51 time: 0.2647 data_time: 0.0072 memory: 5828 grad_norm: 3.1137 loss: 2.6491 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6491 2023/06/05 08:28:40 - mmengine - INFO - Epoch(train) [85][ 480/2569] lr: 4.0000e-02 eta: 12:28:46 time: 0.2647 data_time: 0.0070 memory: 5828 grad_norm: 3.1666 loss: 2.1324 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1324 2023/06/05 08:28:45 - mmengine - INFO - Epoch(train) [85][ 500/2569] lr: 4.0000e-02 eta: 12:28:41 time: 0.2585 data_time: 0.0073 memory: 5828 grad_norm: 3.1414 loss: 2.6811 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6811 2023/06/05 08:28:51 - mmengine - INFO - Epoch(train) [85][ 520/2569] lr: 4.0000e-02 eta: 12:28:35 time: 0.2759 data_time: 0.0068 memory: 5828 grad_norm: 3.1476 loss: 2.6235 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6235 2023/06/05 08:28:56 - mmengine - INFO - Epoch(train) [85][ 540/2569] lr: 4.0000e-02 eta: 12:28:30 time: 0.2589 data_time: 0.0071 memory: 5828 grad_norm: 3.2474 loss: 2.5511 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5511 2023/06/05 08:29:01 - mmengine - INFO - Epoch(train) [85][ 560/2569] lr: 4.0000e-02 eta: 12:28:25 time: 0.2640 data_time: 0.0071 memory: 5828 grad_norm: 3.1356 loss: 2.5395 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5395 2023/06/05 08:29:06 - mmengine - INFO - Epoch(train) [85][ 580/2569] lr: 4.0000e-02 eta: 12:28:19 time: 0.2587 data_time: 0.0071 memory: 5828 grad_norm: 3.1315 loss: 2.5587 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5587 2023/06/05 08:29:12 - mmengine - INFO - Epoch(train) [85][ 600/2569] lr: 4.0000e-02 eta: 12:28:14 time: 0.2700 data_time: 0.0072 memory: 5828 grad_norm: 3.1149 loss: 2.3882 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3882 2023/06/05 08:29:17 - mmengine - INFO - Epoch(train) [85][ 620/2569] lr: 4.0000e-02 eta: 12:28:09 time: 0.2707 data_time: 0.0073 memory: 5828 grad_norm: 3.1696 loss: 2.5500 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.5500 2023/06/05 08:29:22 - mmengine - INFO - Epoch(train) [85][ 640/2569] lr: 4.0000e-02 eta: 12:28:03 time: 0.2672 data_time: 0.0076 memory: 5828 grad_norm: 3.1048 loss: 2.6682 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6682 2023/06/05 08:29:28 - mmengine - INFO - Epoch(train) [85][ 660/2569] lr: 4.0000e-02 eta: 12:27:58 time: 0.2646 data_time: 0.0071 memory: 5828 grad_norm: 3.1665 loss: 2.3061 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3061 2023/06/05 08:29:33 - mmengine - INFO - Epoch(train) [85][ 680/2569] lr: 4.0000e-02 eta: 12:27:53 time: 0.2712 data_time: 0.0075 memory: 5828 grad_norm: 3.1050 loss: 2.2306 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2306 2023/06/05 08:29:38 - mmengine - INFO - Epoch(train) [85][ 700/2569] lr: 4.0000e-02 eta: 12:27:48 time: 0.2610 data_time: 0.0073 memory: 5828 grad_norm: 3.1715 loss: 2.4957 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4957 2023/06/05 08:29:44 - mmengine - INFO - Epoch(train) [85][ 720/2569] lr: 4.0000e-02 eta: 12:27:42 time: 0.2739 data_time: 0.0073 memory: 5828 grad_norm: 3.1965 loss: 2.5277 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5277 2023/06/05 08:29:49 - mmengine - INFO - Epoch(train) [85][ 740/2569] lr: 4.0000e-02 eta: 12:27:37 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 3.1006 loss: 2.5466 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5466 2023/06/05 08:29:55 - mmengine - INFO - Epoch(train) [85][ 760/2569] lr: 4.0000e-02 eta: 12:27:32 time: 0.2700 data_time: 0.0086 memory: 5828 grad_norm: 3.1244 loss: 2.5065 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5065 2023/06/05 08:30:00 - mmengine - INFO - Epoch(train) [85][ 780/2569] lr: 4.0000e-02 eta: 12:27:26 time: 0.2649 data_time: 0.0071 memory: 5828 grad_norm: 3.1373 loss: 2.2848 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2848 2023/06/05 08:30:05 - mmengine - INFO - Epoch(train) [85][ 800/2569] lr: 4.0000e-02 eta: 12:27:21 time: 0.2757 data_time: 0.0074 memory: 5828 grad_norm: 3.1057 loss: 2.5910 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5910 2023/06/05 08:30:11 - mmengine - INFO - Epoch(train) [85][ 820/2569] lr: 4.0000e-02 eta: 12:27:16 time: 0.2603 data_time: 0.0073 memory: 5828 grad_norm: 3.1592 loss: 2.6175 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6175 2023/06/05 08:30:16 - mmengine - INFO - Epoch(train) [85][ 840/2569] lr: 4.0000e-02 eta: 12:27:11 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 3.1829 loss: 2.8818 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8818 2023/06/05 08:30:21 - mmengine - INFO - Epoch(train) [85][ 860/2569] lr: 4.0000e-02 eta: 12:27:05 time: 0.2567 data_time: 0.0071 memory: 5828 grad_norm: 3.0700 loss: 2.4939 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4939 2023/06/05 08:30:26 - mmengine - INFO - Epoch(train) [85][ 880/2569] lr: 4.0000e-02 eta: 12:27:00 time: 0.2682 data_time: 0.0071 memory: 5828 grad_norm: 3.1629 loss: 2.4224 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4224 2023/06/05 08:30:32 - mmengine - INFO - Epoch(train) [85][ 900/2569] lr: 4.0000e-02 eta: 12:26:54 time: 0.2601 data_time: 0.0072 memory: 5828 grad_norm: 3.1434 loss: 2.3322 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3322 2023/06/05 08:30:37 - mmengine - INFO - Epoch(train) [85][ 920/2569] lr: 4.0000e-02 eta: 12:26:49 time: 0.2603 data_time: 0.0072 memory: 5828 grad_norm: 3.0368 loss: 2.5491 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5491 2023/06/05 08:30:42 - mmengine - INFO - Epoch(train) [85][ 940/2569] lr: 4.0000e-02 eta: 12:26:44 time: 0.2595 data_time: 0.0073 memory: 5828 grad_norm: 3.1356 loss: 2.2991 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2991 2023/06/05 08:30:47 - mmengine - INFO - Epoch(train) [85][ 960/2569] lr: 4.0000e-02 eta: 12:26:38 time: 0.2701 data_time: 0.0074 memory: 5828 grad_norm: 3.1333 loss: 2.4290 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4290 2023/06/05 08:30:53 - mmengine - INFO - Epoch(train) [85][ 980/2569] lr: 4.0000e-02 eta: 12:26:33 time: 0.2645 data_time: 0.0082 memory: 5828 grad_norm: 3.1309 loss: 2.5450 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5450 2023/06/05 08:30:58 - mmengine - INFO - Epoch(train) [85][1000/2569] lr: 4.0000e-02 eta: 12:26:28 time: 0.2649 data_time: 0.0075 memory: 5828 grad_norm: 3.1146 loss: 2.5390 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5390 2023/06/05 08:31:03 - mmengine - INFO - Epoch(train) [85][1020/2569] lr: 4.0000e-02 eta: 12:26:22 time: 0.2595 data_time: 0.0077 memory: 5828 grad_norm: 3.1708 loss: 2.3810 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3810 2023/06/05 08:31:08 - mmengine - INFO - Epoch(train) [85][1040/2569] lr: 4.0000e-02 eta: 12:26:17 time: 0.2609 data_time: 0.0083 memory: 5828 grad_norm: 3.1591 loss: 2.2775 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2775 2023/06/05 08:31:14 - mmengine - INFO - Epoch(train) [85][1060/2569] lr: 4.0000e-02 eta: 12:26:11 time: 0.2577 data_time: 0.0076 memory: 5828 grad_norm: 3.1180 loss: 2.6809 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6809 2023/06/05 08:31:19 - mmengine - INFO - Epoch(train) [85][1080/2569] lr: 4.0000e-02 eta: 12:26:06 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.1606 loss: 2.3748 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3748 2023/06/05 08:31:24 - mmengine - INFO - Epoch(train) [85][1100/2569] lr: 4.0000e-02 eta: 12:26:01 time: 0.2639 data_time: 0.0077 memory: 5828 grad_norm: 3.1267 loss: 2.5303 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5303 2023/06/05 08:31:29 - mmengine - INFO - Epoch(train) [85][1120/2569] lr: 4.0000e-02 eta: 12:25:55 time: 0.2614 data_time: 0.0075 memory: 5828 grad_norm: 3.1374 loss: 2.5823 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5823 2023/06/05 08:31:35 - mmengine - INFO - Epoch(train) [85][1140/2569] lr: 4.0000e-02 eta: 12:25:50 time: 0.2697 data_time: 0.0079 memory: 5828 grad_norm: 3.1758 loss: 2.3855 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3855 2023/06/05 08:31:40 - mmengine - INFO - Epoch(train) [85][1160/2569] lr: 4.0000e-02 eta: 12:25:45 time: 0.2638 data_time: 0.0080 memory: 5828 grad_norm: 3.1671 loss: 2.3933 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3933 2023/06/05 08:31:45 - mmengine - INFO - Epoch(train) [85][1180/2569] lr: 4.0000e-02 eta: 12:25:39 time: 0.2601 data_time: 0.0070 memory: 5828 grad_norm: 3.0788 loss: 2.7261 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7261 2023/06/05 08:31:51 - mmengine - INFO - Epoch(train) [85][1200/2569] lr: 4.0000e-02 eta: 12:25:34 time: 0.2596 data_time: 0.0073 memory: 5828 grad_norm: 3.1154 loss: 2.3908 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3908 2023/06/05 08:31:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:31:56 - mmengine - INFO - Epoch(train) [85][1220/2569] lr: 4.0000e-02 eta: 12:25:29 time: 0.2671 data_time: 0.0071 memory: 5828 grad_norm: 3.1793 loss: 2.5379 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5379 2023/06/05 08:32:01 - mmengine - INFO - Epoch(train) [85][1240/2569] lr: 4.0000e-02 eta: 12:25:23 time: 0.2596 data_time: 0.0073 memory: 5828 grad_norm: 3.0798 loss: 2.3491 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3491 2023/06/05 08:32:06 - mmengine - INFO - Epoch(train) [85][1260/2569] lr: 4.0000e-02 eta: 12:25:18 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 3.0945 loss: 2.7192 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7192 2023/06/05 08:32:12 - mmengine - INFO - Epoch(train) [85][1280/2569] lr: 4.0000e-02 eta: 12:25:13 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 3.0758 loss: 2.3809 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3809 2023/06/05 08:32:17 - mmengine - INFO - Epoch(train) [85][1300/2569] lr: 4.0000e-02 eta: 12:25:07 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 3.0878 loss: 2.4606 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4606 2023/06/05 08:32:23 - mmengine - INFO - Epoch(train) [85][1320/2569] lr: 4.0000e-02 eta: 12:25:02 time: 0.2753 data_time: 0.0078 memory: 5828 grad_norm: 3.1564 loss: 2.4294 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4294 2023/06/05 08:32:28 - mmengine - INFO - Epoch(train) [85][1340/2569] lr: 4.0000e-02 eta: 12:24:57 time: 0.2628 data_time: 0.0073 memory: 5828 grad_norm: 3.1490 loss: 2.7910 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7910 2023/06/05 08:32:33 - mmengine - INFO - Epoch(train) [85][1360/2569] lr: 4.0000e-02 eta: 12:24:51 time: 0.2576 data_time: 0.0072 memory: 5828 grad_norm: 3.1009 loss: 2.4797 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4797 2023/06/05 08:32:38 - mmengine - INFO - Epoch(train) [85][1380/2569] lr: 4.0000e-02 eta: 12:24:46 time: 0.2665 data_time: 0.0083 memory: 5828 grad_norm: 3.1040 loss: 2.2883 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2883 2023/06/05 08:32:44 - mmengine - INFO - Epoch(train) [85][1400/2569] lr: 4.0000e-02 eta: 12:24:41 time: 0.2596 data_time: 0.0073 memory: 5828 grad_norm: 3.1599 loss: 2.5402 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5402 2023/06/05 08:32:49 - mmengine - INFO - Epoch(train) [85][1420/2569] lr: 4.0000e-02 eta: 12:24:35 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 3.1507 loss: 2.3841 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3841 2023/06/05 08:32:54 - mmengine - INFO - Epoch(train) [85][1440/2569] lr: 4.0000e-02 eta: 12:24:30 time: 0.2658 data_time: 0.0074 memory: 5828 grad_norm: 3.1385 loss: 2.6448 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6448 2023/06/05 08:33:00 - mmengine - INFO - Epoch(train) [85][1460/2569] lr: 4.0000e-02 eta: 12:24:25 time: 0.2699 data_time: 0.0075 memory: 5828 grad_norm: 3.1085 loss: 2.3895 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3895 2023/06/05 08:33:05 - mmengine - INFO - Epoch(train) [85][1480/2569] lr: 4.0000e-02 eta: 12:24:20 time: 0.2743 data_time: 0.0076 memory: 5828 grad_norm: 3.2067 loss: 2.6336 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6336 2023/06/05 08:33:11 - mmengine - INFO - Epoch(train) [85][1500/2569] lr: 4.0000e-02 eta: 12:24:14 time: 0.2755 data_time: 0.0076 memory: 5828 grad_norm: 3.1748 loss: 2.9556 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9556 2023/06/05 08:33:16 - mmengine - INFO - Epoch(train) [85][1520/2569] lr: 4.0000e-02 eta: 12:24:09 time: 0.2589 data_time: 0.0079 memory: 5828 grad_norm: 3.1164 loss: 2.4311 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4311 2023/06/05 08:33:21 - mmengine - INFO - Epoch(train) [85][1540/2569] lr: 4.0000e-02 eta: 12:24:04 time: 0.2679 data_time: 0.0076 memory: 5828 grad_norm: 3.1318 loss: 2.4524 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4524 2023/06/05 08:33:26 - mmengine - INFO - Epoch(train) [85][1560/2569] lr: 4.0000e-02 eta: 12:23:58 time: 0.2593 data_time: 0.0075 memory: 5828 grad_norm: 3.1762 loss: 2.4380 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4380 2023/06/05 08:33:32 - mmengine - INFO - Epoch(train) [85][1580/2569] lr: 4.0000e-02 eta: 12:23:53 time: 0.2584 data_time: 0.0077 memory: 5828 grad_norm: 3.0988 loss: 2.2946 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2946 2023/06/05 08:33:37 - mmengine - INFO - Epoch(train) [85][1600/2569] lr: 4.0000e-02 eta: 12:23:48 time: 0.2613 data_time: 0.0073 memory: 5828 grad_norm: 3.1401 loss: 2.4156 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4156 2023/06/05 08:33:42 - mmengine - INFO - Epoch(train) [85][1620/2569] lr: 4.0000e-02 eta: 12:23:42 time: 0.2629 data_time: 0.0074 memory: 5828 grad_norm: 3.1175 loss: 2.7253 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7253 2023/06/05 08:33:48 - mmengine - INFO - Epoch(train) [85][1640/2569] lr: 4.0000e-02 eta: 12:23:37 time: 0.2760 data_time: 0.0075 memory: 5828 grad_norm: 3.1640 loss: 2.4491 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4491 2023/06/05 08:33:53 - mmengine - INFO - Epoch(train) [85][1660/2569] lr: 4.0000e-02 eta: 12:23:32 time: 0.2784 data_time: 0.0072 memory: 5828 grad_norm: 3.1963 loss: 2.1267 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1267 2023/06/05 08:33:58 - mmengine - INFO - Epoch(train) [85][1680/2569] lr: 4.0000e-02 eta: 12:23:27 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 3.1431 loss: 2.4999 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4999 2023/06/05 08:34:04 - mmengine - INFO - Epoch(train) [85][1700/2569] lr: 4.0000e-02 eta: 12:23:21 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 3.2056 loss: 2.6581 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6581 2023/06/05 08:34:09 - mmengine - INFO - Epoch(train) [85][1720/2569] lr: 4.0000e-02 eta: 12:23:16 time: 0.2739 data_time: 0.0077 memory: 5828 grad_norm: 3.1180 loss: 2.9198 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9198 2023/06/05 08:34:15 - mmengine - INFO - Epoch(train) [85][1740/2569] lr: 4.0000e-02 eta: 12:23:11 time: 0.2705 data_time: 0.0076 memory: 5828 grad_norm: 3.1060 loss: 2.7441 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7441 2023/06/05 08:34:20 - mmengine - INFO - Epoch(train) [85][1760/2569] lr: 4.0000e-02 eta: 12:23:06 time: 0.2653 data_time: 0.0078 memory: 5828 grad_norm: 3.1937 loss: 2.4451 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4451 2023/06/05 08:34:25 - mmengine - INFO - Epoch(train) [85][1780/2569] lr: 4.0000e-02 eta: 12:23:00 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 3.2311 loss: 2.5146 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5146 2023/06/05 08:34:31 - mmengine - INFO - Epoch(train) [85][1800/2569] lr: 4.0000e-02 eta: 12:22:55 time: 0.2596 data_time: 0.0083 memory: 5828 grad_norm: 3.0881 loss: 2.7249 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7249 2023/06/05 08:34:36 - mmengine - INFO - Epoch(train) [85][1820/2569] lr: 4.0000e-02 eta: 12:22:50 time: 0.2633 data_time: 0.0073 memory: 5828 grad_norm: 3.1651 loss: 2.7021 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7021 2023/06/05 08:34:41 - mmengine - INFO - Epoch(train) [85][1840/2569] lr: 4.0000e-02 eta: 12:22:44 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 3.1088 loss: 2.6622 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6622 2023/06/05 08:34:47 - mmengine - INFO - Epoch(train) [85][1860/2569] lr: 4.0000e-02 eta: 12:22:39 time: 0.2638 data_time: 0.0077 memory: 5828 grad_norm: 3.1734 loss: 2.4604 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4604 2023/06/05 08:34:52 - mmengine - INFO - Epoch(train) [85][1880/2569] lr: 4.0000e-02 eta: 12:22:34 time: 0.2637 data_time: 0.0080 memory: 5828 grad_norm: 3.1162 loss: 2.4809 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.4809 2023/06/05 08:34:57 - mmengine - INFO - Epoch(train) [85][1900/2569] lr: 4.0000e-02 eta: 12:22:28 time: 0.2590 data_time: 0.0080 memory: 5828 grad_norm: 3.1688 loss: 2.5364 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5364 2023/06/05 08:35:02 - mmengine - INFO - Epoch(train) [85][1920/2569] lr: 4.0000e-02 eta: 12:22:23 time: 0.2595 data_time: 0.0077 memory: 5828 grad_norm: 3.1432 loss: 2.5429 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5429 2023/06/05 08:35:07 - mmengine - INFO - Epoch(train) [85][1940/2569] lr: 4.0000e-02 eta: 12:22:17 time: 0.2575 data_time: 0.0079 memory: 5828 grad_norm: 3.1143 loss: 2.4502 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4502 2023/06/05 08:35:13 - mmengine - INFO - Epoch(train) [85][1960/2569] lr: 4.0000e-02 eta: 12:22:12 time: 0.2682 data_time: 0.0077 memory: 5828 grad_norm: 3.0809 loss: 2.5208 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5208 2023/06/05 08:35:18 - mmengine - INFO - Epoch(train) [85][1980/2569] lr: 4.0000e-02 eta: 12:22:07 time: 0.2584 data_time: 0.0074 memory: 5828 grad_norm: 3.1729 loss: 2.6841 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6841 2023/06/05 08:35:24 - mmengine - INFO - Epoch(train) [85][2000/2569] lr: 4.0000e-02 eta: 12:22:01 time: 0.2743 data_time: 0.0079 memory: 5828 grad_norm: 3.1478 loss: 2.5484 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5484 2023/06/05 08:35:29 - mmengine - INFO - Epoch(train) [85][2020/2569] lr: 4.0000e-02 eta: 12:21:56 time: 0.2588 data_time: 0.0075 memory: 5828 grad_norm: 3.1604 loss: 2.5330 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5330 2023/06/05 08:35:34 - mmengine - INFO - Epoch(train) [85][2040/2569] lr: 4.0000e-02 eta: 12:21:51 time: 0.2620 data_time: 0.0078 memory: 5828 grad_norm: 3.1113 loss: 2.2471 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2471 2023/06/05 08:35:39 - mmengine - INFO - Epoch(train) [85][2060/2569] lr: 4.0000e-02 eta: 12:21:45 time: 0.2636 data_time: 0.0070 memory: 5828 grad_norm: 3.1385 loss: 2.3031 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.3031 2023/06/05 08:35:44 - mmengine - INFO - Epoch(train) [85][2080/2569] lr: 4.0000e-02 eta: 12:21:40 time: 0.2586 data_time: 0.0074 memory: 5828 grad_norm: 3.1118 loss: 2.7750 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7750 2023/06/05 08:35:50 - mmengine - INFO - Epoch(train) [85][2100/2569] lr: 4.0000e-02 eta: 12:21:35 time: 0.2710 data_time: 0.0072 memory: 5828 grad_norm: 3.1105 loss: 2.6442 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6442 2023/06/05 08:35:55 - mmengine - INFO - Epoch(train) [85][2120/2569] lr: 4.0000e-02 eta: 12:21:29 time: 0.2607 data_time: 0.0074 memory: 5828 grad_norm: 3.0675 loss: 2.7484 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7484 2023/06/05 08:36:00 - mmengine - INFO - Epoch(train) [85][2140/2569] lr: 4.0000e-02 eta: 12:21:24 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 3.1356 loss: 2.3427 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3427 2023/06/05 08:36:06 - mmengine - INFO - Epoch(train) [85][2160/2569] lr: 4.0000e-02 eta: 12:21:19 time: 0.2640 data_time: 0.0072 memory: 5828 grad_norm: 3.0947 loss: 2.3457 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3457 2023/06/05 08:36:11 - mmengine - INFO - Epoch(train) [85][2180/2569] lr: 4.0000e-02 eta: 12:21:13 time: 0.2640 data_time: 0.0075 memory: 5828 grad_norm: 3.0875 loss: 2.6903 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6903 2023/06/05 08:36:16 - mmengine - INFO - Epoch(train) [85][2200/2569] lr: 4.0000e-02 eta: 12:21:08 time: 0.2610 data_time: 0.0074 memory: 5828 grad_norm: 3.1400 loss: 2.4635 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4635 2023/06/05 08:36:17 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:36:22 - mmengine - INFO - Epoch(train) [85][2220/2569] lr: 4.0000e-02 eta: 12:21:03 time: 0.2771 data_time: 0.0075 memory: 5828 grad_norm: 3.2145 loss: 2.7595 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7595 2023/06/05 08:36:27 - mmengine - INFO - Epoch(train) [85][2240/2569] lr: 4.0000e-02 eta: 12:20:57 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 3.0894 loss: 2.4835 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4835 2023/06/05 08:36:32 - mmengine - INFO - Epoch(train) [85][2260/2569] lr: 4.0000e-02 eta: 12:20:52 time: 0.2740 data_time: 0.0071 memory: 5828 grad_norm: 3.1453 loss: 2.4702 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4702 2023/06/05 08:36:38 - mmengine - INFO - Epoch(train) [85][2280/2569] lr: 4.0000e-02 eta: 12:20:47 time: 0.2704 data_time: 0.0076 memory: 5828 grad_norm: 3.1317 loss: 2.8442 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8442 2023/06/05 08:36:43 - mmengine - INFO - Epoch(train) [85][2300/2569] lr: 4.0000e-02 eta: 12:20:42 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 3.1104 loss: 2.5222 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5222 2023/06/05 08:36:48 - mmengine - INFO - Epoch(train) [85][2320/2569] lr: 4.0000e-02 eta: 12:20:36 time: 0.2596 data_time: 0.0075 memory: 5828 grad_norm: 3.1115 loss: 2.1750 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1750 2023/06/05 08:36:54 - mmengine - INFO - Epoch(train) [85][2340/2569] lr: 4.0000e-02 eta: 12:20:31 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 3.0564 loss: 2.9425 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.9425 2023/06/05 08:36:59 - mmengine - INFO - Epoch(train) [85][2360/2569] lr: 4.0000e-02 eta: 12:20:26 time: 0.2696 data_time: 0.0073 memory: 5828 grad_norm: 3.2034 loss: 2.5436 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.5436 2023/06/05 08:37:04 - mmengine - INFO - Epoch(train) [85][2380/2569] lr: 4.0000e-02 eta: 12:20:20 time: 0.2590 data_time: 0.0071 memory: 5828 grad_norm: 3.1008 loss: 2.5427 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5427 2023/06/05 08:37:10 - mmengine - INFO - Epoch(train) [85][2400/2569] lr: 4.0000e-02 eta: 12:20:15 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 3.1842 loss: 2.5716 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5716 2023/06/05 08:37:15 - mmengine - INFO - Epoch(train) [85][2420/2569] lr: 4.0000e-02 eta: 12:20:10 time: 0.2762 data_time: 0.0070 memory: 5828 grad_norm: 3.0920 loss: 2.8150 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8150 2023/06/05 08:37:20 - mmengine - INFO - Epoch(train) [85][2440/2569] lr: 4.0000e-02 eta: 12:20:04 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 3.1696 loss: 2.5786 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5786 2023/06/05 08:37:26 - mmengine - INFO - Epoch(train) [85][2460/2569] lr: 4.0000e-02 eta: 12:19:59 time: 0.2738 data_time: 0.0075 memory: 5828 grad_norm: 3.1198 loss: 2.3779 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3779 2023/06/05 08:37:31 - mmengine - INFO - Epoch(train) [85][2480/2569] lr: 4.0000e-02 eta: 12:19:54 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 3.1550 loss: 2.7149 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7149 2023/06/05 08:37:36 - mmengine - INFO - Epoch(train) [85][2500/2569] lr: 4.0000e-02 eta: 12:19:49 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 3.1567 loss: 2.3726 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3726 2023/06/05 08:37:42 - mmengine - INFO - Epoch(train) [85][2520/2569] lr: 4.0000e-02 eta: 12:19:43 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 3.1142 loss: 2.4453 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4453 2023/06/05 08:37:47 - mmengine - INFO - Epoch(train) [85][2540/2569] lr: 4.0000e-02 eta: 12:19:38 time: 0.2588 data_time: 0.0073 memory: 5828 grad_norm: 3.1183 loss: 2.5950 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5950 2023/06/05 08:37:52 - mmengine - INFO - Epoch(train) [85][2560/2569] lr: 4.0000e-02 eta: 12:19:32 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 3.1444 loss: 2.4714 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4714 2023/06/05 08:37:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:37:55 - mmengine - INFO - Epoch(train) [85][2569/2569] lr: 4.0000e-02 eta: 12:19:30 time: 0.2597 data_time: 0.0073 memory: 5828 grad_norm: 3.1703 loss: 2.4228 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.4228 2023/06/05 08:37:58 - mmengine - INFO - Epoch(val) [85][ 20/260] eta: 0:00:44 time: 0.1867 data_time: 0.1278 memory: 1238 2023/06/05 08:38:01 - mmengine - INFO - Epoch(val) [85][ 40/260] eta: 0:00:37 time: 0.1514 data_time: 0.0928 memory: 1238 2023/06/05 08:38:05 - mmengine - INFO - Epoch(val) [85][ 60/260] eta: 0:00:33 time: 0.1620 data_time: 0.1029 memory: 1238 2023/06/05 08:38:07 - mmengine - INFO - Epoch(val) [85][ 80/260] eta: 0:00:27 time: 0.1157 data_time: 0.0571 memory: 1238 2023/06/05 08:38:10 - mmengine - INFO - Epoch(val) [85][100/260] eta: 0:00:24 time: 0.1469 data_time: 0.0881 memory: 1238 2023/06/05 08:38:12 - mmengine - INFO - Epoch(val) [85][120/260] eta: 0:00:20 time: 0.1332 data_time: 0.0747 memory: 1238 2023/06/05 08:38:15 - mmengine - INFO - Epoch(val) [85][140/260] eta: 0:00:17 time: 0.1370 data_time: 0.0777 memory: 1238 2023/06/05 08:38:18 - mmengine - INFO - Epoch(val) [85][160/260] eta: 0:00:14 time: 0.1371 data_time: 0.0787 memory: 1238 2023/06/05 08:38:21 - mmengine - INFO - Epoch(val) [85][180/260] eta: 0:00:11 time: 0.1563 data_time: 0.0976 memory: 1238 2023/06/05 08:38:24 - mmengine - INFO - Epoch(val) [85][200/260] eta: 0:00:08 time: 0.1287 data_time: 0.0703 memory: 1238 2023/06/05 08:38:27 - mmengine - INFO - Epoch(val) [85][220/260] eta: 0:00:05 time: 0.1602 data_time: 0.1019 memory: 1238 2023/06/05 08:38:29 - mmengine - INFO - Epoch(val) [85][240/260] eta: 0:00:02 time: 0.1231 data_time: 0.0648 memory: 1238 2023/06/05 08:38:32 - mmengine - INFO - Epoch(val) [85][260/260] eta: 0:00:00 time: 0.1350 data_time: 0.0787 memory: 1238 2023/06/05 08:38:39 - mmengine - INFO - Epoch(val) [85][260/260] acc/top1: 0.5068 acc/top5: 0.7485 acc/mean1: 0.4968 data_time: 0.0853 time: 0.1437 2023/06/05 08:38:39 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_80.pth is removed 2023/06/05 08:38:41 - mmengine - INFO - The best checkpoint with 0.5068 acc/top1 at 85 epoch is saved to best_acc_top1_epoch_85.pth. 2023/06/05 08:38:47 - mmengine - INFO - Epoch(train) [86][ 20/2569] lr: 4.0000e-02 eta: 12:19:25 time: 0.3019 data_time: 0.0482 memory: 5828 grad_norm: 3.1487 loss: 2.6863 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6863 2023/06/05 08:38:52 - mmengine - INFO - Epoch(train) [86][ 40/2569] lr: 4.0000e-02 eta: 12:19:20 time: 0.2597 data_time: 0.0075 memory: 5828 grad_norm: 3.1045 loss: 2.4076 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4076 2023/06/05 08:38:57 - mmengine - INFO - Epoch(train) [86][ 60/2569] lr: 4.0000e-02 eta: 12:19:14 time: 0.2617 data_time: 0.0076 memory: 5828 grad_norm: 3.0605 loss: 2.4260 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.4260 2023/06/05 08:39:03 - mmengine - INFO - Epoch(train) [86][ 80/2569] lr: 4.0000e-02 eta: 12:19:09 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 3.0675 loss: 2.4990 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4990 2023/06/05 08:39:08 - mmengine - INFO - Epoch(train) [86][ 100/2569] lr: 4.0000e-02 eta: 12:19:04 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.0993 loss: 2.4667 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4667 2023/06/05 08:39:13 - mmengine - INFO - Epoch(train) [86][ 120/2569] lr: 4.0000e-02 eta: 12:18:59 time: 0.2721 data_time: 0.0074 memory: 5828 grad_norm: 3.1383 loss: 2.7648 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7648 2023/06/05 08:39:19 - mmengine - INFO - Epoch(train) [86][ 140/2569] lr: 4.0000e-02 eta: 12:18:53 time: 0.2630 data_time: 0.0077 memory: 5828 grad_norm: 3.0952 loss: 2.6433 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6433 2023/06/05 08:39:24 - mmengine - INFO - Epoch(train) [86][ 160/2569] lr: 4.0000e-02 eta: 12:18:48 time: 0.2649 data_time: 0.0075 memory: 5828 grad_norm: 3.0603 loss: 2.2563 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2563 2023/06/05 08:39:29 - mmengine - INFO - Epoch(train) [86][ 180/2569] lr: 4.0000e-02 eta: 12:18:42 time: 0.2601 data_time: 0.0072 memory: 5828 grad_norm: 3.1304 loss: 2.4107 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4107 2023/06/05 08:39:34 - mmengine - INFO - Epoch(train) [86][ 200/2569] lr: 4.0000e-02 eta: 12:18:37 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 3.1249 loss: 2.5555 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5555 2023/06/05 08:39:40 - mmengine - INFO - Epoch(train) [86][ 220/2569] lr: 4.0000e-02 eta: 12:18:32 time: 0.2689 data_time: 0.0071 memory: 5828 grad_norm: 3.1418 loss: 2.3302 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3302 2023/06/05 08:39:45 - mmengine - INFO - Epoch(train) [86][ 240/2569] lr: 4.0000e-02 eta: 12:18:27 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 3.1125 loss: 2.2903 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2903 2023/06/05 08:39:50 - mmengine - INFO - Epoch(train) [86][ 260/2569] lr: 4.0000e-02 eta: 12:18:21 time: 0.2644 data_time: 0.0077 memory: 5828 grad_norm: 3.1584 loss: 2.4240 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4240 2023/06/05 08:39:56 - mmengine - INFO - Epoch(train) [86][ 280/2569] lr: 4.0000e-02 eta: 12:18:16 time: 0.2659 data_time: 0.0079 memory: 5828 grad_norm: 3.1634 loss: 2.7103 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7103 2023/06/05 08:40:01 - mmengine - INFO - Epoch(train) [86][ 300/2569] lr: 4.0000e-02 eta: 12:18:11 time: 0.2680 data_time: 0.0072 memory: 5828 grad_norm: 3.1514 loss: 2.4573 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4573 2023/06/05 08:40:06 - mmengine - INFO - Epoch(train) [86][ 320/2569] lr: 4.0000e-02 eta: 12:18:05 time: 0.2669 data_time: 0.0071 memory: 5828 grad_norm: 3.1658 loss: 2.2863 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2863 2023/06/05 08:40:12 - mmengine - INFO - Epoch(train) [86][ 340/2569] lr: 4.0000e-02 eta: 12:18:00 time: 0.2589 data_time: 0.0076 memory: 5828 grad_norm: 3.1351 loss: 2.4797 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4797 2023/06/05 08:40:17 - mmengine - INFO - Epoch(train) [86][ 360/2569] lr: 4.0000e-02 eta: 12:17:55 time: 0.2677 data_time: 0.0078 memory: 5828 grad_norm: 3.1896 loss: 2.6835 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6835 2023/06/05 08:40:22 - mmengine - INFO - Epoch(train) [86][ 380/2569] lr: 4.0000e-02 eta: 12:17:49 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 3.1409 loss: 2.2677 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2677 2023/06/05 08:40:28 - mmengine - INFO - Epoch(train) [86][ 400/2569] lr: 4.0000e-02 eta: 12:17:44 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 3.1849 loss: 2.5139 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5139 2023/06/05 08:40:33 - mmengine - INFO - Epoch(train) [86][ 420/2569] lr: 4.0000e-02 eta: 12:17:39 time: 0.2716 data_time: 0.0077 memory: 5828 grad_norm: 3.1118 loss: 2.5902 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5902 2023/06/05 08:40:38 - mmengine - INFO - Epoch(train) [86][ 440/2569] lr: 4.0000e-02 eta: 12:17:34 time: 0.2702 data_time: 0.0074 memory: 5828 grad_norm: 3.1822 loss: 2.6576 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6576 2023/06/05 08:40:44 - mmengine - INFO - Epoch(train) [86][ 460/2569] lr: 4.0000e-02 eta: 12:17:28 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 3.1483 loss: 2.5164 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5164 2023/06/05 08:40:49 - mmengine - INFO - Epoch(train) [86][ 480/2569] lr: 4.0000e-02 eta: 12:17:23 time: 0.2613 data_time: 0.0075 memory: 5828 grad_norm: 3.1360 loss: 2.5749 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5749 2023/06/05 08:40:54 - mmengine - INFO - Epoch(train) [86][ 500/2569] lr: 4.0000e-02 eta: 12:17:17 time: 0.2659 data_time: 0.0076 memory: 5828 grad_norm: 3.0964 loss: 2.9203 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9203 2023/06/05 08:41:00 - mmengine - INFO - Epoch(train) [86][ 520/2569] lr: 4.0000e-02 eta: 12:17:12 time: 0.2621 data_time: 0.0077 memory: 5828 grad_norm: 3.1427 loss: 2.4575 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4575 2023/06/05 08:41:05 - mmengine - INFO - Epoch(train) [86][ 540/2569] lr: 4.0000e-02 eta: 12:17:07 time: 0.2586 data_time: 0.0075 memory: 5828 grad_norm: 3.1553 loss: 2.2114 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2114 2023/06/05 08:41:10 - mmengine - INFO - Epoch(train) [86][ 560/2569] lr: 4.0000e-02 eta: 12:17:01 time: 0.2593 data_time: 0.0074 memory: 5828 grad_norm: 3.0917 loss: 2.5078 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5078 2023/06/05 08:41:15 - mmengine - INFO - Epoch(train) [86][ 580/2569] lr: 4.0000e-02 eta: 12:16:56 time: 0.2678 data_time: 0.0072 memory: 5828 grad_norm: 3.1555 loss: 2.7381 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7381 2023/06/05 08:41:20 - mmengine - INFO - Epoch(train) [86][ 600/2569] lr: 4.0000e-02 eta: 12:16:51 time: 0.2571 data_time: 0.0077 memory: 5828 grad_norm: 3.1213 loss: 2.6004 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6004 2023/06/05 08:41:26 - mmengine - INFO - Epoch(train) [86][ 620/2569] lr: 4.0000e-02 eta: 12:16:45 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 3.1795 loss: 2.7604 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7604 2023/06/05 08:41:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:41:31 - mmengine - INFO - Epoch(train) [86][ 640/2569] lr: 4.0000e-02 eta: 12:16:40 time: 0.2637 data_time: 0.0084 memory: 5828 grad_norm: 3.1040 loss: 2.4562 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4562 2023/06/05 08:41:36 - mmengine - INFO - Epoch(train) [86][ 660/2569] lr: 4.0000e-02 eta: 12:16:35 time: 0.2696 data_time: 0.0082 memory: 5828 grad_norm: 3.1678 loss: 2.3051 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3051 2023/06/05 08:41:42 - mmengine - INFO - Epoch(train) [86][ 680/2569] lr: 4.0000e-02 eta: 12:16:29 time: 0.2589 data_time: 0.0075 memory: 5828 grad_norm: 3.1499 loss: 2.3362 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3362 2023/06/05 08:41:47 - mmengine - INFO - Epoch(train) [86][ 700/2569] lr: 4.0000e-02 eta: 12:16:24 time: 0.2701 data_time: 0.0076 memory: 5828 grad_norm: 3.2271 loss: 2.6384 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6384 2023/06/05 08:41:52 - mmengine - INFO - Epoch(train) [86][ 720/2569] lr: 4.0000e-02 eta: 12:16:19 time: 0.2628 data_time: 0.0078 memory: 5828 grad_norm: 3.0399 loss: 2.4223 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4223 2023/06/05 08:41:58 - mmengine - INFO - Epoch(train) [86][ 740/2569] lr: 4.0000e-02 eta: 12:16:13 time: 0.2747 data_time: 0.0071 memory: 5828 grad_norm: 3.1409 loss: 2.6739 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6739 2023/06/05 08:42:03 - mmengine - INFO - Epoch(train) [86][ 760/2569] lr: 4.0000e-02 eta: 12:16:08 time: 0.2622 data_time: 0.0074 memory: 5828 grad_norm: 3.1425 loss: 2.7057 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7057 2023/06/05 08:42:08 - mmengine - INFO - Epoch(train) [86][ 780/2569] lr: 4.0000e-02 eta: 12:16:03 time: 0.2634 data_time: 0.0070 memory: 5828 grad_norm: 3.0712 loss: 2.4571 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4571 2023/06/05 08:42:14 - mmengine - INFO - Epoch(train) [86][ 800/2569] lr: 4.0000e-02 eta: 12:15:57 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 3.1501 loss: 2.2071 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2071 2023/06/05 08:42:19 - mmengine - INFO - Epoch(train) [86][ 820/2569] lr: 4.0000e-02 eta: 12:15:52 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 3.1260 loss: 2.4970 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4970 2023/06/05 08:42:24 - mmengine - INFO - Epoch(train) [86][ 840/2569] lr: 4.0000e-02 eta: 12:15:47 time: 0.2599 data_time: 0.0080 memory: 5828 grad_norm: 3.1315 loss: 2.8073 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8073 2023/06/05 08:42:30 - mmengine - INFO - Epoch(train) [86][ 860/2569] lr: 4.0000e-02 eta: 12:15:41 time: 0.2702 data_time: 0.0072 memory: 5828 grad_norm: 3.1225 loss: 2.5400 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5400 2023/06/05 08:42:35 - mmengine - INFO - Epoch(train) [86][ 880/2569] lr: 4.0000e-02 eta: 12:15:36 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 3.0880 loss: 2.5132 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.5132 2023/06/05 08:42:40 - mmengine - INFO - Epoch(train) [86][ 900/2569] lr: 4.0000e-02 eta: 12:15:31 time: 0.2590 data_time: 0.0078 memory: 5828 grad_norm: 3.1775 loss: 2.7556 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7556 2023/06/05 08:42:45 - mmengine - INFO - Epoch(train) [86][ 920/2569] lr: 4.0000e-02 eta: 12:15:25 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 3.1993 loss: 2.5356 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5356 2023/06/05 08:42:51 - mmengine - INFO - Epoch(train) [86][ 940/2569] lr: 4.0000e-02 eta: 12:15:20 time: 0.2593 data_time: 0.0073 memory: 5828 grad_norm: 3.0723 loss: 2.5884 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5884 2023/06/05 08:42:56 - mmengine - INFO - Epoch(train) [86][ 960/2569] lr: 4.0000e-02 eta: 12:15:15 time: 0.2685 data_time: 0.0078 memory: 5828 grad_norm: 3.1618 loss: 2.7226 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7226 2023/06/05 08:43:01 - mmengine - INFO - Epoch(train) [86][ 980/2569] lr: 4.0000e-02 eta: 12:15:09 time: 0.2588 data_time: 0.0077 memory: 5828 grad_norm: 3.1493 loss: 2.5629 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5629 2023/06/05 08:43:06 - mmengine - INFO - Epoch(train) [86][1000/2569] lr: 4.0000e-02 eta: 12:15:04 time: 0.2658 data_time: 0.0075 memory: 5828 grad_norm: 3.1627 loss: 2.1140 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1140 2023/06/05 08:43:12 - mmengine - INFO - Epoch(train) [86][1020/2569] lr: 4.0000e-02 eta: 12:14:59 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 3.1590 loss: 2.5186 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5186 2023/06/05 08:43:17 - mmengine - INFO - Epoch(train) [86][1040/2569] lr: 4.0000e-02 eta: 12:14:53 time: 0.2696 data_time: 0.0074 memory: 5828 grad_norm: 3.1152 loss: 2.5370 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5370 2023/06/05 08:43:22 - mmengine - INFO - Epoch(train) [86][1060/2569] lr: 4.0000e-02 eta: 12:14:48 time: 0.2596 data_time: 0.0075 memory: 5828 grad_norm: 3.0591 loss: 2.5461 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5461 2023/06/05 08:43:28 - mmengine - INFO - Epoch(train) [86][1080/2569] lr: 4.0000e-02 eta: 12:14:43 time: 0.2604 data_time: 0.0079 memory: 5828 grad_norm: 3.0535 loss: 2.6606 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6606 2023/06/05 08:43:33 - mmengine - INFO - Epoch(train) [86][1100/2569] lr: 4.0000e-02 eta: 12:14:37 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 3.1226 loss: 2.5106 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5106 2023/06/05 08:43:38 - mmengine - INFO - Epoch(train) [86][1120/2569] lr: 4.0000e-02 eta: 12:14:32 time: 0.2582 data_time: 0.0078 memory: 5828 grad_norm: 3.1549 loss: 2.4632 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4632 2023/06/05 08:43:43 - mmengine - INFO - Epoch(train) [86][1140/2569] lr: 4.0000e-02 eta: 12:14:27 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.0802 loss: 2.1055 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.1055 2023/06/05 08:43:49 - mmengine - INFO - Epoch(train) [86][1160/2569] lr: 4.0000e-02 eta: 12:14:21 time: 0.2684 data_time: 0.0074 memory: 5828 grad_norm: 3.0923 loss: 2.7006 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7006 2023/06/05 08:43:54 - mmengine - INFO - Epoch(train) [86][1180/2569] lr: 4.0000e-02 eta: 12:14:16 time: 0.2657 data_time: 0.0073 memory: 5828 grad_norm: 3.1863 loss: 2.4212 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4212 2023/06/05 08:43:59 - mmengine - INFO - Epoch(train) [86][1200/2569] lr: 4.0000e-02 eta: 12:14:11 time: 0.2603 data_time: 0.0076 memory: 5828 grad_norm: 3.0414 loss: 2.8133 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8133 2023/06/05 08:44:05 - mmengine - INFO - Epoch(train) [86][1220/2569] lr: 4.0000e-02 eta: 12:14:05 time: 0.2698 data_time: 0.0076 memory: 5828 grad_norm: 3.1335 loss: 2.3640 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3640 2023/06/05 08:44:10 - mmengine - INFO - Epoch(train) [86][1240/2569] lr: 4.0000e-02 eta: 12:14:00 time: 0.2582 data_time: 0.0074 memory: 5828 grad_norm: 3.0982 loss: 2.5293 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5293 2023/06/05 08:44:15 - mmengine - INFO - Epoch(train) [86][1260/2569] lr: 4.0000e-02 eta: 12:13:54 time: 0.2611 data_time: 0.0090 memory: 5828 grad_norm: 3.1067 loss: 2.4746 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4746 2023/06/05 08:44:20 - mmengine - INFO - Epoch(train) [86][1280/2569] lr: 4.0000e-02 eta: 12:13:49 time: 0.2602 data_time: 0.0076 memory: 5828 grad_norm: 3.1002 loss: 2.5898 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5898 2023/06/05 08:44:26 - mmengine - INFO - Epoch(train) [86][1300/2569] lr: 4.0000e-02 eta: 12:13:44 time: 0.2587 data_time: 0.0074 memory: 5828 grad_norm: 3.1799 loss: 2.9111 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.9111 2023/06/05 08:44:31 - mmengine - INFO - Epoch(train) [86][1320/2569] lr: 4.0000e-02 eta: 12:13:38 time: 0.2592 data_time: 0.0075 memory: 5828 grad_norm: 3.1456 loss: 2.5122 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5122 2023/06/05 08:44:36 - mmengine - INFO - Epoch(train) [86][1340/2569] lr: 4.0000e-02 eta: 12:13:33 time: 0.2594 data_time: 0.0079 memory: 5828 grad_norm: 3.1095 loss: 2.2628 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2628 2023/06/05 08:44:41 - mmengine - INFO - Epoch(train) [86][1360/2569] lr: 4.0000e-02 eta: 12:13:28 time: 0.2769 data_time: 0.0074 memory: 5828 grad_norm: 3.1641 loss: 2.6033 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6033 2023/06/05 08:44:47 - mmengine - INFO - Epoch(train) [86][1380/2569] lr: 4.0000e-02 eta: 12:13:22 time: 0.2588 data_time: 0.0075 memory: 5828 grad_norm: 3.1563 loss: 2.2449 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2449 2023/06/05 08:44:52 - mmengine - INFO - Epoch(train) [86][1400/2569] lr: 4.0000e-02 eta: 12:13:17 time: 0.2630 data_time: 0.0081 memory: 5828 grad_norm: 3.0677 loss: 2.5952 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5952 2023/06/05 08:44:57 - mmengine - INFO - Epoch(train) [86][1420/2569] lr: 4.0000e-02 eta: 12:13:12 time: 0.2620 data_time: 0.0074 memory: 5828 grad_norm: 3.0757 loss: 2.6299 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6299 2023/06/05 08:45:02 - mmengine - INFO - Epoch(train) [86][1440/2569] lr: 4.0000e-02 eta: 12:13:06 time: 0.2579 data_time: 0.0076 memory: 5828 grad_norm: 3.2843 loss: 2.5528 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5528 2023/06/05 08:45:07 - mmengine - INFO - Epoch(train) [86][1460/2569] lr: 4.0000e-02 eta: 12:13:01 time: 0.2564 data_time: 0.0072 memory: 5828 grad_norm: 3.1093 loss: 2.4494 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4494 2023/06/05 08:45:13 - mmengine - INFO - Epoch(train) [86][1480/2569] lr: 4.0000e-02 eta: 12:12:55 time: 0.2701 data_time: 0.0075 memory: 5828 grad_norm: 3.1910 loss: 2.6427 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6427 2023/06/05 08:45:18 - mmengine - INFO - Epoch(train) [86][1500/2569] lr: 4.0000e-02 eta: 12:12:50 time: 0.2575 data_time: 0.0076 memory: 5828 grad_norm: 3.1052 loss: 2.2653 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2653 2023/06/05 08:45:23 - mmengine - INFO - Epoch(train) [86][1520/2569] lr: 4.0000e-02 eta: 12:12:45 time: 0.2591 data_time: 0.0076 memory: 5828 grad_norm: 3.1265 loss: 2.5003 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5003 2023/06/05 08:45:29 - mmengine - INFO - Epoch(train) [86][1540/2569] lr: 4.0000e-02 eta: 12:12:39 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 3.1819 loss: 2.4652 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4652 2023/06/05 08:45:34 - mmengine - INFO - Epoch(train) [86][1560/2569] lr: 4.0000e-02 eta: 12:12:34 time: 0.2619 data_time: 0.0074 memory: 5828 grad_norm: 3.1352 loss: 2.3889 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3889 2023/06/05 08:45:39 - mmengine - INFO - Epoch(train) [86][1580/2569] lr: 4.0000e-02 eta: 12:12:28 time: 0.2599 data_time: 0.0078 memory: 5828 grad_norm: 3.1362 loss: 2.3476 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3476 2023/06/05 08:45:44 - mmengine - INFO - Epoch(train) [86][1600/2569] lr: 4.0000e-02 eta: 12:12:23 time: 0.2678 data_time: 0.0077 memory: 5828 grad_norm: 3.2080 loss: 2.7392 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7392 2023/06/05 08:45:50 - mmengine - INFO - Epoch(train) [86][1620/2569] lr: 4.0000e-02 eta: 12:12:18 time: 0.2591 data_time: 0.0073 memory: 5828 grad_norm: 3.1150 loss: 2.5574 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 2.5574 2023/06/05 08:45:54 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:45:55 - mmengine - INFO - Epoch(train) [86][1640/2569] lr: 4.0000e-02 eta: 12:12:12 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 3.0875 loss: 2.1448 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.1448 2023/06/05 08:46:00 - mmengine - INFO - Epoch(train) [86][1660/2569] lr: 4.0000e-02 eta: 12:12:07 time: 0.2584 data_time: 0.0074 memory: 5828 grad_norm: 3.1672 loss: 2.5522 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5522 2023/06/05 08:46:05 - mmengine - INFO - Epoch(train) [86][1680/2569] lr: 4.0000e-02 eta: 12:12:02 time: 0.2697 data_time: 0.0070 memory: 5828 grad_norm: 3.0908 loss: 2.2366 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2366 2023/06/05 08:46:11 - mmengine - INFO - Epoch(train) [86][1700/2569] lr: 4.0000e-02 eta: 12:11:56 time: 0.2655 data_time: 0.0071 memory: 5828 grad_norm: 3.1929 loss: 2.4597 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4597 2023/06/05 08:46:16 - mmengine - INFO - Epoch(train) [86][1720/2569] lr: 4.0000e-02 eta: 12:11:51 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.0786 loss: 2.5873 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5873 2023/06/05 08:46:21 - mmengine - INFO - Epoch(train) [86][1740/2569] lr: 4.0000e-02 eta: 12:11:46 time: 0.2699 data_time: 0.0075 memory: 5828 grad_norm: 3.1463 loss: 2.5355 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5355 2023/06/05 08:46:27 - mmengine - INFO - Epoch(train) [86][1760/2569] lr: 4.0000e-02 eta: 12:11:41 time: 0.2640 data_time: 0.0075 memory: 5828 grad_norm: 3.1674 loss: 2.6056 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6056 2023/06/05 08:46:32 - mmengine - INFO - Epoch(train) [86][1780/2569] lr: 4.0000e-02 eta: 12:11:35 time: 0.2643 data_time: 0.0076 memory: 5828 grad_norm: 3.1096 loss: 2.6763 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6763 2023/06/05 08:46:37 - mmengine - INFO - Epoch(train) [86][1800/2569] lr: 4.0000e-02 eta: 12:11:30 time: 0.2614 data_time: 0.0079 memory: 5828 grad_norm: 3.1402 loss: 2.0809 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0809 2023/06/05 08:46:43 - mmengine - INFO - Epoch(train) [86][1820/2569] lr: 4.0000e-02 eta: 12:11:25 time: 0.2692 data_time: 0.0076 memory: 5828 grad_norm: 3.1659 loss: 2.5365 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5365 2023/06/05 08:46:48 - mmengine - INFO - Epoch(train) [86][1840/2569] lr: 4.0000e-02 eta: 12:11:19 time: 0.2627 data_time: 0.0083 memory: 5828 grad_norm: 3.1144 loss: 2.5713 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5713 2023/06/05 08:46:53 - mmengine - INFO - Epoch(train) [86][1860/2569] lr: 4.0000e-02 eta: 12:11:14 time: 0.2591 data_time: 0.0079 memory: 5828 grad_norm: 3.1589 loss: 2.5619 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5619 2023/06/05 08:46:58 - mmengine - INFO - Epoch(train) [86][1880/2569] lr: 4.0000e-02 eta: 12:11:08 time: 0.2656 data_time: 0.0086 memory: 5828 grad_norm: 3.0723 loss: 2.6351 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6351 2023/06/05 08:47:04 - mmengine - INFO - Epoch(train) [86][1900/2569] lr: 4.0000e-02 eta: 12:11:03 time: 0.2655 data_time: 0.0074 memory: 5828 grad_norm: 3.0949 loss: 2.6255 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6255 2023/06/05 08:47:09 - mmengine - INFO - Epoch(train) [86][1920/2569] lr: 4.0000e-02 eta: 12:10:58 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 3.0854 loss: 2.6054 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6054 2023/06/05 08:47:14 - mmengine - INFO - Epoch(train) [86][1940/2569] lr: 4.0000e-02 eta: 12:10:53 time: 0.2705 data_time: 0.0077 memory: 5828 grad_norm: 3.1847 loss: 2.1613 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1613 2023/06/05 08:47:20 - mmengine - INFO - Epoch(train) [86][1960/2569] lr: 4.0000e-02 eta: 12:10:47 time: 0.2659 data_time: 0.0079 memory: 5828 grad_norm: 3.1450 loss: 2.4559 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4559 2023/06/05 08:47:25 - mmengine - INFO - Epoch(train) [86][1980/2569] lr: 4.0000e-02 eta: 12:10:42 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 3.1713 loss: 2.4782 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4782 2023/06/05 08:47:30 - mmengine - INFO - Epoch(train) [86][2000/2569] lr: 4.0000e-02 eta: 12:10:37 time: 0.2637 data_time: 0.0070 memory: 5828 grad_norm: 3.1268 loss: 2.3701 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3701 2023/06/05 08:47:36 - mmengine - INFO - Epoch(train) [86][2020/2569] lr: 4.0000e-02 eta: 12:10:31 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 3.0832 loss: 2.5281 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5281 2023/06/05 08:47:41 - mmengine - INFO - Epoch(train) [86][2040/2569] lr: 4.0000e-02 eta: 12:10:26 time: 0.2600 data_time: 0.0071 memory: 5828 grad_norm: 3.1187 loss: 2.4218 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4218 2023/06/05 08:47:46 - mmengine - INFO - Epoch(train) [86][2060/2569] lr: 4.0000e-02 eta: 12:10:21 time: 0.2615 data_time: 0.0071 memory: 5828 grad_norm: 3.1510 loss: 2.5559 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5559 2023/06/05 08:47:51 - mmengine - INFO - Epoch(train) [86][2080/2569] lr: 4.0000e-02 eta: 12:10:15 time: 0.2600 data_time: 0.0073 memory: 5828 grad_norm: 3.1633 loss: 2.4863 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4863 2023/06/05 08:47:57 - mmengine - INFO - Epoch(train) [86][2100/2569] lr: 4.0000e-02 eta: 12:10:10 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 3.1253 loss: 2.4843 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4843 2023/06/05 08:48:02 - mmengine - INFO - Epoch(train) [86][2120/2569] lr: 4.0000e-02 eta: 12:10:04 time: 0.2660 data_time: 0.0071 memory: 5828 grad_norm: 3.1062 loss: 2.5140 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5140 2023/06/05 08:48:07 - mmengine - INFO - Epoch(train) [86][2140/2569] lr: 4.0000e-02 eta: 12:09:59 time: 0.2651 data_time: 0.0072 memory: 5828 grad_norm: 3.1341 loss: 2.4535 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4535 2023/06/05 08:48:13 - mmengine - INFO - Epoch(train) [86][2160/2569] lr: 4.0000e-02 eta: 12:09:54 time: 0.2628 data_time: 0.0073 memory: 5828 grad_norm: 3.1487 loss: 2.7134 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7134 2023/06/05 08:48:18 - mmengine - INFO - Epoch(train) [86][2180/2569] lr: 4.0000e-02 eta: 12:09:48 time: 0.2662 data_time: 0.0075 memory: 5828 grad_norm: 3.1466 loss: 2.3757 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3757 2023/06/05 08:48:23 - mmengine - INFO - Epoch(train) [86][2200/2569] lr: 4.0000e-02 eta: 12:09:43 time: 0.2766 data_time: 0.0073 memory: 5828 grad_norm: 3.1992 loss: 2.4107 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4107 2023/06/05 08:48:29 - mmengine - INFO - Epoch(train) [86][2220/2569] lr: 4.0000e-02 eta: 12:09:38 time: 0.2691 data_time: 0.0075 memory: 5828 grad_norm: 3.1278 loss: 2.1592 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1592 2023/06/05 08:48:34 - mmengine - INFO - Epoch(train) [86][2240/2569] lr: 4.0000e-02 eta: 12:09:33 time: 0.2667 data_time: 0.0079 memory: 5828 grad_norm: 3.1564 loss: 2.5571 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5571 2023/06/05 08:48:40 - mmengine - INFO - Epoch(train) [86][2260/2569] lr: 4.0000e-02 eta: 12:09:28 time: 0.2732 data_time: 0.0072 memory: 5828 grad_norm: 3.1458 loss: 2.5678 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5678 2023/06/05 08:48:45 - mmengine - INFO - Epoch(train) [86][2280/2569] lr: 4.0000e-02 eta: 12:09:22 time: 0.2636 data_time: 0.0098 memory: 5828 grad_norm: 3.1243 loss: 2.4424 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4424 2023/06/05 08:48:50 - mmengine - INFO - Epoch(train) [86][2300/2569] lr: 4.0000e-02 eta: 12:09:17 time: 0.2752 data_time: 0.0076 memory: 5828 grad_norm: 3.1390 loss: 2.3083 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3083 2023/06/05 08:48:56 - mmengine - INFO - Epoch(train) [86][2320/2569] lr: 4.0000e-02 eta: 12:09:12 time: 0.2698 data_time: 0.0078 memory: 5828 grad_norm: 3.0976 loss: 2.6898 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6898 2023/06/05 08:49:01 - mmengine - INFO - Epoch(train) [86][2340/2569] lr: 4.0000e-02 eta: 12:09:07 time: 0.2794 data_time: 0.0075 memory: 5828 grad_norm: 3.1996 loss: 2.4622 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4622 2023/06/05 08:49:07 - mmengine - INFO - Epoch(train) [86][2360/2569] lr: 4.0000e-02 eta: 12:09:01 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 3.1494 loss: 2.4281 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4281 2023/06/05 08:49:12 - mmengine - INFO - Epoch(train) [86][2380/2569] lr: 4.0000e-02 eta: 12:08:56 time: 0.2591 data_time: 0.0071 memory: 5828 grad_norm: 3.1392 loss: 2.6480 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6480 2023/06/05 08:49:17 - mmengine - INFO - Epoch(train) [86][2400/2569] lr: 4.0000e-02 eta: 12:08:51 time: 0.2707 data_time: 0.0073 memory: 5828 grad_norm: 3.1150 loss: 2.3599 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3599 2023/06/05 08:49:23 - mmengine - INFO - Epoch(train) [86][2420/2569] lr: 4.0000e-02 eta: 12:08:45 time: 0.2597 data_time: 0.0072 memory: 5828 grad_norm: 3.1266 loss: 2.5881 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5881 2023/06/05 08:49:28 - mmengine - INFO - Epoch(train) [86][2440/2569] lr: 4.0000e-02 eta: 12:08:40 time: 0.2587 data_time: 0.0076 memory: 5828 grad_norm: 3.1474 loss: 2.2087 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2087 2023/06/05 08:49:33 - mmengine - INFO - Epoch(train) [86][2460/2569] lr: 4.0000e-02 eta: 12:08:35 time: 0.2591 data_time: 0.0073 memory: 5828 grad_norm: 3.1846 loss: 2.8640 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.8640 2023/06/05 08:49:39 - mmengine - INFO - Epoch(train) [86][2480/2569] lr: 4.0000e-02 eta: 12:08:29 time: 0.2797 data_time: 0.0071 memory: 5828 grad_norm: 3.1511 loss: 2.9189 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9189 2023/06/05 08:49:44 - mmengine - INFO - Epoch(train) [86][2500/2569] lr: 4.0000e-02 eta: 12:08:24 time: 0.2618 data_time: 0.0081 memory: 5828 grad_norm: 3.1577 loss: 2.1794 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1794 2023/06/05 08:49:50 - mmengine - INFO - Epoch(train) [86][2520/2569] lr: 4.0000e-02 eta: 12:08:19 time: 0.2863 data_time: 0.0074 memory: 5828 grad_norm: 3.0573 loss: 2.5593 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5593 2023/06/05 08:49:55 - mmengine - INFO - Epoch(train) [86][2540/2569] lr: 4.0000e-02 eta: 12:08:14 time: 0.2593 data_time: 0.0078 memory: 5828 grad_norm: 3.1755 loss: 2.3985 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3985 2023/06/05 08:50:00 - mmengine - INFO - Epoch(train) [86][2560/2569] lr: 4.0000e-02 eta: 12:08:08 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 3.1140 loss: 2.8508 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8508 2023/06/05 08:50:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:50:02 - mmengine - INFO - Epoch(train) [86][2569/2569] lr: 4.0000e-02 eta: 12:08:06 time: 0.2597 data_time: 0.0072 memory: 5828 grad_norm: 3.0682 loss: 2.7522 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.7522 2023/06/05 08:50:09 - mmengine - INFO - Epoch(train) [87][ 20/2569] lr: 4.0000e-02 eta: 12:08:02 time: 0.3320 data_time: 0.0588 memory: 5828 grad_norm: 3.0995 loss: 2.4822 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4822 2023/06/05 08:50:14 - mmengine - INFO - Epoch(train) [87][ 40/2569] lr: 4.0000e-02 eta: 12:07:56 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 3.1227 loss: 2.8527 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8527 2023/06/05 08:50:20 - mmengine - INFO - Epoch(train) [87][ 60/2569] lr: 4.0000e-02 eta: 12:07:51 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 3.0935 loss: 2.2547 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2547 2023/06/05 08:50:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:50:25 - mmengine - INFO - Epoch(train) [87][ 80/2569] lr: 4.0000e-02 eta: 12:07:46 time: 0.2720 data_time: 0.0076 memory: 5828 grad_norm: 3.1308 loss: 2.5672 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5672 2023/06/05 08:50:31 - mmengine - INFO - Epoch(train) [87][ 100/2569] lr: 4.0000e-02 eta: 12:07:41 time: 0.2788 data_time: 0.0071 memory: 5828 grad_norm: 3.1514 loss: 2.7796 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7796 2023/06/05 08:50:36 - mmengine - INFO - Epoch(train) [87][ 120/2569] lr: 4.0000e-02 eta: 12:07:35 time: 0.2580 data_time: 0.0086 memory: 5828 grad_norm: 3.1484 loss: 2.5004 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5004 2023/06/05 08:50:41 - mmengine - INFO - Epoch(train) [87][ 140/2569] lr: 4.0000e-02 eta: 12:07:30 time: 0.2606 data_time: 0.0076 memory: 5828 grad_norm: 3.1101 loss: 2.6544 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6544 2023/06/05 08:50:46 - mmengine - INFO - Epoch(train) [87][ 160/2569] lr: 4.0000e-02 eta: 12:07:24 time: 0.2627 data_time: 0.0077 memory: 5828 grad_norm: 3.1558 loss: 2.3727 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3727 2023/06/05 08:50:52 - mmengine - INFO - Epoch(train) [87][ 180/2569] lr: 4.0000e-02 eta: 12:07:19 time: 0.2638 data_time: 0.0075 memory: 5828 grad_norm: 3.1510 loss: 2.3043 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3043 2023/06/05 08:50:57 - mmengine - INFO - Epoch(train) [87][ 200/2569] lr: 4.0000e-02 eta: 12:07:14 time: 0.2605 data_time: 0.0087 memory: 5828 grad_norm: 3.1107 loss: 2.3449 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3449 2023/06/05 08:51:02 - mmengine - INFO - Epoch(train) [87][ 220/2569] lr: 4.0000e-02 eta: 12:07:08 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.0949 loss: 2.3784 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3784 2023/06/05 08:51:07 - mmengine - INFO - Epoch(train) [87][ 240/2569] lr: 4.0000e-02 eta: 12:07:03 time: 0.2629 data_time: 0.0081 memory: 5828 grad_norm: 3.2408 loss: 2.0529 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0529 2023/06/05 08:51:13 - mmengine - INFO - Epoch(train) [87][ 260/2569] lr: 4.0000e-02 eta: 12:06:58 time: 0.2628 data_time: 0.0077 memory: 5828 grad_norm: 3.1082 loss: 2.6645 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6645 2023/06/05 08:51:18 - mmengine - INFO - Epoch(train) [87][ 280/2569] lr: 4.0000e-02 eta: 12:06:52 time: 0.2593 data_time: 0.0078 memory: 5828 grad_norm: 3.1842 loss: 2.3070 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3070 2023/06/05 08:51:23 - mmengine - INFO - Epoch(train) [87][ 300/2569] lr: 4.0000e-02 eta: 12:06:47 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 3.2251 loss: 2.5144 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5144 2023/06/05 08:51:28 - mmengine - INFO - Epoch(train) [87][ 320/2569] lr: 4.0000e-02 eta: 12:06:41 time: 0.2589 data_time: 0.0075 memory: 5828 grad_norm: 3.1460 loss: 2.4680 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4680 2023/06/05 08:51:34 - mmengine - INFO - Epoch(train) [87][ 340/2569] lr: 4.0000e-02 eta: 12:06:36 time: 0.2689 data_time: 0.0072 memory: 5828 grad_norm: 3.1203 loss: 2.6282 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6282 2023/06/05 08:51:39 - mmengine - INFO - Epoch(train) [87][ 360/2569] lr: 4.0000e-02 eta: 12:06:31 time: 0.2671 data_time: 0.0075 memory: 5828 grad_norm: 3.1207 loss: 2.6898 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6898 2023/06/05 08:51:44 - mmengine - INFO - Epoch(train) [87][ 380/2569] lr: 4.0000e-02 eta: 12:06:26 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 3.1509 loss: 2.0811 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0811 2023/06/05 08:51:50 - mmengine - INFO - Epoch(train) [87][ 400/2569] lr: 4.0000e-02 eta: 12:06:20 time: 0.2621 data_time: 0.0077 memory: 5828 grad_norm: 3.1047 loss: 2.4710 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4710 2023/06/05 08:51:55 - mmengine - INFO - Epoch(train) [87][ 420/2569] lr: 4.0000e-02 eta: 12:06:15 time: 0.2616 data_time: 0.0070 memory: 5828 grad_norm: 3.2217 loss: 2.5368 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5368 2023/06/05 08:52:00 - mmengine - INFO - Epoch(train) [87][ 440/2569] lr: 4.0000e-02 eta: 12:06:10 time: 0.2673 data_time: 0.0074 memory: 5828 grad_norm: 3.1367 loss: 2.6502 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6502 2023/06/05 08:52:06 - mmengine - INFO - Epoch(train) [87][ 460/2569] lr: 4.0000e-02 eta: 12:06:04 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 3.1361 loss: 2.4386 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4386 2023/06/05 08:52:11 - mmengine - INFO - Epoch(train) [87][ 480/2569] lr: 4.0000e-02 eta: 12:05:59 time: 0.2739 data_time: 0.0073 memory: 5828 grad_norm: 3.0774 loss: 2.6274 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6274 2023/06/05 08:52:16 - mmengine - INFO - Epoch(train) [87][ 500/2569] lr: 4.0000e-02 eta: 12:05:54 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 3.2042 loss: 2.7296 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7296 2023/06/05 08:52:22 - mmengine - INFO - Epoch(train) [87][ 520/2569] lr: 4.0000e-02 eta: 12:05:48 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 3.1808 loss: 2.4590 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4590 2023/06/05 08:52:27 - mmengine - INFO - Epoch(train) [87][ 540/2569] lr: 4.0000e-02 eta: 12:05:43 time: 0.2605 data_time: 0.0087 memory: 5828 grad_norm: 3.1587 loss: 2.3879 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3879 2023/06/05 08:52:32 - mmengine - INFO - Epoch(train) [87][ 560/2569] lr: 4.0000e-02 eta: 12:05:38 time: 0.2681 data_time: 0.0090 memory: 5828 grad_norm: 3.1467 loss: 2.3288 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3288 2023/06/05 08:52:38 - mmengine - INFO - Epoch(train) [87][ 580/2569] lr: 4.0000e-02 eta: 12:05:32 time: 0.2597 data_time: 0.0073 memory: 5828 grad_norm: 3.1177 loss: 2.6128 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6128 2023/06/05 08:52:43 - mmengine - INFO - Epoch(train) [87][ 600/2569] lr: 4.0000e-02 eta: 12:05:27 time: 0.2672 data_time: 0.0067 memory: 5828 grad_norm: 3.1832 loss: 2.4881 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4881 2023/06/05 08:52:48 - mmengine - INFO - Epoch(train) [87][ 620/2569] lr: 4.0000e-02 eta: 12:05:22 time: 0.2649 data_time: 0.0071 memory: 5828 grad_norm: 3.0951 loss: 2.4930 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4930 2023/06/05 08:52:54 - mmengine - INFO - Epoch(train) [87][ 640/2569] lr: 4.0000e-02 eta: 12:05:17 time: 0.2735 data_time: 0.0070 memory: 5828 grad_norm: 3.1013 loss: 2.6244 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6244 2023/06/05 08:52:59 - mmengine - INFO - Epoch(train) [87][ 660/2569] lr: 4.0000e-02 eta: 12:05:11 time: 0.2681 data_time: 0.0069 memory: 5828 grad_norm: 3.1291 loss: 2.3423 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3423 2023/06/05 08:53:05 - mmengine - INFO - Epoch(train) [87][ 680/2569] lr: 4.0000e-02 eta: 12:05:06 time: 0.2712 data_time: 0.0070 memory: 5828 grad_norm: 3.0970 loss: 2.1188 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.1188 2023/06/05 08:53:10 - mmengine - INFO - Epoch(train) [87][ 700/2569] lr: 4.0000e-02 eta: 12:05:01 time: 0.2642 data_time: 0.0076 memory: 5828 grad_norm: 3.1054 loss: 2.2174 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2174 2023/06/05 08:53:15 - mmengine - INFO - Epoch(train) [87][ 720/2569] lr: 4.0000e-02 eta: 12:04:55 time: 0.2619 data_time: 0.0077 memory: 5828 grad_norm: 3.1446 loss: 2.3836 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3836 2023/06/05 08:53:20 - mmengine - INFO - Epoch(train) [87][ 740/2569] lr: 4.0000e-02 eta: 12:04:50 time: 0.2619 data_time: 0.0071 memory: 5828 grad_norm: 3.1974 loss: 2.2924 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2924 2023/06/05 08:53:26 - mmengine - INFO - Epoch(train) [87][ 760/2569] lr: 4.0000e-02 eta: 12:04:45 time: 0.2603 data_time: 0.0074 memory: 5828 grad_norm: 3.1758 loss: 2.3246 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3246 2023/06/05 08:53:31 - mmengine - INFO - Epoch(train) [87][ 780/2569] lr: 4.0000e-02 eta: 12:04:39 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 3.1410 loss: 2.6681 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6681 2023/06/05 08:53:36 - mmengine - INFO - Epoch(train) [87][ 800/2569] lr: 4.0000e-02 eta: 12:04:34 time: 0.2640 data_time: 0.0078 memory: 5828 grad_norm: 3.1392 loss: 2.5122 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5122 2023/06/05 08:53:43 - mmengine - INFO - Epoch(train) [87][ 820/2569] lr: 4.0000e-02 eta: 12:04:29 time: 0.3228 data_time: 0.0071 memory: 5828 grad_norm: 3.1150 loss: 2.5446 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5446 2023/06/05 08:53:49 - mmengine - INFO - Epoch(train) [87][ 840/2569] lr: 4.0000e-02 eta: 12:04:25 time: 0.2950 data_time: 0.0074 memory: 5828 grad_norm: 3.1774 loss: 2.5193 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5193 2023/06/05 08:53:54 - mmengine - INFO - Epoch(train) [87][ 860/2569] lr: 4.0000e-02 eta: 12:04:19 time: 0.2626 data_time: 0.0070 memory: 5828 grad_norm: 3.1785 loss: 2.6274 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6274 2023/06/05 08:53:59 - mmengine - INFO - Epoch(train) [87][ 880/2569] lr: 4.0000e-02 eta: 12:04:14 time: 0.2768 data_time: 0.0072 memory: 5828 grad_norm: 3.1358 loss: 2.3235 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3235 2023/06/05 08:54:05 - mmengine - INFO - Epoch(train) [87][ 900/2569] lr: 4.0000e-02 eta: 12:04:09 time: 0.2590 data_time: 0.0072 memory: 5828 grad_norm: 3.1174 loss: 2.5793 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 2.5793 2023/06/05 08:54:10 - mmengine - INFO - Epoch(train) [87][ 920/2569] lr: 4.0000e-02 eta: 12:04:03 time: 0.2700 data_time: 0.0070 memory: 5828 grad_norm: 3.2048 loss: 2.3839 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3839 2023/06/05 08:54:15 - mmengine - INFO - Epoch(train) [87][ 940/2569] lr: 4.0000e-02 eta: 12:03:58 time: 0.2590 data_time: 0.0074 memory: 5828 grad_norm: 3.1015 loss: 2.4681 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4681 2023/06/05 08:54:21 - mmengine - INFO - Epoch(train) [87][ 960/2569] lr: 4.0000e-02 eta: 12:03:53 time: 0.2782 data_time: 0.0071 memory: 5828 grad_norm: 3.0636 loss: 2.5386 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5386 2023/06/05 08:54:26 - mmengine - INFO - Epoch(train) [87][ 980/2569] lr: 4.0000e-02 eta: 12:03:47 time: 0.2593 data_time: 0.0069 memory: 5828 grad_norm: 3.0990 loss: 2.5742 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5742 2023/06/05 08:54:31 - mmengine - INFO - Epoch(train) [87][1000/2569] lr: 4.0000e-02 eta: 12:03:42 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 3.1258 loss: 2.4203 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4203 2023/06/05 08:54:36 - mmengine - INFO - Epoch(train) [87][1020/2569] lr: 4.0000e-02 eta: 12:03:37 time: 0.2594 data_time: 0.0075 memory: 5828 grad_norm: 3.1020 loss: 2.7071 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7071 2023/06/05 08:54:42 - mmengine - INFO - Epoch(train) [87][1040/2569] lr: 4.0000e-02 eta: 12:03:31 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 3.1687 loss: 2.4991 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4991 2023/06/05 08:54:47 - mmengine - INFO - Epoch(train) [87][1060/2569] lr: 4.0000e-02 eta: 12:03:26 time: 0.2736 data_time: 0.0073 memory: 5828 grad_norm: 3.1289 loss: 2.4255 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4255 2023/06/05 08:54:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:54:53 - mmengine - INFO - Epoch(train) [87][1080/2569] lr: 4.0000e-02 eta: 12:03:21 time: 0.2701 data_time: 0.0074 memory: 5828 grad_norm: 3.2480 loss: 2.2668 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2668 2023/06/05 08:54:58 - mmengine - INFO - Epoch(train) [87][1100/2569] lr: 4.0000e-02 eta: 12:03:16 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 3.1530 loss: 2.6389 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6389 2023/06/05 08:55:03 - mmengine - INFO - Epoch(train) [87][1120/2569] lr: 4.0000e-02 eta: 12:03:10 time: 0.2596 data_time: 0.0078 memory: 5828 grad_norm: 3.1179 loss: 2.2354 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2354 2023/06/05 08:55:08 - mmengine - INFO - Epoch(train) [87][1140/2569] lr: 4.0000e-02 eta: 12:03:05 time: 0.2577 data_time: 0.0072 memory: 5828 grad_norm: 3.2027 loss: 2.4858 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4858 2023/06/05 08:55:14 - mmengine - INFO - Epoch(train) [87][1160/2569] lr: 4.0000e-02 eta: 12:02:59 time: 0.2614 data_time: 0.0083 memory: 5828 grad_norm: 3.1514 loss: 2.6541 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6541 2023/06/05 08:55:19 - mmengine - INFO - Epoch(train) [87][1180/2569] lr: 4.0000e-02 eta: 12:02:54 time: 0.2649 data_time: 0.0073 memory: 5828 grad_norm: 3.1815 loss: 2.8114 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8114 2023/06/05 08:55:24 - mmengine - INFO - Epoch(train) [87][1200/2569] lr: 4.0000e-02 eta: 12:02:49 time: 0.2718 data_time: 0.0073 memory: 5828 grad_norm: 3.1161 loss: 2.6473 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6473 2023/06/05 08:55:30 - mmengine - INFO - Epoch(train) [87][1220/2569] lr: 4.0000e-02 eta: 12:02:44 time: 0.2609 data_time: 0.0076 memory: 5828 grad_norm: 3.2014 loss: 2.2604 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2604 2023/06/05 08:55:35 - mmengine - INFO - Epoch(train) [87][1240/2569] lr: 4.0000e-02 eta: 12:02:38 time: 0.2667 data_time: 0.0071 memory: 5828 grad_norm: 3.1587 loss: 2.4567 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4567 2023/06/05 08:55:40 - mmengine - INFO - Epoch(train) [87][1260/2569] lr: 4.0000e-02 eta: 12:02:33 time: 0.2593 data_time: 0.0075 memory: 5828 grad_norm: 3.1006 loss: 2.5323 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5323 2023/06/05 08:55:45 - mmengine - INFO - Epoch(train) [87][1280/2569] lr: 4.0000e-02 eta: 12:02:27 time: 0.2614 data_time: 0.0076 memory: 5828 grad_norm: 3.1523 loss: 2.2830 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2830 2023/06/05 08:55:51 - mmengine - INFO - Epoch(train) [87][1300/2569] lr: 4.0000e-02 eta: 12:02:22 time: 0.2674 data_time: 0.0070 memory: 5828 grad_norm: 3.1005 loss: 2.5519 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5519 2023/06/05 08:55:56 - mmengine - INFO - Epoch(train) [87][1320/2569] lr: 4.0000e-02 eta: 12:02:17 time: 0.2590 data_time: 0.0074 memory: 5828 grad_norm: 3.1927 loss: 2.2066 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2066 2023/06/05 08:56:01 - mmengine - INFO - Epoch(train) [87][1340/2569] lr: 4.0000e-02 eta: 12:02:11 time: 0.2601 data_time: 0.0071 memory: 5828 grad_norm: 3.1488 loss: 2.1720 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1720 2023/06/05 08:56:06 - mmengine - INFO - Epoch(train) [87][1360/2569] lr: 4.0000e-02 eta: 12:02:06 time: 0.2651 data_time: 0.0072 memory: 5828 grad_norm: 3.1345 loss: 2.5672 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5672 2023/06/05 08:56:12 - mmengine - INFO - Epoch(train) [87][1380/2569] lr: 4.0000e-02 eta: 12:02:01 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 3.1216 loss: 2.3002 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3002 2023/06/05 08:56:17 - mmengine - INFO - Epoch(train) [87][1400/2569] lr: 4.0000e-02 eta: 12:01:55 time: 0.2701 data_time: 0.0074 memory: 5828 grad_norm: 3.0620 loss: 2.7033 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.7033 2023/06/05 08:56:22 - mmengine - INFO - Epoch(train) [87][1420/2569] lr: 4.0000e-02 eta: 12:01:50 time: 0.2650 data_time: 0.0074 memory: 5828 grad_norm: 3.1780 loss: 2.3907 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3907 2023/06/05 08:56:28 - mmengine - INFO - Epoch(train) [87][1440/2569] lr: 4.0000e-02 eta: 12:01:45 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 3.1499 loss: 2.9010 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9010 2023/06/05 08:56:33 - mmengine - INFO - Epoch(train) [87][1460/2569] lr: 4.0000e-02 eta: 12:01:39 time: 0.2577 data_time: 0.0074 memory: 5828 grad_norm: 3.1450 loss: 2.5153 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.5153 2023/06/05 08:56:38 - mmengine - INFO - Epoch(train) [87][1480/2569] lr: 4.0000e-02 eta: 12:01:34 time: 0.2619 data_time: 0.0077 memory: 5828 grad_norm: 3.1648 loss: 2.5799 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5799 2023/06/05 08:56:43 - mmengine - INFO - Epoch(train) [87][1500/2569] lr: 4.0000e-02 eta: 12:01:29 time: 0.2666 data_time: 0.0075 memory: 5828 grad_norm: 3.1907 loss: 2.4577 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4577 2023/06/05 08:56:49 - mmengine - INFO - Epoch(train) [87][1520/2569] lr: 4.0000e-02 eta: 12:01:24 time: 0.2765 data_time: 0.0072 memory: 5828 grad_norm: 3.1568 loss: 2.8723 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8723 2023/06/05 08:56:54 - mmengine - INFO - Epoch(train) [87][1540/2569] lr: 4.0000e-02 eta: 12:01:18 time: 0.2687 data_time: 0.0072 memory: 5828 grad_norm: 3.1079 loss: 2.5138 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5138 2023/06/05 08:57:00 - mmengine - INFO - Epoch(train) [87][1560/2569] lr: 4.0000e-02 eta: 12:01:13 time: 0.2575 data_time: 0.0082 memory: 5828 grad_norm: 3.2064 loss: 2.7856 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7856 2023/06/05 08:57:05 - mmengine - INFO - Epoch(train) [87][1580/2569] lr: 4.0000e-02 eta: 12:01:08 time: 0.2734 data_time: 0.0078 memory: 5828 grad_norm: 3.1262 loss: 2.5140 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5140 2023/06/05 08:57:10 - mmengine - INFO - Epoch(train) [87][1600/2569] lr: 4.0000e-02 eta: 12:01:02 time: 0.2673 data_time: 0.0080 memory: 5828 grad_norm: 3.0773 loss: 2.5194 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5194 2023/06/05 08:57:16 - mmengine - INFO - Epoch(train) [87][1620/2569] lr: 4.0000e-02 eta: 12:00:57 time: 0.2698 data_time: 0.0073 memory: 5828 grad_norm: 3.1285 loss: 2.5029 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5029 2023/06/05 08:57:21 - mmengine - INFO - Epoch(train) [87][1640/2569] lr: 4.0000e-02 eta: 12:00:52 time: 0.2653 data_time: 0.0076 memory: 5828 grad_norm: 3.1305 loss: 2.4885 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4885 2023/06/05 08:57:27 - mmengine - INFO - Epoch(train) [87][1660/2569] lr: 4.0000e-02 eta: 12:00:47 time: 0.2730 data_time: 0.0074 memory: 5828 grad_norm: 3.1555 loss: 2.6680 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6680 2023/06/05 08:57:32 - mmengine - INFO - Epoch(train) [87][1680/2569] lr: 4.0000e-02 eta: 12:00:41 time: 0.2601 data_time: 0.0073 memory: 5828 grad_norm: 3.1148 loss: 2.3235 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3235 2023/06/05 08:57:37 - mmengine - INFO - Epoch(train) [87][1700/2569] lr: 4.0000e-02 eta: 12:00:36 time: 0.2682 data_time: 0.0075 memory: 5828 grad_norm: 3.1210 loss: 2.3838 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3838 2023/06/05 08:57:42 - mmengine - INFO - Epoch(train) [87][1720/2569] lr: 4.0000e-02 eta: 12:00:30 time: 0.2597 data_time: 0.0070 memory: 5828 grad_norm: 3.1318 loss: 2.1181 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1181 2023/06/05 08:57:48 - mmengine - INFO - Epoch(train) [87][1740/2569] lr: 4.0000e-02 eta: 12:00:25 time: 0.2596 data_time: 0.0072 memory: 5828 grad_norm: 3.1114 loss: 2.5301 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5301 2023/06/05 08:57:53 - mmengine - INFO - Epoch(train) [87][1760/2569] lr: 4.0000e-02 eta: 12:00:20 time: 0.2743 data_time: 0.0074 memory: 5828 grad_norm: 3.1502 loss: 2.4630 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4630 2023/06/05 08:57:58 - mmengine - INFO - Epoch(train) [87][1780/2569] lr: 4.0000e-02 eta: 12:00:14 time: 0.2596 data_time: 0.0090 memory: 5828 grad_norm: 3.1435 loss: 2.2813 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2813 2023/06/05 08:58:04 - mmengine - INFO - Epoch(train) [87][1800/2569] lr: 4.0000e-02 eta: 12:00:09 time: 0.2727 data_time: 0.0076 memory: 5828 grad_norm: 3.0922 loss: 2.1226 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1226 2023/06/05 08:58:09 - mmengine - INFO - Epoch(train) [87][1820/2569] lr: 4.0000e-02 eta: 12:00:04 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 3.1253 loss: 2.6311 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6311 2023/06/05 08:58:15 - mmengine - INFO - Epoch(train) [87][1840/2569] lr: 4.0000e-02 eta: 11:59:59 time: 0.2756 data_time: 0.0076 memory: 5828 grad_norm: 3.1239 loss: 2.9893 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9893 2023/06/05 08:58:20 - mmengine - INFO - Epoch(train) [87][1860/2569] lr: 4.0000e-02 eta: 11:59:54 time: 0.2706 data_time: 0.0075 memory: 5828 grad_norm: 3.1712 loss: 2.6888 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6888 2023/06/05 08:58:25 - mmengine - INFO - Epoch(train) [87][1880/2569] lr: 4.0000e-02 eta: 11:59:48 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 3.0754 loss: 2.4940 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4940 2023/06/05 08:58:31 - mmengine - INFO - Epoch(train) [87][1900/2569] lr: 4.0000e-02 eta: 11:59:43 time: 0.2702 data_time: 0.0072 memory: 5828 grad_norm: 3.1293 loss: 2.5937 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5937 2023/06/05 08:58:36 - mmengine - INFO - Epoch(train) [87][1920/2569] lr: 4.0000e-02 eta: 11:59:38 time: 0.2591 data_time: 0.0076 memory: 5828 grad_norm: 3.1174 loss: 2.8278 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8278 2023/06/05 08:58:41 - mmengine - INFO - Epoch(train) [87][1940/2569] lr: 4.0000e-02 eta: 11:59:32 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.1384 loss: 2.5333 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5333 2023/06/05 08:58:46 - mmengine - INFO - Epoch(train) [87][1960/2569] lr: 4.0000e-02 eta: 11:59:27 time: 0.2607 data_time: 0.0074 memory: 5828 grad_norm: 3.1326 loss: 2.4596 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4596 2023/06/05 08:58:52 - mmengine - INFO - Epoch(train) [87][1980/2569] lr: 4.0000e-02 eta: 11:59:21 time: 0.2607 data_time: 0.0074 memory: 5828 grad_norm: 3.1150 loss: 2.9217 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9217 2023/06/05 08:58:57 - mmengine - INFO - Epoch(train) [87][2000/2569] lr: 4.0000e-02 eta: 11:59:16 time: 0.2631 data_time: 0.0070 memory: 5828 grad_norm: 3.1921 loss: 2.7108 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7108 2023/06/05 08:59:02 - mmengine - INFO - Epoch(train) [87][2020/2569] lr: 4.0000e-02 eta: 11:59:11 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 3.0958 loss: 2.5834 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5834 2023/06/05 08:59:07 - mmengine - INFO - Epoch(train) [87][2040/2569] lr: 4.0000e-02 eta: 11:59:05 time: 0.2624 data_time: 0.0074 memory: 5828 grad_norm: 3.1299 loss: 2.6329 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6329 2023/06/05 08:59:13 - mmengine - INFO - Epoch(train) [87][2060/2569] lr: 4.0000e-02 eta: 11:59:00 time: 0.2706 data_time: 0.0071 memory: 5828 grad_norm: 3.1024 loss: 2.6929 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6929 2023/06/05 08:59:14 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 08:59:18 - mmengine - INFO - Epoch(train) [87][2080/2569] lr: 4.0000e-02 eta: 11:58:55 time: 0.2584 data_time: 0.0072 memory: 5828 grad_norm: 3.1799 loss: 2.8210 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8210 2023/06/05 08:59:23 - mmengine - INFO - Epoch(train) [87][2100/2569] lr: 4.0000e-02 eta: 11:58:49 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 3.1384 loss: 2.6108 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6108 2023/06/05 08:59:29 - mmengine - INFO - Epoch(train) [87][2120/2569] lr: 4.0000e-02 eta: 11:58:44 time: 0.2602 data_time: 0.0071 memory: 5828 grad_norm: 3.1385 loss: 2.1969 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1969 2023/06/05 08:59:34 - mmengine - INFO - Epoch(train) [87][2140/2569] lr: 4.0000e-02 eta: 11:58:39 time: 0.2705 data_time: 0.0072 memory: 5828 grad_norm: 3.0944 loss: 2.5193 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5193 2023/06/05 08:59:39 - mmengine - INFO - Epoch(train) [87][2160/2569] lr: 4.0000e-02 eta: 11:58:33 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 3.1121 loss: 2.5405 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5405 2023/06/05 08:59:45 - mmengine - INFO - Epoch(train) [87][2180/2569] lr: 4.0000e-02 eta: 11:58:28 time: 0.2700 data_time: 0.0071 memory: 5828 grad_norm: 3.1574 loss: 2.2401 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2401 2023/06/05 08:59:50 - mmengine - INFO - Epoch(train) [87][2200/2569] lr: 4.0000e-02 eta: 11:58:23 time: 0.2607 data_time: 0.0076 memory: 5828 grad_norm: 3.1753 loss: 2.7004 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7004 2023/06/05 08:59:55 - mmengine - INFO - Epoch(train) [87][2220/2569] lr: 4.0000e-02 eta: 11:58:17 time: 0.2622 data_time: 0.0074 memory: 5828 grad_norm: 3.1458 loss: 2.3903 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.3903 2023/06/05 09:00:00 - mmengine - INFO - Epoch(train) [87][2240/2569] lr: 4.0000e-02 eta: 11:58:12 time: 0.2637 data_time: 0.0074 memory: 5828 grad_norm: 3.1650 loss: 2.4565 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4565 2023/06/05 09:00:06 - mmengine - INFO - Epoch(train) [87][2260/2569] lr: 4.0000e-02 eta: 11:58:07 time: 0.2593 data_time: 0.0072 memory: 5828 grad_norm: 3.1753 loss: 2.6212 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6212 2023/06/05 09:00:11 - mmengine - INFO - Epoch(train) [87][2280/2569] lr: 4.0000e-02 eta: 11:58:01 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 3.1202 loss: 2.4700 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4700 2023/06/05 09:00:16 - mmengine - INFO - Epoch(train) [87][2300/2569] lr: 4.0000e-02 eta: 11:57:56 time: 0.2695 data_time: 0.0076 memory: 5828 grad_norm: 3.1171 loss: 2.4799 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4799 2023/06/05 09:00:22 - mmengine - INFO - Epoch(train) [87][2320/2569] lr: 4.0000e-02 eta: 11:57:51 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 3.1254 loss: 2.3911 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3911 2023/06/05 09:00:27 - mmengine - INFO - Epoch(train) [87][2340/2569] lr: 4.0000e-02 eta: 11:57:45 time: 0.2661 data_time: 0.0085 memory: 5828 grad_norm: 3.1798 loss: 2.5821 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5821 2023/06/05 09:00:32 - mmengine - INFO - Epoch(train) [87][2360/2569] lr: 4.0000e-02 eta: 11:57:40 time: 0.2743 data_time: 0.0074 memory: 5828 grad_norm: 3.1779 loss: 2.4081 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4081 2023/06/05 09:00:38 - mmengine - INFO - Epoch(train) [87][2380/2569] lr: 4.0000e-02 eta: 11:57:35 time: 0.2587 data_time: 0.0072 memory: 5828 grad_norm: 3.1054 loss: 2.1598 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1598 2023/06/05 09:00:43 - mmengine - INFO - Epoch(train) [87][2400/2569] lr: 4.0000e-02 eta: 11:57:29 time: 0.2637 data_time: 0.0082 memory: 5828 grad_norm: 3.1624 loss: 2.3904 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3904 2023/06/05 09:00:48 - mmengine - INFO - Epoch(train) [87][2420/2569] lr: 4.0000e-02 eta: 11:57:24 time: 0.2693 data_time: 0.0076 memory: 5828 grad_norm: 3.1604 loss: 1.8960 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8960 2023/06/05 09:00:54 - mmengine - INFO - Epoch(train) [87][2440/2569] lr: 4.0000e-02 eta: 11:57:19 time: 0.2652 data_time: 0.0085 memory: 5828 grad_norm: 3.0874 loss: 2.4958 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4958 2023/06/05 09:00:59 - mmengine - INFO - Epoch(train) [87][2460/2569] lr: 4.0000e-02 eta: 11:57:14 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 3.1298 loss: 2.7771 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7771 2023/06/05 09:01:04 - mmengine - INFO - Epoch(train) [87][2480/2569] lr: 4.0000e-02 eta: 11:57:08 time: 0.2611 data_time: 0.0076 memory: 5828 grad_norm: 3.1117 loss: 2.4458 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4458 2023/06/05 09:01:09 - mmengine - INFO - Epoch(train) [87][2500/2569] lr: 4.0000e-02 eta: 11:57:03 time: 0.2662 data_time: 0.0077 memory: 5828 grad_norm: 3.1131 loss: 2.8179 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8179 2023/06/05 09:01:15 - mmengine - INFO - Epoch(train) [87][2520/2569] lr: 4.0000e-02 eta: 11:56:58 time: 0.2731 data_time: 0.0071 memory: 5828 grad_norm: 3.1482 loss: 2.1869 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1869 2023/06/05 09:01:20 - mmengine - INFO - Epoch(train) [87][2540/2569] lr: 4.0000e-02 eta: 11:56:52 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 3.0926 loss: 2.5273 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5273 2023/06/05 09:01:26 - mmengine - INFO - Epoch(train) [87][2560/2569] lr: 4.0000e-02 eta: 11:56:47 time: 0.2734 data_time: 0.0070 memory: 5828 grad_norm: 3.1492 loss: 2.2681 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2681 2023/06/05 09:01:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:01:28 - mmengine - INFO - Epoch(train) [87][2569/2569] lr: 4.0000e-02 eta: 11:56:45 time: 0.2669 data_time: 0.0071 memory: 5828 grad_norm: 3.1552 loss: 2.2669 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.2669 2023/06/05 09:01:35 - mmengine - INFO - Epoch(train) [88][ 20/2569] lr: 4.0000e-02 eta: 11:56:40 time: 0.3327 data_time: 0.0611 memory: 5828 grad_norm: 3.1252 loss: 2.4582 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4582 2023/06/05 09:01:40 - mmengine - INFO - Epoch(train) [88][ 40/2569] lr: 4.0000e-02 eta: 11:56:35 time: 0.2719 data_time: 0.0079 memory: 5828 grad_norm: 3.1875 loss: 2.5079 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5079 2023/06/05 09:01:45 - mmengine - INFO - Epoch(train) [88][ 60/2569] lr: 4.0000e-02 eta: 11:56:30 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 3.0962 loss: 2.4631 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4631 2023/06/05 09:01:51 - mmengine - INFO - Epoch(train) [88][ 80/2569] lr: 4.0000e-02 eta: 11:56:24 time: 0.2594 data_time: 0.0074 memory: 5828 grad_norm: 3.1468 loss: 2.4037 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4037 2023/06/05 09:01:56 - mmengine - INFO - Epoch(train) [88][ 100/2569] lr: 4.0000e-02 eta: 11:56:19 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 3.1678 loss: 2.4900 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4900 2023/06/05 09:02:01 - mmengine - INFO - Epoch(train) [88][ 120/2569] lr: 4.0000e-02 eta: 11:56:14 time: 0.2612 data_time: 0.0076 memory: 5828 grad_norm: 3.1498 loss: 2.2756 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2756 2023/06/05 09:02:07 - mmengine - INFO - Epoch(train) [88][ 140/2569] lr: 4.0000e-02 eta: 11:56:08 time: 0.2676 data_time: 0.0082 memory: 5828 grad_norm: 3.1624 loss: 2.7752 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7752 2023/06/05 09:02:12 - mmengine - INFO - Epoch(train) [88][ 160/2569] lr: 4.0000e-02 eta: 11:56:03 time: 0.2731 data_time: 0.0087 memory: 5828 grad_norm: 3.1370 loss: 2.8195 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8195 2023/06/05 09:02:17 - mmengine - INFO - Epoch(train) [88][ 180/2569] lr: 4.0000e-02 eta: 11:55:58 time: 0.2626 data_time: 0.0072 memory: 5828 grad_norm: 3.0947 loss: 2.4572 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4572 2023/06/05 09:02:23 - mmengine - INFO - Epoch(train) [88][ 200/2569] lr: 4.0000e-02 eta: 11:55:52 time: 0.2648 data_time: 0.0078 memory: 5828 grad_norm: 3.0933 loss: 2.9180 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9180 2023/06/05 09:02:28 - mmengine - INFO - Epoch(train) [88][ 220/2569] lr: 4.0000e-02 eta: 11:55:47 time: 0.2594 data_time: 0.0077 memory: 5828 grad_norm: 3.1536 loss: 2.5389 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5389 2023/06/05 09:02:33 - mmengine - INFO - Epoch(train) [88][ 240/2569] lr: 4.0000e-02 eta: 11:55:42 time: 0.2671 data_time: 0.0079 memory: 5828 grad_norm: 3.1010 loss: 2.2654 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2654 2023/06/05 09:02:38 - mmengine - INFO - Epoch(train) [88][ 260/2569] lr: 4.0000e-02 eta: 11:55:36 time: 0.2683 data_time: 0.0076 memory: 5828 grad_norm: 3.0987 loss: 2.6238 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6238 2023/06/05 09:02:44 - mmengine - INFO - Epoch(train) [88][ 280/2569] lr: 4.0000e-02 eta: 11:55:31 time: 0.2651 data_time: 0.0090 memory: 5828 grad_norm: 3.1640 loss: 2.4879 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4879 2023/06/05 09:02:49 - mmengine - INFO - Epoch(train) [88][ 300/2569] lr: 4.0000e-02 eta: 11:55:26 time: 0.2689 data_time: 0.0078 memory: 5828 grad_norm: 3.1732 loss: 2.2133 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2133 2023/06/05 09:02:54 - mmengine - INFO - Epoch(train) [88][ 320/2569] lr: 4.0000e-02 eta: 11:55:21 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 3.0706 loss: 2.2606 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2606 2023/06/05 09:03:00 - mmengine - INFO - Epoch(train) [88][ 340/2569] lr: 4.0000e-02 eta: 11:55:15 time: 0.2797 data_time: 0.0074 memory: 5828 grad_norm: 3.1775 loss: 2.6078 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6078 2023/06/05 09:03:05 - mmengine - INFO - Epoch(train) [88][ 360/2569] lr: 4.0000e-02 eta: 11:55:10 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 3.1688 loss: 2.4171 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4171 2023/06/05 09:03:11 - mmengine - INFO - Epoch(train) [88][ 380/2569] lr: 4.0000e-02 eta: 11:55:05 time: 0.2767 data_time: 0.0076 memory: 5828 grad_norm: 3.1827 loss: 2.5953 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5953 2023/06/05 09:03:16 - mmengine - INFO - Epoch(train) [88][ 400/2569] lr: 4.0000e-02 eta: 11:55:00 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 3.1360 loss: 2.2191 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2191 2023/06/05 09:03:21 - mmengine - INFO - Epoch(train) [88][ 420/2569] lr: 4.0000e-02 eta: 11:54:54 time: 0.2611 data_time: 0.0072 memory: 5828 grad_norm: 3.1533 loss: 2.7020 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7020 2023/06/05 09:03:27 - mmengine - INFO - Epoch(train) [88][ 440/2569] lr: 4.0000e-02 eta: 11:54:49 time: 0.2582 data_time: 0.0079 memory: 5828 grad_norm: 3.1557 loss: 2.6245 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6245 2023/06/05 09:03:32 - mmengine - INFO - Epoch(train) [88][ 460/2569] lr: 4.0000e-02 eta: 11:54:43 time: 0.2600 data_time: 0.0072 memory: 5828 grad_norm: 3.1667 loss: 2.4770 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4770 2023/06/05 09:03:37 - mmengine - INFO - Epoch(train) [88][ 480/2569] lr: 4.0000e-02 eta: 11:54:38 time: 0.2669 data_time: 0.0076 memory: 5828 grad_norm: 3.0825 loss: 2.4500 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4500 2023/06/05 09:03:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:03:42 - mmengine - INFO - Epoch(train) [88][ 500/2569] lr: 4.0000e-02 eta: 11:54:33 time: 0.2645 data_time: 0.0081 memory: 5828 grad_norm: 3.1347 loss: 2.4180 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4180 2023/06/05 09:03:48 - mmengine - INFO - Epoch(train) [88][ 520/2569] lr: 4.0000e-02 eta: 11:54:27 time: 0.2661 data_time: 0.0074 memory: 5828 grad_norm: 3.1754 loss: 2.4601 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4601 2023/06/05 09:03:53 - mmengine - INFO - Epoch(train) [88][ 540/2569] lr: 4.0000e-02 eta: 11:54:22 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 3.1378 loss: 2.3378 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3378 2023/06/05 09:03:58 - mmengine - INFO - Epoch(train) [88][ 560/2569] lr: 4.0000e-02 eta: 11:54:17 time: 0.2682 data_time: 0.0074 memory: 5828 grad_norm: 3.1429 loss: 2.7864 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7864 2023/06/05 09:04:04 - mmengine - INFO - Epoch(train) [88][ 580/2569] lr: 4.0000e-02 eta: 11:54:12 time: 0.2660 data_time: 0.0079 memory: 5828 grad_norm: 3.1519 loss: 2.3785 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3785 2023/06/05 09:04:09 - mmengine - INFO - Epoch(train) [88][ 600/2569] lr: 4.0000e-02 eta: 11:54:06 time: 0.2598 data_time: 0.0075 memory: 5828 grad_norm: 3.2104 loss: 2.7046 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7046 2023/06/05 09:04:15 - mmengine - INFO - Epoch(train) [88][ 620/2569] lr: 4.0000e-02 eta: 11:54:01 time: 0.2804 data_time: 0.0079 memory: 5828 grad_norm: 3.1417 loss: 2.3888 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3888 2023/06/05 09:04:20 - mmengine - INFO - Epoch(train) [88][ 640/2569] lr: 4.0000e-02 eta: 11:53:56 time: 0.2585 data_time: 0.0071 memory: 5828 grad_norm: 3.1421 loss: 2.5788 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5788 2023/06/05 09:04:25 - mmengine - INFO - Epoch(train) [88][ 660/2569] lr: 4.0000e-02 eta: 11:53:50 time: 0.2721 data_time: 0.0070 memory: 5828 grad_norm: 3.1482 loss: 2.7388 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7388 2023/06/05 09:04:30 - mmengine - INFO - Epoch(train) [88][ 680/2569] lr: 4.0000e-02 eta: 11:53:45 time: 0.2597 data_time: 0.0084 memory: 5828 grad_norm: 3.1420 loss: 2.3431 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.3431 2023/06/05 09:04:36 - mmengine - INFO - Epoch(train) [88][ 700/2569] lr: 4.0000e-02 eta: 11:53:40 time: 0.2602 data_time: 0.0073 memory: 5828 grad_norm: 3.1463 loss: 2.4790 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4790 2023/06/05 09:04:41 - mmengine - INFO - Epoch(train) [88][ 720/2569] lr: 4.0000e-02 eta: 11:53:34 time: 0.2641 data_time: 0.0085 memory: 5828 grad_norm: 3.0852 loss: 2.5109 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5109 2023/06/05 09:04:46 - mmengine - INFO - Epoch(train) [88][ 740/2569] lr: 4.0000e-02 eta: 11:53:29 time: 0.2619 data_time: 0.0077 memory: 5828 grad_norm: 3.1445 loss: 2.5928 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5928 2023/06/05 09:04:52 - mmengine - INFO - Epoch(train) [88][ 760/2569] lr: 4.0000e-02 eta: 11:53:24 time: 0.2668 data_time: 0.0074 memory: 5828 grad_norm: 3.1379 loss: 2.3010 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3010 2023/06/05 09:04:57 - mmengine - INFO - Epoch(train) [88][ 780/2569] lr: 4.0000e-02 eta: 11:53:18 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 3.1586 loss: 2.4436 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4436 2023/06/05 09:05:03 - mmengine - INFO - Epoch(train) [88][ 800/2569] lr: 4.0000e-02 eta: 11:53:13 time: 0.2822 data_time: 0.0072 memory: 5828 grad_norm: 3.0930 loss: 2.2851 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2851 2023/06/05 09:05:08 - mmengine - INFO - Epoch(train) [88][ 820/2569] lr: 4.0000e-02 eta: 11:53:08 time: 0.2597 data_time: 0.0076 memory: 5828 grad_norm: 3.1462 loss: 2.3688 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3688 2023/06/05 09:05:13 - mmengine - INFO - Epoch(train) [88][ 840/2569] lr: 4.0000e-02 eta: 11:53:03 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 3.0855 loss: 2.6642 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6642 2023/06/05 09:05:18 - mmengine - INFO - Epoch(train) [88][ 860/2569] lr: 4.0000e-02 eta: 11:52:57 time: 0.2637 data_time: 0.0074 memory: 5828 grad_norm: 3.0865 loss: 2.7946 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7946 2023/06/05 09:05:24 - mmengine - INFO - Epoch(train) [88][ 880/2569] lr: 4.0000e-02 eta: 11:52:52 time: 0.2689 data_time: 0.0076 memory: 5828 grad_norm: 3.2042 loss: 2.4540 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4540 2023/06/05 09:05:29 - mmengine - INFO - Epoch(train) [88][ 900/2569] lr: 4.0000e-02 eta: 11:52:46 time: 0.2602 data_time: 0.0076 memory: 5828 grad_norm: 3.1448 loss: 2.1295 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1295 2023/06/05 09:05:34 - mmengine - INFO - Epoch(train) [88][ 920/2569] lr: 4.0000e-02 eta: 11:52:41 time: 0.2766 data_time: 0.0080 memory: 5828 grad_norm: 3.1353 loss: 2.9371 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9371 2023/06/05 09:05:40 - mmengine - INFO - Epoch(train) [88][ 940/2569] lr: 4.0000e-02 eta: 11:52:36 time: 0.2665 data_time: 0.0071 memory: 5828 grad_norm: 3.2108 loss: 2.4744 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4744 2023/06/05 09:05:45 - mmengine - INFO - Epoch(train) [88][ 960/2569] lr: 4.0000e-02 eta: 11:52:31 time: 0.2603 data_time: 0.0074 memory: 5828 grad_norm: 3.1399 loss: 2.4109 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4109 2023/06/05 09:05:50 - mmengine - INFO - Epoch(train) [88][ 980/2569] lr: 4.0000e-02 eta: 11:52:25 time: 0.2600 data_time: 0.0075 memory: 5828 grad_norm: 3.0410 loss: 2.5908 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5908 2023/06/05 09:05:55 - mmengine - INFO - Epoch(train) [88][1000/2569] lr: 4.0000e-02 eta: 11:52:20 time: 0.2595 data_time: 0.0076 memory: 5828 grad_norm: 3.1774 loss: 2.5281 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5281 2023/06/05 09:06:01 - mmengine - INFO - Epoch(train) [88][1020/2569] lr: 4.0000e-02 eta: 11:52:14 time: 0.2594 data_time: 0.0078 memory: 5828 grad_norm: 3.0965 loss: 2.6485 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6485 2023/06/05 09:06:06 - mmengine - INFO - Epoch(train) [88][1040/2569] lr: 4.0000e-02 eta: 11:52:09 time: 0.2711 data_time: 0.0078 memory: 5828 grad_norm: 3.1141 loss: 2.2742 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2742 2023/06/05 09:06:11 - mmengine - INFO - Epoch(train) [88][1060/2569] lr: 4.0000e-02 eta: 11:52:04 time: 0.2647 data_time: 0.0095 memory: 5828 grad_norm: 3.1282 loss: 2.5513 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5513 2023/06/05 09:06:17 - mmengine - INFO - Epoch(train) [88][1080/2569] lr: 4.0000e-02 eta: 11:51:59 time: 0.2667 data_time: 0.0076 memory: 5828 grad_norm: 3.0993 loss: 2.4784 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4784 2023/06/05 09:06:22 - mmengine - INFO - Epoch(train) [88][1100/2569] lr: 4.0000e-02 eta: 11:51:53 time: 0.2648 data_time: 0.0075 memory: 5828 grad_norm: 3.1395 loss: 2.6566 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6566 2023/06/05 09:06:27 - mmengine - INFO - Epoch(train) [88][1120/2569] lr: 4.0000e-02 eta: 11:51:48 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 3.1491 loss: 2.3917 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3917 2023/06/05 09:06:33 - mmengine - INFO - Epoch(train) [88][1140/2569] lr: 4.0000e-02 eta: 11:51:43 time: 0.2705 data_time: 0.0070 memory: 5828 grad_norm: 3.1063 loss: 2.7028 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7028 2023/06/05 09:06:38 - mmengine - INFO - Epoch(train) [88][1160/2569] lr: 4.0000e-02 eta: 11:51:37 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 3.1281 loss: 2.5239 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5239 2023/06/05 09:06:43 - mmengine - INFO - Epoch(train) [88][1180/2569] lr: 4.0000e-02 eta: 11:51:32 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 3.0914 loss: 2.2728 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2728 2023/06/05 09:06:49 - mmengine - INFO - Epoch(train) [88][1200/2569] lr: 4.0000e-02 eta: 11:51:27 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 3.1779 loss: 2.5641 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5641 2023/06/05 09:06:54 - mmengine - INFO - Epoch(train) [88][1220/2569] lr: 4.0000e-02 eta: 11:51:21 time: 0.2594 data_time: 0.0073 memory: 5828 grad_norm: 3.1660 loss: 2.6435 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6435 2023/06/05 09:06:59 - mmengine - INFO - Epoch(train) [88][1240/2569] lr: 4.0000e-02 eta: 11:51:16 time: 0.2776 data_time: 0.0072 memory: 5828 grad_norm: 3.1764 loss: 2.8188 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8188 2023/06/05 09:07:05 - mmengine - INFO - Epoch(train) [88][1260/2569] lr: 4.0000e-02 eta: 11:51:11 time: 0.2609 data_time: 0.0076 memory: 5828 grad_norm: 3.1368 loss: 2.2826 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2826 2023/06/05 09:07:10 - mmengine - INFO - Epoch(train) [88][1280/2569] lr: 4.0000e-02 eta: 11:51:06 time: 0.2679 data_time: 0.0079 memory: 5828 grad_norm: 3.1837 loss: 2.4294 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4294 2023/06/05 09:07:15 - mmengine - INFO - Epoch(train) [88][1300/2569] lr: 4.0000e-02 eta: 11:51:00 time: 0.2588 data_time: 0.0074 memory: 5828 grad_norm: 3.1336 loss: 2.4595 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4595 2023/06/05 09:07:21 - mmengine - INFO - Epoch(train) [88][1320/2569] lr: 4.0000e-02 eta: 11:50:55 time: 0.2741 data_time: 0.0073 memory: 5828 grad_norm: 3.1194 loss: 2.4839 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4839 2023/06/05 09:07:26 - mmengine - INFO - Epoch(train) [88][1340/2569] lr: 4.0000e-02 eta: 11:50:50 time: 0.2595 data_time: 0.0073 memory: 5828 grad_norm: 3.0583 loss: 2.3990 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.3990 2023/06/05 09:07:31 - mmengine - INFO - Epoch(train) [88][1360/2569] lr: 4.0000e-02 eta: 11:50:44 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 3.0943 loss: 2.5662 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5662 2023/06/05 09:07:36 - mmengine - INFO - Epoch(train) [88][1380/2569] lr: 4.0000e-02 eta: 11:50:39 time: 0.2589 data_time: 0.0075 memory: 5828 grad_norm: 3.1449 loss: 2.6000 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6000 2023/06/05 09:07:42 - mmengine - INFO - Epoch(train) [88][1400/2569] lr: 4.0000e-02 eta: 11:50:34 time: 0.2717 data_time: 0.0073 memory: 5828 grad_norm: 3.1335 loss: 2.4044 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4044 2023/06/05 09:07:47 - mmengine - INFO - Epoch(train) [88][1420/2569] lr: 4.0000e-02 eta: 11:50:28 time: 0.2729 data_time: 0.0076 memory: 5828 grad_norm: 3.1260 loss: 2.3549 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3549 2023/06/05 09:07:52 - mmengine - INFO - Epoch(train) [88][1440/2569] lr: 4.0000e-02 eta: 11:50:23 time: 0.2594 data_time: 0.0076 memory: 5828 grad_norm: 3.1388 loss: 2.5905 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5905 2023/06/05 09:07:58 - mmengine - INFO - Epoch(train) [88][1460/2569] lr: 4.0000e-02 eta: 11:50:18 time: 0.2657 data_time: 0.0071 memory: 5828 grad_norm: 3.1458 loss: 2.3056 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3056 2023/06/05 09:08:03 - mmengine - INFO - Epoch(train) [88][1480/2569] lr: 4.0000e-02 eta: 11:50:12 time: 0.2675 data_time: 0.0076 memory: 5828 grad_norm: 3.1686 loss: 2.5811 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5811 2023/06/05 09:08:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:08:08 - mmengine - INFO - Epoch(train) [88][1500/2569] lr: 4.0000e-02 eta: 11:50:07 time: 0.2641 data_time: 0.0077 memory: 5828 grad_norm: 3.1280 loss: 2.8376 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8376 2023/06/05 09:08:14 - mmengine - INFO - Epoch(train) [88][1520/2569] lr: 4.0000e-02 eta: 11:50:02 time: 0.2641 data_time: 0.0070 memory: 5828 grad_norm: 3.0979 loss: 2.3276 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3276 2023/06/05 09:08:19 - mmengine - INFO - Epoch(train) [88][1540/2569] lr: 4.0000e-02 eta: 11:49:56 time: 0.2722 data_time: 0.0074 memory: 5828 grad_norm: 3.1274 loss: 2.5621 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5621 2023/06/05 09:08:25 - mmengine - INFO - Epoch(train) [88][1560/2569] lr: 4.0000e-02 eta: 11:49:51 time: 0.2652 data_time: 0.0076 memory: 5828 grad_norm: 3.2219 loss: 2.2154 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2154 2023/06/05 09:08:30 - mmengine - INFO - Epoch(train) [88][1580/2569] lr: 4.0000e-02 eta: 11:49:46 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 3.1180 loss: 2.7399 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.7399 2023/06/05 09:08:35 - mmengine - INFO - Epoch(train) [88][1600/2569] lr: 4.0000e-02 eta: 11:49:40 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 3.1130 loss: 2.7471 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7471 2023/06/05 09:08:41 - mmengine - INFO - Epoch(train) [88][1620/2569] lr: 4.0000e-02 eta: 11:49:35 time: 0.2706 data_time: 0.0073 memory: 5828 grad_norm: 3.1676 loss: 2.9342 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9342 2023/06/05 09:08:46 - mmengine - INFO - Epoch(train) [88][1640/2569] lr: 4.0000e-02 eta: 11:49:30 time: 0.2578 data_time: 0.0073 memory: 5828 grad_norm: 3.1112 loss: 2.6440 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6440 2023/06/05 09:08:51 - mmengine - INFO - Epoch(train) [88][1660/2569] lr: 4.0000e-02 eta: 11:49:25 time: 0.2740 data_time: 0.0074 memory: 5828 grad_norm: 3.1045 loss: 2.4558 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4558 2023/06/05 09:08:56 - mmengine - INFO - Epoch(train) [88][1680/2569] lr: 4.0000e-02 eta: 11:49:19 time: 0.2601 data_time: 0.0084 memory: 5828 grad_norm: 3.1092 loss: 2.3870 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3870 2023/06/05 09:09:02 - mmengine - INFO - Epoch(train) [88][1700/2569] lr: 4.0000e-02 eta: 11:49:14 time: 0.2748 data_time: 0.0077 memory: 5828 grad_norm: 3.1035 loss: 2.4665 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4665 2023/06/05 09:09:07 - mmengine - INFO - Epoch(train) [88][1720/2569] lr: 4.0000e-02 eta: 11:49:09 time: 0.2634 data_time: 0.0083 memory: 5828 grad_norm: 3.0922 loss: 2.6507 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6507 2023/06/05 09:09:12 - mmengine - INFO - Epoch(train) [88][1740/2569] lr: 4.0000e-02 eta: 11:49:03 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.1324 loss: 2.2867 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2867 2023/06/05 09:09:18 - mmengine - INFO - Epoch(train) [88][1760/2569] lr: 4.0000e-02 eta: 11:48:58 time: 0.2768 data_time: 0.0077 memory: 5828 grad_norm: 3.1858 loss: 2.2994 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2994 2023/06/05 09:09:23 - mmengine - INFO - Epoch(train) [88][1780/2569] lr: 4.0000e-02 eta: 11:48:53 time: 0.2646 data_time: 0.0081 memory: 5828 grad_norm: 3.2072 loss: 2.4386 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4386 2023/06/05 09:09:29 - mmengine - INFO - Epoch(train) [88][1800/2569] lr: 4.0000e-02 eta: 11:48:47 time: 0.2603 data_time: 0.0082 memory: 5828 grad_norm: 3.1058 loss: 3.0015 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 3.0015 2023/06/05 09:09:34 - mmengine - INFO - Epoch(train) [88][1820/2569] lr: 4.0000e-02 eta: 11:48:42 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 3.0599 loss: 2.0471 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0471 2023/06/05 09:09:39 - mmengine - INFO - Epoch(train) [88][1840/2569] lr: 4.0000e-02 eta: 11:48:37 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 3.1330 loss: 2.6654 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6654 2023/06/05 09:09:44 - mmengine - INFO - Epoch(train) [88][1860/2569] lr: 4.0000e-02 eta: 11:48:31 time: 0.2601 data_time: 0.0077 memory: 5828 grad_norm: 3.0741 loss: 2.6881 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6881 2023/06/05 09:09:50 - mmengine - INFO - Epoch(train) [88][1880/2569] lr: 4.0000e-02 eta: 11:48:26 time: 0.2645 data_time: 0.0075 memory: 5828 grad_norm: 3.1831 loss: 2.5086 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5086 2023/06/05 09:09:55 - mmengine - INFO - Epoch(train) [88][1900/2569] lr: 4.0000e-02 eta: 11:48:21 time: 0.2775 data_time: 0.0077 memory: 5828 grad_norm: 3.1160 loss: 2.5073 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5073 2023/06/05 09:10:00 - mmengine - INFO - Epoch(train) [88][1920/2569] lr: 4.0000e-02 eta: 11:48:15 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 3.1315 loss: 2.7453 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7453 2023/06/05 09:10:06 - mmengine - INFO - Epoch(train) [88][1940/2569] lr: 4.0000e-02 eta: 11:48:10 time: 0.2658 data_time: 0.0077 memory: 5828 grad_norm: 3.2098 loss: 2.6547 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6547 2023/06/05 09:10:11 - mmengine - INFO - Epoch(train) [88][1960/2569] lr: 4.0000e-02 eta: 11:48:05 time: 0.2621 data_time: 0.0072 memory: 5828 grad_norm: 3.1558 loss: 2.5481 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5481 2023/06/05 09:10:16 - mmengine - INFO - Epoch(train) [88][1980/2569] lr: 4.0000e-02 eta: 11:48:00 time: 0.2709 data_time: 0.0076 memory: 5828 grad_norm: 3.1430 loss: 2.9553 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.9553 2023/06/05 09:10:22 - mmengine - INFO - Epoch(train) [88][2000/2569] lr: 4.0000e-02 eta: 11:47:54 time: 0.2617 data_time: 0.0080 memory: 5828 grad_norm: 3.0821 loss: 2.4774 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4774 2023/06/05 09:10:27 - mmengine - INFO - Epoch(train) [88][2020/2569] lr: 4.0000e-02 eta: 11:47:49 time: 0.2750 data_time: 0.0074 memory: 5828 grad_norm: 3.1257 loss: 2.7991 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7991 2023/06/05 09:10:32 - mmengine - INFO - Epoch(train) [88][2040/2569] lr: 4.0000e-02 eta: 11:47:44 time: 0.2620 data_time: 0.0071 memory: 5828 grad_norm: 3.1726 loss: 2.4745 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4745 2023/06/05 09:10:38 - mmengine - INFO - Epoch(train) [88][2060/2569] lr: 4.0000e-02 eta: 11:47:38 time: 0.2745 data_time: 0.0073 memory: 5828 grad_norm: 3.1536 loss: 2.3952 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3952 2023/06/05 09:10:43 - mmengine - INFO - Epoch(train) [88][2080/2569] lr: 4.0000e-02 eta: 11:47:33 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 3.0839 loss: 2.5092 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5092 2023/06/05 09:10:49 - mmengine - INFO - Epoch(train) [88][2100/2569] lr: 4.0000e-02 eta: 11:47:28 time: 0.2705 data_time: 0.0072 memory: 5828 grad_norm: 3.1372 loss: 2.4824 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4824 2023/06/05 09:10:54 - mmengine - INFO - Epoch(train) [88][2120/2569] lr: 4.0000e-02 eta: 11:47:22 time: 0.2587 data_time: 0.0074 memory: 5828 grad_norm: 3.1940 loss: 2.8033 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8033 2023/06/05 09:10:59 - mmengine - INFO - Epoch(train) [88][2140/2569] lr: 4.0000e-02 eta: 11:47:17 time: 0.2613 data_time: 0.0072 memory: 5828 grad_norm: 3.1129 loss: 2.3268 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3268 2023/06/05 09:11:04 - mmengine - INFO - Epoch(train) [88][2160/2569] lr: 4.0000e-02 eta: 11:47:12 time: 0.2584 data_time: 0.0078 memory: 5828 grad_norm: 3.0507 loss: 2.5728 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5728 2023/06/05 09:11:10 - mmengine - INFO - Epoch(train) [88][2180/2569] lr: 4.0000e-02 eta: 11:47:06 time: 0.2755 data_time: 0.0073 memory: 5828 grad_norm: 3.1479 loss: 2.3927 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3927 2023/06/05 09:11:15 - mmengine - INFO - Epoch(train) [88][2200/2569] lr: 4.0000e-02 eta: 11:47:01 time: 0.2586 data_time: 0.0076 memory: 5828 grad_norm: 3.1468 loss: 2.5883 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5883 2023/06/05 09:11:20 - mmengine - INFO - Epoch(train) [88][2220/2569] lr: 4.0000e-02 eta: 11:46:56 time: 0.2761 data_time: 0.0073 memory: 5828 grad_norm: 3.1473 loss: 2.5642 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5642 2023/06/05 09:11:26 - mmengine - INFO - Epoch(train) [88][2240/2569] lr: 4.0000e-02 eta: 11:46:51 time: 0.2756 data_time: 0.0074 memory: 5828 grad_norm: 3.1058 loss: 2.7804 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7804 2023/06/05 09:11:31 - mmengine - INFO - Epoch(train) [88][2260/2569] lr: 4.0000e-02 eta: 11:46:45 time: 0.2601 data_time: 0.0079 memory: 5828 grad_norm: 3.1668 loss: 2.2931 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.2931 2023/06/05 09:11:37 - mmengine - INFO - Epoch(train) [88][2280/2569] lr: 4.0000e-02 eta: 11:46:40 time: 0.2761 data_time: 0.0077 memory: 5828 grad_norm: 3.1116 loss: 2.4100 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4100 2023/06/05 09:11:42 - mmengine - INFO - Epoch(train) [88][2300/2569] lr: 4.0000e-02 eta: 11:46:35 time: 0.2654 data_time: 0.0084 memory: 5828 grad_norm: 3.1493 loss: 2.4676 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4676 2023/06/05 09:11:47 - mmengine - INFO - Epoch(train) [88][2320/2569] lr: 4.0000e-02 eta: 11:46:30 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 3.2090 loss: 2.4826 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4826 2023/06/05 09:11:53 - mmengine - INFO - Epoch(train) [88][2340/2569] lr: 4.0000e-02 eta: 11:46:24 time: 0.2637 data_time: 0.0072 memory: 5828 grad_norm: 3.0766 loss: 2.8969 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8969 2023/06/05 09:11:58 - mmengine - INFO - Epoch(train) [88][2360/2569] lr: 4.0000e-02 eta: 11:46:19 time: 0.2644 data_time: 0.0071 memory: 5828 grad_norm: 3.1020 loss: 2.4912 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4912 2023/06/05 09:12:03 - mmengine - INFO - Epoch(train) [88][2380/2569] lr: 4.0000e-02 eta: 11:46:13 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 3.1700 loss: 2.4632 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4632 2023/06/05 09:12:08 - mmengine - INFO - Epoch(train) [88][2400/2569] lr: 4.0000e-02 eta: 11:46:08 time: 0.2657 data_time: 0.0077 memory: 5828 grad_norm: 3.1004 loss: 2.3124 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3124 2023/06/05 09:12:14 - mmengine - INFO - Epoch(train) [88][2420/2569] lr: 4.0000e-02 eta: 11:46:03 time: 0.2647 data_time: 0.0075 memory: 5828 grad_norm: 3.1486 loss: 2.6254 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6254 2023/06/05 09:12:19 - mmengine - INFO - Epoch(train) [88][2440/2569] lr: 4.0000e-02 eta: 11:45:57 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 3.1928 loss: 2.2679 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2679 2023/06/05 09:12:24 - mmengine - INFO - Epoch(train) [88][2460/2569] lr: 4.0000e-02 eta: 11:45:52 time: 0.2597 data_time: 0.0070 memory: 5828 grad_norm: 3.1018 loss: 2.5284 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5284 2023/06/05 09:12:29 - mmengine - INFO - Epoch(train) [88][2480/2569] lr: 4.0000e-02 eta: 11:45:47 time: 0.2614 data_time: 0.0076 memory: 5828 grad_norm: 3.1294 loss: 2.5780 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5780 2023/06/05 09:12:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:12:35 - mmengine - INFO - Epoch(train) [88][2500/2569] lr: 4.0000e-02 eta: 11:45:41 time: 0.2584 data_time: 0.0075 memory: 5828 grad_norm: 3.0639 loss: 2.7398 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7398 2023/06/05 09:12:40 - mmengine - INFO - Epoch(train) [88][2520/2569] lr: 4.0000e-02 eta: 11:45:36 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 3.1699 loss: 2.5670 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5670 2023/06/05 09:12:45 - mmengine - INFO - Epoch(train) [88][2540/2569] lr: 4.0000e-02 eta: 11:45:31 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 3.1586 loss: 2.5890 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5890 2023/06/05 09:12:50 - mmengine - INFO - Epoch(train) [88][2560/2569] lr: 4.0000e-02 eta: 11:45:25 time: 0.2633 data_time: 0.0072 memory: 5828 grad_norm: 3.0649 loss: 2.8469 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8469 2023/06/05 09:12:53 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:12:53 - mmengine - INFO - Epoch(train) [88][2569/2569] lr: 4.0000e-02 eta: 11:45:23 time: 0.2586 data_time: 0.0067 memory: 5828 grad_norm: 3.1137 loss: 2.8680 top1_acc: 0.1667 top5_acc: 0.3333 loss_cls: 2.8680 2023/06/05 09:12:53 - mmengine - INFO - Saving checkpoint at 88 epochs 2023/06/05 09:13:01 - mmengine - INFO - Epoch(train) [89][ 20/2569] lr: 4.0000e-02 eta: 11:45:18 time: 0.2981 data_time: 0.0452 memory: 5828 grad_norm: 3.1274 loss: 2.5981 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5981 2023/06/05 09:13:06 - mmengine - INFO - Epoch(train) [89][ 40/2569] lr: 4.0000e-02 eta: 11:45:13 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 3.1501 loss: 2.5040 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5040 2023/06/05 09:13:11 - mmengine - INFO - Epoch(train) [89][ 60/2569] lr: 4.0000e-02 eta: 11:45:07 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 3.1608 loss: 2.5471 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5471 2023/06/05 09:13:17 - mmengine - INFO - Epoch(train) [89][ 80/2569] lr: 4.0000e-02 eta: 11:45:02 time: 0.2596 data_time: 0.0072 memory: 5828 grad_norm: 3.1529 loss: 2.4998 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4998 2023/06/05 09:13:22 - mmengine - INFO - Epoch(train) [89][ 100/2569] lr: 4.0000e-02 eta: 11:44:57 time: 0.2709 data_time: 0.0074 memory: 5828 grad_norm: 3.0914 loss: 2.6192 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6192 2023/06/05 09:13:27 - mmengine - INFO - Epoch(train) [89][ 120/2569] lr: 4.0000e-02 eta: 11:44:51 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 3.1810 loss: 2.5516 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5516 2023/06/05 09:13:33 - mmengine - INFO - Epoch(train) [89][ 140/2569] lr: 4.0000e-02 eta: 11:44:46 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 3.1474 loss: 2.8714 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8714 2023/06/05 09:13:38 - mmengine - INFO - Epoch(train) [89][ 160/2569] lr: 4.0000e-02 eta: 11:44:41 time: 0.2794 data_time: 0.0074 memory: 5828 grad_norm: 3.1514 loss: 2.5209 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5209 2023/06/05 09:13:44 - mmengine - INFO - Epoch(train) [89][ 180/2569] lr: 4.0000e-02 eta: 11:44:36 time: 0.2704 data_time: 0.0072 memory: 5828 grad_norm: 3.1371 loss: 2.5236 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5236 2023/06/05 09:13:49 - mmengine - INFO - Epoch(train) [89][ 200/2569] lr: 4.0000e-02 eta: 11:44:30 time: 0.2652 data_time: 0.0076 memory: 5828 grad_norm: 3.2014 loss: 2.3847 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3847 2023/06/05 09:13:54 - mmengine - INFO - Epoch(train) [89][ 220/2569] lr: 4.0000e-02 eta: 11:44:25 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 3.1542 loss: 2.5012 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5012 2023/06/05 09:14:00 - mmengine - INFO - Epoch(train) [89][ 240/2569] lr: 4.0000e-02 eta: 11:44:20 time: 0.2706 data_time: 0.0074 memory: 5828 grad_norm: 3.1433 loss: 2.4250 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4250 2023/06/05 09:14:05 - mmengine - INFO - Epoch(train) [89][ 260/2569] lr: 4.0000e-02 eta: 11:44:14 time: 0.2660 data_time: 0.0074 memory: 5828 grad_norm: 3.1173 loss: 2.5579 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5579 2023/06/05 09:14:10 - mmengine - INFO - Epoch(train) [89][ 280/2569] lr: 4.0000e-02 eta: 11:44:09 time: 0.2703 data_time: 0.0074 memory: 5828 grad_norm: 3.1598 loss: 2.3576 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.3576 2023/06/05 09:14:16 - mmengine - INFO - Epoch(train) [89][ 300/2569] lr: 4.0000e-02 eta: 11:44:04 time: 0.2650 data_time: 0.0073 memory: 5828 grad_norm: 3.1989 loss: 2.4138 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4138 2023/06/05 09:14:21 - mmengine - INFO - Epoch(train) [89][ 320/2569] lr: 4.0000e-02 eta: 11:43:59 time: 0.2707 data_time: 0.0075 memory: 5828 grad_norm: 3.1621 loss: 2.2498 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.2498 2023/06/05 09:14:26 - mmengine - INFO - Epoch(train) [89][ 340/2569] lr: 4.0000e-02 eta: 11:43:53 time: 0.2633 data_time: 0.0079 memory: 5828 grad_norm: 3.1092 loss: 2.3440 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3440 2023/06/05 09:14:32 - mmengine - INFO - Epoch(train) [89][ 360/2569] lr: 4.0000e-02 eta: 11:43:48 time: 0.2764 data_time: 0.0073 memory: 5828 grad_norm: 3.1288 loss: 2.7199 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7199 2023/06/05 09:14:37 - mmengine - INFO - Epoch(train) [89][ 380/2569] lr: 4.0000e-02 eta: 11:43:43 time: 0.2723 data_time: 0.0071 memory: 5828 grad_norm: 3.1160 loss: 2.6262 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6262 2023/06/05 09:14:43 - mmengine - INFO - Epoch(train) [89][ 400/2569] lr: 4.0000e-02 eta: 11:43:37 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 3.1409 loss: 2.8906 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8906 2023/06/05 09:14:48 - mmengine - INFO - Epoch(train) [89][ 420/2569] lr: 4.0000e-02 eta: 11:43:32 time: 0.2621 data_time: 0.0071 memory: 5828 grad_norm: 3.0691 loss: 2.3729 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3729 2023/06/05 09:14:53 - mmengine - INFO - Epoch(train) [89][ 440/2569] lr: 4.0000e-02 eta: 11:43:27 time: 0.2768 data_time: 0.0072 memory: 5828 grad_norm: 3.0708 loss: 2.8225 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8225 2023/06/05 09:14:59 - mmengine - INFO - Epoch(train) [89][ 460/2569] lr: 4.0000e-02 eta: 11:43:22 time: 0.2744 data_time: 0.0071 memory: 5828 grad_norm: 3.1331 loss: 2.4821 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4821 2023/06/05 09:15:05 - mmengine - INFO - Epoch(train) [89][ 480/2569] lr: 4.0000e-02 eta: 11:43:17 time: 0.2806 data_time: 0.0072 memory: 5828 grad_norm: 3.1054 loss: 2.6100 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6100 2023/06/05 09:15:10 - mmengine - INFO - Epoch(train) [89][ 500/2569] lr: 4.0000e-02 eta: 11:43:11 time: 0.2652 data_time: 0.0080 memory: 5828 grad_norm: 3.1838 loss: 2.5707 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5707 2023/06/05 09:15:15 - mmengine - INFO - Epoch(train) [89][ 520/2569] lr: 4.0000e-02 eta: 11:43:06 time: 0.2712 data_time: 0.0072 memory: 5828 grad_norm: 3.1263 loss: 2.5404 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5404 2023/06/05 09:15:21 - mmengine - INFO - Epoch(train) [89][ 540/2569] lr: 4.0000e-02 eta: 11:43:01 time: 0.2634 data_time: 0.0076 memory: 5828 grad_norm: 3.1424 loss: 2.5228 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5228 2023/06/05 09:15:26 - mmengine - INFO - Epoch(train) [89][ 560/2569] lr: 4.0000e-02 eta: 11:42:56 time: 0.2789 data_time: 0.0078 memory: 5828 grad_norm: 3.1282 loss: 2.6270 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6270 2023/06/05 09:15:32 - mmengine - INFO - Epoch(train) [89][ 580/2569] lr: 4.0000e-02 eta: 11:42:50 time: 0.2720 data_time: 0.0070 memory: 5828 grad_norm: 3.1755 loss: 2.3475 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.3475 2023/06/05 09:15:37 - mmengine - INFO - Epoch(train) [89][ 600/2569] lr: 4.0000e-02 eta: 11:42:45 time: 0.2608 data_time: 0.0076 memory: 5828 grad_norm: 3.1134 loss: 2.5604 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5604 2023/06/05 09:15:42 - mmengine - INFO - Epoch(train) [89][ 620/2569] lr: 4.0000e-02 eta: 11:42:40 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 3.1786 loss: 2.5201 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5201 2023/06/05 09:15:48 - mmengine - INFO - Epoch(train) [89][ 640/2569] lr: 4.0000e-02 eta: 11:42:34 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 3.1281 loss: 2.6822 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6822 2023/06/05 09:15:53 - mmengine - INFO - Epoch(train) [89][ 660/2569] lr: 4.0000e-02 eta: 11:42:29 time: 0.2686 data_time: 0.0070 memory: 5828 grad_norm: 3.1112 loss: 2.6850 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6850 2023/06/05 09:15:58 - mmengine - INFO - Epoch(train) [89][ 680/2569] lr: 4.0000e-02 eta: 11:42:24 time: 0.2593 data_time: 0.0073 memory: 5828 grad_norm: 3.1164 loss: 2.6609 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6609 2023/06/05 09:16:03 - mmengine - INFO - Epoch(train) [89][ 700/2569] lr: 4.0000e-02 eta: 11:42:18 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 3.1770 loss: 2.8405 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8405 2023/06/05 09:16:09 - mmengine - INFO - Epoch(train) [89][ 720/2569] lr: 4.0000e-02 eta: 11:42:13 time: 0.2652 data_time: 0.0074 memory: 5828 grad_norm: 3.0867 loss: 2.4164 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4164 2023/06/05 09:16:14 - mmengine - INFO - Epoch(train) [89][ 740/2569] lr: 4.0000e-02 eta: 11:42:08 time: 0.2597 data_time: 0.0075 memory: 5828 grad_norm: 3.2129 loss: 2.5554 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5554 2023/06/05 09:16:19 - mmengine - INFO - Epoch(train) [89][ 760/2569] lr: 4.0000e-02 eta: 11:42:02 time: 0.2655 data_time: 0.0072 memory: 5828 grad_norm: 3.0589 loss: 2.4177 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4177 2023/06/05 09:16:25 - mmengine - INFO - Epoch(train) [89][ 780/2569] lr: 4.0000e-02 eta: 11:41:57 time: 0.2742 data_time: 0.0070 memory: 5828 grad_norm: 3.2102 loss: 2.9638 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9638 2023/06/05 09:16:30 - mmengine - INFO - Epoch(train) [89][ 800/2569] lr: 4.0000e-02 eta: 11:41:52 time: 0.2656 data_time: 0.0072 memory: 5828 grad_norm: 3.0628 loss: 2.5306 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5306 2023/06/05 09:16:35 - mmengine - INFO - Epoch(train) [89][ 820/2569] lr: 4.0000e-02 eta: 11:41:47 time: 0.2659 data_time: 0.0073 memory: 5828 grad_norm: 3.0882 loss: 2.1646 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1646 2023/06/05 09:16:41 - mmengine - INFO - Epoch(train) [89][ 840/2569] lr: 4.0000e-02 eta: 11:41:41 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 3.1586 loss: 2.2084 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2084 2023/06/05 09:16:46 - mmengine - INFO - Epoch(train) [89][ 860/2569] lr: 4.0000e-02 eta: 11:41:36 time: 0.2600 data_time: 0.0073 memory: 5828 grad_norm: 3.1446 loss: 2.7331 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7331 2023/06/05 09:16:51 - mmengine - INFO - Epoch(train) [89][ 880/2569] lr: 4.0000e-02 eta: 11:41:31 time: 0.2698 data_time: 0.0076 memory: 5828 grad_norm: 3.1509 loss: 2.4035 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4035 2023/06/05 09:16:57 - mmengine - INFO - Epoch(train) [89][ 900/2569] lr: 4.0000e-02 eta: 11:41:25 time: 0.2639 data_time: 0.0072 memory: 5828 grad_norm: 3.1151 loss: 2.5158 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5158 2023/06/05 09:17:02 - mmengine - INFO - Epoch(train) [89][ 920/2569] lr: 4.0000e-02 eta: 11:41:20 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 3.1336 loss: 2.4053 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4053 2023/06/05 09:17:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:17:07 - mmengine - INFO - Epoch(train) [89][ 940/2569] lr: 4.0000e-02 eta: 11:41:15 time: 0.2740 data_time: 0.0077 memory: 5828 grad_norm: 3.1003 loss: 2.5160 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5160 2023/06/05 09:17:13 - mmengine - INFO - Epoch(train) [89][ 960/2569] lr: 4.0000e-02 eta: 11:41:09 time: 0.2607 data_time: 0.0076 memory: 5828 grad_norm: 3.1167 loss: 2.3200 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3200 2023/06/05 09:17:18 - mmengine - INFO - Epoch(train) [89][ 980/2569] lr: 4.0000e-02 eta: 11:41:04 time: 0.2652 data_time: 0.0076 memory: 5828 grad_norm: 3.1228 loss: 2.4885 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4885 2023/06/05 09:17:23 - mmengine - INFO - Epoch(train) [89][1000/2569] lr: 4.0000e-02 eta: 11:40:59 time: 0.2595 data_time: 0.0077 memory: 5828 grad_norm: 3.0954 loss: 2.6194 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6194 2023/06/05 09:17:29 - mmengine - INFO - Epoch(train) [89][1020/2569] lr: 4.0000e-02 eta: 11:40:53 time: 0.2688 data_time: 0.0071 memory: 5828 grad_norm: 3.1584 loss: 2.3640 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3640 2023/06/05 09:17:34 - mmengine - INFO - Epoch(train) [89][1040/2569] lr: 4.0000e-02 eta: 11:40:48 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 3.1392 loss: 2.1710 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1710 2023/06/05 09:17:39 - mmengine - INFO - Epoch(train) [89][1060/2569] lr: 4.0000e-02 eta: 11:40:43 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 3.1311 loss: 2.5055 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5055 2023/06/05 09:17:45 - mmengine - INFO - Epoch(train) [89][1080/2569] lr: 4.0000e-02 eta: 11:40:37 time: 0.2658 data_time: 0.0073 memory: 5828 grad_norm: 3.1001 loss: 2.7119 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7119 2023/06/05 09:17:50 - mmengine - INFO - Epoch(train) [89][1100/2569] lr: 4.0000e-02 eta: 11:40:32 time: 0.2677 data_time: 0.0075 memory: 5828 grad_norm: 3.1942 loss: 2.2865 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2865 2023/06/05 09:17:55 - mmengine - INFO - Epoch(train) [89][1120/2569] lr: 4.0000e-02 eta: 11:40:27 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.1376 loss: 2.4951 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4951 2023/06/05 09:18:01 - mmengine - INFO - Epoch(train) [89][1140/2569] lr: 4.0000e-02 eta: 11:40:22 time: 0.2675 data_time: 0.0078 memory: 5828 grad_norm: 3.1758 loss: 2.2901 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2901 2023/06/05 09:18:06 - mmengine - INFO - Epoch(train) [89][1160/2569] lr: 4.0000e-02 eta: 11:40:16 time: 0.2645 data_time: 0.0075 memory: 5828 grad_norm: 3.1553 loss: 2.3235 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3235 2023/06/05 09:18:11 - mmengine - INFO - Epoch(train) [89][1180/2569] lr: 4.0000e-02 eta: 11:40:11 time: 0.2629 data_time: 0.0071 memory: 5828 grad_norm: 3.1441 loss: 2.6532 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6532 2023/06/05 09:18:16 - mmengine - INFO - Epoch(train) [89][1200/2569] lr: 4.0000e-02 eta: 11:40:05 time: 0.2596 data_time: 0.0073 memory: 5828 grad_norm: 3.1561 loss: 2.8092 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8092 2023/06/05 09:18:22 - mmengine - INFO - Epoch(train) [89][1220/2569] lr: 4.0000e-02 eta: 11:40:00 time: 0.2596 data_time: 0.0071 memory: 5828 grad_norm: 3.1038 loss: 2.4182 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4182 2023/06/05 09:18:27 - mmengine - INFO - Epoch(train) [89][1240/2569] lr: 4.0000e-02 eta: 11:39:55 time: 0.2594 data_time: 0.0073 memory: 5828 grad_norm: 3.0806 loss: 2.5006 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5006 2023/06/05 09:18:32 - mmengine - INFO - Epoch(train) [89][1260/2569] lr: 4.0000e-02 eta: 11:39:49 time: 0.2727 data_time: 0.0074 memory: 5828 grad_norm: 3.1648 loss: 2.2632 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2632 2023/06/05 09:18:38 - mmengine - INFO - Epoch(train) [89][1280/2569] lr: 4.0000e-02 eta: 11:39:44 time: 0.2725 data_time: 0.0074 memory: 5828 grad_norm: 3.1387 loss: 2.1901 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1901 2023/06/05 09:18:43 - mmengine - INFO - Epoch(train) [89][1300/2569] lr: 4.0000e-02 eta: 11:39:39 time: 0.2623 data_time: 0.0076 memory: 5828 grad_norm: 3.1053 loss: 2.4737 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4737 2023/06/05 09:18:48 - mmengine - INFO - Epoch(train) [89][1320/2569] lr: 4.0000e-02 eta: 11:39:34 time: 0.2680 data_time: 0.0078 memory: 5828 grad_norm: 3.1256 loss: 2.2252 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2252 2023/06/05 09:18:54 - mmengine - INFO - Epoch(train) [89][1340/2569] lr: 4.0000e-02 eta: 11:39:28 time: 0.2656 data_time: 0.0080 memory: 5828 grad_norm: 3.1160 loss: 2.4910 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4910 2023/06/05 09:18:59 - mmengine - INFO - Epoch(train) [89][1360/2569] lr: 4.0000e-02 eta: 11:39:23 time: 0.2676 data_time: 0.0075 memory: 5828 grad_norm: 3.1616 loss: 2.6258 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6258 2023/06/05 09:19:04 - mmengine - INFO - Epoch(train) [89][1380/2569] lr: 4.0000e-02 eta: 11:39:18 time: 0.2660 data_time: 0.0074 memory: 5828 grad_norm: 3.1256 loss: 2.3471 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3471 2023/06/05 09:19:10 - mmengine - INFO - Epoch(train) [89][1400/2569] lr: 4.0000e-02 eta: 11:39:12 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 3.1244 loss: 2.9824 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9824 2023/06/05 09:19:15 - mmengine - INFO - Epoch(train) [89][1420/2569] lr: 4.0000e-02 eta: 11:39:07 time: 0.2683 data_time: 0.0069 memory: 5828 grad_norm: 3.1557 loss: 2.6479 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6479 2023/06/05 09:19:20 - mmengine - INFO - Epoch(train) [89][1440/2569] lr: 4.0000e-02 eta: 11:39:02 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 3.1750 loss: 2.3576 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3576 2023/06/05 09:19:26 - mmengine - INFO - Epoch(train) [89][1460/2569] lr: 4.0000e-02 eta: 11:38:57 time: 0.2699 data_time: 0.0076 memory: 5828 grad_norm: 3.1169 loss: 2.6002 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6002 2023/06/05 09:19:31 - mmengine - INFO - Epoch(train) [89][1480/2569] lr: 4.0000e-02 eta: 11:38:51 time: 0.2624 data_time: 0.0074 memory: 5828 grad_norm: 3.1955 loss: 2.2157 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2157 2023/06/05 09:19:37 - mmengine - INFO - Epoch(train) [89][1500/2569] lr: 4.0000e-02 eta: 11:38:46 time: 0.2705 data_time: 0.0075 memory: 5828 grad_norm: 3.1682 loss: 2.5498 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5498 2023/06/05 09:19:42 - mmengine - INFO - Epoch(train) [89][1520/2569] lr: 4.0000e-02 eta: 11:38:41 time: 0.2605 data_time: 0.0072 memory: 5828 grad_norm: 3.1576 loss: 2.4222 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4222 2023/06/05 09:19:47 - mmengine - INFO - Epoch(train) [89][1540/2569] lr: 4.0000e-02 eta: 11:38:35 time: 0.2643 data_time: 0.0076 memory: 5828 grad_norm: 3.0914 loss: 2.4960 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4960 2023/06/05 09:19:52 - mmengine - INFO - Epoch(train) [89][1560/2569] lr: 4.0000e-02 eta: 11:38:30 time: 0.2633 data_time: 0.0076 memory: 5828 grad_norm: 3.1132 loss: 2.7049 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7049 2023/06/05 09:19:58 - mmengine - INFO - Epoch(train) [89][1580/2569] lr: 4.0000e-02 eta: 11:38:25 time: 0.2660 data_time: 0.0081 memory: 5828 grad_norm: 3.1248 loss: 2.5781 top1_acc: 0.0000 top5_acc: 0.7500 loss_cls: 2.5781 2023/06/05 09:20:03 - mmengine - INFO - Epoch(train) [89][1600/2569] lr: 4.0000e-02 eta: 11:38:19 time: 0.2715 data_time: 0.0075 memory: 5828 grad_norm: 3.1467 loss: 2.6644 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6644 2023/06/05 09:20:09 - mmengine - INFO - Epoch(train) [89][1620/2569] lr: 4.0000e-02 eta: 11:38:14 time: 0.2763 data_time: 0.0072 memory: 5828 grad_norm: 3.2175 loss: 2.5786 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5786 2023/06/05 09:20:14 - mmengine - INFO - Epoch(train) [89][1640/2569] lr: 4.0000e-02 eta: 11:38:09 time: 0.2763 data_time: 0.0072 memory: 5828 grad_norm: 3.1420 loss: 2.1759 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1759 2023/06/05 09:20:20 - mmengine - INFO - Epoch(train) [89][1660/2569] lr: 4.0000e-02 eta: 11:38:04 time: 0.2707 data_time: 0.0072 memory: 5828 grad_norm: 3.1222 loss: 2.5419 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5419 2023/06/05 09:20:25 - mmengine - INFO - Epoch(train) [89][1680/2569] lr: 4.0000e-02 eta: 11:37:58 time: 0.2631 data_time: 0.0071 memory: 5828 grad_norm: 3.1226 loss: 2.4353 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4353 2023/06/05 09:20:30 - mmengine - INFO - Epoch(train) [89][1700/2569] lr: 4.0000e-02 eta: 11:37:53 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 3.1376 loss: 2.4396 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4396 2023/06/05 09:20:36 - mmengine - INFO - Epoch(train) [89][1720/2569] lr: 4.0000e-02 eta: 11:37:48 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 3.0897 loss: 2.6967 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6967 2023/06/05 09:20:41 - mmengine - INFO - Epoch(train) [89][1740/2569] lr: 4.0000e-02 eta: 11:37:43 time: 0.2703 data_time: 0.0072 memory: 5828 grad_norm: 3.0885 loss: 2.5167 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5167 2023/06/05 09:20:46 - mmengine - INFO - Epoch(train) [89][1760/2569] lr: 4.0000e-02 eta: 11:37:37 time: 0.2705 data_time: 0.0076 memory: 5828 grad_norm: 3.1179 loss: 2.3901 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.3901 2023/06/05 09:20:52 - mmengine - INFO - Epoch(train) [89][1780/2569] lr: 4.0000e-02 eta: 11:37:32 time: 0.2655 data_time: 0.0077 memory: 5828 grad_norm: 3.1482 loss: 2.4457 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4457 2023/06/05 09:20:57 - mmengine - INFO - Epoch(train) [89][1800/2569] lr: 4.0000e-02 eta: 11:37:27 time: 0.2699 data_time: 0.0077 memory: 5828 grad_norm: 3.0957 loss: 2.8951 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.8951 2023/06/05 09:21:02 - mmengine - INFO - Epoch(train) [89][1820/2569] lr: 4.0000e-02 eta: 11:37:21 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 3.1371 loss: 2.3307 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3307 2023/06/05 09:21:08 - mmengine - INFO - Epoch(train) [89][1840/2569] lr: 4.0000e-02 eta: 11:37:16 time: 0.2693 data_time: 0.0075 memory: 5828 grad_norm: 3.1118 loss: 2.5393 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5393 2023/06/05 09:21:13 - mmengine - INFO - Epoch(train) [89][1860/2569] lr: 4.0000e-02 eta: 11:37:11 time: 0.2700 data_time: 0.0082 memory: 5828 grad_norm: 3.1111 loss: 2.4993 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4993 2023/06/05 09:21:18 - mmengine - INFO - Epoch(train) [89][1880/2569] lr: 4.0000e-02 eta: 11:37:06 time: 0.2644 data_time: 0.0075 memory: 5828 grad_norm: 3.1769 loss: 2.5539 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5539 2023/06/05 09:21:24 - mmengine - INFO - Epoch(train) [89][1900/2569] lr: 4.0000e-02 eta: 11:37:00 time: 0.2663 data_time: 0.0082 memory: 5828 grad_norm: 3.1474 loss: 2.6141 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6141 2023/06/05 09:21:29 - mmengine - INFO - Epoch(train) [89][1920/2569] lr: 4.0000e-02 eta: 11:36:55 time: 0.2604 data_time: 0.0070 memory: 5828 grad_norm: 3.1725 loss: 2.4361 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4361 2023/06/05 09:21:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:21:34 - mmengine - INFO - Epoch(train) [89][1940/2569] lr: 4.0000e-02 eta: 11:36:49 time: 0.2599 data_time: 0.0077 memory: 5828 grad_norm: 3.1476 loss: 2.6198 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6198 2023/06/05 09:21:40 - mmengine - INFO - Epoch(train) [89][1960/2569] lr: 4.0000e-02 eta: 11:36:44 time: 0.2763 data_time: 0.0075 memory: 5828 grad_norm: 3.2051 loss: 2.5007 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5007 2023/06/05 09:21:45 - mmengine - INFO - Epoch(train) [89][1980/2569] lr: 4.0000e-02 eta: 11:36:39 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 3.1021 loss: 2.6179 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6179 2023/06/05 09:21:50 - mmengine - INFO - Epoch(train) [89][2000/2569] lr: 4.0000e-02 eta: 11:36:34 time: 0.2697 data_time: 0.0077 memory: 5828 grad_norm: 3.0742 loss: 2.4305 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4305 2023/06/05 09:21:56 - mmengine - INFO - Epoch(train) [89][2020/2569] lr: 4.0000e-02 eta: 11:36:28 time: 0.2656 data_time: 0.0078 memory: 5828 grad_norm: 3.1261 loss: 2.5317 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5317 2023/06/05 09:22:01 - mmengine - INFO - Epoch(train) [89][2040/2569] lr: 4.0000e-02 eta: 11:36:23 time: 0.2693 data_time: 0.0083 memory: 5828 grad_norm: 3.1140 loss: 2.6859 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6859 2023/06/05 09:22:07 - mmengine - INFO - Epoch(train) [89][2060/2569] lr: 4.0000e-02 eta: 11:36:18 time: 0.2675 data_time: 0.0076 memory: 5828 grad_norm: 3.1115 loss: 2.6117 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6117 2023/06/05 09:22:12 - mmengine - INFO - Epoch(train) [89][2080/2569] lr: 4.0000e-02 eta: 11:36:12 time: 0.2667 data_time: 0.0076 memory: 5828 grad_norm: 3.1366 loss: 2.3949 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.3949 2023/06/05 09:22:17 - mmengine - INFO - Epoch(train) [89][2100/2569] lr: 4.0000e-02 eta: 11:36:07 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 3.1193 loss: 2.4023 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4023 2023/06/05 09:22:22 - mmengine - INFO - Epoch(train) [89][2120/2569] lr: 4.0000e-02 eta: 11:36:02 time: 0.2612 data_time: 0.0078 memory: 5828 grad_norm: 3.1707 loss: 2.3612 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3612 2023/06/05 09:22:28 - mmengine - INFO - Epoch(train) [89][2140/2569] lr: 4.0000e-02 eta: 11:35:57 time: 0.2740 data_time: 0.0069 memory: 5828 grad_norm: 3.0665 loss: 2.3888 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3888 2023/06/05 09:22:33 - mmengine - INFO - Epoch(train) [89][2160/2569] lr: 4.0000e-02 eta: 11:35:51 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 3.1061 loss: 2.3376 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3376 2023/06/05 09:22:39 - mmengine - INFO - Epoch(train) [89][2180/2569] lr: 4.0000e-02 eta: 11:35:46 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 3.0547 loss: 2.7390 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7390 2023/06/05 09:22:44 - mmengine - INFO - Epoch(train) [89][2200/2569] lr: 4.0000e-02 eta: 11:35:41 time: 0.2605 data_time: 0.0088 memory: 5828 grad_norm: 3.1778 loss: 2.5971 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5971 2023/06/05 09:22:49 - mmengine - INFO - Epoch(train) [89][2220/2569] lr: 4.0000e-02 eta: 11:35:35 time: 0.2613 data_time: 0.0071 memory: 5828 grad_norm: 3.0985 loss: 2.3166 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3166 2023/06/05 09:22:54 - mmengine - INFO - Epoch(train) [89][2240/2569] lr: 4.0000e-02 eta: 11:35:30 time: 0.2632 data_time: 0.0079 memory: 5828 grad_norm: 3.1784 loss: 2.4871 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4871 2023/06/05 09:23:00 - mmengine - INFO - Epoch(train) [89][2260/2569] lr: 4.0000e-02 eta: 11:35:25 time: 0.2617 data_time: 0.0077 memory: 5828 grad_norm: 3.0993 loss: 2.5661 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5661 2023/06/05 09:23:05 - mmengine - INFO - Epoch(train) [89][2280/2569] lr: 4.0000e-02 eta: 11:35:19 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 3.1488 loss: 2.5674 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.5674 2023/06/05 09:23:10 - mmengine - INFO - Epoch(train) [89][2300/2569] lr: 4.0000e-02 eta: 11:35:14 time: 0.2578 data_time: 0.0072 memory: 5828 grad_norm: 3.1164 loss: 2.5537 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5537 2023/06/05 09:23:15 - mmengine - INFO - Epoch(train) [89][2320/2569] lr: 4.0000e-02 eta: 11:35:08 time: 0.2598 data_time: 0.0075 memory: 5828 grad_norm: 3.0977 loss: 2.8297 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8297 2023/06/05 09:23:21 - mmengine - INFO - Epoch(train) [89][2340/2569] lr: 4.0000e-02 eta: 11:35:03 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 3.1457 loss: 2.8192 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8192 2023/06/05 09:23:26 - mmengine - INFO - Epoch(train) [89][2360/2569] lr: 4.0000e-02 eta: 11:34:58 time: 0.2692 data_time: 0.0076 memory: 5828 grad_norm: 3.1428 loss: 2.4905 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4905 2023/06/05 09:23:31 - mmengine - INFO - Epoch(train) [89][2380/2569] lr: 4.0000e-02 eta: 11:34:52 time: 0.2657 data_time: 0.0074 memory: 5828 grad_norm: 3.1593 loss: 2.5111 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5111 2023/06/05 09:23:37 - mmengine - INFO - Epoch(train) [89][2400/2569] lr: 4.0000e-02 eta: 11:34:47 time: 0.2618 data_time: 0.0071 memory: 5828 grad_norm: 3.1246 loss: 2.9932 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.9932 2023/06/05 09:23:42 - mmengine - INFO - Epoch(train) [89][2420/2569] lr: 4.0000e-02 eta: 11:34:42 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 3.2156 loss: 2.5291 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5291 2023/06/05 09:23:47 - mmengine - INFO - Epoch(train) [89][2440/2569] lr: 4.0000e-02 eta: 11:34:37 time: 0.2785 data_time: 0.0070 memory: 5828 grad_norm: 3.1198 loss: 2.5536 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5536 2023/06/05 09:23:53 - mmengine - INFO - Epoch(train) [89][2460/2569] lr: 4.0000e-02 eta: 11:34:31 time: 0.2639 data_time: 0.0069 memory: 5828 grad_norm: 3.1188 loss: 2.6541 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6541 2023/06/05 09:23:58 - mmengine - INFO - Epoch(train) [89][2480/2569] lr: 4.0000e-02 eta: 11:34:26 time: 0.2709 data_time: 0.0072 memory: 5828 grad_norm: 3.1640 loss: 2.6178 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6178 2023/06/05 09:24:04 - mmengine - INFO - Epoch(train) [89][2500/2569] lr: 4.0000e-02 eta: 11:34:21 time: 0.2717 data_time: 0.0072 memory: 5828 grad_norm: 3.1231 loss: 2.7045 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7045 2023/06/05 09:24:09 - mmengine - INFO - Epoch(train) [89][2520/2569] lr: 4.0000e-02 eta: 11:34:16 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 3.1267 loss: 2.7620 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.7620 2023/06/05 09:24:14 - mmengine - INFO - Epoch(train) [89][2540/2569] lr: 4.0000e-02 eta: 11:34:10 time: 0.2619 data_time: 0.0075 memory: 5828 grad_norm: 3.0733 loss: 2.3380 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3380 2023/06/05 09:24:19 - mmengine - INFO - Epoch(train) [89][2560/2569] lr: 4.0000e-02 eta: 11:34:05 time: 0.2577 data_time: 0.0075 memory: 5828 grad_norm: 3.1400 loss: 2.4733 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4733 2023/06/05 09:24:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:24:22 - mmengine - INFO - Epoch(train) [89][2569/2569] lr: 4.0000e-02 eta: 11:34:02 time: 0.2503 data_time: 0.0068 memory: 5828 grad_norm: 3.1718 loss: 2.3351 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.3351 2023/06/05 09:24:28 - mmengine - INFO - Epoch(train) [90][ 20/2569] lr: 4.0000e-02 eta: 11:33:58 time: 0.3406 data_time: 0.0468 memory: 5828 grad_norm: 3.1667 loss: 2.5624 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5624 2023/06/05 09:24:34 - mmengine - INFO - Epoch(train) [90][ 40/2569] lr: 4.0000e-02 eta: 11:33:53 time: 0.2746 data_time: 0.0089 memory: 5828 grad_norm: 3.1747 loss: 2.2263 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2263 2023/06/05 09:24:39 - mmengine - INFO - Epoch(train) [90][ 60/2569] lr: 4.0000e-02 eta: 11:33:47 time: 0.2676 data_time: 0.0083 memory: 5828 grad_norm: 3.1261 loss: 2.6642 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6642 2023/06/05 09:24:45 - mmengine - INFO - Epoch(train) [90][ 80/2569] lr: 4.0000e-02 eta: 11:33:42 time: 0.2661 data_time: 0.0080 memory: 5828 grad_norm: 3.1324 loss: 2.3917 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3917 2023/06/05 09:24:50 - mmengine - INFO - Epoch(train) [90][ 100/2569] lr: 4.0000e-02 eta: 11:33:37 time: 0.2777 data_time: 0.0079 memory: 5828 grad_norm: 3.1105 loss: 2.5158 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5158 2023/06/05 09:24:55 - mmengine - INFO - Epoch(train) [90][ 120/2569] lr: 4.0000e-02 eta: 11:33:32 time: 0.2655 data_time: 0.0074 memory: 5828 grad_norm: 3.1821 loss: 2.5087 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5087 2023/06/05 09:25:01 - mmengine - INFO - Epoch(train) [90][ 140/2569] lr: 4.0000e-02 eta: 11:33:27 time: 0.2823 data_time: 0.0074 memory: 5828 grad_norm: 3.1110 loss: 2.4419 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4419 2023/06/05 09:25:06 - mmengine - INFO - Epoch(train) [90][ 160/2569] lr: 4.0000e-02 eta: 11:33:21 time: 0.2582 data_time: 0.0076 memory: 5828 grad_norm: 3.0986 loss: 2.4058 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4058 2023/06/05 09:25:12 - mmengine - INFO - Epoch(train) [90][ 180/2569] lr: 4.0000e-02 eta: 11:33:16 time: 0.2701 data_time: 0.0074 memory: 5828 grad_norm: 3.1225 loss: 2.4109 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4109 2023/06/05 09:25:17 - mmengine - INFO - Epoch(train) [90][ 200/2569] lr: 4.0000e-02 eta: 11:33:11 time: 0.2599 data_time: 0.0076 memory: 5828 grad_norm: 3.1392 loss: 2.5123 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5123 2023/06/05 09:25:22 - mmengine - INFO - Epoch(train) [90][ 220/2569] lr: 4.0000e-02 eta: 11:33:05 time: 0.2669 data_time: 0.0075 memory: 5828 grad_norm: 3.1403 loss: 2.3149 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3149 2023/06/05 09:25:28 - mmengine - INFO - Epoch(train) [90][ 240/2569] lr: 4.0000e-02 eta: 11:33:00 time: 0.2669 data_time: 0.0083 memory: 5828 grad_norm: 3.1648 loss: 2.2725 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2725 2023/06/05 09:25:33 - mmengine - INFO - Epoch(train) [90][ 260/2569] lr: 4.0000e-02 eta: 11:32:55 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 3.2203 loss: 2.6341 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6341 2023/06/05 09:25:38 - mmengine - INFO - Epoch(train) [90][ 280/2569] lr: 4.0000e-02 eta: 11:32:49 time: 0.2609 data_time: 0.0073 memory: 5828 grad_norm: 3.0908 loss: 2.7926 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7926 2023/06/05 09:25:44 - mmengine - INFO - Epoch(train) [90][ 300/2569] lr: 4.0000e-02 eta: 11:32:44 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 3.0971 loss: 2.3693 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3693 2023/06/05 09:25:49 - mmengine - INFO - Epoch(train) [90][ 320/2569] lr: 4.0000e-02 eta: 11:32:39 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 3.1847 loss: 2.5698 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5698 2023/06/05 09:25:54 - mmengine - INFO - Epoch(train) [90][ 340/2569] lr: 4.0000e-02 eta: 11:32:33 time: 0.2691 data_time: 0.0071 memory: 5828 grad_norm: 3.1119 loss: 2.6202 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6202 2023/06/05 09:25:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:26:00 - mmengine - INFO - Epoch(train) [90][ 360/2569] lr: 4.0000e-02 eta: 11:32:28 time: 0.2693 data_time: 0.0078 memory: 5828 grad_norm: 3.1321 loss: 2.4553 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4553 2023/06/05 09:26:05 - mmengine - INFO - Epoch(train) [90][ 380/2569] lr: 4.0000e-02 eta: 11:32:23 time: 0.2663 data_time: 0.0085 memory: 5828 grad_norm: 3.0847 loss: 2.2540 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2540 2023/06/05 09:26:10 - mmengine - INFO - Epoch(train) [90][ 400/2569] lr: 4.0000e-02 eta: 11:32:18 time: 0.2717 data_time: 0.0083 memory: 5828 grad_norm: 3.1739 loss: 2.4226 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4226 2023/06/05 09:26:16 - mmengine - INFO - Epoch(train) [90][ 420/2569] lr: 4.0000e-02 eta: 11:32:12 time: 0.2594 data_time: 0.0073 memory: 5828 grad_norm: 3.1112 loss: 2.3759 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3759 2023/06/05 09:26:21 - mmengine - INFO - Epoch(train) [90][ 440/2569] lr: 4.0000e-02 eta: 11:32:07 time: 0.2677 data_time: 0.0078 memory: 5828 grad_norm: 3.1267 loss: 2.5811 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5811 2023/06/05 09:26:26 - mmengine - INFO - Epoch(train) [90][ 460/2569] lr: 4.0000e-02 eta: 11:32:01 time: 0.2604 data_time: 0.0073 memory: 5828 grad_norm: 3.1256 loss: 2.7073 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7073 2023/06/05 09:26:32 - mmengine - INFO - Epoch(train) [90][ 480/2569] lr: 4.0000e-02 eta: 11:31:56 time: 0.2700 data_time: 0.0073 memory: 5828 grad_norm: 3.1407 loss: 2.5272 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5272 2023/06/05 09:26:37 - mmengine - INFO - Epoch(train) [90][ 500/2569] lr: 4.0000e-02 eta: 11:31:51 time: 0.2677 data_time: 0.0079 memory: 5828 grad_norm: 3.1564 loss: 2.0666 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0666 2023/06/05 09:26:42 - mmengine - INFO - Epoch(train) [90][ 520/2569] lr: 4.0000e-02 eta: 11:31:46 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 3.1250 loss: 2.3847 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3847 2023/06/05 09:26:48 - mmengine - INFO - Epoch(train) [90][ 540/2569] lr: 4.0000e-02 eta: 11:31:40 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 3.1416 loss: 2.1240 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1240 2023/06/05 09:26:53 - mmengine - INFO - Epoch(train) [90][ 560/2569] lr: 4.0000e-02 eta: 11:31:35 time: 0.2714 data_time: 0.0072 memory: 5828 grad_norm: 3.1379 loss: 2.9048 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.9048 2023/06/05 09:26:58 - mmengine - INFO - Epoch(train) [90][ 580/2569] lr: 4.0000e-02 eta: 11:31:30 time: 0.2596 data_time: 0.0074 memory: 5828 grad_norm: 3.1091 loss: 2.3867 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3867 2023/06/05 09:27:03 - mmengine - INFO - Epoch(train) [90][ 600/2569] lr: 4.0000e-02 eta: 11:31:24 time: 0.2605 data_time: 0.0074 memory: 5828 grad_norm: 3.1131 loss: 2.3651 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3651 2023/06/05 09:27:09 - mmengine - INFO - Epoch(train) [90][ 620/2569] lr: 4.0000e-02 eta: 11:31:19 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 3.1157 loss: 2.6246 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6246 2023/06/05 09:27:14 - mmengine - INFO - Epoch(train) [90][ 640/2569] lr: 4.0000e-02 eta: 11:31:14 time: 0.2662 data_time: 0.0074 memory: 5828 grad_norm: 3.1770 loss: 2.5488 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5488 2023/06/05 09:27:19 - mmengine - INFO - Epoch(train) [90][ 660/2569] lr: 4.0000e-02 eta: 11:31:08 time: 0.2723 data_time: 0.0072 memory: 5828 grad_norm: 3.0953 loss: 2.5051 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5051 2023/06/05 09:27:25 - mmengine - INFO - Epoch(train) [90][ 680/2569] lr: 4.0000e-02 eta: 11:31:03 time: 0.2747 data_time: 0.0074 memory: 5828 grad_norm: 3.1220 loss: 2.2731 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2731 2023/06/05 09:27:31 - mmengine - INFO - Epoch(train) [90][ 700/2569] lr: 4.0000e-02 eta: 11:30:58 time: 0.2761 data_time: 0.0084 memory: 5828 grad_norm: 3.1517 loss: 2.4649 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4649 2023/06/05 09:27:36 - mmengine - INFO - Epoch(train) [90][ 720/2569] lr: 4.0000e-02 eta: 11:30:53 time: 0.2649 data_time: 0.0075 memory: 5828 grad_norm: 3.0835 loss: 2.3633 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3633 2023/06/05 09:27:41 - mmengine - INFO - Epoch(train) [90][ 740/2569] lr: 4.0000e-02 eta: 11:30:47 time: 0.2694 data_time: 0.0076 memory: 5828 grad_norm: 3.0988 loss: 2.8354 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8354 2023/06/05 09:27:46 - mmengine - INFO - Epoch(train) [90][ 760/2569] lr: 4.0000e-02 eta: 11:30:42 time: 0.2589 data_time: 0.0077 memory: 5828 grad_norm: 3.2358 loss: 2.7458 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7458 2023/06/05 09:27:52 - mmengine - INFO - Epoch(train) [90][ 780/2569] lr: 4.0000e-02 eta: 11:30:37 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 3.0625 loss: 2.3903 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3903 2023/06/05 09:27:57 - mmengine - INFO - Epoch(train) [90][ 800/2569] lr: 4.0000e-02 eta: 11:30:31 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 3.1579 loss: 2.6243 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6243 2023/06/05 09:28:02 - mmengine - INFO - Epoch(train) [90][ 820/2569] lr: 4.0000e-02 eta: 11:30:26 time: 0.2592 data_time: 0.0087 memory: 5828 grad_norm: 3.1212 loss: 2.2879 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2879 2023/06/05 09:28:08 - mmengine - INFO - Epoch(train) [90][ 840/2569] lr: 4.0000e-02 eta: 11:30:21 time: 0.2584 data_time: 0.0078 memory: 5828 grad_norm: 3.1032 loss: 2.6116 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6116 2023/06/05 09:28:13 - mmengine - INFO - Epoch(train) [90][ 860/2569] lr: 4.0000e-02 eta: 11:30:15 time: 0.2604 data_time: 0.0082 memory: 5828 grad_norm: 3.0772 loss: 2.5170 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5170 2023/06/05 09:28:18 - mmengine - INFO - Epoch(train) [90][ 880/2569] lr: 4.0000e-02 eta: 11:30:10 time: 0.2610 data_time: 0.0076 memory: 5828 grad_norm: 3.0980 loss: 2.6347 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6347 2023/06/05 09:28:23 - mmengine - INFO - Epoch(train) [90][ 900/2569] lr: 4.0000e-02 eta: 11:30:04 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 3.1291 loss: 2.8299 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8299 2023/06/05 09:28:28 - mmengine - INFO - Epoch(train) [90][ 920/2569] lr: 4.0000e-02 eta: 11:29:59 time: 0.2600 data_time: 0.0078 memory: 5828 grad_norm: 3.1429 loss: 2.5764 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5764 2023/06/05 09:28:34 - mmengine - INFO - Epoch(train) [90][ 940/2569] lr: 4.0000e-02 eta: 11:29:54 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 3.0950 loss: 2.2171 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2171 2023/06/05 09:28:39 - mmengine - INFO - Epoch(train) [90][ 960/2569] lr: 4.0000e-02 eta: 11:29:48 time: 0.2636 data_time: 0.0070 memory: 5828 grad_norm: 3.0931 loss: 2.5415 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5415 2023/06/05 09:28:44 - mmengine - INFO - Epoch(train) [90][ 980/2569] lr: 4.0000e-02 eta: 11:29:43 time: 0.2647 data_time: 0.0076 memory: 5828 grad_norm: 3.1619 loss: 2.7316 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7316 2023/06/05 09:28:50 - mmengine - INFO - Epoch(train) [90][1000/2569] lr: 4.0000e-02 eta: 11:29:38 time: 0.2654 data_time: 0.0073 memory: 5828 grad_norm: 3.1790 loss: 2.6184 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6184 2023/06/05 09:28:55 - mmengine - INFO - Epoch(train) [90][1020/2569] lr: 4.0000e-02 eta: 11:29:32 time: 0.2602 data_time: 0.0076 memory: 5828 grad_norm: 3.1248 loss: 2.2627 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2627 2023/06/05 09:29:00 - mmengine - INFO - Epoch(train) [90][1040/2569] lr: 4.0000e-02 eta: 11:29:27 time: 0.2741 data_time: 0.0073 memory: 5828 grad_norm: 3.1411 loss: 2.3991 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3991 2023/06/05 09:29:06 - mmengine - INFO - Epoch(train) [90][1060/2569] lr: 4.0000e-02 eta: 11:29:22 time: 0.2647 data_time: 0.0071 memory: 5828 grad_norm: 3.1293 loss: 2.6480 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6480 2023/06/05 09:29:11 - mmengine - INFO - Epoch(train) [90][1080/2569] lr: 4.0000e-02 eta: 11:29:17 time: 0.2700 data_time: 0.0076 memory: 5828 grad_norm: 3.1222 loss: 2.2064 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2064 2023/06/05 09:29:16 - mmengine - INFO - Epoch(train) [90][1100/2569] lr: 4.0000e-02 eta: 11:29:11 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 3.1269 loss: 2.6566 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6566 2023/06/05 09:29:22 - mmengine - INFO - Epoch(train) [90][1120/2569] lr: 4.0000e-02 eta: 11:29:06 time: 0.2720 data_time: 0.0073 memory: 5828 grad_norm: 3.1532 loss: 2.4415 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4415 2023/06/05 09:29:27 - mmengine - INFO - Epoch(train) [90][1140/2569] lr: 4.0000e-02 eta: 11:29:01 time: 0.2601 data_time: 0.0075 memory: 5828 grad_norm: 3.1236 loss: 2.5759 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5759 2023/06/05 09:29:32 - mmengine - INFO - Epoch(train) [90][1160/2569] lr: 4.0000e-02 eta: 11:28:55 time: 0.2588 data_time: 0.0074 memory: 5828 grad_norm: 3.1939 loss: 2.2512 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2512 2023/06/05 09:29:38 - mmengine - INFO - Epoch(train) [90][1180/2569] lr: 4.0000e-02 eta: 11:28:50 time: 0.2673 data_time: 0.0072 memory: 5828 grad_norm: 3.1333 loss: 2.5531 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5531 2023/06/05 09:29:43 - mmengine - INFO - Epoch(train) [90][1200/2569] lr: 4.0000e-02 eta: 11:28:45 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 3.2011 loss: 2.7117 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7117 2023/06/05 09:29:48 - mmengine - INFO - Epoch(train) [90][1220/2569] lr: 4.0000e-02 eta: 11:28:39 time: 0.2704 data_time: 0.0070 memory: 5828 grad_norm: 3.1062 loss: 2.7725 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7725 2023/06/05 09:29:54 - mmengine - INFO - Epoch(train) [90][1240/2569] lr: 4.0000e-02 eta: 11:28:34 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 3.1717 loss: 2.3580 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3580 2023/06/05 09:29:59 - mmengine - INFO - Epoch(train) [90][1260/2569] lr: 4.0000e-02 eta: 11:28:29 time: 0.2669 data_time: 0.0076 memory: 5828 grad_norm: 3.1567 loss: 2.6229 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6229 2023/06/05 09:30:04 - mmengine - INFO - Epoch(train) [90][1280/2569] lr: 4.0000e-02 eta: 11:28:24 time: 0.2741 data_time: 0.0080 memory: 5828 grad_norm: 3.1087 loss: 2.5448 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5448 2023/06/05 09:30:10 - mmengine - INFO - Epoch(train) [90][1300/2569] lr: 4.0000e-02 eta: 11:28:18 time: 0.2657 data_time: 0.0075 memory: 5828 grad_norm: 3.2190 loss: 2.6045 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6045 2023/06/05 09:30:15 - mmengine - INFO - Epoch(train) [90][1320/2569] lr: 4.0000e-02 eta: 11:28:13 time: 0.2753 data_time: 0.0077 memory: 5828 grad_norm: 3.1475 loss: 2.2890 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2890 2023/06/05 09:30:20 - mmengine - INFO - Epoch(train) [90][1340/2569] lr: 4.0000e-02 eta: 11:28:08 time: 0.2581 data_time: 0.0073 memory: 5828 grad_norm: 3.1013 loss: 2.5122 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5122 2023/06/05 09:30:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:30:26 - mmengine - INFO - Epoch(train) [90][1360/2569] lr: 4.0000e-02 eta: 11:28:02 time: 0.2714 data_time: 0.0075 memory: 5828 grad_norm: 3.1593 loss: 2.4524 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4524 2023/06/05 09:30:31 - mmengine - INFO - Epoch(train) [90][1380/2569] lr: 4.0000e-02 eta: 11:27:57 time: 0.2714 data_time: 0.0073 memory: 5828 grad_norm: 3.0917 loss: 2.6021 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6021 2023/06/05 09:30:37 - mmengine - INFO - Epoch(train) [90][1400/2569] lr: 4.0000e-02 eta: 11:27:52 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 3.1001 loss: 2.9230 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.9230 2023/06/05 09:30:42 - mmengine - INFO - Epoch(train) [90][1420/2569] lr: 4.0000e-02 eta: 11:27:46 time: 0.2581 data_time: 0.0074 memory: 5828 grad_norm: 3.1069 loss: 2.3158 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3158 2023/06/05 09:30:47 - mmengine - INFO - Epoch(train) [90][1440/2569] lr: 4.0000e-02 eta: 11:27:41 time: 0.2698 data_time: 0.0084 memory: 5828 grad_norm: 3.1131 loss: 2.4428 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4428 2023/06/05 09:30:52 - mmengine - INFO - Epoch(train) [90][1460/2569] lr: 4.0000e-02 eta: 11:27:36 time: 0.2608 data_time: 0.0072 memory: 5828 grad_norm: 3.1425 loss: 2.4052 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4052 2023/06/05 09:30:58 - mmengine - INFO - Epoch(train) [90][1480/2569] lr: 4.0000e-02 eta: 11:27:31 time: 0.2769 data_time: 0.0074 memory: 5828 grad_norm: 3.1273 loss: 2.6206 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6206 2023/06/05 09:31:03 - mmengine - INFO - Epoch(train) [90][1500/2569] lr: 4.0000e-02 eta: 11:27:25 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 3.1238 loss: 2.4700 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4700 2023/06/05 09:31:09 - mmengine - INFO - Epoch(train) [90][1520/2569] lr: 4.0000e-02 eta: 11:27:20 time: 0.2748 data_time: 0.0072 memory: 5828 grad_norm: 3.1163 loss: 2.5266 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5266 2023/06/05 09:31:14 - mmengine - INFO - Epoch(train) [90][1540/2569] lr: 4.0000e-02 eta: 11:27:15 time: 0.2753 data_time: 0.0074 memory: 5828 grad_norm: 3.1806 loss: 2.3332 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3332 2023/06/05 09:31:19 - mmengine - INFO - Epoch(train) [90][1560/2569] lr: 4.0000e-02 eta: 11:27:09 time: 0.2595 data_time: 0.0075 memory: 5828 grad_norm: 3.1268 loss: 2.2187 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2187 2023/06/05 09:31:25 - mmengine - INFO - Epoch(train) [90][1580/2569] lr: 4.0000e-02 eta: 11:27:04 time: 0.2670 data_time: 0.0072 memory: 5828 grad_norm: 3.1358 loss: 2.7981 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7981 2023/06/05 09:31:30 - mmengine - INFO - Epoch(train) [90][1600/2569] lr: 4.0000e-02 eta: 11:26:59 time: 0.2703 data_time: 0.0074 memory: 5828 grad_norm: 3.1311 loss: 2.6978 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6978 2023/06/05 09:31:36 - mmengine - INFO - Epoch(train) [90][1620/2569] lr: 4.0000e-02 eta: 11:26:54 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 3.0551 loss: 2.2475 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2475 2023/06/05 09:31:41 - mmengine - INFO - Epoch(train) [90][1640/2569] lr: 4.0000e-02 eta: 11:26:48 time: 0.2719 data_time: 0.0080 memory: 5828 grad_norm: 3.1482 loss: 2.2482 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2482 2023/06/05 09:31:46 - mmengine - INFO - Epoch(train) [90][1660/2569] lr: 4.0000e-02 eta: 11:26:43 time: 0.2738 data_time: 0.0077 memory: 5828 grad_norm: 3.1203 loss: 2.7468 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7468 2023/06/05 09:31:52 - mmengine - INFO - Epoch(train) [90][1680/2569] lr: 4.0000e-02 eta: 11:26:38 time: 0.2594 data_time: 0.0075 memory: 5828 grad_norm: 3.1242 loss: 2.4055 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4055 2023/06/05 09:31:57 - mmengine - INFO - Epoch(train) [90][1700/2569] lr: 4.0000e-02 eta: 11:26:32 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 3.1255 loss: 2.8147 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8147 2023/06/05 09:32:02 - mmengine - INFO - Epoch(train) [90][1720/2569] lr: 4.0000e-02 eta: 11:26:27 time: 0.2606 data_time: 0.0074 memory: 5828 grad_norm: 3.1517 loss: 2.5561 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5561 2023/06/05 09:32:07 - mmengine - INFO - Epoch(train) [90][1740/2569] lr: 4.0000e-02 eta: 11:26:22 time: 0.2702 data_time: 0.0075 memory: 5828 grad_norm: 3.1596 loss: 2.8654 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.8654 2023/06/05 09:32:13 - mmengine - INFO - Epoch(train) [90][1760/2569] lr: 4.0000e-02 eta: 11:26:16 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 3.2150 loss: 2.4921 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4921 2023/06/05 09:32:18 - mmengine - INFO - Epoch(train) [90][1780/2569] lr: 4.0000e-02 eta: 11:26:11 time: 0.2575 data_time: 0.0071 memory: 5828 grad_norm: 3.1400 loss: 2.1059 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1059 2023/06/05 09:32:23 - mmengine - INFO - Epoch(train) [90][1800/2569] lr: 4.0000e-02 eta: 11:26:06 time: 0.2592 data_time: 0.0082 memory: 5828 grad_norm: 3.1276 loss: 2.2552 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2552 2023/06/05 09:32:28 - mmengine - INFO - Epoch(train) [90][1820/2569] lr: 4.0000e-02 eta: 11:26:00 time: 0.2696 data_time: 0.0073 memory: 5828 grad_norm: 3.1620 loss: 2.3908 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3908 2023/06/05 09:32:34 - mmengine - INFO - Epoch(train) [90][1840/2569] lr: 4.0000e-02 eta: 11:25:55 time: 0.2643 data_time: 0.0075 memory: 5828 grad_norm: 3.1741 loss: 2.6221 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6221 2023/06/05 09:32:39 - mmengine - INFO - Epoch(train) [90][1860/2569] lr: 4.0000e-02 eta: 11:25:50 time: 0.2696 data_time: 0.0079 memory: 5828 grad_norm: 3.0925 loss: 2.3765 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3765 2023/06/05 09:32:44 - mmengine - INFO - Epoch(train) [90][1880/2569] lr: 4.0000e-02 eta: 11:25:44 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 3.1402 loss: 2.4600 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4600 2023/06/05 09:32:50 - mmengine - INFO - Epoch(train) [90][1900/2569] lr: 4.0000e-02 eta: 11:25:39 time: 0.2683 data_time: 0.0079 memory: 5828 grad_norm: 3.1640 loss: 2.7784 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7784 2023/06/05 09:32:55 - mmengine - INFO - Epoch(train) [90][1920/2569] lr: 4.0000e-02 eta: 11:25:34 time: 0.2602 data_time: 0.0071 memory: 5828 grad_norm: 3.1447 loss: 2.6054 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6054 2023/06/05 09:33:00 - mmengine - INFO - Epoch(train) [90][1940/2569] lr: 4.0000e-02 eta: 11:25:28 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 3.1012 loss: 2.6011 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6011 2023/06/05 09:33:06 - mmengine - INFO - Epoch(train) [90][1960/2569] lr: 4.0000e-02 eta: 11:25:23 time: 0.2601 data_time: 0.0080 memory: 5828 grad_norm: 3.0871 loss: 2.7148 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7148 2023/06/05 09:33:11 - mmengine - INFO - Epoch(train) [90][1980/2569] lr: 4.0000e-02 eta: 11:25:18 time: 0.2704 data_time: 0.0073 memory: 5828 grad_norm: 3.1247 loss: 2.5786 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5786 2023/06/05 09:33:16 - mmengine - INFO - Epoch(train) [90][2000/2569] lr: 4.0000e-02 eta: 11:25:12 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 3.1577 loss: 2.5500 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5500 2023/06/05 09:33:22 - mmengine - INFO - Epoch(train) [90][2020/2569] lr: 4.0000e-02 eta: 11:25:07 time: 0.2710 data_time: 0.0072 memory: 5828 grad_norm: 3.1841 loss: 2.7001 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7001 2023/06/05 09:33:27 - mmengine - INFO - Epoch(train) [90][2040/2569] lr: 4.0000e-02 eta: 11:25:02 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 3.1130 loss: 2.5015 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5015 2023/06/05 09:33:33 - mmengine - INFO - Epoch(train) [90][2060/2569] lr: 4.0000e-02 eta: 11:24:57 time: 0.2826 data_time: 0.0074 memory: 5828 grad_norm: 3.1005 loss: 2.4209 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4209 2023/06/05 09:33:38 - mmengine - INFO - Epoch(train) [90][2080/2569] lr: 4.0000e-02 eta: 11:24:51 time: 0.2716 data_time: 0.0077 memory: 5828 grad_norm: 3.1683 loss: 2.2669 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2669 2023/06/05 09:33:44 - mmengine - INFO - Epoch(train) [90][2100/2569] lr: 4.0000e-02 eta: 11:24:46 time: 0.2725 data_time: 0.0087 memory: 5828 grad_norm: 3.2119 loss: 2.1633 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1633 2023/06/05 09:33:49 - mmengine - INFO - Epoch(train) [90][2120/2569] lr: 4.0000e-02 eta: 11:24:41 time: 0.2650 data_time: 0.0074 memory: 5828 grad_norm: 3.1398 loss: 2.3801 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3801 2023/06/05 09:33:54 - mmengine - INFO - Epoch(train) [90][2140/2569] lr: 4.0000e-02 eta: 11:24:36 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 3.1087 loss: 2.6014 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6014 2023/06/05 09:33:59 - mmengine - INFO - Epoch(train) [90][2160/2569] lr: 4.0000e-02 eta: 11:24:30 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 3.1365 loss: 2.6530 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6530 2023/06/05 09:34:05 - mmengine - INFO - Epoch(train) [90][2180/2569] lr: 4.0000e-02 eta: 11:24:25 time: 0.2600 data_time: 0.0072 memory: 5828 grad_norm: 3.1344 loss: 2.9325 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9325 2023/06/05 09:34:10 - mmengine - INFO - Epoch(train) [90][2200/2569] lr: 4.0000e-02 eta: 11:24:19 time: 0.2638 data_time: 0.0077 memory: 5828 grad_norm: 3.0525 loss: 2.5164 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5164 2023/06/05 09:34:15 - mmengine - INFO - Epoch(train) [90][2220/2569] lr: 4.0000e-02 eta: 11:24:14 time: 0.2670 data_time: 0.0071 memory: 5828 grad_norm: 3.0654 loss: 2.2691 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2691 2023/06/05 09:34:21 - mmengine - INFO - Epoch(train) [90][2240/2569] lr: 4.0000e-02 eta: 11:24:09 time: 0.2619 data_time: 0.0074 memory: 5828 grad_norm: 3.1776 loss: 2.4989 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4989 2023/06/05 09:34:26 - mmengine - INFO - Epoch(train) [90][2260/2569] lr: 4.0000e-02 eta: 11:24:03 time: 0.2591 data_time: 0.0075 memory: 5828 grad_norm: 3.1370 loss: 2.1822 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1822 2023/06/05 09:34:31 - mmengine - INFO - Epoch(train) [90][2280/2569] lr: 4.0000e-02 eta: 11:23:58 time: 0.2604 data_time: 0.0073 memory: 5828 grad_norm: 3.0836 loss: 2.3765 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3765 2023/06/05 09:34:36 - mmengine - INFO - Epoch(train) [90][2300/2569] lr: 4.0000e-02 eta: 11:23:53 time: 0.2740 data_time: 0.0075 memory: 5828 grad_norm: 3.1767 loss: 2.3666 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3666 2023/06/05 09:34:42 - mmengine - INFO - Epoch(train) [90][2320/2569] lr: 4.0000e-02 eta: 11:23:48 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 3.1740 loss: 2.6259 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6259 2023/06/05 09:34:47 - mmengine - INFO - Epoch(train) [90][2340/2569] lr: 4.0000e-02 eta: 11:23:42 time: 0.2601 data_time: 0.0073 memory: 5828 grad_norm: 3.1900 loss: 2.7005 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.7005 2023/06/05 09:34:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:34:52 - mmengine - INFO - Epoch(train) [90][2360/2569] lr: 4.0000e-02 eta: 11:23:37 time: 0.2655 data_time: 0.0076 memory: 5828 grad_norm: 3.0995 loss: 2.1316 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1316 2023/06/05 09:34:58 - mmengine - INFO - Epoch(train) [90][2380/2569] lr: 4.0000e-02 eta: 11:23:31 time: 0.2612 data_time: 0.0071 memory: 5828 grad_norm: 3.1055 loss: 2.6814 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6814 2023/06/05 09:35:03 - mmengine - INFO - Epoch(train) [90][2400/2569] lr: 4.0000e-02 eta: 11:23:26 time: 0.2749 data_time: 0.0079 memory: 5828 grad_norm: 3.0910 loss: 2.2758 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2758 2023/06/05 09:35:08 - mmengine - INFO - Epoch(train) [90][2420/2569] lr: 4.0000e-02 eta: 11:23:21 time: 0.2615 data_time: 0.0073 memory: 5828 grad_norm: 3.1333 loss: 2.3919 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3919 2023/06/05 09:35:14 - mmengine - INFO - Epoch(train) [90][2440/2569] lr: 4.0000e-02 eta: 11:23:16 time: 0.2706 data_time: 0.0077 memory: 5828 grad_norm: 3.2287 loss: 2.5048 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5048 2023/06/05 09:35:19 - mmengine - INFO - Epoch(train) [90][2460/2569] lr: 4.0000e-02 eta: 11:23:10 time: 0.2694 data_time: 0.0074 memory: 5828 grad_norm: 3.1716 loss: 2.6302 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6302 2023/06/05 09:35:24 - mmengine - INFO - Epoch(train) [90][2480/2569] lr: 4.0000e-02 eta: 11:23:05 time: 0.2663 data_time: 0.0078 memory: 5828 grad_norm: 3.1547 loss: 2.5121 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5121 2023/06/05 09:35:30 - mmengine - INFO - Epoch(train) [90][2500/2569] lr: 4.0000e-02 eta: 11:23:00 time: 0.2669 data_time: 0.0076 memory: 5828 grad_norm: 3.1329 loss: 2.1033 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1033 2023/06/05 09:35:35 - mmengine - INFO - Epoch(train) [90][2520/2569] lr: 4.0000e-02 eta: 11:22:55 time: 0.2717 data_time: 0.0069 memory: 5828 grad_norm: 3.1298 loss: 2.4559 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4559 2023/06/05 09:35:41 - mmengine - INFO - Epoch(train) [90][2540/2569] lr: 4.0000e-02 eta: 11:22:49 time: 0.2670 data_time: 0.0074 memory: 5828 grad_norm: 3.1692 loss: 2.6554 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6554 2023/06/05 09:35:46 - mmengine - INFO - Epoch(train) [90][2560/2569] lr: 4.0000e-02 eta: 11:22:44 time: 0.2708 data_time: 0.0074 memory: 5828 grad_norm: 3.1422 loss: 2.1717 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1717 2023/06/05 09:35:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:35:48 - mmengine - INFO - Epoch(train) [90][2569/2569] lr: 4.0000e-02 eta: 11:22:41 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 3.1829 loss: 2.4493 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.4493 2023/06/05 09:35:52 - mmengine - INFO - Epoch(val) [90][ 20/260] eta: 0:00:40 time: 0.1708 data_time: 0.1118 memory: 1238 2023/06/05 09:35:54 - mmengine - INFO - Epoch(val) [90][ 40/260] eta: 0:00:33 time: 0.1304 data_time: 0.0721 memory: 1238 2023/06/05 09:35:58 - mmengine - INFO - Epoch(val) [90][ 60/260] eta: 0:00:30 time: 0.1607 data_time: 0.1022 memory: 1238 2023/06/05 09:36:00 - mmengine - INFO - Epoch(val) [90][ 80/260] eta: 0:00:26 time: 0.1348 data_time: 0.0762 memory: 1238 2023/06/05 09:36:03 - mmengine - INFO - Epoch(val) [90][100/260] eta: 0:00:23 time: 0.1418 data_time: 0.0828 memory: 1238 2023/06/05 09:36:06 - mmengine - INFO - Epoch(val) [90][120/260] eta: 0:00:20 time: 0.1466 data_time: 0.0877 memory: 1238 2023/06/05 09:36:08 - mmengine - INFO - Epoch(val) [90][140/260] eta: 0:00:17 time: 0.1257 data_time: 0.0668 memory: 1238 2023/06/05 09:36:12 - mmengine - INFO - Epoch(val) [90][160/260] eta: 0:00:14 time: 0.1545 data_time: 0.0960 memory: 1238 2023/06/05 09:36:14 - mmengine - INFO - Epoch(val) [90][180/260] eta: 0:00:11 time: 0.1132 data_time: 0.0551 memory: 1238 2023/06/05 09:36:17 - mmengine - INFO - Epoch(val) [90][200/260] eta: 0:00:08 time: 0.1571 data_time: 0.0981 memory: 1238 2023/06/05 09:36:19 - mmengine - INFO - Epoch(val) [90][220/260] eta: 0:00:05 time: 0.1217 data_time: 0.0630 memory: 1238 2023/06/05 09:36:22 - mmengine - INFO - Epoch(val) [90][240/260] eta: 0:00:02 time: 0.1447 data_time: 0.0862 memory: 1238 2023/06/05 09:36:25 - mmengine - INFO - Epoch(val) [90][260/260] eta: 0:00:00 time: 0.1185 data_time: 0.0617 memory: 1238 2023/06/05 09:36:33 - mmengine - INFO - Epoch(val) [90][260/260] acc/top1: 0.5136 acc/top5: 0.7531 acc/mean1: 0.5060 data_time: 0.0812 time: 0.1397 2023/06/05 09:36:33 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_85.pth is removed 2023/06/05 09:36:34 - mmengine - INFO - The best checkpoint with 0.5136 acc/top1 at 90 epoch is saved to best_acc_top1_epoch_90.pth. 2023/06/05 09:36:40 - mmengine - INFO - Epoch(train) [91][ 20/2569] lr: 4.0000e-02 eta: 11:22:37 time: 0.2945 data_time: 0.0442 memory: 5828 grad_norm: 3.1639 loss: 2.5814 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5814 2023/06/05 09:36:45 - mmengine - INFO - Epoch(train) [91][ 40/2569] lr: 4.0000e-02 eta: 11:22:31 time: 0.2591 data_time: 0.0075 memory: 5828 grad_norm: 3.1280 loss: 2.7863 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7863 2023/06/05 09:36:51 - mmengine - INFO - Epoch(train) [91][ 60/2569] lr: 4.0000e-02 eta: 11:22:26 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 3.1797 loss: 2.5143 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5143 2023/06/05 09:36:56 - mmengine - INFO - Epoch(train) [91][ 80/2569] lr: 4.0000e-02 eta: 11:22:20 time: 0.2599 data_time: 0.0079 memory: 5828 grad_norm: 3.1442 loss: 2.6492 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6492 2023/06/05 09:37:01 - mmengine - INFO - Epoch(train) [91][ 100/2569] lr: 4.0000e-02 eta: 11:22:15 time: 0.2616 data_time: 0.0075 memory: 5828 grad_norm: 3.0951 loss: 2.7701 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7701 2023/06/05 09:37:06 - mmengine - INFO - Epoch(train) [91][ 120/2569] lr: 4.0000e-02 eta: 11:22:10 time: 0.2592 data_time: 0.0090 memory: 5828 grad_norm: 3.1624 loss: 2.5045 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5045 2023/06/05 09:37:12 - mmengine - INFO - Epoch(train) [91][ 140/2569] lr: 4.0000e-02 eta: 11:22:04 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 3.0470 loss: 2.2707 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2707 2023/06/05 09:37:17 - mmengine - INFO - Epoch(train) [91][ 160/2569] lr: 4.0000e-02 eta: 11:21:59 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 3.0898 loss: 2.4304 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4304 2023/06/05 09:37:22 - mmengine - INFO - Epoch(train) [91][ 180/2569] lr: 4.0000e-02 eta: 11:21:54 time: 0.2596 data_time: 0.0074 memory: 5828 grad_norm: 3.1595 loss: 2.6814 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6814 2023/06/05 09:37:28 - mmengine - INFO - Epoch(train) [91][ 200/2569] lr: 4.0000e-02 eta: 11:21:48 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 3.2056 loss: 2.4784 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4784 2023/06/05 09:37:33 - mmengine - INFO - Epoch(train) [91][ 220/2569] lr: 4.0000e-02 eta: 11:21:43 time: 0.2620 data_time: 0.0069 memory: 5828 grad_norm: 3.1366 loss: 2.7181 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7181 2023/06/05 09:37:38 - mmengine - INFO - Epoch(train) [91][ 240/2569] lr: 4.0000e-02 eta: 11:21:38 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 3.1327 loss: 2.8313 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8313 2023/06/05 09:37:43 - mmengine - INFO - Epoch(train) [91][ 260/2569] lr: 4.0000e-02 eta: 11:21:32 time: 0.2636 data_time: 0.0071 memory: 5828 grad_norm: 3.2068 loss: 2.4944 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4944 2023/06/05 09:37:49 - mmengine - INFO - Epoch(train) [91][ 280/2569] lr: 4.0000e-02 eta: 11:21:27 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 3.1683 loss: 2.6452 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6452 2023/06/05 09:37:54 - mmengine - INFO - Epoch(train) [91][ 300/2569] lr: 4.0000e-02 eta: 11:21:22 time: 0.2643 data_time: 0.0081 memory: 5828 grad_norm: 3.1146 loss: 2.1813 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1813 2023/06/05 09:37:59 - mmengine - INFO - Epoch(train) [91][ 320/2569] lr: 4.0000e-02 eta: 11:21:16 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 3.0845 loss: 2.3732 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3732 2023/06/05 09:38:05 - mmengine - INFO - Epoch(train) [91][ 340/2569] lr: 4.0000e-02 eta: 11:21:11 time: 0.2724 data_time: 0.0075 memory: 5828 grad_norm: 3.1085 loss: 2.2188 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2188 2023/06/05 09:38:10 - mmengine - INFO - Epoch(train) [91][ 360/2569] lr: 4.0000e-02 eta: 11:21:06 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 3.1906 loss: 2.5486 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5486 2023/06/05 09:38:16 - mmengine - INFO - Epoch(train) [91][ 380/2569] lr: 4.0000e-02 eta: 11:21:01 time: 0.2799 data_time: 0.0073 memory: 5828 grad_norm: 3.1344 loss: 2.2172 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2172 2023/06/05 09:38:21 - mmengine - INFO - Epoch(train) [91][ 400/2569] lr: 4.0000e-02 eta: 11:20:55 time: 0.2660 data_time: 0.0072 memory: 5828 grad_norm: 3.1900 loss: 2.8941 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8941 2023/06/05 09:38:26 - mmengine - INFO - Epoch(train) [91][ 420/2569] lr: 4.0000e-02 eta: 11:20:50 time: 0.2785 data_time: 0.0070 memory: 5828 grad_norm: 3.0918 loss: 2.0981 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.0981 2023/06/05 09:38:32 - mmengine - INFO - Epoch(train) [91][ 440/2569] lr: 4.0000e-02 eta: 11:20:45 time: 0.2727 data_time: 0.0081 memory: 5828 grad_norm: 3.1176 loss: 2.2839 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2839 2023/06/05 09:38:37 - mmengine - INFO - Epoch(train) [91][ 460/2569] lr: 4.0000e-02 eta: 11:20:40 time: 0.2704 data_time: 0.0074 memory: 5828 grad_norm: 3.1019 loss: 2.7434 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.7434 2023/06/05 09:38:43 - mmengine - INFO - Epoch(train) [91][ 480/2569] lr: 4.0000e-02 eta: 11:20:34 time: 0.2649 data_time: 0.0075 memory: 5828 grad_norm: 3.1304 loss: 2.2411 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2411 2023/06/05 09:38:48 - mmengine - INFO - Epoch(train) [91][ 500/2569] lr: 4.0000e-02 eta: 11:20:29 time: 0.2582 data_time: 0.0072 memory: 5828 grad_norm: 3.1455 loss: 2.6886 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6886 2023/06/05 09:38:53 - mmengine - INFO - Epoch(train) [91][ 520/2569] lr: 4.0000e-02 eta: 11:20:24 time: 0.2607 data_time: 0.0076 memory: 5828 grad_norm: 3.1700 loss: 2.6699 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6699 2023/06/05 09:38:58 - mmengine - INFO - Epoch(train) [91][ 540/2569] lr: 4.0000e-02 eta: 11:20:18 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 3.1408 loss: 2.5082 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5082 2023/06/05 09:39:04 - mmengine - INFO - Epoch(train) [91][ 560/2569] lr: 4.0000e-02 eta: 11:20:13 time: 0.2644 data_time: 0.0083 memory: 5828 grad_norm: 3.1924 loss: 2.5607 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5607 2023/06/05 09:39:09 - mmengine - INFO - Epoch(train) [91][ 580/2569] lr: 4.0000e-02 eta: 11:20:08 time: 0.2601 data_time: 0.0071 memory: 5828 grad_norm: 3.0823 loss: 2.2944 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2944 2023/06/05 09:39:14 - mmengine - INFO - Epoch(train) [91][ 600/2569] lr: 4.0000e-02 eta: 11:20:02 time: 0.2600 data_time: 0.0078 memory: 5828 grad_norm: 3.2028 loss: 2.6864 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6864 2023/06/05 09:39:19 - mmengine - INFO - Epoch(train) [91][ 620/2569] lr: 4.0000e-02 eta: 11:19:57 time: 0.2610 data_time: 0.0072 memory: 5828 grad_norm: 3.1245 loss: 2.6568 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6568 2023/06/05 09:39:25 - mmengine - INFO - Epoch(train) [91][ 640/2569] lr: 4.0000e-02 eta: 11:19:51 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 3.1644 loss: 2.3194 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3194 2023/06/05 09:39:30 - mmengine - INFO - Epoch(train) [91][ 660/2569] lr: 4.0000e-02 eta: 11:19:46 time: 0.2696 data_time: 0.0072 memory: 5828 grad_norm: 3.0824 loss: 2.3127 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3127 2023/06/05 09:39:35 - mmengine - INFO - Epoch(train) [91][ 680/2569] lr: 4.0000e-02 eta: 11:19:41 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 3.1643 loss: 2.7087 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7087 2023/06/05 09:39:41 - mmengine - INFO - Epoch(train) [91][ 700/2569] lr: 4.0000e-02 eta: 11:19:36 time: 0.2661 data_time: 0.0073 memory: 5828 grad_norm: 3.1435 loss: 2.7494 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7494 2023/06/05 09:39:46 - mmengine - INFO - Epoch(train) [91][ 720/2569] lr: 4.0000e-02 eta: 11:19:30 time: 0.2700 data_time: 0.0077 memory: 5828 grad_norm: 3.1012 loss: 2.5101 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5101 2023/06/05 09:39:51 - mmengine - INFO - Epoch(train) [91][ 740/2569] lr: 4.0000e-02 eta: 11:19:25 time: 0.2697 data_time: 0.0081 memory: 5828 grad_norm: 3.1332 loss: 2.5509 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5509 2023/06/05 09:39:57 - mmengine - INFO - Epoch(train) [91][ 760/2569] lr: 4.0000e-02 eta: 11:19:20 time: 0.2733 data_time: 0.0073 memory: 5828 grad_norm: 3.1125 loss: 2.7136 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7136 2023/06/05 09:40:02 - mmengine - INFO - Epoch(train) [91][ 780/2569] lr: 4.0000e-02 eta: 11:19:14 time: 0.2583 data_time: 0.0072 memory: 5828 grad_norm: 3.1393 loss: 2.1347 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1347 2023/06/05 09:40:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:40:08 - mmengine - INFO - Epoch(train) [91][ 800/2569] lr: 4.0000e-02 eta: 11:19:09 time: 0.2694 data_time: 0.0073 memory: 5828 grad_norm: 3.2190 loss: 2.5330 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5330 2023/06/05 09:40:13 - mmengine - INFO - Epoch(train) [91][ 820/2569] lr: 4.0000e-02 eta: 11:19:04 time: 0.2599 data_time: 0.0074 memory: 5828 grad_norm: 3.1625 loss: 2.1760 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1760 2023/06/05 09:40:18 - mmengine - INFO - Epoch(train) [91][ 840/2569] lr: 4.0000e-02 eta: 11:18:58 time: 0.2588 data_time: 0.0079 memory: 5828 grad_norm: 3.1143 loss: 2.7787 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7787 2023/06/05 09:40:23 - mmengine - INFO - Epoch(train) [91][ 860/2569] lr: 4.0000e-02 eta: 11:18:53 time: 0.2734 data_time: 0.0077 memory: 5828 grad_norm: 3.1122 loss: 2.9480 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.9480 2023/06/05 09:40:29 - mmengine - INFO - Epoch(train) [91][ 880/2569] lr: 4.0000e-02 eta: 11:18:48 time: 0.2643 data_time: 0.0076 memory: 5828 grad_norm: 3.1160 loss: 2.6251 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6251 2023/06/05 09:40:34 - mmengine - INFO - Epoch(train) [91][ 900/2569] lr: 4.0000e-02 eta: 11:18:42 time: 0.2600 data_time: 0.0084 memory: 5828 grad_norm: 3.1725 loss: 2.5914 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5914 2023/06/05 09:40:39 - mmengine - INFO - Epoch(train) [91][ 920/2569] lr: 4.0000e-02 eta: 11:18:37 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 3.1038 loss: 2.2740 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2740 2023/06/05 09:40:44 - mmengine - INFO - Epoch(train) [91][ 940/2569] lr: 4.0000e-02 eta: 11:18:32 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 3.1824 loss: 2.4800 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4800 2023/06/05 09:40:50 - mmengine - INFO - Epoch(train) [91][ 960/2569] lr: 4.0000e-02 eta: 11:18:26 time: 0.2596 data_time: 0.0071 memory: 5828 grad_norm: 3.0980 loss: 2.4093 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4093 2023/06/05 09:40:55 - mmengine - INFO - Epoch(train) [91][ 980/2569] lr: 4.0000e-02 eta: 11:18:21 time: 0.2676 data_time: 0.0071 memory: 5828 grad_norm: 3.1434 loss: 2.2776 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2776 2023/06/05 09:41:00 - mmengine - INFO - Epoch(train) [91][1000/2569] lr: 4.0000e-02 eta: 11:18:16 time: 0.2594 data_time: 0.0071 memory: 5828 grad_norm: 3.0880 loss: 2.8060 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8060 2023/06/05 09:41:06 - mmengine - INFO - Epoch(train) [91][1020/2569] lr: 4.0000e-02 eta: 11:18:10 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 3.1499 loss: 2.6383 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6383 2023/06/05 09:41:11 - mmengine - INFO - Epoch(train) [91][1040/2569] lr: 4.0000e-02 eta: 11:18:05 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 3.0470 loss: 2.2379 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2379 2023/06/05 09:41:16 - mmengine - INFO - Epoch(train) [91][1060/2569] lr: 4.0000e-02 eta: 11:18:00 time: 0.2761 data_time: 0.0071 memory: 5828 grad_norm: 3.1598 loss: 2.3427 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3427 2023/06/05 09:41:22 - mmengine - INFO - Epoch(train) [91][1080/2569] lr: 4.0000e-02 eta: 11:17:54 time: 0.2611 data_time: 0.0069 memory: 5828 grad_norm: 3.1052 loss: 2.6013 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6013 2023/06/05 09:41:27 - mmengine - INFO - Epoch(train) [91][1100/2569] lr: 4.0000e-02 eta: 11:17:49 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 3.0990 loss: 2.6212 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6212 2023/06/05 09:41:32 - mmengine - INFO - Epoch(train) [91][1120/2569] lr: 4.0000e-02 eta: 11:17:44 time: 0.2672 data_time: 0.0076 memory: 5828 grad_norm: 3.1082 loss: 2.7767 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7767 2023/06/05 09:41:38 - mmengine - INFO - Epoch(train) [91][1140/2569] lr: 4.0000e-02 eta: 11:17:38 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 3.1309 loss: 2.4884 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4884 2023/06/05 09:41:43 - mmengine - INFO - Epoch(train) [91][1160/2569] lr: 4.0000e-02 eta: 11:17:33 time: 0.2672 data_time: 0.0080 memory: 5828 grad_norm: 3.1370 loss: 2.6011 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6011 2023/06/05 09:41:48 - mmengine - INFO - Epoch(train) [91][1180/2569] lr: 4.0000e-02 eta: 11:17:28 time: 0.2651 data_time: 0.0072 memory: 5828 grad_norm: 3.1408 loss: 2.2625 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2625 2023/06/05 09:41:53 - mmengine - INFO - Epoch(train) [91][1200/2569] lr: 4.0000e-02 eta: 11:17:22 time: 0.2621 data_time: 0.0082 memory: 5828 grad_norm: 3.1213 loss: 2.7597 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7597 2023/06/05 09:41:59 - mmengine - INFO - Epoch(train) [91][1220/2569] lr: 4.0000e-02 eta: 11:17:17 time: 0.2599 data_time: 0.0077 memory: 5828 grad_norm: 3.0874 loss: 2.5008 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5008 2023/06/05 09:42:04 - mmengine - INFO - Epoch(train) [91][1240/2569] lr: 4.0000e-02 eta: 11:17:12 time: 0.2729 data_time: 0.0073 memory: 5828 grad_norm: 3.1459 loss: 2.2812 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2812 2023/06/05 09:42:09 - mmengine - INFO - Epoch(train) [91][1260/2569] lr: 4.0000e-02 eta: 11:17:07 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 3.1235 loss: 2.5559 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5559 2023/06/05 09:42:15 - mmengine - INFO - Epoch(train) [91][1280/2569] lr: 4.0000e-02 eta: 11:17:01 time: 0.2587 data_time: 0.0074 memory: 5828 grad_norm: 3.1006 loss: 2.4546 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4546 2023/06/05 09:42:20 - mmengine - INFO - Epoch(train) [91][1300/2569] lr: 4.0000e-02 eta: 11:16:56 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 3.1129 loss: 2.6242 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6242 2023/06/05 09:42:25 - mmengine - INFO - Epoch(train) [91][1320/2569] lr: 4.0000e-02 eta: 11:16:50 time: 0.2596 data_time: 0.0074 memory: 5828 grad_norm: 3.1434 loss: 2.3738 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3738 2023/06/05 09:42:31 - mmengine - INFO - Epoch(train) [91][1340/2569] lr: 4.0000e-02 eta: 11:16:45 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 3.1273 loss: 2.1342 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1342 2023/06/05 09:42:36 - mmengine - INFO - Epoch(train) [91][1360/2569] lr: 4.0000e-02 eta: 11:16:40 time: 0.2601 data_time: 0.0083 memory: 5828 grad_norm: 3.1531 loss: 2.4261 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4261 2023/06/05 09:42:41 - mmengine - INFO - Epoch(train) [91][1380/2569] lr: 4.0000e-02 eta: 11:16:34 time: 0.2679 data_time: 0.0075 memory: 5828 grad_norm: 3.0974 loss: 2.4104 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4104 2023/06/05 09:42:47 - mmengine - INFO - Epoch(train) [91][1400/2569] lr: 4.0000e-02 eta: 11:16:29 time: 0.2707 data_time: 0.0078 memory: 5828 grad_norm: 3.1502 loss: 2.6994 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6994 2023/06/05 09:42:52 - mmengine - INFO - Epoch(train) [91][1420/2569] lr: 4.0000e-02 eta: 11:16:24 time: 0.2733 data_time: 0.0072 memory: 5828 grad_norm: 3.0651 loss: 2.4912 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4912 2023/06/05 09:42:57 - mmengine - INFO - Epoch(train) [91][1440/2569] lr: 4.0000e-02 eta: 11:16:19 time: 0.2613 data_time: 0.0076 memory: 5828 grad_norm: 3.1274 loss: 2.1932 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1932 2023/06/05 09:43:03 - mmengine - INFO - Epoch(train) [91][1460/2569] lr: 4.0000e-02 eta: 11:16:13 time: 0.2699 data_time: 0.0079 memory: 5828 grad_norm: 3.1278 loss: 2.5067 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5067 2023/06/05 09:43:08 - mmengine - INFO - Epoch(train) [91][1480/2569] lr: 4.0000e-02 eta: 11:16:08 time: 0.2645 data_time: 0.0080 memory: 5828 grad_norm: 3.1423 loss: 2.6390 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6390 2023/06/05 09:43:14 - mmengine - INFO - Epoch(train) [91][1500/2569] lr: 4.0000e-02 eta: 11:16:03 time: 0.2802 data_time: 0.0074 memory: 5828 grad_norm: 3.1536 loss: 2.6808 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6808 2023/06/05 09:43:19 - mmengine - INFO - Epoch(train) [91][1520/2569] lr: 4.0000e-02 eta: 11:15:58 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 3.1238 loss: 2.3489 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3489 2023/06/05 09:43:24 - mmengine - INFO - Epoch(train) [91][1540/2569] lr: 4.0000e-02 eta: 11:15:52 time: 0.2701 data_time: 0.0075 memory: 5828 grad_norm: 3.1432 loss: 2.5175 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5175 2023/06/05 09:43:29 - mmengine - INFO - Epoch(train) [91][1560/2569] lr: 4.0000e-02 eta: 11:15:47 time: 0.2593 data_time: 0.0075 memory: 5828 grad_norm: 3.0890 loss: 2.4130 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4130 2023/06/05 09:43:35 - mmengine - INFO - Epoch(train) [91][1580/2569] lr: 4.0000e-02 eta: 11:15:42 time: 0.2754 data_time: 0.0073 memory: 5828 grad_norm: 3.1218 loss: 2.3947 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3947 2023/06/05 09:43:40 - mmengine - INFO - Epoch(train) [91][1600/2569] lr: 4.0000e-02 eta: 11:15:36 time: 0.2686 data_time: 0.0075 memory: 5828 grad_norm: 3.1381 loss: 2.2495 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2495 2023/06/05 09:43:46 - mmengine - INFO - Epoch(train) [91][1620/2569] lr: 4.0000e-02 eta: 11:15:31 time: 0.2655 data_time: 0.0078 memory: 5828 grad_norm: 3.1711 loss: 2.3711 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3711 2023/06/05 09:43:51 - mmengine - INFO - Epoch(train) [91][1640/2569] lr: 4.0000e-02 eta: 11:15:26 time: 0.2602 data_time: 0.0072 memory: 5828 grad_norm: 3.1762 loss: 2.6425 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6425 2023/06/05 09:43:56 - mmengine - INFO - Epoch(train) [91][1660/2569] lr: 4.0000e-02 eta: 11:15:21 time: 0.2817 data_time: 0.0071 memory: 5828 grad_norm: 3.1622 loss: 2.2758 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2758 2023/06/05 09:44:02 - mmengine - INFO - Epoch(train) [91][1680/2569] lr: 4.0000e-02 eta: 11:15:15 time: 0.2736 data_time: 0.0072 memory: 5828 grad_norm: 3.1598 loss: 2.2810 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.2810 2023/06/05 09:44:07 - mmengine - INFO - Epoch(train) [91][1700/2569] lr: 4.0000e-02 eta: 11:15:10 time: 0.2711 data_time: 0.0073 memory: 5828 grad_norm: 3.0612 loss: 2.4551 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4551 2023/06/05 09:44:13 - mmengine - INFO - Epoch(train) [91][1720/2569] lr: 4.0000e-02 eta: 11:15:05 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 3.1183 loss: 2.3932 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3932 2023/06/05 09:44:18 - mmengine - INFO - Epoch(train) [91][1740/2569] lr: 4.0000e-02 eta: 11:15:00 time: 0.2648 data_time: 0.0069 memory: 5828 grad_norm: 3.1176 loss: 2.8214 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8214 2023/06/05 09:44:23 - mmengine - INFO - Epoch(train) [91][1760/2569] lr: 4.0000e-02 eta: 11:14:54 time: 0.2586 data_time: 0.0072 memory: 5828 grad_norm: 3.1539 loss: 2.8017 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8017 2023/06/05 09:44:29 - mmengine - INFO - Epoch(train) [91][1780/2569] lr: 4.0000e-02 eta: 11:14:49 time: 0.2703 data_time: 0.0074 memory: 5828 grad_norm: 3.0981 loss: 2.3788 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3788 2023/06/05 09:44:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:44:34 - mmengine - INFO - Epoch(train) [91][1800/2569] lr: 4.0000e-02 eta: 11:14:43 time: 0.2581 data_time: 0.0073 memory: 5828 grad_norm: 3.1819 loss: 2.6256 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6256 2023/06/05 09:44:39 - mmengine - INFO - Epoch(train) [91][1820/2569] lr: 4.0000e-02 eta: 11:14:38 time: 0.2660 data_time: 0.0069 memory: 5828 grad_norm: 3.1404 loss: 2.3549 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3549 2023/06/05 09:44:45 - mmengine - INFO - Epoch(train) [91][1840/2569] lr: 4.0000e-02 eta: 11:14:33 time: 0.2733 data_time: 0.0072 memory: 5828 grad_norm: 3.1293 loss: 2.7587 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7587 2023/06/05 09:44:50 - mmengine - INFO - Epoch(train) [91][1860/2569] lr: 4.0000e-02 eta: 11:14:28 time: 0.2642 data_time: 0.0076 memory: 5828 grad_norm: 3.1428 loss: 2.3200 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3200 2023/06/05 09:44:55 - mmengine - INFO - Epoch(train) [91][1880/2569] lr: 4.0000e-02 eta: 11:14:22 time: 0.2643 data_time: 0.0071 memory: 5828 grad_norm: 3.1334 loss: 2.4576 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4576 2023/06/05 09:45:01 - mmengine - INFO - Epoch(train) [91][1900/2569] lr: 4.0000e-02 eta: 11:14:17 time: 0.2649 data_time: 0.0077 memory: 5828 grad_norm: 3.1309 loss: 2.4408 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4408 2023/06/05 09:45:06 - mmengine - INFO - Epoch(train) [91][1920/2569] lr: 4.0000e-02 eta: 11:14:12 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 3.1257 loss: 2.9048 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9048 2023/06/05 09:45:11 - mmengine - INFO - Epoch(train) [91][1940/2569] lr: 4.0000e-02 eta: 11:14:06 time: 0.2622 data_time: 0.0074 memory: 5828 grad_norm: 3.0864 loss: 2.7137 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7137 2023/06/05 09:45:16 - mmengine - INFO - Epoch(train) [91][1960/2569] lr: 4.0000e-02 eta: 11:14:01 time: 0.2588 data_time: 0.0080 memory: 5828 grad_norm: 3.1425 loss: 2.6295 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6295 2023/06/05 09:45:22 - mmengine - INFO - Epoch(train) [91][1980/2569] lr: 4.0000e-02 eta: 11:13:55 time: 0.2607 data_time: 0.0085 memory: 5828 grad_norm: 3.1244 loss: 2.5720 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5720 2023/06/05 09:45:27 - mmengine - INFO - Epoch(train) [91][2000/2569] lr: 4.0000e-02 eta: 11:13:50 time: 0.2737 data_time: 0.0075 memory: 5828 grad_norm: 3.1373 loss: 2.3214 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3214 2023/06/05 09:45:32 - mmengine - INFO - Epoch(train) [91][2020/2569] lr: 4.0000e-02 eta: 11:13:45 time: 0.2676 data_time: 0.0078 memory: 5828 grad_norm: 3.1152 loss: 2.6354 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6354 2023/06/05 09:45:38 - mmengine - INFO - Epoch(train) [91][2040/2569] lr: 4.0000e-02 eta: 11:13:40 time: 0.2635 data_time: 0.0085 memory: 5828 grad_norm: 3.1176 loss: 2.5071 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5071 2023/06/05 09:45:43 - mmengine - INFO - Epoch(train) [91][2060/2569] lr: 4.0000e-02 eta: 11:13:34 time: 0.2644 data_time: 0.0076 memory: 5828 grad_norm: 3.1206 loss: 2.5754 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5754 2023/06/05 09:45:48 - mmengine - INFO - Epoch(train) [91][2080/2569] lr: 4.0000e-02 eta: 11:13:29 time: 0.2684 data_time: 0.0074 memory: 5828 grad_norm: 3.2006 loss: 2.5872 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5872 2023/06/05 09:45:54 - mmengine - INFO - Epoch(train) [91][2100/2569] lr: 4.0000e-02 eta: 11:13:24 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 3.0872 loss: 2.6484 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6484 2023/06/05 09:45:59 - mmengine - INFO - Epoch(train) [91][2120/2569] lr: 4.0000e-02 eta: 11:13:18 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 3.1055 loss: 2.5977 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5977 2023/06/05 09:46:04 - mmengine - INFO - Epoch(train) [91][2140/2569] lr: 4.0000e-02 eta: 11:13:13 time: 0.2595 data_time: 0.0079 memory: 5828 grad_norm: 3.0886 loss: 2.9273 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.9273 2023/06/05 09:46:09 - mmengine - INFO - Epoch(train) [91][2160/2569] lr: 4.0000e-02 eta: 11:13:08 time: 0.2705 data_time: 0.0071 memory: 5828 grad_norm: 3.1283 loss: 2.2806 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2806 2023/06/05 09:46:15 - mmengine - INFO - Epoch(train) [91][2180/2569] lr: 4.0000e-02 eta: 11:13:02 time: 0.2690 data_time: 0.0074 memory: 5828 grad_norm: 3.1776 loss: 2.7423 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7423 2023/06/05 09:46:20 - mmengine - INFO - Epoch(train) [91][2200/2569] lr: 4.0000e-02 eta: 11:12:57 time: 0.2696 data_time: 0.0075 memory: 5828 grad_norm: 3.0966 loss: 2.3609 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3609 2023/06/05 09:46:26 - mmengine - INFO - Epoch(train) [91][2220/2569] lr: 4.0000e-02 eta: 11:12:52 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 3.1930 loss: 2.6212 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6212 2023/06/05 09:46:31 - mmengine - INFO - Epoch(train) [91][2240/2569] lr: 4.0000e-02 eta: 11:12:46 time: 0.2602 data_time: 0.0076 memory: 5828 grad_norm: 3.1064 loss: 2.5907 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5907 2023/06/05 09:46:36 - mmengine - INFO - Epoch(train) [91][2260/2569] lr: 4.0000e-02 eta: 11:12:41 time: 0.2601 data_time: 0.0074 memory: 5828 grad_norm: 3.1239 loss: 2.7240 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7240 2023/06/05 09:46:41 - mmengine - INFO - Epoch(train) [91][2280/2569] lr: 4.0000e-02 eta: 11:12:36 time: 0.2658 data_time: 0.0094 memory: 5828 grad_norm: 3.0342 loss: 2.4844 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4844 2023/06/05 09:46:47 - mmengine - INFO - Epoch(train) [91][2300/2569] lr: 4.0000e-02 eta: 11:12:30 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 3.1376 loss: 2.7124 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7124 2023/06/05 09:46:52 - mmengine - INFO - Epoch(train) [91][2320/2569] lr: 4.0000e-02 eta: 11:12:25 time: 0.2670 data_time: 0.0076 memory: 5828 grad_norm: 3.1617 loss: 2.2983 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2983 2023/06/05 09:46:57 - mmengine - INFO - Epoch(train) [91][2340/2569] lr: 4.0000e-02 eta: 11:12:20 time: 0.2588 data_time: 0.0074 memory: 5828 grad_norm: 3.1762 loss: 2.3447 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3447 2023/06/05 09:47:02 - mmengine - INFO - Epoch(train) [91][2360/2569] lr: 4.0000e-02 eta: 11:12:14 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 3.1551 loss: 2.4979 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4979 2023/06/05 09:47:08 - mmengine - INFO - Epoch(train) [91][2380/2569] lr: 4.0000e-02 eta: 11:12:09 time: 0.2633 data_time: 0.0072 memory: 5828 grad_norm: 3.0970 loss: 2.4316 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4316 2023/06/05 09:47:13 - mmengine - INFO - Epoch(train) [91][2400/2569] lr: 4.0000e-02 eta: 11:12:04 time: 0.2665 data_time: 0.0079 memory: 5828 grad_norm: 3.1438 loss: 2.5425 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5425 2023/06/05 09:47:18 - mmengine - INFO - Epoch(train) [91][2420/2569] lr: 4.0000e-02 eta: 11:11:58 time: 0.2596 data_time: 0.0074 memory: 5828 grad_norm: 3.1302 loss: 2.4005 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4005 2023/06/05 09:47:24 - mmengine - INFO - Epoch(train) [91][2440/2569] lr: 4.0000e-02 eta: 11:11:53 time: 0.2658 data_time: 0.0075 memory: 5828 grad_norm: 3.1878 loss: 2.4780 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4780 2023/06/05 09:47:29 - mmengine - INFO - Epoch(train) [91][2460/2569] lr: 4.0000e-02 eta: 11:11:48 time: 0.2653 data_time: 0.0075 memory: 5828 grad_norm: 3.0923 loss: 2.6482 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6482 2023/06/05 09:47:34 - mmengine - INFO - Epoch(train) [91][2480/2569] lr: 4.0000e-02 eta: 11:11:42 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.0923 loss: 2.7086 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7086 2023/06/05 09:47:39 - mmengine - INFO - Epoch(train) [91][2500/2569] lr: 4.0000e-02 eta: 11:11:37 time: 0.2626 data_time: 0.0077 memory: 5828 grad_norm: 3.1670 loss: 2.6232 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.6232 2023/06/05 09:47:45 - mmengine - INFO - Epoch(train) [91][2520/2569] lr: 4.0000e-02 eta: 11:11:32 time: 0.2727 data_time: 0.0077 memory: 5828 grad_norm: 3.0951 loss: 2.0953 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0953 2023/06/05 09:47:50 - mmengine - INFO - Epoch(train) [91][2540/2569] lr: 4.0000e-02 eta: 11:11:26 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 3.1484 loss: 2.9572 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.9572 2023/06/05 09:47:55 - mmengine - INFO - Epoch(train) [91][2560/2569] lr: 4.0000e-02 eta: 11:11:21 time: 0.2684 data_time: 0.0075 memory: 5828 grad_norm: 3.1839 loss: 2.6871 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6871 2023/06/05 09:47:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:47:58 - mmengine - INFO - Epoch(train) [91][2569/2569] lr: 4.0000e-02 eta: 11:11:19 time: 0.2570 data_time: 0.0082 memory: 5828 grad_norm: 3.2073 loss: 2.8204 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.8204 2023/06/05 09:48:05 - mmengine - INFO - Epoch(train) [92][ 20/2569] lr: 4.0000e-02 eta: 11:11:14 time: 0.3401 data_time: 0.0557 memory: 5828 grad_norm: 3.1383 loss: 2.2851 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2851 2023/06/05 09:48:10 - mmengine - INFO - Epoch(train) [92][ 40/2569] lr: 4.0000e-02 eta: 11:11:09 time: 0.2659 data_time: 0.0072 memory: 5828 grad_norm: 3.0404 loss: 2.3249 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3249 2023/06/05 09:48:15 - mmengine - INFO - Epoch(train) [92][ 60/2569] lr: 4.0000e-02 eta: 11:11:04 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 3.1152 loss: 2.5480 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5480 2023/06/05 09:48:20 - mmengine - INFO - Epoch(train) [92][ 80/2569] lr: 4.0000e-02 eta: 11:10:58 time: 0.2592 data_time: 0.0077 memory: 5828 grad_norm: 3.1488 loss: 2.3980 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3980 2023/06/05 09:48:26 - mmengine - INFO - Epoch(train) [92][ 100/2569] lr: 4.0000e-02 eta: 11:10:53 time: 0.2597 data_time: 0.0076 memory: 5828 grad_norm: 3.1362 loss: 2.4026 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4026 2023/06/05 09:48:31 - mmengine - INFO - Epoch(train) [92][ 120/2569] lr: 4.0000e-02 eta: 11:10:47 time: 0.2674 data_time: 0.0077 memory: 5828 grad_norm: 3.1852 loss: 2.1587 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1587 2023/06/05 09:48:36 - mmengine - INFO - Epoch(train) [92][ 140/2569] lr: 4.0000e-02 eta: 11:10:42 time: 0.2594 data_time: 0.0081 memory: 5828 grad_norm: 3.1114 loss: 2.3577 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3577 2023/06/05 09:48:41 - mmengine - INFO - Epoch(train) [92][ 160/2569] lr: 4.0000e-02 eta: 11:10:37 time: 0.2651 data_time: 0.0078 memory: 5828 grad_norm: 3.1323 loss: 2.3975 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3975 2023/06/05 09:48:47 - mmengine - INFO - Epoch(train) [92][ 180/2569] lr: 4.0000e-02 eta: 11:10:31 time: 0.2653 data_time: 0.0078 memory: 5828 grad_norm: 3.1565 loss: 2.4635 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4635 2023/06/05 09:48:52 - mmengine - INFO - Epoch(train) [92][ 200/2569] lr: 4.0000e-02 eta: 11:10:26 time: 0.2658 data_time: 0.0076 memory: 5828 grad_norm: 3.1993 loss: 2.4104 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4104 2023/06/05 09:48:57 - mmengine - INFO - Epoch(train) [92][ 220/2569] lr: 4.0000e-02 eta: 11:10:21 time: 0.2660 data_time: 0.0082 memory: 5828 grad_norm: 3.1509 loss: 2.7566 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7566 2023/06/05 09:48:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:49:03 - mmengine - INFO - Epoch(train) [92][ 240/2569] lr: 4.0000e-02 eta: 11:10:16 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 3.1499 loss: 2.5201 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5201 2023/06/05 09:49:08 - mmengine - INFO - Epoch(train) [92][ 260/2569] lr: 4.0000e-02 eta: 11:10:10 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 3.1817 loss: 2.6140 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6140 2023/06/05 09:49:13 - mmengine - INFO - Epoch(train) [92][ 280/2569] lr: 4.0000e-02 eta: 11:10:05 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 3.1449 loss: 2.3529 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3529 2023/06/05 09:49:19 - mmengine - INFO - Epoch(train) [92][ 300/2569] lr: 4.0000e-02 eta: 11:10:00 time: 0.2670 data_time: 0.0082 memory: 5828 grad_norm: 3.1689 loss: 2.7236 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7236 2023/06/05 09:49:24 - mmengine - INFO - Epoch(train) [92][ 320/2569] lr: 4.0000e-02 eta: 11:09:54 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 3.1456 loss: 2.3517 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3517 2023/06/05 09:49:29 - mmengine - INFO - Epoch(train) [92][ 340/2569] lr: 4.0000e-02 eta: 11:09:49 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 3.2005 loss: 2.2976 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.2976 2023/06/05 09:49:34 - mmengine - INFO - Epoch(train) [92][ 360/2569] lr: 4.0000e-02 eta: 11:09:43 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 3.1644 loss: 2.3870 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3870 2023/06/05 09:49:40 - mmengine - INFO - Epoch(train) [92][ 380/2569] lr: 4.0000e-02 eta: 11:09:38 time: 0.2738 data_time: 0.0075 memory: 5828 grad_norm: 3.1539 loss: 2.5671 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5671 2023/06/05 09:49:45 - mmengine - INFO - Epoch(train) [92][ 400/2569] lr: 4.0000e-02 eta: 11:09:33 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 3.1967 loss: 2.3483 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3483 2023/06/05 09:49:51 - mmengine - INFO - Epoch(train) [92][ 420/2569] lr: 4.0000e-02 eta: 11:09:28 time: 0.2772 data_time: 0.0082 memory: 5828 grad_norm: 3.1723 loss: 2.1060 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1060 2023/06/05 09:49:56 - mmengine - INFO - Epoch(train) [92][ 440/2569] lr: 4.0000e-02 eta: 11:09:22 time: 0.2651 data_time: 0.0085 memory: 5828 grad_norm: 3.1721 loss: 2.7021 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7021 2023/06/05 09:50:02 - mmengine - INFO - Epoch(train) [92][ 460/2569] lr: 4.0000e-02 eta: 11:09:17 time: 0.2705 data_time: 0.0069 memory: 5828 grad_norm: 3.1125 loss: 2.1862 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1862 2023/06/05 09:50:07 - mmengine - INFO - Epoch(train) [92][ 480/2569] lr: 4.0000e-02 eta: 11:09:12 time: 0.2726 data_time: 0.0073 memory: 5828 grad_norm: 3.0932 loss: 2.2394 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2394 2023/06/05 09:50:12 - mmengine - INFO - Epoch(train) [92][ 500/2569] lr: 4.0000e-02 eta: 11:09:07 time: 0.2595 data_time: 0.0072 memory: 5828 grad_norm: 3.1061 loss: 2.3443 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3443 2023/06/05 09:50:18 - mmengine - INFO - Epoch(train) [92][ 520/2569] lr: 4.0000e-02 eta: 11:09:01 time: 0.2730 data_time: 0.0072 memory: 5828 grad_norm: 3.0699 loss: 2.4096 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4096 2023/06/05 09:50:23 - mmengine - INFO - Epoch(train) [92][ 540/2569] lr: 4.0000e-02 eta: 11:08:56 time: 0.2598 data_time: 0.0080 memory: 5828 grad_norm: 3.1429 loss: 2.6638 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6638 2023/06/05 09:50:28 - mmengine - INFO - Epoch(train) [92][ 560/2569] lr: 4.0000e-02 eta: 11:08:51 time: 0.2654 data_time: 0.0074 memory: 5828 grad_norm: 3.1622 loss: 2.4874 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4874 2023/06/05 09:50:34 - mmengine - INFO - Epoch(train) [92][ 580/2569] lr: 4.0000e-02 eta: 11:08:45 time: 0.2651 data_time: 0.0080 memory: 5828 grad_norm: 3.1321 loss: 2.4567 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4567 2023/06/05 09:50:39 - mmengine - INFO - Epoch(train) [92][ 600/2569] lr: 4.0000e-02 eta: 11:08:40 time: 0.2724 data_time: 0.0081 memory: 5828 grad_norm: 3.1700 loss: 2.4697 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4697 2023/06/05 09:50:45 - mmengine - INFO - Epoch(train) [92][ 620/2569] lr: 4.0000e-02 eta: 11:08:35 time: 0.2781 data_time: 0.0070 memory: 5828 grad_norm: 3.1818 loss: 2.5143 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5143 2023/06/05 09:50:50 - mmengine - INFO - Epoch(train) [92][ 640/2569] lr: 4.0000e-02 eta: 11:08:30 time: 0.2588 data_time: 0.0088 memory: 5828 grad_norm: 3.1084 loss: 2.9191 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9191 2023/06/05 09:50:55 - mmengine - INFO - Epoch(train) [92][ 660/2569] lr: 4.0000e-02 eta: 11:08:24 time: 0.2654 data_time: 0.0071 memory: 5828 grad_norm: 3.1294 loss: 2.4089 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4089 2023/06/05 09:51:00 - mmengine - INFO - Epoch(train) [92][ 680/2569] lr: 4.0000e-02 eta: 11:08:19 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 3.1519 loss: 2.6397 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6397 2023/06/05 09:51:06 - mmengine - INFO - Epoch(train) [92][ 700/2569] lr: 4.0000e-02 eta: 11:08:14 time: 0.2700 data_time: 0.0073 memory: 5828 grad_norm: 3.0881 loss: 2.2315 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.2315 2023/06/05 09:51:11 - mmengine - INFO - Epoch(train) [92][ 720/2569] lr: 4.0000e-02 eta: 11:08:08 time: 0.2714 data_time: 0.0083 memory: 5828 grad_norm: 3.1116 loss: 2.6411 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6411 2023/06/05 09:51:17 - mmengine - INFO - Epoch(train) [92][ 740/2569] lr: 4.0000e-02 eta: 11:08:03 time: 0.2708 data_time: 0.0071 memory: 5828 grad_norm: 3.1664 loss: 2.7202 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7202 2023/06/05 09:51:22 - mmengine - INFO - Epoch(train) [92][ 760/2569] lr: 4.0000e-02 eta: 11:07:58 time: 0.2619 data_time: 0.0075 memory: 5828 grad_norm: 3.1857 loss: 2.3487 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3487 2023/06/05 09:51:27 - mmengine - INFO - Epoch(train) [92][ 780/2569] lr: 4.0000e-02 eta: 11:07:53 time: 0.2740 data_time: 0.0074 memory: 5828 grad_norm: 3.1838 loss: 2.7649 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7649 2023/06/05 09:51:33 - mmengine - INFO - Epoch(train) [92][ 800/2569] lr: 4.0000e-02 eta: 11:07:47 time: 0.2597 data_time: 0.0075 memory: 5828 grad_norm: 3.1519 loss: 2.7153 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.7153 2023/06/05 09:51:38 - mmengine - INFO - Epoch(train) [92][ 820/2569] lr: 4.0000e-02 eta: 11:07:42 time: 0.2587 data_time: 0.0074 memory: 5828 grad_norm: 3.1480 loss: 2.6811 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6811 2023/06/05 09:51:43 - mmengine - INFO - Epoch(train) [92][ 840/2569] lr: 4.0000e-02 eta: 11:07:37 time: 0.2701 data_time: 0.0077 memory: 5828 grad_norm: 3.1298 loss: 2.5566 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5566 2023/06/05 09:51:49 - mmengine - INFO - Epoch(train) [92][ 860/2569] lr: 4.0000e-02 eta: 11:07:31 time: 0.2700 data_time: 0.0071 memory: 5828 grad_norm: 3.1973 loss: 2.0472 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0472 2023/06/05 09:51:54 - mmengine - INFO - Epoch(train) [92][ 880/2569] lr: 4.0000e-02 eta: 11:07:26 time: 0.2831 data_time: 0.0077 memory: 5828 grad_norm: 3.1605 loss: 2.3515 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3515 2023/06/05 09:52:00 - mmengine - INFO - Epoch(train) [92][ 900/2569] lr: 4.0000e-02 eta: 11:07:21 time: 0.2658 data_time: 0.0075 memory: 5828 grad_norm: 3.1412 loss: 2.2224 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2224 2023/06/05 09:52:05 - mmengine - INFO - Epoch(train) [92][ 920/2569] lr: 4.0000e-02 eta: 11:07:16 time: 0.2727 data_time: 0.0077 memory: 5828 grad_norm: 3.1261 loss: 2.4167 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4167 2023/06/05 09:52:10 - mmengine - INFO - Epoch(train) [92][ 940/2569] lr: 4.0000e-02 eta: 11:07:10 time: 0.2604 data_time: 0.0076 memory: 5828 grad_norm: 3.1545 loss: 2.5039 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5039 2023/06/05 09:52:16 - mmengine - INFO - Epoch(train) [92][ 960/2569] lr: 4.0000e-02 eta: 11:07:05 time: 0.2653 data_time: 0.0076 memory: 5828 grad_norm: 3.1394 loss: 2.4756 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4756 2023/06/05 09:52:21 - mmengine - INFO - Epoch(train) [92][ 980/2569] lr: 4.0000e-02 eta: 11:07:00 time: 0.2682 data_time: 0.0076 memory: 5828 grad_norm: 3.1973 loss: 2.4775 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4775 2023/06/05 09:52:26 - mmengine - INFO - Epoch(train) [92][1000/2569] lr: 4.0000e-02 eta: 11:06:54 time: 0.2711 data_time: 0.0073 memory: 5828 grad_norm: 3.0848 loss: 2.2919 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2919 2023/06/05 09:52:32 - mmengine - INFO - Epoch(train) [92][1020/2569] lr: 4.0000e-02 eta: 11:06:49 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 3.1969 loss: 2.6651 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6651 2023/06/05 09:52:37 - mmengine - INFO - Epoch(train) [92][1040/2569] lr: 4.0000e-02 eta: 11:06:44 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 3.1684 loss: 2.2441 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.2441 2023/06/05 09:52:42 - mmengine - INFO - Epoch(train) [92][1060/2569] lr: 4.0000e-02 eta: 11:06:38 time: 0.2708 data_time: 0.0073 memory: 5828 grad_norm: 3.1393 loss: 2.8881 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8881 2023/06/05 09:52:48 - mmengine - INFO - Epoch(train) [92][1080/2569] lr: 4.0000e-02 eta: 11:06:33 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 3.1647 loss: 2.6455 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.6455 2023/06/05 09:52:53 - mmengine - INFO - Epoch(train) [92][1100/2569] lr: 4.0000e-02 eta: 11:06:28 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 3.1657 loss: 2.7141 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.7141 2023/06/05 09:52:58 - mmengine - INFO - Epoch(train) [92][1120/2569] lr: 4.0000e-02 eta: 11:06:22 time: 0.2652 data_time: 0.0073 memory: 5828 grad_norm: 3.1152 loss: 2.5898 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5898 2023/06/05 09:53:04 - mmengine - INFO - Epoch(train) [92][1140/2569] lr: 4.0000e-02 eta: 11:06:17 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 3.1072 loss: 2.4746 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4746 2023/06/05 09:53:09 - mmengine - INFO - Epoch(train) [92][1160/2569] lr: 4.0000e-02 eta: 11:06:12 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 3.1065 loss: 2.5378 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5378 2023/06/05 09:53:14 - mmengine - INFO - Epoch(train) [92][1180/2569] lr: 4.0000e-02 eta: 11:06:06 time: 0.2603 data_time: 0.0073 memory: 5828 grad_norm: 3.1551 loss: 2.9044 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.9044 2023/06/05 09:53:19 - mmengine - INFO - Epoch(train) [92][1200/2569] lr: 4.0000e-02 eta: 11:06:01 time: 0.2660 data_time: 0.0077 memory: 5828 grad_norm: 3.1110 loss: 2.2463 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2463 2023/06/05 09:53:25 - mmengine - INFO - Epoch(train) [92][1220/2569] lr: 4.0000e-02 eta: 11:05:56 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 3.1439 loss: 2.3051 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3051 2023/06/05 09:53:25 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:53:30 - mmengine - INFO - Epoch(train) [92][1240/2569] lr: 4.0000e-02 eta: 11:05:50 time: 0.2652 data_time: 0.0076 memory: 5828 grad_norm: 3.1700 loss: 2.3293 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3293 2023/06/05 09:53:35 - mmengine - INFO - Epoch(train) [92][1260/2569] lr: 4.0000e-02 eta: 11:05:45 time: 0.2659 data_time: 0.0083 memory: 5828 grad_norm: 3.1244 loss: 2.3521 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3521 2023/06/05 09:53:41 - mmengine - INFO - Epoch(train) [92][1280/2569] lr: 4.0000e-02 eta: 11:05:40 time: 0.2645 data_time: 0.0076 memory: 5828 grad_norm: 3.1478 loss: 2.7021 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7021 2023/06/05 09:53:46 - mmengine - INFO - Epoch(train) [92][1300/2569] lr: 4.0000e-02 eta: 11:05:34 time: 0.2610 data_time: 0.0074 memory: 5828 grad_norm: 3.0851 loss: 2.7222 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7222 2023/06/05 09:53:51 - mmengine - INFO - Epoch(train) [92][1320/2569] lr: 4.0000e-02 eta: 11:05:29 time: 0.2720 data_time: 0.0075 memory: 5828 grad_norm: 3.1399 loss: 2.6588 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6588 2023/06/05 09:53:57 - mmengine - INFO - Epoch(train) [92][1340/2569] lr: 4.0000e-02 eta: 11:05:24 time: 0.2654 data_time: 0.0071 memory: 5828 grad_norm: 3.1456 loss: 2.2959 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2959 2023/06/05 09:54:02 - mmengine - INFO - Epoch(train) [92][1360/2569] lr: 4.0000e-02 eta: 11:05:19 time: 0.2695 data_time: 0.0071 memory: 5828 grad_norm: 3.0965 loss: 3.0903 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.0903 2023/06/05 09:54:07 - mmengine - INFO - Epoch(train) [92][1380/2569] lr: 4.0000e-02 eta: 11:05:13 time: 0.2693 data_time: 0.0075 memory: 5828 grad_norm: 3.0823 loss: 2.4651 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4651 2023/06/05 09:54:13 - mmengine - INFO - Epoch(train) [92][1400/2569] lr: 4.0000e-02 eta: 11:05:08 time: 0.2657 data_time: 0.0072 memory: 5828 grad_norm: 3.1331 loss: 2.6280 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6280 2023/06/05 09:54:18 - mmengine - INFO - Epoch(train) [92][1420/2569] lr: 4.0000e-02 eta: 11:05:03 time: 0.2659 data_time: 0.0072 memory: 5828 grad_norm: 3.1260 loss: 2.5590 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5590 2023/06/05 09:54:23 - mmengine - INFO - Epoch(train) [92][1440/2569] lr: 4.0000e-02 eta: 11:04:57 time: 0.2705 data_time: 0.0072 memory: 5828 grad_norm: 3.1576 loss: 2.2506 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2506 2023/06/05 09:54:29 - mmengine - INFO - Epoch(train) [92][1460/2569] lr: 4.0000e-02 eta: 11:04:52 time: 0.2653 data_time: 0.0071 memory: 5828 grad_norm: 3.1640 loss: 2.3424 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3424 2023/06/05 09:54:34 - mmengine - INFO - Epoch(train) [92][1480/2569] lr: 4.0000e-02 eta: 11:04:47 time: 0.2662 data_time: 0.0076 memory: 5828 grad_norm: 3.1450 loss: 2.5628 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5628 2023/06/05 09:54:40 - mmengine - INFO - Epoch(train) [92][1500/2569] lr: 4.0000e-02 eta: 11:04:42 time: 0.2694 data_time: 0.0081 memory: 5828 grad_norm: 3.2117 loss: 2.8191 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8191 2023/06/05 09:54:45 - mmengine - INFO - Epoch(train) [92][1520/2569] lr: 4.0000e-02 eta: 11:04:36 time: 0.2681 data_time: 0.0078 memory: 5828 grad_norm: 3.1429 loss: 2.3097 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3097 2023/06/05 09:54:50 - mmengine - INFO - Epoch(train) [92][1540/2569] lr: 4.0000e-02 eta: 11:04:31 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 3.1810 loss: 2.4074 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4074 2023/06/05 09:54:56 - mmengine - INFO - Epoch(train) [92][1560/2569] lr: 4.0000e-02 eta: 11:04:26 time: 0.2677 data_time: 0.0075 memory: 5828 grad_norm: 3.1782 loss: 2.8047 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8047 2023/06/05 09:55:01 - mmengine - INFO - Epoch(train) [92][1580/2569] lr: 4.0000e-02 eta: 11:04:20 time: 0.2593 data_time: 0.0077 memory: 5828 grad_norm: 3.1337 loss: 2.7158 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7158 2023/06/05 09:55:06 - mmengine - INFO - Epoch(train) [92][1600/2569] lr: 4.0000e-02 eta: 11:04:15 time: 0.2724 data_time: 0.0073 memory: 5828 grad_norm: 3.1566 loss: 2.2585 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2585 2023/06/05 09:55:12 - mmengine - INFO - Epoch(train) [92][1620/2569] lr: 4.0000e-02 eta: 11:04:10 time: 0.2642 data_time: 0.0075 memory: 5828 grad_norm: 3.1509 loss: 2.4132 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.4132 2023/06/05 09:55:17 - mmengine - INFO - Epoch(train) [92][1640/2569] lr: 4.0000e-02 eta: 11:04:04 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 3.1780 loss: 2.3248 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3248 2023/06/05 09:55:22 - mmengine - INFO - Epoch(train) [92][1660/2569] lr: 4.0000e-02 eta: 11:03:59 time: 0.2601 data_time: 0.0071 memory: 5828 grad_norm: 3.1742 loss: 2.7429 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.7429 2023/06/05 09:55:28 - mmengine - INFO - Epoch(train) [92][1680/2569] lr: 4.0000e-02 eta: 11:03:54 time: 0.2757 data_time: 0.0072 memory: 5828 grad_norm: 3.1091 loss: 2.4952 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4952 2023/06/05 09:55:33 - mmengine - INFO - Epoch(train) [92][1700/2569] lr: 4.0000e-02 eta: 11:03:48 time: 0.2666 data_time: 0.0071 memory: 5828 grad_norm: 3.1350 loss: 2.3684 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3684 2023/06/05 09:55:38 - mmengine - INFO - Epoch(train) [92][1720/2569] lr: 4.0000e-02 eta: 11:03:43 time: 0.2646 data_time: 0.0076 memory: 5828 grad_norm: 3.1570 loss: 2.5530 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5530 2023/06/05 09:55:43 - mmengine - INFO - Epoch(train) [92][1740/2569] lr: 4.0000e-02 eta: 11:03:38 time: 0.2635 data_time: 0.0075 memory: 5828 grad_norm: 3.1706 loss: 2.3170 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3170 2023/06/05 09:55:49 - mmengine - INFO - Epoch(train) [92][1760/2569] lr: 4.0000e-02 eta: 11:03:32 time: 0.2634 data_time: 0.0078 memory: 5828 grad_norm: 3.1478 loss: 2.6527 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6527 2023/06/05 09:55:54 - mmengine - INFO - Epoch(train) [92][1780/2569] lr: 4.0000e-02 eta: 11:03:27 time: 0.2713 data_time: 0.0076 memory: 5828 grad_norm: 3.2207 loss: 2.5563 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5563 2023/06/05 09:55:59 - mmengine - INFO - Epoch(train) [92][1800/2569] lr: 4.0000e-02 eta: 11:03:22 time: 0.2654 data_time: 0.0083 memory: 5828 grad_norm: 3.0942 loss: 2.3576 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3576 2023/06/05 09:56:05 - mmengine - INFO - Epoch(train) [92][1820/2569] lr: 4.0000e-02 eta: 11:03:17 time: 0.2662 data_time: 0.0074 memory: 5828 grad_norm: 3.1152 loss: 2.5003 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5003 2023/06/05 09:56:10 - mmengine - INFO - Epoch(train) [92][1840/2569] lr: 4.0000e-02 eta: 11:03:11 time: 0.2793 data_time: 0.0076 memory: 5828 grad_norm: 3.1442 loss: 2.7008 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7008 2023/06/05 09:56:16 - mmengine - INFO - Epoch(train) [92][1860/2569] lr: 4.0000e-02 eta: 11:03:06 time: 0.2780 data_time: 0.0071 memory: 5828 grad_norm: 3.1349 loss: 2.4972 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4972 2023/06/05 09:56:21 - mmengine - INFO - Epoch(train) [92][1880/2569] lr: 4.0000e-02 eta: 11:03:01 time: 0.2656 data_time: 0.0084 memory: 5828 grad_norm: 3.1056 loss: 2.7042 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7042 2023/06/05 09:56:27 - mmengine - INFO - Epoch(train) [92][1900/2569] lr: 4.0000e-02 eta: 11:02:56 time: 0.2660 data_time: 0.0071 memory: 5828 grad_norm: 3.1555 loss: 2.4536 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4536 2023/06/05 09:56:32 - mmengine - INFO - Epoch(train) [92][1920/2569] lr: 4.0000e-02 eta: 11:02:50 time: 0.2656 data_time: 0.0072 memory: 5828 grad_norm: 3.1990 loss: 2.8993 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8993 2023/06/05 09:56:37 - mmengine - INFO - Epoch(train) [92][1940/2569] lr: 4.0000e-02 eta: 11:02:45 time: 0.2595 data_time: 0.0070 memory: 5828 grad_norm: 3.1249 loss: 2.6721 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6721 2023/06/05 09:56:43 - mmengine - INFO - Epoch(train) [92][1960/2569] lr: 4.0000e-02 eta: 11:02:40 time: 0.2780 data_time: 0.0077 memory: 5828 grad_norm: 3.2002 loss: 2.7261 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7261 2023/06/05 09:56:48 - mmengine - INFO - Epoch(train) [92][1980/2569] lr: 4.0000e-02 eta: 11:02:34 time: 0.2629 data_time: 0.0070 memory: 5828 grad_norm: 3.1517 loss: 2.6297 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 2.6297 2023/06/05 09:56:53 - mmengine - INFO - Epoch(train) [92][2000/2569] lr: 4.0000e-02 eta: 11:02:29 time: 0.2727 data_time: 0.0074 memory: 5828 grad_norm: 3.2084 loss: 2.4202 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4202 2023/06/05 09:56:59 - mmengine - INFO - Epoch(train) [92][2020/2569] lr: 4.0000e-02 eta: 11:02:24 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.0881 loss: 2.4152 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4152 2023/06/05 09:57:04 - mmengine - INFO - Epoch(train) [92][2040/2569] lr: 4.0000e-02 eta: 11:02:19 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 3.1263 loss: 2.3193 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3193 2023/06/05 09:57:09 - mmengine - INFO - Epoch(train) [92][2060/2569] lr: 4.0000e-02 eta: 11:02:13 time: 0.2702 data_time: 0.0078 memory: 5828 grad_norm: 3.1529 loss: 2.8834 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8834 2023/06/05 09:57:15 - mmengine - INFO - Epoch(train) [92][2080/2569] lr: 4.0000e-02 eta: 11:02:08 time: 0.2616 data_time: 0.0069 memory: 5828 grad_norm: 3.2062 loss: 2.4847 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4847 2023/06/05 09:57:20 - mmengine - INFO - Epoch(train) [92][2100/2569] lr: 4.0000e-02 eta: 11:02:03 time: 0.2651 data_time: 0.0070 memory: 5828 grad_norm: 3.1261 loss: 2.6526 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6526 2023/06/05 09:57:25 - mmengine - INFO - Epoch(train) [92][2120/2569] lr: 4.0000e-02 eta: 11:01:57 time: 0.2723 data_time: 0.0080 memory: 5828 grad_norm: 3.1692 loss: 3.0140 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 3.0140 2023/06/05 09:57:31 - mmengine - INFO - Epoch(train) [92][2140/2569] lr: 4.0000e-02 eta: 11:01:52 time: 0.2702 data_time: 0.0070 memory: 5828 grad_norm: 3.1055 loss: 2.8840 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8840 2023/06/05 09:57:36 - mmengine - INFO - Epoch(train) [92][2160/2569] lr: 4.0000e-02 eta: 11:01:47 time: 0.2671 data_time: 0.0075 memory: 5828 grad_norm: 3.0736 loss: 2.4583 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4583 2023/06/05 09:57:42 - mmengine - INFO - Epoch(train) [92][2180/2569] lr: 4.0000e-02 eta: 11:01:42 time: 0.2786 data_time: 0.0074 memory: 5828 grad_norm: 3.2019 loss: 2.2668 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2668 2023/06/05 09:57:47 - mmengine - INFO - Epoch(train) [92][2200/2569] lr: 4.0000e-02 eta: 11:01:36 time: 0.2604 data_time: 0.0075 memory: 5828 grad_norm: 3.2443 loss: 2.7550 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7550 2023/06/05 09:57:53 - mmengine - INFO - Epoch(train) [92][2220/2569] lr: 4.0000e-02 eta: 11:01:31 time: 0.2761 data_time: 0.0067 memory: 5828 grad_norm: 3.0828 loss: 2.6247 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6247 2023/06/05 09:57:53 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:57:58 - mmengine - INFO - Epoch(train) [92][2240/2569] lr: 4.0000e-02 eta: 11:01:26 time: 0.2661 data_time: 0.0071 memory: 5828 grad_norm: 3.1641 loss: 2.4522 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4522 2023/06/05 09:58:03 - mmengine - INFO - Epoch(train) [92][2260/2569] lr: 4.0000e-02 eta: 11:01:21 time: 0.2721 data_time: 0.0078 memory: 5828 grad_norm: 3.1439 loss: 2.6361 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6361 2023/06/05 09:58:09 - mmengine - INFO - Epoch(train) [92][2280/2569] lr: 4.0000e-02 eta: 11:01:15 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 3.0945 loss: 2.5126 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5126 2023/06/05 09:58:14 - mmengine - INFO - Epoch(train) [92][2300/2569] lr: 4.0000e-02 eta: 11:01:10 time: 0.2785 data_time: 0.0071 memory: 5828 grad_norm: 3.1629 loss: 2.6261 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6261 2023/06/05 09:58:20 - mmengine - INFO - Epoch(train) [92][2320/2569] lr: 4.0000e-02 eta: 11:01:05 time: 0.2688 data_time: 0.0072 memory: 5828 grad_norm: 3.1005 loss: 2.8938 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.8938 2023/06/05 09:58:25 - mmengine - INFO - Epoch(train) [92][2340/2569] lr: 4.0000e-02 eta: 11:01:00 time: 0.2786 data_time: 0.0073 memory: 5828 grad_norm: 3.1554 loss: 2.3961 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3961 2023/06/05 09:58:30 - mmengine - INFO - Epoch(train) [92][2360/2569] lr: 4.0000e-02 eta: 11:00:54 time: 0.2612 data_time: 0.0076 memory: 5828 grad_norm: 3.0911 loss: 2.6957 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6957 2023/06/05 09:58:36 - mmengine - INFO - Epoch(train) [92][2380/2569] lr: 4.0000e-02 eta: 11:00:49 time: 0.2672 data_time: 0.0077 memory: 5828 grad_norm: 3.1167 loss: 2.4430 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4430 2023/06/05 09:58:41 - mmengine - INFO - Epoch(train) [92][2400/2569] lr: 4.0000e-02 eta: 11:00:44 time: 0.2605 data_time: 0.0084 memory: 5828 grad_norm: 3.1504 loss: 2.3689 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3689 2023/06/05 09:58:46 - mmengine - INFO - Epoch(train) [92][2420/2569] lr: 4.0000e-02 eta: 11:00:38 time: 0.2695 data_time: 0.0075 memory: 5828 grad_norm: 3.1173 loss: 2.4447 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4447 2023/06/05 09:58:52 - mmengine - INFO - Epoch(train) [92][2440/2569] lr: 4.0000e-02 eta: 11:00:33 time: 0.2617 data_time: 0.0075 memory: 5828 grad_norm: 3.0936 loss: 2.4350 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4350 2023/06/05 09:58:57 - mmengine - INFO - Epoch(train) [92][2460/2569] lr: 4.0000e-02 eta: 11:00:28 time: 0.2714 data_time: 0.0075 memory: 5828 grad_norm: 3.1408 loss: 2.5485 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5485 2023/06/05 09:59:02 - mmengine - INFO - Epoch(train) [92][2480/2569] lr: 4.0000e-02 eta: 11:00:22 time: 0.2603 data_time: 0.0074 memory: 5828 grad_norm: 3.1321 loss: 2.5387 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5387 2023/06/05 09:59:08 - mmengine - INFO - Epoch(train) [92][2500/2569] lr: 4.0000e-02 eta: 11:00:17 time: 0.2720 data_time: 0.0083 memory: 5828 grad_norm: 3.0640 loss: 2.4020 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.4020 2023/06/05 09:59:13 - mmengine - INFO - Epoch(train) [92][2520/2569] lr: 4.0000e-02 eta: 11:00:12 time: 0.2591 data_time: 0.0075 memory: 5828 grad_norm: 3.1677 loss: 2.8887 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8887 2023/06/05 09:59:18 - mmengine - INFO - Epoch(train) [92][2540/2569] lr: 4.0000e-02 eta: 11:00:06 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 3.1184 loss: 2.2853 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2853 2023/06/05 09:59:23 - mmengine - INFO - Epoch(train) [92][2560/2569] lr: 4.0000e-02 eta: 11:00:01 time: 0.2588 data_time: 0.0071 memory: 5828 grad_norm: 3.1331 loss: 2.3522 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3522 2023/06/05 09:59:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 09:59:26 - mmengine - INFO - Epoch(train) [92][2569/2569] lr: 4.0000e-02 eta: 10:59:58 time: 0.2512 data_time: 0.0070 memory: 5828 grad_norm: 3.0998 loss: 2.3170 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 2.3170 2023/06/05 09:59:26 - mmengine - INFO - Saving checkpoint at 92 epochs 2023/06/05 09:59:33 - mmengine - INFO - Epoch(train) [93][ 20/2569] lr: 4.0000e-02 eta: 10:59:53 time: 0.2948 data_time: 0.0375 memory: 5828 grad_norm: 3.1964 loss: 2.4365 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4365 2023/06/05 09:59:39 - mmengine - INFO - Epoch(train) [93][ 40/2569] lr: 4.0000e-02 eta: 10:59:48 time: 0.2692 data_time: 0.0069 memory: 5828 grad_norm: 3.1543 loss: 2.3811 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3811 2023/06/05 09:59:44 - mmengine - INFO - Epoch(train) [93][ 60/2569] lr: 4.0000e-02 eta: 10:59:43 time: 0.2596 data_time: 0.0071 memory: 5828 grad_norm: 3.0941 loss: 2.5540 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5540 2023/06/05 09:59:49 - mmengine - INFO - Epoch(train) [93][ 80/2569] lr: 4.0000e-02 eta: 10:59:37 time: 0.2683 data_time: 0.0077 memory: 5828 grad_norm: 3.1149 loss: 2.6513 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6513 2023/06/05 09:59:55 - mmengine - INFO - Epoch(train) [93][ 100/2569] lr: 4.0000e-02 eta: 10:59:32 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 3.1265 loss: 2.3223 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3223 2023/06/05 10:00:00 - mmengine - INFO - Epoch(train) [93][ 120/2569] lr: 4.0000e-02 eta: 10:59:27 time: 0.2657 data_time: 0.0072 memory: 5828 grad_norm: 3.1053 loss: 2.4681 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4681 2023/06/05 10:00:05 - mmengine - INFO - Epoch(train) [93][ 140/2569] lr: 4.0000e-02 eta: 10:59:21 time: 0.2590 data_time: 0.0071 memory: 5828 grad_norm: 3.1715 loss: 2.3710 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3710 2023/06/05 10:00:10 - mmengine - INFO - Epoch(train) [93][ 160/2569] lr: 4.0000e-02 eta: 10:59:16 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 3.1689 loss: 2.5008 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5008 2023/06/05 10:00:16 - mmengine - INFO - Epoch(train) [93][ 180/2569] lr: 4.0000e-02 eta: 10:59:11 time: 0.2696 data_time: 0.0071 memory: 5828 grad_norm: 3.1662 loss: 2.5702 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5702 2023/06/05 10:00:21 - mmengine - INFO - Epoch(train) [93][ 200/2569] lr: 4.0000e-02 eta: 10:59:06 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 3.0599 loss: 2.3168 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3168 2023/06/05 10:00:27 - mmengine - INFO - Epoch(train) [93][ 220/2569] lr: 4.0000e-02 eta: 10:59:00 time: 0.2684 data_time: 0.0069 memory: 5828 grad_norm: 3.1473 loss: 2.3564 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3564 2023/06/05 10:00:32 - mmengine - INFO - Epoch(train) [93][ 240/2569] lr: 4.0000e-02 eta: 10:58:55 time: 0.2659 data_time: 0.0076 memory: 5828 grad_norm: 3.0980 loss: 2.5166 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5166 2023/06/05 10:00:37 - mmengine - INFO - Epoch(train) [93][ 260/2569] lr: 4.0000e-02 eta: 10:58:50 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 3.0957 loss: 2.3770 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3770 2023/06/05 10:00:43 - mmengine - INFO - Epoch(train) [93][ 280/2569] lr: 4.0000e-02 eta: 10:58:44 time: 0.2683 data_time: 0.0077 memory: 5828 grad_norm: 3.1769 loss: 2.6315 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6315 2023/06/05 10:00:48 - mmengine - INFO - Epoch(train) [93][ 300/2569] lr: 4.0000e-02 eta: 10:58:39 time: 0.2712 data_time: 0.0078 memory: 5828 grad_norm: 3.1886 loss: 2.8433 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.8433 2023/06/05 10:00:53 - mmengine - INFO - Epoch(train) [93][ 320/2569] lr: 4.0000e-02 eta: 10:58:34 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 3.1984 loss: 2.3454 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3454 2023/06/05 10:00:59 - mmengine - INFO - Epoch(train) [93][ 340/2569] lr: 4.0000e-02 eta: 10:58:28 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 3.1580 loss: 2.4806 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4806 2023/06/05 10:01:04 - mmengine - INFO - Epoch(train) [93][ 360/2569] lr: 4.0000e-02 eta: 10:58:23 time: 0.2662 data_time: 0.0079 memory: 5828 grad_norm: 3.2054 loss: 2.4916 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4916 2023/06/05 10:01:09 - mmengine - INFO - Epoch(train) [93][ 380/2569] lr: 4.0000e-02 eta: 10:58:18 time: 0.2597 data_time: 0.0071 memory: 5828 grad_norm: 3.1634 loss: 2.4787 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4787 2023/06/05 10:01:14 - mmengine - INFO - Epoch(train) [93][ 400/2569] lr: 4.0000e-02 eta: 10:58:12 time: 0.2601 data_time: 0.0079 memory: 5828 grad_norm: 3.1066 loss: 2.3176 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3176 2023/06/05 10:01:20 - mmengine - INFO - Epoch(train) [93][ 420/2569] lr: 4.0000e-02 eta: 10:58:07 time: 0.2609 data_time: 0.0070 memory: 5828 grad_norm: 3.1105 loss: 2.3532 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3532 2023/06/05 10:01:25 - mmengine - INFO - Epoch(train) [93][ 440/2569] lr: 4.0000e-02 eta: 10:58:02 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 3.1365 loss: 2.2975 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2975 2023/06/05 10:01:30 - mmengine - INFO - Epoch(train) [93][ 460/2569] lr: 4.0000e-02 eta: 10:57:56 time: 0.2614 data_time: 0.0069 memory: 5828 grad_norm: 3.0949 loss: 2.2449 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2449 2023/06/05 10:01:35 - mmengine - INFO - Epoch(train) [93][ 480/2569] lr: 4.0000e-02 eta: 10:57:51 time: 0.2603 data_time: 0.0073 memory: 5828 grad_norm: 3.0880 loss: 2.5569 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5569 2023/06/05 10:01:41 - mmengine - INFO - Epoch(train) [93][ 500/2569] lr: 4.0000e-02 eta: 10:57:45 time: 0.2626 data_time: 0.0092 memory: 5828 grad_norm: 3.1708 loss: 2.7592 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7592 2023/06/05 10:01:46 - mmengine - INFO - Epoch(train) [93][ 520/2569] lr: 4.0000e-02 eta: 10:57:40 time: 0.2626 data_time: 0.0073 memory: 5828 grad_norm: 3.1099 loss: 2.4753 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4753 2023/06/05 10:01:51 - mmengine - INFO - Epoch(train) [93][ 540/2569] lr: 4.0000e-02 eta: 10:57:35 time: 0.2816 data_time: 0.0090 memory: 5828 grad_norm: 3.1849 loss: 2.4131 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4131 2023/06/05 10:01:57 - mmengine - INFO - Epoch(train) [93][ 560/2569] lr: 4.0000e-02 eta: 10:57:30 time: 0.2584 data_time: 0.0073 memory: 5828 grad_norm: 3.1761 loss: 2.8103 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8103 2023/06/05 10:02:02 - mmengine - INFO - Epoch(train) [93][ 580/2569] lr: 4.0000e-02 eta: 10:57:24 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 3.1437 loss: 2.8343 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8343 2023/06/05 10:02:07 - mmengine - INFO - Epoch(train) [93][ 600/2569] lr: 4.0000e-02 eta: 10:57:19 time: 0.2667 data_time: 0.0071 memory: 5828 grad_norm: 3.1394 loss: 2.7112 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7112 2023/06/05 10:02:13 - mmengine - INFO - Epoch(train) [93][ 620/2569] lr: 4.0000e-02 eta: 10:57:14 time: 0.2651 data_time: 0.0070 memory: 5828 grad_norm: 3.1277 loss: 2.6957 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6957 2023/06/05 10:02:18 - mmengine - INFO - Epoch(train) [93][ 640/2569] lr: 4.0000e-02 eta: 10:57:08 time: 0.2658 data_time: 0.0076 memory: 5828 grad_norm: 3.1387 loss: 2.4216 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4216 2023/06/05 10:02:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:02:23 - mmengine - INFO - Epoch(train) [93][ 660/2569] lr: 4.0000e-02 eta: 10:57:03 time: 0.2659 data_time: 0.0072 memory: 5828 grad_norm: 3.1365 loss: 2.5283 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5283 2023/06/05 10:02:29 - mmengine - INFO - Epoch(train) [93][ 680/2569] lr: 4.0000e-02 eta: 10:56:58 time: 0.2621 data_time: 0.0071 memory: 5828 grad_norm: 3.0922 loss: 2.6016 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6016 2023/06/05 10:02:34 - mmengine - INFO - Epoch(train) [93][ 700/2569] lr: 4.0000e-02 eta: 10:56:52 time: 0.2624 data_time: 0.0070 memory: 5828 grad_norm: 3.0530 loss: 2.2731 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2731 2023/06/05 10:02:39 - mmengine - INFO - Epoch(train) [93][ 720/2569] lr: 4.0000e-02 eta: 10:56:47 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 3.1110 loss: 2.4189 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4189 2023/06/05 10:02:44 - mmengine - INFO - Epoch(train) [93][ 740/2569] lr: 4.0000e-02 eta: 10:56:42 time: 0.2592 data_time: 0.0073 memory: 5828 grad_norm: 3.1636 loss: 2.6124 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6124 2023/06/05 10:02:50 - mmengine - INFO - Epoch(train) [93][ 760/2569] lr: 4.0000e-02 eta: 10:56:36 time: 0.2647 data_time: 0.0076 memory: 5828 grad_norm: 3.1491 loss: 2.5852 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5852 2023/06/05 10:02:55 - mmengine - INFO - Epoch(train) [93][ 780/2569] lr: 4.0000e-02 eta: 10:56:31 time: 0.2684 data_time: 0.0068 memory: 5828 grad_norm: 3.1804 loss: 2.4838 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4838 2023/06/05 10:03:00 - mmengine - INFO - Epoch(train) [93][ 800/2569] lr: 4.0000e-02 eta: 10:56:26 time: 0.2662 data_time: 0.0072 memory: 5828 grad_norm: 3.1805 loss: 2.5523 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5523 2023/06/05 10:03:06 - mmengine - INFO - Epoch(train) [93][ 820/2569] lr: 4.0000e-02 eta: 10:56:20 time: 0.2648 data_time: 0.0070 memory: 5828 grad_norm: 3.1387 loss: 2.5645 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5645 2023/06/05 10:03:11 - mmengine - INFO - Epoch(train) [93][ 840/2569] lr: 4.0000e-02 eta: 10:56:15 time: 0.2719 data_time: 0.0072 memory: 5828 grad_norm: 3.1117 loss: 2.3730 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3730 2023/06/05 10:03:16 - mmengine - INFO - Epoch(train) [93][ 860/2569] lr: 4.0000e-02 eta: 10:56:10 time: 0.2644 data_time: 0.0070 memory: 5828 grad_norm: 3.1244 loss: 2.5342 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5342 2023/06/05 10:03:22 - mmengine - INFO - Epoch(train) [93][ 880/2569] lr: 4.0000e-02 eta: 10:56:05 time: 0.2701 data_time: 0.0071 memory: 5828 grad_norm: 3.1877 loss: 2.3298 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3298 2023/06/05 10:03:27 - mmengine - INFO - Epoch(train) [93][ 900/2569] lr: 4.0000e-02 eta: 10:55:59 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 3.1322 loss: 2.4976 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4976 2023/06/05 10:03:32 - mmengine - INFO - Epoch(train) [93][ 920/2569] lr: 4.0000e-02 eta: 10:55:54 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.1061 loss: 2.5058 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5058 2023/06/05 10:03:38 - mmengine - INFO - Epoch(train) [93][ 940/2569] lr: 4.0000e-02 eta: 10:55:48 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 3.1767 loss: 2.4415 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4415 2023/06/05 10:03:43 - mmengine - INFO - Epoch(train) [93][ 960/2569] lr: 4.0000e-02 eta: 10:55:43 time: 0.2666 data_time: 0.0072 memory: 5828 grad_norm: 3.0972 loss: 2.5667 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5667 2023/06/05 10:03:48 - mmengine - INFO - Epoch(train) [93][ 980/2569] lr: 4.0000e-02 eta: 10:55:38 time: 0.2730 data_time: 0.0071 memory: 5828 grad_norm: 3.1235 loss: 2.2861 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2861 2023/06/05 10:03:54 - mmengine - INFO - Epoch(train) [93][1000/2569] lr: 4.0000e-02 eta: 10:55:33 time: 0.2672 data_time: 0.0069 memory: 5828 grad_norm: 3.1858 loss: 2.6472 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6472 2023/06/05 10:03:59 - mmengine - INFO - Epoch(train) [93][1020/2569] lr: 4.0000e-02 eta: 10:55:27 time: 0.2599 data_time: 0.0073 memory: 5828 grad_norm: 3.1614 loss: 2.8344 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8344 2023/06/05 10:04:04 - mmengine - INFO - Epoch(train) [93][1040/2569] lr: 4.0000e-02 eta: 10:55:22 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.1520 loss: 2.4779 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4779 2023/06/05 10:04:10 - mmengine - INFO - Epoch(train) [93][1060/2569] lr: 4.0000e-02 eta: 10:55:17 time: 0.2702 data_time: 0.0073 memory: 5828 grad_norm: 3.1650 loss: 2.7962 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7962 2023/06/05 10:04:15 - mmengine - INFO - Epoch(train) [93][1080/2569] lr: 4.0000e-02 eta: 10:55:11 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.1168 loss: 2.4525 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4525 2023/06/05 10:04:20 - mmengine - INFO - Epoch(train) [93][1100/2569] lr: 4.0000e-02 eta: 10:55:06 time: 0.2734 data_time: 0.0074 memory: 5828 grad_norm: 3.1328 loss: 2.3118 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3118 2023/06/05 10:04:26 - mmengine - INFO - Epoch(train) [93][1120/2569] lr: 4.0000e-02 eta: 10:55:01 time: 0.2669 data_time: 0.0069 memory: 5828 grad_norm: 3.1465 loss: 2.2971 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2971 2023/06/05 10:04:31 - mmengine - INFO - Epoch(train) [93][1140/2569] lr: 4.0000e-02 eta: 10:54:55 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 3.1138 loss: 2.4229 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4229 2023/06/05 10:04:37 - mmengine - INFO - Epoch(train) [93][1160/2569] lr: 4.0000e-02 eta: 10:54:50 time: 0.2722 data_time: 0.0080 memory: 5828 grad_norm: 3.1604 loss: 2.6668 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.6668 2023/06/05 10:04:42 - mmengine - INFO - Epoch(train) [93][1180/2569] lr: 4.0000e-02 eta: 10:54:45 time: 0.2647 data_time: 0.0071 memory: 5828 grad_norm: 3.1532 loss: 2.4737 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4737 2023/06/05 10:04:47 - mmengine - INFO - Epoch(train) [93][1200/2569] lr: 4.0000e-02 eta: 10:54:40 time: 0.2656 data_time: 0.0076 memory: 5828 grad_norm: 3.1525 loss: 2.5524 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5524 2023/06/05 10:04:53 - mmengine - INFO - Epoch(train) [93][1220/2569] lr: 4.0000e-02 eta: 10:54:34 time: 0.2700 data_time: 0.0078 memory: 5828 grad_norm: 3.1399 loss: 2.6275 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6275 2023/06/05 10:04:58 - mmengine - INFO - Epoch(train) [93][1240/2569] lr: 4.0000e-02 eta: 10:54:29 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 3.2265 loss: 2.4151 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4151 2023/06/05 10:05:03 - mmengine - INFO - Epoch(train) [93][1260/2569] lr: 4.0000e-02 eta: 10:54:24 time: 0.2659 data_time: 0.0077 memory: 5828 grad_norm: 3.1443 loss: 2.7282 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7282 2023/06/05 10:05:08 - mmengine - INFO - Epoch(train) [93][1280/2569] lr: 4.0000e-02 eta: 10:54:18 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 3.2011 loss: 2.4225 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4225 2023/06/05 10:05:14 - mmengine - INFO - Epoch(train) [93][1300/2569] lr: 4.0000e-02 eta: 10:54:13 time: 0.2591 data_time: 0.0073 memory: 5828 grad_norm: 3.1019 loss: 2.4505 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.4505 2023/06/05 10:05:19 - mmengine - INFO - Epoch(train) [93][1320/2569] lr: 4.0000e-02 eta: 10:54:08 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 3.0621 loss: 2.5718 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5718 2023/06/05 10:05:24 - mmengine - INFO - Epoch(train) [93][1340/2569] lr: 4.0000e-02 eta: 10:54:02 time: 0.2735 data_time: 0.0073 memory: 5828 grad_norm: 3.1897 loss: 2.6432 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6432 2023/06/05 10:05:30 - mmengine - INFO - Epoch(train) [93][1360/2569] lr: 4.0000e-02 eta: 10:53:57 time: 0.2716 data_time: 0.0074 memory: 5828 grad_norm: 3.1143 loss: 2.5491 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5491 2023/06/05 10:05:35 - mmengine - INFO - Epoch(train) [93][1380/2569] lr: 4.0000e-02 eta: 10:53:52 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 3.1197 loss: 2.3020 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3020 2023/06/05 10:05:41 - mmengine - INFO - Epoch(train) [93][1400/2569] lr: 4.0000e-02 eta: 10:53:47 time: 0.2738 data_time: 0.0071 memory: 5828 grad_norm: 3.1893 loss: 2.6384 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6384 2023/06/05 10:05:46 - mmengine - INFO - Epoch(train) [93][1420/2569] lr: 4.0000e-02 eta: 10:53:41 time: 0.2641 data_time: 0.0070 memory: 5828 grad_norm: 3.2260 loss: 2.6434 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6434 2023/06/05 10:05:51 - mmengine - INFO - Epoch(train) [93][1440/2569] lr: 4.0000e-02 eta: 10:53:36 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 3.1349 loss: 2.5005 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5005 2023/06/05 10:05:57 - mmengine - INFO - Epoch(train) [93][1460/2569] lr: 4.0000e-02 eta: 10:53:31 time: 0.2687 data_time: 0.0072 memory: 5828 grad_norm: 3.1411 loss: 2.3064 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3064 2023/06/05 10:06:02 - mmengine - INFO - Epoch(train) [93][1480/2569] lr: 4.0000e-02 eta: 10:53:25 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 3.0930 loss: 2.6544 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6544 2023/06/05 10:06:07 - mmengine - INFO - Epoch(train) [93][1500/2569] lr: 4.0000e-02 eta: 10:53:20 time: 0.2704 data_time: 0.0076 memory: 5828 grad_norm: 3.2434 loss: 2.4080 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4080 2023/06/05 10:06:13 - mmengine - INFO - Epoch(train) [93][1520/2569] lr: 4.0000e-02 eta: 10:53:15 time: 0.2680 data_time: 0.0072 memory: 5828 grad_norm: 3.1534 loss: 2.6369 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6369 2023/06/05 10:06:18 - mmengine - INFO - Epoch(train) [93][1540/2569] lr: 4.0000e-02 eta: 10:53:10 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 3.1536 loss: 2.3880 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3880 2023/06/05 10:06:24 - mmengine - INFO - Epoch(train) [93][1560/2569] lr: 4.0000e-02 eta: 10:53:04 time: 0.2691 data_time: 0.0075 memory: 5828 grad_norm: 3.1053 loss: 2.5241 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5241 2023/06/05 10:06:29 - mmengine - INFO - Epoch(train) [93][1580/2569] lr: 4.0000e-02 eta: 10:52:59 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 3.1781 loss: 2.3894 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.3894 2023/06/05 10:06:34 - mmengine - INFO - Epoch(train) [93][1600/2569] lr: 4.0000e-02 eta: 10:52:54 time: 0.2600 data_time: 0.0072 memory: 5828 grad_norm: 3.1200 loss: 2.6126 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.6126 2023/06/05 10:06:39 - mmengine - INFO - Epoch(train) [93][1620/2569] lr: 4.0000e-02 eta: 10:52:48 time: 0.2706 data_time: 0.0075 memory: 5828 grad_norm: 3.1556 loss: 2.3673 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3673 2023/06/05 10:06:45 - mmengine - INFO - Epoch(train) [93][1640/2569] lr: 4.0000e-02 eta: 10:52:43 time: 0.2601 data_time: 0.0070 memory: 5828 grad_norm: 3.1112 loss: 2.4858 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4858 2023/06/05 10:06:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:06:50 - mmengine - INFO - Epoch(train) [93][1660/2569] lr: 4.0000e-02 eta: 10:52:38 time: 0.2667 data_time: 0.0071 memory: 5828 grad_norm: 3.1901 loss: 2.4626 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 2.4626 2023/06/05 10:06:55 - mmengine - INFO - Epoch(train) [93][1680/2569] lr: 4.0000e-02 eta: 10:52:32 time: 0.2650 data_time: 0.0073 memory: 5828 grad_norm: 3.1173 loss: 2.4167 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4167 2023/06/05 10:07:01 - mmengine - INFO - Epoch(train) [93][1700/2569] lr: 4.0000e-02 eta: 10:52:27 time: 0.2695 data_time: 0.0072 memory: 5828 grad_norm: 3.1169 loss: 2.8830 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.8830 2023/06/05 10:07:06 - mmengine - INFO - Epoch(train) [93][1720/2569] lr: 4.0000e-02 eta: 10:52:22 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 3.1065 loss: 2.5355 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5355 2023/06/05 10:07:11 - mmengine - INFO - Epoch(train) [93][1740/2569] lr: 4.0000e-02 eta: 10:52:16 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 3.2002 loss: 2.5184 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5184 2023/06/05 10:07:17 - mmengine - INFO - Epoch(train) [93][1760/2569] lr: 4.0000e-02 eta: 10:52:11 time: 0.2699 data_time: 0.0071 memory: 5828 grad_norm: 3.0794 loss: 2.6339 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6339 2023/06/05 10:07:22 - mmengine - INFO - Epoch(train) [93][1780/2569] lr: 4.0000e-02 eta: 10:52:06 time: 0.2650 data_time: 0.0077 memory: 5828 grad_norm: 3.1291 loss: 2.4372 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4372 2023/06/05 10:07:28 - mmengine - INFO - Epoch(train) [93][1800/2569] lr: 4.0000e-02 eta: 10:52:01 time: 0.2713 data_time: 0.0075 memory: 5828 grad_norm: 3.1250 loss: 2.2728 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2728 2023/06/05 10:07:33 - mmengine - INFO - Epoch(train) [93][1820/2569] lr: 4.0000e-02 eta: 10:51:55 time: 0.2614 data_time: 0.0070 memory: 5828 grad_norm: 3.1914 loss: 2.6892 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6892 2023/06/05 10:07:38 - mmengine - INFO - Epoch(train) [93][1840/2569] lr: 4.0000e-02 eta: 10:51:50 time: 0.2716 data_time: 0.0074 memory: 5828 grad_norm: 3.0827 loss: 2.8288 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.8288 2023/06/05 10:07:44 - mmengine - INFO - Epoch(train) [93][1860/2569] lr: 4.0000e-02 eta: 10:51:45 time: 0.2655 data_time: 0.0072 memory: 5828 grad_norm: 3.1102 loss: 2.7307 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7307 2023/06/05 10:07:49 - mmengine - INFO - Epoch(train) [93][1880/2569] lr: 4.0000e-02 eta: 10:51:39 time: 0.2746 data_time: 0.0072 memory: 5828 grad_norm: 3.1591 loss: 2.3687 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3687 2023/06/05 10:07:54 - mmengine - INFO - Epoch(train) [93][1900/2569] lr: 4.0000e-02 eta: 10:51:34 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 3.1480 loss: 2.7897 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7897 2023/06/05 10:08:00 - mmengine - INFO - Epoch(train) [93][1920/2569] lr: 4.0000e-02 eta: 10:51:29 time: 0.2670 data_time: 0.0068 memory: 5828 grad_norm: 3.2353 loss: 2.4526 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4526 2023/06/05 10:08:05 - mmengine - INFO - Epoch(train) [93][1940/2569] lr: 4.0000e-02 eta: 10:51:23 time: 0.2591 data_time: 0.0069 memory: 5828 grad_norm: 3.0987 loss: 2.4496 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4496 2023/06/05 10:08:10 - mmengine - INFO - Epoch(train) [93][1960/2569] lr: 4.0000e-02 eta: 10:51:18 time: 0.2711 data_time: 0.0071 memory: 5828 grad_norm: 3.1128 loss: 2.6429 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6429 2023/06/05 10:08:16 - mmengine - INFO - Epoch(train) [93][1980/2569] lr: 4.0000e-02 eta: 10:51:13 time: 0.2590 data_time: 0.0071 memory: 5828 grad_norm: 3.1107 loss: 2.3795 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.3795 2023/06/05 10:08:21 - mmengine - INFO - Epoch(train) [93][2000/2569] lr: 4.0000e-02 eta: 10:51:07 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 3.1385 loss: 2.7954 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7954 2023/06/05 10:08:26 - mmengine - INFO - Epoch(train) [93][2020/2569] lr: 4.0000e-02 eta: 10:51:02 time: 0.2586 data_time: 0.0069 memory: 5828 grad_norm: 3.0868 loss: 2.6210 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6210 2023/06/05 10:08:31 - mmengine - INFO - Epoch(train) [93][2040/2569] lr: 4.0000e-02 eta: 10:50:57 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 3.1721 loss: 2.3440 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3440 2023/06/05 10:08:36 - mmengine - INFO - Epoch(train) [93][2060/2569] lr: 4.0000e-02 eta: 10:50:51 time: 0.2583 data_time: 0.0071 memory: 5828 grad_norm: 3.0782 loss: 2.4554 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4554 2023/06/05 10:08:42 - mmengine - INFO - Epoch(train) [93][2080/2569] lr: 4.0000e-02 eta: 10:50:46 time: 0.2732 data_time: 0.0075 memory: 5828 grad_norm: 3.1877 loss: 2.5023 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5023 2023/06/05 10:08:47 - mmengine - INFO - Epoch(train) [93][2100/2569] lr: 4.0000e-02 eta: 10:50:41 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 3.2352 loss: 2.4328 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4328 2023/06/05 10:08:53 - mmengine - INFO - Epoch(train) [93][2120/2569] lr: 4.0000e-02 eta: 10:50:35 time: 0.2720 data_time: 0.0073 memory: 5828 grad_norm: 3.0683 loss: 2.5091 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5091 2023/06/05 10:08:58 - mmengine - INFO - Epoch(train) [93][2140/2569] lr: 4.0000e-02 eta: 10:50:30 time: 0.2596 data_time: 0.0073 memory: 5828 grad_norm: 3.0967 loss: 2.3773 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3773 2023/06/05 10:09:03 - mmengine - INFO - Epoch(train) [93][2160/2569] lr: 4.0000e-02 eta: 10:50:25 time: 0.2800 data_time: 0.0072 memory: 5828 grad_norm: 3.1302 loss: 2.2417 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2417 2023/06/05 10:09:09 - mmengine - INFO - Epoch(train) [93][2180/2569] lr: 4.0000e-02 eta: 10:50:20 time: 0.2605 data_time: 0.0074 memory: 5828 grad_norm: 3.1072 loss: 2.7568 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7568 2023/06/05 10:09:14 - mmengine - INFO - Epoch(train) [93][2200/2569] lr: 4.0000e-02 eta: 10:50:14 time: 0.2696 data_time: 0.0071 memory: 5828 grad_norm: 3.0813 loss: 2.6802 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6802 2023/06/05 10:09:19 - mmengine - INFO - Epoch(train) [93][2220/2569] lr: 4.0000e-02 eta: 10:50:09 time: 0.2684 data_time: 0.0075 memory: 5828 grad_norm: 3.0710 loss: 2.7539 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7539 2023/06/05 10:09:25 - mmengine - INFO - Epoch(train) [93][2240/2569] lr: 4.0000e-02 eta: 10:50:04 time: 0.2612 data_time: 0.0075 memory: 5828 grad_norm: 3.1328 loss: 2.3415 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3415 2023/06/05 10:09:30 - mmengine - INFO - Epoch(train) [93][2260/2569] lr: 4.0000e-02 eta: 10:49:58 time: 0.2601 data_time: 0.0074 memory: 5828 grad_norm: 3.0804 loss: 2.1076 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1076 2023/06/05 10:09:35 - mmengine - INFO - Epoch(train) [93][2280/2569] lr: 4.0000e-02 eta: 10:49:53 time: 0.2670 data_time: 0.0074 memory: 5828 grad_norm: 3.1198 loss: 2.1379 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1379 2023/06/05 10:09:41 - mmengine - INFO - Epoch(train) [93][2300/2569] lr: 4.0000e-02 eta: 10:49:48 time: 0.2639 data_time: 0.0078 memory: 5828 grad_norm: 3.1236 loss: 2.6537 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6537 2023/06/05 10:09:46 - mmengine - INFO - Epoch(train) [93][2320/2569] lr: 4.0000e-02 eta: 10:49:42 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 3.1891 loss: 2.4186 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4186 2023/06/05 10:09:51 - mmengine - INFO - Epoch(train) [93][2340/2569] lr: 4.0000e-02 eta: 10:49:37 time: 0.2710 data_time: 0.0074 memory: 5828 grad_norm: 3.1387 loss: 2.7824 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7824 2023/06/05 10:09:57 - mmengine - INFO - Epoch(train) [93][2360/2569] lr: 4.0000e-02 eta: 10:49:32 time: 0.2697 data_time: 0.0075 memory: 5828 grad_norm: 3.1241 loss: 2.4219 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4219 2023/06/05 10:10:02 - mmengine - INFO - Epoch(train) [93][2380/2569] lr: 4.0000e-02 eta: 10:49:27 time: 0.2782 data_time: 0.0071 memory: 5828 grad_norm: 3.1054 loss: 2.4942 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4942 2023/06/05 10:10:08 - mmengine - INFO - Epoch(train) [93][2400/2569] lr: 4.0000e-02 eta: 10:49:21 time: 0.2700 data_time: 0.0070 memory: 5828 grad_norm: 3.1597 loss: 3.0063 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.0063 2023/06/05 10:10:13 - mmengine - INFO - Epoch(train) [93][2420/2569] lr: 4.0000e-02 eta: 10:49:16 time: 0.2693 data_time: 0.0073 memory: 5828 grad_norm: 3.1521 loss: 2.4676 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.4676 2023/06/05 10:10:18 - mmengine - INFO - Epoch(train) [93][2440/2569] lr: 4.0000e-02 eta: 10:49:11 time: 0.2592 data_time: 0.0071 memory: 5828 grad_norm: 3.0761 loss: 2.4356 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4356 2023/06/05 10:10:24 - mmengine - INFO - Epoch(train) [93][2460/2569] lr: 4.0000e-02 eta: 10:49:05 time: 0.2647 data_time: 0.0071 memory: 5828 grad_norm: 3.0648 loss: 2.3176 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3176 2023/06/05 10:10:29 - mmengine - INFO - Epoch(train) [93][2480/2569] lr: 4.0000e-02 eta: 10:49:00 time: 0.2606 data_time: 0.0071 memory: 5828 grad_norm: 3.0772 loss: 2.4018 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4018 2023/06/05 10:10:34 - mmengine - INFO - Epoch(train) [93][2500/2569] lr: 4.0000e-02 eta: 10:48:55 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 3.1767 loss: 2.3483 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3483 2023/06/05 10:10:39 - mmengine - INFO - Epoch(train) [93][2520/2569] lr: 4.0000e-02 eta: 10:48:49 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.1184 loss: 2.3302 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3302 2023/06/05 10:10:45 - mmengine - INFO - Epoch(train) [93][2540/2569] lr: 4.0000e-02 eta: 10:48:44 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 3.1732 loss: 2.5527 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5527 2023/06/05 10:10:50 - mmengine - INFO - Epoch(train) [93][2560/2569] lr: 4.0000e-02 eta: 10:48:39 time: 0.2574 data_time: 0.0070 memory: 5828 grad_norm: 3.1554 loss: 2.4315 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4315 2023/06/05 10:10:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:10:52 - mmengine - INFO - Epoch(train) [93][2569/2569] lr: 4.0000e-02 eta: 10:48:36 time: 0.2568 data_time: 0.0069 memory: 5828 grad_norm: 3.1281 loss: 2.1459 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1459 2023/06/05 10:10:59 - mmengine - INFO - Epoch(train) [94][ 20/2569] lr: 4.0000e-02 eta: 10:48:32 time: 0.3428 data_time: 0.0641 memory: 5828 grad_norm: 3.1434 loss: 2.5131 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5131 2023/06/05 10:11:04 - mmengine - INFO - Epoch(train) [94][ 40/2569] lr: 4.0000e-02 eta: 10:48:26 time: 0.2599 data_time: 0.0077 memory: 5828 grad_norm: 3.1030 loss: 2.4130 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4130 2023/06/05 10:11:10 - mmengine - INFO - Epoch(train) [94][ 60/2569] lr: 4.0000e-02 eta: 10:48:21 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 3.1381 loss: 2.4760 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4760 2023/06/05 10:11:15 - mmengine - INFO - Epoch(train) [94][ 80/2569] lr: 4.0000e-02 eta: 10:48:16 time: 0.2640 data_time: 0.0076 memory: 5828 grad_norm: 3.0953 loss: 2.6310 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6310 2023/06/05 10:11:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:11:20 - mmengine - INFO - Epoch(train) [94][ 100/2569] lr: 4.0000e-02 eta: 10:48:10 time: 0.2692 data_time: 0.0076 memory: 5828 grad_norm: 3.1001 loss: 2.6550 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6550 2023/06/05 10:11:26 - mmengine - INFO - Epoch(train) [94][ 120/2569] lr: 4.0000e-02 eta: 10:48:05 time: 0.2704 data_time: 0.0074 memory: 5828 grad_norm: 3.0906 loss: 2.7041 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.7041 2023/06/05 10:11:31 - mmengine - INFO - Epoch(train) [94][ 140/2569] lr: 4.0000e-02 eta: 10:48:00 time: 0.2649 data_time: 0.0082 memory: 5828 grad_norm: 3.1041 loss: 2.4204 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4204 2023/06/05 10:11:36 - mmengine - INFO - Epoch(train) [94][ 160/2569] lr: 4.0000e-02 eta: 10:47:55 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 3.0843 loss: 2.3957 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3957 2023/06/05 10:11:42 - mmengine - INFO - Epoch(train) [94][ 180/2569] lr: 4.0000e-02 eta: 10:47:49 time: 0.2739 data_time: 0.0074 memory: 5828 grad_norm: 3.1147 loss: 2.4834 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4834 2023/06/05 10:11:47 - mmengine - INFO - Epoch(train) [94][ 200/2569] lr: 4.0000e-02 eta: 10:47:44 time: 0.2659 data_time: 0.0072 memory: 5828 grad_norm: 3.1951 loss: 2.7886 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7886 2023/06/05 10:11:52 - mmengine - INFO - Epoch(train) [94][ 220/2569] lr: 4.0000e-02 eta: 10:47:39 time: 0.2668 data_time: 0.0070 memory: 5828 grad_norm: 3.0687 loss: 2.4162 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4162 2023/06/05 10:11:58 - mmengine - INFO - Epoch(train) [94][ 240/2569] lr: 4.0000e-02 eta: 10:47:33 time: 0.2686 data_time: 0.0070 memory: 5828 grad_norm: 3.1207 loss: 2.1496 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1496 2023/06/05 10:12:03 - mmengine - INFO - Epoch(train) [94][ 260/2569] lr: 4.0000e-02 eta: 10:47:28 time: 0.2648 data_time: 0.0071 memory: 5828 grad_norm: 3.1423 loss: 2.2903 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2903 2023/06/05 10:12:08 - mmengine - INFO - Epoch(train) [94][ 280/2569] lr: 4.0000e-02 eta: 10:47:23 time: 0.2624 data_time: 0.0071 memory: 5828 grad_norm: 3.1004 loss: 2.2820 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2820 2023/06/05 10:12:14 - mmengine - INFO - Epoch(train) [94][ 300/2569] lr: 4.0000e-02 eta: 10:47:17 time: 0.2666 data_time: 0.0074 memory: 5828 grad_norm: 3.1500 loss: 2.3322 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3322 2023/06/05 10:12:19 - mmengine - INFO - Epoch(train) [94][ 320/2569] lr: 4.0000e-02 eta: 10:47:12 time: 0.2595 data_time: 0.0070 memory: 5828 grad_norm: 3.2022 loss: 2.2548 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2548 2023/06/05 10:12:24 - mmengine - INFO - Epoch(train) [94][ 340/2569] lr: 4.0000e-02 eta: 10:47:07 time: 0.2762 data_time: 0.0073 memory: 5828 grad_norm: 3.2002 loss: 2.5240 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5240 2023/06/05 10:12:30 - mmengine - INFO - Epoch(train) [94][ 360/2569] lr: 4.0000e-02 eta: 10:47:02 time: 0.2710 data_time: 0.0070 memory: 5828 grad_norm: 3.0895 loss: 2.6279 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6279 2023/06/05 10:12:35 - mmengine - INFO - Epoch(train) [94][ 380/2569] lr: 4.0000e-02 eta: 10:46:56 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 3.1520 loss: 2.5085 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5085 2023/06/05 10:12:41 - mmengine - INFO - Epoch(train) [94][ 400/2569] lr: 4.0000e-02 eta: 10:46:51 time: 0.2725 data_time: 0.0076 memory: 5828 grad_norm: 3.0873 loss: 2.7915 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7915 2023/06/05 10:12:46 - mmengine - INFO - Epoch(train) [94][ 420/2569] lr: 4.0000e-02 eta: 10:46:46 time: 0.2777 data_time: 0.0072 memory: 5828 grad_norm: 3.1678 loss: 2.5769 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5769 2023/06/05 10:12:52 - mmengine - INFO - Epoch(train) [94][ 440/2569] lr: 4.0000e-02 eta: 10:46:41 time: 0.2666 data_time: 0.0075 memory: 5828 grad_norm: 3.0975 loss: 2.4197 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4197 2023/06/05 10:12:57 - mmengine - INFO - Epoch(train) [94][ 460/2569] lr: 4.0000e-02 eta: 10:46:35 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 3.1138 loss: 2.6103 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6103 2023/06/05 10:13:02 - mmengine - INFO - Epoch(train) [94][ 480/2569] lr: 4.0000e-02 eta: 10:46:30 time: 0.2643 data_time: 0.0071 memory: 5828 grad_norm: 3.1942 loss: 2.9388 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.9388 2023/06/05 10:13:07 - mmengine - INFO - Epoch(train) [94][ 500/2569] lr: 4.0000e-02 eta: 10:46:24 time: 0.2589 data_time: 0.0074 memory: 5828 grad_norm: 3.1234 loss: 2.3564 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3564 2023/06/05 10:13:12 - mmengine - INFO - Epoch(train) [94][ 520/2569] lr: 4.0000e-02 eta: 10:46:19 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 3.1654 loss: 2.2768 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2768 2023/06/05 10:13:18 - mmengine - INFO - Epoch(train) [94][ 540/2569] lr: 4.0000e-02 eta: 10:46:14 time: 0.2715 data_time: 0.0074 memory: 5828 grad_norm: 3.1489 loss: 2.5584 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5584 2023/06/05 10:13:23 - mmengine - INFO - Epoch(train) [94][ 560/2569] lr: 4.0000e-02 eta: 10:46:09 time: 0.2637 data_time: 0.0072 memory: 5828 grad_norm: 3.1102 loss: 2.7576 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.7576 2023/06/05 10:13:29 - mmengine - INFO - Epoch(train) [94][ 580/2569] lr: 4.0000e-02 eta: 10:46:03 time: 0.2690 data_time: 0.0070 memory: 5828 grad_norm: 3.1354 loss: 2.5201 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.5201 2023/06/05 10:13:34 - mmengine - INFO - Epoch(train) [94][ 600/2569] lr: 4.0000e-02 eta: 10:45:58 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 3.1381 loss: 2.9473 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9473 2023/06/05 10:13:39 - mmengine - INFO - Epoch(train) [94][ 620/2569] lr: 4.0000e-02 eta: 10:45:52 time: 0.2612 data_time: 0.0072 memory: 5828 grad_norm: 3.1971 loss: 2.1608 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1608 2023/06/05 10:13:44 - mmengine - INFO - Epoch(train) [94][ 640/2569] lr: 4.0000e-02 eta: 10:45:47 time: 0.2600 data_time: 0.0073 memory: 5828 grad_norm: 3.1915 loss: 2.3441 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3441 2023/06/05 10:13:49 - mmengine - INFO - Epoch(train) [94][ 660/2569] lr: 4.0000e-02 eta: 10:45:42 time: 0.2593 data_time: 0.0071 memory: 5828 grad_norm: 3.1072 loss: 2.5151 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5151 2023/06/05 10:13:55 - mmengine - INFO - Epoch(train) [94][ 680/2569] lr: 4.0000e-02 eta: 10:45:36 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 3.1077 loss: 2.7520 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7520 2023/06/05 10:14:00 - mmengine - INFO - Epoch(train) [94][ 700/2569] lr: 4.0000e-02 eta: 10:45:31 time: 0.2598 data_time: 0.0071 memory: 5828 grad_norm: 3.1513 loss: 2.3336 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3336 2023/06/05 10:14:05 - mmengine - INFO - Epoch(train) [94][ 720/2569] lr: 4.0000e-02 eta: 10:45:26 time: 0.2703 data_time: 0.0073 memory: 5828 grad_norm: 3.1785 loss: 2.1556 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1556 2023/06/05 10:14:11 - mmengine - INFO - Epoch(train) [94][ 740/2569] lr: 4.0000e-02 eta: 10:45:20 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 3.2067 loss: 2.3853 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3853 2023/06/05 10:14:16 - mmengine - INFO - Epoch(train) [94][ 760/2569] lr: 4.0000e-02 eta: 10:45:15 time: 0.2720 data_time: 0.0071 memory: 5828 grad_norm: 3.1754 loss: 2.5542 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5542 2023/06/05 10:14:21 - mmengine - INFO - Epoch(train) [94][ 780/2569] lr: 4.0000e-02 eta: 10:45:10 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 3.1827 loss: 2.6499 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6499 2023/06/05 10:14:27 - mmengine - INFO - Epoch(train) [94][ 800/2569] lr: 4.0000e-02 eta: 10:45:05 time: 0.2808 data_time: 0.0072 memory: 5828 grad_norm: 3.1173 loss: 2.7476 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7476 2023/06/05 10:14:32 - mmengine - INFO - Epoch(train) [94][ 820/2569] lr: 4.0000e-02 eta: 10:44:59 time: 0.2695 data_time: 0.0071 memory: 5828 grad_norm: 3.0726 loss: 2.5605 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5605 2023/06/05 10:14:38 - mmengine - INFO - Epoch(train) [94][ 840/2569] lr: 4.0000e-02 eta: 10:44:54 time: 0.2712 data_time: 0.0074 memory: 5828 grad_norm: 3.0934 loss: 2.4969 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4969 2023/06/05 10:14:43 - mmengine - INFO - Epoch(train) [94][ 860/2569] lr: 4.0000e-02 eta: 10:44:49 time: 0.2618 data_time: 0.0069 memory: 5828 grad_norm: 3.1612 loss: 2.5148 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5148 2023/06/05 10:14:48 - mmengine - INFO - Epoch(train) [94][ 880/2569] lr: 4.0000e-02 eta: 10:44:43 time: 0.2693 data_time: 0.0077 memory: 5828 grad_norm: 3.1523 loss: 2.4180 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4180 2023/06/05 10:14:54 - mmengine - INFO - Epoch(train) [94][ 900/2569] lr: 4.0000e-02 eta: 10:44:38 time: 0.2672 data_time: 0.0082 memory: 5828 grad_norm: 3.1886 loss: 2.4625 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4625 2023/06/05 10:14:59 - mmengine - INFO - Epoch(train) [94][ 920/2569] lr: 4.0000e-02 eta: 10:44:33 time: 0.2648 data_time: 0.0084 memory: 5828 grad_norm: 3.1213 loss: 2.6967 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.6967 2023/06/05 10:15:05 - mmengine - INFO - Epoch(train) [94][ 940/2569] lr: 4.0000e-02 eta: 10:44:28 time: 0.2730 data_time: 0.0071 memory: 5828 grad_norm: 3.1011 loss: 2.3506 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3506 2023/06/05 10:15:10 - mmengine - INFO - Epoch(train) [94][ 960/2569] lr: 4.0000e-02 eta: 10:44:22 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 3.1798 loss: 2.5962 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5962 2023/06/05 10:15:15 - mmengine - INFO - Epoch(train) [94][ 980/2569] lr: 4.0000e-02 eta: 10:44:17 time: 0.2735 data_time: 0.0072 memory: 5828 grad_norm: 3.1362 loss: 2.6713 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6713 2023/06/05 10:15:21 - mmengine - INFO - Epoch(train) [94][1000/2569] lr: 4.0000e-02 eta: 10:44:12 time: 0.2621 data_time: 0.0071 memory: 5828 grad_norm: 3.1161 loss: 2.6349 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6349 2023/06/05 10:15:26 - mmengine - INFO - Epoch(train) [94][1020/2569] lr: 4.0000e-02 eta: 10:44:06 time: 0.2657 data_time: 0.0070 memory: 5828 grad_norm: 3.1051 loss: 2.6370 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6370 2023/06/05 10:15:31 - mmengine - INFO - Epoch(train) [94][1040/2569] lr: 4.0000e-02 eta: 10:44:01 time: 0.2665 data_time: 0.0073 memory: 5828 grad_norm: 3.1792 loss: 2.4570 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.4570 2023/06/05 10:15:37 - mmengine - INFO - Epoch(train) [94][1060/2569] lr: 4.0000e-02 eta: 10:43:56 time: 0.2774 data_time: 0.0072 memory: 5828 grad_norm: 3.1273 loss: 2.5685 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5685 2023/06/05 10:15:42 - mmengine - INFO - Epoch(train) [94][1080/2569] lr: 4.0000e-02 eta: 10:43:51 time: 0.2667 data_time: 0.0070 memory: 5828 grad_norm: 3.2107 loss: 2.5447 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5447 2023/06/05 10:15:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:15:47 - mmengine - INFO - Epoch(train) [94][1100/2569] lr: 4.0000e-02 eta: 10:43:45 time: 0.2669 data_time: 0.0069 memory: 5828 grad_norm: 3.1212 loss: 2.4122 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4122 2023/06/05 10:15:53 - mmengine - INFO - Epoch(train) [94][1120/2569] lr: 4.0000e-02 eta: 10:43:40 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 3.0726 loss: 2.4215 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4215 2023/06/05 10:15:58 - mmengine - INFO - Epoch(train) [94][1140/2569] lr: 4.0000e-02 eta: 10:43:35 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 3.1463 loss: 2.6666 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6666 2023/06/05 10:16:03 - mmengine - INFO - Epoch(train) [94][1160/2569] lr: 4.0000e-02 eta: 10:43:29 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 3.0911 loss: 2.5157 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5157 2023/06/05 10:16:09 - mmengine - INFO - Epoch(train) [94][1180/2569] lr: 4.0000e-02 eta: 10:43:24 time: 0.2600 data_time: 0.0072 memory: 5828 grad_norm: 3.1250 loss: 2.6017 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6017 2023/06/05 10:16:14 - mmengine - INFO - Epoch(train) [94][1200/2569] lr: 4.0000e-02 eta: 10:43:19 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 3.2013 loss: 2.1490 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.1490 2023/06/05 10:16:19 - mmengine - INFO - Epoch(train) [94][1220/2569] lr: 4.0000e-02 eta: 10:43:13 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 3.1438 loss: 2.6935 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6935 2023/06/05 10:16:24 - mmengine - INFO - Epoch(train) [94][1240/2569] lr: 4.0000e-02 eta: 10:43:08 time: 0.2596 data_time: 0.0073 memory: 5828 grad_norm: 3.0923 loss: 2.2918 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2918 2023/06/05 10:16:30 - mmengine - INFO - Epoch(train) [94][1260/2569] lr: 4.0000e-02 eta: 10:43:03 time: 0.2699 data_time: 0.0072 memory: 5828 grad_norm: 3.1553 loss: 2.4819 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4819 2023/06/05 10:16:35 - mmengine - INFO - Epoch(train) [94][1280/2569] lr: 4.0000e-02 eta: 10:42:57 time: 0.2604 data_time: 0.0072 memory: 5828 grad_norm: 3.1211 loss: 2.7096 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7096 2023/06/05 10:16:40 - mmengine - INFO - Epoch(train) [94][1300/2569] lr: 4.0000e-02 eta: 10:42:52 time: 0.2654 data_time: 0.0073 memory: 5828 grad_norm: 3.1766 loss: 2.3554 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3554 2023/06/05 10:16:46 - mmengine - INFO - Epoch(train) [94][1320/2569] lr: 4.0000e-02 eta: 10:42:47 time: 0.2691 data_time: 0.0077 memory: 5828 grad_norm: 3.1242 loss: 2.7099 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7099 2023/06/05 10:16:51 - mmengine - INFO - Epoch(train) [94][1340/2569] lr: 4.0000e-02 eta: 10:42:41 time: 0.2730 data_time: 0.0079 memory: 5828 grad_norm: 3.1405 loss: 2.7133 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.7133 2023/06/05 10:16:57 - mmengine - INFO - Epoch(train) [94][1360/2569] lr: 4.0000e-02 eta: 10:42:36 time: 0.2655 data_time: 0.0078 memory: 5828 grad_norm: 3.1400 loss: 2.2622 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2622 2023/06/05 10:17:02 - mmengine - INFO - Epoch(train) [94][1380/2569] lr: 4.0000e-02 eta: 10:42:31 time: 0.2732 data_time: 0.0068 memory: 5828 grad_norm: 3.1428 loss: 2.7583 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7583 2023/06/05 10:17:07 - mmengine - INFO - Epoch(train) [94][1400/2569] lr: 4.0000e-02 eta: 10:42:26 time: 0.2663 data_time: 0.0077 memory: 5828 grad_norm: 3.1475 loss: 2.5876 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5876 2023/06/05 10:17:13 - mmengine - INFO - Epoch(train) [94][1420/2569] lr: 4.0000e-02 eta: 10:42:20 time: 0.2699 data_time: 0.0069 memory: 5828 grad_norm: 3.1318 loss: 2.3370 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3370 2023/06/05 10:17:18 - mmengine - INFO - Epoch(train) [94][1440/2569] lr: 4.0000e-02 eta: 10:42:15 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 3.1060 loss: 2.5509 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5509 2023/06/05 10:17:23 - mmengine - INFO - Epoch(train) [94][1460/2569] lr: 4.0000e-02 eta: 10:42:10 time: 0.2698 data_time: 0.0080 memory: 5828 grad_norm: 3.2442 loss: 2.3777 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3777 2023/06/05 10:17:29 - mmengine - INFO - Epoch(train) [94][1480/2569] lr: 4.0000e-02 eta: 10:42:04 time: 0.2571 data_time: 0.0076 memory: 5828 grad_norm: 3.1182 loss: 2.4301 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4301 2023/06/05 10:17:34 - mmengine - INFO - Epoch(train) [94][1500/2569] lr: 4.0000e-02 eta: 10:41:59 time: 0.2665 data_time: 0.0075 memory: 5828 grad_norm: 3.0941 loss: 2.3745 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3745 2023/06/05 10:17:39 - mmengine - INFO - Epoch(train) [94][1520/2569] lr: 4.0000e-02 eta: 10:41:54 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 3.1699 loss: 2.7511 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7511 2023/06/05 10:17:45 - mmengine - INFO - Epoch(train) [94][1540/2569] lr: 4.0000e-02 eta: 10:41:48 time: 0.2633 data_time: 0.0069 memory: 5828 grad_norm: 3.1372 loss: 2.3950 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3950 2023/06/05 10:17:50 - mmengine - INFO - Epoch(train) [94][1560/2569] lr: 4.0000e-02 eta: 10:41:43 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 3.1800 loss: 2.2597 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2597 2023/06/05 10:17:55 - mmengine - INFO - Epoch(train) [94][1580/2569] lr: 4.0000e-02 eta: 10:41:38 time: 0.2621 data_time: 0.0070 memory: 5828 grad_norm: 3.0981 loss: 2.6058 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6058 2023/06/05 10:18:00 - mmengine - INFO - Epoch(train) [94][1600/2569] lr: 4.0000e-02 eta: 10:41:32 time: 0.2593 data_time: 0.0072 memory: 5828 grad_norm: 3.1316 loss: 2.8209 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8209 2023/06/05 10:18:05 - mmengine - INFO - Epoch(train) [94][1620/2569] lr: 4.0000e-02 eta: 10:41:27 time: 0.2595 data_time: 0.0078 memory: 5828 grad_norm: 3.0932 loss: 2.7384 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7384 2023/06/05 10:18:11 - mmengine - INFO - Epoch(train) [94][1640/2569] lr: 4.0000e-02 eta: 10:41:22 time: 0.2715 data_time: 0.0078 memory: 5828 grad_norm: 3.1732 loss: 2.4615 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4615 2023/06/05 10:18:16 - mmengine - INFO - Epoch(train) [94][1660/2569] lr: 4.0000e-02 eta: 10:41:16 time: 0.2594 data_time: 0.0072 memory: 5828 grad_norm: 3.1540 loss: 2.4368 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4368 2023/06/05 10:18:21 - mmengine - INFO - Epoch(train) [94][1680/2569] lr: 4.0000e-02 eta: 10:41:11 time: 0.2617 data_time: 0.0082 memory: 5828 grad_norm: 3.1695 loss: 2.9176 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.9176 2023/06/05 10:18:26 - mmengine - INFO - Epoch(train) [94][1700/2569] lr: 4.0000e-02 eta: 10:41:05 time: 0.2603 data_time: 0.0073 memory: 5828 grad_norm: 3.1349 loss: 2.2591 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2591 2023/06/05 10:18:32 - mmengine - INFO - Epoch(train) [94][1720/2569] lr: 4.0000e-02 eta: 10:41:00 time: 0.2810 data_time: 0.0071 memory: 5828 grad_norm: 3.0691 loss: 2.8187 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8187 2023/06/05 10:18:38 - mmengine - INFO - Epoch(train) [94][1740/2569] lr: 4.0000e-02 eta: 10:40:55 time: 0.2782 data_time: 0.0074 memory: 5828 grad_norm: 3.2050 loss: 2.5908 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5908 2023/06/05 10:18:43 - mmengine - INFO - Epoch(train) [94][1760/2569] lr: 4.0000e-02 eta: 10:40:50 time: 0.2667 data_time: 0.0076 memory: 5828 grad_norm: 3.1106 loss: 2.4535 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4535 2023/06/05 10:18:48 - mmengine - INFO - Epoch(train) [94][1780/2569] lr: 4.0000e-02 eta: 10:40:44 time: 0.2620 data_time: 0.0078 memory: 5828 grad_norm: 3.1105 loss: 2.4759 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4759 2023/06/05 10:18:54 - mmengine - INFO - Epoch(train) [94][1800/2569] lr: 4.0000e-02 eta: 10:40:39 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 3.1267 loss: 2.5346 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5346 2023/06/05 10:18:59 - mmengine - INFO - Epoch(train) [94][1820/2569] lr: 4.0000e-02 eta: 10:40:34 time: 0.2658 data_time: 0.0074 memory: 5828 grad_norm: 3.2140 loss: 2.3925 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3925 2023/06/05 10:19:04 - mmengine - INFO - Epoch(train) [94][1840/2569] lr: 4.0000e-02 eta: 10:40:28 time: 0.2615 data_time: 0.0076 memory: 5828 grad_norm: 3.0546 loss: 2.4095 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4095 2023/06/05 10:19:09 - mmengine - INFO - Epoch(train) [94][1860/2569] lr: 4.0000e-02 eta: 10:40:23 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 3.1861 loss: 2.7557 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7557 2023/06/05 10:19:15 - mmengine - INFO - Epoch(train) [94][1880/2569] lr: 4.0000e-02 eta: 10:40:18 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 3.1525 loss: 2.4790 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.4790 2023/06/05 10:19:20 - mmengine - INFO - Epoch(train) [94][1900/2569] lr: 4.0000e-02 eta: 10:40:12 time: 0.2621 data_time: 0.0082 memory: 5828 grad_norm: 3.0931 loss: 2.2405 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2405 2023/06/05 10:19:26 - mmengine - INFO - Epoch(train) [94][1920/2569] lr: 4.0000e-02 eta: 10:40:07 time: 0.2766 data_time: 0.0079 memory: 5828 grad_norm: 3.1454 loss: 2.6168 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6168 2023/06/05 10:19:31 - mmengine - INFO - Epoch(train) [94][1940/2569] lr: 4.0000e-02 eta: 10:40:02 time: 0.2755 data_time: 0.0075 memory: 5828 grad_norm: 3.1266 loss: 2.6306 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.6306 2023/06/05 10:19:36 - mmengine - INFO - Epoch(train) [94][1960/2569] lr: 4.0000e-02 eta: 10:39:57 time: 0.2610 data_time: 0.0076 memory: 5828 grad_norm: 3.1536 loss: 2.3912 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3912 2023/06/05 10:19:42 - mmengine - INFO - Epoch(train) [94][1980/2569] lr: 4.0000e-02 eta: 10:39:51 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 3.0731 loss: 2.4233 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4233 2023/06/05 10:19:47 - mmengine - INFO - Epoch(train) [94][2000/2569] lr: 4.0000e-02 eta: 10:39:46 time: 0.2608 data_time: 0.0076 memory: 5828 grad_norm: 3.1085 loss: 2.7218 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7218 2023/06/05 10:19:52 - mmengine - INFO - Epoch(train) [94][2020/2569] lr: 4.0000e-02 eta: 10:39:41 time: 0.2703 data_time: 0.0070 memory: 5828 grad_norm: 3.1159 loss: 2.4748 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4748 2023/06/05 10:19:58 - mmengine - INFO - Epoch(train) [94][2040/2569] lr: 4.0000e-02 eta: 10:39:35 time: 0.2673 data_time: 0.0079 memory: 5828 grad_norm: 3.1143 loss: 2.3988 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3988 2023/06/05 10:20:03 - mmengine - INFO - Epoch(train) [94][2060/2569] lr: 4.0000e-02 eta: 10:39:30 time: 0.2598 data_time: 0.0076 memory: 5828 grad_norm: 3.1714 loss: 2.6310 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6310 2023/06/05 10:20:08 - mmengine - INFO - Epoch(train) [94][2080/2569] lr: 4.0000e-02 eta: 10:39:25 time: 0.2591 data_time: 0.0078 memory: 5828 grad_norm: 3.0440 loss: 2.4518 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4518 2023/06/05 10:20:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:20:13 - mmengine - INFO - Epoch(train) [94][2100/2569] lr: 4.0000e-02 eta: 10:39:19 time: 0.2681 data_time: 0.0070 memory: 5828 grad_norm: 3.1488 loss: 2.6363 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6363 2023/06/05 10:20:19 - mmengine - INFO - Epoch(train) [94][2120/2569] lr: 4.0000e-02 eta: 10:39:14 time: 0.2655 data_time: 0.0073 memory: 5828 grad_norm: 3.1129 loss: 2.4487 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4487 2023/06/05 10:20:24 - mmengine - INFO - Epoch(train) [94][2140/2569] lr: 4.0000e-02 eta: 10:39:09 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 3.1530 loss: 3.0535 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 3.0535 2023/06/05 10:20:29 - mmengine - INFO - Epoch(train) [94][2160/2569] lr: 4.0000e-02 eta: 10:39:03 time: 0.2653 data_time: 0.0071 memory: 5828 grad_norm: 3.1020 loss: 2.3352 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.3352 2023/06/05 10:20:35 - mmengine - INFO - Epoch(train) [94][2180/2569] lr: 4.0000e-02 eta: 10:38:58 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 3.1533 loss: 2.6479 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6479 2023/06/05 10:20:40 - mmengine - INFO - Epoch(train) [94][2200/2569] lr: 4.0000e-02 eta: 10:38:53 time: 0.2700 data_time: 0.0072 memory: 5828 grad_norm: 3.0804 loss: 2.6197 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6197 2023/06/05 10:20:45 - mmengine - INFO - Epoch(train) [94][2220/2569] lr: 4.0000e-02 eta: 10:38:48 time: 0.2704 data_time: 0.0072 memory: 5828 grad_norm: 3.1308 loss: 2.3805 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3805 2023/06/05 10:20:51 - mmengine - INFO - Epoch(train) [94][2240/2569] lr: 4.0000e-02 eta: 10:38:42 time: 0.2667 data_time: 0.0076 memory: 5828 grad_norm: 3.1543 loss: 3.0455 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 3.0455 2023/06/05 10:20:56 - mmengine - INFO - Epoch(train) [94][2260/2569] lr: 4.0000e-02 eta: 10:38:37 time: 0.2746 data_time: 0.0074 memory: 5828 grad_norm: 3.1208 loss: 2.5058 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5058 2023/06/05 10:21:02 - mmengine - INFO - Epoch(train) [94][2280/2569] lr: 4.0000e-02 eta: 10:38:32 time: 0.2665 data_time: 0.0072 memory: 5828 grad_norm: 3.1585 loss: 2.6703 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6703 2023/06/05 10:21:07 - mmengine - INFO - Epoch(train) [94][2300/2569] lr: 4.0000e-02 eta: 10:38:27 time: 0.2818 data_time: 0.0082 memory: 5828 grad_norm: 3.1348 loss: 2.4924 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4924 2023/06/05 10:21:13 - mmengine - INFO - Epoch(train) [94][2320/2569] lr: 4.0000e-02 eta: 10:38:21 time: 0.2662 data_time: 0.0071 memory: 5828 grad_norm: 3.0864 loss: 2.4928 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4928 2023/06/05 10:21:18 - mmengine - INFO - Epoch(train) [94][2340/2569] lr: 4.0000e-02 eta: 10:38:16 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 3.0887 loss: 2.3786 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3786 2023/06/05 10:21:23 - mmengine - INFO - Epoch(train) [94][2360/2569] lr: 4.0000e-02 eta: 10:38:11 time: 0.2616 data_time: 0.0077 memory: 5828 grad_norm: 3.1424 loss: 2.3847 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3847 2023/06/05 10:21:28 - mmengine - INFO - Epoch(train) [94][2380/2569] lr: 4.0000e-02 eta: 10:38:05 time: 0.2616 data_time: 0.0069 memory: 5828 grad_norm: 3.1498 loss: 2.4879 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4879 2023/06/05 10:21:34 - mmengine - INFO - Epoch(train) [94][2400/2569] lr: 4.0000e-02 eta: 10:38:00 time: 0.2601 data_time: 0.0075 memory: 5828 grad_norm: 3.1440 loss: 2.3766 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.3766 2023/06/05 10:21:39 - mmengine - INFO - Epoch(train) [94][2420/2569] lr: 4.0000e-02 eta: 10:37:54 time: 0.2650 data_time: 0.0077 memory: 5828 grad_norm: 3.1145 loss: 2.5940 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5940 2023/06/05 10:21:44 - mmengine - INFO - Epoch(train) [94][2440/2569] lr: 4.0000e-02 eta: 10:37:49 time: 0.2615 data_time: 0.0070 memory: 5828 grad_norm: 3.1614 loss: 2.4645 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4645 2023/06/05 10:21:49 - mmengine - INFO - Epoch(train) [94][2460/2569] lr: 4.0000e-02 eta: 10:37:44 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 3.1318 loss: 2.3084 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3084 2023/06/05 10:21:55 - mmengine - INFO - Epoch(train) [94][2480/2569] lr: 4.0000e-02 eta: 10:37:38 time: 0.2623 data_time: 0.0076 memory: 5828 grad_norm: 3.1566 loss: 2.5748 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5748 2023/06/05 10:22:00 - mmengine - INFO - Epoch(train) [94][2500/2569] lr: 4.0000e-02 eta: 10:37:33 time: 0.2664 data_time: 0.0079 memory: 5828 grad_norm: 3.1140 loss: 2.5612 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5612 2023/06/05 10:22:05 - mmengine - INFO - Epoch(train) [94][2520/2569] lr: 4.0000e-02 eta: 10:37:28 time: 0.2591 data_time: 0.0075 memory: 5828 grad_norm: 3.1136 loss: 2.3641 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3641 2023/06/05 10:22:11 - mmengine - INFO - Epoch(train) [94][2540/2569] lr: 4.0000e-02 eta: 10:37:22 time: 0.2760 data_time: 0.0071 memory: 5828 grad_norm: 3.1061 loss: 2.6357 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6357 2023/06/05 10:22:16 - mmengine - INFO - Epoch(train) [94][2560/2569] lr: 4.0000e-02 eta: 10:37:17 time: 0.2795 data_time: 0.0075 memory: 5828 grad_norm: 3.1242 loss: 2.2551 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2551 2023/06/05 10:22:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:22:19 - mmengine - INFO - Epoch(train) [94][2569/2569] lr: 4.0000e-02 eta: 10:37:15 time: 0.2786 data_time: 0.0077 memory: 5828 grad_norm: 3.1704 loss: 2.4494 top1_acc: 0.3333 top5_acc: 0.3333 loss_cls: 2.4494 2023/06/05 10:22:25 - mmengine - INFO - Epoch(train) [95][ 20/2569] lr: 4.0000e-02 eta: 10:37:11 time: 0.3335 data_time: 0.0605 memory: 5828 grad_norm: 3.1235 loss: 2.4411 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4411 2023/06/05 10:22:31 - mmengine - INFO - Epoch(train) [95][ 40/2569] lr: 4.0000e-02 eta: 10:37:05 time: 0.2808 data_time: 0.0073 memory: 5828 grad_norm: 3.0810 loss: 2.8401 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8401 2023/06/05 10:22:36 - mmengine - INFO - Epoch(train) [95][ 60/2569] lr: 4.0000e-02 eta: 10:37:00 time: 0.2659 data_time: 0.0072 memory: 5828 grad_norm: 3.1390 loss: 2.3193 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3193 2023/06/05 10:22:42 - mmengine - INFO - Epoch(train) [95][ 80/2569] lr: 4.0000e-02 eta: 10:36:55 time: 0.2756 data_time: 0.0072 memory: 5828 grad_norm: 3.1260 loss: 2.7375 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7375 2023/06/05 10:22:47 - mmengine - INFO - Epoch(train) [95][ 100/2569] lr: 4.0000e-02 eta: 10:36:49 time: 0.2613 data_time: 0.0073 memory: 5828 grad_norm: 3.1259 loss: 2.6207 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6207 2023/06/05 10:22:52 - mmengine - INFO - Epoch(train) [95][ 120/2569] lr: 4.0000e-02 eta: 10:36:44 time: 0.2592 data_time: 0.0077 memory: 5828 grad_norm: 3.2194 loss: 2.4869 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.4869 2023/06/05 10:22:58 - mmengine - INFO - Epoch(train) [95][ 140/2569] lr: 4.0000e-02 eta: 10:36:39 time: 0.2693 data_time: 0.0071 memory: 5828 grad_norm: 3.1654 loss: 2.3534 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.3534 2023/06/05 10:23:03 - mmengine - INFO - Epoch(train) [95][ 160/2569] lr: 4.0000e-02 eta: 10:36:33 time: 0.2587 data_time: 0.0071 memory: 5828 grad_norm: 3.1583 loss: 2.3484 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3484 2023/06/05 10:23:08 - mmengine - INFO - Epoch(train) [95][ 180/2569] lr: 4.0000e-02 eta: 10:36:28 time: 0.2635 data_time: 0.0075 memory: 5828 grad_norm: 3.1464 loss: 2.2929 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2929 2023/06/05 10:23:13 - mmengine - INFO - Epoch(train) [95][ 200/2569] lr: 4.0000e-02 eta: 10:36:23 time: 0.2596 data_time: 0.0072 memory: 5828 grad_norm: 3.1087 loss: 2.1666 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.1666 2023/06/05 10:23:19 - mmengine - INFO - Epoch(train) [95][ 220/2569] lr: 4.0000e-02 eta: 10:36:17 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 3.2400 loss: 2.4839 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4839 2023/06/05 10:23:24 - mmengine - INFO - Epoch(train) [95][ 240/2569] lr: 4.0000e-02 eta: 10:36:12 time: 0.2657 data_time: 0.0079 memory: 5828 grad_norm: 3.1104 loss: 2.5484 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5484 2023/06/05 10:23:29 - mmengine - INFO - Epoch(train) [95][ 260/2569] lr: 4.0000e-02 eta: 10:36:07 time: 0.2663 data_time: 0.0073 memory: 5828 grad_norm: 3.1584 loss: 2.7097 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7097 2023/06/05 10:23:35 - mmengine - INFO - Epoch(train) [95][ 280/2569] lr: 4.0000e-02 eta: 10:36:01 time: 0.2725 data_time: 0.0075 memory: 5828 grad_norm: 3.1374 loss: 2.4800 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4800 2023/06/05 10:23:40 - mmengine - INFO - Epoch(train) [95][ 300/2569] lr: 4.0000e-02 eta: 10:35:56 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 3.0808 loss: 2.5613 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5613 2023/06/05 10:23:45 - mmengine - INFO - Epoch(train) [95][ 320/2569] lr: 4.0000e-02 eta: 10:35:51 time: 0.2654 data_time: 0.0079 memory: 5828 grad_norm: 3.1199 loss: 2.3865 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3865 2023/06/05 10:23:51 - mmengine - INFO - Epoch(train) [95][ 340/2569] lr: 4.0000e-02 eta: 10:35:45 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.1439 loss: 2.6448 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6448 2023/06/05 10:23:56 - mmengine - INFO - Epoch(train) [95][ 360/2569] lr: 4.0000e-02 eta: 10:35:40 time: 0.2605 data_time: 0.0072 memory: 5828 grad_norm: 3.1625 loss: 2.4480 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4480 2023/06/05 10:24:01 - mmengine - INFO - Epoch(train) [95][ 380/2569] lr: 4.0000e-02 eta: 10:35:35 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 3.1280 loss: 2.5310 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5310 2023/06/05 10:24:07 - mmengine - INFO - Epoch(train) [95][ 400/2569] lr: 4.0000e-02 eta: 10:35:30 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 3.1635 loss: 2.4352 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.4352 2023/06/05 10:24:12 - mmengine - INFO - Epoch(train) [95][ 420/2569] lr: 4.0000e-02 eta: 10:35:24 time: 0.2629 data_time: 0.0073 memory: 5828 grad_norm: 3.1430 loss: 2.5429 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5429 2023/06/05 10:24:17 - mmengine - INFO - Epoch(train) [95][ 440/2569] lr: 4.0000e-02 eta: 10:35:19 time: 0.2639 data_time: 0.0071 memory: 5828 grad_norm: 3.1362 loss: 2.3597 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.3597 2023/06/05 10:24:22 - mmengine - INFO - Epoch(train) [95][ 460/2569] lr: 4.0000e-02 eta: 10:35:13 time: 0.2605 data_time: 0.0073 memory: 5828 grad_norm: 3.1245 loss: 2.5446 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5446 2023/06/05 10:24:28 - mmengine - INFO - Epoch(train) [95][ 480/2569] lr: 4.0000e-02 eta: 10:35:08 time: 0.2577 data_time: 0.0075 memory: 5828 grad_norm: 3.1166 loss: 2.6926 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6926 2023/06/05 10:24:33 - mmengine - INFO - Epoch(train) [95][ 500/2569] lr: 4.0000e-02 eta: 10:35:03 time: 0.2719 data_time: 0.0071 memory: 5828 grad_norm: 3.1733 loss: 2.5896 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5896 2023/06/05 10:24:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:24:38 - mmengine - INFO - Epoch(train) [95][ 520/2569] lr: 4.0000e-02 eta: 10:34:57 time: 0.2653 data_time: 0.0078 memory: 5828 grad_norm: 3.1993 loss: 2.8107 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8107 2023/06/05 10:24:44 - mmengine - INFO - Epoch(train) [95][ 540/2569] lr: 4.0000e-02 eta: 10:34:52 time: 0.2681 data_time: 0.0076 memory: 5828 grad_norm: 3.1459 loss: 2.4106 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4106 2023/06/05 10:24:49 - mmengine - INFO - Epoch(train) [95][ 560/2569] lr: 4.0000e-02 eta: 10:34:47 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.1912 loss: 2.3822 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3822 2023/06/05 10:24:54 - mmengine - INFO - Epoch(train) [95][ 580/2569] lr: 4.0000e-02 eta: 10:34:42 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 3.1363 loss: 2.5877 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5877 2023/06/05 10:25:00 - mmengine - INFO - Epoch(train) [95][ 600/2569] lr: 4.0000e-02 eta: 10:34:36 time: 0.2593 data_time: 0.0075 memory: 5828 grad_norm: 3.1737 loss: 2.3000 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3000 2023/06/05 10:25:05 - mmengine - INFO - Epoch(train) [95][ 620/2569] lr: 4.0000e-02 eta: 10:34:31 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 3.1121 loss: 2.3862 top1_acc: 0.1250 top5_acc: 0.1250 loss_cls: 2.3862 2023/06/05 10:25:10 - mmengine - INFO - Epoch(train) [95][ 640/2569] lr: 4.0000e-02 eta: 10:34:25 time: 0.2603 data_time: 0.0073 memory: 5828 grad_norm: 3.1392 loss: 2.4273 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4273 2023/06/05 10:25:15 - mmengine - INFO - Epoch(train) [95][ 660/2569] lr: 4.0000e-02 eta: 10:34:20 time: 0.2626 data_time: 0.0070 memory: 5828 grad_norm: 3.1633 loss: 2.3315 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3315 2023/06/05 10:25:21 - mmengine - INFO - Epoch(train) [95][ 680/2569] lr: 4.0000e-02 eta: 10:34:15 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 3.0883 loss: 2.3560 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3560 2023/06/05 10:25:26 - mmengine - INFO - Epoch(train) [95][ 700/2569] lr: 4.0000e-02 eta: 10:34:10 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 3.1074 loss: 2.3680 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3680 2023/06/05 10:25:31 - mmengine - INFO - Epoch(train) [95][ 720/2569] lr: 4.0000e-02 eta: 10:34:04 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 3.0959 loss: 2.6169 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6169 2023/06/05 10:25:37 - mmengine - INFO - Epoch(train) [95][ 740/2569] lr: 4.0000e-02 eta: 10:33:59 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 3.2334 loss: 2.6213 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6213 2023/06/05 10:25:42 - mmengine - INFO - Epoch(train) [95][ 760/2569] lr: 4.0000e-02 eta: 10:33:54 time: 0.2717 data_time: 0.0075 memory: 5828 grad_norm: 3.1754 loss: 2.5144 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5144 2023/06/05 10:25:47 - mmengine - INFO - Epoch(train) [95][ 780/2569] lr: 4.0000e-02 eta: 10:33:48 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.1585 loss: 2.5513 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5513 2023/06/05 10:25:53 - mmengine - INFO - Epoch(train) [95][ 800/2569] lr: 4.0000e-02 eta: 10:33:43 time: 0.2710 data_time: 0.0076 memory: 5828 grad_norm: 3.1781 loss: 2.2153 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2153 2023/06/05 10:25:58 - mmengine - INFO - Epoch(train) [95][ 820/2569] lr: 4.0000e-02 eta: 10:33:38 time: 0.2620 data_time: 0.0077 memory: 5828 grad_norm: 3.1507 loss: 2.5957 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5957 2023/06/05 10:26:04 - mmengine - INFO - Epoch(train) [95][ 840/2569] lr: 4.0000e-02 eta: 10:33:32 time: 0.2705 data_time: 0.0075 memory: 5828 grad_norm: 3.0561 loss: 2.3452 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3452 2023/06/05 10:26:09 - mmengine - INFO - Epoch(train) [95][ 860/2569] lr: 4.0000e-02 eta: 10:33:27 time: 0.2603 data_time: 0.0075 memory: 5828 grad_norm: 3.1771 loss: 2.2912 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2912 2023/06/05 10:26:14 - mmengine - INFO - Epoch(train) [95][ 880/2569] lr: 4.0000e-02 eta: 10:33:22 time: 0.2683 data_time: 0.0071 memory: 5828 grad_norm: 3.1999 loss: 2.6501 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6501 2023/06/05 10:26:19 - mmengine - INFO - Epoch(train) [95][ 900/2569] lr: 4.0000e-02 eta: 10:33:16 time: 0.2639 data_time: 0.0072 memory: 5828 grad_norm: 3.1610 loss: 2.6047 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6047 2023/06/05 10:26:25 - mmengine - INFO - Epoch(train) [95][ 920/2569] lr: 4.0000e-02 eta: 10:33:11 time: 0.2812 data_time: 0.0074 memory: 5828 grad_norm: 3.1306 loss: 2.6800 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6800 2023/06/05 10:26:30 - mmengine - INFO - Epoch(train) [95][ 940/2569] lr: 4.0000e-02 eta: 10:33:06 time: 0.2588 data_time: 0.0082 memory: 5828 grad_norm: 3.1781 loss: 2.2810 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2810 2023/06/05 10:26:35 - mmengine - INFO - Epoch(train) [95][ 960/2569] lr: 4.0000e-02 eta: 10:33:01 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 3.1954 loss: 2.6604 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6604 2023/06/05 10:26:41 - mmengine - INFO - Epoch(train) [95][ 980/2569] lr: 4.0000e-02 eta: 10:32:55 time: 0.2573 data_time: 0.0072 memory: 5828 grad_norm: 3.1157 loss: 2.4339 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4339 2023/06/05 10:26:46 - mmengine - INFO - Epoch(train) [95][1000/2569] lr: 4.0000e-02 eta: 10:32:50 time: 0.2768 data_time: 0.0072 memory: 5828 grad_norm: 3.1484 loss: 2.6555 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6555 2023/06/05 10:26:52 - mmengine - INFO - Epoch(train) [95][1020/2569] lr: 4.0000e-02 eta: 10:32:45 time: 0.2666 data_time: 0.0071 memory: 5828 grad_norm: 3.1047 loss: 2.7235 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7235 2023/06/05 10:26:57 - mmengine - INFO - Epoch(train) [95][1040/2569] lr: 4.0000e-02 eta: 10:32:39 time: 0.2691 data_time: 0.0074 memory: 5828 grad_norm: 3.1880 loss: 2.2001 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2001 2023/06/05 10:27:02 - mmengine - INFO - Epoch(train) [95][1060/2569] lr: 4.0000e-02 eta: 10:32:34 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 3.1906 loss: 2.7047 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7047 2023/06/05 10:27:08 - mmengine - INFO - Epoch(train) [95][1080/2569] lr: 4.0000e-02 eta: 10:32:29 time: 0.2669 data_time: 0.0076 memory: 5828 grad_norm: 3.0794 loss: 2.7531 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.7531 2023/06/05 10:27:13 - mmengine - INFO - Epoch(train) [95][1100/2569] lr: 4.0000e-02 eta: 10:32:23 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 3.0792 loss: 2.3887 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.3887 2023/06/05 10:27:18 - mmengine - INFO - Epoch(train) [95][1120/2569] lr: 4.0000e-02 eta: 10:32:18 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 3.1369 loss: 2.5315 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5315 2023/06/05 10:27:23 - mmengine - INFO - Epoch(train) [95][1140/2569] lr: 4.0000e-02 eta: 10:32:13 time: 0.2600 data_time: 0.0074 memory: 5828 grad_norm: 3.1350 loss: 2.5168 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5168 2023/06/05 10:27:29 - mmengine - INFO - Epoch(train) [95][1160/2569] lr: 4.0000e-02 eta: 10:32:07 time: 0.2760 data_time: 0.0075 memory: 5828 grad_norm: 3.1961 loss: 2.2975 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2975 2023/06/05 10:27:34 - mmengine - INFO - Epoch(train) [95][1180/2569] lr: 4.0000e-02 eta: 10:32:02 time: 0.2598 data_time: 0.0077 memory: 5828 grad_norm: 3.1134 loss: 2.7470 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7470 2023/06/05 10:27:39 - mmengine - INFO - Epoch(train) [95][1200/2569] lr: 4.0000e-02 eta: 10:31:57 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 3.1465 loss: 2.4187 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4187 2023/06/05 10:27:45 - mmengine - INFO - Epoch(train) [95][1220/2569] lr: 4.0000e-02 eta: 10:31:51 time: 0.2724 data_time: 0.0074 memory: 5828 grad_norm: 3.1545 loss: 2.4591 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4591 2023/06/05 10:27:50 - mmengine - INFO - Epoch(train) [95][1240/2569] lr: 4.0000e-02 eta: 10:31:46 time: 0.2652 data_time: 0.0073 memory: 5828 grad_norm: 3.1497 loss: 2.1349 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1349 2023/06/05 10:27:56 - mmengine - INFO - Epoch(train) [95][1260/2569] lr: 4.0000e-02 eta: 10:31:41 time: 0.2728 data_time: 0.0076 memory: 5828 grad_norm: 3.1590 loss: 2.4743 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4743 2023/06/05 10:28:01 - mmengine - INFO - Epoch(train) [95][1280/2569] lr: 4.0000e-02 eta: 10:31:36 time: 0.2709 data_time: 0.0073 memory: 5828 grad_norm: 3.1261 loss: 2.4745 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4745 2023/06/05 10:28:06 - mmengine - INFO - Epoch(train) [95][1300/2569] lr: 4.0000e-02 eta: 10:31:30 time: 0.2625 data_time: 0.0071 memory: 5828 grad_norm: 3.1042 loss: 2.5695 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5695 2023/06/05 10:28:12 - mmengine - INFO - Epoch(train) [95][1320/2569] lr: 4.0000e-02 eta: 10:31:25 time: 0.2635 data_time: 0.0072 memory: 5828 grad_norm: 3.1588 loss: 2.9429 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.9429 2023/06/05 10:28:17 - mmengine - INFO - Epoch(train) [95][1340/2569] lr: 4.0000e-02 eta: 10:31:20 time: 0.2661 data_time: 0.0071 memory: 5828 grad_norm: 3.0848 loss: 2.4301 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4301 2023/06/05 10:28:22 - mmengine - INFO - Epoch(train) [95][1360/2569] lr: 4.0000e-02 eta: 10:31:14 time: 0.2702 data_time: 0.0072 memory: 5828 grad_norm: 3.1565 loss: 2.7868 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7868 2023/06/05 10:28:28 - mmengine - INFO - Epoch(train) [95][1380/2569] lr: 4.0000e-02 eta: 10:31:09 time: 0.2740 data_time: 0.0071 memory: 5828 grad_norm: 3.1328 loss: 2.5679 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5679 2023/06/05 10:28:33 - mmengine - INFO - Epoch(train) [95][1400/2569] lr: 4.0000e-02 eta: 10:31:04 time: 0.2638 data_time: 0.0075 memory: 5828 grad_norm: 3.1771 loss: 2.4288 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4288 2023/06/05 10:28:38 - mmengine - INFO - Epoch(train) [95][1420/2569] lr: 4.0000e-02 eta: 10:30:58 time: 0.2632 data_time: 0.0070 memory: 5828 grad_norm: 3.1859 loss: 2.5973 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5973 2023/06/05 10:28:44 - mmengine - INFO - Epoch(train) [95][1440/2569] lr: 4.0000e-02 eta: 10:30:53 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.1124 loss: 2.5055 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5055 2023/06/05 10:28:49 - mmengine - INFO - Epoch(train) [95][1460/2569] lr: 4.0000e-02 eta: 10:30:48 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 3.1705 loss: 2.5452 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5452 2023/06/05 10:28:55 - mmengine - INFO - Epoch(train) [95][1480/2569] lr: 4.0000e-02 eta: 10:30:43 time: 0.2845 data_time: 0.0075 memory: 5828 grad_norm: 3.1918 loss: 2.4605 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4605 2023/06/05 10:29:00 - mmengine - INFO - Epoch(train) [95][1500/2569] lr: 4.0000e-02 eta: 10:30:37 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 3.0967 loss: 2.3830 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3830 2023/06/05 10:29:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:29:05 - mmengine - INFO - Epoch(train) [95][1520/2569] lr: 4.0000e-02 eta: 10:30:32 time: 0.2723 data_time: 0.0073 memory: 5828 grad_norm: 3.1993 loss: 2.9485 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.9485 2023/06/05 10:29:11 - mmengine - INFO - Epoch(train) [95][1540/2569] lr: 4.0000e-02 eta: 10:30:27 time: 0.2597 data_time: 0.0074 memory: 5828 grad_norm: 3.1694 loss: 2.8073 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8073 2023/06/05 10:29:16 - mmengine - INFO - Epoch(train) [95][1560/2569] lr: 4.0000e-02 eta: 10:30:21 time: 0.2603 data_time: 0.0073 memory: 5828 grad_norm: 3.1121 loss: 2.8510 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.8510 2023/06/05 10:29:21 - mmengine - INFO - Epoch(train) [95][1580/2569] lr: 4.0000e-02 eta: 10:30:16 time: 0.2607 data_time: 0.0071 memory: 5828 grad_norm: 3.2047 loss: 2.9061 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9061 2023/06/05 10:29:26 - mmengine - INFO - Epoch(train) [95][1600/2569] lr: 4.0000e-02 eta: 10:30:11 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 3.1564 loss: 2.4058 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4058 2023/06/05 10:29:32 - mmengine - INFO - Epoch(train) [95][1620/2569] lr: 4.0000e-02 eta: 10:30:06 time: 0.2765 data_time: 0.0072 memory: 5828 grad_norm: 3.1792 loss: 2.5492 top1_acc: 0.0000 top5_acc: 0.2500 loss_cls: 2.5492 2023/06/05 10:29:37 - mmengine - INFO - Epoch(train) [95][1640/2569] lr: 4.0000e-02 eta: 10:30:00 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 3.1041 loss: 2.4317 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4317 2023/06/05 10:29:42 - mmengine - INFO - Epoch(train) [95][1660/2569] lr: 4.0000e-02 eta: 10:29:55 time: 0.2607 data_time: 0.0068 memory: 5828 grad_norm: 3.1273 loss: 2.7776 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7776 2023/06/05 10:29:48 - mmengine - INFO - Epoch(train) [95][1680/2569] lr: 4.0000e-02 eta: 10:29:49 time: 0.2629 data_time: 0.0073 memory: 5828 grad_norm: 3.1225 loss: 2.8192 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8192 2023/06/05 10:29:53 - mmengine - INFO - Epoch(train) [95][1700/2569] lr: 4.0000e-02 eta: 10:29:44 time: 0.2709 data_time: 0.0075 memory: 5828 grad_norm: 3.1456 loss: 2.7933 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7933 2023/06/05 10:29:58 - mmengine - INFO - Epoch(train) [95][1720/2569] lr: 4.0000e-02 eta: 10:29:39 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 3.0937 loss: 2.4249 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4249 2023/06/05 10:30:04 - mmengine - INFO - Epoch(train) [95][1740/2569] lr: 4.0000e-02 eta: 10:29:34 time: 0.2777 data_time: 0.0075 memory: 5828 grad_norm: 3.1375 loss: 2.7528 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.7528 2023/06/05 10:30:09 - mmengine - INFO - Epoch(train) [95][1760/2569] lr: 4.0000e-02 eta: 10:29:28 time: 0.2600 data_time: 0.0072 memory: 5828 grad_norm: 3.1242 loss: 2.5765 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5765 2023/06/05 10:30:15 - mmengine - INFO - Epoch(train) [95][1780/2569] lr: 4.0000e-02 eta: 10:29:23 time: 0.2703 data_time: 0.0079 memory: 5828 grad_norm: 3.1155 loss: 2.7317 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7317 2023/06/05 10:30:20 - mmengine - INFO - Epoch(train) [95][1800/2569] lr: 4.0000e-02 eta: 10:29:18 time: 0.2596 data_time: 0.0077 memory: 5828 grad_norm: 3.1277 loss: 2.7566 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7566 2023/06/05 10:30:25 - mmengine - INFO - Epoch(train) [95][1820/2569] lr: 4.0000e-02 eta: 10:29:12 time: 0.2804 data_time: 0.0078 memory: 5828 grad_norm: 3.1794 loss: 2.6557 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6557 2023/06/05 10:30:30 - mmengine - INFO - Epoch(train) [95][1840/2569] lr: 4.0000e-02 eta: 10:29:07 time: 0.2580 data_time: 0.0074 memory: 5828 grad_norm: 3.0823 loss: 2.3290 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3290 2023/06/05 10:30:36 - mmengine - INFO - Epoch(train) [95][1860/2569] lr: 4.0000e-02 eta: 10:29:02 time: 0.2701 data_time: 0.0072 memory: 5828 grad_norm: 3.0781 loss: 2.2050 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2050 2023/06/05 10:30:41 - mmengine - INFO - Epoch(train) [95][1880/2569] lr: 4.0000e-02 eta: 10:28:57 time: 0.2696 data_time: 0.0074 memory: 5828 grad_norm: 3.1454 loss: 2.3579 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3579 2023/06/05 10:30:47 - mmengine - INFO - Epoch(train) [95][1900/2569] lr: 4.0000e-02 eta: 10:28:51 time: 0.2625 data_time: 0.0070 memory: 5828 grad_norm: 3.1489 loss: 2.2317 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2317 2023/06/05 10:30:52 - mmengine - INFO - Epoch(train) [95][1920/2569] lr: 4.0000e-02 eta: 10:28:46 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 3.1324 loss: 2.3669 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3669 2023/06/05 10:30:57 - mmengine - INFO - Epoch(train) [95][1940/2569] lr: 4.0000e-02 eta: 10:28:41 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 3.1503 loss: 2.4370 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4370 2023/06/05 10:31:03 - mmengine - INFO - Epoch(train) [95][1960/2569] lr: 4.0000e-02 eta: 10:28:35 time: 0.2717 data_time: 0.0073 memory: 5828 grad_norm: 3.1218 loss: 2.2616 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2616 2023/06/05 10:31:08 - mmengine - INFO - Epoch(train) [95][1980/2569] lr: 4.0000e-02 eta: 10:28:30 time: 0.2605 data_time: 0.0074 memory: 5828 grad_norm: 3.1327 loss: 2.3923 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3923 2023/06/05 10:31:13 - mmengine - INFO - Epoch(train) [95][2000/2569] lr: 4.0000e-02 eta: 10:28:25 time: 0.2702 data_time: 0.0072 memory: 5828 grad_norm: 3.1217 loss: 2.2923 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2923 2023/06/05 10:31:19 - mmengine - INFO - Epoch(train) [95][2020/2569] lr: 4.0000e-02 eta: 10:28:19 time: 0.2709 data_time: 0.0073 memory: 5828 grad_norm: 3.1455 loss: 2.5094 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5094 2023/06/05 10:31:24 - mmengine - INFO - Epoch(train) [95][2040/2569] lr: 4.0000e-02 eta: 10:28:14 time: 0.2670 data_time: 0.0074 memory: 5828 grad_norm: 3.1343 loss: 2.6406 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6406 2023/06/05 10:31:29 - mmengine - INFO - Epoch(train) [95][2060/2569] lr: 4.0000e-02 eta: 10:28:09 time: 0.2650 data_time: 0.0071 memory: 5828 grad_norm: 3.1628 loss: 2.5059 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5059 2023/06/05 10:31:35 - mmengine - INFO - Epoch(train) [95][2080/2569] lr: 4.0000e-02 eta: 10:28:03 time: 0.2660 data_time: 0.0077 memory: 5828 grad_norm: 3.1885 loss: 2.4254 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4254 2023/06/05 10:31:40 - mmengine - INFO - Epoch(train) [95][2100/2569] lr: 4.0000e-02 eta: 10:27:58 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 3.1014 loss: 2.6228 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.6228 2023/06/05 10:31:45 - mmengine - INFO - Epoch(train) [95][2120/2569] lr: 4.0000e-02 eta: 10:27:53 time: 0.2660 data_time: 0.0074 memory: 5828 grad_norm: 3.1260 loss: 2.5123 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5123 2023/06/05 10:31:51 - mmengine - INFO - Epoch(train) [95][2140/2569] lr: 4.0000e-02 eta: 10:27:48 time: 0.2794 data_time: 0.0073 memory: 5828 grad_norm: 3.1716 loss: 2.5113 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5113 2023/06/05 10:31:56 - mmengine - INFO - Epoch(train) [95][2160/2569] lr: 4.0000e-02 eta: 10:27:42 time: 0.2678 data_time: 0.0074 memory: 5828 grad_norm: 3.1738 loss: 2.5185 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5185 2023/06/05 10:32:02 - mmengine - INFO - Epoch(train) [95][2180/2569] lr: 4.0000e-02 eta: 10:27:37 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 3.1323 loss: 2.8320 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8320 2023/06/05 10:32:07 - mmengine - INFO - Epoch(train) [95][2200/2569] lr: 4.0000e-02 eta: 10:27:32 time: 0.2579 data_time: 0.0074 memory: 5828 grad_norm: 3.0897 loss: 2.3883 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3883 2023/06/05 10:32:12 - mmengine - INFO - Epoch(train) [95][2220/2569] lr: 4.0000e-02 eta: 10:27:27 time: 0.2752 data_time: 0.0071 memory: 5828 grad_norm: 3.0969 loss: 2.3759 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.3759 2023/06/05 10:32:18 - mmengine - INFO - Epoch(train) [95][2240/2569] lr: 4.0000e-02 eta: 10:27:21 time: 0.2622 data_time: 0.0068 memory: 5828 grad_norm: 3.1278 loss: 2.6541 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6541 2023/06/05 10:32:23 - mmengine - INFO - Epoch(train) [95][2260/2569] lr: 4.0000e-02 eta: 10:27:16 time: 0.2718 data_time: 0.0073 memory: 5828 grad_norm: 3.1050 loss: 2.5739 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5739 2023/06/05 10:32:28 - mmengine - INFO - Epoch(train) [95][2280/2569] lr: 4.0000e-02 eta: 10:27:11 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 3.1250 loss: 2.2532 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.2532 2023/06/05 10:32:34 - mmengine - INFO - Epoch(train) [95][2300/2569] lr: 4.0000e-02 eta: 10:27:05 time: 0.2646 data_time: 0.0072 memory: 5828 grad_norm: 3.1997 loss: 2.6409 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6409 2023/06/05 10:32:39 - mmengine - INFO - Epoch(train) [95][2320/2569] lr: 4.0000e-02 eta: 10:27:00 time: 0.2761 data_time: 0.0079 memory: 5828 grad_norm: 3.1267 loss: 2.3557 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3557 2023/06/05 10:32:44 - mmengine - INFO - Epoch(train) [95][2340/2569] lr: 4.0000e-02 eta: 10:26:55 time: 0.2630 data_time: 0.0070 memory: 5828 grad_norm: 3.1302 loss: 2.5218 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5218 2023/06/05 10:32:50 - mmengine - INFO - Epoch(train) [95][2360/2569] lr: 4.0000e-02 eta: 10:26:49 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.0946 loss: 2.2567 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2567 2023/06/05 10:32:55 - mmengine - INFO - Epoch(train) [95][2380/2569] lr: 4.0000e-02 eta: 10:26:44 time: 0.2639 data_time: 0.0072 memory: 5828 grad_norm: 3.1062 loss: 2.2184 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2184 2023/06/05 10:33:00 - mmengine - INFO - Epoch(train) [95][2400/2569] lr: 4.0000e-02 eta: 10:26:39 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 3.1510 loss: 2.7428 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7428 2023/06/05 10:33:06 - mmengine - INFO - Epoch(train) [95][2420/2569] lr: 4.0000e-02 eta: 10:26:33 time: 0.2587 data_time: 0.0072 memory: 5828 grad_norm: 3.0884 loss: 2.3695 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3695 2023/06/05 10:33:11 - mmengine - INFO - Epoch(train) [95][2440/2569] lr: 4.0000e-02 eta: 10:26:28 time: 0.2688 data_time: 0.0072 memory: 5828 grad_norm: 3.0996 loss: 2.5768 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5768 2023/06/05 10:33:16 - mmengine - INFO - Epoch(train) [95][2460/2569] lr: 4.0000e-02 eta: 10:26:23 time: 0.2622 data_time: 0.0092 memory: 5828 grad_norm: 3.1418 loss: 2.7830 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7830 2023/06/05 10:33:21 - mmengine - INFO - Epoch(train) [95][2480/2569] lr: 4.0000e-02 eta: 10:26:17 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 3.1634 loss: 2.9356 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.9356 2023/06/05 10:33:27 - mmengine - INFO - Epoch(train) [95][2500/2569] lr: 4.0000e-02 eta: 10:26:12 time: 0.2613 data_time: 0.0070 memory: 5828 grad_norm: 3.1626 loss: 2.5169 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5169 2023/06/05 10:33:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:33:32 - mmengine - INFO - Epoch(train) [95][2520/2569] lr: 4.0000e-02 eta: 10:26:07 time: 0.2628 data_time: 0.0074 memory: 5828 grad_norm: 3.0924 loss: 2.3396 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3396 2023/06/05 10:33:37 - mmengine - INFO - Epoch(train) [95][2540/2569] lr: 4.0000e-02 eta: 10:26:01 time: 0.2654 data_time: 0.0073 memory: 5828 grad_norm: 3.2019 loss: 2.5843 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5843 2023/06/05 10:33:43 - mmengine - INFO - Epoch(train) [95][2560/2569] lr: 4.0000e-02 eta: 10:25:56 time: 0.2641 data_time: 0.0078 memory: 5828 grad_norm: 3.1302 loss: 2.3340 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3340 2023/06/05 10:33:45 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:33:45 - mmengine - INFO - Epoch(train) [95][2569/2569] lr: 4.0000e-02 eta: 10:25:53 time: 0.2550 data_time: 0.0071 memory: 5828 grad_norm: 3.1786 loss: 2.2527 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2527 2023/06/05 10:33:48 - mmengine - INFO - Epoch(val) [95][ 20/260] eta: 0:00:43 time: 0.1804 data_time: 0.1212 memory: 1238 2023/06/05 10:33:51 - mmengine - INFO - Epoch(val) [95][ 40/260] eta: 0:00:35 time: 0.1395 data_time: 0.0801 memory: 1238 2023/06/05 10:33:54 - mmengine - INFO - Epoch(val) [95][ 60/260] eta: 0:00:31 time: 0.1534 data_time: 0.0943 memory: 1238 2023/06/05 10:33:57 - mmengine - INFO - Epoch(val) [95][ 80/260] eta: 0:00:26 time: 0.1254 data_time: 0.0665 memory: 1238 2023/06/05 10:34:00 - mmengine - INFO - Epoch(val) [95][100/260] eta: 0:00:23 time: 0.1510 data_time: 0.0920 memory: 1238 2023/06/05 10:34:03 - mmengine - INFO - Epoch(val) [95][120/260] eta: 0:00:20 time: 0.1374 data_time: 0.0785 memory: 1238 2023/06/05 10:34:05 - mmengine - INFO - Epoch(val) [95][140/260] eta: 0:00:17 time: 0.1277 data_time: 0.0691 memory: 1238 2023/06/05 10:34:08 - mmengine - INFO - Epoch(val) [95][160/260] eta: 0:00:14 time: 0.1513 data_time: 0.0925 memory: 1238 2023/06/05 10:34:11 - mmengine - INFO - Epoch(val) [95][180/260] eta: 0:00:11 time: 0.1440 data_time: 0.0855 memory: 1238 2023/06/05 10:34:14 - mmengine - INFO - Epoch(val) [95][200/260] eta: 0:00:08 time: 0.1267 data_time: 0.0670 memory: 1238 2023/06/05 10:34:17 - mmengine - INFO - Epoch(val) [95][220/260] eta: 0:00:05 time: 0.1689 data_time: 0.1096 memory: 1238 2023/06/05 10:34:20 - mmengine - INFO - Epoch(val) [95][240/260] eta: 0:00:02 time: 0.1292 data_time: 0.0704 memory: 1238 2023/06/05 10:34:22 - mmengine - INFO - Epoch(val) [95][260/260] eta: 0:00:00 time: 0.1234 data_time: 0.0671 memory: 1238 2023/06/05 10:34:29 - mmengine - INFO - Epoch(val) [95][260/260] acc/top1: 0.5020 acc/top5: 0.7455 acc/mean1: 0.4939 data_time: 0.0838 time: 0.1426 2023/06/05 10:34:36 - mmengine - INFO - Epoch(train) [96][ 20/2569] lr: 4.0000e-02 eta: 10:25:49 time: 0.3295 data_time: 0.0601 memory: 5828 grad_norm: 3.1575 loss: 2.1873 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1873 2023/06/05 10:34:41 - mmengine - INFO - Epoch(train) [96][ 40/2569] lr: 4.0000e-02 eta: 10:25:44 time: 0.2607 data_time: 0.0078 memory: 5828 grad_norm: 3.0714 loss: 2.8316 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.8316 2023/06/05 10:34:46 - mmengine - INFO - Epoch(train) [96][ 60/2569] lr: 4.0000e-02 eta: 10:25:38 time: 0.2587 data_time: 0.0067 memory: 5828 grad_norm: 3.1411 loss: 2.3209 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3209 2023/06/05 10:34:52 - mmengine - INFO - Epoch(train) [96][ 80/2569] lr: 4.0000e-02 eta: 10:25:33 time: 0.2803 data_time: 0.0070 memory: 5828 grad_norm: 3.1248 loss: 2.2778 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2778 2023/06/05 10:34:57 - mmengine - INFO - Epoch(train) [96][ 100/2569] lr: 4.0000e-02 eta: 10:25:28 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 3.0981 loss: 2.5103 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5103 2023/06/05 10:35:03 - mmengine - INFO - Epoch(train) [96][ 120/2569] lr: 4.0000e-02 eta: 10:25:22 time: 0.2647 data_time: 0.0076 memory: 5828 grad_norm: 3.0931 loss: 2.4621 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4621 2023/06/05 10:35:08 - mmengine - INFO - Epoch(train) [96][ 140/2569] lr: 4.0000e-02 eta: 10:25:17 time: 0.2584 data_time: 0.0073 memory: 5828 grad_norm: 3.1677 loss: 2.5056 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5056 2023/06/05 10:35:13 - mmengine - INFO - Epoch(train) [96][ 160/2569] lr: 4.0000e-02 eta: 10:25:12 time: 0.2657 data_time: 0.0069 memory: 5828 grad_norm: 3.1459 loss: 2.7464 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7464 2023/06/05 10:35:18 - mmengine - INFO - Epoch(train) [96][ 180/2569] lr: 4.0000e-02 eta: 10:25:06 time: 0.2651 data_time: 0.0070 memory: 5828 grad_norm: 3.1344 loss: 2.7354 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.7354 2023/06/05 10:35:24 - mmengine - INFO - Epoch(train) [96][ 200/2569] lr: 4.0000e-02 eta: 10:25:01 time: 0.2704 data_time: 0.0073 memory: 5828 grad_norm: 3.1155 loss: 2.4302 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4302 2023/06/05 10:35:29 - mmengine - INFO - Epoch(train) [96][ 220/2569] lr: 4.0000e-02 eta: 10:24:56 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 3.1588 loss: 2.4766 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4766 2023/06/05 10:35:34 - mmengine - INFO - Epoch(train) [96][ 240/2569] lr: 4.0000e-02 eta: 10:24:50 time: 0.2693 data_time: 0.0075 memory: 5828 grad_norm: 3.0970 loss: 2.1087 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1087 2023/06/05 10:35:40 - mmengine - INFO - Epoch(train) [96][ 260/2569] lr: 4.0000e-02 eta: 10:24:45 time: 0.2756 data_time: 0.0072 memory: 5828 grad_norm: 3.0818 loss: 2.4166 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4166 2023/06/05 10:35:45 - mmengine - INFO - Epoch(train) [96][ 280/2569] lr: 4.0000e-02 eta: 10:24:40 time: 0.2650 data_time: 0.0077 memory: 5828 grad_norm: 3.1425 loss: 2.4910 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.4910 2023/06/05 10:35:51 - mmengine - INFO - Epoch(train) [96][ 300/2569] lr: 4.0000e-02 eta: 10:24:35 time: 0.2756 data_time: 0.0074 memory: 5828 grad_norm: 3.1411 loss: 2.4324 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4324 2023/06/05 10:35:56 - mmengine - INFO - Epoch(train) [96][ 320/2569] lr: 4.0000e-02 eta: 10:24:29 time: 0.2682 data_time: 0.0071 memory: 5828 grad_norm: 3.1949 loss: 2.4394 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4394 2023/06/05 10:36:02 - mmengine - INFO - Epoch(train) [96][ 340/2569] lr: 4.0000e-02 eta: 10:24:24 time: 0.2678 data_time: 0.0069 memory: 5828 grad_norm: 3.1159 loss: 2.4902 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4902 2023/06/05 10:36:07 - mmengine - INFO - Epoch(train) [96][ 360/2569] lr: 4.0000e-02 eta: 10:24:19 time: 0.2666 data_time: 0.0071 memory: 5828 grad_norm: 3.0783 loss: 2.3900 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3900 2023/06/05 10:36:12 - mmengine - INFO - Epoch(train) [96][ 380/2569] lr: 4.0000e-02 eta: 10:24:13 time: 0.2595 data_time: 0.0069 memory: 5828 grad_norm: 3.2479 loss: 2.3495 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3495 2023/06/05 10:36:17 - mmengine - INFO - Epoch(train) [96][ 400/2569] lr: 4.0000e-02 eta: 10:24:08 time: 0.2618 data_time: 0.0071 memory: 5828 grad_norm: 3.1312 loss: 2.6893 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6893 2023/06/05 10:36:23 - mmengine - INFO - Epoch(train) [96][ 420/2569] lr: 4.0000e-02 eta: 10:24:03 time: 0.2660 data_time: 0.0070 memory: 5828 grad_norm: 3.1494 loss: 2.4264 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4264 2023/06/05 10:36:28 - mmengine - INFO - Epoch(train) [96][ 440/2569] lr: 4.0000e-02 eta: 10:23:57 time: 0.2689 data_time: 0.0072 memory: 5828 grad_norm: 3.1324 loss: 2.7091 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7091 2023/06/05 10:36:33 - mmengine - INFO - Epoch(train) [96][ 460/2569] lr: 4.0000e-02 eta: 10:23:52 time: 0.2644 data_time: 0.0071 memory: 5828 grad_norm: 3.1633 loss: 2.5559 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5559 2023/06/05 10:36:39 - mmengine - INFO - Epoch(train) [96][ 480/2569] lr: 4.0000e-02 eta: 10:23:47 time: 0.2691 data_time: 0.0073 memory: 5828 grad_norm: 3.1704 loss: 2.4821 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4821 2023/06/05 10:36:44 - mmengine - INFO - Epoch(train) [96][ 500/2569] lr: 4.0000e-02 eta: 10:23:42 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 3.1419 loss: 2.6358 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6358 2023/06/05 10:36:49 - mmengine - INFO - Epoch(train) [96][ 520/2569] lr: 4.0000e-02 eta: 10:23:36 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 3.1277 loss: 2.6398 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6398 2023/06/05 10:36:55 - mmengine - INFO - Epoch(train) [96][ 540/2569] lr: 4.0000e-02 eta: 10:23:31 time: 0.2605 data_time: 0.0070 memory: 5828 grad_norm: 3.1380 loss: 2.6367 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6367 2023/06/05 10:37:00 - mmengine - INFO - Epoch(train) [96][ 560/2569] lr: 4.0000e-02 eta: 10:23:26 time: 0.2739 data_time: 0.0071 memory: 5828 grad_norm: 3.1087 loss: 2.5295 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5295 2023/06/05 10:37:06 - mmengine - INFO - Epoch(train) [96][ 580/2569] lr: 4.0000e-02 eta: 10:23:20 time: 0.2726 data_time: 0.0070 memory: 5828 grad_norm: 3.1600 loss: 2.6252 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6252 2023/06/05 10:37:11 - mmengine - INFO - Epoch(train) [96][ 600/2569] lr: 4.0000e-02 eta: 10:23:15 time: 0.2664 data_time: 0.0077 memory: 5828 grad_norm: 3.0890 loss: 2.7029 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7029 2023/06/05 10:37:16 - mmengine - INFO - Epoch(train) [96][ 620/2569] lr: 4.0000e-02 eta: 10:23:10 time: 0.2779 data_time: 0.0073 memory: 5828 grad_norm: 3.1214 loss: 2.4299 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4299 2023/06/05 10:37:22 - mmengine - INFO - Epoch(train) [96][ 640/2569] lr: 4.0000e-02 eta: 10:23:05 time: 0.2710 data_time: 0.0076 memory: 5828 grad_norm: 3.1374 loss: 2.2726 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2726 2023/06/05 10:37:27 - mmengine - INFO - Epoch(train) [96][ 660/2569] lr: 4.0000e-02 eta: 10:22:59 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 3.0858 loss: 2.6566 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6566 2023/06/05 10:37:33 - mmengine - INFO - Epoch(train) [96][ 680/2569] lr: 4.0000e-02 eta: 10:22:54 time: 0.2711 data_time: 0.0072 memory: 5828 grad_norm: 3.1738 loss: 2.5007 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5007 2023/06/05 10:37:38 - mmengine - INFO - Epoch(train) [96][ 700/2569] lr: 4.0000e-02 eta: 10:22:49 time: 0.2607 data_time: 0.0082 memory: 5828 grad_norm: 3.1013 loss: 2.6511 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6511 2023/06/05 10:37:43 - mmengine - INFO - Epoch(train) [96][ 720/2569] lr: 4.0000e-02 eta: 10:22:43 time: 0.2696 data_time: 0.0077 memory: 5828 grad_norm: 3.1279 loss: 2.4282 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4282 2023/06/05 10:37:48 - mmengine - INFO - Epoch(train) [96][ 740/2569] lr: 4.0000e-02 eta: 10:22:38 time: 0.2589 data_time: 0.0071 memory: 5828 grad_norm: 3.0776 loss: 2.5092 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5092 2023/06/05 10:37:54 - mmengine - INFO - Epoch(train) [96][ 760/2569] lr: 4.0000e-02 eta: 10:22:33 time: 0.2611 data_time: 0.0071 memory: 5828 grad_norm: 3.1304 loss: 2.7021 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7021 2023/06/05 10:37:59 - mmengine - INFO - Epoch(train) [96][ 780/2569] lr: 4.0000e-02 eta: 10:22:27 time: 0.2640 data_time: 0.0071 memory: 5828 grad_norm: 3.1316 loss: 2.7617 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7617 2023/06/05 10:38:04 - mmengine - INFO - Epoch(train) [96][ 800/2569] lr: 4.0000e-02 eta: 10:22:22 time: 0.2720 data_time: 0.0071 memory: 5828 grad_norm: 3.0785 loss: 2.6161 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6161 2023/06/05 10:38:10 - mmengine - INFO - Epoch(train) [96][ 820/2569] lr: 4.0000e-02 eta: 10:22:17 time: 0.2650 data_time: 0.0070 memory: 5828 grad_norm: 3.1345 loss: 2.0337 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0337 2023/06/05 10:38:15 - mmengine - INFO - Epoch(train) [96][ 840/2569] lr: 4.0000e-02 eta: 10:22:11 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 3.1007 loss: 2.2956 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2956 2023/06/05 10:38:20 - mmengine - INFO - Epoch(train) [96][ 860/2569] lr: 4.0000e-02 eta: 10:22:06 time: 0.2662 data_time: 0.0070 memory: 5828 grad_norm: 3.0997 loss: 2.4217 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4217 2023/06/05 10:38:26 - mmengine - INFO - Epoch(train) [96][ 880/2569] lr: 4.0000e-02 eta: 10:22:01 time: 0.2657 data_time: 0.0070 memory: 5828 grad_norm: 3.2175 loss: 2.4929 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4929 2023/06/05 10:38:31 - mmengine - INFO - Epoch(train) [96][ 900/2569] lr: 4.0000e-02 eta: 10:21:55 time: 0.2707 data_time: 0.0073 memory: 5828 grad_norm: 3.1407 loss: 2.1094 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1094 2023/06/05 10:38:36 - mmengine - INFO - Epoch(train) [96][ 920/2569] lr: 4.0000e-02 eta: 10:21:50 time: 0.2605 data_time: 0.0072 memory: 5828 grad_norm: 3.1770 loss: 2.1925 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1925 2023/06/05 10:38:42 - mmengine - INFO - Epoch(train) [96][ 940/2569] lr: 4.0000e-02 eta: 10:21:45 time: 0.2613 data_time: 0.0070 memory: 5828 grad_norm: 3.1516 loss: 2.7250 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.7250 2023/06/05 10:38:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:38:47 - mmengine - INFO - Epoch(train) [96][ 960/2569] lr: 4.0000e-02 eta: 10:21:39 time: 0.2712 data_time: 0.0071 memory: 5828 grad_norm: 3.1594 loss: 2.5082 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5082 2023/06/05 10:38:52 - mmengine - INFO - Epoch(train) [96][ 980/2569] lr: 4.0000e-02 eta: 10:21:34 time: 0.2650 data_time: 0.0070 memory: 5828 grad_norm: 3.1930 loss: 2.8500 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8500 2023/06/05 10:38:58 - mmengine - INFO - Epoch(train) [96][1000/2569] lr: 4.0000e-02 eta: 10:21:29 time: 0.2686 data_time: 0.0073 memory: 5828 grad_norm: 3.1380 loss: 2.5220 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5220 2023/06/05 10:39:03 - mmengine - INFO - Epoch(train) [96][1020/2569] lr: 4.0000e-02 eta: 10:21:24 time: 0.2661 data_time: 0.0070 memory: 5828 grad_norm: 3.1335 loss: 2.6414 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6414 2023/06/05 10:39:08 - mmengine - INFO - Epoch(train) [96][1040/2569] lr: 4.0000e-02 eta: 10:21:18 time: 0.2597 data_time: 0.0071 memory: 5828 grad_norm: 3.0948 loss: 2.2525 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2525 2023/06/05 10:39:13 - mmengine - INFO - Epoch(train) [96][1060/2569] lr: 4.0000e-02 eta: 10:21:13 time: 0.2598 data_time: 0.0072 memory: 5828 grad_norm: 3.0946 loss: 2.6153 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.6153 2023/06/05 10:39:19 - mmengine - INFO - Epoch(train) [96][1080/2569] lr: 4.0000e-02 eta: 10:21:07 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 3.1262 loss: 2.5675 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5675 2023/06/05 10:39:24 - mmengine - INFO - Epoch(train) [96][1100/2569] lr: 4.0000e-02 eta: 10:21:02 time: 0.2621 data_time: 0.0072 memory: 5828 grad_norm: 3.1512 loss: 2.3155 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3155 2023/06/05 10:39:30 - mmengine - INFO - Epoch(train) [96][1120/2569] lr: 4.0000e-02 eta: 10:20:57 time: 0.2783 data_time: 0.0077 memory: 5828 grad_norm: 3.1357 loss: 2.2994 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.2994 2023/06/05 10:39:35 - mmengine - INFO - Epoch(train) [96][1140/2569] lr: 4.0000e-02 eta: 10:20:52 time: 0.2625 data_time: 0.0080 memory: 5828 grad_norm: 3.1495 loss: 2.3602 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3602 2023/06/05 10:39:40 - mmengine - INFO - Epoch(train) [96][1160/2569] lr: 4.0000e-02 eta: 10:20:46 time: 0.2716 data_time: 0.0072 memory: 5828 grad_norm: 3.0619 loss: 2.6155 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6155 2023/06/05 10:39:46 - mmengine - INFO - Epoch(train) [96][1180/2569] lr: 4.0000e-02 eta: 10:20:41 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 3.1347 loss: 2.3964 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3964 2023/06/05 10:39:51 - mmengine - INFO - Epoch(train) [96][1200/2569] lr: 4.0000e-02 eta: 10:20:36 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 3.1510 loss: 2.4860 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4860 2023/06/05 10:39:56 - mmengine - INFO - Epoch(train) [96][1220/2569] lr: 4.0000e-02 eta: 10:20:30 time: 0.2702 data_time: 0.0079 memory: 5828 grad_norm: 3.0755 loss: 2.7114 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7114 2023/06/05 10:40:01 - mmengine - INFO - Epoch(train) [96][1240/2569] lr: 4.0000e-02 eta: 10:20:25 time: 0.2649 data_time: 0.0076 memory: 5828 grad_norm: 3.1597 loss: 2.2812 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2812 2023/06/05 10:40:07 - mmengine - INFO - Epoch(train) [96][1260/2569] lr: 4.0000e-02 eta: 10:20:20 time: 0.2696 data_time: 0.0072 memory: 5828 grad_norm: 3.1826 loss: 2.5587 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5587 2023/06/05 10:40:12 - mmengine - INFO - Epoch(train) [96][1280/2569] lr: 4.0000e-02 eta: 10:20:14 time: 0.2605 data_time: 0.0079 memory: 5828 grad_norm: 3.1671 loss: 2.3776 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3776 2023/06/05 10:40:17 - mmengine - INFO - Epoch(train) [96][1300/2569] lr: 4.0000e-02 eta: 10:20:09 time: 0.2661 data_time: 0.0075 memory: 5828 grad_norm: 3.1423 loss: 2.6263 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6263 2023/06/05 10:40:23 - mmengine - INFO - Epoch(train) [96][1320/2569] lr: 4.0000e-02 eta: 10:20:04 time: 0.2665 data_time: 0.0071 memory: 5828 grad_norm: 3.1486 loss: 2.5363 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.5363 2023/06/05 10:40:28 - mmengine - INFO - Epoch(train) [96][1340/2569] lr: 4.0000e-02 eta: 10:19:58 time: 0.2652 data_time: 0.0073 memory: 5828 grad_norm: 3.1468 loss: 2.5651 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5651 2023/06/05 10:40:33 - mmengine - INFO - Epoch(train) [96][1360/2569] lr: 4.0000e-02 eta: 10:19:53 time: 0.2686 data_time: 0.0073 memory: 5828 grad_norm: 3.1301 loss: 2.7336 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7336 2023/06/05 10:40:39 - mmengine - INFO - Epoch(train) [96][1380/2569] lr: 4.0000e-02 eta: 10:19:48 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 3.1110 loss: 2.3716 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3716 2023/06/05 10:40:44 - mmengine - INFO - Epoch(train) [96][1400/2569] lr: 4.0000e-02 eta: 10:19:43 time: 0.2840 data_time: 0.0077 memory: 5828 grad_norm: 3.1908 loss: 2.4712 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.4712 2023/06/05 10:40:50 - mmengine - INFO - Epoch(train) [96][1420/2569] lr: 4.0000e-02 eta: 10:19:37 time: 0.2595 data_time: 0.0073 memory: 5828 grad_norm: 3.1185 loss: 2.5119 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5119 2023/06/05 10:40:55 - mmengine - INFO - Epoch(train) [96][1440/2569] lr: 4.0000e-02 eta: 10:19:32 time: 0.2672 data_time: 0.0071 memory: 5828 grad_norm: 3.0724 loss: 2.4544 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4544 2023/06/05 10:41:00 - mmengine - INFO - Epoch(train) [96][1460/2569] lr: 4.0000e-02 eta: 10:19:27 time: 0.2602 data_time: 0.0072 memory: 5828 grad_norm: 3.0792 loss: 2.6900 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6900 2023/06/05 10:41:06 - mmengine - INFO - Epoch(train) [96][1480/2569] lr: 4.0000e-02 eta: 10:19:21 time: 0.2764 data_time: 0.0077 memory: 5828 grad_norm: 3.1704 loss: 2.5912 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5912 2023/06/05 10:41:11 - mmengine - INFO - Epoch(train) [96][1500/2569] lr: 4.0000e-02 eta: 10:19:16 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 3.1093 loss: 2.4250 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4250 2023/06/05 10:41:16 - mmengine - INFO - Epoch(train) [96][1520/2569] lr: 4.0000e-02 eta: 10:19:11 time: 0.2748 data_time: 0.0072 memory: 5828 grad_norm: 3.1547 loss: 2.6179 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6179 2023/06/05 10:41:22 - mmengine - INFO - Epoch(train) [96][1540/2569] lr: 4.0000e-02 eta: 10:19:06 time: 0.2738 data_time: 0.0072 memory: 5828 grad_norm: 3.1229 loss: 2.0474 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0474 2023/06/05 10:41:27 - mmengine - INFO - Epoch(train) [96][1560/2569] lr: 4.0000e-02 eta: 10:19:00 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 3.1545 loss: 2.4759 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4759 2023/06/05 10:41:33 - mmengine - INFO - Epoch(train) [96][1580/2569] lr: 4.0000e-02 eta: 10:18:55 time: 0.2692 data_time: 0.0076 memory: 5828 grad_norm: 3.0987 loss: 2.5683 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5683 2023/06/05 10:41:38 - mmengine - INFO - Epoch(train) [96][1600/2569] lr: 4.0000e-02 eta: 10:18:50 time: 0.2670 data_time: 0.0069 memory: 5828 grad_norm: 3.1484 loss: 2.4361 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4361 2023/06/05 10:41:43 - mmengine - INFO - Epoch(train) [96][1620/2569] lr: 4.0000e-02 eta: 10:18:44 time: 0.2705 data_time: 0.0075 memory: 5828 grad_norm: 3.0773 loss: 2.7419 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7419 2023/06/05 10:41:49 - mmengine - INFO - Epoch(train) [96][1640/2569] lr: 4.0000e-02 eta: 10:18:39 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 3.0513 loss: 2.1363 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1363 2023/06/05 10:41:54 - mmengine - INFO - Epoch(train) [96][1660/2569] lr: 4.0000e-02 eta: 10:18:34 time: 0.2655 data_time: 0.0073 memory: 5828 grad_norm: 3.1592 loss: 2.5216 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5216 2023/06/05 10:42:00 - mmengine - INFO - Epoch(train) [96][1680/2569] lr: 4.0000e-02 eta: 10:18:29 time: 0.2723 data_time: 0.0072 memory: 5828 grad_norm: 3.1328 loss: 2.5389 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5389 2023/06/05 10:42:05 - mmengine - INFO - Epoch(train) [96][1700/2569] lr: 4.0000e-02 eta: 10:18:23 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 3.1357 loss: 2.3537 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3537 2023/06/05 10:42:10 - mmengine - INFO - Epoch(train) [96][1720/2569] lr: 4.0000e-02 eta: 10:18:18 time: 0.2642 data_time: 0.0075 memory: 5828 grad_norm: 3.1149 loss: 2.5651 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5651 2023/06/05 10:42:15 - mmengine - INFO - Epoch(train) [96][1740/2569] lr: 4.0000e-02 eta: 10:18:13 time: 0.2594 data_time: 0.0068 memory: 5828 grad_norm: 3.1250 loss: 2.4807 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4807 2023/06/05 10:42:21 - mmengine - INFO - Epoch(train) [96][1760/2569] lr: 4.0000e-02 eta: 10:18:07 time: 0.2764 data_time: 0.0072 memory: 5828 grad_norm: 3.2137 loss: 2.2295 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.2295 2023/06/05 10:42:26 - mmengine - INFO - Epoch(train) [96][1780/2569] lr: 4.0000e-02 eta: 10:18:02 time: 0.2660 data_time: 0.0072 memory: 5828 grad_norm: 3.0470 loss: 2.4849 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.4849 2023/06/05 10:42:32 - mmengine - INFO - Epoch(train) [96][1800/2569] lr: 4.0000e-02 eta: 10:17:57 time: 0.2653 data_time: 0.0068 memory: 5828 grad_norm: 3.1453 loss: 2.7255 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7255 2023/06/05 10:42:37 - mmengine - INFO - Epoch(train) [96][1820/2569] lr: 4.0000e-02 eta: 10:17:51 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 3.1012 loss: 2.7175 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7175 2023/06/05 10:42:42 - mmengine - INFO - Epoch(train) [96][1840/2569] lr: 4.0000e-02 eta: 10:17:46 time: 0.2594 data_time: 0.0070 memory: 5828 grad_norm: 3.1143 loss: 2.8763 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8763 2023/06/05 10:42:48 - mmengine - INFO - Epoch(train) [96][1860/2569] lr: 4.0000e-02 eta: 10:17:41 time: 0.2651 data_time: 0.0068 memory: 5828 grad_norm: 3.1664 loss: 2.4266 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4266 2023/06/05 10:42:53 - mmengine - INFO - Epoch(train) [96][1880/2569] lr: 4.0000e-02 eta: 10:17:35 time: 0.2602 data_time: 0.0071 memory: 5828 grad_norm: 3.1666 loss: 2.4484 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.4484 2023/06/05 10:42:58 - mmengine - INFO - Epoch(train) [96][1900/2569] lr: 4.0000e-02 eta: 10:17:30 time: 0.2626 data_time: 0.0070 memory: 5828 grad_norm: 3.1340 loss: 2.5915 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5915 2023/06/05 10:43:03 - mmengine - INFO - Epoch(train) [96][1920/2569] lr: 4.0000e-02 eta: 10:17:25 time: 0.2617 data_time: 0.0071 memory: 5828 grad_norm: 3.1332 loss: 2.7121 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7121 2023/06/05 10:43:09 - mmengine - INFO - Epoch(train) [96][1940/2569] lr: 4.0000e-02 eta: 10:17:19 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 3.0979 loss: 2.5858 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5858 2023/06/05 10:43:10 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:43:14 - mmengine - INFO - Epoch(train) [96][1960/2569] lr: 4.0000e-02 eta: 10:17:14 time: 0.2736 data_time: 0.0070 memory: 5828 grad_norm: 3.1703 loss: 2.6616 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6616 2023/06/05 10:43:19 - mmengine - INFO - Epoch(train) [96][1980/2569] lr: 4.0000e-02 eta: 10:17:09 time: 0.2672 data_time: 0.0072 memory: 5828 grad_norm: 3.1215 loss: 2.4753 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4753 2023/06/05 10:43:25 - mmengine - INFO - Epoch(train) [96][2000/2569] lr: 4.0000e-02 eta: 10:17:04 time: 0.2788 data_time: 0.0068 memory: 5828 grad_norm: 3.1255 loss: 2.1017 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1017 2023/06/05 10:43:30 - mmengine - INFO - Epoch(train) [96][2020/2569] lr: 4.0000e-02 eta: 10:16:58 time: 0.2698 data_time: 0.0069 memory: 5828 grad_norm: 3.1267 loss: 2.3656 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3656 2023/06/05 10:43:36 - mmengine - INFO - Epoch(train) [96][2040/2569] lr: 4.0000e-02 eta: 10:16:53 time: 0.2709 data_time: 0.0073 memory: 5828 grad_norm: 3.1191 loss: 2.3637 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3637 2023/06/05 10:43:41 - mmengine - INFO - Epoch(train) [96][2060/2569] lr: 4.0000e-02 eta: 10:16:48 time: 0.2682 data_time: 0.0069 memory: 5828 grad_norm: 3.1514 loss: 2.3513 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3513 2023/06/05 10:43:47 - mmengine - INFO - Epoch(train) [96][2080/2569] lr: 4.0000e-02 eta: 10:16:43 time: 0.2711 data_time: 0.0073 memory: 5828 grad_norm: 3.1230 loss: 2.6044 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6044 2023/06/05 10:43:52 - mmengine - INFO - Epoch(train) [96][2100/2569] lr: 4.0000e-02 eta: 10:16:37 time: 0.2695 data_time: 0.0073 memory: 5828 grad_norm: 3.0931 loss: 3.2069 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 3.2069 2023/06/05 10:43:58 - mmengine - INFO - Epoch(train) [96][2120/2569] lr: 4.0000e-02 eta: 10:16:32 time: 0.2818 data_time: 0.0071 memory: 5828 grad_norm: 3.1402 loss: 2.6786 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6786 2023/06/05 10:44:03 - mmengine - INFO - Epoch(train) [96][2140/2569] lr: 4.0000e-02 eta: 10:16:27 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 3.1381 loss: 2.2878 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2878 2023/06/05 10:44:08 - mmengine - INFO - Epoch(train) [96][2160/2569] lr: 4.0000e-02 eta: 10:16:22 time: 0.2715 data_time: 0.0072 memory: 5828 grad_norm: 3.1629 loss: 2.3673 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3673 2023/06/05 10:44:14 - mmengine - INFO - Epoch(train) [96][2180/2569] lr: 4.0000e-02 eta: 10:16:16 time: 0.2790 data_time: 0.0071 memory: 5828 grad_norm: 3.1324 loss: 2.7627 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7627 2023/06/05 10:44:19 - mmengine - INFO - Epoch(train) [96][2200/2569] lr: 4.0000e-02 eta: 10:16:11 time: 0.2657 data_time: 0.0072 memory: 5828 grad_norm: 3.1402 loss: 2.4803 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4803 2023/06/05 10:44:25 - mmengine - INFO - Epoch(train) [96][2220/2569] lr: 4.0000e-02 eta: 10:16:06 time: 0.2792 data_time: 0.0071 memory: 5828 grad_norm: 3.0986 loss: 2.6866 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6866 2023/06/05 10:44:30 - mmengine - INFO - Epoch(train) [96][2240/2569] lr: 4.0000e-02 eta: 10:16:01 time: 0.2695 data_time: 0.0083 memory: 5828 grad_norm: 3.1850 loss: 2.7093 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7093 2023/06/05 10:44:36 - mmengine - INFO - Epoch(train) [96][2260/2569] lr: 4.0000e-02 eta: 10:15:55 time: 0.2684 data_time: 0.0069 memory: 5828 grad_norm: 3.0610 loss: 2.6740 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6740 2023/06/05 10:44:41 - mmengine - INFO - Epoch(train) [96][2280/2569] lr: 4.0000e-02 eta: 10:15:50 time: 0.2640 data_time: 0.0072 memory: 5828 grad_norm: 3.1313 loss: 2.8377 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.8377 2023/06/05 10:44:46 - mmengine - INFO - Epoch(train) [96][2300/2569] lr: 4.0000e-02 eta: 10:15:45 time: 0.2660 data_time: 0.0071 memory: 5828 grad_norm: 3.1190 loss: 2.6406 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6406 2023/06/05 10:44:52 - mmengine - INFO - Epoch(train) [96][2320/2569] lr: 4.0000e-02 eta: 10:15:40 time: 0.2787 data_time: 0.0069 memory: 5828 grad_norm: 3.1392 loss: 2.4839 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.4839 2023/06/05 10:44:57 - mmengine - INFO - Epoch(train) [96][2340/2569] lr: 4.0000e-02 eta: 10:15:34 time: 0.2698 data_time: 0.0070 memory: 5828 grad_norm: 3.1804 loss: 2.8573 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.8573 2023/06/05 10:45:03 - mmengine - INFO - Epoch(train) [96][2360/2569] lr: 4.0000e-02 eta: 10:15:29 time: 0.2690 data_time: 0.0075 memory: 5828 grad_norm: 3.0745 loss: 2.6415 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6415 2023/06/05 10:45:08 - mmengine - INFO - Epoch(train) [96][2380/2569] lr: 4.0000e-02 eta: 10:15:24 time: 0.2739 data_time: 0.0075 memory: 5828 grad_norm: 3.0613 loss: 2.3831 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3831 2023/06/05 10:45:13 - mmengine - INFO - Epoch(train) [96][2400/2569] lr: 4.0000e-02 eta: 10:15:18 time: 0.2609 data_time: 0.0073 memory: 5828 grad_norm: 3.1399 loss: 2.6955 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6955 2023/06/05 10:45:19 - mmengine - INFO - Epoch(train) [96][2420/2569] lr: 4.0000e-02 eta: 10:15:13 time: 0.2615 data_time: 0.0074 memory: 5828 grad_norm: 3.0985 loss: 2.3693 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3693 2023/06/05 10:45:24 - mmengine - INFO - Epoch(train) [96][2440/2569] lr: 4.0000e-02 eta: 10:15:08 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 3.1676 loss: 2.3670 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3670 2023/06/05 10:45:29 - mmengine - INFO - Epoch(train) [96][2460/2569] lr: 4.0000e-02 eta: 10:15:02 time: 0.2664 data_time: 0.0075 memory: 5828 grad_norm: 3.1851 loss: 2.4028 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4028 2023/06/05 10:45:35 - mmengine - INFO - Epoch(train) [96][2480/2569] lr: 4.0000e-02 eta: 10:14:57 time: 0.2667 data_time: 0.0071 memory: 5828 grad_norm: 3.1206 loss: 2.6541 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6541 2023/06/05 10:45:40 - mmengine - INFO - Epoch(train) [96][2500/2569] lr: 4.0000e-02 eta: 10:14:52 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 3.0902 loss: 2.4821 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4821 2023/06/05 10:45:45 - mmengine - INFO - Epoch(train) [96][2520/2569] lr: 4.0000e-02 eta: 10:14:46 time: 0.2685 data_time: 0.0070 memory: 5828 grad_norm: 3.1598 loss: 2.4880 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4880 2023/06/05 10:45:51 - mmengine - INFO - Epoch(train) [96][2540/2569] lr: 4.0000e-02 eta: 10:14:41 time: 0.2751 data_time: 0.0072 memory: 5828 grad_norm: 3.1744 loss: 2.2634 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2634 2023/06/05 10:45:56 - mmengine - INFO - Epoch(train) [96][2560/2569] lr: 4.0000e-02 eta: 10:14:36 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 3.0909 loss: 2.3135 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3135 2023/06/05 10:45:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:45:58 - mmengine - INFO - Epoch(train) [96][2569/2569] lr: 4.0000e-02 eta: 10:14:33 time: 0.2571 data_time: 0.0069 memory: 5828 grad_norm: 3.1211 loss: 2.1540 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1540 2023/06/05 10:45:58 - mmengine - INFO - Saving checkpoint at 96 epochs 2023/06/05 10:46:06 - mmengine - INFO - Epoch(train) [97][ 20/2569] lr: 4.0000e-02 eta: 10:14:29 time: 0.3101 data_time: 0.0548 memory: 5828 grad_norm: 3.0652 loss: 2.6510 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6510 2023/06/05 10:46:12 - mmengine - INFO - Epoch(train) [97][ 40/2569] lr: 4.0000e-02 eta: 10:14:23 time: 0.2738 data_time: 0.0072 memory: 5828 grad_norm: 3.1069 loss: 2.1728 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1728 2023/06/05 10:46:17 - mmengine - INFO - Epoch(train) [97][ 60/2569] lr: 4.0000e-02 eta: 10:14:18 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 3.1001 loss: 2.6362 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6362 2023/06/05 10:46:23 - mmengine - INFO - Epoch(train) [97][ 80/2569] lr: 4.0000e-02 eta: 10:14:13 time: 0.2835 data_time: 0.0073 memory: 5828 grad_norm: 3.1050 loss: 2.3533 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3533 2023/06/05 10:46:28 - mmengine - INFO - Epoch(train) [97][ 100/2569] lr: 4.0000e-02 eta: 10:14:08 time: 0.2640 data_time: 0.0071 memory: 5828 grad_norm: 3.1326 loss: 2.5895 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5895 2023/06/05 10:46:34 - mmengine - INFO - Epoch(train) [97][ 120/2569] lr: 4.0000e-02 eta: 10:14:03 time: 0.2804 data_time: 0.0076 memory: 5828 grad_norm: 3.1804 loss: 2.4456 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4456 2023/06/05 10:46:39 - mmengine - INFO - Epoch(train) [97][ 140/2569] lr: 4.0000e-02 eta: 10:13:57 time: 0.2642 data_time: 0.0071 memory: 5828 grad_norm: 3.1948 loss: 2.2585 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2585 2023/06/05 10:46:44 - mmengine - INFO - Epoch(train) [97][ 160/2569] lr: 4.0000e-02 eta: 10:13:52 time: 0.2649 data_time: 0.0070 memory: 5828 grad_norm: 3.1118 loss: 2.3061 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3061 2023/06/05 10:46:50 - mmengine - INFO - Epoch(train) [97][ 180/2569] lr: 4.0000e-02 eta: 10:13:47 time: 0.2826 data_time: 0.0072 memory: 5828 grad_norm: 3.1078 loss: 2.4706 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4706 2023/06/05 10:46:55 - mmengine - INFO - Epoch(train) [97][ 200/2569] lr: 4.0000e-02 eta: 10:13:41 time: 0.2670 data_time: 0.0070 memory: 5828 grad_norm: 3.1879 loss: 2.2018 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2018 2023/06/05 10:47:01 - mmengine - INFO - Epoch(train) [97][ 220/2569] lr: 4.0000e-02 eta: 10:13:36 time: 0.2678 data_time: 0.0070 memory: 5828 grad_norm: 3.1258 loss: 2.5112 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5112 2023/06/05 10:47:06 - mmengine - INFO - Epoch(train) [97][ 240/2569] lr: 4.0000e-02 eta: 10:13:31 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 3.1380 loss: 2.4630 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4630 2023/06/05 10:47:11 - mmengine - INFO - Epoch(train) [97][ 260/2569] lr: 4.0000e-02 eta: 10:13:25 time: 0.2650 data_time: 0.0071 memory: 5828 grad_norm: 3.0960 loss: 2.4267 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4267 2023/06/05 10:47:17 - mmengine - INFO - Epoch(train) [97][ 280/2569] lr: 4.0000e-02 eta: 10:13:20 time: 0.2714 data_time: 0.0070 memory: 5828 grad_norm: 3.0727 loss: 2.3925 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.3925 2023/06/05 10:47:22 - mmengine - INFO - Epoch(train) [97][ 300/2569] lr: 4.0000e-02 eta: 10:13:15 time: 0.2687 data_time: 0.0074 memory: 5828 grad_norm: 3.1390 loss: 2.4965 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4965 2023/06/05 10:47:28 - mmengine - INFO - Epoch(train) [97][ 320/2569] lr: 4.0000e-02 eta: 10:13:10 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 3.1474 loss: 2.6192 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6192 2023/06/05 10:47:33 - mmengine - INFO - Epoch(train) [97][ 340/2569] lr: 4.0000e-02 eta: 10:13:04 time: 0.2654 data_time: 0.0071 memory: 5828 grad_norm: 3.1646 loss: 2.5292 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5292 2023/06/05 10:47:38 - mmengine - INFO - Epoch(train) [97][ 360/2569] lr: 4.0000e-02 eta: 10:12:59 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 3.1357 loss: 2.4595 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4595 2023/06/05 10:47:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:47:44 - mmengine - INFO - Epoch(train) [97][ 380/2569] lr: 4.0000e-02 eta: 10:12:54 time: 0.2661 data_time: 0.0072 memory: 5828 grad_norm: 3.1039 loss: 2.4880 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4880 2023/06/05 10:47:49 - mmengine - INFO - Epoch(train) [97][ 400/2569] lr: 4.0000e-02 eta: 10:12:48 time: 0.2581 data_time: 0.0070 memory: 5828 grad_norm: 3.1411 loss: 2.3444 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3444 2023/06/05 10:47:54 - mmengine - INFO - Epoch(train) [97][ 420/2569] lr: 4.0000e-02 eta: 10:12:43 time: 0.2712 data_time: 0.0068 memory: 5828 grad_norm: 3.1403 loss: 2.6130 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6130 2023/06/05 10:47:59 - mmengine - INFO - Epoch(train) [97][ 440/2569] lr: 4.0000e-02 eta: 10:12:38 time: 0.2605 data_time: 0.0072 memory: 5828 grad_norm: 3.0878 loss: 2.6144 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.6144 2023/06/05 10:48:05 - mmengine - INFO - Epoch(train) [97][ 460/2569] lr: 4.0000e-02 eta: 10:12:32 time: 0.2623 data_time: 0.0068 memory: 5828 grad_norm: 3.1539 loss: 2.6049 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6049 2023/06/05 10:48:10 - mmengine - INFO - Epoch(train) [97][ 480/2569] lr: 4.0000e-02 eta: 10:12:27 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 3.1647 loss: 2.5354 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.5354 2023/06/05 10:48:15 - mmengine - INFO - Epoch(train) [97][ 500/2569] lr: 4.0000e-02 eta: 10:12:22 time: 0.2734 data_time: 0.0068 memory: 5828 grad_norm: 3.1096 loss: 2.3381 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.3381 2023/06/05 10:48:21 - mmengine - INFO - Epoch(train) [97][ 520/2569] lr: 4.0000e-02 eta: 10:12:16 time: 0.2696 data_time: 0.0073 memory: 5828 grad_norm: 3.1298 loss: 2.6109 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6109 2023/06/05 10:48:26 - mmengine - INFO - Epoch(train) [97][ 540/2569] lr: 4.0000e-02 eta: 10:12:11 time: 0.2616 data_time: 0.0072 memory: 5828 grad_norm: 3.1576 loss: 2.2868 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2868 2023/06/05 10:48:31 - mmengine - INFO - Epoch(train) [97][ 560/2569] lr: 4.0000e-02 eta: 10:12:06 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 3.1080 loss: 2.6812 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6812 2023/06/05 10:48:37 - mmengine - INFO - Epoch(train) [97][ 580/2569] lr: 4.0000e-02 eta: 10:12:00 time: 0.2616 data_time: 0.0069 memory: 5828 grad_norm: 3.1328 loss: 2.7972 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7972 2023/06/05 10:48:42 - mmengine - INFO - Epoch(train) [97][ 600/2569] lr: 4.0000e-02 eta: 10:11:55 time: 0.2595 data_time: 0.0076 memory: 5828 grad_norm: 3.1699 loss: 2.4739 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4739 2023/06/05 10:48:47 - mmengine - INFO - Epoch(train) [97][ 620/2569] lr: 4.0000e-02 eta: 10:11:50 time: 0.2680 data_time: 0.0069 memory: 5828 grad_norm: 3.1380 loss: 2.4891 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4891 2023/06/05 10:48:53 - mmengine - INFO - Epoch(train) [97][ 640/2569] lr: 4.0000e-02 eta: 10:11:44 time: 0.2656 data_time: 0.0070 memory: 5828 grad_norm: 3.1422 loss: 2.4891 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4891 2023/06/05 10:48:58 - mmengine - INFO - Epoch(train) [97][ 660/2569] lr: 4.0000e-02 eta: 10:11:39 time: 0.2778 data_time: 0.0072 memory: 5828 grad_norm: 3.1949 loss: 2.6093 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6093 2023/06/05 10:49:03 - mmengine - INFO - Epoch(train) [97][ 680/2569] lr: 4.0000e-02 eta: 10:11:34 time: 0.2621 data_time: 0.0070 memory: 5828 grad_norm: 3.1604 loss: 2.2798 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2798 2023/06/05 10:49:09 - mmengine - INFO - Epoch(train) [97][ 700/2569] lr: 4.0000e-02 eta: 10:11:29 time: 0.2603 data_time: 0.0075 memory: 5828 grad_norm: 3.1221 loss: 2.6758 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6758 2023/06/05 10:49:14 - mmengine - INFO - Epoch(train) [97][ 720/2569] lr: 4.0000e-02 eta: 10:11:23 time: 0.2586 data_time: 0.0074 memory: 5828 grad_norm: 3.1732 loss: 2.5630 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5630 2023/06/05 10:49:19 - mmengine - INFO - Epoch(train) [97][ 740/2569] lr: 4.0000e-02 eta: 10:11:18 time: 0.2788 data_time: 0.0072 memory: 5828 grad_norm: 3.0836 loss: 2.3602 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3602 2023/06/05 10:49:25 - mmengine - INFO - Epoch(train) [97][ 760/2569] lr: 4.0000e-02 eta: 10:11:13 time: 0.2668 data_time: 0.0075 memory: 5828 grad_norm: 3.1696 loss: 2.5738 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5738 2023/06/05 10:49:30 - mmengine - INFO - Epoch(train) [97][ 780/2569] lr: 4.0000e-02 eta: 10:11:07 time: 0.2687 data_time: 0.0079 memory: 5828 grad_norm: 3.1946 loss: 2.5151 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5151 2023/06/05 10:49:35 - mmengine - INFO - Epoch(train) [97][ 800/2569] lr: 4.0000e-02 eta: 10:11:02 time: 0.2596 data_time: 0.0072 memory: 5828 grad_norm: 3.1499 loss: 2.5115 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5115 2023/06/05 10:49:41 - mmengine - INFO - Epoch(train) [97][ 820/2569] lr: 4.0000e-02 eta: 10:10:57 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 3.1749 loss: 2.6684 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.6684 2023/06/05 10:49:46 - mmengine - INFO - Epoch(train) [97][ 840/2569] lr: 4.0000e-02 eta: 10:10:51 time: 0.2616 data_time: 0.0072 memory: 5828 grad_norm: 3.0820 loss: 2.9691 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.9691 2023/06/05 10:49:51 - mmengine - INFO - Epoch(train) [97][ 860/2569] lr: 4.0000e-02 eta: 10:10:46 time: 0.2698 data_time: 0.0070 memory: 5828 grad_norm: 3.0666 loss: 2.5086 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5086 2023/06/05 10:49:56 - mmengine - INFO - Epoch(train) [97][ 880/2569] lr: 4.0000e-02 eta: 10:10:41 time: 0.2604 data_time: 0.0075 memory: 5828 grad_norm: 3.1452 loss: 2.8137 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.8137 2023/06/05 10:50:02 - mmengine - INFO - Epoch(train) [97][ 900/2569] lr: 4.0000e-02 eta: 10:10:35 time: 0.2691 data_time: 0.0069 memory: 5828 grad_norm: 3.1514 loss: 2.6063 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.6063 2023/06/05 10:50:07 - mmengine - INFO - Epoch(train) [97][ 920/2569] lr: 4.0000e-02 eta: 10:10:30 time: 0.2716 data_time: 0.0071 memory: 5828 grad_norm: 3.1596 loss: 2.8624 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8624 2023/06/05 10:50:12 - mmengine - INFO - Epoch(train) [97][ 940/2569] lr: 4.0000e-02 eta: 10:10:25 time: 0.2616 data_time: 0.0070 memory: 5828 grad_norm: 3.1728 loss: 2.5253 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5253 2023/06/05 10:50:18 - mmengine - INFO - Epoch(train) [97][ 960/2569] lr: 4.0000e-02 eta: 10:10:19 time: 0.2648 data_time: 0.0071 memory: 5828 grad_norm: 3.1263 loss: 2.8574 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.8574 2023/06/05 10:50:23 - mmengine - INFO - Epoch(train) [97][ 980/2569] lr: 4.0000e-02 eta: 10:10:14 time: 0.2598 data_time: 0.0073 memory: 5828 grad_norm: 3.1061 loss: 2.5570 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5570 2023/06/05 10:50:29 - mmengine - INFO - Epoch(train) [97][1000/2569] lr: 4.0000e-02 eta: 10:10:09 time: 0.2825 data_time: 0.0067 memory: 5828 grad_norm: 3.2015 loss: 2.4436 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4436 2023/06/05 10:50:34 - mmengine - INFO - Epoch(train) [97][1020/2569] lr: 4.0000e-02 eta: 10:10:04 time: 0.2678 data_time: 0.0070 memory: 5828 grad_norm: 3.1850 loss: 2.4041 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4041 2023/06/05 10:50:40 - mmengine - INFO - Epoch(train) [97][1040/2569] lr: 4.0000e-02 eta: 10:09:58 time: 0.2785 data_time: 0.0071 memory: 5828 grad_norm: 3.1189 loss: 2.4990 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4990 2023/06/05 10:50:45 - mmengine - INFO - Epoch(train) [97][1060/2569] lr: 4.0000e-02 eta: 10:09:53 time: 0.2600 data_time: 0.0073 memory: 5828 grad_norm: 3.1174 loss: 2.2957 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2957 2023/06/05 10:50:50 - mmengine - INFO - Epoch(train) [97][1080/2569] lr: 4.0000e-02 eta: 10:09:48 time: 0.2648 data_time: 0.0084 memory: 5828 grad_norm: 3.2386 loss: 2.5313 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5313 2023/06/05 10:50:55 - mmengine - INFO - Epoch(train) [97][1100/2569] lr: 4.0000e-02 eta: 10:09:42 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.1546 loss: 2.7348 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.7348 2023/06/05 10:51:01 - mmengine - INFO - Epoch(train) [97][1120/2569] lr: 4.0000e-02 eta: 10:09:37 time: 0.2719 data_time: 0.0075 memory: 5828 grad_norm: 3.0885 loss: 2.6702 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6702 2023/06/05 10:51:06 - mmengine - INFO - Epoch(train) [97][1140/2569] lr: 4.0000e-02 eta: 10:09:32 time: 0.2648 data_time: 0.0079 memory: 5828 grad_norm: 3.1772 loss: 2.3136 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3136 2023/06/05 10:51:11 - mmengine - INFO - Epoch(train) [97][1160/2569] lr: 4.0000e-02 eta: 10:09:26 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.1668 loss: 2.3193 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3193 2023/06/05 10:51:17 - mmengine - INFO - Epoch(train) [97][1180/2569] lr: 4.0000e-02 eta: 10:09:21 time: 0.2601 data_time: 0.0076 memory: 5828 grad_norm: 3.1523 loss: 2.6768 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6768 2023/06/05 10:51:22 - mmengine - INFO - Epoch(train) [97][1200/2569] lr: 4.0000e-02 eta: 10:09:16 time: 0.2591 data_time: 0.0076 memory: 5828 grad_norm: 3.1744 loss: 2.5315 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5315 2023/06/05 10:51:27 - mmengine - INFO - Epoch(train) [97][1220/2569] lr: 4.0000e-02 eta: 10:09:10 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 3.1161 loss: 2.4459 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4459 2023/06/05 10:51:32 - mmengine - INFO - Epoch(train) [97][1240/2569] lr: 4.0000e-02 eta: 10:09:05 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 3.1452 loss: 2.4218 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4218 2023/06/05 10:51:37 - mmengine - INFO - Epoch(train) [97][1260/2569] lr: 4.0000e-02 eta: 10:09:00 time: 0.2634 data_time: 0.0073 memory: 5828 grad_norm: 3.2227 loss: 2.3865 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3865 2023/06/05 10:51:43 - mmengine - INFO - Epoch(train) [97][1280/2569] lr: 4.0000e-02 eta: 10:08:54 time: 0.2601 data_time: 0.0071 memory: 5828 grad_norm: 3.1539 loss: 2.4259 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4259 2023/06/05 10:51:48 - mmengine - INFO - Epoch(train) [97][1300/2569] lr: 4.0000e-02 eta: 10:08:49 time: 0.2763 data_time: 0.0075 memory: 5828 grad_norm: 3.1726 loss: 2.3802 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3802 2023/06/05 10:51:53 - mmengine - INFO - Epoch(train) [97][1320/2569] lr: 4.0000e-02 eta: 10:08:44 time: 0.2611 data_time: 0.0068 memory: 5828 grad_norm: 3.1300 loss: 2.5617 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5617 2023/06/05 10:51:59 - mmengine - INFO - Epoch(train) [97][1340/2569] lr: 4.0000e-02 eta: 10:08:38 time: 0.2647 data_time: 0.0070 memory: 5828 grad_norm: 3.1765 loss: 2.3148 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3148 2023/06/05 10:52:04 - mmengine - INFO - Epoch(train) [97][1360/2569] lr: 4.0000e-02 eta: 10:08:33 time: 0.2635 data_time: 0.0072 memory: 5828 grad_norm: 3.1746 loss: 2.3670 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3670 2023/06/05 10:52:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:52:09 - mmengine - INFO - Epoch(train) [97][1380/2569] lr: 4.0000e-02 eta: 10:08:28 time: 0.2688 data_time: 0.0072 memory: 5828 grad_norm: 3.1142 loss: 2.3941 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3941 2023/06/05 10:52:15 - mmengine - INFO - Epoch(train) [97][1400/2569] lr: 4.0000e-02 eta: 10:08:23 time: 0.2834 data_time: 0.0074 memory: 5828 grad_norm: 3.1208 loss: 2.3339 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3339 2023/06/05 10:52:20 - mmengine - INFO - Epoch(train) [97][1420/2569] lr: 4.0000e-02 eta: 10:08:17 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 3.1381 loss: 2.3590 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3590 2023/06/05 10:52:26 - mmengine - INFO - Epoch(train) [97][1440/2569] lr: 4.0000e-02 eta: 10:08:12 time: 0.2735 data_time: 0.0074 memory: 5828 grad_norm: 3.1928 loss: 2.4766 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4766 2023/06/05 10:52:31 - mmengine - INFO - Epoch(train) [97][1460/2569] lr: 4.0000e-02 eta: 10:08:07 time: 0.2699 data_time: 0.0071 memory: 5828 grad_norm: 3.1441 loss: 2.4629 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4629 2023/06/05 10:52:37 - mmengine - INFO - Epoch(train) [97][1480/2569] lr: 4.0000e-02 eta: 10:08:01 time: 0.2647 data_time: 0.0069 memory: 5828 grad_norm: 3.1472 loss: 2.5467 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5467 2023/06/05 10:52:42 - mmengine - INFO - Epoch(train) [97][1500/2569] lr: 4.0000e-02 eta: 10:07:56 time: 0.2643 data_time: 0.0069 memory: 5828 grad_norm: 3.1112 loss: 2.4075 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4075 2023/06/05 10:52:47 - mmengine - INFO - Epoch(train) [97][1520/2569] lr: 4.0000e-02 eta: 10:07:51 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 3.1663 loss: 2.3874 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3874 2023/06/05 10:52:53 - mmengine - INFO - Epoch(train) [97][1540/2569] lr: 4.0000e-02 eta: 10:07:46 time: 0.2700 data_time: 0.0069 memory: 5828 grad_norm: 3.0934 loss: 2.4461 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.4461 2023/06/05 10:52:58 - mmengine - INFO - Epoch(train) [97][1560/2569] lr: 4.0000e-02 eta: 10:07:40 time: 0.2594 data_time: 0.0074 memory: 5828 grad_norm: 3.1680 loss: 2.4680 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4680 2023/06/05 10:53:03 - mmengine - INFO - Epoch(train) [97][1580/2569] lr: 4.0000e-02 eta: 10:07:35 time: 0.2607 data_time: 0.0071 memory: 5828 grad_norm: 3.1283 loss: 2.4640 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4640 2023/06/05 10:53:08 - mmengine - INFO - Epoch(train) [97][1600/2569] lr: 4.0000e-02 eta: 10:07:29 time: 0.2598 data_time: 0.0069 memory: 5828 grad_norm: 3.1615 loss: 2.4440 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4440 2023/06/05 10:53:14 - mmengine - INFO - Epoch(train) [97][1620/2569] lr: 4.0000e-02 eta: 10:07:24 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 3.1126 loss: 2.2091 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2091 2023/06/05 10:53:19 - mmengine - INFO - Epoch(train) [97][1640/2569] lr: 4.0000e-02 eta: 10:07:19 time: 0.2650 data_time: 0.0071 memory: 5828 grad_norm: 3.2171 loss: 2.7288 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7288 2023/06/05 10:53:24 - mmengine - INFO - Epoch(train) [97][1660/2569] lr: 4.0000e-02 eta: 10:07:13 time: 0.2599 data_time: 0.0077 memory: 5828 grad_norm: 3.0997 loss: 2.5759 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5759 2023/06/05 10:53:30 - mmengine - INFO - Epoch(train) [97][1680/2569] lr: 4.0000e-02 eta: 10:07:08 time: 0.2843 data_time: 0.0071 memory: 5828 grad_norm: 3.1091 loss: 2.3677 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3677 2023/06/05 10:53:35 - mmengine - INFO - Epoch(train) [97][1700/2569] lr: 4.0000e-02 eta: 10:07:03 time: 0.2600 data_time: 0.0072 memory: 5828 grad_norm: 3.1188 loss: 2.9590 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9590 2023/06/05 10:53:41 - mmengine - INFO - Epoch(train) [97][1720/2569] lr: 4.0000e-02 eta: 10:06:58 time: 0.2782 data_time: 0.0069 memory: 5828 grad_norm: 3.1846 loss: 2.5848 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.5848 2023/06/05 10:53:46 - mmengine - INFO - Epoch(train) [97][1740/2569] lr: 4.0000e-02 eta: 10:06:52 time: 0.2602 data_time: 0.0073 memory: 5828 grad_norm: 3.1955 loss: 2.3951 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3951 2023/06/05 10:53:51 - mmengine - INFO - Epoch(train) [97][1760/2569] lr: 4.0000e-02 eta: 10:06:47 time: 0.2688 data_time: 0.0076 memory: 5828 grad_norm: 3.0821 loss: 2.4874 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4874 2023/06/05 10:53:57 - mmengine - INFO - Epoch(train) [97][1780/2569] lr: 4.0000e-02 eta: 10:06:42 time: 0.2656 data_time: 0.0070 memory: 5828 grad_norm: 3.1125 loss: 2.7082 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7082 2023/06/05 10:54:02 - mmengine - INFO - Epoch(train) [97][1800/2569] lr: 4.0000e-02 eta: 10:06:36 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 3.1094 loss: 2.5763 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5763 2023/06/05 10:54:07 - mmengine - INFO - Epoch(train) [97][1820/2569] lr: 4.0000e-02 eta: 10:06:31 time: 0.2612 data_time: 0.0072 memory: 5828 grad_norm: 3.1785 loss: 2.5437 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5437 2023/06/05 10:54:13 - mmengine - INFO - Epoch(train) [97][1840/2569] lr: 4.0000e-02 eta: 10:06:26 time: 0.2689 data_time: 0.0071 memory: 5828 grad_norm: 3.1985 loss: 2.5526 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5526 2023/06/05 10:54:18 - mmengine - INFO - Epoch(train) [97][1860/2569] lr: 4.0000e-02 eta: 10:06:20 time: 0.2695 data_time: 0.0069 memory: 5828 grad_norm: 3.1331 loss: 2.6036 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6036 2023/06/05 10:54:23 - mmengine - INFO - Epoch(train) [97][1880/2569] lr: 4.0000e-02 eta: 10:06:15 time: 0.2670 data_time: 0.0072 memory: 5828 grad_norm: 3.1517 loss: 2.4392 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.4392 2023/06/05 10:54:29 - mmengine - INFO - Epoch(train) [97][1900/2569] lr: 4.0000e-02 eta: 10:06:10 time: 0.2755 data_time: 0.0071 memory: 5828 grad_norm: 3.1467 loss: 2.2491 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2491 2023/06/05 10:54:34 - mmengine - INFO - Epoch(train) [97][1920/2569] lr: 4.0000e-02 eta: 10:06:05 time: 0.2641 data_time: 0.0071 memory: 5828 grad_norm: 3.2017 loss: 2.4536 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4536 2023/06/05 10:54:39 - mmengine - INFO - Epoch(train) [97][1940/2569] lr: 4.0000e-02 eta: 10:05:59 time: 0.2664 data_time: 0.0071 memory: 5828 grad_norm: 3.1376 loss: 2.4126 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.4126 2023/06/05 10:54:45 - mmengine - INFO - Epoch(train) [97][1960/2569] lr: 4.0000e-02 eta: 10:05:54 time: 0.2699 data_time: 0.0072 memory: 5828 grad_norm: 3.1433 loss: 2.1963 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1963 2023/06/05 10:54:50 - mmengine - INFO - Epoch(train) [97][1980/2569] lr: 4.0000e-02 eta: 10:05:49 time: 0.2705 data_time: 0.0070 memory: 5828 grad_norm: 3.1636 loss: 2.2519 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2519 2023/06/05 10:54:55 - mmengine - INFO - Epoch(train) [97][2000/2569] lr: 4.0000e-02 eta: 10:05:43 time: 0.2618 data_time: 0.0070 memory: 5828 grad_norm: 3.0710 loss: 2.3571 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.3571 2023/06/05 10:55:01 - mmengine - INFO - Epoch(train) [97][2020/2569] lr: 4.0000e-02 eta: 10:05:38 time: 0.2763 data_time: 0.0072 memory: 5828 grad_norm: 3.1399 loss: 2.0790 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0790 2023/06/05 10:55:06 - mmengine - INFO - Epoch(train) [97][2040/2569] lr: 4.0000e-02 eta: 10:05:33 time: 0.2601 data_time: 0.0071 memory: 5828 grad_norm: 3.1407 loss: 2.5811 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5811 2023/06/05 10:55:12 - mmengine - INFO - Epoch(train) [97][2060/2569] lr: 4.0000e-02 eta: 10:05:28 time: 0.2730 data_time: 0.0068 memory: 5828 grad_norm: 3.1007 loss: 2.2896 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2896 2023/06/05 10:55:17 - mmengine - INFO - Epoch(train) [97][2080/2569] lr: 4.0000e-02 eta: 10:05:22 time: 0.2764 data_time: 0.0071 memory: 5828 grad_norm: 3.1095 loss: 2.4846 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4846 2023/06/05 10:55:23 - mmengine - INFO - Epoch(train) [97][2100/2569] lr: 4.0000e-02 eta: 10:05:17 time: 0.2641 data_time: 0.0070 memory: 5828 grad_norm: 3.1717 loss: 2.3813 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3813 2023/06/05 10:55:28 - mmengine - INFO - Epoch(train) [97][2120/2569] lr: 4.0000e-02 eta: 10:05:12 time: 0.2692 data_time: 0.0070 memory: 5828 grad_norm: 3.0997 loss: 2.8556 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.8556 2023/06/05 10:55:33 - mmengine - INFO - Epoch(train) [97][2140/2569] lr: 4.0000e-02 eta: 10:05:06 time: 0.2668 data_time: 0.0069 memory: 5828 grad_norm: 3.2218 loss: 2.4319 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.4319 2023/06/05 10:55:39 - mmengine - INFO - Epoch(train) [97][2160/2569] lr: 4.0000e-02 eta: 10:05:01 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 3.1271 loss: 2.5372 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5372 2023/06/05 10:55:44 - mmengine - INFO - Epoch(train) [97][2180/2569] lr: 4.0000e-02 eta: 10:04:56 time: 0.2595 data_time: 0.0074 memory: 5828 grad_norm: 3.0707 loss: 3.1840 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 3.1840 2023/06/05 10:55:49 - mmengine - INFO - Epoch(train) [97][2200/2569] lr: 4.0000e-02 eta: 10:04:51 time: 0.2701 data_time: 0.0070 memory: 5828 grad_norm: 3.1100 loss: 2.5246 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5246 2023/06/05 10:55:55 - mmengine - INFO - Epoch(train) [97][2220/2569] lr: 4.0000e-02 eta: 10:04:45 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 3.1791 loss: 2.7541 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7541 2023/06/05 10:56:00 - mmengine - INFO - Epoch(train) [97][2240/2569] lr: 4.0000e-02 eta: 10:04:40 time: 0.2694 data_time: 0.0071 memory: 5828 grad_norm: 3.1073 loss: 2.3810 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3810 2023/06/05 10:56:05 - mmengine - INFO - Epoch(train) [97][2260/2569] lr: 4.0000e-02 eta: 10:04:35 time: 0.2646 data_time: 0.0074 memory: 5828 grad_norm: 3.0969 loss: 2.5881 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5881 2023/06/05 10:56:11 - mmengine - INFO - Epoch(train) [97][2280/2569] lr: 4.0000e-02 eta: 10:04:29 time: 0.2733 data_time: 0.0069 memory: 5828 grad_norm: 3.1032 loss: 2.6102 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6102 2023/06/05 10:56:16 - mmengine - INFO - Epoch(train) [97][2300/2569] lr: 4.0000e-02 eta: 10:04:24 time: 0.2677 data_time: 0.0068 memory: 5828 grad_norm: 3.0548 loss: 2.6327 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6327 2023/06/05 10:56:21 - mmengine - INFO - Epoch(train) [97][2320/2569] lr: 4.0000e-02 eta: 10:04:19 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 3.1205 loss: 2.8398 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.8398 2023/06/05 10:56:27 - mmengine - INFO - Epoch(train) [97][2340/2569] lr: 4.0000e-02 eta: 10:04:13 time: 0.2603 data_time: 0.0068 memory: 5828 grad_norm: 3.0965 loss: 2.2863 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2863 2023/06/05 10:56:32 - mmengine - INFO - Epoch(train) [97][2360/2569] lr: 4.0000e-02 eta: 10:04:08 time: 0.2591 data_time: 0.0075 memory: 5828 grad_norm: 3.1427 loss: 2.3612 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3612 2023/06/05 10:56:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:56:37 - mmengine - INFO - Epoch(train) [97][2380/2569] lr: 4.0000e-02 eta: 10:04:03 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 3.1673 loss: 2.5420 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5420 2023/06/05 10:56:42 - mmengine - INFO - Epoch(train) [97][2400/2569] lr: 4.0000e-02 eta: 10:03:57 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 3.1236 loss: 2.5420 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5420 2023/06/05 10:56:48 - mmengine - INFO - Epoch(train) [97][2420/2569] lr: 4.0000e-02 eta: 10:03:52 time: 0.2666 data_time: 0.0070 memory: 5828 grad_norm: 3.1282 loss: 2.3198 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3198 2023/06/05 10:56:53 - mmengine - INFO - Epoch(train) [97][2440/2569] lr: 4.0000e-02 eta: 10:03:47 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 3.1047 loss: 2.7797 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7797 2023/06/05 10:56:58 - mmengine - INFO - Epoch(train) [97][2460/2569] lr: 4.0000e-02 eta: 10:03:41 time: 0.2672 data_time: 0.0072 memory: 5828 grad_norm: 3.1835 loss: 2.6129 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6129 2023/06/05 10:57:04 - mmengine - INFO - Epoch(train) [97][2480/2569] lr: 4.0000e-02 eta: 10:03:36 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 3.1320 loss: 2.8066 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8066 2023/06/05 10:57:09 - mmengine - INFO - Epoch(train) [97][2500/2569] lr: 4.0000e-02 eta: 10:03:31 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 3.1894 loss: 2.4157 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4157 2023/06/05 10:57:14 - mmengine - INFO - Epoch(train) [97][2520/2569] lr: 4.0000e-02 eta: 10:03:25 time: 0.2712 data_time: 0.0072 memory: 5828 grad_norm: 3.1285 loss: 2.5420 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5420 2023/06/05 10:57:20 - mmengine - INFO - Epoch(train) [97][2540/2569] lr: 4.0000e-02 eta: 10:03:20 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 3.1719 loss: 2.7299 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.7299 2023/06/05 10:57:25 - mmengine - INFO - Epoch(train) [97][2560/2569] lr: 4.0000e-02 eta: 10:03:15 time: 0.2693 data_time: 0.0073 memory: 5828 grad_norm: 3.1012 loss: 2.5205 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5205 2023/06/05 10:57:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 10:57:28 - mmengine - INFO - Epoch(train) [97][2569/2569] lr: 4.0000e-02 eta: 10:03:12 time: 0.2571 data_time: 0.0071 memory: 5828 grad_norm: 3.1102 loss: 2.5175 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 2.5175 2023/06/05 10:57:34 - mmengine - INFO - Epoch(train) [98][ 20/2569] lr: 4.0000e-02 eta: 10:03:08 time: 0.3401 data_time: 0.0594 memory: 5828 grad_norm: 3.0838 loss: 2.5405 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5405 2023/06/05 10:57:40 - mmengine - INFO - Epoch(train) [98][ 40/2569] lr: 4.0000e-02 eta: 10:03:03 time: 0.2667 data_time: 0.0069 memory: 5828 grad_norm: 3.1787 loss: 2.6369 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6369 2023/06/05 10:57:45 - mmengine - INFO - Epoch(train) [98][ 60/2569] lr: 4.0000e-02 eta: 10:02:57 time: 0.2631 data_time: 0.0072 memory: 5828 grad_norm: 3.0900 loss: 2.3465 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.3465 2023/06/05 10:57:50 - mmengine - INFO - Epoch(train) [98][ 80/2569] lr: 4.0000e-02 eta: 10:02:52 time: 0.2633 data_time: 0.0073 memory: 5828 grad_norm: 3.0212 loss: 2.2679 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2679 2023/06/05 10:57:55 - mmengine - INFO - Epoch(train) [98][ 100/2569] lr: 4.0000e-02 eta: 10:02:47 time: 0.2599 data_time: 0.0081 memory: 5828 grad_norm: 3.1334 loss: 2.4120 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4120 2023/06/05 10:58:01 - mmengine - INFO - Epoch(train) [98][ 120/2569] lr: 4.0000e-02 eta: 10:02:41 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 3.1454 loss: 2.6545 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6545 2023/06/05 10:58:06 - mmengine - INFO - Epoch(train) [98][ 140/2569] lr: 4.0000e-02 eta: 10:02:36 time: 0.2676 data_time: 0.0071 memory: 5828 grad_norm: 3.1342 loss: 2.5259 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5259 2023/06/05 10:58:11 - mmengine - INFO - Epoch(train) [98][ 160/2569] lr: 4.0000e-02 eta: 10:02:31 time: 0.2622 data_time: 0.0077 memory: 5828 grad_norm: 3.0724 loss: 2.5386 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5386 2023/06/05 10:58:17 - mmengine - INFO - Epoch(train) [98][ 180/2569] lr: 4.0000e-02 eta: 10:02:25 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 3.1064 loss: 2.7692 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7692 2023/06/05 10:58:22 - mmengine - INFO - Epoch(train) [98][ 200/2569] lr: 4.0000e-02 eta: 10:02:20 time: 0.2599 data_time: 0.0081 memory: 5828 grad_norm: 3.1765 loss: 2.2595 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2595 2023/06/05 10:58:27 - mmengine - INFO - Epoch(train) [98][ 220/2569] lr: 4.0000e-02 eta: 10:02:14 time: 0.2611 data_time: 0.0068 memory: 5828 grad_norm: 3.0997 loss: 2.4388 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4388 2023/06/05 10:58:32 - mmengine - INFO - Epoch(train) [98][ 240/2569] lr: 4.0000e-02 eta: 10:02:09 time: 0.2604 data_time: 0.0070 memory: 5828 grad_norm: 3.1285 loss: 2.4882 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.4882 2023/06/05 10:58:38 - mmengine - INFO - Epoch(train) [98][ 260/2569] lr: 4.0000e-02 eta: 10:02:04 time: 0.2599 data_time: 0.0070 memory: 5828 grad_norm: 3.1607 loss: 2.3355 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3355 2023/06/05 10:58:43 - mmengine - INFO - Epoch(train) [98][ 280/2569] lr: 4.0000e-02 eta: 10:01:58 time: 0.2713 data_time: 0.0070 memory: 5828 grad_norm: 3.1012 loss: 2.4838 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4838 2023/06/05 10:58:48 - mmengine - INFO - Epoch(train) [98][ 300/2569] lr: 4.0000e-02 eta: 10:01:53 time: 0.2672 data_time: 0.0071 memory: 5828 grad_norm: 3.1410 loss: 2.2590 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.2590 2023/06/05 10:58:54 - mmengine - INFO - Epoch(train) [98][ 320/2569] lr: 4.0000e-02 eta: 10:01:48 time: 0.2780 data_time: 0.0072 memory: 5828 grad_norm: 3.1882 loss: 2.5392 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5392 2023/06/05 10:58:59 - mmengine - INFO - Epoch(train) [98][ 340/2569] lr: 4.0000e-02 eta: 10:01:43 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 3.1796 loss: 2.4094 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4094 2023/06/05 10:59:05 - mmengine - INFO - Epoch(train) [98][ 360/2569] lr: 4.0000e-02 eta: 10:01:37 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 3.1090 loss: 2.5786 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.5786 2023/06/05 10:59:10 - mmengine - INFO - Epoch(train) [98][ 380/2569] lr: 4.0000e-02 eta: 10:01:32 time: 0.2670 data_time: 0.0068 memory: 5828 grad_norm: 3.1016 loss: 2.3205 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3205 2023/06/05 10:59:15 - mmengine - INFO - Epoch(train) [98][ 400/2569] lr: 4.0000e-02 eta: 10:01:27 time: 0.2661 data_time: 0.0072 memory: 5828 grad_norm: 3.1122 loss: 2.3242 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3242 2023/06/05 10:59:20 - mmengine - INFO - Epoch(train) [98][ 420/2569] lr: 4.0000e-02 eta: 10:01:21 time: 0.2602 data_time: 0.0071 memory: 5828 grad_norm: 3.1802 loss: 2.4973 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4973 2023/06/05 10:59:26 - mmengine - INFO - Epoch(train) [98][ 440/2569] lr: 4.0000e-02 eta: 10:01:16 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 3.1519 loss: 2.5767 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5767 2023/06/05 10:59:31 - mmengine - INFO - Epoch(train) [98][ 460/2569] lr: 4.0000e-02 eta: 10:01:11 time: 0.2666 data_time: 0.0072 memory: 5828 grad_norm: 3.1443 loss: 2.7649 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.7649 2023/06/05 10:59:36 - mmengine - INFO - Epoch(train) [98][ 480/2569] lr: 4.0000e-02 eta: 10:01:05 time: 0.2636 data_time: 0.0070 memory: 5828 grad_norm: 3.1815 loss: 2.2384 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2384 2023/06/05 10:59:42 - mmengine - INFO - Epoch(train) [98][ 500/2569] lr: 4.0000e-02 eta: 10:01:00 time: 0.2604 data_time: 0.0076 memory: 5828 grad_norm: 3.1490 loss: 2.5924 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5924 2023/06/05 10:59:47 - mmengine - INFO - Epoch(train) [98][ 520/2569] lr: 4.0000e-02 eta: 10:00:55 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.1508 loss: 2.5545 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.5545 2023/06/05 10:59:52 - mmengine - INFO - Epoch(train) [98][ 540/2569] lr: 4.0000e-02 eta: 10:00:49 time: 0.2658 data_time: 0.0070 memory: 5828 grad_norm: 3.2205 loss: 2.5086 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5086 2023/06/05 10:59:58 - mmengine - INFO - Epoch(train) [98][ 560/2569] lr: 4.0000e-02 eta: 10:00:44 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 3.1769 loss: 2.5651 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5651 2023/06/05 11:00:03 - mmengine - INFO - Epoch(train) [98][ 580/2569] lr: 4.0000e-02 eta: 10:00:39 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 3.1665 loss: 3.1262 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 3.1262 2023/06/05 11:00:08 - mmengine - INFO - Epoch(train) [98][ 600/2569] lr: 4.0000e-02 eta: 10:00:33 time: 0.2661 data_time: 0.0082 memory: 5828 grad_norm: 3.1896 loss: 2.1392 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1392 2023/06/05 11:00:14 - mmengine - INFO - Epoch(train) [98][ 620/2569] lr: 4.0000e-02 eta: 10:00:28 time: 0.2733 data_time: 0.0070 memory: 5828 grad_norm: 3.0949 loss: 2.4649 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4649 2023/06/05 11:00:19 - mmengine - INFO - Epoch(train) [98][ 640/2569] lr: 4.0000e-02 eta: 10:00:23 time: 0.2664 data_time: 0.0070 memory: 5828 grad_norm: 3.1204 loss: 2.5386 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.5386 2023/06/05 11:00:24 - mmengine - INFO - Epoch(train) [98][ 660/2569] lr: 4.0000e-02 eta: 10:00:18 time: 0.2679 data_time: 0.0069 memory: 5828 grad_norm: 3.1550 loss: 2.4453 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4453 2023/06/05 11:00:30 - mmengine - INFO - Epoch(train) [98][ 680/2569] lr: 4.0000e-02 eta: 10:00:12 time: 0.2819 data_time: 0.0070 memory: 5828 grad_norm: 3.1561 loss: 2.5284 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5284 2023/06/05 11:00:35 - mmengine - INFO - Epoch(train) [98][ 700/2569] lr: 4.0000e-02 eta: 10:00:07 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 3.1229 loss: 2.6193 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6193 2023/06/05 11:00:41 - mmengine - INFO - Epoch(train) [98][ 720/2569] lr: 4.0000e-02 eta: 10:00:02 time: 0.2790 data_time: 0.0075 memory: 5828 grad_norm: 3.1149 loss: 2.7262 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7262 2023/06/05 11:00:46 - mmengine - INFO - Epoch(train) [98][ 740/2569] lr: 4.0000e-02 eta: 9:59:57 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 3.1532 loss: 2.6592 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6592 2023/06/05 11:00:51 - mmengine - INFO - Epoch(train) [98][ 760/2569] lr: 4.0000e-02 eta: 9:59:51 time: 0.2613 data_time: 0.0069 memory: 5828 grad_norm: 3.1619 loss: 2.8736 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8736 2023/06/05 11:00:57 - mmengine - INFO - Epoch(train) [98][ 780/2569] lr: 4.0000e-02 eta: 9:59:46 time: 0.2662 data_time: 0.0070 memory: 5828 grad_norm: 3.1638 loss: 2.5021 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5021 2023/06/05 11:01:02 - mmengine - INFO - Epoch(train) [98][ 800/2569] lr: 4.0000e-02 eta: 9:59:41 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 3.1481 loss: 2.3117 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3117 2023/06/05 11:01:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:01:07 - mmengine - INFO - Epoch(train) [98][ 820/2569] lr: 4.0000e-02 eta: 9:59:35 time: 0.2606 data_time: 0.0070 memory: 5828 grad_norm: 3.0769 loss: 2.3050 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3050 2023/06/05 11:01:13 - mmengine - INFO - Epoch(train) [98][ 840/2569] lr: 4.0000e-02 eta: 9:59:30 time: 0.2661 data_time: 0.0070 memory: 5828 grad_norm: 3.1226 loss: 2.5498 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5498 2023/06/05 11:01:18 - mmengine - INFO - Epoch(train) [98][ 860/2569] lr: 4.0000e-02 eta: 9:59:25 time: 0.2654 data_time: 0.0070 memory: 5828 grad_norm: 3.1211 loss: 2.6270 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6270 2023/06/05 11:01:23 - mmengine - INFO - Epoch(train) [98][ 880/2569] lr: 4.0000e-02 eta: 9:59:19 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 3.1336 loss: 2.2249 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2249 2023/06/05 11:01:29 - mmengine - INFO - Epoch(train) [98][ 900/2569] lr: 4.0000e-02 eta: 9:59:14 time: 0.2593 data_time: 0.0071 memory: 5828 grad_norm: 3.1633 loss: 2.2481 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2481 2023/06/05 11:01:34 - mmengine - INFO - Epoch(train) [98][ 920/2569] lr: 4.0000e-02 eta: 9:59:09 time: 0.2688 data_time: 0.0068 memory: 5828 grad_norm: 3.0869 loss: 2.3203 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.3203 2023/06/05 11:01:39 - mmengine - INFO - Epoch(train) [98][ 940/2569] lr: 4.0000e-02 eta: 9:59:03 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 3.1439 loss: 2.7600 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7600 2023/06/05 11:01:45 - mmengine - INFO - Epoch(train) [98][ 960/2569] lr: 4.0000e-02 eta: 9:58:58 time: 0.2784 data_time: 0.0068 memory: 5828 grad_norm: 3.1736 loss: 2.4495 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4495 2023/06/05 11:01:50 - mmengine - INFO - Epoch(train) [98][ 980/2569] lr: 4.0000e-02 eta: 9:58:53 time: 0.2656 data_time: 0.0067 memory: 5828 grad_norm: 3.1225 loss: 2.5754 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5754 2023/06/05 11:01:55 - mmengine - INFO - Epoch(train) [98][1000/2569] lr: 4.0000e-02 eta: 9:58:48 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 3.1688 loss: 2.3909 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.3909 2023/06/05 11:02:01 - mmengine - INFO - Epoch(train) [98][1020/2569] lr: 4.0000e-02 eta: 9:58:42 time: 0.2601 data_time: 0.0071 memory: 5828 grad_norm: 3.1288 loss: 2.1553 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1553 2023/06/05 11:02:06 - mmengine - INFO - Epoch(train) [98][1040/2569] lr: 4.0000e-02 eta: 9:58:37 time: 0.2652 data_time: 0.0071 memory: 5828 grad_norm: 3.1155 loss: 2.2537 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2537 2023/06/05 11:02:11 - mmengine - INFO - Epoch(train) [98][1060/2569] lr: 4.0000e-02 eta: 9:58:31 time: 0.2631 data_time: 0.0070 memory: 5828 grad_norm: 3.1775 loss: 2.2109 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2109 2023/06/05 11:02:17 - mmengine - INFO - Epoch(train) [98][1080/2569] lr: 4.0000e-02 eta: 9:58:26 time: 0.2727 data_time: 0.0071 memory: 5828 grad_norm: 3.2033 loss: 2.2427 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.2427 2023/06/05 11:02:22 - mmengine - INFO - Epoch(train) [98][1100/2569] lr: 4.0000e-02 eta: 9:58:21 time: 0.2725 data_time: 0.0075 memory: 5828 grad_norm: 3.1430 loss: 2.5709 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.5709 2023/06/05 11:02:27 - mmengine - INFO - Epoch(train) [98][1120/2569] lr: 4.0000e-02 eta: 9:58:16 time: 0.2615 data_time: 0.0073 memory: 5828 grad_norm: 3.0708 loss: 2.4783 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4783 2023/06/05 11:02:33 - mmengine - INFO - Epoch(train) [98][1140/2569] lr: 4.0000e-02 eta: 9:58:10 time: 0.2716 data_time: 0.0087 memory: 5828 grad_norm: 3.1663 loss: 2.8208 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8208 2023/06/05 11:02:38 - mmengine - INFO - Epoch(train) [98][1160/2569] lr: 4.0000e-02 eta: 9:58:05 time: 0.2659 data_time: 0.0072 memory: 5828 grad_norm: 3.1018 loss: 2.4393 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4393 2023/06/05 11:02:44 - mmengine - INFO - Epoch(train) [98][1180/2569] lr: 4.0000e-02 eta: 9:58:00 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 3.0868 loss: 2.5073 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5073 2023/06/05 11:02:49 - mmengine - INFO - Epoch(train) [98][1200/2569] lr: 4.0000e-02 eta: 9:57:54 time: 0.2698 data_time: 0.0071 memory: 5828 grad_norm: 3.1813 loss: 2.6512 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6512 2023/06/05 11:02:54 - mmengine - INFO - Epoch(train) [98][1220/2569] lr: 4.0000e-02 eta: 9:57:49 time: 0.2743 data_time: 0.0072 memory: 5828 grad_norm: 3.1049 loss: 2.2661 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2661 2023/06/05 11:03:00 - mmengine - INFO - Epoch(train) [98][1240/2569] lr: 4.0000e-02 eta: 9:57:44 time: 0.2603 data_time: 0.0085 memory: 5828 grad_norm: 3.1246 loss: 2.1826 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1826 2023/06/05 11:03:05 - mmengine - INFO - Epoch(train) [98][1260/2569] lr: 4.0000e-02 eta: 9:57:39 time: 0.2660 data_time: 0.0074 memory: 5828 grad_norm: 3.0636 loss: 2.3721 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.3721 2023/06/05 11:03:10 - mmengine - INFO - Epoch(train) [98][1280/2569] lr: 4.0000e-02 eta: 9:57:33 time: 0.2626 data_time: 0.0082 memory: 5828 grad_norm: 3.1470 loss: 2.4440 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4440 2023/06/05 11:03:16 - mmengine - INFO - Epoch(train) [98][1300/2569] lr: 4.0000e-02 eta: 9:57:28 time: 0.2663 data_time: 0.0083 memory: 5828 grad_norm: 3.2196 loss: 2.6214 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6214 2023/06/05 11:03:21 - mmengine - INFO - Epoch(train) [98][1320/2569] lr: 4.0000e-02 eta: 9:57:23 time: 0.2706 data_time: 0.0067 memory: 5828 grad_norm: 3.1126 loss: 2.2975 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2975 2023/06/05 11:03:26 - mmengine - INFO - Epoch(train) [98][1340/2569] lr: 4.0000e-02 eta: 9:57:17 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 3.0907 loss: 2.5508 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5508 2023/06/05 11:03:32 - mmengine - INFO - Epoch(train) [98][1360/2569] lr: 4.0000e-02 eta: 9:57:12 time: 0.2710 data_time: 0.0070 memory: 5828 grad_norm: 3.1860 loss: 2.5656 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5656 2023/06/05 11:03:37 - mmengine - INFO - Epoch(train) [98][1380/2569] lr: 4.0000e-02 eta: 9:57:07 time: 0.2646 data_time: 0.0089 memory: 5828 grad_norm: 3.1110 loss: 2.5110 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5110 2023/06/05 11:03:42 - mmengine - INFO - Epoch(train) [98][1400/2569] lr: 4.0000e-02 eta: 9:57:01 time: 0.2586 data_time: 0.0075 memory: 5828 grad_norm: 3.1036 loss: 2.3758 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3758 2023/06/05 11:03:48 - mmengine - INFO - Epoch(train) [98][1420/2569] lr: 4.0000e-02 eta: 9:56:56 time: 0.2663 data_time: 0.0071 memory: 5828 grad_norm: 3.1740 loss: 2.7600 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7600 2023/06/05 11:03:53 - mmengine - INFO - Epoch(train) [98][1440/2569] lr: 4.0000e-02 eta: 9:56:51 time: 0.2602 data_time: 0.0072 memory: 5828 grad_norm: 3.1278 loss: 2.2404 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2404 2023/06/05 11:03:58 - mmengine - INFO - Epoch(train) [98][1460/2569] lr: 4.0000e-02 eta: 9:56:45 time: 0.2671 data_time: 0.0071 memory: 5828 grad_norm: 3.1428 loss: 2.5185 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5185 2023/06/05 11:04:04 - mmengine - INFO - Epoch(train) [98][1480/2569] lr: 4.0000e-02 eta: 9:56:40 time: 0.2762 data_time: 0.0070 memory: 5828 grad_norm: 3.0684 loss: 2.2406 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2406 2023/06/05 11:04:09 - mmengine - INFO - Epoch(train) [98][1500/2569] lr: 4.0000e-02 eta: 9:56:35 time: 0.2706 data_time: 0.0072 memory: 5828 grad_norm: 3.0791 loss: 2.2102 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2102 2023/06/05 11:04:14 - mmengine - INFO - Epoch(train) [98][1520/2569] lr: 4.0000e-02 eta: 9:56:30 time: 0.2630 data_time: 0.0072 memory: 5828 grad_norm: 3.0400 loss: 2.5215 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5215 2023/06/05 11:04:20 - mmengine - INFO - Epoch(train) [98][1540/2569] lr: 4.0000e-02 eta: 9:56:24 time: 0.2632 data_time: 0.0071 memory: 5828 grad_norm: 3.1837 loss: 2.4932 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4932 2023/06/05 11:04:25 - mmengine - INFO - Epoch(train) [98][1560/2569] lr: 4.0000e-02 eta: 9:56:19 time: 0.2641 data_time: 0.0069 memory: 5828 grad_norm: 3.1424 loss: 2.4232 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4232 2023/06/05 11:04:30 - mmengine - INFO - Epoch(train) [98][1580/2569] lr: 4.0000e-02 eta: 9:56:14 time: 0.2702 data_time: 0.0072 memory: 5828 grad_norm: 3.1720 loss: 2.4921 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.4921 2023/06/05 11:04:36 - mmengine - INFO - Epoch(train) [98][1600/2569] lr: 4.0000e-02 eta: 9:56:08 time: 0.2586 data_time: 0.0071 memory: 5828 grad_norm: 3.1688 loss: 2.4425 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4425 2023/06/05 11:04:41 - mmengine - INFO - Epoch(train) [98][1620/2569] lr: 4.0000e-02 eta: 9:56:03 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 3.1605 loss: 2.5440 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.5440 2023/06/05 11:04:46 - mmengine - INFO - Epoch(train) [98][1640/2569] lr: 4.0000e-02 eta: 9:55:58 time: 0.2617 data_time: 0.0070 memory: 5828 grad_norm: 3.1503 loss: 2.6702 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6702 2023/06/05 11:04:51 - mmengine - INFO - Epoch(train) [98][1660/2569] lr: 4.0000e-02 eta: 9:55:52 time: 0.2603 data_time: 0.0072 memory: 5828 grad_norm: 3.1198 loss: 2.7584 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7584 2023/06/05 11:04:57 - mmengine - INFO - Epoch(train) [98][1680/2569] lr: 4.0000e-02 eta: 9:55:47 time: 0.2604 data_time: 0.0077 memory: 5828 grad_norm: 3.1897 loss: 2.5128 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5128 2023/06/05 11:05:02 - mmengine - INFO - Epoch(train) [98][1700/2569] lr: 4.0000e-02 eta: 9:55:41 time: 0.2662 data_time: 0.0069 memory: 5828 grad_norm: 3.1273 loss: 2.5086 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.5086 2023/06/05 11:05:07 - mmengine - INFO - Epoch(train) [98][1720/2569] lr: 4.0000e-02 eta: 9:55:36 time: 0.2605 data_time: 0.0072 memory: 5828 grad_norm: 3.2178 loss: 2.3022 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3022 2023/06/05 11:05:12 - mmengine - INFO - Epoch(train) [98][1740/2569] lr: 4.0000e-02 eta: 9:55:31 time: 0.2636 data_time: 0.0072 memory: 5828 grad_norm: 3.1064 loss: 2.5846 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5846 2023/06/05 11:05:18 - mmengine - INFO - Epoch(train) [98][1760/2569] lr: 4.0000e-02 eta: 9:55:25 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 3.1586 loss: 2.7183 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7183 2023/06/05 11:05:23 - mmengine - INFO - Epoch(train) [98][1780/2569] lr: 4.0000e-02 eta: 9:55:20 time: 0.2742 data_time: 0.0071 memory: 5828 grad_norm: 3.1679 loss: 2.4029 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4029 2023/06/05 11:05:28 - mmengine - INFO - Epoch(train) [98][1800/2569] lr: 4.0000e-02 eta: 9:55:15 time: 0.2595 data_time: 0.0074 memory: 5828 grad_norm: 3.1247 loss: 2.3192 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3192 2023/06/05 11:05:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:05:34 - mmengine - INFO - Epoch(train) [98][1820/2569] lr: 4.0000e-02 eta: 9:55:10 time: 0.2715 data_time: 0.0072 memory: 5828 grad_norm: 3.0842 loss: 2.2581 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2581 2023/06/05 11:05:39 - mmengine - INFO - Epoch(train) [98][1840/2569] lr: 4.0000e-02 eta: 9:55:04 time: 0.2706 data_time: 0.0073 memory: 5828 grad_norm: 3.1478 loss: 2.3221 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3221 2023/06/05 11:05:45 - mmengine - INFO - Epoch(train) [98][1860/2569] lr: 4.0000e-02 eta: 9:54:59 time: 0.2802 data_time: 0.0089 memory: 5828 grad_norm: 3.1598 loss: 2.6558 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6558 2023/06/05 11:05:50 - mmengine - INFO - Epoch(train) [98][1880/2569] lr: 4.0000e-02 eta: 9:54:54 time: 0.2708 data_time: 0.0072 memory: 5828 grad_norm: 3.0905 loss: 2.5034 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5034 2023/06/05 11:05:56 - mmengine - INFO - Epoch(train) [98][1900/2569] lr: 4.0000e-02 eta: 9:54:49 time: 0.2666 data_time: 0.0074 memory: 5828 grad_norm: 3.1543 loss: 2.8029 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.8029 2023/06/05 11:06:01 - mmengine - INFO - Epoch(train) [98][1920/2569] lr: 4.0000e-02 eta: 9:54:43 time: 0.2664 data_time: 0.0071 memory: 5828 grad_norm: 3.1524 loss: 2.7255 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7255 2023/06/05 11:06:06 - mmengine - INFO - Epoch(train) [98][1940/2569] lr: 4.0000e-02 eta: 9:54:38 time: 0.2648 data_time: 0.0075 memory: 5828 grad_norm: 3.1207 loss: 2.7608 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7608 2023/06/05 11:06:12 - mmengine - INFO - Epoch(train) [98][1960/2569] lr: 4.0000e-02 eta: 9:54:33 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 3.1831 loss: 2.3665 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3665 2023/06/05 11:06:17 - mmengine - INFO - Epoch(train) [98][1980/2569] lr: 4.0000e-02 eta: 9:54:27 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 3.1355 loss: 2.5765 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5765 2023/06/05 11:06:22 - mmengine - INFO - Epoch(train) [98][2000/2569] lr: 4.0000e-02 eta: 9:54:22 time: 0.2732 data_time: 0.0072 memory: 5828 grad_norm: 3.1385 loss: 2.3677 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3677 2023/06/05 11:06:28 - mmengine - INFO - Epoch(train) [98][2020/2569] lr: 4.0000e-02 eta: 9:54:17 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 3.0871 loss: 2.5361 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5361 2023/06/05 11:06:33 - mmengine - INFO - Epoch(train) [98][2040/2569] lr: 4.0000e-02 eta: 9:54:11 time: 0.2685 data_time: 0.0071 memory: 5828 grad_norm: 3.1233 loss: 2.5548 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5548 2023/06/05 11:06:38 - mmengine - INFO - Epoch(train) [98][2060/2569] lr: 4.0000e-02 eta: 9:54:06 time: 0.2663 data_time: 0.0071 memory: 5828 grad_norm: 3.1467 loss: 2.3925 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3925 2023/06/05 11:06:44 - mmengine - INFO - Epoch(train) [98][2080/2569] lr: 4.0000e-02 eta: 9:54:01 time: 0.2665 data_time: 0.0074 memory: 5828 grad_norm: 3.1200 loss: 2.5879 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5879 2023/06/05 11:06:49 - mmengine - INFO - Epoch(train) [98][2100/2569] lr: 4.0000e-02 eta: 9:53:56 time: 0.2764 data_time: 0.0073 memory: 5828 grad_norm: 3.1217 loss: 2.6654 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6654 2023/06/05 11:06:55 - mmengine - INFO - Epoch(train) [98][2120/2569] lr: 4.0000e-02 eta: 9:53:50 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 3.1041 loss: 2.6501 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.6501 2023/06/05 11:07:00 - mmengine - INFO - Epoch(train) [98][2140/2569] lr: 4.0000e-02 eta: 9:53:45 time: 0.2670 data_time: 0.0068 memory: 5828 grad_norm: 3.1345 loss: 2.4647 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4647 2023/06/05 11:07:05 - mmengine - INFO - Epoch(train) [98][2160/2569] lr: 4.0000e-02 eta: 9:53:40 time: 0.2611 data_time: 0.0068 memory: 5828 grad_norm: 3.0811 loss: 2.0801 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0801 2023/06/05 11:07:10 - mmengine - INFO - Epoch(train) [98][2180/2569] lr: 4.0000e-02 eta: 9:53:34 time: 0.2600 data_time: 0.0070 memory: 5828 grad_norm: 3.1800 loss: 2.5918 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5918 2023/06/05 11:07:16 - mmengine - INFO - Epoch(train) [98][2200/2569] lr: 4.0000e-02 eta: 9:53:29 time: 0.2696 data_time: 0.0071 memory: 5828 grad_norm: 3.1360 loss: 2.3414 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3414 2023/06/05 11:07:21 - mmengine - INFO - Epoch(train) [98][2220/2569] lr: 4.0000e-02 eta: 9:53:24 time: 0.2610 data_time: 0.0070 memory: 5828 grad_norm: 3.0993 loss: 2.5471 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5471 2023/06/05 11:07:27 - mmengine - INFO - Epoch(train) [98][2240/2569] lr: 4.0000e-02 eta: 9:53:18 time: 0.2832 data_time: 0.0069 memory: 5828 grad_norm: 3.1291 loss: 2.6215 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6215 2023/06/05 11:07:32 - mmengine - INFO - Epoch(train) [98][2260/2569] lr: 4.0000e-02 eta: 9:53:13 time: 0.2706 data_time: 0.0072 memory: 5828 grad_norm: 3.0731 loss: 2.4159 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4159 2023/06/05 11:07:38 - mmengine - INFO - Epoch(train) [98][2280/2569] lr: 4.0000e-02 eta: 9:53:08 time: 0.2725 data_time: 0.0069 memory: 5828 grad_norm: 3.1563 loss: 2.5973 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5973 2023/06/05 11:07:43 - mmengine - INFO - Epoch(train) [98][2300/2569] lr: 4.0000e-02 eta: 9:53:03 time: 0.2767 data_time: 0.0070 memory: 5828 grad_norm: 3.2094 loss: 2.6134 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6134 2023/06/05 11:07:49 - mmengine - INFO - Epoch(train) [98][2320/2569] lr: 4.0000e-02 eta: 9:52:57 time: 0.2724 data_time: 0.0071 memory: 5828 grad_norm: 3.1457 loss: 2.6988 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6988 2023/06/05 11:07:54 - mmengine - INFO - Epoch(train) [98][2340/2569] lr: 4.0000e-02 eta: 9:52:52 time: 0.2726 data_time: 0.0072 memory: 5828 grad_norm: 3.1335 loss: 2.5306 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5306 2023/06/05 11:07:59 - mmengine - INFO - Epoch(train) [98][2360/2569] lr: 4.0000e-02 eta: 9:52:47 time: 0.2727 data_time: 0.0070 memory: 5828 grad_norm: 3.1266 loss: 2.5963 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5963 2023/06/05 11:08:05 - mmengine - INFO - Epoch(train) [98][2380/2569] lr: 4.0000e-02 eta: 9:52:42 time: 0.2640 data_time: 0.0070 memory: 5828 grad_norm: 3.0850 loss: 2.7078 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7078 2023/06/05 11:08:10 - mmengine - INFO - Epoch(train) [98][2400/2569] lr: 4.0000e-02 eta: 9:52:37 time: 0.2807 data_time: 0.0070 memory: 5828 grad_norm: 3.2241 loss: 2.0168 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0168 2023/06/05 11:08:16 - mmengine - INFO - Epoch(train) [98][2420/2569] lr: 4.0000e-02 eta: 9:52:31 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 3.2053 loss: 2.2459 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2459 2023/06/05 11:08:21 - mmengine - INFO - Epoch(train) [98][2440/2569] lr: 4.0000e-02 eta: 9:52:26 time: 0.2645 data_time: 0.0069 memory: 5828 grad_norm: 3.1148 loss: 2.5703 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5703 2023/06/05 11:08:26 - mmengine - INFO - Epoch(train) [98][2460/2569] lr: 4.0000e-02 eta: 9:52:20 time: 0.2607 data_time: 0.0069 memory: 5828 grad_norm: 3.1111 loss: 2.2348 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2348 2023/06/05 11:08:32 - mmengine - INFO - Epoch(train) [98][2480/2569] lr: 4.0000e-02 eta: 9:52:15 time: 0.2734 data_time: 0.0070 memory: 5828 grad_norm: 3.1626 loss: 2.6492 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.6492 2023/06/05 11:08:37 - mmengine - INFO - Epoch(train) [98][2500/2569] lr: 4.0000e-02 eta: 9:52:10 time: 0.2604 data_time: 0.0075 memory: 5828 grad_norm: 3.1690 loss: 2.5895 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5895 2023/06/05 11:08:42 - mmengine - INFO - Epoch(train) [98][2520/2569] lr: 4.0000e-02 eta: 9:52:05 time: 0.2716 data_time: 0.0076 memory: 5828 grad_norm: 3.1213 loss: 2.4036 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4036 2023/06/05 11:08:47 - mmengine - INFO - Epoch(train) [98][2540/2569] lr: 4.0000e-02 eta: 9:51:59 time: 0.2630 data_time: 0.0071 memory: 5828 grad_norm: 3.1247 loss: 2.4154 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4154 2023/06/05 11:08:53 - mmengine - INFO - Epoch(train) [98][2560/2569] lr: 4.0000e-02 eta: 9:51:54 time: 0.2578 data_time: 0.0073 memory: 5828 grad_norm: 3.1940 loss: 2.3287 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3287 2023/06/05 11:08:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:08:55 - mmengine - INFO - Epoch(train) [98][2569/2569] lr: 4.0000e-02 eta: 9:51:51 time: 0.2529 data_time: 0.0072 memory: 5828 grad_norm: 3.2548 loss: 2.2911 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.2911 2023/06/05 11:09:02 - mmengine - INFO - Epoch(train) [99][ 20/2569] lr: 4.0000e-02 eta: 9:51:47 time: 0.3427 data_time: 0.0635 memory: 5828 grad_norm: 3.0981 loss: 2.2869 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2869 2023/06/05 11:09:07 - mmengine - INFO - Epoch(train) [99][ 40/2569] lr: 4.0000e-02 eta: 9:51:42 time: 0.2725 data_time: 0.0072 memory: 5828 grad_norm: 3.1938 loss: 2.3557 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3557 2023/06/05 11:09:13 - mmengine - INFO - Epoch(train) [99][ 60/2569] lr: 4.0000e-02 eta: 9:51:36 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 3.0729 loss: 2.4214 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4214 2023/06/05 11:09:18 - mmengine - INFO - Epoch(train) [99][ 80/2569] lr: 4.0000e-02 eta: 9:51:31 time: 0.2628 data_time: 0.0071 memory: 5828 grad_norm: 3.1267 loss: 2.8866 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8866 2023/06/05 11:09:23 - mmengine - INFO - Epoch(train) [99][ 100/2569] lr: 4.0000e-02 eta: 9:51:26 time: 0.2737 data_time: 0.0069 memory: 5828 grad_norm: 3.0765 loss: 2.7015 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7015 2023/06/05 11:09:29 - mmengine - INFO - Epoch(train) [99][ 120/2569] lr: 4.0000e-02 eta: 9:51:20 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 3.1069 loss: 2.4241 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.4241 2023/06/05 11:09:34 - mmengine - INFO - Epoch(train) [99][ 140/2569] lr: 4.0000e-02 eta: 9:51:15 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 3.1785 loss: 2.4724 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4724 2023/06/05 11:09:39 - mmengine - INFO - Epoch(train) [99][ 160/2569] lr: 4.0000e-02 eta: 9:51:10 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 3.1723 loss: 2.6133 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6133 2023/06/05 11:09:45 - mmengine - INFO - Epoch(train) [99][ 180/2569] lr: 4.0000e-02 eta: 9:51:04 time: 0.2761 data_time: 0.0073 memory: 5828 grad_norm: 3.1456 loss: 2.4202 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4202 2023/06/05 11:09:50 - mmengine - INFO - Epoch(train) [99][ 200/2569] lr: 4.0000e-02 eta: 9:50:59 time: 0.2719 data_time: 0.0072 memory: 5828 grad_norm: 3.1193 loss: 2.6561 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.6561 2023/06/05 11:09:56 - mmengine - INFO - Epoch(train) [99][ 220/2569] lr: 4.0000e-02 eta: 9:50:54 time: 0.2725 data_time: 0.0075 memory: 5828 grad_norm: 3.2068 loss: 2.7868 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7868 2023/06/05 11:10:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:10:01 - mmengine - INFO - Epoch(train) [99][ 240/2569] lr: 4.0000e-02 eta: 9:50:49 time: 0.2624 data_time: 0.0071 memory: 5828 grad_norm: 3.1060 loss: 2.4179 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4179 2023/06/05 11:10:06 - mmengine - INFO - Epoch(train) [99][ 260/2569] lr: 4.0000e-02 eta: 9:50:43 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 3.0958 loss: 2.3647 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3647 2023/06/05 11:10:11 - mmengine - INFO - Epoch(train) [99][ 280/2569] lr: 4.0000e-02 eta: 9:50:38 time: 0.2597 data_time: 0.0071 memory: 5828 grad_norm: 3.1439 loss: 2.2919 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2919 2023/06/05 11:10:17 - mmengine - INFO - Epoch(train) [99][ 300/2569] lr: 4.0000e-02 eta: 9:50:33 time: 0.2736 data_time: 0.0069 memory: 5828 grad_norm: 3.0877 loss: 2.4650 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4650 2023/06/05 11:10:22 - mmengine - INFO - Epoch(train) [99][ 320/2569] lr: 4.0000e-02 eta: 9:50:27 time: 0.2657 data_time: 0.0074 memory: 5828 grad_norm: 3.1749 loss: 2.4403 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4403 2023/06/05 11:10:28 - mmengine - INFO - Epoch(train) [99][ 340/2569] lr: 4.0000e-02 eta: 9:50:22 time: 0.2682 data_time: 0.0074 memory: 5828 grad_norm: 3.1541 loss: 2.5483 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5483 2023/06/05 11:10:33 - mmengine - INFO - Epoch(train) [99][ 360/2569] lr: 4.0000e-02 eta: 9:50:17 time: 0.2728 data_time: 0.0072 memory: 5828 grad_norm: 3.1665 loss: 2.6885 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6885 2023/06/05 11:10:38 - mmengine - INFO - Epoch(train) [99][ 380/2569] lr: 4.0000e-02 eta: 9:50:11 time: 0.2607 data_time: 0.0071 memory: 5828 grad_norm: 3.0946 loss: 2.8332 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8332 2023/06/05 11:10:44 - mmengine - INFO - Epoch(train) [99][ 400/2569] lr: 4.0000e-02 eta: 9:50:06 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 3.1269 loss: 2.4362 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4362 2023/06/05 11:10:49 - mmengine - INFO - Epoch(train) [99][ 420/2569] lr: 4.0000e-02 eta: 9:50:01 time: 0.2735 data_time: 0.0073 memory: 5828 grad_norm: 3.1437 loss: 2.7806 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.7806 2023/06/05 11:10:54 - mmengine - INFO - Epoch(train) [99][ 440/2569] lr: 4.0000e-02 eta: 9:49:56 time: 0.2594 data_time: 0.0073 memory: 5828 grad_norm: 3.1009 loss: 2.5318 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5318 2023/06/05 11:11:00 - mmengine - INFO - Epoch(train) [99][ 460/2569] lr: 4.0000e-02 eta: 9:49:50 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 3.1737 loss: 2.7909 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7909 2023/06/05 11:11:05 - mmengine - INFO - Epoch(train) [99][ 480/2569] lr: 4.0000e-02 eta: 9:49:45 time: 0.2608 data_time: 0.0072 memory: 5828 grad_norm: 3.1590 loss: 2.7358 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7358 2023/06/05 11:11:10 - mmengine - INFO - Epoch(train) [99][ 500/2569] lr: 4.0000e-02 eta: 9:49:39 time: 0.2612 data_time: 0.0074 memory: 5828 grad_norm: 3.2026 loss: 2.5217 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5217 2023/06/05 11:11:15 - mmengine - INFO - Epoch(train) [99][ 520/2569] lr: 4.0000e-02 eta: 9:49:34 time: 0.2671 data_time: 0.0069 memory: 5828 grad_norm: 3.0762 loss: 2.4953 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4953 2023/06/05 11:11:21 - mmengine - INFO - Epoch(train) [99][ 540/2569] lr: 4.0000e-02 eta: 9:49:29 time: 0.2685 data_time: 0.0071 memory: 5828 grad_norm: 3.1487 loss: 2.1539 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1539 2023/06/05 11:11:26 - mmengine - INFO - Epoch(train) [99][ 560/2569] lr: 4.0000e-02 eta: 9:49:24 time: 0.2712 data_time: 0.0073 memory: 5828 grad_norm: 3.1274 loss: 2.2028 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2028 2023/06/05 11:11:31 - mmengine - INFO - Epoch(train) [99][ 580/2569] lr: 4.0000e-02 eta: 9:49:18 time: 0.2597 data_time: 0.0072 memory: 5828 grad_norm: 3.1279 loss: 2.4424 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.4424 2023/06/05 11:11:37 - mmengine - INFO - Epoch(train) [99][ 600/2569] lr: 4.0000e-02 eta: 9:49:13 time: 0.2793 data_time: 0.0072 memory: 5828 grad_norm: 3.0791 loss: 2.6780 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6780 2023/06/05 11:11:42 - mmengine - INFO - Epoch(train) [99][ 620/2569] lr: 4.0000e-02 eta: 9:49:08 time: 0.2665 data_time: 0.0073 memory: 5828 grad_norm: 3.1736 loss: 2.5054 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5054 2023/06/05 11:11:48 - mmengine - INFO - Epoch(train) [99][ 640/2569] lr: 4.0000e-02 eta: 9:49:02 time: 0.2663 data_time: 0.0071 memory: 5828 grad_norm: 3.0644 loss: 2.5249 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5249 2023/06/05 11:11:53 - mmengine - INFO - Epoch(train) [99][ 660/2569] lr: 4.0000e-02 eta: 9:48:57 time: 0.2663 data_time: 0.0071 memory: 5828 grad_norm: 3.0968 loss: 2.4263 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4263 2023/06/05 11:11:58 - mmengine - INFO - Epoch(train) [99][ 680/2569] lr: 4.0000e-02 eta: 9:48:52 time: 0.2616 data_time: 0.0071 memory: 5828 grad_norm: 3.1329 loss: 2.6658 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6658 2023/06/05 11:12:04 - mmengine - INFO - Epoch(train) [99][ 700/2569] lr: 4.0000e-02 eta: 9:48:47 time: 0.2705 data_time: 0.0069 memory: 5828 grad_norm: 3.1097 loss: 2.6857 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.6857 2023/06/05 11:12:09 - mmengine - INFO - Epoch(train) [99][ 720/2569] lr: 4.0000e-02 eta: 9:48:41 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 3.1139 loss: 2.2814 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2814 2023/06/05 11:12:14 - mmengine - INFO - Epoch(train) [99][ 740/2569] lr: 4.0000e-02 eta: 9:48:36 time: 0.2667 data_time: 0.0075 memory: 5828 grad_norm: 3.1044 loss: 2.3149 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3149 2023/06/05 11:12:20 - mmengine - INFO - Epoch(train) [99][ 760/2569] lr: 4.0000e-02 eta: 9:48:30 time: 0.2605 data_time: 0.0069 memory: 5828 grad_norm: 3.1488 loss: 2.5853 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5853 2023/06/05 11:12:25 - mmengine - INFO - Epoch(train) [99][ 780/2569] lr: 4.0000e-02 eta: 9:48:25 time: 0.2767 data_time: 0.0070 memory: 5828 grad_norm: 3.0865 loss: 2.6313 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6313 2023/06/05 11:12:30 - mmengine - INFO - Epoch(train) [99][ 800/2569] lr: 4.0000e-02 eta: 9:48:20 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 3.1273 loss: 2.4420 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4420 2023/06/05 11:12:36 - mmengine - INFO - Epoch(train) [99][ 820/2569] lr: 4.0000e-02 eta: 9:48:15 time: 0.2714 data_time: 0.0070 memory: 5828 grad_norm: 3.1105 loss: 2.5471 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5471 2023/06/05 11:12:41 - mmengine - INFO - Epoch(train) [99][ 840/2569] lr: 4.0000e-02 eta: 9:48:09 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 3.0764 loss: 2.5527 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5527 2023/06/05 11:12:46 - mmengine - INFO - Epoch(train) [99][ 860/2569] lr: 4.0000e-02 eta: 9:48:04 time: 0.2693 data_time: 0.0083 memory: 5828 grad_norm: 3.1547 loss: 2.3432 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3432 2023/06/05 11:12:52 - mmengine - INFO - Epoch(train) [99][ 880/2569] lr: 4.0000e-02 eta: 9:47:59 time: 0.2663 data_time: 0.0072 memory: 5828 grad_norm: 3.1092 loss: 2.3708 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3708 2023/06/05 11:12:57 - mmengine - INFO - Epoch(train) [99][ 900/2569] lr: 4.0000e-02 eta: 9:47:53 time: 0.2642 data_time: 0.0069 memory: 5828 grad_norm: 3.1456 loss: 2.6702 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6702 2023/06/05 11:13:03 - mmengine - INFO - Epoch(train) [99][ 920/2569] lr: 4.0000e-02 eta: 9:47:48 time: 0.2687 data_time: 0.0072 memory: 5828 grad_norm: 3.1284 loss: 2.2666 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2666 2023/06/05 11:13:08 - mmengine - INFO - Epoch(train) [99][ 940/2569] lr: 4.0000e-02 eta: 9:47:43 time: 0.2620 data_time: 0.0079 memory: 5828 grad_norm: 3.1042 loss: 2.5186 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5186 2023/06/05 11:13:13 - mmengine - INFO - Epoch(train) [99][ 960/2569] lr: 4.0000e-02 eta: 9:47:38 time: 0.2711 data_time: 0.0073 memory: 5828 grad_norm: 3.1481 loss: 2.5997 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5997 2023/06/05 11:13:19 - mmengine - INFO - Epoch(train) [99][ 980/2569] lr: 4.0000e-02 eta: 9:47:32 time: 0.2741 data_time: 0.0074 memory: 5828 grad_norm: 3.1787 loss: 2.3657 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3657 2023/06/05 11:13:24 - mmengine - INFO - Epoch(train) [99][1000/2569] lr: 4.0000e-02 eta: 9:47:27 time: 0.2667 data_time: 0.0070 memory: 5828 grad_norm: 3.1740 loss: 2.3953 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.3953 2023/06/05 11:13:29 - mmengine - INFO - Epoch(train) [99][1020/2569] lr: 4.0000e-02 eta: 9:47:22 time: 0.2648 data_time: 0.0073 memory: 5828 grad_norm: 3.0978 loss: 2.4568 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4568 2023/06/05 11:13:35 - mmengine - INFO - Epoch(train) [99][1040/2569] lr: 4.0000e-02 eta: 9:47:16 time: 0.2676 data_time: 0.0070 memory: 5828 grad_norm: 3.1815 loss: 2.5956 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5956 2023/06/05 11:13:40 - mmengine - INFO - Epoch(train) [99][1060/2569] lr: 4.0000e-02 eta: 9:47:11 time: 0.2610 data_time: 0.0074 memory: 5828 grad_norm: 3.1759 loss: 2.6793 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6793 2023/06/05 11:13:45 - mmengine - INFO - Epoch(train) [99][1080/2569] lr: 4.0000e-02 eta: 9:47:06 time: 0.2595 data_time: 0.0074 memory: 5828 grad_norm: 3.1631 loss: 2.5672 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.5672 2023/06/05 11:13:50 - mmengine - INFO - Epoch(train) [99][1100/2569] lr: 4.0000e-02 eta: 9:47:00 time: 0.2607 data_time: 0.0070 memory: 5828 grad_norm: 3.1702 loss: 2.5345 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5345 2023/06/05 11:13:56 - mmengine - INFO - Epoch(train) [99][1120/2569] lr: 4.0000e-02 eta: 9:46:55 time: 0.2614 data_time: 0.0070 memory: 5828 grad_norm: 3.2338 loss: 2.5076 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5076 2023/06/05 11:14:01 - mmengine - INFO - Epoch(train) [99][1140/2569] lr: 4.0000e-02 eta: 9:46:50 time: 0.2631 data_time: 0.0072 memory: 5828 grad_norm: 3.1286 loss: 2.4284 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4284 2023/06/05 11:14:06 - mmengine - INFO - Epoch(train) [99][1160/2569] lr: 4.0000e-02 eta: 9:46:44 time: 0.2643 data_time: 0.0071 memory: 5828 grad_norm: 3.0878 loss: 2.3758 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.3758 2023/06/05 11:14:12 - mmengine - INFO - Epoch(train) [99][1180/2569] lr: 4.0000e-02 eta: 9:46:39 time: 0.2767 data_time: 0.0067 memory: 5828 grad_norm: 3.1272 loss: 2.3473 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3473 2023/06/05 11:14:17 - mmengine - INFO - Epoch(train) [99][1200/2569] lr: 4.0000e-02 eta: 9:46:34 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 3.0942 loss: 2.6042 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.6042 2023/06/05 11:14:23 - mmengine - INFO - Epoch(train) [99][1220/2569] lr: 4.0000e-02 eta: 9:46:28 time: 0.2739 data_time: 0.0071 memory: 5828 grad_norm: 3.2235 loss: 2.4256 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4256 2023/06/05 11:14:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:14:28 - mmengine - INFO - Epoch(train) [99][1240/2569] lr: 4.0000e-02 eta: 9:46:23 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 3.1644 loss: 2.9783 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.9783 2023/06/05 11:14:34 - mmengine - INFO - Epoch(train) [99][1260/2569] lr: 4.0000e-02 eta: 9:46:18 time: 0.2898 data_time: 0.0072 memory: 5828 grad_norm: 3.0872 loss: 2.4674 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4674 2023/06/05 11:14:39 - mmengine - INFO - Epoch(train) [99][1280/2569] lr: 4.0000e-02 eta: 9:46:13 time: 0.2724 data_time: 0.0071 memory: 5828 grad_norm: 3.1232 loss: 2.5208 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5208 2023/06/05 11:14:45 - mmengine - INFO - Epoch(train) [99][1300/2569] lr: 4.0000e-02 eta: 9:46:08 time: 0.2720 data_time: 0.0072 memory: 5828 grad_norm: 3.1076 loss: 2.3529 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3529 2023/06/05 11:14:50 - mmengine - INFO - Epoch(train) [99][1320/2569] lr: 4.0000e-02 eta: 9:46:02 time: 0.2622 data_time: 0.0071 memory: 5828 grad_norm: 3.2113 loss: 2.8155 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.8155 2023/06/05 11:14:55 - mmengine - INFO - Epoch(train) [99][1340/2569] lr: 4.0000e-02 eta: 9:45:57 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 3.1327 loss: 2.5501 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5501 2023/06/05 11:15:01 - mmengine - INFO - Epoch(train) [99][1360/2569] lr: 4.0000e-02 eta: 9:45:52 time: 0.2714 data_time: 0.0070 memory: 5828 grad_norm: 3.0941 loss: 2.1232 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1232 2023/06/05 11:15:06 - mmengine - INFO - Epoch(train) [99][1380/2569] lr: 4.0000e-02 eta: 9:45:46 time: 0.2607 data_time: 0.0073 memory: 5828 grad_norm: 3.1200 loss: 2.5227 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5227 2023/06/05 11:15:11 - mmengine - INFO - Epoch(train) [99][1400/2569] lr: 4.0000e-02 eta: 9:45:41 time: 0.2698 data_time: 0.0074 memory: 5828 grad_norm: 3.2086 loss: 2.5236 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5236 2023/06/05 11:15:17 - mmengine - INFO - Epoch(train) [99][1420/2569] lr: 4.0000e-02 eta: 9:45:36 time: 0.2635 data_time: 0.0072 memory: 5828 grad_norm: 3.1923 loss: 2.4073 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4073 2023/06/05 11:15:22 - mmengine - INFO - Epoch(train) [99][1440/2569] lr: 4.0000e-02 eta: 9:45:30 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 3.0687 loss: 2.9840 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.9840 2023/06/05 11:15:27 - mmengine - INFO - Epoch(train) [99][1460/2569] lr: 4.0000e-02 eta: 9:45:25 time: 0.2717 data_time: 0.0078 memory: 5828 grad_norm: 3.1073 loss: 2.1919 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1919 2023/06/05 11:15:33 - mmengine - INFO - Epoch(train) [99][1480/2569] lr: 4.0000e-02 eta: 9:45:20 time: 0.2712 data_time: 0.0081 memory: 5828 grad_norm: 3.1887 loss: 2.5198 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.5198 2023/06/05 11:15:38 - mmengine - INFO - Epoch(train) [99][1500/2569] lr: 4.0000e-02 eta: 9:45:14 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 3.0681 loss: 2.4953 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4953 2023/06/05 11:15:43 - mmengine - INFO - Epoch(train) [99][1520/2569] lr: 4.0000e-02 eta: 9:45:09 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 3.1356 loss: 2.6917 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6917 2023/06/05 11:15:49 - mmengine - INFO - Epoch(train) [99][1540/2569] lr: 4.0000e-02 eta: 9:45:04 time: 0.2660 data_time: 0.0083 memory: 5828 grad_norm: 3.0567 loss: 2.5642 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5642 2023/06/05 11:15:54 - mmengine - INFO - Epoch(train) [99][1560/2569] lr: 4.0000e-02 eta: 9:44:58 time: 0.2663 data_time: 0.0073 memory: 5828 grad_norm: 3.1190 loss: 2.5468 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5468 2023/06/05 11:15:59 - mmengine - INFO - Epoch(train) [99][1580/2569] lr: 4.0000e-02 eta: 9:44:53 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 3.1642 loss: 2.6596 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6596 2023/06/05 11:16:05 - mmengine - INFO - Epoch(train) [99][1600/2569] lr: 4.0000e-02 eta: 9:44:48 time: 0.2733 data_time: 0.0073 memory: 5828 grad_norm: 3.1130 loss: 2.6189 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6189 2023/06/05 11:16:10 - mmengine - INFO - Epoch(train) [99][1620/2569] lr: 4.0000e-02 eta: 9:44:43 time: 0.2609 data_time: 0.0072 memory: 5828 grad_norm: 3.1182 loss: 2.7900 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7900 2023/06/05 11:16:15 - mmengine - INFO - Epoch(train) [99][1640/2569] lr: 4.0000e-02 eta: 9:44:37 time: 0.2699 data_time: 0.0072 memory: 5828 grad_norm: 3.0862 loss: 2.6534 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6534 2023/06/05 11:16:21 - mmengine - INFO - Epoch(train) [99][1660/2569] lr: 4.0000e-02 eta: 9:44:32 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.1120 loss: 2.3542 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3542 2023/06/05 11:16:26 - mmengine - INFO - Epoch(train) [99][1680/2569] lr: 4.0000e-02 eta: 9:44:27 time: 0.2659 data_time: 0.0073 memory: 5828 grad_norm: 3.1668 loss: 2.6369 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6369 2023/06/05 11:16:31 - mmengine - INFO - Epoch(train) [99][1700/2569] lr: 4.0000e-02 eta: 9:44:21 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 3.1395 loss: 2.6575 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6575 2023/06/05 11:16:37 - mmengine - INFO - Epoch(train) [99][1720/2569] lr: 4.0000e-02 eta: 9:44:16 time: 0.2667 data_time: 0.0076 memory: 5828 grad_norm: 3.1078 loss: 2.5270 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5270 2023/06/05 11:16:42 - mmengine - INFO - Epoch(train) [99][1740/2569] lr: 4.0000e-02 eta: 9:44:11 time: 0.2742 data_time: 0.0080 memory: 5828 grad_norm: 3.0776 loss: 2.4662 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4662 2023/06/05 11:16:47 - mmengine - INFO - Epoch(train) [99][1760/2569] lr: 4.0000e-02 eta: 9:44:05 time: 0.2667 data_time: 0.0071 memory: 5828 grad_norm: 3.1488 loss: 2.4225 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4225 2023/06/05 11:16:53 - mmengine - INFO - Epoch(train) [99][1780/2569] lr: 4.0000e-02 eta: 9:44:00 time: 0.2709 data_time: 0.0071 memory: 5828 grad_norm: 3.1563 loss: 2.4977 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4977 2023/06/05 11:16:58 - mmengine - INFO - Epoch(train) [99][1800/2569] lr: 4.0000e-02 eta: 9:43:55 time: 0.2611 data_time: 0.0072 memory: 5828 grad_norm: 3.1313 loss: 2.5606 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5606 2023/06/05 11:17:03 - mmengine - INFO - Epoch(train) [99][1820/2569] lr: 4.0000e-02 eta: 9:43:50 time: 0.2662 data_time: 0.0071 memory: 5828 grad_norm: 3.0698 loss: 2.4005 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4005 2023/06/05 11:17:09 - mmengine - INFO - Epoch(train) [99][1840/2569] lr: 4.0000e-02 eta: 9:43:44 time: 0.2697 data_time: 0.0070 memory: 5828 grad_norm: 3.1187 loss: 2.4644 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4644 2023/06/05 11:17:14 - mmengine - INFO - Epoch(train) [99][1860/2569] lr: 4.0000e-02 eta: 9:43:39 time: 0.2780 data_time: 0.0070 memory: 5828 grad_norm: 3.2359 loss: 2.6522 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.6522 2023/06/05 11:17:20 - mmengine - INFO - Epoch(train) [99][1880/2569] lr: 4.0000e-02 eta: 9:43:34 time: 0.2615 data_time: 0.0068 memory: 5828 grad_norm: 3.1645 loss: 2.3757 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3757 2023/06/05 11:17:25 - mmengine - INFO - Epoch(train) [99][1900/2569] lr: 4.0000e-02 eta: 9:43:28 time: 0.2676 data_time: 0.0070 memory: 5828 grad_norm: 3.1560 loss: 2.7753 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.7753 2023/06/05 11:17:30 - mmengine - INFO - Epoch(train) [99][1920/2569] lr: 4.0000e-02 eta: 9:43:23 time: 0.2595 data_time: 0.0071 memory: 5828 grad_norm: 3.0889 loss: 2.6215 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6215 2023/06/05 11:17:35 - mmengine - INFO - Epoch(train) [99][1940/2569] lr: 4.0000e-02 eta: 9:43:18 time: 0.2600 data_time: 0.0073 memory: 5828 grad_norm: 3.1533 loss: 2.4502 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4502 2023/06/05 11:17:41 - mmengine - INFO - Epoch(train) [99][1960/2569] lr: 4.0000e-02 eta: 9:43:12 time: 0.2659 data_time: 0.0072 memory: 5828 grad_norm: 3.1000 loss: 2.3818 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3818 2023/06/05 11:17:46 - mmengine - INFO - Epoch(train) [99][1980/2569] lr: 4.0000e-02 eta: 9:43:07 time: 0.2621 data_time: 0.0070 memory: 5828 grad_norm: 3.0897 loss: 2.6399 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6399 2023/06/05 11:17:51 - mmengine - INFO - Epoch(train) [99][2000/2569] lr: 4.0000e-02 eta: 9:43:02 time: 0.2740 data_time: 0.0072 memory: 5828 grad_norm: 3.1594 loss: 2.5693 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5693 2023/06/05 11:17:57 - mmengine - INFO - Epoch(train) [99][2020/2569] lr: 4.0000e-02 eta: 9:42:56 time: 0.2718 data_time: 0.0072 memory: 5828 grad_norm: 3.1259 loss: 2.6341 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6341 2023/06/05 11:18:02 - mmengine - INFO - Epoch(train) [99][2040/2569] lr: 4.0000e-02 eta: 9:42:51 time: 0.2660 data_time: 0.0069 memory: 5828 grad_norm: 3.1672 loss: 1.9454 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9454 2023/06/05 11:18:08 - mmengine - INFO - Epoch(train) [99][2060/2569] lr: 4.0000e-02 eta: 9:42:46 time: 0.2700 data_time: 0.0067 memory: 5828 grad_norm: 3.1623 loss: 2.4605 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4605 2023/06/05 11:18:13 - mmengine - INFO - Epoch(train) [99][2080/2569] lr: 4.0000e-02 eta: 9:42:41 time: 0.2662 data_time: 0.0071 memory: 5828 grad_norm: 3.2082 loss: 2.6063 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6063 2023/06/05 11:18:18 - mmengine - INFO - Epoch(train) [99][2100/2569] lr: 4.0000e-02 eta: 9:42:35 time: 0.2678 data_time: 0.0069 memory: 5828 grad_norm: 3.1293 loss: 2.5041 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.5041 2023/06/05 11:18:24 - mmengine - INFO - Epoch(train) [99][2120/2569] lr: 4.0000e-02 eta: 9:42:30 time: 0.2707 data_time: 0.0068 memory: 5828 grad_norm: 3.0918 loss: 2.5287 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5287 2023/06/05 11:18:29 - mmengine - INFO - Epoch(train) [99][2140/2569] lr: 4.0000e-02 eta: 9:42:25 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 3.1347 loss: 2.1267 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1267 2023/06/05 11:18:35 - mmengine - INFO - Epoch(train) [99][2160/2569] lr: 4.0000e-02 eta: 9:42:19 time: 0.2743 data_time: 0.0080 memory: 5828 grad_norm: 3.1237 loss: 2.6831 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.6831 2023/06/05 11:18:40 - mmengine - INFO - Epoch(train) [99][2180/2569] lr: 4.0000e-02 eta: 9:42:14 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 3.1814 loss: 2.7268 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7268 2023/06/05 11:18:45 - mmengine - INFO - Epoch(train) [99][2200/2569] lr: 4.0000e-02 eta: 9:42:09 time: 0.2676 data_time: 0.0073 memory: 5828 grad_norm: 3.1647 loss: 2.6729 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6729 2023/06/05 11:18:50 - mmengine - INFO - Epoch(train) [99][2220/2569] lr: 4.0000e-02 eta: 9:42:03 time: 0.2656 data_time: 0.0070 memory: 5828 grad_norm: 3.1610 loss: 2.5350 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.5350 2023/06/05 11:18:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:18:56 - mmengine - INFO - Epoch(train) [99][2240/2569] lr: 4.0000e-02 eta: 9:41:58 time: 0.2610 data_time: 0.0074 memory: 5828 grad_norm: 3.0928 loss: 2.3010 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3010 2023/06/05 11:19:01 - mmengine - INFO - Epoch(train) [99][2260/2569] lr: 4.0000e-02 eta: 9:41:53 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 3.1293 loss: 2.5672 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5672 2023/06/05 11:19:06 - mmengine - INFO - Epoch(train) [99][2280/2569] lr: 4.0000e-02 eta: 9:41:47 time: 0.2668 data_time: 0.0074 memory: 5828 grad_norm: 3.1284 loss: 2.8273 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.8273 2023/06/05 11:19:12 - mmengine - INFO - Epoch(train) [99][2300/2569] lr: 4.0000e-02 eta: 9:41:42 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 3.1825 loss: 2.6098 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.6098 2023/06/05 11:19:17 - mmengine - INFO - Epoch(train) [99][2320/2569] lr: 4.0000e-02 eta: 9:41:37 time: 0.2707 data_time: 0.0070 memory: 5828 grad_norm: 3.1886 loss: 2.4302 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4302 2023/06/05 11:19:23 - mmengine - INFO - Epoch(train) [99][2340/2569] lr: 4.0000e-02 eta: 9:41:32 time: 0.2651 data_time: 0.0071 memory: 5828 grad_norm: 3.1477 loss: 2.5180 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.5180 2023/06/05 11:19:28 - mmengine - INFO - Epoch(train) [99][2360/2569] lr: 4.0000e-02 eta: 9:41:26 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 3.1898 loss: 2.7552 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7552 2023/06/05 11:19:33 - mmengine - INFO - Epoch(train) [99][2380/2569] lr: 4.0000e-02 eta: 9:41:21 time: 0.2693 data_time: 0.0071 memory: 5828 grad_norm: 3.1549 loss: 2.4531 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4531 2023/06/05 11:19:39 - mmengine - INFO - Epoch(train) [99][2400/2569] lr: 4.0000e-02 eta: 9:41:16 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 3.1718 loss: 2.8189 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.8189 2023/06/05 11:19:44 - mmengine - INFO - Epoch(train) [99][2420/2569] lr: 4.0000e-02 eta: 9:41:10 time: 0.2653 data_time: 0.0071 memory: 5828 grad_norm: 3.1672 loss: 2.5474 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.5474 2023/06/05 11:19:49 - mmengine - INFO - Epoch(train) [99][2440/2569] lr: 4.0000e-02 eta: 9:41:05 time: 0.2670 data_time: 0.0074 memory: 5828 grad_norm: 3.1726 loss: 2.4165 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4165 2023/06/05 11:19:54 - mmengine - INFO - Epoch(train) [99][2460/2569] lr: 4.0000e-02 eta: 9:41:00 time: 0.2605 data_time: 0.0074 memory: 5828 grad_norm: 3.1651 loss: 2.3378 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3378 2023/06/05 11:20:00 - mmengine - INFO - Epoch(train) [99][2480/2569] lr: 4.0000e-02 eta: 9:40:54 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 3.1413 loss: 2.4475 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4475 2023/06/05 11:20:05 - mmengine - INFO - Epoch(train) [99][2500/2569] lr: 4.0000e-02 eta: 9:40:49 time: 0.2691 data_time: 0.0075 memory: 5828 grad_norm: 3.1452 loss: 2.3846 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3846 2023/06/05 11:20:10 - mmengine - INFO - Epoch(train) [99][2520/2569] lr: 4.0000e-02 eta: 9:40:44 time: 0.2659 data_time: 0.0072 memory: 5828 grad_norm: 3.1411 loss: 2.2101 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2101 2023/06/05 11:20:16 - mmengine - INFO - Epoch(train) [99][2540/2569] lr: 4.0000e-02 eta: 9:40:38 time: 0.2640 data_time: 0.0076 memory: 5828 grad_norm: 3.1252 loss: 2.6182 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.6182 2023/06/05 11:20:21 - mmengine - INFO - Epoch(train) [99][2560/2569] lr: 4.0000e-02 eta: 9:40:33 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 3.1357 loss: 2.5762 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5762 2023/06/05 11:20:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:20:23 - mmengine - INFO - Epoch(train) [99][2569/2569] lr: 4.0000e-02 eta: 9:40:31 time: 0.2526 data_time: 0.0069 memory: 5828 grad_norm: 3.1969 loss: 2.5705 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.5705 2023/06/05 11:20:30 - mmengine - INFO - Epoch(train) [100][ 20/2569] lr: 4.0000e-02 eta: 9:40:26 time: 0.3357 data_time: 0.0564 memory: 5828 grad_norm: 3.0650 loss: 2.7053 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.7053 2023/06/05 11:20:35 - mmengine - INFO - Epoch(train) [100][ 40/2569] lr: 4.0000e-02 eta: 9:40:21 time: 0.2666 data_time: 0.0074 memory: 5828 grad_norm: 3.0906 loss: 2.3702 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3702 2023/06/05 11:20:41 - mmengine - INFO - Epoch(train) [100][ 60/2569] lr: 4.0000e-02 eta: 9:40:15 time: 0.2744 data_time: 0.0072 memory: 5828 grad_norm: 3.0875 loss: 2.5835 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5835 2023/06/05 11:20:46 - mmengine - INFO - Epoch(train) [100][ 80/2569] lr: 4.0000e-02 eta: 9:40:10 time: 0.2736 data_time: 0.0076 memory: 5828 grad_norm: 3.1762 loss: 2.5866 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.5866 2023/06/05 11:20:52 - mmengine - INFO - Epoch(train) [100][ 100/2569] lr: 4.0000e-02 eta: 9:40:05 time: 0.2642 data_time: 0.0071 memory: 5828 grad_norm: 3.1403 loss: 2.4600 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4600 2023/06/05 11:20:57 - mmengine - INFO - Epoch(train) [100][ 120/2569] lr: 4.0000e-02 eta: 9:40:00 time: 0.2616 data_time: 0.0079 memory: 5828 grad_norm: 3.1139 loss: 2.3828 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3828 2023/06/05 11:21:02 - mmengine - INFO - Epoch(train) [100][ 140/2569] lr: 4.0000e-02 eta: 9:39:54 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 3.2080 loss: 2.4549 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.4549 2023/06/05 11:21:07 - mmengine - INFO - Epoch(train) [100][ 160/2569] lr: 4.0000e-02 eta: 9:39:49 time: 0.2665 data_time: 0.0075 memory: 5828 grad_norm: 3.1160 loss: 2.3883 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.3883 2023/06/05 11:21:13 - mmengine - INFO - Epoch(train) [100][ 180/2569] lr: 4.0000e-02 eta: 9:39:44 time: 0.2721 data_time: 0.0078 memory: 5828 grad_norm: 3.1695 loss: 2.6272 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.6272 2023/06/05 11:21:18 - mmengine - INFO - Epoch(train) [100][ 200/2569] lr: 4.0000e-02 eta: 9:39:38 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 3.1296 loss: 2.7025 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.7025 2023/06/05 11:21:23 - mmengine - INFO - Epoch(train) [100][ 220/2569] lr: 4.0000e-02 eta: 9:39:33 time: 0.2608 data_time: 0.0072 memory: 5828 grad_norm: 3.1177 loss: 2.5813 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5813 2023/06/05 11:21:29 - mmengine - INFO - Epoch(train) [100][ 240/2569] lr: 4.0000e-02 eta: 9:39:28 time: 0.2721 data_time: 0.0070 memory: 5828 grad_norm: 3.1610 loss: 2.5556 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.5556 2023/06/05 11:21:34 - mmengine - INFO - Epoch(train) [100][ 260/2569] lr: 4.0000e-02 eta: 9:39:22 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 3.1484 loss: 2.3665 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3665 2023/06/05 11:21:40 - mmengine - INFO - Epoch(train) [100][ 280/2569] lr: 4.0000e-02 eta: 9:39:17 time: 0.2703 data_time: 0.0075 memory: 5828 grad_norm: 3.2010 loss: 2.4826 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.4826 2023/06/05 11:21:45 - mmengine - INFO - Epoch(train) [100][ 300/2569] lr: 4.0000e-02 eta: 9:39:12 time: 0.2670 data_time: 0.0069 memory: 5828 grad_norm: 3.0658 loss: 2.5259 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5259 2023/06/05 11:21:50 - mmengine - INFO - Epoch(train) [100][ 320/2569] lr: 4.0000e-02 eta: 9:39:06 time: 0.2613 data_time: 0.0073 memory: 5828 grad_norm: 3.1975 loss: 2.5680 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.5680 2023/06/05 11:21:56 - mmengine - INFO - Epoch(train) [100][ 340/2569] lr: 4.0000e-02 eta: 9:39:01 time: 0.2868 data_time: 0.0071 memory: 5828 grad_norm: 3.2155 loss: 2.3856 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.3856 2023/06/05 11:22:01 - mmengine - INFO - Epoch(train) [100][ 360/2569] lr: 4.0000e-02 eta: 9:38:56 time: 0.2658 data_time: 0.0070 memory: 5828 grad_norm: 3.1229 loss: 2.4156 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4156 2023/06/05 11:22:07 - mmengine - INFO - Epoch(train) [100][ 380/2569] lr: 4.0000e-02 eta: 9:38:51 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 3.1439 loss: 2.5065 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.5065 2023/06/05 11:22:12 - mmengine - INFO - Epoch(train) [100][ 400/2569] lr: 4.0000e-02 eta: 9:38:46 time: 0.2755 data_time: 0.0070 memory: 5828 grad_norm: 3.0646 loss: 2.1467 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1467 2023/06/05 11:22:18 - mmengine - INFO - Epoch(train) [100][ 420/2569] lr: 4.0000e-02 eta: 9:38:40 time: 0.2681 data_time: 0.0069 memory: 5828 grad_norm: 3.1129 loss: 2.8719 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.8719 2023/06/05 11:22:23 - mmengine - INFO - Epoch(train) [100][ 440/2569] lr: 4.0000e-02 eta: 9:38:35 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 3.1439 loss: 2.3838 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3838 2023/06/05 11:22:28 - mmengine - INFO - Epoch(train) [100][ 460/2569] lr: 4.0000e-02 eta: 9:38:30 time: 0.2716 data_time: 0.0071 memory: 5828 grad_norm: 3.1262 loss: 2.4936 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4936 2023/06/05 11:22:34 - mmengine - INFO - Epoch(train) [100][ 480/2569] lr: 4.0000e-02 eta: 9:38:24 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 3.1545 loss: 2.5716 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5716 2023/06/05 11:22:39 - mmengine - INFO - Epoch(train) [100][ 500/2569] lr: 4.0000e-02 eta: 9:38:19 time: 0.2767 data_time: 0.0080 memory: 5828 grad_norm: 3.1587 loss: 2.9173 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.9173 2023/06/05 11:22:45 - mmengine - INFO - Epoch(train) [100][ 520/2569] lr: 4.0000e-02 eta: 9:38:14 time: 0.2665 data_time: 0.0078 memory: 5828 grad_norm: 3.0748 loss: 2.6828 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6828 2023/06/05 11:22:50 - mmengine - INFO - Epoch(train) [100][ 540/2569] lr: 4.0000e-02 eta: 9:38:09 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 3.0814 loss: 2.5937 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.5937 2023/06/05 11:22:55 - mmengine - INFO - Epoch(train) [100][ 560/2569] lr: 4.0000e-02 eta: 9:38:03 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.1282 loss: 2.4942 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.4942 2023/06/05 11:23:01 - mmengine - INFO - Epoch(train) [100][ 580/2569] lr: 4.0000e-02 eta: 9:37:58 time: 0.2672 data_time: 0.0070 memory: 5828 grad_norm: 3.1712 loss: 2.4135 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4135 2023/06/05 11:23:06 - mmengine - INFO - Epoch(train) [100][ 600/2569] lr: 4.0000e-02 eta: 9:37:53 time: 0.2681 data_time: 0.0074 memory: 5828 grad_norm: 3.1502 loss: 2.4999 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4999 2023/06/05 11:23:11 - mmengine - INFO - Epoch(train) [100][ 620/2569] lr: 4.0000e-02 eta: 9:37:47 time: 0.2646 data_time: 0.0070 memory: 5828 grad_norm: 3.0605 loss: 2.4524 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.4524 2023/06/05 11:23:17 - mmengine - INFO - Epoch(train) [100][ 640/2569] lr: 4.0000e-02 eta: 9:37:42 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 3.0892 loss: 2.5131 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5131 2023/06/05 11:23:22 - mmengine - INFO - Epoch(train) [100][ 660/2569] lr: 4.0000e-02 eta: 9:37:37 time: 0.2617 data_time: 0.0069 memory: 5828 grad_norm: 3.1191 loss: 2.2625 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.2625 2023/06/05 11:23:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:23:27 - mmengine - INFO - Epoch(train) [100][ 680/2569] lr: 4.0000e-02 eta: 9:37:31 time: 0.2661 data_time: 0.0068 memory: 5828 grad_norm: 3.1600 loss: 2.4094 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4094 2023/06/05 11:23:32 - mmengine - INFO - Epoch(train) [100][ 700/2569] lr: 4.0000e-02 eta: 9:37:26 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 3.1388 loss: 2.5029 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.5029 2023/06/05 11:23:38 - mmengine - INFO - Epoch(train) [100][ 720/2569] lr: 4.0000e-02 eta: 9:37:21 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 3.0784 loss: 2.2702 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2702 2023/06/05 11:23:43 - mmengine - INFO - Epoch(train) [100][ 740/2569] lr: 4.0000e-02 eta: 9:37:15 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 3.1591 loss: 2.1587 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1587 2023/06/05 11:23:48 - mmengine - INFO - Epoch(train) [100][ 760/2569] lr: 4.0000e-02 eta: 9:37:10 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 3.1668 loss: 2.5318 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.5318 2023/06/05 11:23:54 - mmengine - INFO - Epoch(train) [100][ 780/2569] lr: 4.0000e-02 eta: 9:37:05 time: 0.2661 data_time: 0.0071 memory: 5828 grad_norm: 3.1594 loss: 2.7848 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7848 2023/06/05 11:23:59 - mmengine - INFO - Epoch(train) [100][ 800/2569] lr: 4.0000e-02 eta: 9:36:59 time: 0.2619 data_time: 0.0070 memory: 5828 grad_norm: 3.1516 loss: 2.6852 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.6852 2023/06/05 11:24:04 - mmengine - INFO - Epoch(train) [100][ 820/2569] lr: 4.0000e-02 eta: 9:36:54 time: 0.2683 data_time: 0.0070 memory: 5828 grad_norm: 3.1854 loss: 2.4578 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.4578 2023/06/05 11:24:09 - mmengine - INFO - Epoch(train) [100][ 840/2569] lr: 4.0000e-02 eta: 9:36:49 time: 0.2634 data_time: 0.0071 memory: 5828 grad_norm: 3.1080 loss: 2.5336 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5336 2023/06/05 11:24:15 - mmengine - INFO - Epoch(train) [100][ 860/2569] lr: 4.0000e-02 eta: 9:36:43 time: 0.2655 data_time: 0.0075 memory: 5828 grad_norm: 3.1490 loss: 2.3709 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.3709 2023/06/05 11:24:20 - mmengine - INFO - Epoch(train) [100][ 880/2569] lr: 4.0000e-02 eta: 9:36:38 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 3.1213 loss: 2.2833 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2833 2023/06/05 11:24:25 - mmengine - INFO - Epoch(train) [100][ 900/2569] lr: 4.0000e-02 eta: 9:36:33 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 3.0840 loss: 2.7556 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.7556 2023/06/05 11:24:31 - mmengine - INFO - Epoch(train) [100][ 920/2569] lr: 4.0000e-02 eta: 9:36:27 time: 0.2739 data_time: 0.0072 memory: 5828 grad_norm: 3.1806 loss: 2.6751 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.6751 2023/06/05 11:24:36 - mmengine - INFO - Epoch(train) [100][ 940/2569] lr: 4.0000e-02 eta: 9:36:22 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 3.1859 loss: 2.3465 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.3465 2023/06/05 11:24:41 - mmengine - INFO - Epoch(train) [100][ 960/2569] lr: 4.0000e-02 eta: 9:36:17 time: 0.2662 data_time: 0.0071 memory: 5828 grad_norm: 3.1455 loss: 2.8153 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8153 2023/06/05 11:24:47 - mmengine - INFO - Epoch(train) [100][ 980/2569] lr: 4.0000e-02 eta: 9:36:11 time: 0.2632 data_time: 0.0071 memory: 5828 grad_norm: 3.1318 loss: 2.5737 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5737 2023/06/05 11:24:52 - mmengine - INFO - Epoch(train) [100][1000/2569] lr: 4.0000e-02 eta: 9:36:06 time: 0.2733 data_time: 0.0072 memory: 5828 grad_norm: 3.2072 loss: 2.7983 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7983 2023/06/05 11:24:58 - mmengine - INFO - Epoch(train) [100][1020/2569] lr: 4.0000e-02 eta: 9:36:01 time: 0.2720 data_time: 0.0072 memory: 5828 grad_norm: 3.1101 loss: 2.1094 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1094 2023/06/05 11:25:03 - mmengine - INFO - Epoch(train) [100][1040/2569] lr: 4.0000e-02 eta: 9:35:55 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 3.1577 loss: 2.4254 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4254 2023/06/05 11:25:08 - mmengine - INFO - Epoch(train) [100][1060/2569] lr: 4.0000e-02 eta: 9:35:50 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 3.0932 loss: 2.7707 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7707 2023/06/05 11:25:13 - mmengine - INFO - Epoch(train) [100][1080/2569] lr: 4.0000e-02 eta: 9:35:45 time: 0.2651 data_time: 0.0080 memory: 5828 grad_norm: 3.1396 loss: 2.3570 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3570 2023/06/05 11:25:19 - mmengine - INFO - Epoch(train) [100][1100/2569] lr: 4.0000e-02 eta: 9:35:40 time: 0.2723 data_time: 0.0073 memory: 5828 grad_norm: 3.1863 loss: 2.4495 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.4495 2023/06/05 11:25:24 - mmengine - INFO - Epoch(train) [100][1120/2569] lr: 4.0000e-02 eta: 9:35:34 time: 0.2596 data_time: 0.0081 memory: 5828 grad_norm: 3.1007 loss: 2.5888 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5888 2023/06/05 11:25:30 - mmengine - INFO - Epoch(train) [100][1140/2569] lr: 4.0000e-02 eta: 9:35:29 time: 0.2759 data_time: 0.0067 memory: 5828 grad_norm: 3.1935 loss: 2.7253 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.7253 2023/06/05 11:25:35 - mmengine - INFO - Epoch(train) [100][1160/2569] lr: 4.0000e-02 eta: 9:35:24 time: 0.2619 data_time: 0.0080 memory: 5828 grad_norm: 3.0596 loss: 2.3027 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3027 2023/06/05 11:25:40 - mmengine - INFO - Epoch(train) [100][1180/2569] lr: 4.0000e-02 eta: 9:35:18 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 3.1105 loss: 2.5509 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.5509 2023/06/05 11:25:45 - mmengine - INFO - Epoch(train) [100][1200/2569] lr: 4.0000e-02 eta: 9:35:13 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 3.1541 loss: 2.4917 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4917 2023/06/05 11:25:51 - mmengine - INFO - Epoch(train) [100][1220/2569] lr: 4.0000e-02 eta: 9:35:08 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 3.1850 loss: 2.1915 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1915 2023/06/05 11:25:56 - mmengine - INFO - Epoch(train) [100][1240/2569] lr: 4.0000e-02 eta: 9:35:02 time: 0.2591 data_time: 0.0072 memory: 5828 grad_norm: 3.0877 loss: 2.8647 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8647 2023/06/05 11:26:01 - mmengine - INFO - Epoch(train) [100][1260/2569] lr: 4.0000e-02 eta: 9:34:57 time: 0.2615 data_time: 0.0069 memory: 5828 grad_norm: 3.1645 loss: 2.5189 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.5189 2023/06/05 11:26:06 - mmengine - INFO - Epoch(train) [100][1280/2569] lr: 4.0000e-02 eta: 9:34:51 time: 0.2654 data_time: 0.0076 memory: 5828 grad_norm: 3.1957 loss: 2.6558 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.6558 2023/06/05 11:26:12 - mmengine - INFO - Epoch(train) [100][1300/2569] lr: 4.0000e-02 eta: 9:34:46 time: 0.2672 data_time: 0.0071 memory: 5828 grad_norm: 3.1870 loss: 2.7178 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.7178 2023/06/05 11:26:17 - mmengine - INFO - Epoch(train) [100][1320/2569] lr: 4.0000e-02 eta: 9:34:41 time: 0.2598 data_time: 0.0084 memory: 5828 grad_norm: 3.1361 loss: 2.5755 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.5755 2023/06/05 11:26:22 - mmengine - INFO - Epoch(train) [100][1340/2569] lr: 4.0000e-02 eta: 9:34:35 time: 0.2598 data_time: 0.0078 memory: 5828 grad_norm: 3.1705 loss: 2.4816 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4816 2023/06/05 11:26:27 - mmengine - INFO - Epoch(train) [100][1360/2569] lr: 4.0000e-02 eta: 9:34:30 time: 0.2614 data_time: 0.0076 memory: 5828 grad_norm: 3.1483 loss: 2.2613 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2613 2023/06/05 11:26:33 - mmengine - INFO - Epoch(train) [100][1380/2569] lr: 4.0000e-02 eta: 9:34:25 time: 0.2666 data_time: 0.0076 memory: 5828 grad_norm: 3.1269 loss: 2.6329 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6329 2023/06/05 11:26:38 - mmengine - INFO - Epoch(train) [100][1400/2569] lr: 4.0000e-02 eta: 9:34:19 time: 0.2666 data_time: 0.0071 memory: 5828 grad_norm: 3.1718 loss: 2.8526 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.8526 2023/06/05 11:26:43 - mmengine - INFO - Epoch(train) [100][1420/2569] lr: 4.0000e-02 eta: 9:34:14 time: 0.2661 data_time: 0.0068 memory: 5828 grad_norm: 3.2430 loss: 2.8035 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.8035 2023/06/05 11:26:49 - mmengine - INFO - Epoch(train) [100][1440/2569] lr: 4.0000e-02 eta: 9:34:09 time: 0.2822 data_time: 0.0071 memory: 5828 grad_norm: 3.1835 loss: 2.3749 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3749 2023/06/05 11:26:54 - mmengine - INFO - Epoch(train) [100][1460/2569] lr: 4.0000e-02 eta: 9:34:04 time: 0.2602 data_time: 0.0069 memory: 5828 grad_norm: 3.1292 loss: 2.7314 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.7314 2023/06/05 11:27:00 - mmengine - INFO - Epoch(train) [100][1480/2569] lr: 4.0000e-02 eta: 9:33:58 time: 0.2706 data_time: 0.0072 memory: 5828 grad_norm: 3.1532 loss: 2.6123 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6123 2023/06/05 11:27:05 - mmengine - INFO - Epoch(train) [100][1500/2569] lr: 4.0000e-02 eta: 9:33:53 time: 0.2606 data_time: 0.0077 memory: 5828 grad_norm: 3.1139 loss: 2.4977 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4977 2023/06/05 11:27:10 - mmengine - INFO - Epoch(train) [100][1520/2569] lr: 4.0000e-02 eta: 9:33:48 time: 0.2672 data_time: 0.0068 memory: 5828 grad_norm: 3.0871 loss: 2.3948 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3948 2023/06/05 11:27:16 - mmengine - INFO - Epoch(train) [100][1540/2569] lr: 4.0000e-02 eta: 9:33:42 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 3.1635 loss: 2.6817 top1_acc: 0.0000 top5_acc: 0.1250 loss_cls: 2.6817 2023/06/05 11:27:21 - mmengine - INFO - Epoch(train) [100][1560/2569] lr: 4.0000e-02 eta: 9:33:37 time: 0.2719 data_time: 0.0070 memory: 5828 grad_norm: 3.1131 loss: 2.4783 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.4783 2023/06/05 11:27:26 - mmengine - INFO - Epoch(train) [100][1580/2569] lr: 4.0000e-02 eta: 9:33:32 time: 0.2669 data_time: 0.0075 memory: 5828 grad_norm: 3.1189 loss: 2.5503 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5503 2023/06/05 11:27:32 - mmengine - INFO - Epoch(train) [100][1600/2569] lr: 4.0000e-02 eta: 9:33:27 time: 0.2728 data_time: 0.0076 memory: 5828 grad_norm: 3.1784 loss: 2.2661 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2661 2023/06/05 11:27:37 - mmengine - INFO - Epoch(train) [100][1620/2569] lr: 4.0000e-02 eta: 9:33:21 time: 0.2624 data_time: 0.0070 memory: 5828 grad_norm: 3.1349 loss: 2.3906 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.3906 2023/06/05 11:27:43 - mmengine - INFO - Epoch(train) [100][1640/2569] lr: 4.0000e-02 eta: 9:33:16 time: 0.2711 data_time: 0.0072 memory: 5828 grad_norm: 3.1126 loss: 2.4570 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4570 2023/06/05 11:27:48 - mmengine - INFO - Epoch(train) [100][1660/2569] lr: 4.0000e-02 eta: 9:33:11 time: 0.2607 data_time: 0.0073 memory: 5828 grad_norm: 3.1398 loss: 2.6144 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.6144 2023/06/05 11:27:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:27:53 - mmengine - INFO - Epoch(train) [100][1680/2569] lr: 4.0000e-02 eta: 9:33:05 time: 0.2644 data_time: 0.0069 memory: 5828 grad_norm: 3.1500 loss: 2.2448 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2448 2023/06/05 11:27:58 - mmengine - INFO - Epoch(train) [100][1700/2569] lr: 4.0000e-02 eta: 9:33:00 time: 0.2690 data_time: 0.0072 memory: 5828 grad_norm: 3.0824 loss: 2.3416 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3416 2023/06/05 11:28:04 - mmengine - INFO - Epoch(train) [100][1720/2569] lr: 4.0000e-02 eta: 9:32:55 time: 0.2631 data_time: 0.0069 memory: 5828 grad_norm: 3.1294 loss: 2.7249 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.7249 2023/06/05 11:28:09 - mmengine - INFO - Epoch(train) [100][1740/2569] lr: 4.0000e-02 eta: 9:32:49 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 3.1610 loss: 2.4956 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4956 2023/06/05 11:28:15 - mmengine - INFO - Epoch(train) [100][1760/2569] lr: 4.0000e-02 eta: 9:32:44 time: 0.2738 data_time: 0.0071 memory: 5828 grad_norm: 3.1529 loss: 2.2535 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2535 2023/06/05 11:28:20 - mmengine - INFO - Epoch(train) [100][1780/2569] lr: 4.0000e-02 eta: 9:32:39 time: 0.2669 data_time: 0.0071 memory: 5828 grad_norm: 3.1550 loss: 2.7015 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.7015 2023/06/05 11:28:25 - mmengine - INFO - Epoch(train) [100][1800/2569] lr: 4.0000e-02 eta: 9:32:33 time: 0.2627 data_time: 0.0070 memory: 5828 grad_norm: 3.1506 loss: 2.2779 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2779 2023/06/05 11:28:30 - mmengine - INFO - Epoch(train) [100][1820/2569] lr: 4.0000e-02 eta: 9:32:28 time: 0.2606 data_time: 0.0070 memory: 5828 grad_norm: 3.1099 loss: 2.6094 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.6094 2023/06/05 11:28:36 - mmengine - INFO - Epoch(train) [100][1840/2569] lr: 4.0000e-02 eta: 9:32:23 time: 0.2607 data_time: 0.0068 memory: 5828 grad_norm: 3.0717 loss: 2.0888 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0888 2023/06/05 11:28:41 - mmengine - INFO - Epoch(train) [100][1860/2569] lr: 4.0000e-02 eta: 9:32:17 time: 0.2665 data_time: 0.0073 memory: 5828 grad_norm: 3.0973 loss: 2.7807 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.7807 2023/06/05 11:28:46 - mmengine - INFO - Epoch(train) [100][1880/2569] lr: 4.0000e-02 eta: 9:32:12 time: 0.2694 data_time: 0.0067 memory: 5828 grad_norm: 3.1560 loss: 2.7413 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.7413 2023/06/05 11:28:52 - mmengine - INFO - Epoch(train) [100][1900/2569] lr: 4.0000e-02 eta: 9:32:07 time: 0.2657 data_time: 0.0070 memory: 5828 grad_norm: 3.1531 loss: 2.5115 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.5115 2023/06/05 11:28:57 - mmengine - INFO - Epoch(train) [100][1920/2569] lr: 4.0000e-02 eta: 9:32:01 time: 0.2714 data_time: 0.0072 memory: 5828 grad_norm: 3.1281 loss: 2.6564 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6564 2023/06/05 11:29:02 - mmengine - INFO - Epoch(train) [100][1940/2569] lr: 4.0000e-02 eta: 9:31:56 time: 0.2675 data_time: 0.0071 memory: 5828 grad_norm: 3.1493 loss: 2.5173 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5173 2023/06/05 11:29:08 - mmengine - INFO - Epoch(train) [100][1960/2569] lr: 4.0000e-02 eta: 9:31:51 time: 0.2736 data_time: 0.0071 memory: 5828 grad_norm: 3.2111 loss: 2.6349 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6349 2023/06/05 11:29:13 - mmengine - INFO - Epoch(train) [100][1980/2569] lr: 4.0000e-02 eta: 9:31:46 time: 0.2688 data_time: 0.0070 memory: 5828 grad_norm: 3.1026 loss: 2.3487 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3487 2023/06/05 11:29:19 - mmengine - INFO - Epoch(train) [100][2000/2569] lr: 4.0000e-02 eta: 9:31:40 time: 0.2676 data_time: 0.0073 memory: 5828 grad_norm: 3.2144 loss: 2.5831 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5831 2023/06/05 11:29:24 - mmengine - INFO - Epoch(train) [100][2020/2569] lr: 4.0000e-02 eta: 9:31:35 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 3.2061 loss: 2.7429 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.7429 2023/06/05 11:29:29 - mmengine - INFO - Epoch(train) [100][2040/2569] lr: 4.0000e-02 eta: 9:31:30 time: 0.2624 data_time: 0.0068 memory: 5828 grad_norm: 3.1490 loss: 2.6214 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.6214 2023/06/05 11:29:35 - mmengine - INFO - Epoch(train) [100][2060/2569] lr: 4.0000e-02 eta: 9:31:24 time: 0.2653 data_time: 0.0071 memory: 5828 grad_norm: 3.0903 loss: 2.5735 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.5735 2023/06/05 11:29:40 - mmengine - INFO - Epoch(train) [100][2080/2569] lr: 4.0000e-02 eta: 9:31:19 time: 0.2674 data_time: 0.0076 memory: 5828 grad_norm: 3.1691 loss: 2.6764 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.6764 2023/06/05 11:29:45 - mmengine - INFO - Epoch(train) [100][2100/2569] lr: 4.0000e-02 eta: 9:31:14 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 3.1253 loss: 2.7765 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.7765 2023/06/05 11:29:51 - mmengine - INFO - Epoch(train) [100][2120/2569] lr: 4.0000e-02 eta: 9:31:08 time: 0.2655 data_time: 0.0071 memory: 5828 grad_norm: 3.1165 loss: 2.5822 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.5822 2023/06/05 11:29:56 - mmengine - INFO - Epoch(train) [100][2140/2569] lr: 4.0000e-02 eta: 9:31:03 time: 0.2717 data_time: 0.0072 memory: 5828 grad_norm: 3.1470 loss: 2.2997 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2997 2023/06/05 11:30:01 - mmengine - INFO - Epoch(train) [100][2160/2569] lr: 4.0000e-02 eta: 9:30:58 time: 0.2713 data_time: 0.0073 memory: 5828 grad_norm: 3.0617 loss: 2.2667 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2667 2023/06/05 11:30:07 - mmengine - INFO - Epoch(train) [100][2180/2569] lr: 4.0000e-02 eta: 9:30:53 time: 0.2718 data_time: 0.0072 memory: 5828 grad_norm: 3.1510 loss: 2.4353 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.4353 2023/06/05 11:30:12 - mmengine - INFO - Epoch(train) [100][2200/2569] lr: 4.0000e-02 eta: 9:30:47 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 3.1529 loss: 2.7290 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.7290 2023/06/05 11:30:17 - mmengine - INFO - Epoch(train) [100][2220/2569] lr: 4.0000e-02 eta: 9:30:42 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 3.0988 loss: 2.5526 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.5526 2023/06/05 11:30:23 - mmengine - INFO - Epoch(train) [100][2240/2569] lr: 4.0000e-02 eta: 9:30:37 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 3.0984 loss: 2.1007 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1007 2023/06/05 11:30:28 - mmengine - INFO - Epoch(train) [100][2260/2569] lr: 4.0000e-02 eta: 9:30:31 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 3.2096 loss: 2.2210 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.2210 2023/06/05 11:30:34 - mmengine - INFO - Epoch(train) [100][2280/2569] lr: 4.0000e-02 eta: 9:30:26 time: 0.2658 data_time: 0.0074 memory: 5828 grad_norm: 3.1646 loss: 2.6317 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6317 2023/06/05 11:30:39 - mmengine - INFO - Epoch(train) [100][2300/2569] lr: 4.0000e-02 eta: 9:30:21 time: 0.2719 data_time: 0.0079 memory: 5828 grad_norm: 3.1262 loss: 2.3084 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.3084 2023/06/05 11:30:44 - mmengine - INFO - Epoch(train) [100][2320/2569] lr: 4.0000e-02 eta: 9:30:15 time: 0.2666 data_time: 0.0076 memory: 5828 grad_norm: 3.1788 loss: 2.6018 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.6018 2023/06/05 11:30:50 - mmengine - INFO - Epoch(train) [100][2340/2569] lr: 4.0000e-02 eta: 9:30:10 time: 0.2685 data_time: 0.0071 memory: 5828 grad_norm: 3.0574 loss: 2.8292 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.8292 2023/06/05 11:30:55 - mmengine - INFO - Epoch(train) [100][2360/2569] lr: 4.0000e-02 eta: 9:30:05 time: 0.2774 data_time: 0.0075 memory: 5828 grad_norm: 3.1172 loss: 2.6562 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 2.6562 2023/06/05 11:31:01 - mmengine - INFO - Epoch(train) [100][2380/2569] lr: 4.0000e-02 eta: 9:30:00 time: 0.2597 data_time: 0.0072 memory: 5828 grad_norm: 3.0796 loss: 2.1452 top1_acc: 0.1250 top5_acc: 0.2500 loss_cls: 2.1452 2023/06/05 11:31:06 - mmengine - INFO - Epoch(train) [100][2400/2569] lr: 4.0000e-02 eta: 9:29:54 time: 0.2742 data_time: 0.0076 memory: 5828 grad_norm: 3.0770 loss: 2.7077 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.7077 2023/06/05 11:31:11 - mmengine - INFO - Epoch(train) [100][2420/2569] lr: 4.0000e-02 eta: 9:29:49 time: 0.2588 data_time: 0.0071 memory: 5828 grad_norm: 3.0884 loss: 2.4257 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4257 2023/06/05 11:31:17 - mmengine - INFO - Epoch(train) [100][2440/2569] lr: 4.0000e-02 eta: 9:29:44 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 3.1591 loss: 2.8489 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.8489 2023/06/05 11:31:22 - mmengine - INFO - Epoch(train) [100][2460/2569] lr: 4.0000e-02 eta: 9:29:38 time: 0.2648 data_time: 0.0069 memory: 5828 grad_norm: 3.1769 loss: 2.6399 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.6399 2023/06/05 11:31:27 - mmengine - INFO - Epoch(train) [100][2480/2569] lr: 4.0000e-02 eta: 9:29:33 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 3.1604 loss: 2.6423 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.6423 2023/06/05 11:31:33 - mmengine - INFO - Epoch(train) [100][2500/2569] lr: 4.0000e-02 eta: 9:29:28 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 3.1786 loss: 2.7248 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.7248 2023/06/05 11:31:38 - mmengine - INFO - Epoch(train) [100][2520/2569] lr: 4.0000e-02 eta: 9:29:23 time: 0.2746 data_time: 0.0076 memory: 5828 grad_norm: 3.1279 loss: 2.8936 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.8936 2023/06/05 11:31:43 - mmengine - INFO - Epoch(train) [100][2540/2569] lr: 4.0000e-02 eta: 9:29:17 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 3.1179 loss: 2.3209 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3209 2023/06/05 11:31:49 - mmengine - INFO - Epoch(train) [100][2560/2569] lr: 4.0000e-02 eta: 9:29:12 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 3.1399 loss: 2.4442 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.4442 2023/06/05 11:31:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:31:51 - mmengine - INFO - Epoch(train) [100][2569/2569] lr: 4.0000e-02 eta: 9:29:09 time: 0.2508 data_time: 0.0068 memory: 5828 grad_norm: 3.1587 loss: 2.3258 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.3258 2023/06/05 11:31:51 - mmengine - INFO - Saving checkpoint at 100 epochs 2023/06/05 11:31:57 - mmengine - INFO - Epoch(val) [100][ 20/260] eta: 0:00:42 time: 0.1779 data_time: 0.1185 memory: 1238 2023/06/05 11:32:00 - mmengine - INFO - Epoch(val) [100][ 40/260] eta: 0:00:35 time: 0.1471 data_time: 0.0877 memory: 1238 2023/06/05 11:32:03 - mmengine - INFO - Epoch(val) [100][ 60/260] eta: 0:00:32 time: 0.1603 data_time: 0.1018 memory: 1238 2023/06/05 11:32:06 - mmengine - INFO - Epoch(val) [100][ 80/260] eta: 0:00:28 time: 0.1406 data_time: 0.0821 memory: 1238 2023/06/05 11:32:09 - mmengine - INFO - Epoch(val) [100][100/260] eta: 0:00:24 time: 0.1506 data_time: 0.0912 memory: 1238 2023/06/05 11:32:12 - mmengine - INFO - Epoch(val) [100][120/260] eta: 0:00:21 time: 0.1466 data_time: 0.0881 memory: 1238 2023/06/05 11:32:14 - mmengine - INFO - Epoch(val) [100][140/260] eta: 0:00:17 time: 0.1226 data_time: 0.0638 memory: 1238 2023/06/05 11:32:17 - mmengine - INFO - Epoch(val) [100][160/260] eta: 0:00:15 time: 0.1554 data_time: 0.0970 memory: 1238 2023/06/05 11:32:20 - mmengine - INFO - Epoch(val) [100][180/260] eta: 0:00:11 time: 0.1263 data_time: 0.0667 memory: 1238 2023/06/05 11:32:23 - mmengine - INFO - Epoch(val) [100][200/260] eta: 0:00:08 time: 0.1546 data_time: 0.0960 memory: 1238 2023/06/05 11:32:25 - mmengine - INFO - Epoch(val) [100][220/260] eta: 0:00:05 time: 0.1166 data_time: 0.0581 memory: 1238 2023/06/05 11:32:28 - mmengine - INFO - Epoch(val) [100][240/260] eta: 0:00:02 time: 0.1247 data_time: 0.0671 memory: 1238 2023/06/05 11:32:29 - mmengine - INFO - Epoch(val) [100][260/260] eta: 0:00:00 time: 0.0897 data_time: 0.0340 memory: 1238 2023/06/05 11:32:36 - mmengine - INFO - Epoch(val) [100][260/260] acc/top1: 0.5043 acc/top5: 0.7481 acc/mean1: 0.4959 data_time: 0.0806 time: 0.1391 2023/06/05 11:32:43 - mmengine - INFO - Epoch(train) [101][ 20/2569] lr: 4.0000e-03 eta: 9:29:05 time: 0.3293 data_time: 0.0572 memory: 5828 grad_norm: 3.0523 loss: 2.6731 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.6731 2023/06/05 11:32:48 - mmengine - INFO - Epoch(train) [101][ 40/2569] lr: 4.0000e-03 eta: 9:28:59 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 2.9998 loss: 2.3664 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3664 2023/06/05 11:32:53 - mmengine - INFO - Epoch(train) [101][ 60/2569] lr: 4.0000e-03 eta: 9:28:54 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 2.9732 loss: 2.0329 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0329 2023/06/05 11:32:59 - mmengine - INFO - Epoch(train) [101][ 80/2569] lr: 4.0000e-03 eta: 9:28:49 time: 0.2773 data_time: 0.0069 memory: 5828 grad_norm: 2.9535 loss: 2.5631 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.5631 2023/06/05 11:33:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:33:04 - mmengine - INFO - Epoch(train) [101][ 100/2569] lr: 4.0000e-03 eta: 9:28:43 time: 0.2630 data_time: 0.0070 memory: 5828 grad_norm: 2.9812 loss: 2.2807 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2807 2023/06/05 11:33:09 - mmengine - INFO - Epoch(train) [101][ 120/2569] lr: 4.0000e-03 eta: 9:28:38 time: 0.2682 data_time: 0.0071 memory: 5828 grad_norm: 3.0343 loss: 2.2474 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2474 2023/06/05 11:33:15 - mmengine - INFO - Epoch(train) [101][ 140/2569] lr: 4.0000e-03 eta: 9:28:33 time: 0.2691 data_time: 0.0071 memory: 5828 grad_norm: 2.9869 loss: 2.1710 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1710 2023/06/05 11:33:20 - mmengine - INFO - Epoch(train) [101][ 160/2569] lr: 4.0000e-03 eta: 9:28:28 time: 0.2697 data_time: 0.0069 memory: 5828 grad_norm: 2.9890 loss: 2.2404 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2404 2023/06/05 11:33:26 - mmengine - INFO - Epoch(train) [101][ 180/2569] lr: 4.0000e-03 eta: 9:28:22 time: 0.2767 data_time: 0.0073 memory: 5828 grad_norm: 2.9808 loss: 2.1920 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1920 2023/06/05 11:33:31 - mmengine - INFO - Epoch(train) [101][ 200/2569] lr: 4.0000e-03 eta: 9:28:17 time: 0.2665 data_time: 0.0080 memory: 5828 grad_norm: 3.0305 loss: 2.1466 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1466 2023/06/05 11:33:36 - mmengine - INFO - Epoch(train) [101][ 220/2569] lr: 4.0000e-03 eta: 9:28:12 time: 0.2670 data_time: 0.0078 memory: 5828 grad_norm: 3.0226 loss: 2.1892 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1892 2023/06/05 11:33:42 - mmengine - INFO - Epoch(train) [101][ 240/2569] lr: 4.0000e-03 eta: 9:28:06 time: 0.2727 data_time: 0.0071 memory: 5828 grad_norm: 3.0068 loss: 2.3774 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3774 2023/06/05 11:33:47 - mmengine - INFO - Epoch(train) [101][ 260/2569] lr: 4.0000e-03 eta: 9:28:01 time: 0.2648 data_time: 0.0080 memory: 5828 grad_norm: 3.0433 loss: 2.1093 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1093 2023/06/05 11:33:53 - mmengine - INFO - Epoch(train) [101][ 280/2569] lr: 4.0000e-03 eta: 9:27:56 time: 0.2693 data_time: 0.0085 memory: 5828 grad_norm: 3.0724 loss: 1.9566 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9566 2023/06/05 11:33:58 - mmengine - INFO - Epoch(train) [101][ 300/2569] lr: 4.0000e-03 eta: 9:27:50 time: 0.2600 data_time: 0.0074 memory: 5828 grad_norm: 3.0394 loss: 2.1946 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1946 2023/06/05 11:34:03 - mmengine - INFO - Epoch(train) [101][ 320/2569] lr: 4.0000e-03 eta: 9:27:45 time: 0.2687 data_time: 0.0072 memory: 5828 grad_norm: 3.0134 loss: 2.2037 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2037 2023/06/05 11:34:08 - mmengine - INFO - Epoch(train) [101][ 340/2569] lr: 4.0000e-03 eta: 9:27:40 time: 0.2636 data_time: 0.0071 memory: 5828 grad_norm: 3.0645 loss: 2.2827 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2827 2023/06/05 11:34:14 - mmengine - INFO - Epoch(train) [101][ 360/2569] lr: 4.0000e-03 eta: 9:27:35 time: 0.2710 data_time: 0.0075 memory: 5828 grad_norm: 3.1067 loss: 2.0648 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0648 2023/06/05 11:34:19 - mmengine - INFO - Epoch(train) [101][ 380/2569] lr: 4.0000e-03 eta: 9:27:29 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 3.0050 loss: 2.0763 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0763 2023/06/05 11:34:25 - mmengine - INFO - Epoch(train) [101][ 400/2569] lr: 4.0000e-03 eta: 9:27:24 time: 0.2706 data_time: 0.0071 memory: 5828 grad_norm: 3.0703 loss: 2.3278 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3278 2023/06/05 11:34:30 - mmengine - INFO - Epoch(train) [101][ 420/2569] lr: 4.0000e-03 eta: 9:27:19 time: 0.2662 data_time: 0.0073 memory: 5828 grad_norm: 3.1197 loss: 2.3170 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.3170 2023/06/05 11:34:35 - mmengine - INFO - Epoch(train) [101][ 440/2569] lr: 4.0000e-03 eta: 9:27:13 time: 0.2596 data_time: 0.0072 memory: 5828 grad_norm: 3.0855 loss: 2.2832 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2832 2023/06/05 11:34:41 - mmengine - INFO - Epoch(train) [101][ 460/2569] lr: 4.0000e-03 eta: 9:27:08 time: 0.2696 data_time: 0.0070 memory: 5828 grad_norm: 3.0755 loss: 2.3053 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3053 2023/06/05 11:34:46 - mmengine - INFO - Epoch(train) [101][ 480/2569] lr: 4.0000e-03 eta: 9:27:03 time: 0.2613 data_time: 0.0071 memory: 5828 grad_norm: 3.0473 loss: 2.2082 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2082 2023/06/05 11:34:51 - mmengine - INFO - Epoch(train) [101][ 500/2569] lr: 4.0000e-03 eta: 9:26:57 time: 0.2720 data_time: 0.0078 memory: 5828 grad_norm: 3.0083 loss: 2.1340 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1340 2023/06/05 11:34:56 - mmengine - INFO - Epoch(train) [101][ 520/2569] lr: 4.0000e-03 eta: 9:26:52 time: 0.2611 data_time: 0.0071 memory: 5828 grad_norm: 3.1099 loss: 2.2454 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2454 2023/06/05 11:35:02 - mmengine - INFO - Epoch(train) [101][ 540/2569] lr: 4.0000e-03 eta: 9:26:47 time: 0.2711 data_time: 0.0070 memory: 5828 grad_norm: 3.1230 loss: 2.1162 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1162 2023/06/05 11:35:07 - mmengine - INFO - Epoch(train) [101][ 560/2569] lr: 4.0000e-03 eta: 9:26:41 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 3.0613 loss: 2.2890 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2890 2023/06/05 11:35:13 - mmengine - INFO - Epoch(train) [101][ 580/2569] lr: 4.0000e-03 eta: 9:26:36 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 3.0897 loss: 2.0436 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0436 2023/06/05 11:35:18 - mmengine - INFO - Epoch(train) [101][ 600/2569] lr: 4.0000e-03 eta: 9:26:31 time: 0.2782 data_time: 0.0071 memory: 5828 grad_norm: 3.0722 loss: 2.1277 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1277 2023/06/05 11:35:24 - mmengine - INFO - Epoch(train) [101][ 620/2569] lr: 4.0000e-03 eta: 9:26:26 time: 0.2653 data_time: 0.0071 memory: 5828 grad_norm: 3.1109 loss: 2.0020 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0020 2023/06/05 11:35:29 - mmengine - INFO - Epoch(train) [101][ 640/2569] lr: 4.0000e-03 eta: 9:26:20 time: 0.2689 data_time: 0.0068 memory: 5828 grad_norm: 3.0852 loss: 2.3300 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3300 2023/06/05 11:35:34 - mmengine - INFO - Epoch(train) [101][ 660/2569] lr: 4.0000e-03 eta: 9:26:15 time: 0.2602 data_time: 0.0071 memory: 5828 grad_norm: 3.1608 loss: 2.3163 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3163 2023/06/05 11:35:40 - mmengine - INFO - Epoch(train) [101][ 680/2569] lr: 4.0000e-03 eta: 9:26:10 time: 0.2808 data_time: 0.0069 memory: 5828 grad_norm: 3.1360 loss: 2.4450 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4450 2023/06/05 11:35:45 - mmengine - INFO - Epoch(train) [101][ 700/2569] lr: 4.0000e-03 eta: 9:26:04 time: 0.2603 data_time: 0.0070 memory: 5828 grad_norm: 3.1200 loss: 2.0544 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0544 2023/06/05 11:35:50 - mmengine - INFO - Epoch(train) [101][ 720/2569] lr: 4.0000e-03 eta: 9:25:59 time: 0.2732 data_time: 0.0069 memory: 5828 grad_norm: 3.0674 loss: 2.1017 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1017 2023/06/05 11:35:56 - mmengine - INFO - Epoch(train) [101][ 740/2569] lr: 4.0000e-03 eta: 9:25:54 time: 0.2614 data_time: 0.0070 memory: 5828 grad_norm: 3.1298 loss: 2.2234 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.2234 2023/06/05 11:36:01 - mmengine - INFO - Epoch(train) [101][ 760/2569] lr: 4.0000e-03 eta: 9:25:48 time: 0.2610 data_time: 0.0070 memory: 5828 grad_norm: 3.1190 loss: 2.1737 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1737 2023/06/05 11:36:06 - mmengine - INFO - Epoch(train) [101][ 780/2569] lr: 4.0000e-03 eta: 9:25:43 time: 0.2605 data_time: 0.0070 memory: 5828 grad_norm: 3.1311 loss: 2.4386 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4386 2023/06/05 11:36:11 - mmengine - INFO - Epoch(train) [101][ 800/2569] lr: 4.0000e-03 eta: 9:25:38 time: 0.2693 data_time: 0.0070 memory: 5828 grad_norm: 3.1885 loss: 2.3041 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3041 2023/06/05 11:36:17 - mmengine - INFO - Epoch(train) [101][ 820/2569] lr: 4.0000e-03 eta: 9:25:32 time: 0.2651 data_time: 0.0069 memory: 5828 grad_norm: 3.1215 loss: 2.0726 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0726 2023/06/05 11:36:22 - mmengine - INFO - Epoch(train) [101][ 840/2569] lr: 4.0000e-03 eta: 9:25:27 time: 0.2713 data_time: 0.0072 memory: 5828 grad_norm: 3.1599 loss: 2.1426 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1426 2023/06/05 11:36:28 - mmengine - INFO - Epoch(train) [101][ 860/2569] lr: 4.0000e-03 eta: 9:25:22 time: 0.2663 data_time: 0.0069 memory: 5828 grad_norm: 3.1749 loss: 1.8218 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8218 2023/06/05 11:36:33 - mmengine - INFO - Epoch(train) [101][ 880/2569] lr: 4.0000e-03 eta: 9:25:17 time: 0.2604 data_time: 0.0072 memory: 5828 grad_norm: 3.1483 loss: 1.8333 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8333 2023/06/05 11:36:38 - mmengine - INFO - Epoch(train) [101][ 900/2569] lr: 4.0000e-03 eta: 9:25:11 time: 0.2637 data_time: 0.0070 memory: 5828 grad_norm: 3.1360 loss: 2.0276 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0276 2023/06/05 11:36:43 - mmengine - INFO - Epoch(train) [101][ 920/2569] lr: 4.0000e-03 eta: 9:25:06 time: 0.2645 data_time: 0.0070 memory: 5828 grad_norm: 3.0923 loss: 1.8526 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8526 2023/06/05 11:36:49 - mmengine - INFO - Epoch(train) [101][ 940/2569] lr: 4.0000e-03 eta: 9:25:01 time: 0.2666 data_time: 0.0068 memory: 5828 grad_norm: 3.1653 loss: 2.1334 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1334 2023/06/05 11:36:54 - mmengine - INFO - Epoch(train) [101][ 960/2569] lr: 4.0000e-03 eta: 9:24:55 time: 0.2649 data_time: 0.0069 memory: 5828 grad_norm: 3.1323 loss: 2.1271 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1271 2023/06/05 11:36:59 - mmengine - INFO - Epoch(train) [101][ 980/2569] lr: 4.0000e-03 eta: 9:24:50 time: 0.2697 data_time: 0.0071 memory: 5828 grad_norm: 3.1446 loss: 2.2440 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2440 2023/06/05 11:37:05 - mmengine - INFO - Epoch(train) [101][1000/2569] lr: 4.0000e-03 eta: 9:24:45 time: 0.2656 data_time: 0.0072 memory: 5828 grad_norm: 3.1544 loss: 2.3965 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3965 2023/06/05 11:37:10 - mmengine - INFO - Epoch(train) [101][1020/2569] lr: 4.0000e-03 eta: 9:24:39 time: 0.2663 data_time: 0.0071 memory: 5828 grad_norm: 3.1432 loss: 2.1664 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1664 2023/06/05 11:37:15 - mmengine - INFO - Epoch(train) [101][1040/2569] lr: 4.0000e-03 eta: 9:24:34 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 3.1349 loss: 1.9370 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9370 2023/06/05 11:37:21 - mmengine - INFO - Epoch(train) [101][1060/2569] lr: 4.0000e-03 eta: 9:24:29 time: 0.2659 data_time: 0.0073 memory: 5828 grad_norm: 3.2151 loss: 2.2595 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2595 2023/06/05 11:37:26 - mmengine - INFO - Epoch(train) [101][1080/2569] lr: 4.0000e-03 eta: 9:24:23 time: 0.2600 data_time: 0.0070 memory: 5828 grad_norm: 3.1420 loss: 2.0055 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0055 2023/06/05 11:37:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:37:32 - mmengine - INFO - Epoch(train) [101][1100/2569] lr: 4.0000e-03 eta: 9:24:18 time: 0.2818 data_time: 0.0068 memory: 5828 grad_norm: 3.1900 loss: 1.8871 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 1.8871 2023/06/05 11:37:37 - mmengine - INFO - Epoch(train) [101][1120/2569] lr: 4.0000e-03 eta: 9:24:13 time: 0.2648 data_time: 0.0076 memory: 5828 grad_norm: 3.1103 loss: 2.3514 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3514 2023/06/05 11:37:42 - mmengine - INFO - Epoch(train) [101][1140/2569] lr: 4.0000e-03 eta: 9:24:08 time: 0.2696 data_time: 0.0077 memory: 5828 grad_norm: 3.1521 loss: 2.4874 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.4874 2023/06/05 11:37:48 - mmengine - INFO - Epoch(train) [101][1160/2569] lr: 4.0000e-03 eta: 9:24:02 time: 0.2717 data_time: 0.0082 memory: 5828 grad_norm: 3.1676 loss: 1.8606 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8606 2023/06/05 11:37:53 - mmengine - INFO - Epoch(train) [101][1180/2569] lr: 4.0000e-03 eta: 9:23:57 time: 0.2690 data_time: 0.0074 memory: 5828 grad_norm: 3.1426 loss: 2.0191 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0191 2023/06/05 11:37:59 - mmengine - INFO - Epoch(train) [101][1200/2569] lr: 4.0000e-03 eta: 9:23:52 time: 0.2738 data_time: 0.0072 memory: 5828 grad_norm: 3.1397 loss: 2.1520 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1520 2023/06/05 11:38:04 - mmengine - INFO - Epoch(train) [101][1220/2569] lr: 4.0000e-03 eta: 9:23:46 time: 0.2623 data_time: 0.0083 memory: 5828 grad_norm: 3.1178 loss: 2.2004 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2004 2023/06/05 11:38:09 - mmengine - INFO - Epoch(train) [101][1240/2569] lr: 4.0000e-03 eta: 9:23:41 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 3.1717 loss: 1.9131 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9131 2023/06/05 11:38:14 - mmengine - INFO - Epoch(train) [101][1260/2569] lr: 4.0000e-03 eta: 9:23:36 time: 0.2600 data_time: 0.0077 memory: 5828 grad_norm: 3.1871 loss: 2.4734 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4734 2023/06/05 11:38:20 - mmengine - INFO - Epoch(train) [101][1280/2569] lr: 4.0000e-03 eta: 9:23:30 time: 0.2662 data_time: 0.0072 memory: 5828 grad_norm: 3.2189 loss: 2.4548 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4548 2023/06/05 11:38:25 - mmengine - INFO - Epoch(train) [101][1300/2569] lr: 4.0000e-03 eta: 9:23:25 time: 0.2655 data_time: 0.0072 memory: 5828 grad_norm: 3.1023 loss: 2.1645 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1645 2023/06/05 11:38:30 - mmengine - INFO - Epoch(train) [101][1320/2569] lr: 4.0000e-03 eta: 9:23:20 time: 0.2685 data_time: 0.0071 memory: 5828 grad_norm: 3.1475 loss: 1.8495 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8495 2023/06/05 11:38:36 - mmengine - INFO - Epoch(train) [101][1340/2569] lr: 4.0000e-03 eta: 9:23:14 time: 0.2679 data_time: 0.0075 memory: 5828 grad_norm: 3.1206 loss: 2.0971 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0971 2023/06/05 11:38:41 - mmengine - INFO - Epoch(train) [101][1360/2569] lr: 4.0000e-03 eta: 9:23:09 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 3.1724 loss: 2.1037 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1037 2023/06/05 11:38:46 - mmengine - INFO - Epoch(train) [101][1380/2569] lr: 4.0000e-03 eta: 9:23:04 time: 0.2597 data_time: 0.0068 memory: 5828 grad_norm: 3.1703 loss: 2.0988 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0988 2023/06/05 11:38:52 - mmengine - INFO - Epoch(train) [101][1400/2569] lr: 4.0000e-03 eta: 9:22:58 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 3.1774 loss: 2.0797 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0797 2023/06/05 11:38:57 - mmengine - INFO - Epoch(train) [101][1420/2569] lr: 4.0000e-03 eta: 9:22:53 time: 0.2678 data_time: 0.0071 memory: 5828 grad_norm: 3.1928 loss: 2.0046 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0046 2023/06/05 11:39:02 - mmengine - INFO - Epoch(train) [101][1440/2569] lr: 4.0000e-03 eta: 9:22:48 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 3.2061 loss: 1.9510 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9510 2023/06/05 11:39:08 - mmengine - INFO - Epoch(train) [101][1460/2569] lr: 4.0000e-03 eta: 9:22:43 time: 0.2722 data_time: 0.0073 memory: 5828 grad_norm: 3.2096 loss: 2.2970 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2970 2023/06/05 11:39:13 - mmengine - INFO - Epoch(train) [101][1480/2569] lr: 4.0000e-03 eta: 9:22:37 time: 0.2608 data_time: 0.0074 memory: 5828 grad_norm: 3.2013 loss: 2.1033 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1033 2023/06/05 11:39:18 - mmengine - INFO - Epoch(train) [101][1500/2569] lr: 4.0000e-03 eta: 9:22:32 time: 0.2607 data_time: 0.0076 memory: 5828 grad_norm: 3.1611 loss: 2.1924 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1924 2023/06/05 11:39:23 - mmengine - INFO - Epoch(train) [101][1520/2569] lr: 4.0000e-03 eta: 9:22:26 time: 0.2631 data_time: 0.0075 memory: 5828 grad_norm: 3.2049 loss: 2.2552 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2552 2023/06/05 11:39:29 - mmengine - INFO - Epoch(train) [101][1540/2569] lr: 4.0000e-03 eta: 9:22:21 time: 0.2652 data_time: 0.0074 memory: 5828 grad_norm: 3.1238 loss: 1.7653 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7653 2023/06/05 11:39:34 - mmengine - INFO - Epoch(train) [101][1560/2569] lr: 4.0000e-03 eta: 9:22:16 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 3.1844 loss: 2.1311 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1311 2023/06/05 11:39:39 - mmengine - INFO - Epoch(train) [101][1580/2569] lr: 4.0000e-03 eta: 9:22:10 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 3.1825 loss: 2.0674 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0674 2023/06/05 11:39:45 - mmengine - INFO - Epoch(train) [101][1600/2569] lr: 4.0000e-03 eta: 9:22:05 time: 0.2749 data_time: 0.0072 memory: 5828 grad_norm: 3.1903 loss: 2.1368 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1368 2023/06/05 11:39:50 - mmengine - INFO - Epoch(train) [101][1620/2569] lr: 4.0000e-03 eta: 9:22:00 time: 0.2631 data_time: 0.0076 memory: 5828 grad_norm: 3.1659 loss: 1.8476 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8476 2023/06/05 11:39:56 - mmengine - INFO - Epoch(train) [101][1640/2569] lr: 4.0000e-03 eta: 9:21:55 time: 0.2736 data_time: 0.0075 memory: 5828 grad_norm: 3.1838 loss: 2.0526 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0526 2023/06/05 11:40:01 - mmengine - INFO - Epoch(train) [101][1660/2569] lr: 4.0000e-03 eta: 9:21:49 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 3.2328 loss: 2.1956 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1956 2023/06/05 11:40:06 - mmengine - INFO - Epoch(train) [101][1680/2569] lr: 4.0000e-03 eta: 9:21:44 time: 0.2605 data_time: 0.0070 memory: 5828 grad_norm: 3.2124 loss: 1.8540 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8540 2023/06/05 11:40:12 - mmengine - INFO - Epoch(train) [101][1700/2569] lr: 4.0000e-03 eta: 9:21:39 time: 0.2711 data_time: 0.0073 memory: 5828 grad_norm: 3.2285 loss: 2.2285 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.2285 2023/06/05 11:40:17 - mmengine - INFO - Epoch(train) [101][1720/2569] lr: 4.0000e-03 eta: 9:21:33 time: 0.2667 data_time: 0.0071 memory: 5828 grad_norm: 3.1503 loss: 2.5580 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.5580 2023/06/05 11:40:22 - mmengine - INFO - Epoch(train) [101][1740/2569] lr: 4.0000e-03 eta: 9:21:28 time: 0.2769 data_time: 0.0071 memory: 5828 grad_norm: 3.2365 loss: 1.8156 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8156 2023/06/05 11:40:28 - mmengine - INFO - Epoch(train) [101][1760/2569] lr: 4.0000e-03 eta: 9:21:23 time: 0.2681 data_time: 0.0076 memory: 5828 grad_norm: 3.1791 loss: 2.1331 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1331 2023/06/05 11:40:33 - mmengine - INFO - Epoch(train) [101][1780/2569] lr: 4.0000e-03 eta: 9:21:18 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 3.2300 loss: 1.9097 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9097 2023/06/05 11:40:38 - mmengine - INFO - Epoch(train) [101][1800/2569] lr: 4.0000e-03 eta: 9:21:12 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 3.1810 loss: 2.2105 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2105 2023/06/05 11:40:44 - mmengine - INFO - Epoch(train) [101][1820/2569] lr: 4.0000e-03 eta: 9:21:07 time: 0.2619 data_time: 0.0068 memory: 5828 grad_norm: 3.2558 loss: 2.0004 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.0004 2023/06/05 11:40:49 - mmengine - INFO - Epoch(train) [101][1840/2569] lr: 4.0000e-03 eta: 9:21:02 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.2210 loss: 2.0187 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0187 2023/06/05 11:40:54 - mmengine - INFO - Epoch(train) [101][1860/2569] lr: 4.0000e-03 eta: 9:20:56 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 3.1996 loss: 1.9612 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9612 2023/06/05 11:41:00 - mmengine - INFO - Epoch(train) [101][1880/2569] lr: 4.0000e-03 eta: 9:20:51 time: 0.2717 data_time: 0.0074 memory: 5828 grad_norm: 3.2154 loss: 1.6869 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6869 2023/06/05 11:41:05 - mmengine - INFO - Epoch(train) [101][1900/2569] lr: 4.0000e-03 eta: 9:20:46 time: 0.2696 data_time: 0.0067 memory: 5828 grad_norm: 3.2137 loss: 1.8930 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8930 2023/06/05 11:41:10 - mmengine - INFO - Epoch(train) [101][1920/2569] lr: 4.0000e-03 eta: 9:20:40 time: 0.2715 data_time: 0.0072 memory: 5828 grad_norm: 3.2524 loss: 2.1284 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1284 2023/06/05 11:41:16 - mmengine - INFO - Epoch(train) [101][1940/2569] lr: 4.0000e-03 eta: 9:20:35 time: 0.2708 data_time: 0.0074 memory: 5828 grad_norm: 3.2073 loss: 1.8239 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.8239 2023/06/05 11:41:21 - mmengine - INFO - Epoch(train) [101][1960/2569] lr: 4.0000e-03 eta: 9:20:30 time: 0.2637 data_time: 0.0070 memory: 5828 grad_norm: 3.1721 loss: 1.9575 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9575 2023/06/05 11:41:27 - mmengine - INFO - Epoch(train) [101][1980/2569] lr: 4.0000e-03 eta: 9:20:25 time: 0.2741 data_time: 0.0069 memory: 5828 grad_norm: 3.1952 loss: 2.2994 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2994 2023/06/05 11:41:32 - mmengine - INFO - Epoch(train) [101][2000/2569] lr: 4.0000e-03 eta: 9:20:19 time: 0.2631 data_time: 0.0069 memory: 5828 grad_norm: 3.1855 loss: 2.1009 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1009 2023/06/05 11:41:37 - mmengine - INFO - Epoch(train) [101][2020/2569] lr: 4.0000e-03 eta: 9:20:14 time: 0.2619 data_time: 0.0070 memory: 5828 grad_norm: 3.1980 loss: 1.7185 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7185 2023/06/05 11:41:43 - mmengine - INFO - Epoch(train) [101][2040/2569] lr: 4.0000e-03 eta: 9:20:09 time: 0.2736 data_time: 0.0083 memory: 5828 grad_norm: 3.2154 loss: 2.1306 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.1306 2023/06/05 11:41:48 - mmengine - INFO - Epoch(train) [101][2060/2569] lr: 4.0000e-03 eta: 9:20:03 time: 0.2643 data_time: 0.0071 memory: 5828 grad_norm: 3.2346 loss: 2.1488 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1488 2023/06/05 11:41:53 - mmengine - INFO - Epoch(train) [101][2080/2569] lr: 4.0000e-03 eta: 9:19:58 time: 0.2659 data_time: 0.0069 memory: 5828 grad_norm: 3.2280 loss: 2.0441 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0441 2023/06/05 11:41:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:41:59 - mmengine - INFO - Epoch(train) [101][2100/2569] lr: 4.0000e-03 eta: 9:19:53 time: 0.2609 data_time: 0.0071 memory: 5828 grad_norm: 3.2069 loss: 2.2875 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2875 2023/06/05 11:42:04 - mmengine - INFO - Epoch(train) [101][2120/2569] lr: 4.0000e-03 eta: 9:19:47 time: 0.2616 data_time: 0.0072 memory: 5828 grad_norm: 3.2384 loss: 2.1296 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1296 2023/06/05 11:42:09 - mmengine - INFO - Epoch(train) [101][2140/2569] lr: 4.0000e-03 eta: 9:19:42 time: 0.2596 data_time: 0.0072 memory: 5828 grad_norm: 3.1949 loss: 2.2352 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2352 2023/06/05 11:42:14 - mmengine - INFO - Epoch(train) [101][2160/2569] lr: 4.0000e-03 eta: 9:19:37 time: 0.2739 data_time: 0.0074 memory: 5828 grad_norm: 3.3068 loss: 2.1269 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1269 2023/06/05 11:42:20 - mmengine - INFO - Epoch(train) [101][2180/2569] lr: 4.0000e-03 eta: 9:19:31 time: 0.2630 data_time: 0.0072 memory: 5828 grad_norm: 3.1604 loss: 2.0393 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0393 2023/06/05 11:42:25 - mmengine - INFO - Epoch(train) [101][2200/2569] lr: 4.0000e-03 eta: 9:19:26 time: 0.2613 data_time: 0.0069 memory: 5828 grad_norm: 3.2282 loss: 2.1122 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1122 2023/06/05 11:42:30 - mmengine - INFO - Epoch(train) [101][2220/2569] lr: 4.0000e-03 eta: 9:19:21 time: 0.2589 data_time: 0.0072 memory: 5828 grad_norm: 3.2163 loss: 2.3434 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3434 2023/06/05 11:42:35 - mmengine - INFO - Epoch(train) [101][2240/2569] lr: 4.0000e-03 eta: 9:19:15 time: 0.2606 data_time: 0.0074 memory: 5828 grad_norm: 3.2694 loss: 1.8286 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8286 2023/06/05 11:42:41 - mmengine - INFO - Epoch(train) [101][2260/2569] lr: 4.0000e-03 eta: 9:19:10 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 3.2406 loss: 2.0154 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0154 2023/06/05 11:42:46 - mmengine - INFO - Epoch(train) [101][2280/2569] lr: 4.0000e-03 eta: 9:19:04 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 3.2115 loss: 2.0527 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0527 2023/06/05 11:42:51 - mmengine - INFO - Epoch(train) [101][2300/2569] lr: 4.0000e-03 eta: 9:18:59 time: 0.2662 data_time: 0.0071 memory: 5828 grad_norm: 3.2933 loss: 2.3371 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.3371 2023/06/05 11:42:57 - mmengine - INFO - Epoch(train) [101][2320/2569] lr: 4.0000e-03 eta: 9:18:54 time: 0.2663 data_time: 0.0072 memory: 5828 grad_norm: 3.3070 loss: 2.1516 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1516 2023/06/05 11:43:02 - mmengine - INFO - Epoch(train) [101][2340/2569] lr: 4.0000e-03 eta: 9:18:48 time: 0.2652 data_time: 0.0073 memory: 5828 grad_norm: 3.2857 loss: 2.0584 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0584 2023/06/05 11:43:07 - mmengine - INFO - Epoch(train) [101][2360/2569] lr: 4.0000e-03 eta: 9:18:43 time: 0.2700 data_time: 0.0074 memory: 5828 grad_norm: 3.2602 loss: 2.1081 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1081 2023/06/05 11:43:13 - mmengine - INFO - Epoch(train) [101][2380/2569] lr: 4.0000e-03 eta: 9:18:38 time: 0.2653 data_time: 0.0069 memory: 5828 grad_norm: 3.2354 loss: 2.0719 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0719 2023/06/05 11:43:18 - mmengine - INFO - Epoch(train) [101][2400/2569] lr: 4.0000e-03 eta: 9:18:33 time: 0.2630 data_time: 0.0074 memory: 5828 grad_norm: 3.2146 loss: 1.9292 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9292 2023/06/05 11:43:23 - mmengine - INFO - Epoch(train) [101][2420/2569] lr: 4.0000e-03 eta: 9:18:27 time: 0.2601 data_time: 0.0071 memory: 5828 grad_norm: 3.2489 loss: 1.8491 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8491 2023/06/05 11:43:28 - mmengine - INFO - Epoch(train) [101][2440/2569] lr: 4.0000e-03 eta: 9:18:22 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.1749 loss: 1.8764 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8764 2023/06/05 11:43:34 - mmengine - INFO - Epoch(train) [101][2460/2569] lr: 4.0000e-03 eta: 9:18:17 time: 0.2718 data_time: 0.0070 memory: 5828 grad_norm: 3.2911 loss: 1.8678 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8678 2023/06/05 11:43:39 - mmengine - INFO - Epoch(train) [101][2480/2569] lr: 4.0000e-03 eta: 9:18:11 time: 0.2675 data_time: 0.0071 memory: 5828 grad_norm: 3.2401 loss: 2.1053 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1053 2023/06/05 11:43:44 - mmengine - INFO - Epoch(train) [101][2500/2569] lr: 4.0000e-03 eta: 9:18:06 time: 0.2613 data_time: 0.0070 memory: 5828 grad_norm: 3.2398 loss: 1.8400 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8400 2023/06/05 11:43:50 - mmengine - INFO - Epoch(train) [101][2520/2569] lr: 4.0000e-03 eta: 9:18:01 time: 0.2635 data_time: 0.0068 memory: 5828 grad_norm: 3.2985 loss: 2.1454 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1454 2023/06/05 11:43:55 - mmengine - INFO - Epoch(train) [101][2540/2569] lr: 4.0000e-03 eta: 9:17:55 time: 0.2690 data_time: 0.0070 memory: 5828 grad_norm: 3.3115 loss: 2.0927 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0927 2023/06/05 11:44:00 - mmengine - INFO - Epoch(train) [101][2560/2569] lr: 4.0000e-03 eta: 9:17:50 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 3.2657 loss: 2.1569 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1569 2023/06/05 11:44:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:44:02 - mmengine - INFO - Epoch(train) [101][2569/2569] lr: 4.0000e-03 eta: 9:17:47 time: 0.2575 data_time: 0.0071 memory: 5828 grad_norm: 3.3118 loss: 1.8033 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.8033 2023/06/05 11:44:09 - mmengine - INFO - Epoch(train) [102][ 20/2569] lr: 4.0000e-03 eta: 9:17:43 time: 0.3389 data_time: 0.0484 memory: 5828 grad_norm: 3.2368 loss: 2.2757 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2757 2023/06/05 11:44:15 - mmengine - INFO - Epoch(train) [102][ 40/2569] lr: 4.0000e-03 eta: 9:17:37 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 3.2215 loss: 2.0866 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0866 2023/06/05 11:44:20 - mmengine - INFO - Epoch(train) [102][ 60/2569] lr: 4.0000e-03 eta: 9:17:32 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 3.1708 loss: 2.1001 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1001 2023/06/05 11:44:25 - mmengine - INFO - Epoch(train) [102][ 80/2569] lr: 4.0000e-03 eta: 9:17:27 time: 0.2663 data_time: 0.0071 memory: 5828 grad_norm: 3.2412 loss: 2.2259 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2259 2023/06/05 11:44:31 - mmengine - INFO - Epoch(train) [102][ 100/2569] lr: 4.0000e-03 eta: 9:17:22 time: 0.2682 data_time: 0.0074 memory: 5828 grad_norm: 3.2547 loss: 2.3574 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3574 2023/06/05 11:44:36 - mmengine - INFO - Epoch(train) [102][ 120/2569] lr: 4.0000e-03 eta: 9:17:16 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 3.2460 loss: 2.0858 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0858 2023/06/05 11:44:41 - mmengine - INFO - Epoch(train) [102][ 140/2569] lr: 4.0000e-03 eta: 9:17:11 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 3.2701 loss: 2.4859 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4859 2023/06/05 11:44:47 - mmengine - INFO - Epoch(train) [102][ 160/2569] lr: 4.0000e-03 eta: 9:17:06 time: 0.2661 data_time: 0.0070 memory: 5828 grad_norm: 3.2179 loss: 1.8565 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8565 2023/06/05 11:44:52 - mmengine - INFO - Epoch(train) [102][ 180/2569] lr: 4.0000e-03 eta: 9:17:00 time: 0.2673 data_time: 0.0070 memory: 5828 grad_norm: 3.2637 loss: 2.1067 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1067 2023/06/05 11:44:57 - mmengine - INFO - Epoch(train) [102][ 200/2569] lr: 4.0000e-03 eta: 9:16:55 time: 0.2651 data_time: 0.0071 memory: 5828 grad_norm: 3.2142 loss: 1.9449 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9449 2023/06/05 11:45:03 - mmengine - INFO - Epoch(train) [102][ 220/2569] lr: 4.0000e-03 eta: 9:16:50 time: 0.2772 data_time: 0.0069 memory: 5828 grad_norm: 3.1861 loss: 2.2571 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2571 2023/06/05 11:45:08 - mmengine - INFO - Epoch(train) [102][ 240/2569] lr: 4.0000e-03 eta: 9:16:44 time: 0.2665 data_time: 0.0071 memory: 5828 grad_norm: 3.2964 loss: 1.8837 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8837 2023/06/05 11:45:14 - mmengine - INFO - Epoch(train) [102][ 260/2569] lr: 4.0000e-03 eta: 9:16:39 time: 0.2719 data_time: 0.0068 memory: 5828 grad_norm: 3.2066 loss: 1.9113 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9113 2023/06/05 11:45:19 - mmengine - INFO - Epoch(train) [102][ 280/2569] lr: 4.0000e-03 eta: 9:16:34 time: 0.2671 data_time: 0.0070 memory: 5828 grad_norm: 3.2697 loss: 1.9887 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9887 2023/06/05 11:45:24 - mmengine - INFO - Epoch(train) [102][ 300/2569] lr: 4.0000e-03 eta: 9:16:29 time: 0.2726 data_time: 0.0075 memory: 5828 grad_norm: 3.2537 loss: 1.9579 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9579 2023/06/05 11:45:30 - mmengine - INFO - Epoch(train) [102][ 320/2569] lr: 4.0000e-03 eta: 9:16:23 time: 0.2676 data_time: 0.0071 memory: 5828 grad_norm: 3.2525 loss: 1.7297 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7297 2023/06/05 11:45:35 - mmengine - INFO - Epoch(train) [102][ 340/2569] lr: 4.0000e-03 eta: 9:16:18 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 3.2867 loss: 2.0046 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0046 2023/06/05 11:45:40 - mmengine - INFO - Epoch(train) [102][ 360/2569] lr: 4.0000e-03 eta: 9:16:13 time: 0.2663 data_time: 0.0069 memory: 5828 grad_norm: 3.2932 loss: 2.1818 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1818 2023/06/05 11:45:46 - mmengine - INFO - Epoch(train) [102][ 380/2569] lr: 4.0000e-03 eta: 9:16:07 time: 0.2611 data_time: 0.0071 memory: 5828 grad_norm: 3.2290 loss: 1.9821 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9821 2023/06/05 11:45:51 - mmengine - INFO - Epoch(train) [102][ 400/2569] lr: 4.0000e-03 eta: 9:16:02 time: 0.2611 data_time: 0.0070 memory: 5828 grad_norm: 3.2333 loss: 2.1139 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1139 2023/06/05 11:45:56 - mmengine - INFO - Epoch(train) [102][ 420/2569] lr: 4.0000e-03 eta: 9:15:57 time: 0.2707 data_time: 0.0070 memory: 5828 grad_norm: 3.2733 loss: 2.1349 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1349 2023/06/05 11:46:02 - mmengine - INFO - Epoch(train) [102][ 440/2569] lr: 4.0000e-03 eta: 9:15:51 time: 0.2660 data_time: 0.0070 memory: 5828 grad_norm: 3.2673 loss: 2.3111 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3111 2023/06/05 11:46:07 - mmengine - INFO - Epoch(train) [102][ 460/2569] lr: 4.0000e-03 eta: 9:15:46 time: 0.2740 data_time: 0.0069 memory: 5828 grad_norm: 3.2320 loss: 1.9765 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9765 2023/06/05 11:46:12 - mmengine - INFO - Epoch(train) [102][ 480/2569] lr: 4.0000e-03 eta: 9:15:41 time: 0.2642 data_time: 0.0072 memory: 5828 grad_norm: 3.2535 loss: 1.9187 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9187 2023/06/05 11:46:18 - mmengine - INFO - Epoch(train) [102][ 500/2569] lr: 4.0000e-03 eta: 9:15:35 time: 0.2634 data_time: 0.0069 memory: 5828 grad_norm: 3.2480 loss: 2.1126 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1126 2023/06/05 11:46:23 - mmengine - INFO - Epoch(train) [102][ 520/2569] lr: 4.0000e-03 eta: 9:15:30 time: 0.2727 data_time: 0.0070 memory: 5828 grad_norm: 3.2642 loss: 2.1810 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1810 2023/06/05 11:46:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:46:28 - mmengine - INFO - Epoch(train) [102][ 540/2569] lr: 4.0000e-03 eta: 9:15:25 time: 0.2639 data_time: 0.0069 memory: 5828 grad_norm: 3.2584 loss: 1.7741 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7741 2023/06/05 11:46:34 - mmengine - INFO - Epoch(train) [102][ 560/2569] lr: 4.0000e-03 eta: 9:15:20 time: 0.2595 data_time: 0.0074 memory: 5828 grad_norm: 3.2355 loss: 1.8839 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8839 2023/06/05 11:46:39 - mmengine - INFO - Epoch(train) [102][ 580/2569] lr: 4.0000e-03 eta: 9:15:14 time: 0.2622 data_time: 0.0070 memory: 5828 grad_norm: 3.2185 loss: 1.7973 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7973 2023/06/05 11:46:44 - mmengine - INFO - Epoch(train) [102][ 600/2569] lr: 4.0000e-03 eta: 9:15:09 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 3.2513 loss: 2.1026 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1026 2023/06/05 11:46:49 - mmengine - INFO - Epoch(train) [102][ 620/2569] lr: 4.0000e-03 eta: 9:15:03 time: 0.2610 data_time: 0.0072 memory: 5828 grad_norm: 3.2088 loss: 2.0771 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0771 2023/06/05 11:46:55 - mmengine - INFO - Epoch(train) [102][ 640/2569] lr: 4.0000e-03 eta: 9:14:58 time: 0.2640 data_time: 0.0072 memory: 5828 grad_norm: 3.2917 loss: 2.2070 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2070 2023/06/05 11:47:00 - mmengine - INFO - Epoch(train) [102][ 660/2569] lr: 4.0000e-03 eta: 9:14:53 time: 0.2729 data_time: 0.0074 memory: 5828 grad_norm: 3.1889 loss: 1.8280 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.8280 2023/06/05 11:47:06 - mmengine - INFO - Epoch(train) [102][ 680/2569] lr: 4.0000e-03 eta: 9:14:48 time: 0.2679 data_time: 0.0078 memory: 5828 grad_norm: 3.2631 loss: 2.0128 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0128 2023/06/05 11:47:11 - mmengine - INFO - Epoch(train) [102][ 700/2569] lr: 4.0000e-03 eta: 9:14:42 time: 0.2738 data_time: 0.0072 memory: 5828 grad_norm: 3.2692 loss: 2.3362 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.3362 2023/06/05 11:47:16 - mmengine - INFO - Epoch(train) [102][ 720/2569] lr: 4.0000e-03 eta: 9:14:37 time: 0.2630 data_time: 0.0072 memory: 5828 grad_norm: 3.2727 loss: 1.7240 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7240 2023/06/05 11:47:22 - mmengine - INFO - Epoch(train) [102][ 740/2569] lr: 4.0000e-03 eta: 9:14:32 time: 0.2859 data_time: 0.0072 memory: 5828 grad_norm: 3.3395 loss: 2.1105 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1105 2023/06/05 11:47:27 - mmengine - INFO - Epoch(train) [102][ 760/2569] lr: 4.0000e-03 eta: 9:14:27 time: 0.2640 data_time: 0.0075 memory: 5828 grad_norm: 3.3276 loss: 1.7948 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7948 2023/06/05 11:47:33 - mmengine - INFO - Epoch(train) [102][ 780/2569] lr: 4.0000e-03 eta: 9:14:21 time: 0.2600 data_time: 0.0075 memory: 5828 grad_norm: 3.2828 loss: 2.2646 top1_acc: 0.0000 top5_acc: 0.5000 loss_cls: 2.2646 2023/06/05 11:47:38 - mmengine - INFO - Epoch(train) [102][ 800/2569] lr: 4.0000e-03 eta: 9:14:16 time: 0.2607 data_time: 0.0075 memory: 5828 grad_norm: 3.2787 loss: 1.7191 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7191 2023/06/05 11:47:43 - mmengine - INFO - Epoch(train) [102][ 820/2569] lr: 4.0000e-03 eta: 9:14:10 time: 0.2609 data_time: 0.0072 memory: 5828 grad_norm: 3.2805 loss: 2.0553 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0553 2023/06/05 11:47:49 - mmengine - INFO - Epoch(train) [102][ 840/2569] lr: 4.0000e-03 eta: 9:14:05 time: 0.2823 data_time: 0.0072 memory: 5828 grad_norm: 3.2794 loss: 1.8342 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8342 2023/06/05 11:47:54 - mmengine - INFO - Epoch(train) [102][ 860/2569] lr: 4.0000e-03 eta: 9:14:00 time: 0.2692 data_time: 0.0076 memory: 5828 grad_norm: 3.2843 loss: 2.0975 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0975 2023/06/05 11:48:00 - mmengine - INFO - Epoch(train) [102][ 880/2569] lr: 4.0000e-03 eta: 9:13:55 time: 0.2772 data_time: 0.0073 memory: 5828 grad_norm: 3.3398 loss: 2.1989 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.1989 2023/06/05 11:48:05 - mmengine - INFO - Epoch(train) [102][ 900/2569] lr: 4.0000e-03 eta: 9:13:49 time: 0.2607 data_time: 0.0074 memory: 5828 grad_norm: 3.2788 loss: 1.6753 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6753 2023/06/05 11:48:10 - mmengine - INFO - Epoch(train) [102][ 920/2569] lr: 4.0000e-03 eta: 9:13:44 time: 0.2655 data_time: 0.0080 memory: 5828 grad_norm: 3.2421 loss: 1.9330 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9330 2023/06/05 11:48:15 - mmengine - INFO - Epoch(train) [102][ 940/2569] lr: 4.0000e-03 eta: 9:13:39 time: 0.2634 data_time: 0.0079 memory: 5828 grad_norm: 3.2483 loss: 1.8655 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8655 2023/06/05 11:48:21 - mmengine - INFO - Epoch(train) [102][ 960/2569] lr: 4.0000e-03 eta: 9:13:33 time: 0.2652 data_time: 0.0074 memory: 5828 grad_norm: 3.2918 loss: 2.2673 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2673 2023/06/05 11:48:26 - mmengine - INFO - Epoch(train) [102][ 980/2569] lr: 4.0000e-03 eta: 9:13:28 time: 0.2730 data_time: 0.0072 memory: 5828 grad_norm: 3.3002 loss: 1.7853 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7853 2023/06/05 11:48:32 - mmengine - INFO - Epoch(train) [102][1000/2569] lr: 4.0000e-03 eta: 9:13:23 time: 0.2668 data_time: 0.0074 memory: 5828 grad_norm: 3.3408 loss: 2.1334 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1334 2023/06/05 11:48:37 - mmengine - INFO - Epoch(train) [102][1020/2569] lr: 4.0000e-03 eta: 9:13:18 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 3.2730 loss: 2.0520 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0520 2023/06/05 11:48:42 - mmengine - INFO - Epoch(train) [102][1040/2569] lr: 4.0000e-03 eta: 9:13:12 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 3.2705 loss: 1.8920 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8920 2023/06/05 11:48:48 - mmengine - INFO - Epoch(train) [102][1060/2569] lr: 4.0000e-03 eta: 9:13:07 time: 0.2820 data_time: 0.0077 memory: 5828 grad_norm: 3.3048 loss: 1.6584 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6584 2023/06/05 11:48:53 - mmengine - INFO - Epoch(train) [102][1080/2569] lr: 4.0000e-03 eta: 9:13:02 time: 0.2712 data_time: 0.0075 memory: 5828 grad_norm: 3.2694 loss: 2.1602 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.1602 2023/06/05 11:48:59 - mmengine - INFO - Epoch(train) [102][1100/2569] lr: 4.0000e-03 eta: 9:12:57 time: 0.2740 data_time: 0.0070 memory: 5828 grad_norm: 3.3345 loss: 2.0341 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0341 2023/06/05 11:49:04 - mmengine - INFO - Epoch(train) [102][1120/2569] lr: 4.0000e-03 eta: 9:12:51 time: 0.2605 data_time: 0.0071 memory: 5828 grad_norm: 3.3148 loss: 1.9728 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9728 2023/06/05 11:49:09 - mmengine - INFO - Epoch(train) [102][1140/2569] lr: 4.0000e-03 eta: 9:12:46 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 3.2728 loss: 2.0598 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0598 2023/06/05 11:49:14 - mmengine - INFO - Epoch(train) [102][1160/2569] lr: 4.0000e-03 eta: 9:12:40 time: 0.2600 data_time: 0.0072 memory: 5828 grad_norm: 3.3462 loss: 1.8734 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8734 2023/06/05 11:49:20 - mmengine - INFO - Epoch(train) [102][1180/2569] lr: 4.0000e-03 eta: 9:12:35 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 3.3146 loss: 2.1617 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1617 2023/06/05 11:49:25 - mmengine - INFO - Epoch(train) [102][1200/2569] lr: 4.0000e-03 eta: 9:12:30 time: 0.2703 data_time: 0.0076 memory: 5828 grad_norm: 3.3238 loss: 1.8120 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8120 2023/06/05 11:49:30 - mmengine - INFO - Epoch(train) [102][1220/2569] lr: 4.0000e-03 eta: 9:12:25 time: 0.2690 data_time: 0.0073 memory: 5828 grad_norm: 3.2895 loss: 1.7416 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7416 2023/06/05 11:49:36 - mmengine - INFO - Epoch(train) [102][1240/2569] lr: 4.0000e-03 eta: 9:12:19 time: 0.2633 data_time: 0.0078 memory: 5828 grad_norm: 3.2656 loss: 1.9103 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.9103 2023/06/05 11:49:41 - mmengine - INFO - Epoch(train) [102][1260/2569] lr: 4.0000e-03 eta: 9:12:14 time: 0.2591 data_time: 0.0075 memory: 5828 grad_norm: 3.3240 loss: 1.9522 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9522 2023/06/05 11:49:46 - mmengine - INFO - Epoch(train) [102][1280/2569] lr: 4.0000e-03 eta: 9:12:08 time: 0.2626 data_time: 0.0071 memory: 5828 grad_norm: 3.3022 loss: 2.0331 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0331 2023/06/05 11:49:52 - mmengine - INFO - Epoch(train) [102][1300/2569] lr: 4.0000e-03 eta: 9:12:03 time: 0.2675 data_time: 0.0071 memory: 5828 grad_norm: 3.2699 loss: 2.1938 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1938 2023/06/05 11:49:57 - mmengine - INFO - Epoch(train) [102][1320/2569] lr: 4.0000e-03 eta: 9:11:58 time: 0.2649 data_time: 0.0070 memory: 5828 grad_norm: 3.3706 loss: 2.0258 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0258 2023/06/05 11:50:02 - mmengine - INFO - Epoch(train) [102][1340/2569] lr: 4.0000e-03 eta: 9:11:53 time: 0.2676 data_time: 0.0071 memory: 5828 grad_norm: 3.2881 loss: 2.1722 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1722 2023/06/05 11:50:07 - mmengine - INFO - Epoch(train) [102][1360/2569] lr: 4.0000e-03 eta: 9:11:47 time: 0.2607 data_time: 0.0075 memory: 5828 grad_norm: 3.2797 loss: 1.9657 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9657 2023/06/05 11:50:13 - mmengine - INFO - Epoch(train) [102][1380/2569] lr: 4.0000e-03 eta: 9:11:42 time: 0.2676 data_time: 0.0068 memory: 5828 grad_norm: 3.2925 loss: 2.4104 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.4104 2023/06/05 11:50:18 - mmengine - INFO - Epoch(train) [102][1400/2569] lr: 4.0000e-03 eta: 9:11:37 time: 0.2682 data_time: 0.0071 memory: 5828 grad_norm: 3.3470 loss: 1.8149 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8149 2023/06/05 11:50:24 - mmengine - INFO - Epoch(train) [102][1420/2569] lr: 4.0000e-03 eta: 9:11:31 time: 0.2691 data_time: 0.0076 memory: 5828 grad_norm: 3.3458 loss: 2.1137 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1137 2023/06/05 11:50:29 - mmengine - INFO - Epoch(train) [102][1440/2569] lr: 4.0000e-03 eta: 9:11:26 time: 0.2738 data_time: 0.0071 memory: 5828 grad_norm: 3.3028 loss: 1.7741 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7741 2023/06/05 11:50:34 - mmengine - INFO - Epoch(train) [102][1460/2569] lr: 4.0000e-03 eta: 9:11:21 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 3.2637 loss: 1.8927 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8927 2023/06/05 11:50:40 - mmengine - INFO - Epoch(train) [102][1480/2569] lr: 4.0000e-03 eta: 9:11:15 time: 0.2713 data_time: 0.0079 memory: 5828 grad_norm: 3.3403 loss: 2.0342 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0342 2023/06/05 11:50:45 - mmengine - INFO - Epoch(train) [102][1500/2569] lr: 4.0000e-03 eta: 9:11:10 time: 0.2685 data_time: 0.0071 memory: 5828 grad_norm: 3.2504 loss: 1.9827 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9827 2023/06/05 11:50:50 - mmengine - INFO - Epoch(train) [102][1520/2569] lr: 4.0000e-03 eta: 9:11:05 time: 0.2599 data_time: 0.0068 memory: 5828 grad_norm: 3.3361 loss: 1.9169 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9169 2023/06/05 11:50:54 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:50:56 - mmengine - INFO - Epoch(train) [102][1540/2569] lr: 4.0000e-03 eta: 9:11:00 time: 0.2739 data_time: 0.0070 memory: 5828 grad_norm: 3.3239 loss: 2.2628 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.2628 2023/06/05 11:51:01 - mmengine - INFO - Epoch(train) [102][1560/2569] lr: 4.0000e-03 eta: 9:10:54 time: 0.2653 data_time: 0.0073 memory: 5828 grad_norm: 3.3094 loss: 1.8345 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8345 2023/06/05 11:51:07 - mmengine - INFO - Epoch(train) [102][1580/2569] lr: 4.0000e-03 eta: 9:10:49 time: 0.2610 data_time: 0.0073 memory: 5828 grad_norm: 3.3444 loss: 2.0583 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0583 2023/06/05 11:51:12 - mmengine - INFO - Epoch(train) [102][1600/2569] lr: 4.0000e-03 eta: 9:10:44 time: 0.2656 data_time: 0.0076 memory: 5828 grad_norm: 3.3393 loss: 2.0918 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0918 2023/06/05 11:51:17 - mmengine - INFO - Epoch(train) [102][1620/2569] lr: 4.0000e-03 eta: 9:10:38 time: 0.2814 data_time: 0.0074 memory: 5828 grad_norm: 3.2961 loss: 2.1272 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1272 2023/06/05 11:51:23 - mmengine - INFO - Epoch(train) [102][1640/2569] lr: 4.0000e-03 eta: 9:10:33 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 3.3350 loss: 1.8272 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8272 2023/06/05 11:51:28 - mmengine - INFO - Epoch(train) [102][1660/2569] lr: 4.0000e-03 eta: 9:10:28 time: 0.2707 data_time: 0.0080 memory: 5828 grad_norm: 3.3097 loss: 1.8032 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8032 2023/06/05 11:51:34 - mmengine - INFO - Epoch(train) [102][1680/2569] lr: 4.0000e-03 eta: 9:10:22 time: 0.2647 data_time: 0.0083 memory: 5828 grad_norm: 3.3199 loss: 1.8800 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8800 2023/06/05 11:51:39 - mmengine - INFO - Epoch(train) [102][1700/2569] lr: 4.0000e-03 eta: 9:10:17 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 3.3382 loss: 2.1767 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1767 2023/06/05 11:51:44 - mmengine - INFO - Epoch(train) [102][1720/2569] lr: 4.0000e-03 eta: 9:10:12 time: 0.2723 data_time: 0.0075 memory: 5828 grad_norm: 3.3100 loss: 1.7040 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7040 2023/06/05 11:51:49 - mmengine - INFO - Epoch(train) [102][1740/2569] lr: 4.0000e-03 eta: 9:10:07 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 3.2633 loss: 1.9038 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9038 2023/06/05 11:51:55 - mmengine - INFO - Epoch(train) [102][1760/2569] lr: 4.0000e-03 eta: 9:10:01 time: 0.2731 data_time: 0.0075 memory: 5828 grad_norm: 3.3203 loss: 1.8920 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8920 2023/06/05 11:52:00 - mmengine - INFO - Epoch(train) [102][1780/2569] lr: 4.0000e-03 eta: 9:09:56 time: 0.2609 data_time: 0.0073 memory: 5828 grad_norm: 3.3160 loss: 1.9867 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9867 2023/06/05 11:52:06 - mmengine - INFO - Epoch(train) [102][1800/2569] lr: 4.0000e-03 eta: 9:09:51 time: 0.2720 data_time: 0.0072 memory: 5828 grad_norm: 3.3640 loss: 2.1755 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1755 2023/06/05 11:52:11 - mmengine - INFO - Epoch(train) [102][1820/2569] lr: 4.0000e-03 eta: 9:09:45 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.3268 loss: 1.9737 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9737 2023/06/05 11:52:16 - mmengine - INFO - Epoch(train) [102][1840/2569] lr: 4.0000e-03 eta: 9:09:40 time: 0.2626 data_time: 0.0069 memory: 5828 grad_norm: 3.4231 loss: 1.8601 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8601 2023/06/05 11:52:21 - mmengine - INFO - Epoch(train) [102][1860/2569] lr: 4.0000e-03 eta: 9:09:35 time: 0.2597 data_time: 0.0074 memory: 5828 grad_norm: 3.3179 loss: 1.9158 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9158 2023/06/05 11:52:27 - mmengine - INFO - Epoch(train) [102][1880/2569] lr: 4.0000e-03 eta: 9:09:29 time: 0.2655 data_time: 0.0078 memory: 5828 grad_norm: 3.3275 loss: 2.0391 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0391 2023/06/05 11:52:32 - mmengine - INFO - Epoch(train) [102][1900/2569] lr: 4.0000e-03 eta: 9:09:24 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 3.3474 loss: 1.7835 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7835 2023/06/05 11:52:37 - mmengine - INFO - Epoch(train) [102][1920/2569] lr: 4.0000e-03 eta: 9:09:19 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 3.3722 loss: 1.8132 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8132 2023/06/05 11:52:43 - mmengine - INFO - Epoch(train) [102][1940/2569] lr: 4.0000e-03 eta: 9:09:13 time: 0.2626 data_time: 0.0072 memory: 5828 grad_norm: 3.3839 loss: 2.2229 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.2229 2023/06/05 11:52:48 - mmengine - INFO - Epoch(train) [102][1960/2569] lr: 4.0000e-03 eta: 9:09:08 time: 0.2714 data_time: 0.0074 memory: 5828 grad_norm: 3.3376 loss: 1.9848 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9848 2023/06/05 11:52:53 - mmengine - INFO - Epoch(train) [102][1980/2569] lr: 4.0000e-03 eta: 9:09:03 time: 0.2611 data_time: 0.0069 memory: 5828 grad_norm: 3.3586 loss: 2.2741 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2741 2023/06/05 11:52:58 - mmengine - INFO - Epoch(train) [102][2000/2569] lr: 4.0000e-03 eta: 9:08:57 time: 0.2605 data_time: 0.0070 memory: 5828 grad_norm: 3.3746 loss: 2.4700 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.4700 2023/06/05 11:53:04 - mmengine - INFO - Epoch(train) [102][2020/2569] lr: 4.0000e-03 eta: 9:08:52 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 3.2802 loss: 1.9777 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9777 2023/06/05 11:53:09 - mmengine - INFO - Epoch(train) [102][2040/2569] lr: 4.0000e-03 eta: 9:08:47 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 3.3479 loss: 1.7528 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7528 2023/06/05 11:53:14 - mmengine - INFO - Epoch(train) [102][2060/2569] lr: 4.0000e-03 eta: 9:08:41 time: 0.2602 data_time: 0.0072 memory: 5828 grad_norm: 3.3655 loss: 1.6982 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.6982 2023/06/05 11:53:19 - mmengine - INFO - Epoch(train) [102][2080/2569] lr: 4.0000e-03 eta: 9:08:36 time: 0.2594 data_time: 0.0070 memory: 5828 grad_norm: 3.3975 loss: 2.1370 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1370 2023/06/05 11:53:25 - mmengine - INFO - Epoch(train) [102][2100/2569] lr: 4.0000e-03 eta: 9:08:30 time: 0.2637 data_time: 0.0069 memory: 5828 grad_norm: 3.3754 loss: 2.0317 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0317 2023/06/05 11:53:30 - mmengine - INFO - Epoch(train) [102][2120/2569] lr: 4.0000e-03 eta: 9:08:25 time: 0.2684 data_time: 0.0075 memory: 5828 grad_norm: 3.2968 loss: 1.9143 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9143 2023/06/05 11:53:35 - mmengine - INFO - Epoch(train) [102][2140/2569] lr: 4.0000e-03 eta: 9:08:20 time: 0.2613 data_time: 0.0075 memory: 5828 grad_norm: 3.3715 loss: 1.8419 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8419 2023/06/05 11:53:41 - mmengine - INFO - Epoch(train) [102][2160/2569] lr: 4.0000e-03 eta: 9:08:15 time: 0.2772 data_time: 0.0074 memory: 5828 grad_norm: 3.3516 loss: 2.2548 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2548 2023/06/05 11:53:46 - mmengine - INFO - Epoch(train) [102][2180/2569] lr: 4.0000e-03 eta: 9:08:09 time: 0.2646 data_time: 0.0069 memory: 5828 grad_norm: 3.3381 loss: 1.8540 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8540 2023/06/05 11:53:52 - mmengine - INFO - Epoch(train) [102][2200/2569] lr: 4.0000e-03 eta: 9:08:04 time: 0.2776 data_time: 0.0071 memory: 5828 grad_norm: 3.3801 loss: 1.8671 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8671 2023/06/05 11:53:57 - mmengine - INFO - Epoch(train) [102][2220/2569] lr: 4.0000e-03 eta: 9:07:59 time: 0.2662 data_time: 0.0079 memory: 5828 grad_norm: 3.4129 loss: 1.9609 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9609 2023/06/05 11:54:02 - mmengine - INFO - Epoch(train) [102][2240/2569] lr: 4.0000e-03 eta: 9:07:53 time: 0.2651 data_time: 0.0080 memory: 5828 grad_norm: 3.3200 loss: 2.2369 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2369 2023/06/05 11:54:08 - mmengine - INFO - Epoch(train) [102][2260/2569] lr: 4.0000e-03 eta: 9:07:48 time: 0.2611 data_time: 0.0083 memory: 5828 grad_norm: 3.3606 loss: 2.0160 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0160 2023/06/05 11:54:13 - mmengine - INFO - Epoch(train) [102][2280/2569] lr: 4.0000e-03 eta: 9:07:43 time: 0.2663 data_time: 0.0070 memory: 5828 grad_norm: 3.3504 loss: 1.9567 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9567 2023/06/05 11:54:19 - mmengine - INFO - Epoch(train) [102][2300/2569] lr: 4.0000e-03 eta: 9:07:38 time: 0.2812 data_time: 0.0073 memory: 5828 grad_norm: 3.3484 loss: 1.9748 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9748 2023/06/05 11:54:24 - mmengine - INFO - Epoch(train) [102][2320/2569] lr: 4.0000e-03 eta: 9:07:32 time: 0.2717 data_time: 0.0077 memory: 5828 grad_norm: 3.3480 loss: 2.0541 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0541 2023/06/05 11:54:29 - mmengine - INFO - Epoch(train) [102][2340/2569] lr: 4.0000e-03 eta: 9:07:27 time: 0.2683 data_time: 0.0079 memory: 5828 grad_norm: 3.3755 loss: 2.1743 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1743 2023/06/05 11:54:35 - mmengine - INFO - Epoch(train) [102][2360/2569] lr: 4.0000e-03 eta: 9:07:22 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 3.3341 loss: 2.0856 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0856 2023/06/05 11:54:40 - mmengine - INFO - Epoch(train) [102][2380/2569] lr: 4.0000e-03 eta: 9:07:16 time: 0.2706 data_time: 0.0073 memory: 5828 grad_norm: 3.3180 loss: 1.7389 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7389 2023/06/05 11:54:45 - mmengine - INFO - Epoch(train) [102][2400/2569] lr: 4.0000e-03 eta: 9:07:11 time: 0.2659 data_time: 0.0073 memory: 5828 grad_norm: 3.3840 loss: 1.8795 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.8795 2023/06/05 11:54:51 - mmengine - INFO - Epoch(train) [102][2420/2569] lr: 4.0000e-03 eta: 9:07:06 time: 0.2785 data_time: 0.0074 memory: 5828 grad_norm: 3.3587 loss: 1.8222 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8222 2023/06/05 11:54:56 - mmengine - INFO - Epoch(train) [102][2440/2569] lr: 4.0000e-03 eta: 9:07:01 time: 0.2609 data_time: 0.0079 memory: 5828 grad_norm: 3.3701 loss: 1.8874 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8874 2023/06/05 11:55:01 - mmengine - INFO - Epoch(train) [102][2460/2569] lr: 4.0000e-03 eta: 9:06:55 time: 0.2646 data_time: 0.0071 memory: 5828 grad_norm: 3.3419 loss: 2.0128 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0128 2023/06/05 11:55:07 - mmengine - INFO - Epoch(train) [102][2480/2569] lr: 4.0000e-03 eta: 9:06:50 time: 0.2630 data_time: 0.0073 memory: 5828 grad_norm: 3.3364 loss: 2.0096 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.0096 2023/06/05 11:55:12 - mmengine - INFO - Epoch(train) [102][2500/2569] lr: 4.0000e-03 eta: 9:06:44 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 3.3585 loss: 2.0364 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.0364 2023/06/05 11:55:17 - mmengine - INFO - Epoch(train) [102][2520/2569] lr: 4.0000e-03 eta: 9:06:39 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 3.4402 loss: 2.0559 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0559 2023/06/05 11:55:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:55:23 - mmengine - INFO - Epoch(train) [102][2540/2569] lr: 4.0000e-03 eta: 9:06:34 time: 0.2673 data_time: 0.0066 memory: 5828 grad_norm: 3.3984 loss: 1.9576 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9576 2023/06/05 11:55:28 - mmengine - INFO - Epoch(train) [102][2560/2569] lr: 4.0000e-03 eta: 9:06:28 time: 0.2615 data_time: 0.0071 memory: 5828 grad_norm: 3.3402 loss: 1.9141 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9141 2023/06/05 11:55:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:55:30 - mmengine - INFO - Epoch(train) [102][2569/2569] lr: 4.0000e-03 eta: 9:06:26 time: 0.2554 data_time: 0.0069 memory: 5828 grad_norm: 3.3686 loss: 2.0204 top1_acc: 0.3333 top5_acc: 0.6667 loss_cls: 2.0204 2023/06/05 11:55:37 - mmengine - INFO - Epoch(train) [103][ 20/2569] lr: 4.0000e-03 eta: 9:06:21 time: 0.3375 data_time: 0.0456 memory: 5828 grad_norm: 3.2698 loss: 1.9109 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9109 2023/06/05 11:55:42 - mmengine - INFO - Epoch(train) [103][ 40/2569] lr: 4.0000e-03 eta: 9:06:16 time: 0.2738 data_time: 0.0076 memory: 5828 grad_norm: 3.3218 loss: 2.0767 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0767 2023/06/05 11:55:48 - mmengine - INFO - Epoch(train) [103][ 60/2569] lr: 4.0000e-03 eta: 9:06:11 time: 0.2653 data_time: 0.0071 memory: 5828 grad_norm: 3.3057 loss: 1.9034 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9034 2023/06/05 11:55:53 - mmengine - INFO - Epoch(train) [103][ 80/2569] lr: 4.0000e-03 eta: 9:06:05 time: 0.2675 data_time: 0.0072 memory: 5828 grad_norm: 3.3476 loss: 2.0537 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0537 2023/06/05 11:55:58 - mmengine - INFO - Epoch(train) [103][ 100/2569] lr: 4.0000e-03 eta: 9:06:00 time: 0.2627 data_time: 0.0079 memory: 5828 grad_norm: 3.3988 loss: 1.9635 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.9635 2023/06/05 11:56:04 - mmengine - INFO - Epoch(train) [103][ 120/2569] lr: 4.0000e-03 eta: 9:05:55 time: 0.2700 data_time: 0.0069 memory: 5828 grad_norm: 3.3606 loss: 2.0435 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0435 2023/06/05 11:56:09 - mmengine - INFO - Epoch(train) [103][ 140/2569] lr: 4.0000e-03 eta: 9:05:50 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 3.3627 loss: 1.7870 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7870 2023/06/05 11:56:14 - mmengine - INFO - Epoch(train) [103][ 160/2569] lr: 4.0000e-03 eta: 9:05:44 time: 0.2596 data_time: 0.0072 memory: 5828 grad_norm: 3.3683 loss: 1.8191 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8191 2023/06/05 11:56:19 - mmengine - INFO - Epoch(train) [103][ 180/2569] lr: 4.0000e-03 eta: 9:05:39 time: 0.2629 data_time: 0.0071 memory: 5828 grad_norm: 3.4289 loss: 1.9431 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9431 2023/06/05 11:56:25 - mmengine - INFO - Epoch(train) [103][ 200/2569] lr: 4.0000e-03 eta: 9:05:33 time: 0.2662 data_time: 0.0072 memory: 5828 grad_norm: 3.3421 loss: 1.8108 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8108 2023/06/05 11:56:30 - mmengine - INFO - Epoch(train) [103][ 220/2569] lr: 4.0000e-03 eta: 9:05:28 time: 0.2698 data_time: 0.0073 memory: 5828 grad_norm: 3.3678 loss: 2.2748 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2748 2023/06/05 11:56:36 - mmengine - INFO - Epoch(train) [103][ 240/2569] lr: 4.0000e-03 eta: 9:05:23 time: 0.2718 data_time: 0.0070 memory: 5828 grad_norm: 3.3867 loss: 2.1584 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1584 2023/06/05 11:56:41 - mmengine - INFO - Epoch(train) [103][ 260/2569] lr: 4.0000e-03 eta: 9:05:18 time: 0.2684 data_time: 0.0068 memory: 5828 grad_norm: 3.3316 loss: 2.2673 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2673 2023/06/05 11:56:46 - mmengine - INFO - Epoch(train) [103][ 280/2569] lr: 4.0000e-03 eta: 9:05:12 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 3.3410 loss: 2.0424 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0424 2023/06/05 11:56:51 - mmengine - INFO - Epoch(train) [103][ 300/2569] lr: 4.0000e-03 eta: 9:05:07 time: 0.2608 data_time: 0.0069 memory: 5828 grad_norm: 3.3703 loss: 2.1912 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1912 2023/06/05 11:56:57 - mmengine - INFO - Epoch(train) [103][ 320/2569] lr: 4.0000e-03 eta: 9:05:02 time: 0.2668 data_time: 0.0069 memory: 5828 grad_norm: 3.3991 loss: 1.9400 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9400 2023/06/05 11:57:02 - mmengine - INFO - Epoch(train) [103][ 340/2569] lr: 4.0000e-03 eta: 9:04:56 time: 0.2669 data_time: 0.0071 memory: 5828 grad_norm: 3.3306 loss: 1.9689 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9689 2023/06/05 11:57:07 - mmengine - INFO - Epoch(train) [103][ 360/2569] lr: 4.0000e-03 eta: 9:04:51 time: 0.2592 data_time: 0.0075 memory: 5828 grad_norm: 3.3324 loss: 1.9479 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9479 2023/06/05 11:57:13 - mmengine - INFO - Epoch(train) [103][ 380/2569] lr: 4.0000e-03 eta: 9:04:46 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 3.4053 loss: 1.9162 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9162 2023/06/05 11:57:18 - mmengine - INFO - Epoch(train) [103][ 400/2569] lr: 4.0000e-03 eta: 9:04:40 time: 0.2678 data_time: 0.0072 memory: 5828 grad_norm: 3.3898 loss: 2.2418 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2418 2023/06/05 11:57:23 - mmengine - INFO - Epoch(train) [103][ 420/2569] lr: 4.0000e-03 eta: 9:04:35 time: 0.2613 data_time: 0.0072 memory: 5828 grad_norm: 3.3961 loss: 2.0425 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0425 2023/06/05 11:57:29 - mmengine - INFO - Epoch(train) [103][ 440/2569] lr: 4.0000e-03 eta: 9:04:30 time: 0.2650 data_time: 0.0073 memory: 5828 grad_norm: 3.4114 loss: 1.9564 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9564 2023/06/05 11:57:34 - mmengine - INFO - Epoch(train) [103][ 460/2569] lr: 4.0000e-03 eta: 9:04:24 time: 0.2625 data_time: 0.0071 memory: 5828 grad_norm: 3.4152 loss: 1.9086 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.9086 2023/06/05 11:57:39 - mmengine - INFO - Epoch(train) [103][ 480/2569] lr: 4.0000e-03 eta: 9:04:19 time: 0.2715 data_time: 0.0071 memory: 5828 grad_norm: 3.4246 loss: 1.9567 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9567 2023/06/05 11:57:45 - mmengine - INFO - Epoch(train) [103][ 500/2569] lr: 4.0000e-03 eta: 9:04:14 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 3.4388 loss: 1.7534 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7534 2023/06/05 11:57:50 - mmengine - INFO - Epoch(train) [103][ 520/2569] lr: 4.0000e-03 eta: 9:04:08 time: 0.2721 data_time: 0.0069 memory: 5828 grad_norm: 3.4161 loss: 1.7397 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7397 2023/06/05 11:57:55 - mmengine - INFO - Epoch(train) [103][ 540/2569] lr: 4.0000e-03 eta: 9:04:03 time: 0.2613 data_time: 0.0070 memory: 5828 grad_norm: 3.3547 loss: 2.0393 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0393 2023/06/05 11:58:01 - mmengine - INFO - Epoch(train) [103][ 560/2569] lr: 4.0000e-03 eta: 9:03:58 time: 0.2602 data_time: 0.0071 memory: 5828 grad_norm: 3.3477 loss: 2.2211 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2211 2023/06/05 11:58:06 - mmengine - INFO - Epoch(train) [103][ 580/2569] lr: 4.0000e-03 eta: 9:03:52 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 3.4077 loss: 1.9937 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9937 2023/06/05 11:58:11 - mmengine - INFO - Epoch(train) [103][ 600/2569] lr: 4.0000e-03 eta: 9:03:47 time: 0.2630 data_time: 0.0069 memory: 5828 grad_norm: 3.3575 loss: 1.9538 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9538 2023/06/05 11:58:16 - mmengine - INFO - Epoch(train) [103][ 620/2569] lr: 4.0000e-03 eta: 9:03:42 time: 0.2677 data_time: 0.0069 memory: 5828 grad_norm: 3.3913 loss: 2.1476 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1476 2023/06/05 11:58:22 - mmengine - INFO - Epoch(train) [103][ 640/2569] lr: 4.0000e-03 eta: 9:03:36 time: 0.2652 data_time: 0.0073 memory: 5828 grad_norm: 3.3707 loss: 1.7067 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7067 2023/06/05 11:58:27 - mmengine - INFO - Epoch(train) [103][ 660/2569] lr: 4.0000e-03 eta: 9:03:31 time: 0.2617 data_time: 0.0069 memory: 5828 grad_norm: 3.4193 loss: 2.1357 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1357 2023/06/05 11:58:32 - mmengine - INFO - Epoch(train) [103][ 680/2569] lr: 4.0000e-03 eta: 9:03:26 time: 0.2653 data_time: 0.0070 memory: 5828 grad_norm: 3.3811 loss: 2.0791 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0791 2023/06/05 11:58:38 - mmengine - INFO - Epoch(train) [103][ 700/2569] lr: 4.0000e-03 eta: 9:03:20 time: 0.2627 data_time: 0.0070 memory: 5828 grad_norm: 3.3928 loss: 2.3497 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3497 2023/06/05 11:58:43 - mmengine - INFO - Epoch(train) [103][ 720/2569] lr: 4.0000e-03 eta: 9:03:15 time: 0.2614 data_time: 0.0069 memory: 5828 grad_norm: 3.3683 loss: 2.1558 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1558 2023/06/05 11:58:48 - mmengine - INFO - Epoch(train) [103][ 740/2569] lr: 4.0000e-03 eta: 9:03:10 time: 0.2652 data_time: 0.0069 memory: 5828 grad_norm: 3.3796 loss: 1.8957 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8957 2023/06/05 11:58:54 - mmengine - INFO - Epoch(train) [103][ 760/2569] lr: 4.0000e-03 eta: 9:03:04 time: 0.2767 data_time: 0.0070 memory: 5828 grad_norm: 3.4047 loss: 1.5279 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.5279 2023/06/05 11:58:59 - mmengine - INFO - Epoch(train) [103][ 780/2569] lr: 4.0000e-03 eta: 9:02:59 time: 0.2657 data_time: 0.0072 memory: 5828 grad_norm: 3.3922 loss: 2.0635 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0635 2023/06/05 11:59:04 - mmengine - INFO - Epoch(train) [103][ 800/2569] lr: 4.0000e-03 eta: 9:02:54 time: 0.2676 data_time: 0.0074 memory: 5828 grad_norm: 3.4015 loss: 1.7672 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7672 2023/06/05 11:59:10 - mmengine - INFO - Epoch(train) [103][ 820/2569] lr: 4.0000e-03 eta: 9:02:49 time: 0.2773 data_time: 0.0073 memory: 5828 grad_norm: 3.3732 loss: 1.9268 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9268 2023/06/05 11:59:15 - mmengine - INFO - Epoch(train) [103][ 840/2569] lr: 4.0000e-03 eta: 9:02:43 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 3.3325 loss: 1.7873 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7873 2023/06/05 11:59:20 - mmengine - INFO - Epoch(train) [103][ 860/2569] lr: 4.0000e-03 eta: 9:02:38 time: 0.2655 data_time: 0.0078 memory: 5828 grad_norm: 3.4196 loss: 1.7638 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7638 2023/06/05 11:59:26 - mmengine - INFO - Epoch(train) [103][ 880/2569] lr: 4.0000e-03 eta: 9:02:33 time: 0.2696 data_time: 0.0073 memory: 5828 grad_norm: 3.3722 loss: 1.9405 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9405 2023/06/05 11:59:31 - mmengine - INFO - Epoch(train) [103][ 900/2569] lr: 4.0000e-03 eta: 9:02:27 time: 0.2609 data_time: 0.0070 memory: 5828 grad_norm: 3.4434 loss: 2.0141 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0141 2023/06/05 11:59:36 - mmengine - INFO - Epoch(train) [103][ 920/2569] lr: 4.0000e-03 eta: 9:02:22 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 3.4522 loss: 1.9986 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9986 2023/06/05 11:59:42 - mmengine - INFO - Epoch(train) [103][ 940/2569] lr: 4.0000e-03 eta: 9:02:17 time: 0.2712 data_time: 0.0071 memory: 5828 grad_norm: 3.3892 loss: 2.0276 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0276 2023/06/05 11:59:47 - mmengine - INFO - Epoch(train) [103][ 960/2569] lr: 4.0000e-03 eta: 9:02:11 time: 0.2773 data_time: 0.0071 memory: 5828 grad_norm: 3.3587 loss: 2.0096 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0096 2023/06/05 11:59:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 11:59:53 - mmengine - INFO - Epoch(train) [103][ 980/2569] lr: 4.0000e-03 eta: 9:02:06 time: 0.2770 data_time: 0.0073 memory: 5828 grad_norm: 3.4226 loss: 1.8290 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8290 2023/06/05 11:59:58 - mmengine - INFO - Epoch(train) [103][1000/2569] lr: 4.0000e-03 eta: 9:02:01 time: 0.2750 data_time: 0.0075 memory: 5828 grad_norm: 3.3725 loss: 2.2552 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2552 2023/06/05 12:00:04 - mmengine - INFO - Epoch(train) [103][1020/2569] lr: 4.0000e-03 eta: 9:01:56 time: 0.2616 data_time: 0.0070 memory: 5828 grad_norm: 3.3995 loss: 1.8529 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8529 2023/06/05 12:00:09 - mmengine - INFO - Epoch(train) [103][1040/2569] lr: 4.0000e-03 eta: 9:01:50 time: 0.2670 data_time: 0.0075 memory: 5828 grad_norm: 3.3833 loss: 1.8914 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8914 2023/06/05 12:00:14 - mmengine - INFO - Epoch(train) [103][1060/2569] lr: 4.0000e-03 eta: 9:01:45 time: 0.2686 data_time: 0.0070 memory: 5828 grad_norm: 3.4754 loss: 2.2485 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2485 2023/06/05 12:00:20 - mmengine - INFO - Epoch(train) [103][1080/2569] lr: 4.0000e-03 eta: 9:01:40 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 3.4315 loss: 2.0717 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0717 2023/06/05 12:00:25 - mmengine - INFO - Epoch(train) [103][1100/2569] lr: 4.0000e-03 eta: 9:01:34 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 3.4325 loss: 2.2115 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2115 2023/06/05 12:00:30 - mmengine - INFO - Epoch(train) [103][1120/2569] lr: 4.0000e-03 eta: 9:01:29 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 3.4145 loss: 1.8903 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8903 2023/06/05 12:00:35 - mmengine - INFO - Epoch(train) [103][1140/2569] lr: 4.0000e-03 eta: 9:01:24 time: 0.2621 data_time: 0.0071 memory: 5828 grad_norm: 3.3867 loss: 1.8673 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8673 2023/06/05 12:00:41 - mmengine - INFO - Epoch(train) [103][1160/2569] lr: 4.0000e-03 eta: 9:01:18 time: 0.2667 data_time: 0.0071 memory: 5828 grad_norm: 3.4916 loss: 2.0569 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0569 2023/06/05 12:00:46 - mmengine - INFO - Epoch(train) [103][1180/2569] lr: 4.0000e-03 eta: 9:01:13 time: 0.2610 data_time: 0.0073 memory: 5828 grad_norm: 3.4469 loss: 2.2532 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2532 2023/06/05 12:00:51 - mmengine - INFO - Epoch(train) [103][1200/2569] lr: 4.0000e-03 eta: 9:01:08 time: 0.2607 data_time: 0.0072 memory: 5828 grad_norm: 3.4347 loss: 2.2400 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2400 2023/06/05 12:00:56 - mmengine - INFO - Epoch(train) [103][1220/2569] lr: 4.0000e-03 eta: 9:01:02 time: 0.2629 data_time: 0.0067 memory: 5828 grad_norm: 3.3986 loss: 1.9502 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9502 2023/06/05 12:01:02 - mmengine - INFO - Epoch(train) [103][1240/2569] lr: 4.0000e-03 eta: 9:00:57 time: 0.2641 data_time: 0.0071 memory: 5828 grad_norm: 3.4565 loss: 2.1444 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1444 2023/06/05 12:01:07 - mmengine - INFO - Epoch(train) [103][1260/2569] lr: 4.0000e-03 eta: 9:00:52 time: 0.2677 data_time: 0.0081 memory: 5828 grad_norm: 3.4119 loss: 1.8885 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8885 2023/06/05 12:01:12 - mmengine - INFO - Epoch(train) [103][1280/2569] lr: 4.0000e-03 eta: 9:00:46 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 3.4643 loss: 2.2503 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2503 2023/06/05 12:01:18 - mmengine - INFO - Epoch(train) [103][1300/2569] lr: 4.0000e-03 eta: 9:00:41 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 3.4362 loss: 2.0142 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0142 2023/06/05 12:01:23 - mmengine - INFO - Epoch(train) [103][1320/2569] lr: 4.0000e-03 eta: 9:00:36 time: 0.2716 data_time: 0.0070 memory: 5828 grad_norm: 3.3645 loss: 2.0419 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0419 2023/06/05 12:01:29 - mmengine - INFO - Epoch(train) [103][1340/2569] lr: 4.0000e-03 eta: 9:00:30 time: 0.2711 data_time: 0.0076 memory: 5828 grad_norm: 3.3873 loss: 2.0369 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0369 2023/06/05 12:01:34 - mmengine - INFO - Epoch(train) [103][1360/2569] lr: 4.0000e-03 eta: 9:00:25 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 3.3535 loss: 1.6264 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6264 2023/06/05 12:01:39 - mmengine - INFO - Epoch(train) [103][1380/2569] lr: 4.0000e-03 eta: 9:00:20 time: 0.2716 data_time: 0.0071 memory: 5828 grad_norm: 3.4399 loss: 1.8483 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8483 2023/06/05 12:01:45 - mmengine - INFO - Epoch(train) [103][1400/2569] lr: 4.0000e-03 eta: 9:00:15 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 3.4165 loss: 2.1336 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1336 2023/06/05 12:01:50 - mmengine - INFO - Epoch(train) [103][1420/2569] lr: 4.0000e-03 eta: 9:00:09 time: 0.2738 data_time: 0.0073 memory: 5828 grad_norm: 3.4473 loss: 2.0500 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0500 2023/06/05 12:01:55 - mmengine - INFO - Epoch(train) [103][1440/2569] lr: 4.0000e-03 eta: 9:00:04 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 3.4770 loss: 1.6807 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6807 2023/06/05 12:02:01 - mmengine - INFO - Epoch(train) [103][1460/2569] lr: 4.0000e-03 eta: 8:59:59 time: 0.2729 data_time: 0.0071 memory: 5828 grad_norm: 3.3588 loss: 1.6643 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6643 2023/06/05 12:02:06 - mmengine - INFO - Epoch(train) [103][1480/2569] lr: 4.0000e-03 eta: 8:59:53 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 3.4130 loss: 1.7871 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7871 2023/06/05 12:02:12 - mmengine - INFO - Epoch(train) [103][1500/2569] lr: 4.0000e-03 eta: 8:59:48 time: 0.2642 data_time: 0.0069 memory: 5828 grad_norm: 3.4607 loss: 2.3231 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.3231 2023/06/05 12:02:17 - mmengine - INFO - Epoch(train) [103][1520/2569] lr: 4.0000e-03 eta: 8:59:43 time: 0.2775 data_time: 0.0074 memory: 5828 grad_norm: 3.3954 loss: 2.3734 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.3734 2023/06/05 12:02:22 - mmengine - INFO - Epoch(train) [103][1540/2569] lr: 4.0000e-03 eta: 8:59:38 time: 0.2669 data_time: 0.0069 memory: 5828 grad_norm: 3.4695 loss: 2.2258 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2258 2023/06/05 12:02:28 - mmengine - INFO - Epoch(train) [103][1560/2569] lr: 4.0000e-03 eta: 8:59:32 time: 0.2842 data_time: 0.0073 memory: 5828 grad_norm: 3.3480 loss: 2.1290 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1290 2023/06/05 12:02:34 - mmengine - INFO - Epoch(train) [103][1580/2569] lr: 4.0000e-03 eta: 8:59:27 time: 0.2684 data_time: 0.0068 memory: 5828 grad_norm: 3.4178 loss: 1.9269 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9269 2023/06/05 12:02:39 - mmengine - INFO - Epoch(train) [103][1600/2569] lr: 4.0000e-03 eta: 8:59:22 time: 0.2788 data_time: 0.0069 memory: 5828 grad_norm: 3.4168 loss: 2.3327 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 2.3327 2023/06/05 12:02:45 - mmengine - INFO - Epoch(train) [103][1620/2569] lr: 4.0000e-03 eta: 8:59:17 time: 0.2721 data_time: 0.0069 memory: 5828 grad_norm: 3.4414 loss: 1.5816 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5816 2023/06/05 12:02:50 - mmengine - INFO - Epoch(train) [103][1640/2569] lr: 4.0000e-03 eta: 8:59:11 time: 0.2798 data_time: 0.0073 memory: 5828 grad_norm: 3.4625 loss: 1.9004 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9004 2023/06/05 12:02:56 - mmengine - INFO - Epoch(train) [103][1660/2569] lr: 4.0000e-03 eta: 8:59:06 time: 0.2709 data_time: 0.0075 memory: 5828 grad_norm: 3.4215 loss: 1.9354 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9354 2023/06/05 12:03:01 - mmengine - INFO - Epoch(train) [103][1680/2569] lr: 4.0000e-03 eta: 8:59:01 time: 0.2604 data_time: 0.0087 memory: 5828 grad_norm: 3.4016 loss: 2.0775 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0775 2023/06/05 12:03:06 - mmengine - INFO - Epoch(train) [103][1700/2569] lr: 4.0000e-03 eta: 8:58:56 time: 0.2748 data_time: 0.0093 memory: 5828 grad_norm: 3.3661 loss: 2.1909 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1909 2023/06/05 12:03:12 - mmengine - INFO - Epoch(train) [103][1720/2569] lr: 4.0000e-03 eta: 8:58:50 time: 0.2661 data_time: 0.0082 memory: 5828 grad_norm: 3.3498 loss: 1.8873 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8873 2023/06/05 12:03:17 - mmengine - INFO - Epoch(train) [103][1740/2569] lr: 4.0000e-03 eta: 8:58:45 time: 0.2671 data_time: 0.0078 memory: 5828 grad_norm: 3.4573 loss: 1.5879 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5879 2023/06/05 12:03:22 - mmengine - INFO - Epoch(train) [103][1760/2569] lr: 4.0000e-03 eta: 8:58:40 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 3.4813 loss: 2.0694 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0694 2023/06/05 12:03:28 - mmengine - INFO - Epoch(train) [103][1780/2569] lr: 4.0000e-03 eta: 8:58:34 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.3615 loss: 2.1009 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.1009 2023/06/05 12:03:33 - mmengine - INFO - Epoch(train) [103][1800/2569] lr: 4.0000e-03 eta: 8:58:29 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 3.4782 loss: 1.9765 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9765 2023/06/05 12:03:38 - mmengine - INFO - Epoch(train) [103][1820/2569] lr: 4.0000e-03 eta: 8:58:24 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 3.4332 loss: 1.7353 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7353 2023/06/05 12:03:44 - mmengine - INFO - Epoch(train) [103][1840/2569] lr: 4.0000e-03 eta: 8:58:18 time: 0.2662 data_time: 0.0071 memory: 5828 grad_norm: 3.4381 loss: 2.1187 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1187 2023/06/05 12:03:49 - mmengine - INFO - Epoch(train) [103][1860/2569] lr: 4.0000e-03 eta: 8:58:13 time: 0.2723 data_time: 0.0068 memory: 5828 grad_norm: 3.4173 loss: 1.9279 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9279 2023/06/05 12:03:54 - mmengine - INFO - Epoch(train) [103][1880/2569] lr: 4.0000e-03 eta: 8:58:08 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 3.4231 loss: 1.6513 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6513 2023/06/05 12:04:00 - mmengine - INFO - Epoch(train) [103][1900/2569] lr: 4.0000e-03 eta: 8:58:03 time: 0.2717 data_time: 0.0072 memory: 5828 grad_norm: 3.4489 loss: 2.1518 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1518 2023/06/05 12:04:05 - mmengine - INFO - Epoch(train) [103][1920/2569] lr: 4.0000e-03 eta: 8:57:57 time: 0.2624 data_time: 0.0071 memory: 5828 grad_norm: 3.4943 loss: 2.1778 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.1778 2023/06/05 12:04:10 - mmengine - INFO - Epoch(train) [103][1940/2569] lr: 4.0000e-03 eta: 8:57:52 time: 0.2601 data_time: 0.0074 memory: 5828 grad_norm: 3.3881 loss: 2.1123 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1123 2023/06/05 12:04:16 - mmengine - INFO - Epoch(train) [103][1960/2569] lr: 4.0000e-03 eta: 8:57:47 time: 0.2774 data_time: 0.0075 memory: 5828 grad_norm: 3.3956 loss: 1.8554 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 1.8554 2023/06/05 12:04:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:04:21 - mmengine - INFO - Epoch(train) [103][1980/2569] lr: 4.0000e-03 eta: 8:57:41 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 3.5521 loss: 1.8748 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8748 2023/06/05 12:04:27 - mmengine - INFO - Epoch(train) [103][2000/2569] lr: 4.0000e-03 eta: 8:57:36 time: 0.2697 data_time: 0.0073 memory: 5828 grad_norm: 3.3836 loss: 1.9427 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9427 2023/06/05 12:04:32 - mmengine - INFO - Epoch(train) [103][2020/2569] lr: 4.0000e-03 eta: 8:57:31 time: 0.2621 data_time: 0.0079 memory: 5828 grad_norm: 3.3894 loss: 1.7704 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7704 2023/06/05 12:04:37 - mmengine - INFO - Epoch(train) [103][2040/2569] lr: 4.0000e-03 eta: 8:57:25 time: 0.2694 data_time: 0.0075 memory: 5828 grad_norm: 3.4134 loss: 2.1653 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1653 2023/06/05 12:04:43 - mmengine - INFO - Epoch(train) [103][2060/2569] lr: 4.0000e-03 eta: 8:57:20 time: 0.2603 data_time: 0.0071 memory: 5828 grad_norm: 3.4468 loss: 1.8205 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8205 2023/06/05 12:04:48 - mmengine - INFO - Epoch(train) [103][2080/2569] lr: 4.0000e-03 eta: 8:57:15 time: 0.2667 data_time: 0.0080 memory: 5828 grad_norm: 3.5057 loss: 1.9068 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9068 2023/06/05 12:04:53 - mmengine - INFO - Epoch(train) [103][2100/2569] lr: 4.0000e-03 eta: 8:57:09 time: 0.2729 data_time: 0.0070 memory: 5828 grad_norm: 3.3987 loss: 1.9042 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9042 2023/06/05 12:04:59 - mmengine - INFO - Epoch(train) [103][2120/2569] lr: 4.0000e-03 eta: 8:57:04 time: 0.2730 data_time: 0.0072 memory: 5828 grad_norm: 3.3617 loss: 1.9923 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9923 2023/06/05 12:05:04 - mmengine - INFO - Epoch(train) [103][2140/2569] lr: 4.0000e-03 eta: 8:56:59 time: 0.2686 data_time: 0.0068 memory: 5828 grad_norm: 3.4295 loss: 2.0574 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0574 2023/06/05 12:05:10 - mmengine - INFO - Epoch(train) [103][2160/2569] lr: 4.0000e-03 eta: 8:56:54 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 3.3620 loss: 2.0723 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0723 2023/06/05 12:05:15 - mmengine - INFO - Epoch(train) [103][2180/2569] lr: 4.0000e-03 eta: 8:56:48 time: 0.2686 data_time: 0.0069 memory: 5828 grad_norm: 3.3960 loss: 1.5418 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5418 2023/06/05 12:05:20 - mmengine - INFO - Epoch(train) [103][2200/2569] lr: 4.0000e-03 eta: 8:56:43 time: 0.2621 data_time: 0.0072 memory: 5828 grad_norm: 3.5218 loss: 1.7665 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7665 2023/06/05 12:05:25 - mmengine - INFO - Epoch(train) [103][2220/2569] lr: 4.0000e-03 eta: 8:56:38 time: 0.2636 data_time: 0.0072 memory: 5828 grad_norm: 3.3805 loss: 1.7374 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7374 2023/06/05 12:05:31 - mmengine - INFO - Epoch(train) [103][2240/2569] lr: 4.0000e-03 eta: 8:56:32 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 3.4608 loss: 1.7119 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7119 2023/06/05 12:05:36 - mmengine - INFO - Epoch(train) [103][2260/2569] lr: 4.0000e-03 eta: 8:56:27 time: 0.2800 data_time: 0.0074 memory: 5828 grad_norm: 3.4231 loss: 1.7662 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7662 2023/06/05 12:05:42 - mmengine - INFO - Epoch(train) [103][2280/2569] lr: 4.0000e-03 eta: 8:56:22 time: 0.2665 data_time: 0.0078 memory: 5828 grad_norm: 3.4507 loss: 2.0428 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0428 2023/06/05 12:05:47 - mmengine - INFO - Epoch(train) [103][2300/2569] lr: 4.0000e-03 eta: 8:56:16 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 3.4714 loss: 2.2718 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2718 2023/06/05 12:05:52 - mmengine - INFO - Epoch(train) [103][2320/2569] lr: 4.0000e-03 eta: 8:56:11 time: 0.2673 data_time: 0.0076 memory: 5828 grad_norm: 3.4339 loss: 1.9178 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9178 2023/06/05 12:05:58 - mmengine - INFO - Epoch(train) [103][2340/2569] lr: 4.0000e-03 eta: 8:56:06 time: 0.2675 data_time: 0.0072 memory: 5828 grad_norm: 3.3870 loss: 2.0398 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0398 2023/06/05 12:06:03 - mmengine - INFO - Epoch(train) [103][2360/2569] lr: 4.0000e-03 eta: 8:56:01 time: 0.2684 data_time: 0.0079 memory: 5828 grad_norm: 3.4751 loss: 1.7456 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7456 2023/06/05 12:06:09 - mmengine - INFO - Epoch(train) [103][2380/2569] lr: 4.0000e-03 eta: 8:55:55 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 3.4235 loss: 2.1808 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.1808 2023/06/05 12:06:14 - mmengine - INFO - Epoch(train) [103][2400/2569] lr: 4.0000e-03 eta: 8:55:50 time: 0.2713 data_time: 0.0074 memory: 5828 grad_norm: 3.4846 loss: 2.1931 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1931 2023/06/05 12:06:19 - mmengine - INFO - Epoch(train) [103][2420/2569] lr: 4.0000e-03 eta: 8:55:45 time: 0.2613 data_time: 0.0073 memory: 5828 grad_norm: 3.4477 loss: 1.9824 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9824 2023/06/05 12:06:25 - mmengine - INFO - Epoch(train) [103][2440/2569] lr: 4.0000e-03 eta: 8:55:39 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 3.4507 loss: 2.1717 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.1717 2023/06/05 12:06:30 - mmengine - INFO - Epoch(train) [103][2460/2569] lr: 4.0000e-03 eta: 8:55:34 time: 0.2599 data_time: 0.0076 memory: 5828 grad_norm: 3.4676 loss: 2.0534 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0534 2023/06/05 12:06:35 - mmengine - INFO - Epoch(train) [103][2480/2569] lr: 4.0000e-03 eta: 8:55:29 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 3.4741 loss: 2.2439 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2439 2023/06/05 12:06:40 - mmengine - INFO - Epoch(train) [103][2500/2569] lr: 4.0000e-03 eta: 8:55:23 time: 0.2718 data_time: 0.0073 memory: 5828 grad_norm: 3.4516 loss: 1.9124 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9124 2023/06/05 12:06:46 - mmengine - INFO - Epoch(train) [103][2520/2569] lr: 4.0000e-03 eta: 8:55:18 time: 0.2663 data_time: 0.0077 memory: 5828 grad_norm: 3.4599 loss: 1.9346 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9346 2023/06/05 12:06:51 - mmengine - INFO - Epoch(train) [103][2540/2569] lr: 4.0000e-03 eta: 8:55:13 time: 0.2662 data_time: 0.0072 memory: 5828 grad_norm: 3.4661 loss: 1.9097 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9097 2023/06/05 12:06:57 - mmengine - INFO - Epoch(train) [103][2560/2569] lr: 4.0000e-03 eta: 8:55:07 time: 0.2742 data_time: 0.0073 memory: 5828 grad_norm: 3.4756 loss: 2.1153 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.1153 2023/06/05 12:06:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:06:59 - mmengine - INFO - Epoch(train) [103][2569/2569] lr: 4.0000e-03 eta: 8:55:05 time: 0.2638 data_time: 0.0070 memory: 5828 grad_norm: 3.5098 loss: 1.8795 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.8795 2023/06/05 12:07:06 - mmengine - INFO - Epoch(train) [104][ 20/2569] lr: 4.0000e-03 eta: 8:55:00 time: 0.3365 data_time: 0.0529 memory: 5828 grad_norm: 3.4617 loss: 1.9097 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9097 2023/06/05 12:07:11 - mmengine - INFO - Epoch(train) [104][ 40/2569] lr: 4.0000e-03 eta: 8:54:55 time: 0.2848 data_time: 0.0073 memory: 5828 grad_norm: 3.3631 loss: 1.9498 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9498 2023/06/05 12:07:17 - mmengine - INFO - Epoch(train) [104][ 60/2569] lr: 4.0000e-03 eta: 8:54:50 time: 0.2727 data_time: 0.0069 memory: 5828 grad_norm: 3.4815 loss: 2.0194 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0194 2023/06/05 12:07:22 - mmengine - INFO - Epoch(train) [104][ 80/2569] lr: 4.0000e-03 eta: 8:54:45 time: 0.2725 data_time: 0.0071 memory: 5828 grad_norm: 3.4888 loss: 1.8339 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8339 2023/06/05 12:07:27 - mmengine - INFO - Epoch(train) [104][ 100/2569] lr: 4.0000e-03 eta: 8:54:39 time: 0.2620 data_time: 0.0074 memory: 5828 grad_norm: 3.4200 loss: 2.0289 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0289 2023/06/05 12:07:33 - mmengine - INFO - Epoch(train) [104][ 120/2569] lr: 4.0000e-03 eta: 8:54:34 time: 0.2674 data_time: 0.0074 memory: 5828 grad_norm: 3.4685 loss: 2.1136 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1136 2023/06/05 12:07:38 - mmengine - INFO - Epoch(train) [104][ 140/2569] lr: 4.0000e-03 eta: 8:54:29 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.4482 loss: 2.0717 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0717 2023/06/05 12:07:43 - mmengine - INFO - Epoch(train) [104][ 160/2569] lr: 4.0000e-03 eta: 8:54:23 time: 0.2682 data_time: 0.0072 memory: 5828 grad_norm: 3.4296 loss: 2.0198 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0198 2023/06/05 12:07:49 - mmengine - INFO - Epoch(train) [104][ 180/2569] lr: 4.0000e-03 eta: 8:54:18 time: 0.2746 data_time: 0.0068 memory: 5828 grad_norm: 3.4484 loss: 1.9484 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9484 2023/06/05 12:07:54 - mmengine - INFO - Epoch(train) [104][ 200/2569] lr: 4.0000e-03 eta: 8:54:13 time: 0.2746 data_time: 0.0074 memory: 5828 grad_norm: 3.5110 loss: 1.8311 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8311 2023/06/05 12:08:00 - mmengine - INFO - Epoch(train) [104][ 220/2569] lr: 4.0000e-03 eta: 8:54:08 time: 0.2673 data_time: 0.0070 memory: 5828 grad_norm: 3.4800 loss: 1.8147 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8147 2023/06/05 12:08:05 - mmengine - INFO - Epoch(train) [104][ 240/2569] lr: 4.0000e-03 eta: 8:54:02 time: 0.2649 data_time: 0.0070 memory: 5828 grad_norm: 3.4472 loss: 1.6791 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6791 2023/06/05 12:08:10 - mmengine - INFO - Epoch(train) [104][ 260/2569] lr: 4.0000e-03 eta: 8:53:57 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 3.4417 loss: 2.0733 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0733 2023/06/05 12:08:16 - mmengine - INFO - Epoch(train) [104][ 280/2569] lr: 4.0000e-03 eta: 8:53:52 time: 0.2602 data_time: 0.0079 memory: 5828 grad_norm: 3.4937 loss: 2.3459 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3459 2023/06/05 12:08:21 - mmengine - INFO - Epoch(train) [104][ 300/2569] lr: 4.0000e-03 eta: 8:53:46 time: 0.2725 data_time: 0.0072 memory: 5828 grad_norm: 3.5072 loss: 2.0945 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0945 2023/06/05 12:08:26 - mmengine - INFO - Epoch(train) [104][ 320/2569] lr: 4.0000e-03 eta: 8:53:41 time: 0.2637 data_time: 0.0072 memory: 5828 grad_norm: 3.4624 loss: 1.8935 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8935 2023/06/05 12:08:32 - mmengine - INFO - Epoch(train) [104][ 340/2569] lr: 4.0000e-03 eta: 8:53:36 time: 0.2604 data_time: 0.0074 memory: 5828 grad_norm: 3.5058 loss: 1.9364 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9364 2023/06/05 12:08:37 - mmengine - INFO - Epoch(train) [104][ 360/2569] lr: 4.0000e-03 eta: 8:53:30 time: 0.2620 data_time: 0.0070 memory: 5828 grad_norm: 3.5250 loss: 1.5985 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5985 2023/06/05 12:08:42 - mmengine - INFO - Epoch(train) [104][ 380/2569] lr: 4.0000e-03 eta: 8:53:25 time: 0.2650 data_time: 0.0070 memory: 5828 grad_norm: 3.5238 loss: 1.9051 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9051 2023/06/05 12:08:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:08:48 - mmengine - INFO - Epoch(train) [104][ 400/2569] lr: 4.0000e-03 eta: 8:53:20 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 3.5227 loss: 2.0528 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0528 2023/06/05 12:08:53 - mmengine - INFO - Epoch(train) [104][ 420/2569] lr: 4.0000e-03 eta: 8:53:14 time: 0.2773 data_time: 0.0070 memory: 5828 grad_norm: 3.4380 loss: 1.9975 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9975 2023/06/05 12:08:58 - mmengine - INFO - Epoch(train) [104][ 440/2569] lr: 4.0000e-03 eta: 8:53:09 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 3.4488 loss: 1.9408 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9408 2023/06/05 12:09:04 - mmengine - INFO - Epoch(train) [104][ 460/2569] lr: 4.0000e-03 eta: 8:53:04 time: 0.2688 data_time: 0.0069 memory: 5828 grad_norm: 3.4330 loss: 2.1094 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1094 2023/06/05 12:09:09 - mmengine - INFO - Epoch(train) [104][ 480/2569] lr: 4.0000e-03 eta: 8:52:59 time: 0.2722 data_time: 0.0075 memory: 5828 grad_norm: 3.3641 loss: 1.6146 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6146 2023/06/05 12:09:15 - mmengine - INFO - Epoch(train) [104][ 500/2569] lr: 4.0000e-03 eta: 8:52:53 time: 0.2757 data_time: 0.0070 memory: 5828 grad_norm: 3.3909 loss: 1.8988 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8988 2023/06/05 12:09:20 - mmengine - INFO - Epoch(train) [104][ 520/2569] lr: 4.0000e-03 eta: 8:52:48 time: 0.2626 data_time: 0.0075 memory: 5828 grad_norm: 3.5138 loss: 1.8949 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8949 2023/06/05 12:09:25 - mmengine - INFO - Epoch(train) [104][ 540/2569] lr: 4.0000e-03 eta: 8:52:43 time: 0.2623 data_time: 0.0071 memory: 5828 grad_norm: 3.4256 loss: 1.9638 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9638 2023/06/05 12:09:31 - mmengine - INFO - Epoch(train) [104][ 560/2569] lr: 4.0000e-03 eta: 8:52:37 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 3.4566 loss: 2.0900 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0900 2023/06/05 12:09:36 - mmengine - INFO - Epoch(train) [104][ 580/2569] lr: 4.0000e-03 eta: 8:52:32 time: 0.2729 data_time: 0.0073 memory: 5828 grad_norm: 3.4468 loss: 1.5880 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5880 2023/06/05 12:09:41 - mmengine - INFO - Epoch(train) [104][ 600/2569] lr: 4.0000e-03 eta: 8:52:27 time: 0.2630 data_time: 0.0071 memory: 5828 grad_norm: 3.4704 loss: 2.2322 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2322 2023/06/05 12:09:47 - mmengine - INFO - Epoch(train) [104][ 620/2569] lr: 4.0000e-03 eta: 8:52:21 time: 0.2735 data_time: 0.0070 memory: 5828 grad_norm: 3.5096 loss: 1.9605 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9605 2023/06/05 12:09:52 - mmengine - INFO - Epoch(train) [104][ 640/2569] lr: 4.0000e-03 eta: 8:52:16 time: 0.2701 data_time: 0.0070 memory: 5828 grad_norm: 3.4563 loss: 1.8771 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8771 2023/06/05 12:09:58 - mmengine - INFO - Epoch(train) [104][ 660/2569] lr: 4.0000e-03 eta: 8:52:11 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 3.4887 loss: 2.0001 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0001 2023/06/05 12:10:03 - mmengine - INFO - Epoch(train) [104][ 680/2569] lr: 4.0000e-03 eta: 8:52:06 time: 0.2682 data_time: 0.0072 memory: 5828 grad_norm: 3.4844 loss: 1.9095 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9095 2023/06/05 12:10:09 - mmengine - INFO - Epoch(train) [104][ 700/2569] lr: 4.0000e-03 eta: 8:52:00 time: 0.2837 data_time: 0.0073 memory: 5828 grad_norm: 3.5169 loss: 1.8413 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8413 2023/06/05 12:10:14 - mmengine - INFO - Epoch(train) [104][ 720/2569] lr: 4.0000e-03 eta: 8:51:55 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 3.5121 loss: 1.9883 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9883 2023/06/05 12:10:19 - mmengine - INFO - Epoch(train) [104][ 740/2569] lr: 4.0000e-03 eta: 8:51:50 time: 0.2678 data_time: 0.0070 memory: 5828 grad_norm: 3.4377 loss: 2.0443 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0443 2023/06/05 12:10:25 - mmengine - INFO - Epoch(train) [104][ 760/2569] lr: 4.0000e-03 eta: 8:51:45 time: 0.2771 data_time: 0.0070 memory: 5828 grad_norm: 3.5016 loss: 1.8449 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8449 2023/06/05 12:10:30 - mmengine - INFO - Epoch(train) [104][ 780/2569] lr: 4.0000e-03 eta: 8:51:39 time: 0.2638 data_time: 0.0071 memory: 5828 grad_norm: 3.5206 loss: 2.1378 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1378 2023/06/05 12:10:35 - mmengine - INFO - Epoch(train) [104][ 800/2569] lr: 4.0000e-03 eta: 8:51:34 time: 0.2616 data_time: 0.0069 memory: 5828 grad_norm: 3.4835 loss: 2.0389 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0389 2023/06/05 12:10:41 - mmengine - INFO - Epoch(train) [104][ 820/2569] lr: 4.0000e-03 eta: 8:51:28 time: 0.2612 data_time: 0.0069 memory: 5828 grad_norm: 3.5198 loss: 1.9622 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9622 2023/06/05 12:10:46 - mmengine - INFO - Epoch(train) [104][ 840/2569] lr: 4.0000e-03 eta: 8:51:23 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 3.4452 loss: 1.8452 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8452 2023/06/05 12:10:51 - mmengine - INFO - Epoch(train) [104][ 860/2569] lr: 4.0000e-03 eta: 8:51:18 time: 0.2619 data_time: 0.0074 memory: 5828 grad_norm: 3.5205 loss: 2.1793 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1793 2023/06/05 12:10:57 - mmengine - INFO - Epoch(train) [104][ 880/2569] lr: 4.0000e-03 eta: 8:51:12 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 3.5121 loss: 2.1313 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1313 2023/06/05 12:11:02 - mmengine - INFO - Epoch(train) [104][ 900/2569] lr: 4.0000e-03 eta: 8:51:07 time: 0.2674 data_time: 0.0075 memory: 5828 grad_norm: 3.5518 loss: 1.9363 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9363 2023/06/05 12:11:07 - mmengine - INFO - Epoch(train) [104][ 920/2569] lr: 4.0000e-03 eta: 8:51:02 time: 0.2726 data_time: 0.0068 memory: 5828 grad_norm: 3.5173 loss: 1.9070 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9070 2023/06/05 12:11:13 - mmengine - INFO - Epoch(train) [104][ 940/2569] lr: 4.0000e-03 eta: 8:50:57 time: 0.2607 data_time: 0.0082 memory: 5828 grad_norm: 3.4459 loss: 2.2765 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.2765 2023/06/05 12:11:18 - mmengine - INFO - Epoch(train) [104][ 960/2569] lr: 4.0000e-03 eta: 8:50:51 time: 0.2677 data_time: 0.0067 memory: 5828 grad_norm: 3.4901 loss: 2.0619 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0619 2023/06/05 12:11:23 - mmengine - INFO - Epoch(train) [104][ 980/2569] lr: 4.0000e-03 eta: 8:50:46 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 3.5082 loss: 1.8557 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8557 2023/06/05 12:11:29 - mmengine - INFO - Epoch(train) [104][1000/2569] lr: 4.0000e-03 eta: 8:50:41 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 3.4544 loss: 1.9232 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9232 2023/06/05 12:11:34 - mmengine - INFO - Epoch(train) [104][1020/2569] lr: 4.0000e-03 eta: 8:50:35 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 3.5138 loss: 1.8923 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8923 2023/06/05 12:11:39 - mmengine - INFO - Epoch(train) [104][1040/2569] lr: 4.0000e-03 eta: 8:50:30 time: 0.2625 data_time: 0.0070 memory: 5828 grad_norm: 3.5473 loss: 2.3010 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3010 2023/06/05 12:11:45 - mmengine - INFO - Epoch(train) [104][1060/2569] lr: 4.0000e-03 eta: 8:50:25 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 3.5241 loss: 1.9892 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9892 2023/06/05 12:11:50 - mmengine - INFO - Epoch(train) [104][1080/2569] lr: 4.0000e-03 eta: 8:50:19 time: 0.2654 data_time: 0.0070 memory: 5828 grad_norm: 3.4983 loss: 1.9708 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9708 2023/06/05 12:11:55 - mmengine - INFO - Epoch(train) [104][1100/2569] lr: 4.0000e-03 eta: 8:50:14 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 3.5468 loss: 1.9409 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9409 2023/06/05 12:12:00 - mmengine - INFO - Epoch(train) [104][1120/2569] lr: 4.0000e-03 eta: 8:50:09 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.4794 loss: 1.7275 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7275 2023/06/05 12:12:06 - mmengine - INFO - Epoch(train) [104][1140/2569] lr: 4.0000e-03 eta: 8:50:03 time: 0.2610 data_time: 0.0076 memory: 5828 grad_norm: 3.4614 loss: 1.9575 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9575 2023/06/05 12:12:11 - mmengine - INFO - Epoch(train) [104][1160/2569] lr: 4.0000e-03 eta: 8:49:58 time: 0.2662 data_time: 0.0073 memory: 5828 grad_norm: 3.4691 loss: 2.0044 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0044 2023/06/05 12:12:16 - mmengine - INFO - Epoch(train) [104][1180/2569] lr: 4.0000e-03 eta: 8:49:53 time: 0.2680 data_time: 0.0072 memory: 5828 grad_norm: 3.4777 loss: 1.5669 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5669 2023/06/05 12:12:22 - mmengine - INFO - Epoch(train) [104][1200/2569] lr: 4.0000e-03 eta: 8:49:47 time: 0.2750 data_time: 0.0076 memory: 5828 grad_norm: 3.4766 loss: 1.9364 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9364 2023/06/05 12:12:27 - mmengine - INFO - Epoch(train) [104][1220/2569] lr: 4.0000e-03 eta: 8:49:42 time: 0.2663 data_time: 0.0075 memory: 5828 grad_norm: 3.5257 loss: 1.8501 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8501 2023/06/05 12:12:33 - mmengine - INFO - Epoch(train) [104][1240/2569] lr: 4.0000e-03 eta: 8:49:37 time: 0.2692 data_time: 0.0072 memory: 5828 grad_norm: 3.4993 loss: 2.0202 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0202 2023/06/05 12:12:38 - mmengine - INFO - Epoch(train) [104][1260/2569] lr: 4.0000e-03 eta: 8:49:31 time: 0.2654 data_time: 0.0071 memory: 5828 grad_norm: 3.4941 loss: 1.6432 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6432 2023/06/05 12:12:43 - mmengine - INFO - Epoch(train) [104][1280/2569] lr: 4.0000e-03 eta: 8:49:26 time: 0.2637 data_time: 0.0075 memory: 5828 grad_norm: 3.5210 loss: 1.7538 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7538 2023/06/05 12:12:48 - mmengine - INFO - Epoch(train) [104][1300/2569] lr: 4.0000e-03 eta: 8:49:21 time: 0.2612 data_time: 0.0083 memory: 5828 grad_norm: 3.5347 loss: 1.9735 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9735 2023/06/05 12:12:54 - mmengine - INFO - Epoch(train) [104][1320/2569] lr: 4.0000e-03 eta: 8:49:15 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 3.5219 loss: 1.5754 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5754 2023/06/05 12:12:59 - mmengine - INFO - Epoch(train) [104][1340/2569] lr: 4.0000e-03 eta: 8:49:10 time: 0.2643 data_time: 0.0076 memory: 5828 grad_norm: 3.5786 loss: 1.8226 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8226 2023/06/05 12:13:05 - mmengine - INFO - Epoch(train) [104][1360/2569] lr: 4.0000e-03 eta: 8:49:05 time: 0.2814 data_time: 0.0074 memory: 5828 grad_norm: 3.5548 loss: 1.9786 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9786 2023/06/05 12:13:10 - mmengine - INFO - Epoch(train) [104][1380/2569] lr: 4.0000e-03 eta: 8:49:00 time: 0.2612 data_time: 0.0069 memory: 5828 grad_norm: 3.5352 loss: 2.0329 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0329 2023/06/05 12:13:13 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:13:15 - mmengine - INFO - Epoch(train) [104][1400/2569] lr: 4.0000e-03 eta: 8:48:54 time: 0.2766 data_time: 0.0068 memory: 5828 grad_norm: 3.5667 loss: 1.9175 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9175 2023/06/05 12:13:21 - mmengine - INFO - Epoch(train) [104][1420/2569] lr: 4.0000e-03 eta: 8:48:49 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 3.5312 loss: 1.9555 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9555 2023/06/05 12:13:26 - mmengine - INFO - Epoch(train) [104][1440/2569] lr: 4.0000e-03 eta: 8:48:44 time: 0.2698 data_time: 0.0072 memory: 5828 grad_norm: 3.5040 loss: 2.0276 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0276 2023/06/05 12:13:31 - mmengine - INFO - Epoch(train) [104][1460/2569] lr: 4.0000e-03 eta: 8:48:38 time: 0.2613 data_time: 0.0070 memory: 5828 grad_norm: 3.4816 loss: 1.9100 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9100 2023/06/05 12:13:37 - mmengine - INFO - Epoch(train) [104][1480/2569] lr: 4.0000e-03 eta: 8:48:33 time: 0.2714 data_time: 0.0073 memory: 5828 grad_norm: 3.5662 loss: 2.0007 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0007 2023/06/05 12:13:42 - mmengine - INFO - Epoch(train) [104][1500/2569] lr: 4.0000e-03 eta: 8:48:28 time: 0.2658 data_time: 0.0075 memory: 5828 grad_norm: 3.5072 loss: 1.7454 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7454 2023/06/05 12:13:48 - mmengine - INFO - Epoch(train) [104][1520/2569] lr: 4.0000e-03 eta: 8:48:23 time: 0.2705 data_time: 0.0071 memory: 5828 grad_norm: 3.4799 loss: 2.1372 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1372 2023/06/05 12:13:53 - mmengine - INFO - Epoch(train) [104][1540/2569] lr: 4.0000e-03 eta: 8:48:17 time: 0.2760 data_time: 0.0074 memory: 5828 grad_norm: 3.5393 loss: 1.8879 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8879 2023/06/05 12:13:59 - mmengine - INFO - Epoch(train) [104][1560/2569] lr: 4.0000e-03 eta: 8:48:12 time: 0.2730 data_time: 0.0072 memory: 5828 grad_norm: 3.5053 loss: 2.2700 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2700 2023/06/05 12:14:04 - mmengine - INFO - Epoch(train) [104][1580/2569] lr: 4.0000e-03 eta: 8:48:07 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 3.4064 loss: 1.9464 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9464 2023/06/05 12:14:09 - mmengine - INFO - Epoch(train) [104][1600/2569] lr: 4.0000e-03 eta: 8:48:01 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 3.4942 loss: 1.6700 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6700 2023/06/05 12:14:15 - mmengine - INFO - Epoch(train) [104][1620/2569] lr: 4.0000e-03 eta: 8:47:56 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 3.5338 loss: 1.8150 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8150 2023/06/05 12:14:20 - mmengine - INFO - Epoch(train) [104][1640/2569] lr: 4.0000e-03 eta: 8:47:51 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.5176 loss: 2.1930 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1930 2023/06/05 12:14:25 - mmengine - INFO - Epoch(train) [104][1660/2569] lr: 4.0000e-03 eta: 8:47:45 time: 0.2633 data_time: 0.0073 memory: 5828 grad_norm: 3.5058 loss: 2.0869 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0869 2023/06/05 12:14:30 - mmengine - INFO - Epoch(train) [104][1680/2569] lr: 4.0000e-03 eta: 8:47:40 time: 0.2678 data_time: 0.0072 memory: 5828 grad_norm: 3.4583 loss: 2.1386 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1386 2023/06/05 12:14:36 - mmengine - INFO - Epoch(train) [104][1700/2569] lr: 4.0000e-03 eta: 8:47:35 time: 0.2666 data_time: 0.0070 memory: 5828 grad_norm: 3.4421 loss: 1.5674 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5674 2023/06/05 12:14:41 - mmengine - INFO - Epoch(train) [104][1720/2569] lr: 4.0000e-03 eta: 8:47:29 time: 0.2600 data_time: 0.0074 memory: 5828 grad_norm: 3.4752 loss: 2.0029 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0029 2023/06/05 12:14:46 - mmengine - INFO - Epoch(train) [104][1740/2569] lr: 4.0000e-03 eta: 8:47:24 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 3.5247 loss: 2.0026 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.0026 2023/06/05 12:14:51 - mmengine - INFO - Epoch(train) [104][1760/2569] lr: 4.0000e-03 eta: 8:47:19 time: 0.2604 data_time: 0.0073 memory: 5828 grad_norm: 3.5141 loss: 1.9808 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9808 2023/06/05 12:14:57 - mmengine - INFO - Epoch(train) [104][1780/2569] lr: 4.0000e-03 eta: 8:47:13 time: 0.2655 data_time: 0.0074 memory: 5828 grad_norm: 3.4554 loss: 2.0446 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0446 2023/06/05 12:15:02 - mmengine - INFO - Epoch(train) [104][1800/2569] lr: 4.0000e-03 eta: 8:47:08 time: 0.2682 data_time: 0.0071 memory: 5828 grad_norm: 3.4556 loss: 1.8658 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8658 2023/06/05 12:15:08 - mmengine - INFO - Epoch(train) [104][1820/2569] lr: 4.0000e-03 eta: 8:47:03 time: 0.2721 data_time: 0.0073 memory: 5828 grad_norm: 3.5325 loss: 1.6791 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6791 2023/06/05 12:15:13 - mmengine - INFO - Epoch(train) [104][1840/2569] lr: 4.0000e-03 eta: 8:46:57 time: 0.2615 data_time: 0.0073 memory: 5828 grad_norm: 3.5040 loss: 2.0800 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0800 2023/06/05 12:15:18 - mmengine - INFO - Epoch(train) [104][1860/2569] lr: 4.0000e-03 eta: 8:46:52 time: 0.2712 data_time: 0.0072 memory: 5828 grad_norm: 3.5493 loss: 2.0918 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0918 2023/06/05 12:15:24 - mmengine - INFO - Epoch(train) [104][1880/2569] lr: 4.0000e-03 eta: 8:46:47 time: 0.2678 data_time: 0.0075 memory: 5828 grad_norm: 3.5059 loss: 2.1981 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1981 2023/06/05 12:15:29 - mmengine - INFO - Epoch(train) [104][1900/2569] lr: 4.0000e-03 eta: 8:46:41 time: 0.2589 data_time: 0.0091 memory: 5828 grad_norm: 3.4692 loss: 1.8987 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8987 2023/06/05 12:15:34 - mmengine - INFO - Epoch(train) [104][1920/2569] lr: 4.0000e-03 eta: 8:46:36 time: 0.2685 data_time: 0.0100 memory: 5828 grad_norm: 3.5466 loss: 2.0347 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0347 2023/06/05 12:15:39 - mmengine - INFO - Epoch(train) [104][1940/2569] lr: 4.0000e-03 eta: 8:46:31 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 3.4946 loss: 1.7367 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7367 2023/06/05 12:15:45 - mmengine - INFO - Epoch(train) [104][1960/2569] lr: 4.0000e-03 eta: 8:46:25 time: 0.2608 data_time: 0.0070 memory: 5828 grad_norm: 3.5021 loss: 2.1055 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1055 2023/06/05 12:15:50 - mmengine - INFO - Epoch(train) [104][1980/2569] lr: 4.0000e-03 eta: 8:46:20 time: 0.2629 data_time: 0.0071 memory: 5828 grad_norm: 3.5677 loss: 1.5889 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5889 2023/06/05 12:15:55 - mmengine - INFO - Epoch(train) [104][2000/2569] lr: 4.0000e-03 eta: 8:46:15 time: 0.2637 data_time: 0.0075 memory: 5828 grad_norm: 3.4474 loss: 1.9322 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9322 2023/06/05 12:16:01 - mmengine - INFO - Epoch(train) [104][2020/2569] lr: 4.0000e-03 eta: 8:46:09 time: 0.2693 data_time: 0.0075 memory: 5828 grad_norm: 3.5604 loss: 1.8447 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8447 2023/06/05 12:16:06 - mmengine - INFO - Epoch(train) [104][2040/2569] lr: 4.0000e-03 eta: 8:46:04 time: 0.2594 data_time: 0.0072 memory: 5828 grad_norm: 3.5648 loss: 2.1094 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1094 2023/06/05 12:16:11 - mmengine - INFO - Epoch(train) [104][2060/2569] lr: 4.0000e-03 eta: 8:45:59 time: 0.2616 data_time: 0.0071 memory: 5828 grad_norm: 3.5418 loss: 1.8250 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8250 2023/06/05 12:16:16 - mmengine - INFO - Epoch(train) [104][2080/2569] lr: 4.0000e-03 eta: 8:45:53 time: 0.2590 data_time: 0.0075 memory: 5828 grad_norm: 3.4524 loss: 2.1657 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1657 2023/06/05 12:16:22 - mmengine - INFO - Epoch(train) [104][2100/2569] lr: 4.0000e-03 eta: 8:45:48 time: 0.2659 data_time: 0.0073 memory: 5828 grad_norm: 3.4744 loss: 2.0790 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0790 2023/06/05 12:16:27 - mmengine - INFO - Epoch(train) [104][2120/2569] lr: 4.0000e-03 eta: 8:45:43 time: 0.2697 data_time: 0.0073 memory: 5828 grad_norm: 3.5003 loss: 1.9139 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9139 2023/06/05 12:16:32 - mmengine - INFO - Epoch(train) [104][2140/2569] lr: 4.0000e-03 eta: 8:45:37 time: 0.2665 data_time: 0.0073 memory: 5828 grad_norm: 3.5789 loss: 2.0535 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0535 2023/06/05 12:16:38 - mmengine - INFO - Epoch(train) [104][2160/2569] lr: 4.0000e-03 eta: 8:45:32 time: 0.2612 data_time: 0.0075 memory: 5828 grad_norm: 3.4886 loss: 2.1489 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1489 2023/06/05 12:16:43 - mmengine - INFO - Epoch(train) [104][2180/2569] lr: 4.0000e-03 eta: 8:45:27 time: 0.2597 data_time: 0.0070 memory: 5828 grad_norm: 3.5457 loss: 1.7723 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7723 2023/06/05 12:16:48 - mmengine - INFO - Epoch(train) [104][2200/2569] lr: 4.0000e-03 eta: 8:45:21 time: 0.2712 data_time: 0.0071 memory: 5828 grad_norm: 3.4391 loss: 1.9160 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9160 2023/06/05 12:16:54 - mmengine - INFO - Epoch(train) [104][2220/2569] lr: 4.0000e-03 eta: 8:45:16 time: 0.2729 data_time: 0.0075 memory: 5828 grad_norm: 3.4926 loss: 2.1825 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1825 2023/06/05 12:16:59 - mmengine - INFO - Epoch(train) [104][2240/2569] lr: 4.0000e-03 eta: 8:45:11 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 3.5534 loss: 1.7589 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7589 2023/06/05 12:17:04 - mmengine - INFO - Epoch(train) [104][2260/2569] lr: 4.0000e-03 eta: 8:45:06 time: 0.2673 data_time: 0.0071 memory: 5828 grad_norm: 3.5342 loss: 2.2026 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2026 2023/06/05 12:17:10 - mmengine - INFO - Epoch(train) [104][2280/2569] lr: 4.0000e-03 eta: 8:45:00 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 3.5410 loss: 2.1730 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1730 2023/06/05 12:17:15 - mmengine - INFO - Epoch(train) [104][2300/2569] lr: 4.0000e-03 eta: 8:44:55 time: 0.2665 data_time: 0.0068 memory: 5828 grad_norm: 3.5005 loss: 1.8484 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8484 2023/06/05 12:17:20 - mmengine - INFO - Epoch(train) [104][2320/2569] lr: 4.0000e-03 eta: 8:44:50 time: 0.2710 data_time: 0.0069 memory: 5828 grad_norm: 3.5716 loss: 1.9580 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9580 2023/06/05 12:17:26 - mmengine - INFO - Epoch(train) [104][2340/2569] lr: 4.0000e-03 eta: 8:44:44 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 3.5068 loss: 2.0397 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0397 2023/06/05 12:17:31 - mmengine - INFO - Epoch(train) [104][2360/2569] lr: 4.0000e-03 eta: 8:44:39 time: 0.2706 data_time: 0.0068 memory: 5828 grad_norm: 3.5164 loss: 2.2820 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2820 2023/06/05 12:17:36 - mmengine - INFO - Epoch(train) [104][2380/2569] lr: 4.0000e-03 eta: 8:44:34 time: 0.2617 data_time: 0.0093 memory: 5828 grad_norm: 3.4919 loss: 1.8319 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8319 2023/06/05 12:17:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:17:42 - mmengine - INFO - Epoch(train) [104][2400/2569] lr: 4.0000e-03 eta: 8:44:28 time: 0.2718 data_time: 0.0074 memory: 5828 grad_norm: 3.5573 loss: 2.0233 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0233 2023/06/05 12:17:47 - mmengine - INFO - Epoch(train) [104][2420/2569] lr: 4.0000e-03 eta: 8:44:23 time: 0.2611 data_time: 0.0073 memory: 5828 grad_norm: 3.6033 loss: 2.0910 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0910 2023/06/05 12:17:52 - mmengine - INFO - Epoch(train) [104][2440/2569] lr: 4.0000e-03 eta: 8:44:18 time: 0.2667 data_time: 0.0071 memory: 5828 grad_norm: 3.5091 loss: 1.5348 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5348 2023/06/05 12:17:58 - mmengine - INFO - Epoch(train) [104][2460/2569] lr: 4.0000e-03 eta: 8:44:12 time: 0.2678 data_time: 0.0075 memory: 5828 grad_norm: 3.4949 loss: 2.1117 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1117 2023/06/05 12:18:03 - mmengine - INFO - Epoch(train) [104][2480/2569] lr: 4.0000e-03 eta: 8:44:07 time: 0.2657 data_time: 0.0075 memory: 5828 grad_norm: 3.4930 loss: 1.6065 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6065 2023/06/05 12:18:08 - mmengine - INFO - Epoch(train) [104][2500/2569] lr: 4.0000e-03 eta: 8:44:02 time: 0.2642 data_time: 0.0077 memory: 5828 grad_norm: 3.5219 loss: 1.8081 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8081 2023/06/05 12:18:14 - mmengine - INFO - Epoch(train) [104][2520/2569] lr: 4.0000e-03 eta: 8:43:57 time: 0.2664 data_time: 0.0071 memory: 5828 grad_norm: 3.4841 loss: 2.0112 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0112 2023/06/05 12:18:19 - mmengine - INFO - Epoch(train) [104][2540/2569] lr: 4.0000e-03 eta: 8:43:51 time: 0.2743 data_time: 0.0074 memory: 5828 grad_norm: 3.5265 loss: 2.0194 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0194 2023/06/05 12:18:24 - mmengine - INFO - Epoch(train) [104][2560/2569] lr: 4.0000e-03 eta: 8:43:46 time: 0.2631 data_time: 0.0075 memory: 5828 grad_norm: 3.6099 loss: 2.1690 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1690 2023/06/05 12:18:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:18:27 - mmengine - INFO - Epoch(train) [104][2569/2569] lr: 4.0000e-03 eta: 8:43:43 time: 0.2538 data_time: 0.0070 memory: 5828 grad_norm: 3.6880 loss: 1.9991 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.9991 2023/06/05 12:18:27 - mmengine - INFO - Saving checkpoint at 104 epochs 2023/06/05 12:18:35 - mmengine - INFO - Epoch(train) [105][ 20/2569] lr: 4.0000e-03 eta: 8:43:39 time: 0.3075 data_time: 0.0497 memory: 5828 grad_norm: 3.5165 loss: 1.6449 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6449 2023/06/05 12:18:40 - mmengine - INFO - Epoch(train) [105][ 40/2569] lr: 4.0000e-03 eta: 8:43:33 time: 0.2705 data_time: 0.0075 memory: 5828 grad_norm: 3.5007 loss: 1.8887 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8887 2023/06/05 12:18:46 - mmengine - INFO - Epoch(train) [105][ 60/2569] lr: 4.0000e-03 eta: 8:43:28 time: 0.2654 data_time: 0.0081 memory: 5828 grad_norm: 3.5449 loss: 2.1150 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1150 2023/06/05 12:18:51 - mmengine - INFO - Epoch(train) [105][ 80/2569] lr: 4.0000e-03 eta: 8:43:23 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 3.5151 loss: 1.6666 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6666 2023/06/05 12:18:56 - mmengine - INFO - Epoch(train) [105][ 100/2569] lr: 4.0000e-03 eta: 8:43:17 time: 0.2611 data_time: 0.0073 memory: 5828 grad_norm: 3.5044 loss: 1.9119 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9119 2023/06/05 12:19:02 - mmengine - INFO - Epoch(train) [105][ 120/2569] lr: 4.0000e-03 eta: 8:43:12 time: 0.2652 data_time: 0.0070 memory: 5828 grad_norm: 3.5003 loss: 1.9133 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9133 2023/06/05 12:19:07 - mmengine - INFO - Epoch(train) [105][ 140/2569] lr: 4.0000e-03 eta: 8:43:07 time: 0.2592 data_time: 0.0073 memory: 5828 grad_norm: 3.5586 loss: 2.0906 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0906 2023/06/05 12:19:12 - mmengine - INFO - Epoch(train) [105][ 160/2569] lr: 4.0000e-03 eta: 8:43:01 time: 0.2629 data_time: 0.0071 memory: 5828 grad_norm: 3.5841 loss: 1.7164 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7164 2023/06/05 12:19:17 - mmengine - INFO - Epoch(train) [105][ 180/2569] lr: 4.0000e-03 eta: 8:42:56 time: 0.2597 data_time: 0.0073 memory: 5828 grad_norm: 3.5115 loss: 1.7206 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7206 2023/06/05 12:19:23 - mmengine - INFO - Epoch(train) [105][ 200/2569] lr: 4.0000e-03 eta: 8:42:51 time: 0.2700 data_time: 0.0070 memory: 5828 grad_norm: 3.5620 loss: 2.0790 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0790 2023/06/05 12:19:28 - mmengine - INFO - Epoch(train) [105][ 220/2569] lr: 4.0000e-03 eta: 8:42:45 time: 0.2662 data_time: 0.0073 memory: 5828 grad_norm: 3.5369 loss: 1.9110 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9110 2023/06/05 12:19:33 - mmengine - INFO - Epoch(train) [105][ 240/2569] lr: 4.0000e-03 eta: 8:42:40 time: 0.2609 data_time: 0.0070 memory: 5828 grad_norm: 3.5131 loss: 1.8442 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8442 2023/06/05 12:19:38 - mmengine - INFO - Epoch(train) [105][ 260/2569] lr: 4.0000e-03 eta: 8:42:34 time: 0.2603 data_time: 0.0073 memory: 5828 grad_norm: 3.5282 loss: 1.7345 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7345 2023/06/05 12:19:44 - mmengine - INFO - Epoch(train) [105][ 280/2569] lr: 4.0000e-03 eta: 8:42:29 time: 0.2605 data_time: 0.0070 memory: 5828 grad_norm: 3.4723 loss: 1.9133 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9133 2023/06/05 12:19:49 - mmengine - INFO - Epoch(train) [105][ 300/2569] lr: 4.0000e-03 eta: 8:42:24 time: 0.2673 data_time: 0.0075 memory: 5828 grad_norm: 3.6063 loss: 2.0668 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0668 2023/06/05 12:19:54 - mmengine - INFO - Epoch(train) [105][ 320/2569] lr: 4.0000e-03 eta: 8:42:18 time: 0.2608 data_time: 0.0074 memory: 5828 grad_norm: 3.5748 loss: 1.8819 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8819 2023/06/05 12:19:59 - mmengine - INFO - Epoch(train) [105][ 340/2569] lr: 4.0000e-03 eta: 8:42:13 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 3.5857 loss: 2.0613 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0613 2023/06/05 12:20:05 - mmengine - INFO - Epoch(train) [105][ 360/2569] lr: 4.0000e-03 eta: 8:42:08 time: 0.2663 data_time: 0.0073 memory: 5828 grad_norm: 3.5172 loss: 1.9830 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9830 2023/06/05 12:20:10 - mmengine - INFO - Epoch(train) [105][ 380/2569] lr: 4.0000e-03 eta: 8:42:02 time: 0.2692 data_time: 0.0069 memory: 5828 grad_norm: 3.6084 loss: 2.1437 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1437 2023/06/05 12:20:15 - mmengine - INFO - Epoch(train) [105][ 400/2569] lr: 4.0000e-03 eta: 8:41:57 time: 0.2644 data_time: 0.0080 memory: 5828 grad_norm: 3.5704 loss: 2.2441 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.2441 2023/06/05 12:20:21 - mmengine - INFO - Epoch(train) [105][ 420/2569] lr: 4.0000e-03 eta: 8:41:52 time: 0.2665 data_time: 0.0071 memory: 5828 grad_norm: 3.5124 loss: 1.7930 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7930 2023/06/05 12:20:26 - mmengine - INFO - Epoch(train) [105][ 440/2569] lr: 4.0000e-03 eta: 8:41:47 time: 0.2697 data_time: 0.0072 memory: 5828 grad_norm: 3.5658 loss: 2.0060 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0060 2023/06/05 12:20:32 - mmengine - INFO - Epoch(train) [105][ 460/2569] lr: 4.0000e-03 eta: 8:41:41 time: 0.2675 data_time: 0.0071 memory: 5828 grad_norm: 3.5184 loss: 2.0940 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0940 2023/06/05 12:20:37 - mmengine - INFO - Epoch(train) [105][ 480/2569] lr: 4.0000e-03 eta: 8:41:36 time: 0.2642 data_time: 0.0072 memory: 5828 grad_norm: 3.5442 loss: 1.8676 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8676 2023/06/05 12:20:42 - mmengine - INFO - Epoch(train) [105][ 500/2569] lr: 4.0000e-03 eta: 8:41:31 time: 0.2712 data_time: 0.0073 memory: 5828 grad_norm: 3.4676 loss: 2.4265 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.4265 2023/06/05 12:20:48 - mmengine - INFO - Epoch(train) [105][ 520/2569] lr: 4.0000e-03 eta: 8:41:25 time: 0.2643 data_time: 0.0075 memory: 5828 grad_norm: 3.5708 loss: 1.6284 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.6284 2023/06/05 12:20:53 - mmengine - INFO - Epoch(train) [105][ 540/2569] lr: 4.0000e-03 eta: 8:41:20 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 3.4743 loss: 2.0334 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0334 2023/06/05 12:20:58 - mmengine - INFO - Epoch(train) [105][ 560/2569] lr: 4.0000e-03 eta: 8:41:15 time: 0.2678 data_time: 0.0070 memory: 5828 grad_norm: 3.5738 loss: 1.6113 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.6113 2023/06/05 12:21:04 - mmengine - INFO - Epoch(train) [105][ 580/2569] lr: 4.0000e-03 eta: 8:41:09 time: 0.2695 data_time: 0.0073 memory: 5828 grad_norm: 3.5178 loss: 1.6051 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6051 2023/06/05 12:21:09 - mmengine - INFO - Epoch(train) [105][ 600/2569] lr: 4.0000e-03 eta: 8:41:04 time: 0.2694 data_time: 0.0073 memory: 5828 grad_norm: 3.5434 loss: 1.6068 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6068 2023/06/05 12:21:15 - mmengine - INFO - Epoch(train) [105][ 620/2569] lr: 4.0000e-03 eta: 8:40:59 time: 0.2778 data_time: 0.0072 memory: 5828 grad_norm: 3.4926 loss: 2.0647 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0647 2023/06/05 12:21:20 - mmengine - INFO - Epoch(train) [105][ 640/2569] lr: 4.0000e-03 eta: 8:40:54 time: 0.2652 data_time: 0.0071 memory: 5828 grad_norm: 3.6171 loss: 1.6260 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6260 2023/06/05 12:21:25 - mmengine - INFO - Epoch(train) [105][ 660/2569] lr: 4.0000e-03 eta: 8:40:48 time: 0.2711 data_time: 0.0073 memory: 5828 grad_norm: 3.5399 loss: 1.9052 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9052 2023/06/05 12:21:31 - mmengine - INFO - Epoch(train) [105][ 680/2569] lr: 4.0000e-03 eta: 8:40:43 time: 0.2695 data_time: 0.0069 memory: 5828 grad_norm: 3.5856 loss: 1.8024 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8024 2023/06/05 12:21:36 - mmengine - INFO - Epoch(train) [105][ 700/2569] lr: 4.0000e-03 eta: 8:40:38 time: 0.2699 data_time: 0.0069 memory: 5828 grad_norm: 3.5893 loss: 2.2656 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.2656 2023/06/05 12:21:41 - mmengine - INFO - Epoch(train) [105][ 720/2569] lr: 4.0000e-03 eta: 8:40:32 time: 0.2673 data_time: 0.0071 memory: 5828 grad_norm: 3.5752 loss: 2.1126 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1126 2023/06/05 12:21:47 - mmengine - INFO - Epoch(train) [105][ 740/2569] lr: 4.0000e-03 eta: 8:40:27 time: 0.2683 data_time: 0.0071 memory: 5828 grad_norm: 3.5937 loss: 1.9120 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9120 2023/06/05 12:21:52 - mmengine - INFO - Epoch(train) [105][ 760/2569] lr: 4.0000e-03 eta: 8:40:22 time: 0.2632 data_time: 0.0070 memory: 5828 grad_norm: 3.5543 loss: 1.8540 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8540 2023/06/05 12:21:58 - mmengine - INFO - Epoch(train) [105][ 780/2569] lr: 4.0000e-03 eta: 8:40:17 time: 0.2705 data_time: 0.0075 memory: 5828 grad_norm: 3.5731 loss: 2.2229 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2229 2023/06/05 12:22:03 - mmengine - INFO - Epoch(train) [105][ 800/2569] lr: 4.0000e-03 eta: 8:40:11 time: 0.2619 data_time: 0.0071 memory: 5828 grad_norm: 3.5856 loss: 2.3503 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.3503 2023/06/05 12:22:08 - mmengine - INFO - Epoch(train) [105][ 820/2569] lr: 4.0000e-03 eta: 8:40:06 time: 0.2715 data_time: 0.0071 memory: 5828 grad_norm: 3.5948 loss: 1.9815 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9815 2023/06/05 12:22:09 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:22:13 - mmengine - INFO - Epoch(train) [105][ 840/2569] lr: 4.0000e-03 eta: 8:40:01 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.5630 loss: 1.9176 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9176 2023/06/05 12:22:19 - mmengine - INFO - Epoch(train) [105][ 860/2569] lr: 4.0000e-03 eta: 8:39:55 time: 0.2836 data_time: 0.0077 memory: 5828 grad_norm: 3.5887 loss: 2.0132 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0132 2023/06/05 12:22:25 - mmengine - INFO - Epoch(train) [105][ 880/2569] lr: 4.0000e-03 eta: 8:39:50 time: 0.2756 data_time: 0.0082 memory: 5828 grad_norm: 3.5607 loss: 2.2079 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.2079 2023/06/05 12:22:30 - mmengine - INFO - Epoch(train) [105][ 900/2569] lr: 4.0000e-03 eta: 8:39:45 time: 0.2695 data_time: 0.0073 memory: 5828 grad_norm: 3.5551 loss: 1.7761 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7761 2023/06/05 12:22:35 - mmengine - INFO - Epoch(train) [105][ 920/2569] lr: 4.0000e-03 eta: 8:39:40 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 3.5300 loss: 1.9451 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.9451 2023/06/05 12:22:41 - mmengine - INFO - Epoch(train) [105][ 940/2569] lr: 4.0000e-03 eta: 8:39:34 time: 0.2695 data_time: 0.0075 memory: 5828 grad_norm: 3.6248 loss: 1.8899 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8899 2023/06/05 12:22:46 - mmengine - INFO - Epoch(train) [105][ 960/2569] lr: 4.0000e-03 eta: 8:39:29 time: 0.2663 data_time: 0.0075 memory: 5828 grad_norm: 3.5273 loss: 1.8311 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8311 2023/06/05 12:22:51 - mmengine - INFO - Epoch(train) [105][ 980/2569] lr: 4.0000e-03 eta: 8:39:24 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 3.6411 loss: 1.8256 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8256 2023/06/05 12:22:57 - mmengine - INFO - Epoch(train) [105][1000/2569] lr: 4.0000e-03 eta: 8:39:18 time: 0.2758 data_time: 0.0074 memory: 5828 grad_norm: 3.6120 loss: 2.1231 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1231 2023/06/05 12:23:02 - mmengine - INFO - Epoch(train) [105][1020/2569] lr: 4.0000e-03 eta: 8:39:13 time: 0.2649 data_time: 0.0070 memory: 5828 grad_norm: 3.5669 loss: 1.8405 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8405 2023/06/05 12:23:08 - mmengine - INFO - Epoch(train) [105][1040/2569] lr: 4.0000e-03 eta: 8:39:08 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 3.5549 loss: 1.7606 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7606 2023/06/05 12:23:13 - mmengine - INFO - Epoch(train) [105][1060/2569] lr: 4.0000e-03 eta: 8:39:03 time: 0.2782 data_time: 0.0073 memory: 5828 grad_norm: 3.5735 loss: 1.8815 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8815 2023/06/05 12:23:19 - mmengine - INFO - Epoch(train) [105][1080/2569] lr: 4.0000e-03 eta: 8:38:57 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 3.6254 loss: 1.7747 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7747 2023/06/05 12:23:24 - mmengine - INFO - Epoch(train) [105][1100/2569] lr: 4.0000e-03 eta: 8:38:52 time: 0.2743 data_time: 0.0072 memory: 5828 grad_norm: 3.5962 loss: 1.9542 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.9542 2023/06/05 12:23:29 - mmengine - INFO - Epoch(train) [105][1120/2569] lr: 4.0000e-03 eta: 8:38:47 time: 0.2594 data_time: 0.0076 memory: 5828 grad_norm: 3.5824 loss: 1.9518 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9518 2023/06/05 12:23:35 - mmengine - INFO - Epoch(train) [105][1140/2569] lr: 4.0000e-03 eta: 8:38:41 time: 0.2673 data_time: 0.0078 memory: 5828 grad_norm: 3.6078 loss: 2.0429 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0429 2023/06/05 12:23:40 - mmengine - INFO - Epoch(train) [105][1160/2569] lr: 4.0000e-03 eta: 8:38:36 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 3.5790 loss: 1.6669 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6669 2023/06/05 12:23:45 - mmengine - INFO - Epoch(train) [105][1180/2569] lr: 4.0000e-03 eta: 8:38:31 time: 0.2661 data_time: 0.0074 memory: 5828 grad_norm: 3.5896 loss: 2.1530 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1530 2023/06/05 12:23:50 - mmengine - INFO - Epoch(train) [105][1200/2569] lr: 4.0000e-03 eta: 8:38:25 time: 0.2605 data_time: 0.0078 memory: 5828 grad_norm: 3.5885 loss: 1.9358 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9358 2023/06/05 12:23:56 - mmengine - INFO - Epoch(train) [105][1220/2569] lr: 4.0000e-03 eta: 8:38:20 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 3.5601 loss: 1.7895 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7895 2023/06/05 12:24:01 - mmengine - INFO - Epoch(train) [105][1240/2569] lr: 4.0000e-03 eta: 8:38:15 time: 0.2667 data_time: 0.0069 memory: 5828 grad_norm: 3.5824 loss: 1.8835 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8835 2023/06/05 12:24:06 - mmengine - INFO - Epoch(train) [105][1260/2569] lr: 4.0000e-03 eta: 8:38:09 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 3.5965 loss: 1.7136 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7136 2023/06/05 12:24:12 - mmengine - INFO - Epoch(train) [105][1280/2569] lr: 4.0000e-03 eta: 8:38:04 time: 0.2719 data_time: 0.0079 memory: 5828 grad_norm: 3.6441 loss: 1.9810 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.9810 2023/06/05 12:24:17 - mmengine - INFO - Epoch(train) [105][1300/2569] lr: 4.0000e-03 eta: 8:37:59 time: 0.2629 data_time: 0.0071 memory: 5828 grad_norm: 3.5717 loss: 1.9896 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9896 2023/06/05 12:24:23 - mmengine - INFO - Epoch(train) [105][1320/2569] lr: 4.0000e-03 eta: 8:37:53 time: 0.2740 data_time: 0.0072 memory: 5828 grad_norm: 3.5636 loss: 1.7730 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7730 2023/06/05 12:24:28 - mmengine - INFO - Epoch(train) [105][1340/2569] lr: 4.0000e-03 eta: 8:37:48 time: 0.2735 data_time: 0.0071 memory: 5828 grad_norm: 3.6204 loss: 2.1915 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1915 2023/06/05 12:24:33 - mmengine - INFO - Epoch(train) [105][1360/2569] lr: 4.0000e-03 eta: 8:37:43 time: 0.2724 data_time: 0.0076 memory: 5828 grad_norm: 3.5832 loss: 2.1081 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1081 2023/06/05 12:24:39 - mmengine - INFO - Epoch(train) [105][1380/2569] lr: 4.0000e-03 eta: 8:37:38 time: 0.2693 data_time: 0.0099 memory: 5828 grad_norm: 3.5558 loss: 2.0277 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0277 2023/06/05 12:24:44 - mmengine - INFO - Epoch(train) [105][1400/2569] lr: 4.0000e-03 eta: 8:37:32 time: 0.2713 data_time: 0.0071 memory: 5828 grad_norm: 3.5839 loss: 2.0368 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0368 2023/06/05 12:24:50 - mmengine - INFO - Epoch(train) [105][1420/2569] lr: 4.0000e-03 eta: 8:37:27 time: 0.2721 data_time: 0.0071 memory: 5828 grad_norm: 3.5948 loss: 1.9756 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9756 2023/06/05 12:24:55 - mmengine - INFO - Epoch(train) [105][1440/2569] lr: 4.0000e-03 eta: 8:37:22 time: 0.2688 data_time: 0.0072 memory: 5828 grad_norm: 3.5953 loss: 2.2116 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2116 2023/06/05 12:25:01 - mmengine - INFO - Epoch(train) [105][1460/2569] lr: 4.0000e-03 eta: 8:37:17 time: 0.2784 data_time: 0.0074 memory: 5828 grad_norm: 3.5018 loss: 1.7232 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7232 2023/06/05 12:25:06 - mmengine - INFO - Epoch(train) [105][1480/2569] lr: 4.0000e-03 eta: 8:37:11 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 3.6128 loss: 1.7527 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7527 2023/06/05 12:25:12 - mmengine - INFO - Epoch(train) [105][1500/2569] lr: 4.0000e-03 eta: 8:37:06 time: 0.2716 data_time: 0.0071 memory: 5828 grad_norm: 3.6278 loss: 1.9226 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9226 2023/06/05 12:25:17 - mmengine - INFO - Epoch(train) [105][1520/2569] lr: 4.0000e-03 eta: 8:37:01 time: 0.2630 data_time: 0.0073 memory: 5828 grad_norm: 3.6044 loss: 1.7848 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7848 2023/06/05 12:25:22 - mmengine - INFO - Epoch(train) [105][1540/2569] lr: 4.0000e-03 eta: 8:36:55 time: 0.2608 data_time: 0.0075 memory: 5828 grad_norm: 3.5719 loss: 2.2374 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2374 2023/06/05 12:25:27 - mmengine - INFO - Epoch(train) [105][1560/2569] lr: 4.0000e-03 eta: 8:36:50 time: 0.2611 data_time: 0.0072 memory: 5828 grad_norm: 3.4993 loss: 1.9544 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9544 2023/06/05 12:25:33 - mmengine - INFO - Epoch(train) [105][1580/2569] lr: 4.0000e-03 eta: 8:36:45 time: 0.2754 data_time: 0.0073 memory: 5828 grad_norm: 3.5449 loss: 1.9434 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 1.9434 2023/06/05 12:25:38 - mmengine - INFO - Epoch(train) [105][1600/2569] lr: 4.0000e-03 eta: 8:36:39 time: 0.2653 data_time: 0.0076 memory: 5828 grad_norm: 3.6236 loss: 1.9544 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9544 2023/06/05 12:25:43 - mmengine - INFO - Epoch(train) [105][1620/2569] lr: 4.0000e-03 eta: 8:36:34 time: 0.2607 data_time: 0.0072 memory: 5828 grad_norm: 3.6088 loss: 1.4872 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4872 2023/06/05 12:25:49 - mmengine - INFO - Epoch(train) [105][1640/2569] lr: 4.0000e-03 eta: 8:36:29 time: 0.2661 data_time: 0.0089 memory: 5828 grad_norm: 3.5848 loss: 1.5863 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5863 2023/06/05 12:25:54 - mmengine - INFO - Epoch(train) [105][1660/2569] lr: 4.0000e-03 eta: 8:36:23 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 3.5718 loss: 1.8316 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8316 2023/06/05 12:25:59 - mmengine - INFO - Epoch(train) [105][1680/2569] lr: 4.0000e-03 eta: 8:36:18 time: 0.2644 data_time: 0.0078 memory: 5828 grad_norm: 3.6071 loss: 1.8600 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8600 2023/06/05 12:26:05 - mmengine - INFO - Epoch(train) [105][1700/2569] lr: 4.0000e-03 eta: 8:36:13 time: 0.2730 data_time: 0.0069 memory: 5828 grad_norm: 3.5669 loss: 1.8583 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8583 2023/06/05 12:26:10 - mmengine - INFO - Epoch(train) [105][1720/2569] lr: 4.0000e-03 eta: 8:36:08 time: 0.2760 data_time: 0.0073 memory: 5828 grad_norm: 3.6228 loss: 1.7039 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7039 2023/06/05 12:26:15 - mmengine - INFO - Epoch(train) [105][1740/2569] lr: 4.0000e-03 eta: 8:36:02 time: 0.2600 data_time: 0.0074 memory: 5828 grad_norm: 3.6464 loss: 1.7013 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7013 2023/06/05 12:26:21 - mmengine - INFO - Epoch(train) [105][1760/2569] lr: 4.0000e-03 eta: 8:35:57 time: 0.2608 data_time: 0.0075 memory: 5828 grad_norm: 3.6487 loss: 1.8292 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8292 2023/06/05 12:26:26 - mmengine - INFO - Epoch(train) [105][1780/2569] lr: 4.0000e-03 eta: 8:35:51 time: 0.2594 data_time: 0.0073 memory: 5828 grad_norm: 3.6147 loss: 1.6943 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6943 2023/06/05 12:26:31 - mmengine - INFO - Epoch(train) [105][1800/2569] lr: 4.0000e-03 eta: 8:35:46 time: 0.2608 data_time: 0.0081 memory: 5828 grad_norm: 3.6213 loss: 2.1757 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1757 2023/06/05 12:26:36 - mmengine - INFO - Epoch(train) [105][1820/2569] lr: 4.0000e-03 eta: 8:35:41 time: 0.2616 data_time: 0.0072 memory: 5828 grad_norm: 3.5737 loss: 1.8712 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8712 2023/06/05 12:26:37 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:26:42 - mmengine - INFO - Epoch(train) [105][1840/2569] lr: 4.0000e-03 eta: 8:35:36 time: 0.2781 data_time: 0.0071 memory: 5828 grad_norm: 3.5871 loss: 2.0179 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0179 2023/06/05 12:26:47 - mmengine - INFO - Epoch(train) [105][1860/2569] lr: 4.0000e-03 eta: 8:35:30 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 3.5311 loss: 2.0773 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 2.0773 2023/06/05 12:26:53 - mmengine - INFO - Epoch(train) [105][1880/2569] lr: 4.0000e-03 eta: 8:35:25 time: 0.2697 data_time: 0.0073 memory: 5828 grad_norm: 3.6300 loss: 1.8717 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8717 2023/06/05 12:26:58 - mmengine - INFO - Epoch(train) [105][1900/2569] lr: 4.0000e-03 eta: 8:35:20 time: 0.2607 data_time: 0.0073 memory: 5828 grad_norm: 3.6279 loss: 2.1143 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1143 2023/06/05 12:27:03 - mmengine - INFO - Epoch(train) [105][1920/2569] lr: 4.0000e-03 eta: 8:35:14 time: 0.2704 data_time: 0.0081 memory: 5828 grad_norm: 3.5982 loss: 1.8469 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8469 2023/06/05 12:27:09 - mmengine - INFO - Epoch(train) [105][1940/2569] lr: 4.0000e-03 eta: 8:35:09 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 3.5558 loss: 1.9048 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9048 2023/06/05 12:27:14 - mmengine - INFO - Epoch(train) [105][1960/2569] lr: 4.0000e-03 eta: 8:35:04 time: 0.2669 data_time: 0.0072 memory: 5828 grad_norm: 3.5727 loss: 2.1588 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1588 2023/06/05 12:27:19 - mmengine - INFO - Epoch(train) [105][1980/2569] lr: 4.0000e-03 eta: 8:34:58 time: 0.2664 data_time: 0.0072 memory: 5828 grad_norm: 3.5916 loss: 1.8948 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8948 2023/06/05 12:27:25 - mmengine - INFO - Epoch(train) [105][2000/2569] lr: 4.0000e-03 eta: 8:34:53 time: 0.2729 data_time: 0.0072 memory: 5828 grad_norm: 3.6413 loss: 1.8114 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8114 2023/06/05 12:27:30 - mmengine - INFO - Epoch(train) [105][2020/2569] lr: 4.0000e-03 eta: 8:34:48 time: 0.2620 data_time: 0.0074 memory: 5828 grad_norm: 3.6171 loss: 1.7709 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7709 2023/06/05 12:27:35 - mmengine - INFO - Epoch(train) [105][2040/2569] lr: 4.0000e-03 eta: 8:34:42 time: 0.2662 data_time: 0.0076 memory: 5828 grad_norm: 3.6149 loss: 1.6180 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6180 2023/06/05 12:27:41 - mmengine - INFO - Epoch(train) [105][2060/2569] lr: 4.0000e-03 eta: 8:34:37 time: 0.2643 data_time: 0.0068 memory: 5828 grad_norm: 3.5615 loss: 1.6852 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6852 2023/06/05 12:27:46 - mmengine - INFO - Epoch(train) [105][2080/2569] lr: 4.0000e-03 eta: 8:34:32 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 3.5694 loss: 1.6070 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6070 2023/06/05 12:27:51 - mmengine - INFO - Epoch(train) [105][2100/2569] lr: 4.0000e-03 eta: 8:34:26 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 3.6105 loss: 1.6451 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6451 2023/06/05 12:27:57 - mmengine - INFO - Epoch(train) [105][2120/2569] lr: 4.0000e-03 eta: 8:34:21 time: 0.2683 data_time: 0.0074 memory: 5828 grad_norm: 3.6861 loss: 1.9107 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9107 2023/06/05 12:28:02 - mmengine - INFO - Epoch(train) [105][2140/2569] lr: 4.0000e-03 eta: 8:34:16 time: 0.2705 data_time: 0.0080 memory: 5828 grad_norm: 3.6012 loss: 1.8664 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8664 2023/06/05 12:28:08 - mmengine - INFO - Epoch(train) [105][2160/2569] lr: 4.0000e-03 eta: 8:34:11 time: 0.2688 data_time: 0.0068 memory: 5828 grad_norm: 3.6470 loss: 1.8304 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8304 2023/06/05 12:28:13 - mmengine - INFO - Epoch(train) [105][2180/2569] lr: 4.0000e-03 eta: 8:34:05 time: 0.2600 data_time: 0.0072 memory: 5828 grad_norm: 3.6039 loss: 2.0540 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0540 2023/06/05 12:28:18 - mmengine - INFO - Epoch(train) [105][2200/2569] lr: 4.0000e-03 eta: 8:34:00 time: 0.2708 data_time: 0.0074 memory: 5828 grad_norm: 3.5893 loss: 1.6512 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6512 2023/06/05 12:28:24 - mmengine - INFO - Epoch(train) [105][2220/2569] lr: 4.0000e-03 eta: 8:33:55 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 3.5122 loss: 1.7234 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7234 2023/06/05 12:28:29 - mmengine - INFO - Epoch(train) [105][2240/2569] lr: 4.0000e-03 eta: 8:33:49 time: 0.2737 data_time: 0.0072 memory: 5828 grad_norm: 3.5555 loss: 1.7863 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7863 2023/06/05 12:28:34 - mmengine - INFO - Epoch(train) [105][2260/2569] lr: 4.0000e-03 eta: 8:33:44 time: 0.2676 data_time: 0.0073 memory: 5828 grad_norm: 3.5592 loss: 2.0009 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0009 2023/06/05 12:28:40 - mmengine - INFO - Epoch(train) [105][2280/2569] lr: 4.0000e-03 eta: 8:33:39 time: 0.2662 data_time: 0.0074 memory: 5828 grad_norm: 3.5558 loss: 1.9186 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.9186 2023/06/05 12:28:45 - mmengine - INFO - Epoch(train) [105][2300/2569] lr: 4.0000e-03 eta: 8:33:33 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 3.5560 loss: 1.7785 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7785 2023/06/05 12:28:50 - mmengine - INFO - Epoch(train) [105][2320/2569] lr: 4.0000e-03 eta: 8:33:28 time: 0.2593 data_time: 0.0070 memory: 5828 grad_norm: 3.5778 loss: 1.8135 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8135 2023/06/05 12:28:55 - mmengine - INFO - Epoch(train) [105][2340/2569] lr: 4.0000e-03 eta: 8:33:23 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 3.5823 loss: 1.9054 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9054 2023/06/05 12:29:01 - mmengine - INFO - Epoch(train) [105][2360/2569] lr: 4.0000e-03 eta: 8:33:17 time: 0.2671 data_time: 0.0069 memory: 5828 grad_norm: 3.6062 loss: 1.9544 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9544 2023/06/05 12:29:06 - mmengine - INFO - Epoch(train) [105][2380/2569] lr: 4.0000e-03 eta: 8:33:12 time: 0.2594 data_time: 0.0072 memory: 5828 grad_norm: 3.5932 loss: 1.9806 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9806 2023/06/05 12:29:11 - mmengine - INFO - Epoch(train) [105][2400/2569] lr: 4.0000e-03 eta: 8:33:07 time: 0.2588 data_time: 0.0072 memory: 5828 grad_norm: 3.6375 loss: 2.0218 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0218 2023/06/05 12:29:16 - mmengine - INFO - Epoch(train) [105][2420/2569] lr: 4.0000e-03 eta: 8:33:01 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 3.6889 loss: 1.9797 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9797 2023/06/05 12:29:22 - mmengine - INFO - Epoch(train) [105][2440/2569] lr: 4.0000e-03 eta: 8:32:56 time: 0.2658 data_time: 0.0071 memory: 5828 grad_norm: 3.5704 loss: 2.0158 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0158 2023/06/05 12:29:27 - mmengine - INFO - Epoch(train) [105][2460/2569] lr: 4.0000e-03 eta: 8:32:51 time: 0.2610 data_time: 0.0073 memory: 5828 grad_norm: 3.5803 loss: 1.5711 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5711 2023/06/05 12:29:32 - mmengine - INFO - Epoch(train) [105][2480/2569] lr: 4.0000e-03 eta: 8:32:45 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 3.6154 loss: 2.0635 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0635 2023/06/05 12:29:38 - mmengine - INFO - Epoch(train) [105][2500/2569] lr: 4.0000e-03 eta: 8:32:40 time: 0.2685 data_time: 0.0069 memory: 5828 grad_norm: 3.5688 loss: 1.8358 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8358 2023/06/05 12:29:43 - mmengine - INFO - Epoch(train) [105][2520/2569] lr: 4.0000e-03 eta: 8:32:35 time: 0.2738 data_time: 0.0072 memory: 5828 grad_norm: 3.6683 loss: 2.2515 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2515 2023/06/05 12:29:48 - mmengine - INFO - Epoch(train) [105][2540/2569] lr: 4.0000e-03 eta: 8:32:29 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 3.6096 loss: 1.8868 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8868 2023/06/05 12:29:54 - mmengine - INFO - Epoch(train) [105][2560/2569] lr: 4.0000e-03 eta: 8:32:24 time: 0.2737 data_time: 0.0072 memory: 5828 grad_norm: 3.6696 loss: 1.9687 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9687 2023/06/05 12:29:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:29:56 - mmengine - INFO - Epoch(train) [105][2569/2569] lr: 4.0000e-03 eta: 8:32:22 time: 0.2581 data_time: 0.0067 memory: 5828 grad_norm: 3.7022 loss: 2.0523 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0523 2023/06/05 12:30:00 - mmengine - INFO - Epoch(val) [105][ 20/260] eta: 0:00:44 time: 0.1850 data_time: 0.1264 memory: 1238 2023/06/05 12:30:03 - mmengine - INFO - Epoch(val) [105][ 40/260] eta: 0:00:36 time: 0.1508 data_time: 0.0919 memory: 1238 2023/06/05 12:30:05 - mmengine - INFO - Epoch(val) [105][ 60/260] eta: 0:00:31 time: 0.1301 data_time: 0.0711 memory: 1238 2023/06/05 12:30:08 - mmengine - INFO - Epoch(val) [105][ 80/260] eta: 0:00:26 time: 0.1331 data_time: 0.0740 memory: 1238 2023/06/05 12:30:11 - mmengine - INFO - Epoch(val) [105][100/260] eta: 0:00:23 time: 0.1352 data_time: 0.0768 memory: 1238 2023/06/05 12:30:14 - mmengine - INFO - Epoch(val) [105][120/260] eta: 0:00:20 time: 0.1426 data_time: 0.0841 memory: 1238 2023/06/05 12:30:16 - mmengine - INFO - Epoch(val) [105][140/260] eta: 0:00:17 time: 0.1229 data_time: 0.0645 memory: 1238 2023/06/05 12:30:19 - mmengine - INFO - Epoch(val) [105][160/260] eta: 0:00:14 time: 0.1519 data_time: 0.0936 memory: 1238 2023/06/05 12:30:22 - mmengine - INFO - Epoch(val) [105][180/260] eta: 0:00:11 time: 0.1341 data_time: 0.0754 memory: 1238 2023/06/05 12:30:24 - mmengine - INFO - Epoch(val) [105][200/260] eta: 0:00:08 time: 0.1358 data_time: 0.0769 memory: 1238 2023/06/05 12:30:27 - mmengine - INFO - Epoch(val) [105][220/260] eta: 0:00:05 time: 0.1452 data_time: 0.0868 memory: 1238 2023/06/05 12:30:30 - mmengine - INFO - Epoch(val) [105][240/260] eta: 0:00:02 time: 0.1319 data_time: 0.0729 memory: 1238 2023/06/05 12:30:33 - mmengine - INFO - Epoch(val) [105][260/260] eta: 0:00:00 time: 0.1415 data_time: 0.0842 memory: 1238 2023/06/05 12:30:40 - mmengine - INFO - Epoch(val) [105][260/260] acc/top1: 0.6032 acc/top5: 0.8211 acc/mean1: 0.5961 data_time: 0.0827 time: 0.1412 2023/06/05 12:30:40 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_90.pth is removed 2023/06/05 12:30:42 - mmengine - INFO - The best checkpoint with 0.6032 acc/top1 at 105 epoch is saved to best_acc_top1_epoch_105.pth. 2023/06/05 12:30:48 - mmengine - INFO - Epoch(train) [106][ 20/2569] lr: 4.0000e-03 eta: 8:32:17 time: 0.3037 data_time: 0.0490 memory: 5828 grad_norm: 3.6510 loss: 1.8165 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8165 2023/06/05 12:30:53 - mmengine - INFO - Epoch(train) [106][ 40/2569] lr: 4.0000e-03 eta: 8:32:11 time: 0.2593 data_time: 0.0076 memory: 5828 grad_norm: 3.7058 loss: 1.6089 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6089 2023/06/05 12:30:59 - mmengine - INFO - Epoch(train) [106][ 60/2569] lr: 4.0000e-03 eta: 8:32:06 time: 0.2669 data_time: 0.0080 memory: 5828 grad_norm: 3.6401 loss: 1.9867 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9867 2023/06/05 12:31:04 - mmengine - INFO - Epoch(train) [106][ 80/2569] lr: 4.0000e-03 eta: 8:32:01 time: 0.2685 data_time: 0.0079 memory: 5828 grad_norm: 3.6596 loss: 1.9866 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9866 2023/06/05 12:31:09 - mmengine - INFO - Epoch(train) [106][ 100/2569] lr: 4.0000e-03 eta: 8:31:55 time: 0.2619 data_time: 0.0074 memory: 5828 grad_norm: 3.6119 loss: 1.6609 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6609 2023/06/05 12:31:15 - mmengine - INFO - Epoch(train) [106][ 120/2569] lr: 4.0000e-03 eta: 8:31:50 time: 0.2735 data_time: 0.0073 memory: 5828 grad_norm: 3.6819 loss: 2.0410 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0410 2023/06/05 12:31:20 - mmengine - INFO - Epoch(train) [106][ 140/2569] lr: 4.0000e-03 eta: 8:31:45 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 3.6540 loss: 1.8668 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.8668 2023/06/05 12:31:25 - mmengine - INFO - Epoch(train) [106][ 160/2569] lr: 4.0000e-03 eta: 8:31:39 time: 0.2628 data_time: 0.0071 memory: 5828 grad_norm: 3.6221 loss: 1.9453 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9453 2023/06/05 12:31:31 - mmengine - INFO - Epoch(train) [106][ 180/2569] lr: 4.0000e-03 eta: 8:31:34 time: 0.2810 data_time: 0.0074 memory: 5828 grad_norm: 3.6323 loss: 2.1035 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1035 2023/06/05 12:31:36 - mmengine - INFO - Epoch(train) [106][ 200/2569] lr: 4.0000e-03 eta: 8:31:29 time: 0.2653 data_time: 0.0072 memory: 5828 grad_norm: 3.7383 loss: 2.0353 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0353 2023/06/05 12:31:42 - mmengine - INFO - Epoch(train) [106][ 220/2569] lr: 4.0000e-03 eta: 8:31:24 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 3.5988 loss: 1.9961 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9961 2023/06/05 12:31:47 - mmengine - INFO - Epoch(train) [106][ 240/2569] lr: 4.0000e-03 eta: 8:31:18 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 3.6343 loss: 1.7607 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7607 2023/06/05 12:31:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:31:52 - mmengine - INFO - Epoch(train) [106][ 260/2569] lr: 4.0000e-03 eta: 8:31:13 time: 0.2620 data_time: 0.0081 memory: 5828 grad_norm: 3.6408 loss: 1.9840 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9840 2023/06/05 12:31:58 - mmengine - INFO - Epoch(train) [106][ 280/2569] lr: 4.0000e-03 eta: 8:31:08 time: 0.2728 data_time: 0.0074 memory: 5828 grad_norm: 3.6346 loss: 1.9035 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9035 2023/06/05 12:32:03 - mmengine - INFO - Epoch(train) [106][ 300/2569] lr: 4.0000e-03 eta: 8:31:02 time: 0.2605 data_time: 0.0076 memory: 5828 grad_norm: 3.5904 loss: 1.8495 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8495 2023/06/05 12:32:09 - mmengine - INFO - Epoch(train) [106][ 320/2569] lr: 4.0000e-03 eta: 8:30:57 time: 0.2665 data_time: 0.0075 memory: 5828 grad_norm: 3.6231 loss: 1.9192 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9192 2023/06/05 12:32:14 - mmengine - INFO - Epoch(train) [106][ 340/2569] lr: 4.0000e-03 eta: 8:30:52 time: 0.2608 data_time: 0.0074 memory: 5828 grad_norm: 3.6470 loss: 1.8058 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8058 2023/06/05 12:32:19 - mmengine - INFO - Epoch(train) [106][ 360/2569] lr: 4.0000e-03 eta: 8:30:46 time: 0.2661 data_time: 0.0071 memory: 5828 grad_norm: 3.6656 loss: 1.8815 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8815 2023/06/05 12:32:24 - mmengine - INFO - Epoch(train) [106][ 380/2569] lr: 4.0000e-03 eta: 8:30:41 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 3.5798 loss: 1.4877 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4877 2023/06/05 12:32:30 - mmengine - INFO - Epoch(train) [106][ 400/2569] lr: 4.0000e-03 eta: 8:30:36 time: 0.2715 data_time: 0.0068 memory: 5828 grad_norm: 3.7285 loss: 1.7741 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7741 2023/06/05 12:32:35 - mmengine - INFO - Epoch(train) [106][ 420/2569] lr: 4.0000e-03 eta: 8:30:31 time: 0.2744 data_time: 0.0069 memory: 5828 grad_norm: 3.7294 loss: 1.7287 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7287 2023/06/05 12:32:41 - mmengine - INFO - Epoch(train) [106][ 440/2569] lr: 4.0000e-03 eta: 8:30:25 time: 0.2615 data_time: 0.0069 memory: 5828 grad_norm: 3.6352 loss: 1.7968 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7968 2023/06/05 12:32:46 - mmengine - INFO - Epoch(train) [106][ 460/2569] lr: 4.0000e-03 eta: 8:30:20 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 3.6213 loss: 1.7724 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7724 2023/06/05 12:32:51 - mmengine - INFO - Epoch(train) [106][ 480/2569] lr: 4.0000e-03 eta: 8:30:15 time: 0.2640 data_time: 0.0072 memory: 5828 grad_norm: 3.6410 loss: 1.9495 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9495 2023/06/05 12:32:57 - mmengine - INFO - Epoch(train) [106][ 500/2569] lr: 4.0000e-03 eta: 8:30:09 time: 0.2662 data_time: 0.0070 memory: 5828 grad_norm: 3.5507 loss: 2.1784 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1784 2023/06/05 12:33:02 - mmengine - INFO - Epoch(train) [106][ 520/2569] lr: 4.0000e-03 eta: 8:30:04 time: 0.2703 data_time: 0.0067 memory: 5828 grad_norm: 3.7033 loss: 2.0680 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0680 2023/06/05 12:33:07 - mmengine - INFO - Epoch(train) [106][ 540/2569] lr: 4.0000e-03 eta: 8:29:59 time: 0.2626 data_time: 0.0086 memory: 5828 grad_norm: 3.6374 loss: 2.0188 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0188 2023/06/05 12:33:13 - mmengine - INFO - Epoch(train) [106][ 560/2569] lr: 4.0000e-03 eta: 8:29:53 time: 0.2641 data_time: 0.0067 memory: 5828 grad_norm: 3.6202 loss: 1.9253 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9253 2023/06/05 12:33:18 - mmengine - INFO - Epoch(train) [106][ 580/2569] lr: 4.0000e-03 eta: 8:29:48 time: 0.2679 data_time: 0.0071 memory: 5828 grad_norm: 3.6883 loss: 1.9044 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9044 2023/06/05 12:33:23 - mmengine - INFO - Epoch(train) [106][ 600/2569] lr: 4.0000e-03 eta: 8:29:43 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 3.6538 loss: 1.7612 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7612 2023/06/05 12:33:29 - mmengine - INFO - Epoch(train) [106][ 620/2569] lr: 4.0000e-03 eta: 8:29:37 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 3.6130 loss: 1.9787 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9787 2023/06/05 12:33:34 - mmengine - INFO - Epoch(train) [106][ 640/2569] lr: 4.0000e-03 eta: 8:29:32 time: 0.2657 data_time: 0.0073 memory: 5828 grad_norm: 3.6185 loss: 1.9344 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9344 2023/06/05 12:33:39 - mmengine - INFO - Epoch(train) [106][ 660/2569] lr: 4.0000e-03 eta: 8:29:27 time: 0.2708 data_time: 0.0074 memory: 5828 grad_norm: 3.6111 loss: 1.5219 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5219 2023/06/05 12:33:45 - mmengine - INFO - Epoch(train) [106][ 680/2569] lr: 4.0000e-03 eta: 8:29:21 time: 0.2624 data_time: 0.0071 memory: 5828 grad_norm: 3.6970 loss: 1.8328 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8328 2023/06/05 12:33:50 - mmengine - INFO - Epoch(train) [106][ 700/2569] lr: 4.0000e-03 eta: 8:29:16 time: 0.2632 data_time: 0.0083 memory: 5828 grad_norm: 3.6466 loss: 1.7780 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7780 2023/06/05 12:33:55 - mmengine - INFO - Epoch(train) [106][ 720/2569] lr: 4.0000e-03 eta: 8:29:11 time: 0.2730 data_time: 0.0075 memory: 5828 grad_norm: 3.6346 loss: 1.9836 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9836 2023/06/05 12:34:01 - mmengine - INFO - Epoch(train) [106][ 740/2569] lr: 4.0000e-03 eta: 8:29:05 time: 0.2629 data_time: 0.0069 memory: 5828 grad_norm: 3.5859 loss: 1.9064 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9064 2023/06/05 12:34:06 - mmengine - INFO - Epoch(train) [106][ 760/2569] lr: 4.0000e-03 eta: 8:29:00 time: 0.2661 data_time: 0.0073 memory: 5828 grad_norm: 3.6111 loss: 1.8185 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8185 2023/06/05 12:34:11 - mmengine - INFO - Epoch(train) [106][ 780/2569] lr: 4.0000e-03 eta: 8:28:55 time: 0.2699 data_time: 0.0072 memory: 5828 grad_norm: 3.6306 loss: 2.0115 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0115 2023/06/05 12:34:17 - mmengine - INFO - Epoch(train) [106][ 800/2569] lr: 4.0000e-03 eta: 8:28:50 time: 0.2665 data_time: 0.0076 memory: 5828 grad_norm: 3.6668 loss: 1.8381 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8381 2023/06/05 12:34:22 - mmengine - INFO - Epoch(train) [106][ 820/2569] lr: 4.0000e-03 eta: 8:28:44 time: 0.2783 data_time: 0.0073 memory: 5828 grad_norm: 3.6009 loss: 1.8311 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8311 2023/06/05 12:34:28 - mmengine - INFO - Epoch(train) [106][ 840/2569] lr: 4.0000e-03 eta: 8:28:39 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 3.6497 loss: 2.2984 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2984 2023/06/05 12:34:33 - mmengine - INFO - Epoch(train) [106][ 860/2569] lr: 4.0000e-03 eta: 8:28:34 time: 0.2665 data_time: 0.0078 memory: 5828 grad_norm: 3.6434 loss: 1.7279 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7279 2023/06/05 12:34:38 - mmengine - INFO - Epoch(train) [106][ 880/2569] lr: 4.0000e-03 eta: 8:28:28 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 3.5620 loss: 2.0088 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0088 2023/06/05 12:34:44 - mmengine - INFO - Epoch(train) [106][ 900/2569] lr: 4.0000e-03 eta: 8:28:23 time: 0.2672 data_time: 0.0072 memory: 5828 grad_norm: 3.6687 loss: 1.9931 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9931 2023/06/05 12:34:49 - mmengine - INFO - Epoch(train) [106][ 920/2569] lr: 4.0000e-03 eta: 8:28:18 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 3.6154 loss: 1.8424 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8424 2023/06/05 12:34:54 - mmengine - INFO - Epoch(train) [106][ 940/2569] lr: 4.0000e-03 eta: 8:28:12 time: 0.2758 data_time: 0.0072 memory: 5828 grad_norm: 3.6676 loss: 1.9346 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9346 2023/06/05 12:35:00 - mmengine - INFO - Epoch(train) [106][ 960/2569] lr: 4.0000e-03 eta: 8:28:07 time: 0.2630 data_time: 0.0072 memory: 5828 grad_norm: 3.6354 loss: 1.8570 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8570 2023/06/05 12:35:05 - mmengine - INFO - Epoch(train) [106][ 980/2569] lr: 4.0000e-03 eta: 8:28:02 time: 0.2822 data_time: 0.0071 memory: 5828 grad_norm: 3.6472 loss: 1.7661 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7661 2023/06/05 12:35:11 - mmengine - INFO - Epoch(train) [106][1000/2569] lr: 4.0000e-03 eta: 8:27:57 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 3.5584 loss: 2.0116 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0116 2023/06/05 12:35:16 - mmengine - INFO - Epoch(train) [106][1020/2569] lr: 4.0000e-03 eta: 8:27:51 time: 0.2694 data_time: 0.0073 memory: 5828 grad_norm: 3.6489 loss: 1.6987 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6987 2023/06/05 12:35:21 - mmengine - INFO - Epoch(train) [106][1040/2569] lr: 4.0000e-03 eta: 8:27:46 time: 0.2653 data_time: 0.0072 memory: 5828 grad_norm: 3.6760 loss: 1.7255 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7255 2023/06/05 12:35:27 - mmengine - INFO - Epoch(train) [106][1060/2569] lr: 4.0000e-03 eta: 8:27:41 time: 0.2764 data_time: 0.0070 memory: 5828 grad_norm: 3.7050 loss: 1.5725 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.5725 2023/06/05 12:35:32 - mmengine - INFO - Epoch(train) [106][1080/2569] lr: 4.0000e-03 eta: 8:27:35 time: 0.2740 data_time: 0.0071 memory: 5828 grad_norm: 3.6966 loss: 2.1389 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1389 2023/06/05 12:35:38 - mmengine - INFO - Epoch(train) [106][1100/2569] lr: 4.0000e-03 eta: 8:27:30 time: 0.2725 data_time: 0.0069 memory: 5828 grad_norm: 3.6610 loss: 1.8681 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8681 2023/06/05 12:35:43 - mmengine - INFO - Epoch(train) [106][1120/2569] lr: 4.0000e-03 eta: 8:27:25 time: 0.2670 data_time: 0.0070 memory: 5828 grad_norm: 3.6573 loss: 2.0279 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0279 2023/06/05 12:35:48 - mmengine - INFO - Epoch(train) [106][1140/2569] lr: 4.0000e-03 eta: 8:27:20 time: 0.2636 data_time: 0.0081 memory: 5828 grad_norm: 3.6121 loss: 2.0038 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0038 2023/06/05 12:35:54 - mmengine - INFO - Epoch(train) [106][1160/2569] lr: 4.0000e-03 eta: 8:27:14 time: 0.2620 data_time: 0.0087 memory: 5828 grad_norm: 3.7563 loss: 1.7071 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7071 2023/06/05 12:35:59 - mmengine - INFO - Epoch(train) [106][1180/2569] lr: 4.0000e-03 eta: 8:27:09 time: 0.2680 data_time: 0.0070 memory: 5828 grad_norm: 3.7441 loss: 1.7775 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7775 2023/06/05 12:36:04 - mmengine - INFO - Epoch(train) [106][1200/2569] lr: 4.0000e-03 eta: 8:27:04 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 3.7089 loss: 1.8534 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8534 2023/06/05 12:36:10 - mmengine - INFO - Epoch(train) [106][1220/2569] lr: 4.0000e-03 eta: 8:26:58 time: 0.2664 data_time: 0.0069 memory: 5828 grad_norm: 3.6219 loss: 2.4728 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.4728 2023/06/05 12:36:15 - mmengine - INFO - Epoch(train) [106][1240/2569] lr: 4.0000e-03 eta: 8:26:53 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.7164 loss: 1.8791 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8791 2023/06/05 12:36:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:36:20 - mmengine - INFO - Epoch(train) [106][1260/2569] lr: 4.0000e-03 eta: 8:26:48 time: 0.2647 data_time: 0.0070 memory: 5828 grad_norm: 3.7207 loss: 1.9206 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9206 2023/06/05 12:36:26 - mmengine - INFO - Epoch(train) [106][1280/2569] lr: 4.0000e-03 eta: 8:26:42 time: 0.2643 data_time: 0.0075 memory: 5828 grad_norm: 3.7451 loss: 2.0342 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0342 2023/06/05 12:36:31 - mmengine - INFO - Epoch(train) [106][1300/2569] lr: 4.0000e-03 eta: 8:26:37 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 3.7027 loss: 2.0082 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0082 2023/06/05 12:36:36 - mmengine - INFO - Epoch(train) [106][1320/2569] lr: 4.0000e-03 eta: 8:26:32 time: 0.2651 data_time: 0.0078 memory: 5828 grad_norm: 3.6722 loss: 1.8760 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8760 2023/06/05 12:36:41 - mmengine - INFO - Epoch(train) [106][1340/2569] lr: 4.0000e-03 eta: 8:26:26 time: 0.2633 data_time: 0.0072 memory: 5828 grad_norm: 3.6395 loss: 1.7750 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7750 2023/06/05 12:36:47 - mmengine - INFO - Epoch(train) [106][1360/2569] lr: 4.0000e-03 eta: 8:26:21 time: 0.2602 data_time: 0.0073 memory: 5828 grad_norm: 3.6344 loss: 1.9756 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9756 2023/06/05 12:36:52 - mmengine - INFO - Epoch(train) [106][1380/2569] lr: 4.0000e-03 eta: 8:26:16 time: 0.2665 data_time: 0.0071 memory: 5828 grad_norm: 3.6041 loss: 1.8637 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8637 2023/06/05 12:36:57 - mmengine - INFO - Epoch(train) [106][1400/2569] lr: 4.0000e-03 eta: 8:26:10 time: 0.2625 data_time: 0.0069 memory: 5828 grad_norm: 3.5732 loss: 2.2039 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.2039 2023/06/05 12:37:03 - mmengine - INFO - Epoch(train) [106][1420/2569] lr: 4.0000e-03 eta: 8:26:05 time: 0.2704 data_time: 0.0073 memory: 5828 grad_norm: 3.6142 loss: 2.1196 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1196 2023/06/05 12:37:08 - mmengine - INFO - Epoch(train) [106][1440/2569] lr: 4.0000e-03 eta: 8:26:00 time: 0.2609 data_time: 0.0070 memory: 5828 grad_norm: 3.6113 loss: 1.7239 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7239 2023/06/05 12:37:13 - mmengine - INFO - Epoch(train) [106][1460/2569] lr: 4.0000e-03 eta: 8:25:54 time: 0.2731 data_time: 0.0068 memory: 5828 grad_norm: 3.6613 loss: 1.8932 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8932 2023/06/05 12:37:19 - mmengine - INFO - Epoch(train) [106][1480/2569] lr: 4.0000e-03 eta: 8:25:49 time: 0.2664 data_time: 0.0080 memory: 5828 grad_norm: 3.6808 loss: 1.7541 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7541 2023/06/05 12:37:24 - mmengine - INFO - Epoch(train) [106][1500/2569] lr: 4.0000e-03 eta: 8:25:44 time: 0.2844 data_time: 0.0070 memory: 5828 grad_norm: 3.6689 loss: 2.0466 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0466 2023/06/05 12:37:30 - mmengine - INFO - Epoch(train) [106][1520/2569] lr: 4.0000e-03 eta: 8:25:39 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 3.6890 loss: 2.0112 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0112 2023/06/05 12:37:35 - mmengine - INFO - Epoch(train) [106][1540/2569] lr: 4.0000e-03 eta: 8:25:33 time: 0.2697 data_time: 0.0070 memory: 5828 grad_norm: 3.6587 loss: 2.0296 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0296 2023/06/05 12:37:41 - mmengine - INFO - Epoch(train) [106][1560/2569] lr: 4.0000e-03 eta: 8:25:28 time: 0.2676 data_time: 0.0074 memory: 5828 grad_norm: 3.6438 loss: 1.8139 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8139 2023/06/05 12:37:46 - mmengine - INFO - Epoch(train) [106][1580/2569] lr: 4.0000e-03 eta: 8:25:23 time: 0.2773 data_time: 0.0068 memory: 5828 grad_norm: 3.5890 loss: 1.7770 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7770 2023/06/05 12:37:51 - mmengine - INFO - Epoch(train) [106][1600/2569] lr: 4.0000e-03 eta: 8:25:17 time: 0.2663 data_time: 0.0068 memory: 5828 grad_norm: 3.6745 loss: 2.0807 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0807 2023/06/05 12:37:57 - mmengine - INFO - Epoch(train) [106][1620/2569] lr: 4.0000e-03 eta: 8:25:12 time: 0.2611 data_time: 0.0069 memory: 5828 grad_norm: 3.7059 loss: 2.1018 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1018 2023/06/05 12:38:02 - mmengine - INFO - Epoch(train) [106][1640/2569] lr: 4.0000e-03 eta: 8:25:07 time: 0.2659 data_time: 0.0070 memory: 5828 grad_norm: 3.6618 loss: 2.3438 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3438 2023/06/05 12:38:07 - mmengine - INFO - Epoch(train) [106][1660/2569] lr: 4.0000e-03 eta: 8:25:01 time: 0.2616 data_time: 0.0070 memory: 5828 grad_norm: 3.6508 loss: 2.2498 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2498 2023/06/05 12:38:13 - mmengine - INFO - Epoch(train) [106][1680/2569] lr: 4.0000e-03 eta: 8:24:56 time: 0.2657 data_time: 0.0073 memory: 5828 grad_norm: 3.6933 loss: 2.0205 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0205 2023/06/05 12:38:18 - mmengine - INFO - Epoch(train) [106][1700/2569] lr: 4.0000e-03 eta: 8:24:51 time: 0.2690 data_time: 0.0068 memory: 5828 grad_norm: 3.6954 loss: 2.0076 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0076 2023/06/05 12:38:23 - mmengine - INFO - Epoch(train) [106][1720/2569] lr: 4.0000e-03 eta: 8:24:46 time: 0.2703 data_time: 0.0069 memory: 5828 grad_norm: 3.6275 loss: 1.9863 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9863 2023/06/05 12:38:29 - mmengine - INFO - Epoch(train) [106][1740/2569] lr: 4.0000e-03 eta: 8:24:40 time: 0.2696 data_time: 0.0071 memory: 5828 grad_norm: 3.6183 loss: 1.7609 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7609 2023/06/05 12:38:34 - mmengine - INFO - Epoch(train) [106][1760/2569] lr: 4.0000e-03 eta: 8:24:35 time: 0.2658 data_time: 0.0071 memory: 5828 grad_norm: 3.6911 loss: 1.9691 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9691 2023/06/05 12:38:40 - mmengine - INFO - Epoch(train) [106][1780/2569] lr: 4.0000e-03 eta: 8:24:30 time: 0.2708 data_time: 0.0069 memory: 5828 grad_norm: 3.6450 loss: 2.0965 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.0965 2023/06/05 12:38:45 - mmengine - INFO - Epoch(train) [106][1800/2569] lr: 4.0000e-03 eta: 8:24:24 time: 0.2778 data_time: 0.0070 memory: 5828 grad_norm: 3.6884 loss: 1.7445 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7445 2023/06/05 12:38:51 - mmengine - INFO - Epoch(train) [106][1820/2569] lr: 4.0000e-03 eta: 8:24:19 time: 0.2710 data_time: 0.0071 memory: 5828 grad_norm: 3.7126 loss: 2.3972 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.3972 2023/06/05 12:38:56 - mmengine - INFO - Epoch(train) [106][1840/2569] lr: 4.0000e-03 eta: 8:24:14 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 3.6966 loss: 2.0284 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0284 2023/06/05 12:39:01 - mmengine - INFO - Epoch(train) [106][1860/2569] lr: 4.0000e-03 eta: 8:24:09 time: 0.2719 data_time: 0.0070 memory: 5828 grad_norm: 3.6508 loss: 1.8558 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8558 2023/06/05 12:39:06 - mmengine - INFO - Epoch(train) [106][1880/2569] lr: 4.0000e-03 eta: 8:24:03 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 3.7027 loss: 1.9677 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9677 2023/06/05 12:39:12 - mmengine - INFO - Epoch(train) [106][1900/2569] lr: 4.0000e-03 eta: 8:23:58 time: 0.2713 data_time: 0.0070 memory: 5828 grad_norm: 3.7377 loss: 1.5625 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5625 2023/06/05 12:39:17 - mmengine - INFO - Epoch(train) [106][1920/2569] lr: 4.0000e-03 eta: 8:23:53 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 3.7278 loss: 1.9090 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9090 2023/06/05 12:39:23 - mmengine - INFO - Epoch(train) [106][1940/2569] lr: 4.0000e-03 eta: 8:23:47 time: 0.2729 data_time: 0.0070 memory: 5828 grad_norm: 3.6279 loss: 1.8923 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8923 2023/06/05 12:39:28 - mmengine - INFO - Epoch(train) [106][1960/2569] lr: 4.0000e-03 eta: 8:23:42 time: 0.2667 data_time: 0.0071 memory: 5828 grad_norm: 3.7015 loss: 1.9384 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9384 2023/06/05 12:39:33 - mmengine - INFO - Epoch(train) [106][1980/2569] lr: 4.0000e-03 eta: 8:23:37 time: 0.2661 data_time: 0.0071 memory: 5828 grad_norm: 3.6638 loss: 2.1962 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1962 2023/06/05 12:39:39 - mmengine - INFO - Epoch(train) [106][2000/2569] lr: 4.0000e-03 eta: 8:23:31 time: 0.2626 data_time: 0.0071 memory: 5828 grad_norm: 3.6865 loss: 2.0627 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.0627 2023/06/05 12:39:44 - mmengine - INFO - Epoch(train) [106][2020/2569] lr: 4.0000e-03 eta: 8:23:26 time: 0.2721 data_time: 0.0072 memory: 5828 grad_norm: 3.7386 loss: 2.1397 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1397 2023/06/05 12:39:49 - mmengine - INFO - Epoch(train) [106][2040/2569] lr: 4.0000e-03 eta: 8:23:21 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 3.7044 loss: 2.0653 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0653 2023/06/05 12:39:55 - mmengine - INFO - Epoch(train) [106][2060/2569] lr: 4.0000e-03 eta: 8:23:15 time: 0.2653 data_time: 0.0077 memory: 5828 grad_norm: 3.6733 loss: 1.7733 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7733 2023/06/05 12:40:00 - mmengine - INFO - Epoch(train) [106][2080/2569] lr: 4.0000e-03 eta: 8:23:10 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 3.6884 loss: 1.9773 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9773 2023/06/05 12:40:05 - mmengine - INFO - Epoch(train) [106][2100/2569] lr: 4.0000e-03 eta: 8:23:05 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 3.6735 loss: 1.8447 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8447 2023/06/05 12:40:11 - mmengine - INFO - Epoch(train) [106][2120/2569] lr: 4.0000e-03 eta: 8:22:59 time: 0.2640 data_time: 0.0071 memory: 5828 grad_norm: 3.6823 loss: 2.1971 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1971 2023/06/05 12:40:16 - mmengine - INFO - Epoch(train) [106][2140/2569] lr: 4.0000e-03 eta: 8:22:54 time: 0.2786 data_time: 0.0068 memory: 5828 grad_norm: 3.6968 loss: 1.9410 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9410 2023/06/05 12:40:22 - mmengine - INFO - Epoch(train) [106][2160/2569] lr: 4.0000e-03 eta: 8:22:49 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 3.7439 loss: 2.1779 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1779 2023/06/05 12:40:27 - mmengine - INFO - Epoch(train) [106][2180/2569] lr: 4.0000e-03 eta: 8:22:44 time: 0.2700 data_time: 0.0070 memory: 5828 grad_norm: 3.7041 loss: 1.6203 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6203 2023/06/05 12:40:32 - mmengine - INFO - Epoch(train) [106][2200/2569] lr: 4.0000e-03 eta: 8:22:38 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 3.6607 loss: 1.8593 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8593 2023/06/05 12:40:38 - mmengine - INFO - Epoch(train) [106][2220/2569] lr: 4.0000e-03 eta: 8:22:33 time: 0.2616 data_time: 0.0072 memory: 5828 grad_norm: 3.6186 loss: 1.8226 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8226 2023/06/05 12:40:43 - mmengine - INFO - Epoch(train) [106][2240/2569] lr: 4.0000e-03 eta: 8:22:28 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 3.6608 loss: 1.9456 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9456 2023/06/05 12:40:47 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:40:48 - mmengine - INFO - Epoch(train) [106][2260/2569] lr: 4.0000e-03 eta: 8:22:22 time: 0.2602 data_time: 0.0069 memory: 5828 grad_norm: 3.6125 loss: 1.9447 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9447 2023/06/05 12:40:54 - mmengine - INFO - Epoch(train) [106][2280/2569] lr: 4.0000e-03 eta: 8:22:17 time: 0.2787 data_time: 0.0070 memory: 5828 grad_norm: 3.6518 loss: 1.6960 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6960 2023/06/05 12:40:59 - mmengine - INFO - Epoch(train) [106][2300/2569] lr: 4.0000e-03 eta: 8:22:12 time: 0.2647 data_time: 0.0072 memory: 5828 grad_norm: 3.7740 loss: 2.1345 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1345 2023/06/05 12:41:04 - mmengine - INFO - Epoch(train) [106][2320/2569] lr: 4.0000e-03 eta: 8:22:06 time: 0.2605 data_time: 0.0071 memory: 5828 grad_norm: 3.7015 loss: 1.9728 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9728 2023/06/05 12:41:10 - mmengine - INFO - Epoch(train) [106][2340/2569] lr: 4.0000e-03 eta: 8:22:01 time: 0.2696 data_time: 0.0067 memory: 5828 grad_norm: 3.6753 loss: 2.2482 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.2482 2023/06/05 12:41:15 - mmengine - INFO - Epoch(train) [106][2360/2569] lr: 4.0000e-03 eta: 8:21:56 time: 0.2810 data_time: 0.0068 memory: 5828 grad_norm: 3.6234 loss: 1.9122 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9122 2023/06/05 12:41:21 - mmengine - INFO - Epoch(train) [106][2380/2569] lr: 4.0000e-03 eta: 8:21:51 time: 0.2796 data_time: 0.0070 memory: 5828 grad_norm: 3.6485 loss: 1.9335 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9335 2023/06/05 12:41:26 - mmengine - INFO - Epoch(train) [106][2400/2569] lr: 4.0000e-03 eta: 8:21:45 time: 0.2737 data_time: 0.0069 memory: 5828 grad_norm: 3.7385 loss: 1.9177 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9177 2023/06/05 12:41:32 - mmengine - INFO - Epoch(train) [106][2420/2569] lr: 4.0000e-03 eta: 8:21:40 time: 0.2680 data_time: 0.0069 memory: 5828 grad_norm: 3.6849 loss: 1.6891 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6891 2023/06/05 12:41:37 - mmengine - INFO - Epoch(train) [106][2440/2569] lr: 4.0000e-03 eta: 8:21:35 time: 0.2734 data_time: 0.0069 memory: 5828 grad_norm: 3.6328 loss: 2.0005 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0005 2023/06/05 12:41:43 - mmengine - INFO - Epoch(train) [106][2460/2569] lr: 4.0000e-03 eta: 8:21:30 time: 0.2729 data_time: 0.0073 memory: 5828 grad_norm: 3.6989 loss: 1.6347 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6347 2023/06/05 12:41:48 - mmengine - INFO - Epoch(train) [106][2480/2569] lr: 4.0000e-03 eta: 8:21:24 time: 0.2659 data_time: 0.0070 memory: 5828 grad_norm: 3.7826 loss: 1.8523 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8523 2023/06/05 12:41:53 - mmengine - INFO - Epoch(train) [106][2500/2569] lr: 4.0000e-03 eta: 8:21:19 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 3.6955 loss: 1.9667 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9667 2023/06/05 12:41:59 - mmengine - INFO - Epoch(train) [106][2520/2569] lr: 4.0000e-03 eta: 8:21:14 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 3.7137 loss: 1.7675 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7675 2023/06/05 12:42:04 - mmengine - INFO - Epoch(train) [106][2540/2569] lr: 4.0000e-03 eta: 8:21:08 time: 0.2632 data_time: 0.0070 memory: 5828 grad_norm: 3.7168 loss: 2.0440 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0440 2023/06/05 12:42:09 - mmengine - INFO - Epoch(train) [106][2560/2569] lr: 4.0000e-03 eta: 8:21:03 time: 0.2572 data_time: 0.0076 memory: 5828 grad_norm: 3.7193 loss: 1.5798 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5798 2023/06/05 12:42:11 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:42:11 - mmengine - INFO - Epoch(train) [106][2569/2569] lr: 4.0000e-03 eta: 8:21:00 time: 0.2545 data_time: 0.0070 memory: 5828 grad_norm: 3.7063 loss: 1.8695 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.8695 2023/06/05 12:42:18 - mmengine - INFO - Epoch(train) [107][ 20/2569] lr: 4.0000e-03 eta: 8:20:56 time: 0.3360 data_time: 0.0596 memory: 5828 grad_norm: 3.6524 loss: 2.1797 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1797 2023/06/05 12:42:23 - mmengine - INFO - Epoch(train) [107][ 40/2569] lr: 4.0000e-03 eta: 8:20:50 time: 0.2595 data_time: 0.0072 memory: 5828 grad_norm: 3.6939 loss: 2.2005 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2005 2023/06/05 12:42:29 - mmengine - INFO - Epoch(train) [107][ 60/2569] lr: 4.0000e-03 eta: 8:20:45 time: 0.2636 data_time: 0.0071 memory: 5828 grad_norm: 3.7410 loss: 2.1770 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1770 2023/06/05 12:42:34 - mmengine - INFO - Epoch(train) [107][ 80/2569] lr: 4.0000e-03 eta: 8:20:40 time: 0.2624 data_time: 0.0070 memory: 5828 grad_norm: 3.6224 loss: 1.6137 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6137 2023/06/05 12:42:39 - mmengine - INFO - Epoch(train) [107][ 100/2569] lr: 4.0000e-03 eta: 8:20:34 time: 0.2713 data_time: 0.0072 memory: 5828 grad_norm: 3.6712 loss: 2.1142 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1142 2023/06/05 12:42:45 - mmengine - INFO - Epoch(train) [107][ 120/2569] lr: 4.0000e-03 eta: 8:20:29 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 3.6987 loss: 1.9962 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.9962 2023/06/05 12:42:50 - mmengine - INFO - Epoch(train) [107][ 140/2569] lr: 4.0000e-03 eta: 8:20:24 time: 0.2614 data_time: 0.0082 memory: 5828 grad_norm: 3.6879 loss: 1.8017 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8017 2023/06/05 12:42:55 - mmengine - INFO - Epoch(train) [107][ 160/2569] lr: 4.0000e-03 eta: 8:20:18 time: 0.2606 data_time: 0.0079 memory: 5828 grad_norm: 3.7666 loss: 2.1669 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1669 2023/06/05 12:43:00 - mmengine - INFO - Epoch(train) [107][ 180/2569] lr: 4.0000e-03 eta: 8:20:13 time: 0.2615 data_time: 0.0073 memory: 5828 grad_norm: 3.7240 loss: 1.7832 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7832 2023/06/05 12:43:06 - mmengine - INFO - Epoch(train) [107][ 200/2569] lr: 4.0000e-03 eta: 8:20:08 time: 0.2713 data_time: 0.0073 memory: 5828 grad_norm: 3.7504 loss: 2.1986 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1986 2023/06/05 12:43:11 - mmengine - INFO - Epoch(train) [107][ 220/2569] lr: 4.0000e-03 eta: 8:20:02 time: 0.2629 data_time: 0.0080 memory: 5828 grad_norm: 3.6922 loss: 1.9863 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9863 2023/06/05 12:43:16 - mmengine - INFO - Epoch(train) [107][ 240/2569] lr: 4.0000e-03 eta: 8:19:57 time: 0.2603 data_time: 0.0078 memory: 5828 grad_norm: 3.7002 loss: 2.0745 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0745 2023/06/05 12:43:21 - mmengine - INFO - Epoch(train) [107][ 260/2569] lr: 4.0000e-03 eta: 8:19:52 time: 0.2609 data_time: 0.0072 memory: 5828 grad_norm: 3.6862 loss: 1.9815 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9815 2023/06/05 12:43:27 - mmengine - INFO - Epoch(train) [107][ 280/2569] lr: 4.0000e-03 eta: 8:19:46 time: 0.2657 data_time: 0.0071 memory: 5828 grad_norm: 3.6692 loss: 1.7019 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7019 2023/06/05 12:43:32 - mmengine - INFO - Epoch(train) [107][ 300/2569] lr: 4.0000e-03 eta: 8:19:41 time: 0.2600 data_time: 0.0071 memory: 5828 grad_norm: 3.7411 loss: 1.8986 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8986 2023/06/05 12:43:37 - mmengine - INFO - Epoch(train) [107][ 320/2569] lr: 4.0000e-03 eta: 8:19:36 time: 0.2676 data_time: 0.0071 memory: 5828 grad_norm: 3.7249 loss: 1.8711 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8711 2023/06/05 12:43:43 - mmengine - INFO - Epoch(train) [107][ 340/2569] lr: 4.0000e-03 eta: 8:19:30 time: 0.2658 data_time: 0.0070 memory: 5828 grad_norm: 3.6993 loss: 2.0736 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0736 2023/06/05 12:43:48 - mmengine - INFO - Epoch(train) [107][ 360/2569] lr: 4.0000e-03 eta: 8:19:25 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 3.6628 loss: 1.9633 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9633 2023/06/05 12:43:53 - mmengine - INFO - Epoch(train) [107][ 380/2569] lr: 4.0000e-03 eta: 8:19:20 time: 0.2659 data_time: 0.0069 memory: 5828 grad_norm: 3.7220 loss: 1.8683 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8683 2023/06/05 12:43:58 - mmengine - INFO - Epoch(train) [107][ 400/2569] lr: 4.0000e-03 eta: 8:19:14 time: 0.2631 data_time: 0.0070 memory: 5828 grad_norm: 3.7300 loss: 1.9249 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9249 2023/06/05 12:44:04 - mmengine - INFO - Epoch(train) [107][ 420/2569] lr: 4.0000e-03 eta: 8:19:09 time: 0.2724 data_time: 0.0072 memory: 5828 grad_norm: 3.6916 loss: 1.7945 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7945 2023/06/05 12:44:09 - mmengine - INFO - Epoch(train) [107][ 440/2569] lr: 4.0000e-03 eta: 8:19:04 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.6884 loss: 1.7363 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7363 2023/06/05 12:44:15 - mmengine - INFO - Epoch(train) [107][ 460/2569] lr: 4.0000e-03 eta: 8:18:58 time: 0.2661 data_time: 0.0072 memory: 5828 grad_norm: 3.7048 loss: 1.7434 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7434 2023/06/05 12:44:20 - mmengine - INFO - Epoch(train) [107][ 480/2569] lr: 4.0000e-03 eta: 8:18:53 time: 0.2678 data_time: 0.0069 memory: 5828 grad_norm: 3.6697 loss: 1.8873 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8873 2023/06/05 12:44:25 - mmengine - INFO - Epoch(train) [107][ 500/2569] lr: 4.0000e-03 eta: 8:18:48 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 3.7379 loss: 2.3067 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.3067 2023/06/05 12:44:31 - mmengine - INFO - Epoch(train) [107][ 520/2569] lr: 4.0000e-03 eta: 8:18:42 time: 0.2658 data_time: 0.0066 memory: 5828 grad_norm: 3.6876 loss: 1.7258 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 1.7258 2023/06/05 12:44:36 - mmengine - INFO - Epoch(train) [107][ 540/2569] lr: 4.0000e-03 eta: 8:18:37 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 3.6844 loss: 2.2565 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.2565 2023/06/05 12:44:41 - mmengine - INFO - Epoch(train) [107][ 560/2569] lr: 4.0000e-03 eta: 8:18:32 time: 0.2726 data_time: 0.0071 memory: 5828 grad_norm: 3.7103 loss: 1.8401 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8401 2023/06/05 12:44:47 - mmengine - INFO - Epoch(train) [107][ 580/2569] lr: 4.0000e-03 eta: 8:18:27 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 3.7796 loss: 2.0534 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0534 2023/06/05 12:44:52 - mmengine - INFO - Epoch(train) [107][ 600/2569] lr: 4.0000e-03 eta: 8:18:21 time: 0.2722 data_time: 0.0068 memory: 5828 grad_norm: 3.7198 loss: 1.8024 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8024 2023/06/05 12:44:57 - mmengine - INFO - Epoch(train) [107][ 620/2569] lr: 4.0000e-03 eta: 8:18:16 time: 0.2626 data_time: 0.0071 memory: 5828 grad_norm: 3.6556 loss: 1.9585 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9585 2023/06/05 12:45:03 - mmengine - INFO - Epoch(train) [107][ 640/2569] lr: 4.0000e-03 eta: 8:18:11 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 3.8000 loss: 1.9364 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9364 2023/06/05 12:45:08 - mmengine - INFO - Epoch(train) [107][ 660/2569] lr: 4.0000e-03 eta: 8:18:05 time: 0.2678 data_time: 0.0071 memory: 5828 grad_norm: 3.7112 loss: 1.9483 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9483 2023/06/05 12:45:13 - mmengine - INFO - Epoch(train) [107][ 680/2569] lr: 4.0000e-03 eta: 8:18:00 time: 0.2725 data_time: 0.0068 memory: 5828 grad_norm: 3.7022 loss: 1.9703 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9703 2023/06/05 12:45:15 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:45:19 - mmengine - INFO - Epoch(train) [107][ 700/2569] lr: 4.0000e-03 eta: 8:17:55 time: 0.2697 data_time: 0.0071 memory: 5828 grad_norm: 3.7223 loss: 1.7044 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7044 2023/06/05 12:45:24 - mmengine - INFO - Epoch(train) [107][ 720/2569] lr: 4.0000e-03 eta: 8:17:49 time: 0.2641 data_time: 0.0070 memory: 5828 grad_norm: 3.8299 loss: 2.0361 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0361 2023/06/05 12:45:30 - mmengine - INFO - Epoch(train) [107][ 740/2569] lr: 4.0000e-03 eta: 8:17:44 time: 0.2703 data_time: 0.0069 memory: 5828 grad_norm: 3.7071 loss: 1.7912 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7912 2023/06/05 12:45:35 - mmengine - INFO - Epoch(train) [107][ 760/2569] lr: 4.0000e-03 eta: 8:17:39 time: 0.2630 data_time: 0.0071 memory: 5828 grad_norm: 3.7090 loss: 2.1311 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1311 2023/06/05 12:45:40 - mmengine - INFO - Epoch(train) [107][ 780/2569] lr: 4.0000e-03 eta: 8:17:33 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 3.7444 loss: 1.7596 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7596 2023/06/05 12:45:45 - mmengine - INFO - Epoch(train) [107][ 800/2569] lr: 4.0000e-03 eta: 8:17:28 time: 0.2604 data_time: 0.0072 memory: 5828 grad_norm: 3.7824 loss: 1.9612 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9612 2023/06/05 12:45:51 - mmengine - INFO - Epoch(train) [107][ 820/2569] lr: 4.0000e-03 eta: 8:17:23 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 3.7586 loss: 1.8286 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8286 2023/06/05 12:45:56 - mmengine - INFO - Epoch(train) [107][ 840/2569] lr: 4.0000e-03 eta: 8:17:17 time: 0.2731 data_time: 0.0072 memory: 5828 grad_norm: 3.7413 loss: 1.6270 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6270 2023/06/05 12:46:01 - mmengine - INFO - Epoch(train) [107][ 860/2569] lr: 4.0000e-03 eta: 8:17:12 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 3.6813 loss: 1.9637 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9637 2023/06/05 12:46:07 - mmengine - INFO - Epoch(train) [107][ 880/2569] lr: 4.0000e-03 eta: 8:17:07 time: 0.2604 data_time: 0.0072 memory: 5828 grad_norm: 3.7291 loss: 1.8270 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8270 2023/06/05 12:46:12 - mmengine - INFO - Epoch(train) [107][ 900/2569] lr: 4.0000e-03 eta: 8:17:01 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 3.6694 loss: 1.6619 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6619 2023/06/05 12:46:17 - mmengine - INFO - Epoch(train) [107][ 920/2569] lr: 4.0000e-03 eta: 8:16:56 time: 0.2682 data_time: 0.0074 memory: 5828 grad_norm: 3.7175 loss: 1.8539 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8539 2023/06/05 12:46:23 - mmengine - INFO - Epoch(train) [107][ 940/2569] lr: 4.0000e-03 eta: 8:16:51 time: 0.2705 data_time: 0.0072 memory: 5828 grad_norm: 3.7745 loss: 1.6866 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6866 2023/06/05 12:46:28 - mmengine - INFO - Epoch(train) [107][ 960/2569] lr: 4.0000e-03 eta: 8:16:46 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 3.6891 loss: 1.6723 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6723 2023/06/05 12:46:34 - mmengine - INFO - Epoch(train) [107][ 980/2569] lr: 4.0000e-03 eta: 8:16:40 time: 0.2724 data_time: 0.0071 memory: 5828 grad_norm: 3.6515 loss: 2.1028 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1028 2023/06/05 12:46:39 - mmengine - INFO - Epoch(train) [107][1000/2569] lr: 4.0000e-03 eta: 8:16:35 time: 0.2623 data_time: 0.0070 memory: 5828 grad_norm: 3.7376 loss: 1.7842 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7842 2023/06/05 12:46:44 - mmengine - INFO - Epoch(train) [107][1020/2569] lr: 4.0000e-03 eta: 8:16:30 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 3.7977 loss: 2.1114 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1114 2023/06/05 12:46:49 - mmengine - INFO - Epoch(train) [107][1040/2569] lr: 4.0000e-03 eta: 8:16:24 time: 0.2621 data_time: 0.0071 memory: 5828 grad_norm: 3.6873 loss: 2.0298 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0298 2023/06/05 12:46:55 - mmengine - INFO - Epoch(train) [107][1060/2569] lr: 4.0000e-03 eta: 8:16:19 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 3.7151 loss: 1.8811 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8811 2023/06/05 12:47:00 - mmengine - INFO - Epoch(train) [107][1080/2569] lr: 4.0000e-03 eta: 8:16:14 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.7432 loss: 1.7159 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7159 2023/06/05 12:47:05 - mmengine - INFO - Epoch(train) [107][1100/2569] lr: 4.0000e-03 eta: 8:16:08 time: 0.2712 data_time: 0.0074 memory: 5828 grad_norm: 3.7634 loss: 1.9216 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9216 2023/06/05 12:47:11 - mmengine - INFO - Epoch(train) [107][1120/2569] lr: 4.0000e-03 eta: 8:16:03 time: 0.2716 data_time: 0.0072 memory: 5828 grad_norm: 3.7953 loss: 1.9764 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9764 2023/06/05 12:47:16 - mmengine - INFO - Epoch(train) [107][1140/2569] lr: 4.0000e-03 eta: 8:15:58 time: 0.2687 data_time: 0.0072 memory: 5828 grad_norm: 3.7174 loss: 1.8594 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8594 2023/06/05 12:47:21 - mmengine - INFO - Epoch(train) [107][1160/2569] lr: 4.0000e-03 eta: 8:15:52 time: 0.2623 data_time: 0.0071 memory: 5828 grad_norm: 3.7483 loss: 1.7242 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7242 2023/06/05 12:47:27 - mmengine - INFO - Epoch(train) [107][1180/2569] lr: 4.0000e-03 eta: 8:15:47 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 3.7084 loss: 1.9457 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9457 2023/06/05 12:47:32 - mmengine - INFO - Epoch(train) [107][1200/2569] lr: 4.0000e-03 eta: 8:15:42 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 3.8519 loss: 1.9343 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9343 2023/06/05 12:47:37 - mmengine - INFO - Epoch(train) [107][1220/2569] lr: 4.0000e-03 eta: 8:15:36 time: 0.2665 data_time: 0.0074 memory: 5828 grad_norm: 3.7448 loss: 1.9702 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9702 2023/06/05 12:47:43 - mmengine - INFO - Epoch(train) [107][1240/2569] lr: 4.0000e-03 eta: 8:15:31 time: 0.2592 data_time: 0.0070 memory: 5828 grad_norm: 3.7220 loss: 1.5670 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5670 2023/06/05 12:47:48 - mmengine - INFO - Epoch(train) [107][1260/2569] lr: 4.0000e-03 eta: 8:15:26 time: 0.2729 data_time: 0.0073 memory: 5828 grad_norm: 3.7265 loss: 1.9854 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9854 2023/06/05 12:47:53 - mmengine - INFO - Epoch(train) [107][1280/2569] lr: 4.0000e-03 eta: 8:15:20 time: 0.2610 data_time: 0.0070 memory: 5828 grad_norm: 3.7370 loss: 1.8805 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8805 2023/06/05 12:47:59 - mmengine - INFO - Epoch(train) [107][1300/2569] lr: 4.0000e-03 eta: 8:15:15 time: 0.2768 data_time: 0.0070 memory: 5828 grad_norm: 3.6447 loss: 2.0995 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0995 2023/06/05 12:48:04 - mmengine - INFO - Epoch(train) [107][1320/2569] lr: 4.0000e-03 eta: 8:15:10 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 3.7715 loss: 1.7161 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7161 2023/06/05 12:48:10 - mmengine - INFO - Epoch(train) [107][1340/2569] lr: 4.0000e-03 eta: 8:15:05 time: 0.2793 data_time: 0.0070 memory: 5828 grad_norm: 3.6880 loss: 2.0746 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0746 2023/06/05 12:48:15 - mmengine - INFO - Epoch(train) [107][1360/2569] lr: 4.0000e-03 eta: 8:14:59 time: 0.2738 data_time: 0.0070 memory: 5828 grad_norm: 3.7983 loss: 1.7708 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7708 2023/06/05 12:48:20 - mmengine - INFO - Epoch(train) [107][1380/2569] lr: 4.0000e-03 eta: 8:14:54 time: 0.2607 data_time: 0.0070 memory: 5828 grad_norm: 3.7042 loss: 2.0801 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0801 2023/06/05 12:48:26 - mmengine - INFO - Epoch(train) [107][1400/2569] lr: 4.0000e-03 eta: 8:14:49 time: 0.2713 data_time: 0.0072 memory: 5828 grad_norm: 3.7305 loss: 2.0781 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0781 2023/06/05 12:48:31 - mmengine - INFO - Epoch(train) [107][1420/2569] lr: 4.0000e-03 eta: 8:14:43 time: 0.2673 data_time: 0.0070 memory: 5828 grad_norm: 3.7302 loss: 2.0511 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0511 2023/06/05 12:48:37 - mmengine - INFO - Epoch(train) [107][1440/2569] lr: 4.0000e-03 eta: 8:14:38 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 3.7347 loss: 1.8768 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8768 2023/06/05 12:48:42 - mmengine - INFO - Epoch(train) [107][1460/2569] lr: 4.0000e-03 eta: 8:14:33 time: 0.2715 data_time: 0.0073 memory: 5828 grad_norm: 3.7511 loss: 1.8310 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8310 2023/06/05 12:48:48 - mmengine - INFO - Epoch(train) [107][1480/2569] lr: 4.0000e-03 eta: 8:14:28 time: 0.2821 data_time: 0.0070 memory: 5828 grad_norm: 3.8374 loss: 1.7078 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7078 2023/06/05 12:48:53 - mmengine - INFO - Epoch(train) [107][1500/2569] lr: 4.0000e-03 eta: 8:14:22 time: 0.2624 data_time: 0.0069 memory: 5828 grad_norm: 3.7895 loss: 1.7520 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7520 2023/06/05 12:48:58 - mmengine - INFO - Epoch(train) [107][1520/2569] lr: 4.0000e-03 eta: 8:14:17 time: 0.2729 data_time: 0.0071 memory: 5828 grad_norm: 3.7519 loss: 1.9712 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9712 2023/06/05 12:49:04 - mmengine - INFO - Epoch(train) [107][1540/2569] lr: 4.0000e-03 eta: 8:14:12 time: 0.2631 data_time: 0.0075 memory: 5828 grad_norm: 3.7417 loss: 1.6107 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6107 2023/06/05 12:49:09 - mmengine - INFO - Epoch(train) [107][1560/2569] lr: 4.0000e-03 eta: 8:14:07 time: 0.2779 data_time: 0.0071 memory: 5828 grad_norm: 3.7121 loss: 1.9013 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9013 2023/06/05 12:49:15 - mmengine - INFO - Epoch(train) [107][1580/2569] lr: 4.0000e-03 eta: 8:14:01 time: 0.2606 data_time: 0.0074 memory: 5828 grad_norm: 3.7974 loss: 1.8348 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8348 2023/06/05 12:49:20 - mmengine - INFO - Epoch(train) [107][1600/2569] lr: 4.0000e-03 eta: 8:13:56 time: 0.2810 data_time: 0.0071 memory: 5828 grad_norm: 3.7201 loss: 1.9867 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9867 2023/06/05 12:49:25 - mmengine - INFO - Epoch(train) [107][1620/2569] lr: 4.0000e-03 eta: 8:13:51 time: 0.2661 data_time: 0.0070 memory: 5828 grad_norm: 3.7156 loss: 2.0528 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0528 2023/06/05 12:49:31 - mmengine - INFO - Epoch(train) [107][1640/2569] lr: 4.0000e-03 eta: 8:13:45 time: 0.2734 data_time: 0.0071 memory: 5828 grad_norm: 3.7011 loss: 1.9664 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9664 2023/06/05 12:49:37 - mmengine - INFO - Epoch(train) [107][1660/2569] lr: 4.0000e-03 eta: 8:13:40 time: 0.2776 data_time: 0.0068 memory: 5828 grad_norm: 3.7747 loss: 1.8094 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8094 2023/06/05 12:49:42 - mmengine - INFO - Epoch(train) [107][1680/2569] lr: 4.0000e-03 eta: 8:13:35 time: 0.2755 data_time: 0.0073 memory: 5828 grad_norm: 3.8085 loss: 1.8470 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8470 2023/06/05 12:49:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:49:47 - mmengine - INFO - Epoch(train) [107][1700/2569] lr: 4.0000e-03 eta: 8:13:30 time: 0.2604 data_time: 0.0069 memory: 5828 grad_norm: 3.7073 loss: 2.0768 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0768 2023/06/05 12:49:53 - mmengine - INFO - Epoch(train) [107][1720/2569] lr: 4.0000e-03 eta: 8:13:24 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 3.6893 loss: 1.6228 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6228 2023/06/05 12:49:58 - mmengine - INFO - Epoch(train) [107][1740/2569] lr: 4.0000e-03 eta: 8:13:19 time: 0.2597 data_time: 0.0070 memory: 5828 grad_norm: 3.7918 loss: 1.7472 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7472 2023/06/05 12:50:03 - mmengine - INFO - Epoch(train) [107][1760/2569] lr: 4.0000e-03 eta: 8:13:14 time: 0.2607 data_time: 0.0072 memory: 5828 grad_norm: 3.7518 loss: 1.9695 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9695 2023/06/05 12:50:08 - mmengine - INFO - Epoch(train) [107][1780/2569] lr: 4.0000e-03 eta: 8:13:08 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 3.7348 loss: 1.9988 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9988 2023/06/05 12:50:14 - mmengine - INFO - Epoch(train) [107][1800/2569] lr: 4.0000e-03 eta: 8:13:03 time: 0.2673 data_time: 0.0071 memory: 5828 grad_norm: 3.7451 loss: 1.8425 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8425 2023/06/05 12:50:19 - mmengine - INFO - Epoch(train) [107][1820/2569] lr: 4.0000e-03 eta: 8:12:58 time: 0.2714 data_time: 0.0071 memory: 5828 grad_norm: 3.7153 loss: 1.5653 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5653 2023/06/05 12:50:25 - mmengine - INFO - Epoch(train) [107][1840/2569] lr: 4.0000e-03 eta: 8:12:52 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 3.7799 loss: 1.9308 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9308 2023/06/05 12:50:30 - mmengine - INFO - Epoch(train) [107][1860/2569] lr: 4.0000e-03 eta: 8:12:47 time: 0.2833 data_time: 0.0070 memory: 5828 grad_norm: 3.7499 loss: 1.9406 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9406 2023/06/05 12:50:35 - mmengine - INFO - Epoch(train) [107][1880/2569] lr: 4.0000e-03 eta: 8:12:42 time: 0.2617 data_time: 0.0069 memory: 5828 grad_norm: 3.7808 loss: 1.7212 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7212 2023/06/05 12:50:41 - mmengine - INFO - Epoch(train) [107][1900/2569] lr: 4.0000e-03 eta: 8:12:37 time: 0.2731 data_time: 0.0073 memory: 5828 grad_norm: 3.7214 loss: 2.1405 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1405 2023/06/05 12:50:46 - mmengine - INFO - Epoch(train) [107][1920/2569] lr: 4.0000e-03 eta: 8:12:31 time: 0.2618 data_time: 0.0069 memory: 5828 grad_norm: 3.7814 loss: 1.9231 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9231 2023/06/05 12:50:51 - mmengine - INFO - Epoch(train) [107][1940/2569] lr: 4.0000e-03 eta: 8:12:26 time: 0.2646 data_time: 0.0072 memory: 5828 grad_norm: 3.7374 loss: 1.9274 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9274 2023/06/05 12:50:57 - mmengine - INFO - Epoch(train) [107][1960/2569] lr: 4.0000e-03 eta: 8:12:21 time: 0.2714 data_time: 0.0070 memory: 5828 grad_norm: 3.6492 loss: 2.1208 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1208 2023/06/05 12:51:02 - mmengine - INFO - Epoch(train) [107][1980/2569] lr: 4.0000e-03 eta: 8:12:15 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 3.6923 loss: 2.0082 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0082 2023/06/05 12:51:08 - mmengine - INFO - Epoch(train) [107][2000/2569] lr: 4.0000e-03 eta: 8:12:10 time: 0.2729 data_time: 0.0070 memory: 5828 grad_norm: 3.7197 loss: 2.0402 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0402 2023/06/05 12:51:13 - mmengine - INFO - Epoch(train) [107][2020/2569] lr: 4.0000e-03 eta: 8:12:05 time: 0.2615 data_time: 0.0071 memory: 5828 grad_norm: 3.7057 loss: 2.2050 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2050 2023/06/05 12:51:18 - mmengine - INFO - Epoch(train) [107][2040/2569] lr: 4.0000e-03 eta: 8:11:59 time: 0.2630 data_time: 0.0073 memory: 5828 grad_norm: 3.7899 loss: 1.8761 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8761 2023/06/05 12:51:23 - mmengine - INFO - Epoch(train) [107][2060/2569] lr: 4.0000e-03 eta: 8:11:54 time: 0.2611 data_time: 0.0070 memory: 5828 grad_norm: 3.7295 loss: 1.9416 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9416 2023/06/05 12:51:29 - mmengine - INFO - Epoch(train) [107][2080/2569] lr: 4.0000e-03 eta: 8:11:49 time: 0.2626 data_time: 0.0070 memory: 5828 grad_norm: 3.7035 loss: 1.7279 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7279 2023/06/05 12:51:34 - mmengine - INFO - Epoch(train) [107][2100/2569] lr: 4.0000e-03 eta: 8:11:43 time: 0.2690 data_time: 0.0073 memory: 5828 grad_norm: 3.7951 loss: 2.0654 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0654 2023/06/05 12:51:39 - mmengine - INFO - Epoch(train) [107][2120/2569] lr: 4.0000e-03 eta: 8:11:38 time: 0.2663 data_time: 0.0067 memory: 5828 grad_norm: 3.7123 loss: 1.7977 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7977 2023/06/05 12:51:45 - mmengine - INFO - Epoch(train) [107][2140/2569] lr: 4.0000e-03 eta: 8:11:33 time: 0.2607 data_time: 0.0071 memory: 5828 grad_norm: 3.7219 loss: 1.8083 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8083 2023/06/05 12:51:50 - mmengine - INFO - Epoch(train) [107][2160/2569] lr: 4.0000e-03 eta: 8:11:27 time: 0.2719 data_time: 0.0072 memory: 5828 grad_norm: 3.7715 loss: 2.0328 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0328 2023/06/05 12:51:55 - mmengine - INFO - Epoch(train) [107][2180/2569] lr: 4.0000e-03 eta: 8:11:22 time: 0.2637 data_time: 0.0069 memory: 5828 grad_norm: 3.7655 loss: 1.9908 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9908 2023/06/05 12:52:01 - mmengine - INFO - Epoch(train) [107][2200/2569] lr: 4.0000e-03 eta: 8:11:17 time: 0.2720 data_time: 0.0070 memory: 5828 grad_norm: 3.6614 loss: 1.9281 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9281 2023/06/05 12:52:06 - mmengine - INFO - Epoch(train) [107][2220/2569] lr: 4.0000e-03 eta: 8:11:11 time: 0.2737 data_time: 0.0070 memory: 5828 grad_norm: 3.7524 loss: 1.9026 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9026 2023/06/05 12:52:12 - mmengine - INFO - Epoch(train) [107][2240/2569] lr: 4.0000e-03 eta: 8:11:06 time: 0.2695 data_time: 0.0070 memory: 5828 grad_norm: 3.7343 loss: 2.2097 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.2097 2023/06/05 12:52:17 - mmengine - INFO - Epoch(train) [107][2260/2569] lr: 4.0000e-03 eta: 8:11:01 time: 0.2647 data_time: 0.0071 memory: 5828 grad_norm: 3.7034 loss: 2.0591 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0591 2023/06/05 12:52:22 - mmengine - INFO - Epoch(train) [107][2280/2569] lr: 4.0000e-03 eta: 8:10:56 time: 0.2678 data_time: 0.0069 memory: 5828 grad_norm: 3.8172 loss: 1.8844 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8844 2023/06/05 12:52:28 - mmengine - INFO - Epoch(train) [107][2300/2569] lr: 4.0000e-03 eta: 8:10:50 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 3.7584 loss: 1.9312 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9312 2023/06/05 12:52:33 - mmengine - INFO - Epoch(train) [107][2320/2569] lr: 4.0000e-03 eta: 8:10:45 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 3.8151 loss: 1.7888 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7888 2023/06/05 12:52:38 - mmengine - INFO - Epoch(train) [107][2340/2569] lr: 4.0000e-03 eta: 8:10:40 time: 0.2655 data_time: 0.0072 memory: 5828 grad_norm: 3.7222 loss: 1.8318 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8318 2023/06/05 12:52:44 - mmengine - INFO - Epoch(train) [107][2360/2569] lr: 4.0000e-03 eta: 8:10:34 time: 0.2785 data_time: 0.0076 memory: 5828 grad_norm: 3.7726 loss: 1.7334 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7334 2023/06/05 12:52:49 - mmengine - INFO - Epoch(train) [107][2380/2569] lr: 4.0000e-03 eta: 8:10:29 time: 0.2689 data_time: 0.0072 memory: 5828 grad_norm: 3.7083 loss: 2.0025 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0025 2023/06/05 12:52:55 - mmengine - INFO - Epoch(train) [107][2400/2569] lr: 4.0000e-03 eta: 8:10:24 time: 0.2650 data_time: 0.0070 memory: 5828 grad_norm: 3.7508 loss: 1.8975 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8975 2023/06/05 12:53:00 - mmengine - INFO - Epoch(train) [107][2420/2569] lr: 4.0000e-03 eta: 8:10:18 time: 0.2691 data_time: 0.0074 memory: 5828 grad_norm: 3.7050 loss: 1.8483 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8483 2023/06/05 12:53:05 - mmengine - INFO - Epoch(train) [107][2440/2569] lr: 4.0000e-03 eta: 8:10:13 time: 0.2601 data_time: 0.0073 memory: 5828 grad_norm: 3.7539 loss: 2.1425 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.1425 2023/06/05 12:53:11 - mmengine - INFO - Epoch(train) [107][2460/2569] lr: 4.0000e-03 eta: 8:10:08 time: 0.2770 data_time: 0.0070 memory: 5828 grad_norm: 3.7200 loss: 1.6949 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6949 2023/06/05 12:53:16 - mmengine - INFO - Epoch(train) [107][2480/2569] lr: 4.0000e-03 eta: 8:10:02 time: 0.2602 data_time: 0.0072 memory: 5828 grad_norm: 3.7676 loss: 2.0953 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0953 2023/06/05 12:53:21 - mmengine - INFO - Epoch(train) [107][2500/2569] lr: 4.0000e-03 eta: 8:09:57 time: 0.2710 data_time: 0.0071 memory: 5828 grad_norm: 3.7561 loss: 1.7190 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7190 2023/06/05 12:53:27 - mmengine - INFO - Epoch(train) [107][2520/2569] lr: 4.0000e-03 eta: 8:09:52 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 3.7872 loss: 1.6717 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6717 2023/06/05 12:53:32 - mmengine - INFO - Epoch(train) [107][2540/2569] lr: 4.0000e-03 eta: 8:09:47 time: 0.2667 data_time: 0.0071 memory: 5828 grad_norm: 3.7874 loss: 1.9073 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9073 2023/06/05 12:53:37 - mmengine - INFO - Epoch(train) [107][2560/2569] lr: 4.0000e-03 eta: 8:09:41 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 3.8086 loss: 1.9732 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9732 2023/06/05 12:53:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:53:39 - mmengine - INFO - Epoch(train) [107][2569/2569] lr: 4.0000e-03 eta: 8:09:39 time: 0.2530 data_time: 0.0070 memory: 5828 grad_norm: 3.8291 loss: 2.0846 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.0846 2023/06/05 12:53:46 - mmengine - INFO - Epoch(train) [108][ 20/2569] lr: 4.0000e-03 eta: 8:09:34 time: 0.3296 data_time: 0.0539 memory: 5828 grad_norm: 3.7311 loss: 2.0390 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0390 2023/06/05 12:53:52 - mmengine - INFO - Epoch(train) [108][ 40/2569] lr: 4.0000e-03 eta: 8:09:29 time: 0.2708 data_time: 0.0068 memory: 5828 grad_norm: 3.7823 loss: 1.7710 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7710 2023/06/05 12:53:57 - mmengine - INFO - Epoch(train) [108][ 60/2569] lr: 4.0000e-03 eta: 8:09:23 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 3.7653 loss: 1.7316 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7316 2023/06/05 12:54:02 - mmengine - INFO - Epoch(train) [108][ 80/2569] lr: 4.0000e-03 eta: 8:09:18 time: 0.2676 data_time: 0.0071 memory: 5828 grad_norm: 3.6749 loss: 1.9338 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9338 2023/06/05 12:54:08 - mmengine - INFO - Epoch(train) [108][ 100/2569] lr: 4.0000e-03 eta: 8:09:13 time: 0.2750 data_time: 0.0073 memory: 5828 grad_norm: 3.7555 loss: 1.8122 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8122 2023/06/05 12:54:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:54:13 - mmengine - INFO - Epoch(train) [108][ 120/2569] lr: 4.0000e-03 eta: 8:09:07 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 3.7651 loss: 1.8403 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8403 2023/06/05 12:54:18 - mmengine - INFO - Epoch(train) [108][ 140/2569] lr: 4.0000e-03 eta: 8:09:02 time: 0.2672 data_time: 0.0071 memory: 5828 grad_norm: 3.7934 loss: 1.9366 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9366 2023/06/05 12:54:24 - mmengine - INFO - Epoch(train) [108][ 160/2569] lr: 4.0000e-03 eta: 8:08:57 time: 0.2664 data_time: 0.0069 memory: 5828 grad_norm: 3.7008 loss: 1.6065 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6065 2023/06/05 12:54:29 - mmengine - INFO - Epoch(train) [108][ 180/2569] lr: 4.0000e-03 eta: 8:08:52 time: 0.2740 data_time: 0.0073 memory: 5828 grad_norm: 3.8150 loss: 1.8666 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8666 2023/06/05 12:54:35 - mmengine - INFO - Epoch(train) [108][ 200/2569] lr: 4.0000e-03 eta: 8:08:46 time: 0.2660 data_time: 0.0070 memory: 5828 grad_norm: 3.7910 loss: 1.9392 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9392 2023/06/05 12:54:40 - mmengine - INFO - Epoch(train) [108][ 220/2569] lr: 4.0000e-03 eta: 8:08:41 time: 0.2683 data_time: 0.0070 memory: 5828 grad_norm: 3.6752 loss: 2.2866 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2866 2023/06/05 12:54:45 - mmengine - INFO - Epoch(train) [108][ 240/2569] lr: 4.0000e-03 eta: 8:08:36 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 3.8086 loss: 1.9791 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9791 2023/06/05 12:54:50 - mmengine - INFO - Epoch(train) [108][ 260/2569] lr: 4.0000e-03 eta: 8:08:30 time: 0.2597 data_time: 0.0071 memory: 5828 grad_norm: 3.7657 loss: 1.7218 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7218 2023/06/05 12:54:56 - mmengine - INFO - Epoch(train) [108][ 280/2569] lr: 4.0000e-03 eta: 8:08:25 time: 0.2639 data_time: 0.0070 memory: 5828 grad_norm: 3.7479 loss: 1.9012 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9012 2023/06/05 12:55:01 - mmengine - INFO - Epoch(train) [108][ 300/2569] lr: 4.0000e-03 eta: 8:08:20 time: 0.2602 data_time: 0.0072 memory: 5828 grad_norm: 3.7500 loss: 1.5702 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 1.5702 2023/06/05 12:55:06 - mmengine - INFO - Epoch(train) [108][ 320/2569] lr: 4.0000e-03 eta: 8:08:14 time: 0.2605 data_time: 0.0073 memory: 5828 grad_norm: 3.8603 loss: 1.5953 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5953 2023/06/05 12:55:11 - mmengine - INFO - Epoch(train) [108][ 340/2569] lr: 4.0000e-03 eta: 8:08:09 time: 0.2609 data_time: 0.0073 memory: 5828 grad_norm: 3.7770 loss: 1.8353 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8353 2023/06/05 12:55:17 - mmengine - INFO - Epoch(train) [108][ 360/2569] lr: 4.0000e-03 eta: 8:08:04 time: 0.2712 data_time: 0.0072 memory: 5828 grad_norm: 3.7984 loss: 2.1796 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1796 2023/06/05 12:55:22 - mmengine - INFO - Epoch(train) [108][ 380/2569] lr: 4.0000e-03 eta: 8:07:58 time: 0.2673 data_time: 0.0072 memory: 5828 grad_norm: 3.7324 loss: 1.8556 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8556 2023/06/05 12:55:28 - mmengine - INFO - Epoch(train) [108][ 400/2569] lr: 4.0000e-03 eta: 8:07:53 time: 0.2663 data_time: 0.0072 memory: 5828 grad_norm: 3.8447 loss: 1.9880 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9880 2023/06/05 12:55:33 - mmengine - INFO - Epoch(train) [108][ 420/2569] lr: 4.0000e-03 eta: 8:07:48 time: 0.2741 data_time: 0.0072 memory: 5828 grad_norm: 3.8666 loss: 1.7584 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7584 2023/06/05 12:55:38 - mmengine - INFO - Epoch(train) [108][ 440/2569] lr: 4.0000e-03 eta: 8:07:42 time: 0.2675 data_time: 0.0070 memory: 5828 grad_norm: 3.8745 loss: 2.1488 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1488 2023/06/05 12:55:44 - mmengine - INFO - Epoch(train) [108][ 460/2569] lr: 4.0000e-03 eta: 8:07:37 time: 0.2660 data_time: 0.0072 memory: 5828 grad_norm: 3.8022 loss: 1.9238 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9238 2023/06/05 12:55:49 - mmengine - INFO - Epoch(train) [108][ 480/2569] lr: 4.0000e-03 eta: 8:07:32 time: 0.2609 data_time: 0.0070 memory: 5828 grad_norm: 3.7800 loss: 1.8481 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8481 2023/06/05 12:55:54 - mmengine - INFO - Epoch(train) [108][ 500/2569] lr: 4.0000e-03 eta: 8:07:26 time: 0.2607 data_time: 0.0072 memory: 5828 grad_norm: 3.7500 loss: 1.7204 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7204 2023/06/05 12:56:00 - mmengine - INFO - Epoch(train) [108][ 520/2569] lr: 4.0000e-03 eta: 8:07:21 time: 0.2718 data_time: 0.0070 memory: 5828 grad_norm: 3.7219 loss: 1.9110 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9110 2023/06/05 12:56:05 - mmengine - INFO - Epoch(train) [108][ 540/2569] lr: 4.0000e-03 eta: 8:07:16 time: 0.2667 data_time: 0.0070 memory: 5828 grad_norm: 3.7689 loss: 1.8238 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8238 2023/06/05 12:56:11 - mmengine - INFO - Epoch(train) [108][ 560/2569] lr: 4.0000e-03 eta: 8:07:11 time: 0.2838 data_time: 0.0070 memory: 5828 grad_norm: 3.7558 loss: 2.1488 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1488 2023/06/05 12:56:16 - mmengine - INFO - Epoch(train) [108][ 580/2569] lr: 4.0000e-03 eta: 8:07:05 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 3.7888 loss: 1.9025 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9025 2023/06/05 12:56:21 - mmengine - INFO - Epoch(train) [108][ 600/2569] lr: 4.0000e-03 eta: 8:07:00 time: 0.2623 data_time: 0.0070 memory: 5828 grad_norm: 3.8184 loss: 1.7903 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7903 2023/06/05 12:56:27 - mmengine - INFO - Epoch(train) [108][ 620/2569] lr: 4.0000e-03 eta: 8:06:55 time: 0.2704 data_time: 0.0070 memory: 5828 grad_norm: 3.7516 loss: 1.9062 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9062 2023/06/05 12:56:32 - mmengine - INFO - Epoch(train) [108][ 640/2569] lr: 4.0000e-03 eta: 8:06:49 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.6896 loss: 2.0120 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0120 2023/06/05 12:56:37 - mmengine - INFO - Epoch(train) [108][ 660/2569] lr: 4.0000e-03 eta: 8:06:44 time: 0.2670 data_time: 0.0070 memory: 5828 grad_norm: 3.8322 loss: 1.8263 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8263 2023/06/05 12:56:43 - mmengine - INFO - Epoch(train) [108][ 680/2569] lr: 4.0000e-03 eta: 8:06:39 time: 0.2610 data_time: 0.0073 memory: 5828 grad_norm: 3.7621 loss: 2.0701 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0701 2023/06/05 12:56:48 - mmengine - INFO - Epoch(train) [108][ 700/2569] lr: 4.0000e-03 eta: 8:06:33 time: 0.2623 data_time: 0.0069 memory: 5828 grad_norm: 3.8456 loss: 1.7060 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7060 2023/06/05 12:56:53 - mmengine - INFO - Epoch(train) [108][ 720/2569] lr: 4.0000e-03 eta: 8:06:28 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 3.8201 loss: 1.7571 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7571 2023/06/05 12:56:59 - mmengine - INFO - Epoch(train) [108][ 740/2569] lr: 4.0000e-03 eta: 8:06:23 time: 0.2753 data_time: 0.0072 memory: 5828 grad_norm: 3.8577 loss: 1.8304 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8304 2023/06/05 12:57:04 - mmengine - INFO - Epoch(train) [108][ 760/2569] lr: 4.0000e-03 eta: 8:06:17 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 3.8421 loss: 1.6614 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6614 2023/06/05 12:57:09 - mmengine - INFO - Epoch(train) [108][ 780/2569] lr: 4.0000e-03 eta: 8:06:12 time: 0.2723 data_time: 0.0074 memory: 5828 grad_norm: 3.7625 loss: 1.8774 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8774 2023/06/05 12:57:15 - mmengine - INFO - Epoch(train) [108][ 800/2569] lr: 4.0000e-03 eta: 8:06:07 time: 0.2665 data_time: 0.0072 memory: 5828 grad_norm: 3.7858 loss: 1.5109 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5109 2023/06/05 12:57:20 - mmengine - INFO - Epoch(train) [108][ 820/2569] lr: 4.0000e-03 eta: 8:06:02 time: 0.2698 data_time: 0.0072 memory: 5828 grad_norm: 3.8805 loss: 1.9386 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9386 2023/06/05 12:57:25 - mmengine - INFO - Epoch(train) [108][ 840/2569] lr: 4.0000e-03 eta: 8:05:56 time: 0.2635 data_time: 0.0071 memory: 5828 grad_norm: 3.7867 loss: 1.8518 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8518 2023/06/05 12:57:31 - mmengine - INFO - Epoch(train) [108][ 860/2569] lr: 4.0000e-03 eta: 8:05:51 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 3.7314 loss: 1.8387 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8387 2023/06/05 12:57:36 - mmengine - INFO - Epoch(train) [108][ 880/2569] lr: 4.0000e-03 eta: 8:05:46 time: 0.2611 data_time: 0.0080 memory: 5828 grad_norm: 3.7915 loss: 1.9396 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9396 2023/06/05 12:57:41 - mmengine - INFO - Epoch(train) [108][ 900/2569] lr: 4.0000e-03 eta: 8:05:40 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 3.8382 loss: 1.6432 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6432 2023/06/05 12:57:47 - mmengine - INFO - Epoch(train) [108][ 920/2569] lr: 4.0000e-03 eta: 8:05:35 time: 0.2682 data_time: 0.0069 memory: 5828 grad_norm: 3.7990 loss: 2.0188 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0188 2023/06/05 12:57:52 - mmengine - INFO - Epoch(train) [108][ 940/2569] lr: 4.0000e-03 eta: 8:05:30 time: 0.2653 data_time: 0.0073 memory: 5828 grad_norm: 3.8272 loss: 1.8702 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8702 2023/06/05 12:57:57 - mmengine - INFO - Epoch(train) [108][ 960/2569] lr: 4.0000e-03 eta: 8:05:24 time: 0.2653 data_time: 0.0070 memory: 5828 grad_norm: 3.7874 loss: 1.9208 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9208 2023/06/05 12:58:03 - mmengine - INFO - Epoch(train) [108][ 980/2569] lr: 4.0000e-03 eta: 8:05:19 time: 0.2698 data_time: 0.0072 memory: 5828 grad_norm: 3.8307 loss: 2.0174 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0174 2023/06/05 12:58:08 - mmengine - INFO - Epoch(train) [108][1000/2569] lr: 4.0000e-03 eta: 8:05:14 time: 0.2609 data_time: 0.0071 memory: 5828 grad_norm: 3.7758 loss: 1.7957 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7957 2023/06/05 12:58:13 - mmengine - INFO - Epoch(train) [108][1020/2569] lr: 4.0000e-03 eta: 8:05:08 time: 0.2703 data_time: 0.0071 memory: 5828 grad_norm: 3.7670 loss: 1.9502 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9502 2023/06/05 12:58:19 - mmengine - INFO - Epoch(train) [108][1040/2569] lr: 4.0000e-03 eta: 8:05:03 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 3.7754 loss: 1.5677 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5677 2023/06/05 12:58:24 - mmengine - INFO - Epoch(train) [108][1060/2569] lr: 4.0000e-03 eta: 8:04:58 time: 0.2624 data_time: 0.0070 memory: 5828 grad_norm: 3.7482 loss: 1.8713 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8713 2023/06/05 12:58:29 - mmengine - INFO - Epoch(train) [108][1080/2569] lr: 4.0000e-03 eta: 8:04:52 time: 0.2709 data_time: 0.0072 memory: 5828 grad_norm: 3.8149 loss: 2.0853 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0853 2023/06/05 12:58:35 - mmengine - INFO - Epoch(train) [108][1100/2569] lr: 4.0000e-03 eta: 8:04:47 time: 0.2733 data_time: 0.0071 memory: 5828 grad_norm: 3.8778 loss: 1.8766 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8766 2023/06/05 12:58:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 12:58:40 - mmengine - INFO - Epoch(train) [108][1120/2569] lr: 4.0000e-03 eta: 8:04:42 time: 0.2647 data_time: 0.0070 memory: 5828 grad_norm: 3.8576 loss: 1.7020 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7020 2023/06/05 12:58:45 - mmengine - INFO - Epoch(train) [108][1140/2569] lr: 4.0000e-03 eta: 8:04:36 time: 0.2607 data_time: 0.0069 memory: 5828 grad_norm: 3.9224 loss: 2.0810 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0810 2023/06/05 12:58:50 - mmengine - INFO - Epoch(train) [108][1160/2569] lr: 4.0000e-03 eta: 8:04:31 time: 0.2588 data_time: 0.0071 memory: 5828 grad_norm: 3.7674 loss: 1.5694 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5694 2023/06/05 12:58:56 - mmengine - INFO - Epoch(train) [108][1180/2569] lr: 4.0000e-03 eta: 8:04:26 time: 0.2772 data_time: 0.0070 memory: 5828 grad_norm: 3.7705 loss: 2.1984 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1984 2023/06/05 12:59:01 - mmengine - INFO - Epoch(train) [108][1200/2569] lr: 4.0000e-03 eta: 8:04:20 time: 0.2659 data_time: 0.0072 memory: 5828 grad_norm: 3.8100 loss: 1.7776 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.7776 2023/06/05 12:59:07 - mmengine - INFO - Epoch(train) [108][1220/2569] lr: 4.0000e-03 eta: 8:04:15 time: 0.2832 data_time: 0.0073 memory: 5828 grad_norm: 3.8294 loss: 1.9207 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9207 2023/06/05 12:59:13 - mmengine - INFO - Epoch(train) [108][1240/2569] lr: 4.0000e-03 eta: 8:04:10 time: 0.2729 data_time: 0.0073 memory: 5828 grad_norm: 3.7773 loss: 1.8920 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8920 2023/06/05 12:59:18 - mmengine - INFO - Epoch(train) [108][1260/2569] lr: 4.0000e-03 eta: 8:04:05 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 3.7851 loss: 1.7210 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7210 2023/06/05 12:59:23 - mmengine - INFO - Epoch(train) [108][1280/2569] lr: 4.0000e-03 eta: 8:03:59 time: 0.2711 data_time: 0.0072 memory: 5828 grad_norm: 3.7808 loss: 1.8854 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8854 2023/06/05 12:59:29 - mmengine - INFO - Epoch(train) [108][1300/2569] lr: 4.0000e-03 eta: 8:03:54 time: 0.2619 data_time: 0.0071 memory: 5828 grad_norm: 3.8049 loss: 1.7816 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7816 2023/06/05 12:59:34 - mmengine - INFO - Epoch(train) [108][1320/2569] lr: 4.0000e-03 eta: 8:03:49 time: 0.2621 data_time: 0.0072 memory: 5828 grad_norm: 3.7643 loss: 1.9421 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9421 2023/06/05 12:59:39 - mmengine - INFO - Epoch(train) [108][1340/2569] lr: 4.0000e-03 eta: 8:03:43 time: 0.2720 data_time: 0.0072 memory: 5828 grad_norm: 3.7258 loss: 1.8209 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8209 2023/06/05 12:59:44 - mmengine - INFO - Epoch(train) [108][1360/2569] lr: 4.0000e-03 eta: 8:03:38 time: 0.2613 data_time: 0.0071 memory: 5828 grad_norm: 3.7919 loss: 1.8069 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8069 2023/06/05 12:59:50 - mmengine - INFO - Epoch(train) [108][1380/2569] lr: 4.0000e-03 eta: 8:03:33 time: 0.2768 data_time: 0.0076 memory: 5828 grad_norm: 3.8317 loss: 1.6497 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6497 2023/06/05 12:59:55 - mmengine - INFO - Epoch(train) [108][1400/2569] lr: 4.0000e-03 eta: 8:03:28 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 3.8492 loss: 1.4416 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4416 2023/06/05 13:00:01 - mmengine - INFO - Epoch(train) [108][1420/2569] lr: 4.0000e-03 eta: 8:03:22 time: 0.2729 data_time: 0.0074 memory: 5828 grad_norm: 3.7788 loss: 1.9690 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9690 2023/06/05 13:00:06 - mmengine - INFO - Epoch(train) [108][1440/2569] lr: 4.0000e-03 eta: 8:03:17 time: 0.2595 data_time: 0.0071 memory: 5828 grad_norm: 3.7959 loss: 1.9021 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9021 2023/06/05 13:00:11 - mmengine - INFO - Epoch(train) [108][1460/2569] lr: 4.0000e-03 eta: 8:03:12 time: 0.2673 data_time: 0.0072 memory: 5828 grad_norm: 3.8269 loss: 2.1501 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1501 2023/06/05 13:00:17 - mmengine - INFO - Epoch(train) [108][1480/2569] lr: 4.0000e-03 eta: 8:03:06 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 3.8172 loss: 2.0277 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0277 2023/06/05 13:00:22 - mmengine - INFO - Epoch(train) [108][1500/2569] lr: 4.0000e-03 eta: 8:03:01 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 3.8150 loss: 1.9477 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9477 2023/06/05 13:00:27 - mmengine - INFO - Epoch(train) [108][1520/2569] lr: 4.0000e-03 eta: 8:02:56 time: 0.2649 data_time: 0.0073 memory: 5828 grad_norm: 3.7340 loss: 2.0749 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0749 2023/06/05 13:00:33 - mmengine - INFO - Epoch(train) [108][1540/2569] lr: 4.0000e-03 eta: 8:02:50 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 3.7745 loss: 1.9218 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9218 2023/06/05 13:00:38 - mmengine - INFO - Epoch(train) [108][1560/2569] lr: 4.0000e-03 eta: 8:02:45 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 3.7200 loss: 1.9606 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9606 2023/06/05 13:00:43 - mmengine - INFO - Epoch(train) [108][1580/2569] lr: 4.0000e-03 eta: 8:02:40 time: 0.2763 data_time: 0.0073 memory: 5828 grad_norm: 3.7575 loss: 1.5112 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5112 2023/06/05 13:00:49 - mmengine - INFO - Epoch(train) [108][1600/2569] lr: 4.0000e-03 eta: 8:02:34 time: 0.2619 data_time: 0.0071 memory: 5828 grad_norm: 3.8237 loss: 1.9720 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9720 2023/06/05 13:00:54 - mmengine - INFO - Epoch(train) [108][1620/2569] lr: 4.0000e-03 eta: 8:02:29 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 3.8317 loss: 1.7751 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7751 2023/06/05 13:00:59 - mmengine - INFO - Epoch(train) [108][1640/2569] lr: 4.0000e-03 eta: 8:02:24 time: 0.2681 data_time: 0.0076 memory: 5828 grad_norm: 3.8261 loss: 1.7179 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7179 2023/06/05 13:01:05 - mmengine - INFO - Epoch(train) [108][1660/2569] lr: 4.0000e-03 eta: 8:02:18 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 3.8031 loss: 2.0701 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0701 2023/06/05 13:01:10 - mmengine - INFO - Epoch(train) [108][1680/2569] lr: 4.0000e-03 eta: 8:02:13 time: 0.2774 data_time: 0.0075 memory: 5828 grad_norm: 3.7775 loss: 1.9606 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9606 2023/06/05 13:01:16 - mmengine - INFO - Epoch(train) [108][1700/2569] lr: 4.0000e-03 eta: 8:02:08 time: 0.2644 data_time: 0.0076 memory: 5828 grad_norm: 3.8186 loss: 1.6985 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6985 2023/06/05 13:01:21 - mmengine - INFO - Epoch(train) [108][1720/2569] lr: 4.0000e-03 eta: 8:02:03 time: 0.2648 data_time: 0.0071 memory: 5828 grad_norm: 3.8159 loss: 1.8845 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8845 2023/06/05 13:01:26 - mmengine - INFO - Epoch(train) [108][1740/2569] lr: 4.0000e-03 eta: 8:01:57 time: 0.2701 data_time: 0.0068 memory: 5828 grad_norm: 3.8124 loss: 1.7616 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7616 2023/06/05 13:01:32 - mmengine - INFO - Epoch(train) [108][1760/2569] lr: 4.0000e-03 eta: 8:01:52 time: 0.2609 data_time: 0.0070 memory: 5828 grad_norm: 3.8518 loss: 2.1268 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1268 2023/06/05 13:01:37 - mmengine - INFO - Epoch(train) [108][1780/2569] lr: 4.0000e-03 eta: 8:01:47 time: 0.2724 data_time: 0.0073 memory: 5828 grad_norm: 3.8288 loss: 1.9225 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9225 2023/06/05 13:01:42 - mmengine - INFO - Epoch(train) [108][1800/2569] lr: 4.0000e-03 eta: 8:01:41 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 3.8438 loss: 1.7721 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.7721 2023/06/05 13:01:48 - mmengine - INFO - Epoch(train) [108][1820/2569] lr: 4.0000e-03 eta: 8:01:36 time: 0.2683 data_time: 0.0070 memory: 5828 grad_norm: 3.7770 loss: 1.9875 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9875 2023/06/05 13:01:53 - mmengine - INFO - Epoch(train) [108][1840/2569] lr: 4.0000e-03 eta: 8:01:31 time: 0.2649 data_time: 0.0070 memory: 5828 grad_norm: 3.7943 loss: 1.7694 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7694 2023/06/05 13:01:58 - mmengine - INFO - Epoch(train) [108][1860/2569] lr: 4.0000e-03 eta: 8:01:25 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 3.7744 loss: 1.8948 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8948 2023/06/05 13:02:04 - mmengine - INFO - Epoch(train) [108][1880/2569] lr: 4.0000e-03 eta: 8:01:20 time: 0.2645 data_time: 0.0071 memory: 5828 grad_norm: 3.8823 loss: 1.9117 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.9117 2023/06/05 13:02:09 - mmengine - INFO - Epoch(train) [108][1900/2569] lr: 4.0000e-03 eta: 8:01:15 time: 0.2652 data_time: 0.0070 memory: 5828 grad_norm: 3.7559 loss: 1.4602 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4602 2023/06/05 13:02:14 - mmengine - INFO - Epoch(train) [108][1920/2569] lr: 4.0000e-03 eta: 8:01:09 time: 0.2813 data_time: 0.0071 memory: 5828 grad_norm: 3.7909 loss: 1.8822 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8822 2023/06/05 13:02:20 - mmengine - INFO - Epoch(train) [108][1940/2569] lr: 4.0000e-03 eta: 8:01:04 time: 0.2613 data_time: 0.0077 memory: 5828 grad_norm: 3.8611 loss: 1.8711 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8711 2023/06/05 13:02:25 - mmengine - INFO - Epoch(train) [108][1960/2569] lr: 4.0000e-03 eta: 8:00:59 time: 0.2737 data_time: 0.0070 memory: 5828 grad_norm: 3.8518 loss: 1.9604 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9604 2023/06/05 13:02:30 - mmengine - INFO - Epoch(train) [108][1980/2569] lr: 4.0000e-03 eta: 8:00:53 time: 0.2611 data_time: 0.0073 memory: 5828 grad_norm: 3.7875 loss: 1.6767 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6767 2023/06/05 13:02:36 - mmengine - INFO - Epoch(train) [108][2000/2569] lr: 4.0000e-03 eta: 8:00:48 time: 0.2650 data_time: 0.0070 memory: 5828 grad_norm: 3.8115 loss: 1.8282 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8282 2023/06/05 13:02:41 - mmengine - INFO - Epoch(train) [108][2020/2569] lr: 4.0000e-03 eta: 8:00:43 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 3.8208 loss: 1.8085 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8085 2023/06/05 13:02:46 - mmengine - INFO - Epoch(train) [108][2040/2569] lr: 4.0000e-03 eta: 8:00:37 time: 0.2615 data_time: 0.0070 memory: 5828 grad_norm: 3.8633 loss: 1.6188 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6188 2023/06/05 13:02:52 - mmengine - INFO - Epoch(train) [108][2060/2569] lr: 4.0000e-03 eta: 8:00:32 time: 0.2716 data_time: 0.0072 memory: 5828 grad_norm: 3.8367 loss: 2.0373 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0373 2023/06/05 13:02:57 - mmengine - INFO - Epoch(train) [108][2080/2569] lr: 4.0000e-03 eta: 8:00:27 time: 0.2608 data_time: 0.0069 memory: 5828 grad_norm: 3.8623 loss: 1.7508 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7508 2023/06/05 13:03:02 - mmengine - INFO - Epoch(train) [108][2100/2569] lr: 4.0000e-03 eta: 8:00:22 time: 0.2663 data_time: 0.0072 memory: 5828 grad_norm: 3.8105 loss: 2.1098 top1_acc: 0.0000 top5_acc: 0.3750 loss_cls: 2.1098 2023/06/05 13:03:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:03:08 - mmengine - INFO - Epoch(train) [108][2120/2569] lr: 4.0000e-03 eta: 8:00:16 time: 0.2672 data_time: 0.0071 memory: 5828 grad_norm: 3.8759 loss: 1.6998 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6998 2023/06/05 13:03:13 - mmengine - INFO - Epoch(train) [108][2140/2569] lr: 4.0000e-03 eta: 8:00:11 time: 0.2603 data_time: 0.0073 memory: 5828 grad_norm: 3.8338 loss: 1.8825 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8825 2023/06/05 13:03:18 - mmengine - INFO - Epoch(train) [108][2160/2569] lr: 4.0000e-03 eta: 8:00:06 time: 0.2758 data_time: 0.0069 memory: 5828 grad_norm: 3.7628 loss: 1.9704 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9704 2023/06/05 13:03:24 - mmengine - INFO - Epoch(train) [108][2180/2569] lr: 4.0000e-03 eta: 8:00:00 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 3.8556 loss: 1.8877 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8877 2023/06/05 13:03:29 - mmengine - INFO - Epoch(train) [108][2200/2569] lr: 4.0000e-03 eta: 7:59:55 time: 0.2690 data_time: 0.0068 memory: 5828 grad_norm: 3.7488 loss: 1.7565 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7565 2023/06/05 13:03:35 - mmengine - INFO - Epoch(train) [108][2220/2569] lr: 4.0000e-03 eta: 7:59:50 time: 0.2711 data_time: 0.0070 memory: 5828 grad_norm: 3.7845 loss: 1.9470 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9470 2023/06/05 13:03:40 - mmengine - INFO - Epoch(train) [108][2240/2569] lr: 4.0000e-03 eta: 7:59:44 time: 0.2670 data_time: 0.0076 memory: 5828 grad_norm: 3.8781 loss: 2.1448 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1448 2023/06/05 13:03:46 - mmengine - INFO - Epoch(train) [108][2260/2569] lr: 4.0000e-03 eta: 7:59:39 time: 0.2904 data_time: 0.0072 memory: 5828 grad_norm: 3.8529 loss: 1.8696 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8696 2023/06/05 13:03:51 - mmengine - INFO - Epoch(train) [108][2280/2569] lr: 4.0000e-03 eta: 7:59:34 time: 0.2733 data_time: 0.0074 memory: 5828 grad_norm: 3.8332 loss: 1.8760 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8760 2023/06/05 13:03:57 - mmengine - INFO - Epoch(train) [108][2300/2569] lr: 4.0000e-03 eta: 7:59:29 time: 0.2662 data_time: 0.0071 memory: 5828 grad_norm: 3.7636 loss: 2.1452 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1452 2023/06/05 13:04:02 - mmengine - INFO - Epoch(train) [108][2320/2569] lr: 4.0000e-03 eta: 7:59:23 time: 0.2689 data_time: 0.0071 memory: 5828 grad_norm: 3.8605 loss: 1.7897 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7897 2023/06/05 13:04:07 - mmengine - INFO - Epoch(train) [108][2340/2569] lr: 4.0000e-03 eta: 7:59:18 time: 0.2608 data_time: 0.0070 memory: 5828 grad_norm: 3.8076 loss: 1.8884 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8884 2023/06/05 13:04:12 - mmengine - INFO - Epoch(train) [108][2360/2569] lr: 4.0000e-03 eta: 7:59:13 time: 0.2649 data_time: 0.0070 memory: 5828 grad_norm: 3.8216 loss: 1.9778 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9778 2023/06/05 13:04:18 - mmengine - INFO - Epoch(train) [108][2380/2569] lr: 4.0000e-03 eta: 7:59:07 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 3.8003 loss: 1.7320 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7320 2023/06/05 13:04:23 - mmengine - INFO - Epoch(train) [108][2400/2569] lr: 4.0000e-03 eta: 7:59:02 time: 0.2639 data_time: 0.0069 memory: 5828 grad_norm: 3.8001 loss: 1.6178 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6178 2023/06/05 13:04:28 - mmengine - INFO - Epoch(train) [108][2420/2569] lr: 4.0000e-03 eta: 7:58:57 time: 0.2629 data_time: 0.0073 memory: 5828 grad_norm: 3.8801 loss: 1.9534 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9534 2023/06/05 13:04:34 - mmengine - INFO - Epoch(train) [108][2440/2569] lr: 4.0000e-03 eta: 7:58:51 time: 0.2649 data_time: 0.0068 memory: 5828 grad_norm: 3.7540 loss: 1.9648 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9648 2023/06/05 13:04:39 - mmengine - INFO - Epoch(train) [108][2460/2569] lr: 4.0000e-03 eta: 7:58:46 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 3.8468 loss: 1.9372 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9372 2023/06/05 13:04:44 - mmengine - INFO - Epoch(train) [108][2480/2569] lr: 4.0000e-03 eta: 7:58:41 time: 0.2639 data_time: 0.0071 memory: 5828 grad_norm: 3.8013 loss: 1.9121 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9121 2023/06/05 13:04:50 - mmengine - INFO - Epoch(train) [108][2500/2569] lr: 4.0000e-03 eta: 7:58:35 time: 0.2720 data_time: 0.0071 memory: 5828 grad_norm: 3.8262 loss: 1.7807 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7807 2023/06/05 13:04:55 - mmengine - INFO - Epoch(train) [108][2520/2569] lr: 4.0000e-03 eta: 7:58:30 time: 0.2595 data_time: 0.0070 memory: 5828 grad_norm: 3.7585 loss: 1.9930 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9930 2023/06/05 13:05:00 - mmengine - INFO - Epoch(train) [108][2540/2569] lr: 4.0000e-03 eta: 7:58:25 time: 0.2691 data_time: 0.0072 memory: 5828 grad_norm: 3.8529 loss: 1.8604 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8604 2023/06/05 13:05:06 - mmengine - INFO - Epoch(train) [108][2560/2569] lr: 4.0000e-03 eta: 7:58:19 time: 0.2589 data_time: 0.0073 memory: 5828 grad_norm: 3.7585 loss: 1.6918 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6918 2023/06/05 13:05:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:05:08 - mmengine - INFO - Epoch(train) [108][2569/2569] lr: 4.0000e-03 eta: 7:58:17 time: 0.2531 data_time: 0.0069 memory: 5828 grad_norm: 3.8048 loss: 2.1290 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.1290 2023/06/05 13:05:08 - mmengine - INFO - Saving checkpoint at 108 epochs 2023/06/05 13:05:16 - mmengine - INFO - Epoch(train) [109][ 20/2569] lr: 4.0000e-03 eta: 7:58:12 time: 0.3063 data_time: 0.0378 memory: 5828 grad_norm: 3.7361 loss: 1.9379 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9379 2023/06/05 13:05:21 - mmengine - INFO - Epoch(train) [109][ 40/2569] lr: 4.0000e-03 eta: 7:58:07 time: 0.2720 data_time: 0.0067 memory: 5828 grad_norm: 3.7826 loss: 1.6441 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6441 2023/06/05 13:05:27 - mmengine - INFO - Epoch(train) [109][ 60/2569] lr: 4.0000e-03 eta: 7:58:01 time: 0.2674 data_time: 0.0070 memory: 5828 grad_norm: 3.8022 loss: 1.8929 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8929 2023/06/05 13:05:32 - mmengine - INFO - Epoch(train) [109][ 80/2569] lr: 4.0000e-03 eta: 7:57:56 time: 0.2650 data_time: 0.0070 memory: 5828 grad_norm: 3.8164 loss: 1.6981 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6981 2023/06/05 13:05:37 - mmengine - INFO - Epoch(train) [109][ 100/2569] lr: 4.0000e-03 eta: 7:57:51 time: 0.2696 data_time: 0.0076 memory: 5828 grad_norm: 3.7555 loss: 1.7828 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7828 2023/06/05 13:05:43 - mmengine - INFO - Epoch(train) [109][ 120/2569] lr: 4.0000e-03 eta: 7:57:45 time: 0.2616 data_time: 0.0068 memory: 5828 grad_norm: 3.8058 loss: 2.1639 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1639 2023/06/05 13:05:48 - mmengine - INFO - Epoch(train) [109][ 140/2569] lr: 4.0000e-03 eta: 7:57:40 time: 0.2723 data_time: 0.0070 memory: 5828 grad_norm: 3.8206 loss: 1.8901 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8901 2023/06/05 13:05:53 - mmengine - INFO - Epoch(train) [109][ 160/2569] lr: 4.0000e-03 eta: 7:57:35 time: 0.2615 data_time: 0.0069 memory: 5828 grad_norm: 3.7686 loss: 1.8454 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8454 2023/06/05 13:05:59 - mmengine - INFO - Epoch(train) [109][ 180/2569] lr: 4.0000e-03 eta: 7:57:30 time: 0.2701 data_time: 0.0074 memory: 5828 grad_norm: 3.8639 loss: 2.1944 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1944 2023/06/05 13:06:04 - mmengine - INFO - Epoch(train) [109][ 200/2569] lr: 4.0000e-03 eta: 7:57:24 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 3.8129 loss: 1.7853 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7853 2023/06/05 13:06:10 - mmengine - INFO - Epoch(train) [109][ 220/2569] lr: 4.0000e-03 eta: 7:57:19 time: 0.2791 data_time: 0.0068 memory: 5828 grad_norm: 3.8444 loss: 1.6801 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6801 2023/06/05 13:06:15 - mmengine - INFO - Epoch(train) [109][ 240/2569] lr: 4.0000e-03 eta: 7:57:14 time: 0.2619 data_time: 0.0070 memory: 5828 grad_norm: 3.8377 loss: 2.0289 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0289 2023/06/05 13:06:20 - mmengine - INFO - Epoch(train) [109][ 260/2569] lr: 4.0000e-03 eta: 7:57:08 time: 0.2702 data_time: 0.0071 memory: 5828 grad_norm: 3.8208 loss: 1.8423 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8423 2023/06/05 13:06:26 - mmengine - INFO - Epoch(train) [109][ 280/2569] lr: 4.0000e-03 eta: 7:57:03 time: 0.2614 data_time: 0.0075 memory: 5828 grad_norm: 3.8535 loss: 1.9993 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9993 2023/06/05 13:06:31 - mmengine - INFO - Epoch(train) [109][ 300/2569] lr: 4.0000e-03 eta: 7:56:58 time: 0.2735 data_time: 0.0071 memory: 5828 grad_norm: 3.8634 loss: 2.1656 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1656 2023/06/05 13:06:36 - mmengine - INFO - Epoch(train) [109][ 320/2569] lr: 4.0000e-03 eta: 7:56:52 time: 0.2645 data_time: 0.0070 memory: 5828 grad_norm: 3.8110 loss: 1.9059 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9059 2023/06/05 13:06:42 - mmengine - INFO - Epoch(train) [109][ 340/2569] lr: 4.0000e-03 eta: 7:56:47 time: 0.2726 data_time: 0.0071 memory: 5828 grad_norm: 3.9453 loss: 1.9090 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9090 2023/06/05 13:06:47 - mmengine - INFO - Epoch(train) [109][ 360/2569] lr: 4.0000e-03 eta: 7:56:42 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 3.8369 loss: 2.0080 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0080 2023/06/05 13:06:53 - mmengine - INFO - Epoch(train) [109][ 380/2569] lr: 4.0000e-03 eta: 7:56:37 time: 0.2701 data_time: 0.0077 memory: 5828 grad_norm: 3.8597 loss: 1.8065 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8065 2023/06/05 13:06:58 - mmengine - INFO - Epoch(train) [109][ 400/2569] lr: 4.0000e-03 eta: 7:56:31 time: 0.2689 data_time: 0.0075 memory: 5828 grad_norm: 3.8389 loss: 2.0285 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0285 2023/06/05 13:07:03 - mmengine - INFO - Epoch(train) [109][ 420/2569] lr: 4.0000e-03 eta: 7:56:26 time: 0.2672 data_time: 0.0076 memory: 5828 grad_norm: 3.8037 loss: 2.1695 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1695 2023/06/05 13:07:09 - mmengine - INFO - Epoch(train) [109][ 440/2569] lr: 4.0000e-03 eta: 7:56:21 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 3.8595 loss: 1.9931 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9931 2023/06/05 13:07:14 - mmengine - INFO - Epoch(train) [109][ 460/2569] lr: 4.0000e-03 eta: 7:56:15 time: 0.2774 data_time: 0.0073 memory: 5828 grad_norm: 3.8877 loss: 1.9458 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9458 2023/06/05 13:07:19 - mmengine - INFO - Epoch(train) [109][ 480/2569] lr: 4.0000e-03 eta: 7:56:10 time: 0.2599 data_time: 0.0077 memory: 5828 grad_norm: 3.9110 loss: 2.1572 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1572 2023/06/05 13:07:25 - mmengine - INFO - Epoch(train) [109][ 500/2569] lr: 4.0000e-03 eta: 7:56:05 time: 0.2830 data_time: 0.0071 memory: 5828 grad_norm: 3.8336 loss: 1.4692 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.4692 2023/06/05 13:07:30 - mmengine - INFO - Epoch(train) [109][ 520/2569] lr: 4.0000e-03 eta: 7:56:00 time: 0.2666 data_time: 0.0079 memory: 5828 grad_norm: 3.9066 loss: 2.1515 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1515 2023/06/05 13:07:36 - mmengine - INFO - Epoch(train) [109][ 540/2569] lr: 4.0000e-03 eta: 7:55:54 time: 0.2715 data_time: 0.0070 memory: 5828 grad_norm: 3.8299 loss: 1.5731 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5731 2023/06/05 13:07:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:07:42 - mmengine - INFO - Epoch(train) [109][ 560/2569] lr: 4.0000e-03 eta: 7:55:49 time: 0.2818 data_time: 0.0072 memory: 5828 grad_norm: 3.8931 loss: 1.7419 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7419 2023/06/05 13:07:47 - mmengine - INFO - Epoch(train) [109][ 580/2569] lr: 4.0000e-03 eta: 7:55:44 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 3.8434 loss: 1.9963 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9963 2023/06/05 13:07:52 - mmengine - INFO - Epoch(train) [109][ 600/2569] lr: 4.0000e-03 eta: 7:55:38 time: 0.2755 data_time: 0.0069 memory: 5828 grad_norm: 3.8421 loss: 2.0664 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0664 2023/06/05 13:07:58 - mmengine - INFO - Epoch(train) [109][ 620/2569] lr: 4.0000e-03 eta: 7:55:33 time: 0.2611 data_time: 0.0073 memory: 5828 grad_norm: 3.8429 loss: 1.9311 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9311 2023/06/05 13:08:03 - mmengine - INFO - Epoch(train) [109][ 640/2569] lr: 4.0000e-03 eta: 7:55:28 time: 0.2728 data_time: 0.0071 memory: 5828 grad_norm: 3.9005 loss: 1.8606 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8606 2023/06/05 13:08:08 - mmengine - INFO - Epoch(train) [109][ 660/2569] lr: 4.0000e-03 eta: 7:55:22 time: 0.2617 data_time: 0.0070 memory: 5828 grad_norm: 3.9213 loss: 1.9172 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.9172 2023/06/05 13:08:14 - mmengine - INFO - Epoch(train) [109][ 680/2569] lr: 4.0000e-03 eta: 7:55:17 time: 0.2744 data_time: 0.0070 memory: 5828 grad_norm: 3.8906 loss: 1.6529 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6529 2023/06/05 13:08:19 - mmengine - INFO - Epoch(train) [109][ 700/2569] lr: 4.0000e-03 eta: 7:55:12 time: 0.2631 data_time: 0.0070 memory: 5828 grad_norm: 3.8556 loss: 1.9883 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9883 2023/06/05 13:08:24 - mmengine - INFO - Epoch(train) [109][ 720/2569] lr: 4.0000e-03 eta: 7:55:07 time: 0.2687 data_time: 0.0076 memory: 5828 grad_norm: 3.8087 loss: 2.0122 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0122 2023/06/05 13:08:30 - mmengine - INFO - Epoch(train) [109][ 740/2569] lr: 4.0000e-03 eta: 7:55:01 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 3.8055 loss: 1.6629 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6629 2023/06/05 13:08:35 - mmengine - INFO - Epoch(train) [109][ 760/2569] lr: 4.0000e-03 eta: 7:54:56 time: 0.2655 data_time: 0.0077 memory: 5828 grad_norm: 3.8770 loss: 1.6369 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6369 2023/06/05 13:08:40 - mmengine - INFO - Epoch(train) [109][ 780/2569] lr: 4.0000e-03 eta: 7:54:51 time: 0.2630 data_time: 0.0071 memory: 5828 grad_norm: 3.9019 loss: 2.1036 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1036 2023/06/05 13:08:46 - mmengine - INFO - Epoch(train) [109][ 800/2569] lr: 4.0000e-03 eta: 7:54:45 time: 0.2697 data_time: 0.0073 memory: 5828 grad_norm: 3.8277 loss: 1.8526 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8526 2023/06/05 13:08:51 - mmengine - INFO - Epoch(train) [109][ 820/2569] lr: 4.0000e-03 eta: 7:54:40 time: 0.2736 data_time: 0.0076 memory: 5828 grad_norm: 3.8334 loss: 2.1202 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1202 2023/06/05 13:08:57 - mmengine - INFO - Epoch(train) [109][ 840/2569] lr: 4.0000e-03 eta: 7:54:35 time: 0.2728 data_time: 0.0069 memory: 5828 grad_norm: 3.9505 loss: 1.9999 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 1.9999 2023/06/05 13:09:02 - mmengine - INFO - Epoch(train) [109][ 860/2569] lr: 4.0000e-03 eta: 7:54:29 time: 0.2630 data_time: 0.0070 memory: 5828 grad_norm: 3.8134 loss: 1.8968 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8968 2023/06/05 13:09:07 - mmengine - INFO - Epoch(train) [109][ 880/2569] lr: 4.0000e-03 eta: 7:54:24 time: 0.2718 data_time: 0.0073 memory: 5828 grad_norm: 3.7049 loss: 1.5601 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5601 2023/06/05 13:09:13 - mmengine - INFO - Epoch(train) [109][ 900/2569] lr: 4.0000e-03 eta: 7:54:19 time: 0.2686 data_time: 0.0072 memory: 5828 grad_norm: 3.8097 loss: 1.6162 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6162 2023/06/05 13:09:18 - mmengine - INFO - Epoch(train) [109][ 920/2569] lr: 4.0000e-03 eta: 7:54:14 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 3.8067 loss: 1.8057 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8057 2023/06/05 13:09:23 - mmengine - INFO - Epoch(train) [109][ 940/2569] lr: 4.0000e-03 eta: 7:54:08 time: 0.2660 data_time: 0.0069 memory: 5828 grad_norm: 3.8252 loss: 1.6547 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6547 2023/06/05 13:09:29 - mmengine - INFO - Epoch(train) [109][ 960/2569] lr: 4.0000e-03 eta: 7:54:03 time: 0.2713 data_time: 0.0072 memory: 5828 grad_norm: 3.8323 loss: 2.2406 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2406 2023/06/05 13:09:34 - mmengine - INFO - Epoch(train) [109][ 980/2569] lr: 4.0000e-03 eta: 7:53:58 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 3.8260 loss: 2.0117 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0117 2023/06/05 13:09:40 - mmengine - INFO - Epoch(train) [109][1000/2569] lr: 4.0000e-03 eta: 7:53:52 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 3.8556 loss: 1.9796 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9796 2023/06/05 13:09:45 - mmengine - INFO - Epoch(train) [109][1020/2569] lr: 4.0000e-03 eta: 7:53:47 time: 0.2719 data_time: 0.0072 memory: 5828 grad_norm: 3.8636 loss: 1.5497 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5497 2023/06/05 13:09:50 - mmengine - INFO - Epoch(train) [109][1040/2569] lr: 4.0000e-03 eta: 7:53:42 time: 0.2613 data_time: 0.0071 memory: 5828 grad_norm: 3.9160 loss: 2.2498 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.2498 2023/06/05 13:09:56 - mmengine - INFO - Epoch(train) [109][1060/2569] lr: 4.0000e-03 eta: 7:53:36 time: 0.2786 data_time: 0.0078 memory: 5828 grad_norm: 3.9010 loss: 2.1028 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.1028 2023/06/05 13:10:01 - mmengine - INFO - Epoch(train) [109][1080/2569] lr: 4.0000e-03 eta: 7:53:31 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 3.7233 loss: 1.9055 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9055 2023/06/05 13:10:07 - mmengine - INFO - Epoch(train) [109][1100/2569] lr: 4.0000e-03 eta: 7:53:26 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 3.9542 loss: 1.9119 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9119 2023/06/05 13:10:12 - mmengine - INFO - Epoch(train) [109][1120/2569] lr: 4.0000e-03 eta: 7:53:21 time: 0.2710 data_time: 0.0076 memory: 5828 grad_norm: 3.9419 loss: 2.0354 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0354 2023/06/05 13:10:17 - mmengine - INFO - Epoch(train) [109][1140/2569] lr: 4.0000e-03 eta: 7:53:15 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 3.8596 loss: 1.8984 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8984 2023/06/05 13:10:22 - mmengine - INFO - Epoch(train) [109][1160/2569] lr: 4.0000e-03 eta: 7:53:10 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 3.7894 loss: 1.9718 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9718 2023/06/05 13:10:28 - mmengine - INFO - Epoch(train) [109][1180/2569] lr: 4.0000e-03 eta: 7:53:05 time: 0.2650 data_time: 0.0071 memory: 5828 grad_norm: 3.8788 loss: 1.7072 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7072 2023/06/05 13:10:33 - mmengine - INFO - Epoch(train) [109][1200/2569] lr: 4.0000e-03 eta: 7:52:59 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 3.8700 loss: 1.9870 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9870 2023/06/05 13:10:38 - mmengine - INFO - Epoch(train) [109][1220/2569] lr: 4.0000e-03 eta: 7:52:54 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 3.9109 loss: 1.9659 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9659 2023/06/05 13:10:44 - mmengine - INFO - Epoch(train) [109][1240/2569] lr: 4.0000e-03 eta: 7:52:49 time: 0.2673 data_time: 0.0071 memory: 5828 grad_norm: 3.9603 loss: 1.7792 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7792 2023/06/05 13:10:49 - mmengine - INFO - Epoch(train) [109][1260/2569] lr: 4.0000e-03 eta: 7:52:43 time: 0.2600 data_time: 0.0072 memory: 5828 grad_norm: 3.8519 loss: 1.9248 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9248 2023/06/05 13:10:54 - mmengine - INFO - Epoch(train) [109][1280/2569] lr: 4.0000e-03 eta: 7:52:38 time: 0.2604 data_time: 0.0073 memory: 5828 grad_norm: 3.8632 loss: 1.6855 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6855 2023/06/05 13:10:59 - mmengine - INFO - Epoch(train) [109][1300/2569] lr: 4.0000e-03 eta: 7:52:33 time: 0.2671 data_time: 0.0071 memory: 5828 grad_norm: 3.9006 loss: 1.8229 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8229 2023/06/05 13:11:05 - mmengine - INFO - Epoch(train) [109][1320/2569] lr: 4.0000e-03 eta: 7:52:27 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 3.8250 loss: 1.9466 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9466 2023/06/05 13:11:10 - mmengine - INFO - Epoch(train) [109][1340/2569] lr: 4.0000e-03 eta: 7:52:22 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 3.7838 loss: 1.9579 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9579 2023/06/05 13:11:16 - mmengine - INFO - Epoch(train) [109][1360/2569] lr: 4.0000e-03 eta: 7:52:17 time: 0.2713 data_time: 0.0073 memory: 5828 grad_norm: 3.8960 loss: 2.1781 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1781 2023/06/05 13:11:21 - mmengine - INFO - Epoch(train) [109][1380/2569] lr: 4.0000e-03 eta: 7:52:11 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 3.8247 loss: 1.8837 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8837 2023/06/05 13:11:26 - mmengine - INFO - Epoch(train) [109][1400/2569] lr: 4.0000e-03 eta: 7:52:06 time: 0.2713 data_time: 0.0070 memory: 5828 grad_norm: 3.8220 loss: 1.7320 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7320 2023/06/05 13:11:32 - mmengine - INFO - Epoch(train) [109][1420/2569] lr: 4.0000e-03 eta: 7:52:01 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 3.8198 loss: 1.5424 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5424 2023/06/05 13:11:37 - mmengine - INFO - Epoch(train) [109][1440/2569] lr: 4.0000e-03 eta: 7:51:55 time: 0.2713 data_time: 0.0070 memory: 5828 grad_norm: 3.8632 loss: 1.8957 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8957 2023/06/05 13:11:42 - mmengine - INFO - Epoch(train) [109][1460/2569] lr: 4.0000e-03 eta: 7:51:50 time: 0.2614 data_time: 0.0071 memory: 5828 grad_norm: 3.8184 loss: 1.9941 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9941 2023/06/05 13:11:47 - mmengine - INFO - Epoch(train) [109][1480/2569] lr: 4.0000e-03 eta: 7:51:45 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 3.8531 loss: 2.0367 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0367 2023/06/05 13:11:53 - mmengine - INFO - Epoch(train) [109][1500/2569] lr: 4.0000e-03 eta: 7:51:39 time: 0.2617 data_time: 0.0070 memory: 5828 grad_norm: 3.8984 loss: 1.9506 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9506 2023/06/05 13:11:58 - mmengine - INFO - Epoch(train) [109][1520/2569] lr: 4.0000e-03 eta: 7:51:34 time: 0.2604 data_time: 0.0073 memory: 5828 grad_norm: 3.8465 loss: 1.7633 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7633 2023/06/05 13:12:03 - mmengine - INFO - Epoch(train) [109][1540/2569] lr: 4.0000e-03 eta: 7:51:29 time: 0.2644 data_time: 0.0069 memory: 5828 grad_norm: 3.7892 loss: 1.9591 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9591 2023/06/05 13:12:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:12:08 - mmengine - INFO - Epoch(train) [109][1560/2569] lr: 4.0000e-03 eta: 7:51:23 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 3.8590 loss: 1.9058 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9058 2023/06/05 13:12:14 - mmengine - INFO - Epoch(train) [109][1580/2569] lr: 4.0000e-03 eta: 7:51:18 time: 0.2718 data_time: 0.0073 memory: 5828 grad_norm: 3.9351 loss: 1.9140 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9140 2023/06/05 13:12:19 - mmengine - INFO - Epoch(train) [109][1600/2569] lr: 4.0000e-03 eta: 7:51:13 time: 0.2619 data_time: 0.0074 memory: 5828 grad_norm: 3.9174 loss: 1.9826 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9826 2023/06/05 13:12:25 - mmengine - INFO - Epoch(train) [109][1620/2569] lr: 4.0000e-03 eta: 7:51:07 time: 0.2677 data_time: 0.0070 memory: 5828 grad_norm: 3.9518 loss: 2.0860 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.0860 2023/06/05 13:12:30 - mmengine - INFO - Epoch(train) [109][1640/2569] lr: 4.0000e-03 eta: 7:51:02 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 3.8429 loss: 1.6822 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6822 2023/06/05 13:12:36 - mmengine - INFO - Epoch(train) [109][1660/2569] lr: 4.0000e-03 eta: 7:50:57 time: 0.2853 data_time: 0.0070 memory: 5828 grad_norm: 3.9935 loss: 1.6179 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6179 2023/06/05 13:12:41 - mmengine - INFO - Epoch(train) [109][1680/2569] lr: 4.0000e-03 eta: 7:50:52 time: 0.2720 data_time: 0.0071 memory: 5828 grad_norm: 3.9111 loss: 1.7212 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7212 2023/06/05 13:12:46 - mmengine - INFO - Epoch(train) [109][1700/2569] lr: 4.0000e-03 eta: 7:50:46 time: 0.2634 data_time: 0.0070 memory: 5828 grad_norm: 3.8273 loss: 2.1254 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1254 2023/06/05 13:12:52 - mmengine - INFO - Epoch(train) [109][1720/2569] lr: 4.0000e-03 eta: 7:50:41 time: 0.2681 data_time: 0.0069 memory: 5828 grad_norm: 3.8811 loss: 1.8920 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8920 2023/06/05 13:12:57 - mmengine - INFO - Epoch(train) [109][1740/2569] lr: 4.0000e-03 eta: 7:50:36 time: 0.2736 data_time: 0.0073 memory: 5828 grad_norm: 3.8521 loss: 1.8959 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8959 2023/06/05 13:13:03 - mmengine - INFO - Epoch(train) [109][1760/2569] lr: 4.0000e-03 eta: 7:50:30 time: 0.2722 data_time: 0.0073 memory: 5828 grad_norm: 3.8793 loss: 1.6557 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6557 2023/06/05 13:13:08 - mmengine - INFO - Epoch(train) [109][1780/2569] lr: 4.0000e-03 eta: 7:50:25 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 3.8875 loss: 2.0811 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0811 2023/06/05 13:13:13 - mmengine - INFO - Epoch(train) [109][1800/2569] lr: 4.0000e-03 eta: 7:50:20 time: 0.2614 data_time: 0.0070 memory: 5828 grad_norm: 3.7781 loss: 1.7041 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7041 2023/06/05 13:13:19 - mmengine - INFO - Epoch(train) [109][1820/2569] lr: 4.0000e-03 eta: 7:50:14 time: 0.2709 data_time: 0.0072 memory: 5828 grad_norm: 3.8846 loss: 1.7071 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7071 2023/06/05 13:13:24 - mmengine - INFO - Epoch(train) [109][1840/2569] lr: 4.0000e-03 eta: 7:50:09 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 3.8476 loss: 1.7041 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7041 2023/06/05 13:13:29 - mmengine - INFO - Epoch(train) [109][1860/2569] lr: 4.0000e-03 eta: 7:50:04 time: 0.2629 data_time: 0.0078 memory: 5828 grad_norm: 3.8185 loss: 1.8274 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.8274 2023/06/05 13:13:35 - mmengine - INFO - Epoch(train) [109][1880/2569] lr: 4.0000e-03 eta: 7:49:59 time: 0.2690 data_time: 0.0073 memory: 5828 grad_norm: 3.8966 loss: 1.7539 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7539 2023/06/05 13:13:40 - mmengine - INFO - Epoch(train) [109][1900/2569] lr: 4.0000e-03 eta: 7:49:53 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 3.8734 loss: 2.0220 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0220 2023/06/05 13:13:45 - mmengine - INFO - Epoch(train) [109][1920/2569] lr: 4.0000e-03 eta: 7:49:48 time: 0.2665 data_time: 0.0069 memory: 5828 grad_norm: 3.9105 loss: 2.0819 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0819 2023/06/05 13:13:50 - mmengine - INFO - Epoch(train) [109][1940/2569] lr: 4.0000e-03 eta: 7:49:42 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 3.9323 loss: 1.5292 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5292 2023/06/05 13:13:56 - mmengine - INFO - Epoch(train) [109][1960/2569] lr: 4.0000e-03 eta: 7:49:37 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 3.9129 loss: 2.0892 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0892 2023/06/05 13:14:01 - mmengine - INFO - Epoch(train) [109][1980/2569] lr: 4.0000e-03 eta: 7:49:32 time: 0.2612 data_time: 0.0069 memory: 5828 grad_norm: 3.9962 loss: 1.8384 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.8384 2023/06/05 13:14:06 - mmengine - INFO - Epoch(train) [109][2000/2569] lr: 4.0000e-03 eta: 7:49:27 time: 0.2735 data_time: 0.0072 memory: 5828 grad_norm: 3.8648 loss: 1.8257 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8257 2023/06/05 13:14:12 - mmengine - INFO - Epoch(train) [109][2020/2569] lr: 4.0000e-03 eta: 7:49:21 time: 0.2658 data_time: 0.0071 memory: 5828 grad_norm: 3.9129 loss: 1.9022 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9022 2023/06/05 13:14:18 - mmengine - INFO - Epoch(train) [109][2040/2569] lr: 4.0000e-03 eta: 7:49:16 time: 0.2953 data_time: 0.0075 memory: 5828 grad_norm: 3.9072 loss: 2.0543 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0543 2023/06/05 13:14:23 - mmengine - INFO - Epoch(train) [109][2060/2569] lr: 4.0000e-03 eta: 7:49:11 time: 0.2636 data_time: 0.0070 memory: 5828 grad_norm: 3.8909 loss: 1.5989 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5989 2023/06/05 13:14:29 - mmengine - INFO - Epoch(train) [109][2080/2569] lr: 4.0000e-03 eta: 7:49:06 time: 0.2815 data_time: 0.0073 memory: 5828 grad_norm: 3.9297 loss: 2.0164 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.0164 2023/06/05 13:14:34 - mmengine - INFO - Epoch(train) [109][2100/2569] lr: 4.0000e-03 eta: 7:49:00 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 3.9411 loss: 2.1881 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1881 2023/06/05 13:14:40 - mmengine - INFO - Epoch(train) [109][2120/2569] lr: 4.0000e-03 eta: 7:48:55 time: 0.2878 data_time: 0.0072 memory: 5828 grad_norm: 3.8831 loss: 1.9381 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9381 2023/06/05 13:14:45 - mmengine - INFO - Epoch(train) [109][2140/2569] lr: 4.0000e-03 eta: 7:48:50 time: 0.2740 data_time: 0.0069 memory: 5828 grad_norm: 3.8818 loss: 2.1426 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1426 2023/06/05 13:14:51 - mmengine - INFO - Epoch(train) [109][2160/2569] lr: 4.0000e-03 eta: 7:48:45 time: 0.2730 data_time: 0.0073 memory: 5828 grad_norm: 3.8695 loss: 1.8046 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8046 2023/06/05 13:14:56 - mmengine - INFO - Epoch(train) [109][2180/2569] lr: 4.0000e-03 eta: 7:48:39 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 3.8555 loss: 2.1001 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1001 2023/06/05 13:15:02 - mmengine - INFO - Epoch(train) [109][2200/2569] lr: 4.0000e-03 eta: 7:48:34 time: 0.2743 data_time: 0.0072 memory: 5828 grad_norm: 3.8871 loss: 1.8848 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8848 2023/06/05 13:15:07 - mmengine - INFO - Epoch(train) [109][2220/2569] lr: 4.0000e-03 eta: 7:48:29 time: 0.2660 data_time: 0.0069 memory: 5828 grad_norm: 3.8862 loss: 1.9691 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.9691 2023/06/05 13:15:12 - mmengine - INFO - Epoch(train) [109][2240/2569] lr: 4.0000e-03 eta: 7:48:23 time: 0.2751 data_time: 0.0069 memory: 5828 grad_norm: 3.8739 loss: 2.0517 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0517 2023/06/05 13:15:18 - mmengine - INFO - Epoch(train) [109][2260/2569] lr: 4.0000e-03 eta: 7:48:18 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 3.8351 loss: 1.7945 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7945 2023/06/05 13:15:23 - mmengine - INFO - Epoch(train) [109][2280/2569] lr: 4.0000e-03 eta: 7:48:13 time: 0.2629 data_time: 0.0074 memory: 5828 grad_norm: 3.9272 loss: 2.1212 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1212 2023/06/05 13:15:28 - mmengine - INFO - Epoch(train) [109][2300/2569] lr: 4.0000e-03 eta: 7:48:07 time: 0.2650 data_time: 0.0077 memory: 5828 grad_norm: 3.8937 loss: 1.6342 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6342 2023/06/05 13:15:33 - mmengine - INFO - Epoch(train) [109][2320/2569] lr: 4.0000e-03 eta: 7:48:02 time: 0.2624 data_time: 0.0070 memory: 5828 grad_norm: 3.9094 loss: 1.6910 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6910 2023/06/05 13:15:39 - mmengine - INFO - Epoch(train) [109][2340/2569] lr: 4.0000e-03 eta: 7:47:57 time: 0.2780 data_time: 0.0073 memory: 5828 grad_norm: 3.8396 loss: 1.7094 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7094 2023/06/05 13:15:44 - mmengine - INFO - Epoch(train) [109][2360/2569] lr: 4.0000e-03 eta: 7:47:52 time: 0.2648 data_time: 0.0073 memory: 5828 grad_norm: 3.9076 loss: 2.1633 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1633 2023/06/05 13:15:50 - mmengine - INFO - Epoch(train) [109][2380/2569] lr: 4.0000e-03 eta: 7:47:46 time: 0.2746 data_time: 0.0072 memory: 5828 grad_norm: 3.9481 loss: 2.0244 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0244 2023/06/05 13:15:55 - mmengine - INFO - Epoch(train) [109][2400/2569] lr: 4.0000e-03 eta: 7:47:41 time: 0.2644 data_time: 0.0073 memory: 5828 grad_norm: 3.8654 loss: 1.7507 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7507 2023/06/05 13:16:00 - mmengine - INFO - Epoch(train) [109][2420/2569] lr: 4.0000e-03 eta: 7:47:36 time: 0.2661 data_time: 0.0070 memory: 5828 grad_norm: 3.9372 loss: 1.7573 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7573 2023/06/05 13:16:06 - mmengine - INFO - Epoch(train) [109][2440/2569] lr: 4.0000e-03 eta: 7:47:30 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 3.9349 loss: 1.6543 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6543 2023/06/05 13:16:11 - mmengine - INFO - Epoch(train) [109][2460/2569] lr: 4.0000e-03 eta: 7:47:25 time: 0.2668 data_time: 0.0074 memory: 5828 grad_norm: 3.8450 loss: 1.8059 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8059 2023/06/05 13:16:17 - mmengine - INFO - Epoch(train) [109][2480/2569] lr: 4.0000e-03 eta: 7:47:20 time: 0.2735 data_time: 0.0073 memory: 5828 grad_norm: 3.9643 loss: 1.9965 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9965 2023/06/05 13:16:22 - mmengine - INFO - Epoch(train) [109][2500/2569] lr: 4.0000e-03 eta: 7:47:14 time: 0.2615 data_time: 0.0071 memory: 5828 grad_norm: 3.9119 loss: 2.0034 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0034 2023/06/05 13:16:27 - mmengine - INFO - Epoch(train) [109][2520/2569] lr: 4.0000e-03 eta: 7:47:09 time: 0.2685 data_time: 0.0074 memory: 5828 grad_norm: 3.8724 loss: 1.6452 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6452 2023/06/05 13:16:33 - mmengine - INFO - Epoch(train) [109][2540/2569] lr: 4.0000e-03 eta: 7:47:04 time: 0.2655 data_time: 0.0069 memory: 5828 grad_norm: 3.8806 loss: 2.1672 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1672 2023/06/05 13:16:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:16:38 - mmengine - INFO - Epoch(train) [109][2560/2569] lr: 4.0000e-03 eta: 7:46:58 time: 0.2584 data_time: 0.0073 memory: 5828 grad_norm: 3.9176 loss: 1.9793 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9793 2023/06/05 13:16:40 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:16:40 - mmengine - INFO - Epoch(train) [109][2569/2569] lr: 4.0000e-03 eta: 7:46:56 time: 0.2587 data_time: 0.0071 memory: 5828 grad_norm: 3.9566 loss: 2.2117 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 2.2117 2023/06/05 13:16:47 - mmengine - INFO - Epoch(train) [110][ 20/2569] lr: 4.0000e-03 eta: 7:46:51 time: 0.3523 data_time: 0.0591 memory: 5828 grad_norm: 3.9351 loss: 2.1130 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1130 2023/06/05 13:16:53 - mmengine - INFO - Epoch(train) [110][ 40/2569] lr: 4.0000e-03 eta: 7:46:46 time: 0.2723 data_time: 0.0070 memory: 5828 grad_norm: 3.7931 loss: 2.0029 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0029 2023/06/05 13:16:58 - mmengine - INFO - Epoch(train) [110][ 60/2569] lr: 4.0000e-03 eta: 7:46:41 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 3.9355 loss: 1.9926 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9926 2023/06/05 13:17:03 - mmengine - INFO - Epoch(train) [110][ 80/2569] lr: 4.0000e-03 eta: 7:46:35 time: 0.2708 data_time: 0.0082 memory: 5828 grad_norm: 3.9571 loss: 2.1057 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1057 2023/06/05 13:17:09 - mmengine - INFO - Epoch(train) [110][ 100/2569] lr: 4.0000e-03 eta: 7:46:30 time: 0.2706 data_time: 0.0075 memory: 5828 grad_norm: 3.8552 loss: 1.8180 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8180 2023/06/05 13:17:14 - mmengine - INFO - Epoch(train) [110][ 120/2569] lr: 4.0000e-03 eta: 7:46:25 time: 0.2712 data_time: 0.0089 memory: 5828 grad_norm: 3.8711 loss: 1.6711 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6711 2023/06/05 13:17:19 - mmengine - INFO - Epoch(train) [110][ 140/2569] lr: 4.0000e-03 eta: 7:46:19 time: 0.2648 data_time: 0.0076 memory: 5828 grad_norm: 3.9570 loss: 2.0745 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0745 2023/06/05 13:17:25 - mmengine - INFO - Epoch(train) [110][ 160/2569] lr: 4.0000e-03 eta: 7:46:14 time: 0.2693 data_time: 0.0074 memory: 5828 grad_norm: 3.9705 loss: 1.9596 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9596 2023/06/05 13:17:30 - mmengine - INFO - Epoch(train) [110][ 180/2569] lr: 4.0000e-03 eta: 7:46:09 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 3.8696 loss: 1.9104 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9104 2023/06/05 13:17:36 - mmengine - INFO - Epoch(train) [110][ 200/2569] lr: 4.0000e-03 eta: 7:46:04 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 3.8067 loss: 2.1248 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1248 2023/06/05 13:17:41 - mmengine - INFO - Epoch(train) [110][ 220/2569] lr: 4.0000e-03 eta: 7:45:58 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 3.9576 loss: 1.5606 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5606 2023/06/05 13:17:47 - mmengine - INFO - Epoch(train) [110][ 240/2569] lr: 4.0000e-03 eta: 7:45:53 time: 0.2796 data_time: 0.0071 memory: 5828 grad_norm: 3.8998 loss: 1.7455 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7455 2023/06/05 13:17:52 - mmengine - INFO - Epoch(train) [110][ 260/2569] lr: 4.0000e-03 eta: 7:45:48 time: 0.2671 data_time: 0.0070 memory: 5828 grad_norm: 3.9069 loss: 1.6887 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6887 2023/06/05 13:17:57 - mmengine - INFO - Epoch(train) [110][ 280/2569] lr: 4.0000e-03 eta: 7:45:42 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 3.9479 loss: 1.8643 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8643 2023/06/05 13:18:03 - mmengine - INFO - Epoch(train) [110][ 300/2569] lr: 4.0000e-03 eta: 7:45:37 time: 0.2700 data_time: 0.0070 memory: 5828 grad_norm: 3.9338 loss: 1.7209 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7209 2023/06/05 13:18:08 - mmengine - INFO - Epoch(train) [110][ 320/2569] lr: 4.0000e-03 eta: 7:45:32 time: 0.2618 data_time: 0.0071 memory: 5828 grad_norm: 3.7957 loss: 1.6704 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6704 2023/06/05 13:18:13 - mmengine - INFO - Epoch(train) [110][ 340/2569] lr: 4.0000e-03 eta: 7:45:27 time: 0.2758 data_time: 0.0072 memory: 5828 grad_norm: 3.8085 loss: 1.9533 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9533 2023/06/05 13:18:19 - mmengine - INFO - Epoch(train) [110][ 360/2569] lr: 4.0000e-03 eta: 7:45:21 time: 0.2744 data_time: 0.0071 memory: 5828 grad_norm: 3.8519 loss: 1.7506 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7506 2023/06/05 13:18:24 - mmengine - INFO - Epoch(train) [110][ 380/2569] lr: 4.0000e-03 eta: 7:45:16 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 3.9221 loss: 2.1852 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1852 2023/06/05 13:18:30 - mmengine - INFO - Epoch(train) [110][ 400/2569] lr: 4.0000e-03 eta: 7:45:11 time: 0.2740 data_time: 0.0072 memory: 5828 grad_norm: 3.9207 loss: 1.7061 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7061 2023/06/05 13:18:35 - mmengine - INFO - Epoch(train) [110][ 420/2569] lr: 4.0000e-03 eta: 7:45:05 time: 0.2700 data_time: 0.0070 memory: 5828 grad_norm: 3.8929 loss: 1.8042 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8042 2023/06/05 13:18:41 - mmengine - INFO - Epoch(train) [110][ 440/2569] lr: 4.0000e-03 eta: 7:45:00 time: 0.2684 data_time: 0.0071 memory: 5828 grad_norm: 3.8825 loss: 2.0043 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0043 2023/06/05 13:18:46 - mmengine - INFO - Epoch(train) [110][ 460/2569] lr: 4.0000e-03 eta: 7:44:55 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 3.9210 loss: 1.8008 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8008 2023/06/05 13:18:51 - mmengine - INFO - Epoch(train) [110][ 480/2569] lr: 4.0000e-03 eta: 7:44:50 time: 0.2727 data_time: 0.0071 memory: 5828 grad_norm: 3.8850 loss: 1.7247 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7247 2023/06/05 13:18:57 - mmengine - INFO - Epoch(train) [110][ 500/2569] lr: 4.0000e-03 eta: 7:44:44 time: 0.2662 data_time: 0.0073 memory: 5828 grad_norm: 3.9355 loss: 1.8502 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8502 2023/06/05 13:19:02 - mmengine - INFO - Epoch(train) [110][ 520/2569] lr: 4.0000e-03 eta: 7:44:39 time: 0.2609 data_time: 0.0077 memory: 5828 grad_norm: 3.8871 loss: 1.5689 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5689 2023/06/05 13:19:07 - mmengine - INFO - Epoch(train) [110][ 540/2569] lr: 4.0000e-03 eta: 7:44:34 time: 0.2637 data_time: 0.0070 memory: 5828 grad_norm: 3.8361 loss: 1.7298 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7298 2023/06/05 13:19:12 - mmengine - INFO - Epoch(train) [110][ 560/2569] lr: 4.0000e-03 eta: 7:44:28 time: 0.2611 data_time: 0.0072 memory: 5828 grad_norm: 3.9499 loss: 1.7908 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7908 2023/06/05 13:19:18 - mmengine - INFO - Epoch(train) [110][ 580/2569] lr: 4.0000e-03 eta: 7:44:23 time: 0.2706 data_time: 0.0074 memory: 5828 grad_norm: 3.8427 loss: 1.7308 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7308 2023/06/05 13:19:23 - mmengine - INFO - Epoch(train) [110][ 600/2569] lr: 4.0000e-03 eta: 7:44:18 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 3.8531 loss: 1.6294 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6294 2023/06/05 13:19:29 - mmengine - INFO - Epoch(train) [110][ 620/2569] lr: 4.0000e-03 eta: 7:44:12 time: 0.2722 data_time: 0.0081 memory: 5828 grad_norm: 3.9832 loss: 1.7531 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7531 2023/06/05 13:19:34 - mmengine - INFO - Epoch(train) [110][ 640/2569] lr: 4.0000e-03 eta: 7:44:07 time: 0.2599 data_time: 0.0074 memory: 5828 grad_norm: 3.9439 loss: 2.2993 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2993 2023/06/05 13:19:39 - mmengine - INFO - Epoch(train) [110][ 660/2569] lr: 4.0000e-03 eta: 7:44:02 time: 0.2696 data_time: 0.0071 memory: 5828 grad_norm: 3.9822 loss: 2.1616 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.1616 2023/06/05 13:19:45 - mmengine - INFO - Epoch(train) [110][ 680/2569] lr: 4.0000e-03 eta: 7:43:56 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 3.8978 loss: 1.8155 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8155 2023/06/05 13:19:50 - mmengine - INFO - Epoch(train) [110][ 700/2569] lr: 4.0000e-03 eta: 7:43:51 time: 0.2595 data_time: 0.0070 memory: 5828 grad_norm: 3.8970 loss: 1.8663 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8663 2023/06/05 13:19:55 - mmengine - INFO - Epoch(train) [110][ 720/2569] lr: 4.0000e-03 eta: 7:43:46 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 3.9323 loss: 1.8117 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8117 2023/06/05 13:20:00 - mmengine - INFO - Epoch(train) [110][ 740/2569] lr: 4.0000e-03 eta: 7:43:40 time: 0.2675 data_time: 0.0072 memory: 5828 grad_norm: 3.9515 loss: 1.7037 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7037 2023/06/05 13:20:06 - mmengine - INFO - Epoch(train) [110][ 760/2569] lr: 4.0000e-03 eta: 7:43:35 time: 0.2696 data_time: 0.0071 memory: 5828 grad_norm: 3.8768 loss: 1.9050 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9050 2023/06/05 13:20:11 - mmengine - INFO - Epoch(train) [110][ 780/2569] lr: 4.0000e-03 eta: 7:43:30 time: 0.2658 data_time: 0.0071 memory: 5828 grad_norm: 3.9235 loss: 1.8974 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8974 2023/06/05 13:20:17 - mmengine - INFO - Epoch(train) [110][ 800/2569] lr: 4.0000e-03 eta: 7:43:24 time: 0.2664 data_time: 0.0070 memory: 5828 grad_norm: 3.9884 loss: 1.8574 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8574 2023/06/05 13:20:22 - mmengine - INFO - Epoch(train) [110][ 820/2569] lr: 4.0000e-03 eta: 7:43:19 time: 0.2601 data_time: 0.0074 memory: 5828 grad_norm: 3.9440 loss: 1.6055 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6055 2023/06/05 13:20:27 - mmengine - INFO - Epoch(train) [110][ 840/2569] lr: 4.0000e-03 eta: 7:43:14 time: 0.2743 data_time: 0.0070 memory: 5828 grad_norm: 3.8953 loss: 1.9752 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9752 2023/06/05 13:20:33 - mmengine - INFO - Epoch(train) [110][ 860/2569] lr: 4.0000e-03 eta: 7:43:08 time: 0.2617 data_time: 0.0075 memory: 5828 grad_norm: 3.9023 loss: 1.9233 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9233 2023/06/05 13:20:38 - mmengine - INFO - Epoch(train) [110][ 880/2569] lr: 4.0000e-03 eta: 7:43:03 time: 0.2814 data_time: 0.0070 memory: 5828 grad_norm: 3.8893 loss: 1.8142 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8142 2023/06/05 13:20:43 - mmengine - INFO - Epoch(train) [110][ 900/2569] lr: 4.0000e-03 eta: 7:42:58 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 4.0074 loss: 1.9735 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9735 2023/06/05 13:20:49 - mmengine - INFO - Epoch(train) [110][ 920/2569] lr: 4.0000e-03 eta: 7:42:53 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 3.9816 loss: 2.0341 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0341 2023/06/05 13:20:54 - mmengine - INFO - Epoch(train) [110][ 940/2569] lr: 4.0000e-03 eta: 7:42:47 time: 0.2746 data_time: 0.0068 memory: 5828 grad_norm: 3.9117 loss: 2.1072 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1072 2023/06/05 13:21:00 - mmengine - INFO - Epoch(train) [110][ 960/2569] lr: 4.0000e-03 eta: 7:42:42 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 3.9341 loss: 1.8321 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8321 2023/06/05 13:21:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:21:05 - mmengine - INFO - Epoch(train) [110][ 980/2569] lr: 4.0000e-03 eta: 7:42:37 time: 0.2631 data_time: 0.0069 memory: 5828 grad_norm: 3.8677 loss: 1.7974 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7974 2023/06/05 13:21:10 - mmengine - INFO - Epoch(train) [110][1000/2569] lr: 4.0000e-03 eta: 7:42:31 time: 0.2653 data_time: 0.0071 memory: 5828 grad_norm: 3.8475 loss: 1.7450 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7450 2023/06/05 13:21:15 - mmengine - INFO - Epoch(train) [110][1020/2569] lr: 4.0000e-03 eta: 7:42:26 time: 0.2656 data_time: 0.0072 memory: 5828 grad_norm: 3.9450 loss: 1.9128 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9128 2023/06/05 13:21:21 - mmengine - INFO - Epoch(train) [110][1040/2569] lr: 4.0000e-03 eta: 7:42:21 time: 0.2773 data_time: 0.0072 memory: 5828 grad_norm: 3.8690 loss: 1.8868 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8868 2023/06/05 13:21:26 - mmengine - INFO - Epoch(train) [110][1060/2569] lr: 4.0000e-03 eta: 7:42:15 time: 0.2620 data_time: 0.0070 memory: 5828 grad_norm: 3.9563 loss: 1.7140 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7140 2023/06/05 13:21:32 - mmengine - INFO - Epoch(train) [110][1080/2569] lr: 4.0000e-03 eta: 7:42:10 time: 0.2685 data_time: 0.0069 memory: 5828 grad_norm: 3.8676 loss: 1.4693 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4693 2023/06/05 13:21:37 - mmengine - INFO - Epoch(train) [110][1100/2569] lr: 4.0000e-03 eta: 7:42:05 time: 0.2606 data_time: 0.0079 memory: 5828 grad_norm: 3.9207 loss: 2.1658 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.1658 2023/06/05 13:21:42 - mmengine - INFO - Epoch(train) [110][1120/2569] lr: 4.0000e-03 eta: 7:41:59 time: 0.2653 data_time: 0.0071 memory: 5828 grad_norm: 3.9572 loss: 1.7111 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7111 2023/06/05 13:21:48 - mmengine - INFO - Epoch(train) [110][1140/2569] lr: 4.0000e-03 eta: 7:41:54 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 3.9715 loss: 2.0859 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0859 2023/06/05 13:21:53 - mmengine - INFO - Epoch(train) [110][1160/2569] lr: 4.0000e-03 eta: 7:41:49 time: 0.2715 data_time: 0.0071 memory: 5828 grad_norm: 3.8634 loss: 1.6632 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.6632 2023/06/05 13:21:58 - mmengine - INFO - Epoch(train) [110][1180/2569] lr: 4.0000e-03 eta: 7:41:43 time: 0.2612 data_time: 0.0072 memory: 5828 grad_norm: 3.9526 loss: 2.0969 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0969 2023/06/05 13:22:03 - mmengine - INFO - Epoch(train) [110][1200/2569] lr: 4.0000e-03 eta: 7:41:38 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 3.9484 loss: 2.0634 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0634 2023/06/05 13:22:09 - mmengine - INFO - Epoch(train) [110][1220/2569] lr: 4.0000e-03 eta: 7:41:33 time: 0.2616 data_time: 0.0071 memory: 5828 grad_norm: 3.9497 loss: 1.9298 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9298 2023/06/05 13:22:14 - mmengine - INFO - Epoch(train) [110][1240/2569] lr: 4.0000e-03 eta: 7:41:27 time: 0.2602 data_time: 0.0069 memory: 5828 grad_norm: 3.9885 loss: 1.5560 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5560 2023/06/05 13:22:19 - mmengine - INFO - Epoch(train) [110][1260/2569] lr: 4.0000e-03 eta: 7:41:22 time: 0.2655 data_time: 0.0086 memory: 5828 grad_norm: 3.9833 loss: 1.8999 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8999 2023/06/05 13:22:24 - mmengine - INFO - Epoch(train) [110][1280/2569] lr: 4.0000e-03 eta: 7:41:17 time: 0.2624 data_time: 0.0077 memory: 5828 grad_norm: 3.9848 loss: 1.9898 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9898 2023/06/05 13:22:30 - mmengine - INFO - Epoch(train) [110][1300/2569] lr: 4.0000e-03 eta: 7:41:11 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.9764 loss: 2.0063 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0063 2023/06/05 13:22:35 - mmengine - INFO - Epoch(train) [110][1320/2569] lr: 4.0000e-03 eta: 7:41:06 time: 0.2611 data_time: 0.0071 memory: 5828 grad_norm: 3.9789 loss: 1.9425 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9425 2023/06/05 13:22:40 - mmengine - INFO - Epoch(train) [110][1340/2569] lr: 4.0000e-03 eta: 7:41:01 time: 0.2664 data_time: 0.0071 memory: 5828 grad_norm: 3.9712 loss: 2.0221 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0221 2023/06/05 13:22:46 - mmengine - INFO - Epoch(train) [110][1360/2569] lr: 4.0000e-03 eta: 7:40:55 time: 0.2724 data_time: 0.0073 memory: 5828 grad_norm: 3.8468 loss: 1.8185 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8185 2023/06/05 13:22:51 - mmengine - INFO - Epoch(train) [110][1380/2569] lr: 4.0000e-03 eta: 7:40:50 time: 0.2669 data_time: 0.0070 memory: 5828 grad_norm: 3.9926 loss: 1.6628 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6628 2023/06/05 13:22:56 - mmengine - INFO - Epoch(train) [110][1400/2569] lr: 4.0000e-03 eta: 7:40:45 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 3.9820 loss: 1.9909 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9909 2023/06/05 13:23:02 - mmengine - INFO - Epoch(train) [110][1420/2569] lr: 4.0000e-03 eta: 7:40:39 time: 0.2656 data_time: 0.0068 memory: 5828 grad_norm: 3.9601 loss: 2.1306 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1306 2023/06/05 13:23:07 - mmengine - INFO - Epoch(train) [110][1440/2569] lr: 4.0000e-03 eta: 7:40:34 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 3.8758 loss: 1.8122 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8122 2023/06/05 13:23:12 - mmengine - INFO - Epoch(train) [110][1460/2569] lr: 4.0000e-03 eta: 7:40:29 time: 0.2693 data_time: 0.0071 memory: 5828 grad_norm: 3.8648 loss: 1.8715 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8715 2023/06/05 13:23:18 - mmengine - INFO - Epoch(train) [110][1480/2569] lr: 4.0000e-03 eta: 7:40:23 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.9279 loss: 2.1273 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1273 2023/06/05 13:23:23 - mmengine - INFO - Epoch(train) [110][1500/2569] lr: 4.0000e-03 eta: 7:40:18 time: 0.2616 data_time: 0.0071 memory: 5828 grad_norm: 3.8783 loss: 1.7120 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7120 2023/06/05 13:23:28 - mmengine - INFO - Epoch(train) [110][1520/2569] lr: 4.0000e-03 eta: 7:40:13 time: 0.2656 data_time: 0.0070 memory: 5828 grad_norm: 3.9211 loss: 2.0034 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0034 2023/06/05 13:23:34 - mmengine - INFO - Epoch(train) [110][1540/2569] lr: 4.0000e-03 eta: 7:40:07 time: 0.2668 data_time: 0.0071 memory: 5828 grad_norm: 3.9359 loss: 2.0934 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0934 2023/06/05 13:23:39 - mmengine - INFO - Epoch(train) [110][1560/2569] lr: 4.0000e-03 eta: 7:40:02 time: 0.2614 data_time: 0.0071 memory: 5828 grad_norm: 3.8773 loss: 1.8507 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8507 2023/06/05 13:23:44 - mmengine - INFO - Epoch(train) [110][1580/2569] lr: 4.0000e-03 eta: 7:39:57 time: 0.2655 data_time: 0.0074 memory: 5828 grad_norm: 3.8885 loss: 2.0715 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0715 2023/06/05 13:23:49 - mmengine - INFO - Epoch(train) [110][1600/2569] lr: 4.0000e-03 eta: 7:39:51 time: 0.2616 data_time: 0.0071 memory: 5828 grad_norm: 3.8889 loss: 1.4283 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4283 2023/06/05 13:23:55 - mmengine - INFO - Epoch(train) [110][1620/2569] lr: 4.0000e-03 eta: 7:39:46 time: 0.2639 data_time: 0.0071 memory: 5828 grad_norm: 3.9079 loss: 1.9105 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9105 2023/06/05 13:24:00 - mmengine - INFO - Epoch(train) [110][1640/2569] lr: 4.0000e-03 eta: 7:39:41 time: 0.2684 data_time: 0.0071 memory: 5828 grad_norm: 3.9719 loss: 2.1566 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1566 2023/06/05 13:24:05 - mmengine - INFO - Epoch(train) [110][1660/2569] lr: 4.0000e-03 eta: 7:39:35 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 3.9170 loss: 1.7803 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7803 2023/06/05 13:24:11 - mmengine - INFO - Epoch(train) [110][1680/2569] lr: 4.0000e-03 eta: 7:39:30 time: 0.2705 data_time: 0.0069 memory: 5828 grad_norm: 3.8979 loss: 1.8460 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8460 2023/06/05 13:24:16 - mmengine - INFO - Epoch(train) [110][1700/2569] lr: 4.0000e-03 eta: 7:39:25 time: 0.2699 data_time: 0.0071 memory: 5828 grad_norm: 3.9731 loss: 1.8574 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8574 2023/06/05 13:24:21 - mmengine - INFO - Epoch(train) [110][1720/2569] lr: 4.0000e-03 eta: 7:39:19 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 3.9428 loss: 1.9986 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9986 2023/06/05 13:24:27 - mmengine - INFO - Epoch(train) [110][1740/2569] lr: 4.0000e-03 eta: 7:39:14 time: 0.2698 data_time: 0.0068 memory: 5828 grad_norm: 4.0194 loss: 1.6772 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6772 2023/06/05 13:24:32 - mmengine - INFO - Epoch(train) [110][1760/2569] lr: 4.0000e-03 eta: 7:39:09 time: 0.2658 data_time: 0.0073 memory: 5828 grad_norm: 3.9719 loss: 1.9317 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9317 2023/06/05 13:24:37 - mmengine - INFO - Epoch(train) [110][1780/2569] lr: 4.0000e-03 eta: 7:39:04 time: 0.2653 data_time: 0.0070 memory: 5828 grad_norm: 3.9160 loss: 1.9683 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9683 2023/06/05 13:24:43 - mmengine - INFO - Epoch(train) [110][1800/2569] lr: 4.0000e-03 eta: 7:38:58 time: 0.2715 data_time: 0.0071 memory: 5828 grad_norm: 3.8805 loss: 1.9519 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9519 2023/06/05 13:24:48 - mmengine - INFO - Epoch(train) [110][1820/2569] lr: 4.0000e-03 eta: 7:38:53 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 3.9454 loss: 1.9539 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.9539 2023/06/05 13:24:53 - mmengine - INFO - Epoch(train) [110][1840/2569] lr: 4.0000e-03 eta: 7:38:48 time: 0.2661 data_time: 0.0070 memory: 5828 grad_norm: 4.0385 loss: 1.9523 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9523 2023/06/05 13:24:59 - mmengine - INFO - Epoch(train) [110][1860/2569] lr: 4.0000e-03 eta: 7:38:42 time: 0.2591 data_time: 0.0073 memory: 5828 grad_norm: 4.0015 loss: 1.8523 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8523 2023/06/05 13:25:04 - mmengine - INFO - Epoch(train) [110][1880/2569] lr: 4.0000e-03 eta: 7:38:37 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 3.9873 loss: 1.7799 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7799 2023/06/05 13:25:09 - mmengine - INFO - Epoch(train) [110][1900/2569] lr: 4.0000e-03 eta: 7:38:32 time: 0.2646 data_time: 0.0071 memory: 5828 grad_norm: 3.9010 loss: 1.8684 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8684 2023/06/05 13:25:15 - mmengine - INFO - Epoch(train) [110][1920/2569] lr: 4.0000e-03 eta: 7:38:26 time: 0.2642 data_time: 0.0070 memory: 5828 grad_norm: 3.9699 loss: 2.1078 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 2.1078 2023/06/05 13:25:20 - mmengine - INFO - Epoch(train) [110][1940/2569] lr: 4.0000e-03 eta: 7:38:21 time: 0.2664 data_time: 0.0071 memory: 5828 grad_norm: 3.9652 loss: 2.1518 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1518 2023/06/05 13:25:25 - mmengine - INFO - Epoch(train) [110][1960/2569] lr: 4.0000e-03 eta: 7:38:16 time: 0.2771 data_time: 0.0071 memory: 5828 grad_norm: 3.9917 loss: 1.7604 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7604 2023/06/05 13:25:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:25:31 - mmengine - INFO - Epoch(train) [110][1980/2569] lr: 4.0000e-03 eta: 7:38:10 time: 0.2654 data_time: 0.0073 memory: 5828 grad_norm: 3.9550 loss: 1.8947 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8947 2023/06/05 13:25:36 - mmengine - INFO - Epoch(train) [110][2000/2569] lr: 4.0000e-03 eta: 7:38:05 time: 0.2764 data_time: 0.0069 memory: 5828 grad_norm: 3.9408 loss: 1.9289 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9289 2023/06/05 13:25:42 - mmengine - INFO - Epoch(train) [110][2020/2569] lr: 4.0000e-03 eta: 7:38:00 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.9344 loss: 1.7808 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7808 2023/06/05 13:25:47 - mmengine - INFO - Epoch(train) [110][2040/2569] lr: 4.0000e-03 eta: 7:37:55 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 3.9010 loss: 1.9941 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9941 2023/06/05 13:25:52 - mmengine - INFO - Epoch(train) [110][2060/2569] lr: 4.0000e-03 eta: 7:37:49 time: 0.2618 data_time: 0.0069 memory: 5828 grad_norm: 3.9896 loss: 1.9735 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9735 2023/06/05 13:25:58 - mmengine - INFO - Epoch(train) [110][2080/2569] lr: 4.0000e-03 eta: 7:37:44 time: 0.2772 data_time: 0.0073 memory: 5828 grad_norm: 3.9810 loss: 2.0069 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0069 2023/06/05 13:26:03 - mmengine - INFO - Epoch(train) [110][2100/2569] lr: 4.0000e-03 eta: 7:37:39 time: 0.2633 data_time: 0.0066 memory: 5828 grad_norm: 3.9256 loss: 1.8359 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8359 2023/06/05 13:26:08 - mmengine - INFO - Epoch(train) [110][2120/2569] lr: 4.0000e-03 eta: 7:37:33 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.9543 loss: 1.8876 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8876 2023/06/05 13:26:14 - mmengine - INFO - Epoch(train) [110][2140/2569] lr: 4.0000e-03 eta: 7:37:28 time: 0.2661 data_time: 0.0072 memory: 5828 grad_norm: 3.9619 loss: 1.8084 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8084 2023/06/05 13:26:19 - mmengine - INFO - Epoch(train) [110][2160/2569] lr: 4.0000e-03 eta: 7:37:23 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 4.0169 loss: 2.1389 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1389 2023/06/05 13:26:24 - mmengine - INFO - Epoch(train) [110][2180/2569] lr: 4.0000e-03 eta: 7:37:17 time: 0.2709 data_time: 0.0072 memory: 5828 grad_norm: 4.0242 loss: 1.9374 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9374 2023/06/05 13:26:30 - mmengine - INFO - Epoch(train) [110][2200/2569] lr: 4.0000e-03 eta: 7:37:12 time: 0.2679 data_time: 0.0070 memory: 5828 grad_norm: 3.9912 loss: 1.8027 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8027 2023/06/05 13:26:35 - mmengine - INFO - Epoch(train) [110][2220/2569] lr: 4.0000e-03 eta: 7:37:07 time: 0.2663 data_time: 0.0071 memory: 5828 grad_norm: 3.8772 loss: 1.9031 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9031 2023/06/05 13:26:40 - mmengine - INFO - Epoch(train) [110][2240/2569] lr: 4.0000e-03 eta: 7:37:01 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 4.0451 loss: 1.7836 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7836 2023/06/05 13:26:46 - mmengine - INFO - Epoch(train) [110][2260/2569] lr: 4.0000e-03 eta: 7:36:56 time: 0.2608 data_time: 0.0067 memory: 5828 grad_norm: 3.9985 loss: 1.9723 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9723 2023/06/05 13:26:51 - mmengine - INFO - Epoch(train) [110][2280/2569] lr: 4.0000e-03 eta: 7:36:51 time: 0.2601 data_time: 0.0069 memory: 5828 grad_norm: 3.9857 loss: 1.8735 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8735 2023/06/05 13:26:56 - mmengine - INFO - Epoch(train) [110][2300/2569] lr: 4.0000e-03 eta: 7:36:45 time: 0.2605 data_time: 0.0073 memory: 5828 grad_norm: 4.0845 loss: 1.6924 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6924 2023/06/05 13:27:01 - mmengine - INFO - Epoch(train) [110][2320/2569] lr: 4.0000e-03 eta: 7:36:40 time: 0.2634 data_time: 0.0071 memory: 5828 grad_norm: 4.0350 loss: 1.7189 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7189 2023/06/05 13:27:07 - mmengine - INFO - Epoch(train) [110][2340/2569] lr: 4.0000e-03 eta: 7:36:35 time: 0.2657 data_time: 0.0071 memory: 5828 grad_norm: 3.9978 loss: 1.8357 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8357 2023/06/05 13:27:12 - mmengine - INFO - Epoch(train) [110][2360/2569] lr: 4.0000e-03 eta: 7:36:29 time: 0.2636 data_time: 0.0071 memory: 5828 grad_norm: 3.9952 loss: 1.8248 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8248 2023/06/05 13:27:17 - mmengine - INFO - Epoch(train) [110][2380/2569] lr: 4.0000e-03 eta: 7:36:24 time: 0.2726 data_time: 0.0071 memory: 5828 grad_norm: 4.0242 loss: 1.8458 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8458 2023/06/05 13:27:23 - mmengine - INFO - Epoch(train) [110][2400/2569] lr: 4.0000e-03 eta: 7:36:19 time: 0.2696 data_time: 0.0070 memory: 5828 grad_norm: 3.9872 loss: 2.0728 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0728 2023/06/05 13:27:28 - mmengine - INFO - Epoch(train) [110][2420/2569] lr: 4.0000e-03 eta: 7:36:13 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 3.9428 loss: 1.8539 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8539 2023/06/05 13:27:33 - mmengine - INFO - Epoch(train) [110][2440/2569] lr: 4.0000e-03 eta: 7:36:08 time: 0.2664 data_time: 0.0070 memory: 5828 grad_norm: 4.0496 loss: 1.7491 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7491 2023/06/05 13:27:39 - mmengine - INFO - Epoch(train) [110][2460/2569] lr: 4.0000e-03 eta: 7:36:03 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 3.8923 loss: 1.7256 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7256 2023/06/05 13:27:44 - mmengine - INFO - Epoch(train) [110][2480/2569] lr: 4.0000e-03 eta: 7:35:57 time: 0.2675 data_time: 0.0070 memory: 5828 grad_norm: 4.0137 loss: 1.7732 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7732 2023/06/05 13:27:49 - mmengine - INFO - Epoch(train) [110][2500/2569] lr: 4.0000e-03 eta: 7:35:52 time: 0.2720 data_time: 0.0071 memory: 5828 grad_norm: 3.9115 loss: 2.0085 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0085 2023/06/05 13:27:55 - mmengine - INFO - Epoch(train) [110][2520/2569] lr: 4.0000e-03 eta: 7:35:47 time: 0.2615 data_time: 0.0071 memory: 5828 grad_norm: 3.9715 loss: 2.0652 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0652 2023/06/05 13:28:00 - mmengine - INFO - Epoch(train) [110][2540/2569] lr: 4.0000e-03 eta: 7:35:41 time: 0.2711 data_time: 0.0072 memory: 5828 grad_norm: 3.9081 loss: 1.8208 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8208 2023/06/05 13:28:05 - mmengine - INFO - Epoch(train) [110][2560/2569] lr: 4.0000e-03 eta: 7:35:36 time: 0.2576 data_time: 0.0073 memory: 5828 grad_norm: 3.9236 loss: 1.7287 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 1.7287 2023/06/05 13:28:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:28:08 - mmengine - INFO - Epoch(train) [110][2569/2569] lr: 4.0000e-03 eta: 7:35:34 time: 0.2515 data_time: 0.0069 memory: 5828 grad_norm: 3.9442 loss: 2.0628 top1_acc: 0.3333 top5_acc: 0.5000 loss_cls: 2.0628 2023/06/05 13:28:11 - mmengine - INFO - Epoch(val) [110][ 20/260] eta: 0:00:44 time: 0.1871 data_time: 0.1280 memory: 1238 2023/06/05 13:28:14 - mmengine - INFO - Epoch(val) [110][ 40/260] eta: 0:00:36 time: 0.1453 data_time: 0.0868 memory: 1238 2023/06/05 13:28:17 - mmengine - INFO - Epoch(val) [110][ 60/260] eta: 0:00:32 time: 0.1541 data_time: 0.0945 memory: 1238 2023/06/05 13:28:20 - mmengine - INFO - Epoch(val) [110][ 80/260] eta: 0:00:26 time: 0.1117 data_time: 0.0526 memory: 1238 2023/06/05 13:28:23 - mmengine - INFO - Epoch(val) [110][100/260] eta: 0:00:24 time: 0.1608 data_time: 0.1019 memory: 1238 2023/06/05 13:28:25 - mmengine - INFO - Epoch(val) [110][120/260] eta: 0:00:20 time: 0.1103 data_time: 0.0516 memory: 1238 2023/06/05 13:28:28 - mmengine - INFO - Epoch(val) [110][140/260] eta: 0:00:17 time: 0.1538 data_time: 0.0951 memory: 1238 2023/06/05 13:28:30 - mmengine - INFO - Epoch(val) [110][160/260] eta: 0:00:14 time: 0.1222 data_time: 0.0638 memory: 1238 2023/06/05 13:28:34 - mmengine - INFO - Epoch(val) [110][180/260] eta: 0:00:11 time: 0.1644 data_time: 0.1057 memory: 1238 2023/06/05 13:28:37 - mmengine - INFO - Epoch(val) [110][200/260] eta: 0:00:08 time: 0.1413 data_time: 0.0820 memory: 1238 2023/06/05 13:28:40 - mmengine - INFO - Epoch(val) [110][220/260] eta: 0:00:05 time: 0.1521 data_time: 0.0938 memory: 1238 2023/06/05 13:28:42 - mmengine - INFO - Epoch(val) [110][240/260] eta: 0:00:02 time: 0.1364 data_time: 0.0779 memory: 1238 2023/06/05 13:28:45 - mmengine - INFO - Epoch(val) [110][260/260] eta: 0:00:00 time: 0.1290 data_time: 0.0729 memory: 1238 2023/06/05 13:28:52 - mmengine - INFO - Epoch(val) [110][260/260] acc/top1: 0.6125 acc/top5: 0.8275 acc/mean1: 0.6051 data_time: 0.0848 time: 0.1434 2023/06/05 13:28:52 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_105.pth is removed 2023/06/05 13:28:53 - mmengine - INFO - The best checkpoint with 0.6125 acc/top1 at 110 epoch is saved to best_acc_top1_epoch_110.pth. 2023/06/05 13:28:59 - mmengine - INFO - Epoch(train) [111][ 20/2569] lr: 4.0000e-03 eta: 7:35:29 time: 0.2956 data_time: 0.0431 memory: 5828 grad_norm: 3.9529 loss: 2.0784 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0784 2023/06/05 13:29:04 - mmengine - INFO - Epoch(train) [111][ 40/2569] lr: 4.0000e-03 eta: 7:35:23 time: 0.2591 data_time: 0.0073 memory: 5828 grad_norm: 3.9611 loss: 1.5276 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5276 2023/06/05 13:29:10 - mmengine - INFO - Epoch(train) [111][ 60/2569] lr: 4.0000e-03 eta: 7:35:18 time: 0.2696 data_time: 0.0067 memory: 5828 grad_norm: 3.9717 loss: 1.4542 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4542 2023/06/05 13:29:15 - mmengine - INFO - Epoch(train) [111][ 80/2569] lr: 4.0000e-03 eta: 7:35:13 time: 0.2707 data_time: 0.0073 memory: 5828 grad_norm: 4.0394 loss: 1.6664 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6664 2023/06/05 13:29:20 - mmengine - INFO - Epoch(train) [111][ 100/2569] lr: 4.0000e-03 eta: 7:35:07 time: 0.2623 data_time: 0.0069 memory: 5828 grad_norm: 3.9096 loss: 1.8777 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8777 2023/06/05 13:29:26 - mmengine - INFO - Epoch(train) [111][ 120/2569] lr: 4.0000e-03 eta: 7:35:02 time: 0.2705 data_time: 0.0070 memory: 5828 grad_norm: 4.0280 loss: 1.9434 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9434 2023/06/05 13:29:31 - mmengine - INFO - Epoch(train) [111][ 140/2569] lr: 4.0000e-03 eta: 7:34:57 time: 0.2625 data_time: 0.0070 memory: 5828 grad_norm: 4.0701 loss: 1.6968 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6968 2023/06/05 13:29:37 - mmengine - INFO - Epoch(train) [111][ 160/2569] lr: 4.0000e-03 eta: 7:34:51 time: 0.2713 data_time: 0.0069 memory: 5828 grad_norm: 4.0128 loss: 1.7880 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7880 2023/06/05 13:29:42 - mmengine - INFO - Epoch(train) [111][ 180/2569] lr: 4.0000e-03 eta: 7:34:46 time: 0.2724 data_time: 0.0072 memory: 5828 grad_norm: 3.9959 loss: 1.9421 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9421 2023/06/05 13:29:47 - mmengine - INFO - Epoch(train) [111][ 200/2569] lr: 4.0000e-03 eta: 7:34:41 time: 0.2709 data_time: 0.0072 memory: 5828 grad_norm: 3.9730 loss: 1.7499 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7499 2023/06/05 13:29:53 - mmengine - INFO - Epoch(train) [111][ 220/2569] lr: 4.0000e-03 eta: 7:34:35 time: 0.2685 data_time: 0.0069 memory: 5828 grad_norm: 3.8442 loss: 1.8255 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8255 2023/06/05 13:29:58 - mmengine - INFO - Epoch(train) [111][ 240/2569] lr: 4.0000e-03 eta: 7:34:30 time: 0.2640 data_time: 0.0071 memory: 5828 grad_norm: 3.9604 loss: 1.9718 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9718 2023/06/05 13:30:03 - mmengine - INFO - Epoch(train) [111][ 260/2569] lr: 4.0000e-03 eta: 7:34:25 time: 0.2678 data_time: 0.0071 memory: 5828 grad_norm: 3.9187 loss: 2.0732 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0732 2023/06/05 13:30:09 - mmengine - INFO - Epoch(train) [111][ 280/2569] lr: 4.0000e-03 eta: 7:34:19 time: 0.2637 data_time: 0.0072 memory: 5828 grad_norm: 3.9389 loss: 1.9427 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9427 2023/06/05 13:30:14 - mmengine - INFO - Epoch(train) [111][ 300/2569] lr: 4.0000e-03 eta: 7:34:14 time: 0.2628 data_time: 0.0069 memory: 5828 grad_norm: 3.9982 loss: 2.0962 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0962 2023/06/05 13:30:19 - mmengine - INFO - Epoch(train) [111][ 320/2569] lr: 4.0000e-03 eta: 7:34:09 time: 0.2686 data_time: 0.0070 memory: 5828 grad_norm: 3.9623 loss: 1.8768 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8768 2023/06/05 13:30:25 - mmengine - INFO - Epoch(train) [111][ 340/2569] lr: 4.0000e-03 eta: 7:34:04 time: 0.2672 data_time: 0.0070 memory: 5828 grad_norm: 3.9343 loss: 1.8108 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8108 2023/06/05 13:30:30 - mmengine - INFO - Epoch(train) [111][ 360/2569] lr: 4.0000e-03 eta: 7:33:58 time: 0.2626 data_time: 0.0071 memory: 5828 grad_norm: 3.9364 loss: 1.6517 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6517 2023/06/05 13:30:35 - mmengine - INFO - Epoch(train) [111][ 380/2569] lr: 4.0000e-03 eta: 7:33:53 time: 0.2635 data_time: 0.0071 memory: 5828 grad_norm: 3.9282 loss: 1.7147 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7147 2023/06/05 13:30:41 - mmengine - INFO - Epoch(train) [111][ 400/2569] lr: 4.0000e-03 eta: 7:33:48 time: 0.2671 data_time: 0.0083 memory: 5828 grad_norm: 3.9134 loss: 2.1246 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1246 2023/06/05 13:30:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:30:46 - mmengine - INFO - Epoch(train) [111][ 420/2569] lr: 4.0000e-03 eta: 7:33:42 time: 0.2598 data_time: 0.0070 memory: 5828 grad_norm: 3.9437 loss: 1.7261 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7261 2023/06/05 13:30:51 - mmengine - INFO - Epoch(train) [111][ 440/2569] lr: 4.0000e-03 eta: 7:33:37 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 3.9928 loss: 1.8306 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8306 2023/06/05 13:30:57 - mmengine - INFO - Epoch(train) [111][ 460/2569] lr: 4.0000e-03 eta: 7:33:32 time: 0.2678 data_time: 0.0076 memory: 5828 grad_norm: 4.0637 loss: 1.8552 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8552 2023/06/05 13:31:02 - mmengine - INFO - Epoch(train) [111][ 480/2569] lr: 4.0000e-03 eta: 7:33:26 time: 0.2664 data_time: 0.0069 memory: 5828 grad_norm: 4.0456 loss: 1.8486 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8486 2023/06/05 13:31:07 - mmengine - INFO - Epoch(train) [111][ 500/2569] lr: 4.0000e-03 eta: 7:33:21 time: 0.2693 data_time: 0.0073 memory: 5828 grad_norm: 3.9893 loss: 1.8386 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8386 2023/06/05 13:31:13 - mmengine - INFO - Epoch(train) [111][ 520/2569] lr: 4.0000e-03 eta: 7:33:16 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 3.9979 loss: 1.8775 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8775 2023/06/05 13:31:18 - mmengine - INFO - Epoch(train) [111][ 540/2569] lr: 4.0000e-03 eta: 7:33:10 time: 0.2620 data_time: 0.0081 memory: 5828 grad_norm: 3.9286 loss: 2.0561 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0561 2023/06/05 13:31:23 - mmengine - INFO - Epoch(train) [111][ 560/2569] lr: 4.0000e-03 eta: 7:33:05 time: 0.2682 data_time: 0.0070 memory: 5828 grad_norm: 3.9532 loss: 1.8469 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8469 2023/06/05 13:31:29 - mmengine - INFO - Epoch(train) [111][ 580/2569] lr: 4.0000e-03 eta: 7:33:00 time: 0.2687 data_time: 0.0070 memory: 5828 grad_norm: 3.9480 loss: 1.9472 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9472 2023/06/05 13:31:34 - mmengine - INFO - Epoch(train) [111][ 600/2569] lr: 4.0000e-03 eta: 7:32:54 time: 0.2714 data_time: 0.0072 memory: 5828 grad_norm: 3.9451 loss: 1.8374 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8374 2023/06/05 13:31:39 - mmengine - INFO - Epoch(train) [111][ 620/2569] lr: 4.0000e-03 eta: 7:32:49 time: 0.2667 data_time: 0.0071 memory: 5828 grad_norm: 3.9290 loss: 1.9316 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9316 2023/06/05 13:31:45 - mmengine - INFO - Epoch(train) [111][ 640/2569] lr: 4.0000e-03 eta: 7:32:44 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 3.9227 loss: 1.6817 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6817 2023/06/05 13:31:50 - mmengine - INFO - Epoch(train) [111][ 660/2569] lr: 4.0000e-03 eta: 7:32:38 time: 0.2654 data_time: 0.0071 memory: 5828 grad_norm: 3.9704 loss: 1.9624 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9624 2023/06/05 13:31:55 - mmengine - INFO - Epoch(train) [111][ 680/2569] lr: 4.0000e-03 eta: 7:32:33 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 4.0372 loss: 2.1392 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1392 2023/06/05 13:32:01 - mmengine - INFO - Epoch(train) [111][ 700/2569] lr: 4.0000e-03 eta: 7:32:28 time: 0.2671 data_time: 0.0070 memory: 5828 grad_norm: 3.9086 loss: 1.3138 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3138 2023/06/05 13:32:06 - mmengine - INFO - Epoch(train) [111][ 720/2569] lr: 4.0000e-03 eta: 7:32:22 time: 0.2679 data_time: 0.0071 memory: 5828 grad_norm: 4.0766 loss: 2.1014 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1014 2023/06/05 13:32:11 - mmengine - INFO - Epoch(train) [111][ 740/2569] lr: 4.0000e-03 eta: 7:32:17 time: 0.2654 data_time: 0.0071 memory: 5828 grad_norm: 3.9490 loss: 2.0703 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0703 2023/06/05 13:32:17 - mmengine - INFO - Epoch(train) [111][ 760/2569] lr: 4.0000e-03 eta: 7:32:12 time: 0.2711 data_time: 0.0071 memory: 5828 grad_norm: 3.9588 loss: 1.6614 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6614 2023/06/05 13:32:22 - mmengine - INFO - Epoch(train) [111][ 780/2569] lr: 4.0000e-03 eta: 7:32:07 time: 0.2650 data_time: 0.0074 memory: 5828 grad_norm: 3.9385 loss: 2.1224 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1224 2023/06/05 13:32:28 - mmengine - INFO - Epoch(train) [111][ 800/2569] lr: 4.0000e-03 eta: 7:32:01 time: 0.2673 data_time: 0.0074 memory: 5828 grad_norm: 3.9696 loss: 1.9399 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9399 2023/06/05 13:32:33 - mmengine - INFO - Epoch(train) [111][ 820/2569] lr: 4.0000e-03 eta: 7:31:56 time: 0.2611 data_time: 0.0070 memory: 5828 grad_norm: 3.9892 loss: 1.8459 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8459 2023/06/05 13:32:38 - mmengine - INFO - Epoch(train) [111][ 840/2569] lr: 4.0000e-03 eta: 7:31:51 time: 0.2665 data_time: 0.0070 memory: 5828 grad_norm: 3.9638 loss: 1.8347 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8347 2023/06/05 13:32:43 - mmengine - INFO - Epoch(train) [111][ 860/2569] lr: 4.0000e-03 eta: 7:31:45 time: 0.2643 data_time: 0.0070 memory: 5828 grad_norm: 4.0042 loss: 1.9187 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9187 2023/06/05 13:32:49 - mmengine - INFO - Epoch(train) [111][ 880/2569] lr: 4.0000e-03 eta: 7:31:40 time: 0.2711 data_time: 0.0072 memory: 5828 grad_norm: 3.9851 loss: 1.5309 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5309 2023/06/05 13:32:54 - mmengine - INFO - Epoch(train) [111][ 900/2569] lr: 4.0000e-03 eta: 7:31:35 time: 0.2607 data_time: 0.0068 memory: 5828 grad_norm: 3.9810 loss: 1.8985 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8985 2023/06/05 13:32:59 - mmengine - INFO - Epoch(train) [111][ 920/2569] lr: 4.0000e-03 eta: 7:31:29 time: 0.2665 data_time: 0.0068 memory: 5828 grad_norm: 4.0303 loss: 1.8085 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.8085 2023/06/05 13:33:05 - mmengine - INFO - Epoch(train) [111][ 940/2569] lr: 4.0000e-03 eta: 7:31:24 time: 0.2742 data_time: 0.0071 memory: 5828 grad_norm: 4.0216 loss: 1.6101 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6101 2023/06/05 13:33:10 - mmengine - INFO - Epoch(train) [111][ 960/2569] lr: 4.0000e-03 eta: 7:31:19 time: 0.2657 data_time: 0.0068 memory: 5828 grad_norm: 3.9385 loss: 2.0010 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0010 2023/06/05 13:33:16 - mmengine - INFO - Epoch(train) [111][ 980/2569] lr: 4.0000e-03 eta: 7:31:13 time: 0.2631 data_time: 0.0071 memory: 5828 grad_norm: 3.9953 loss: 2.0455 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0455 2023/06/05 13:33:21 - mmengine - INFO - Epoch(train) [111][1000/2569] lr: 4.0000e-03 eta: 7:31:08 time: 0.2770 data_time: 0.0070 memory: 5828 grad_norm: 4.0036 loss: 1.8798 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8798 2023/06/05 13:33:26 - mmengine - INFO - Epoch(train) [111][1020/2569] lr: 4.0000e-03 eta: 7:31:03 time: 0.2712 data_time: 0.0071 memory: 5828 grad_norm: 3.9576 loss: 2.0132 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0132 2023/06/05 13:33:32 - mmengine - INFO - Epoch(train) [111][1040/2569] lr: 4.0000e-03 eta: 7:30:58 time: 0.2663 data_time: 0.0070 memory: 5828 grad_norm: 4.0074 loss: 1.8277 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8277 2023/06/05 13:33:37 - mmengine - INFO - Epoch(train) [111][1060/2569] lr: 4.0000e-03 eta: 7:30:52 time: 0.2681 data_time: 0.0070 memory: 5828 grad_norm: 4.0202 loss: 2.0420 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0420 2023/06/05 13:33:43 - mmengine - INFO - Epoch(train) [111][1080/2569] lr: 4.0000e-03 eta: 7:30:47 time: 0.2708 data_time: 0.0070 memory: 5828 grad_norm: 3.9963 loss: 1.9465 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9465 2023/06/05 13:33:48 - mmengine - INFO - Epoch(train) [111][1100/2569] lr: 4.0000e-03 eta: 7:30:42 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 3.9352 loss: 1.8619 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8619 2023/06/05 13:33:53 - mmengine - INFO - Epoch(train) [111][1120/2569] lr: 4.0000e-03 eta: 7:30:36 time: 0.2715 data_time: 0.0075 memory: 5828 grad_norm: 3.9794 loss: 1.8847 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8847 2023/06/05 13:33:59 - mmengine - INFO - Epoch(train) [111][1140/2569] lr: 4.0000e-03 eta: 7:30:31 time: 0.2607 data_time: 0.0072 memory: 5828 grad_norm: 4.0530 loss: 2.1694 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1694 2023/06/05 13:34:04 - mmengine - INFO - Epoch(train) [111][1160/2569] lr: 4.0000e-03 eta: 7:30:26 time: 0.2708 data_time: 0.0075 memory: 5828 grad_norm: 3.9660 loss: 1.8497 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8497 2023/06/05 13:34:09 - mmengine - INFO - Epoch(train) [111][1180/2569] lr: 4.0000e-03 eta: 7:30:20 time: 0.2662 data_time: 0.0073 memory: 5828 grad_norm: 4.0545 loss: 1.8522 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8522 2023/06/05 13:34:15 - mmengine - INFO - Epoch(train) [111][1200/2569] lr: 4.0000e-03 eta: 7:30:15 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 3.9699 loss: 1.7408 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7408 2023/06/05 13:34:20 - mmengine - INFO - Epoch(train) [111][1220/2569] lr: 4.0000e-03 eta: 7:30:10 time: 0.2682 data_time: 0.0071 memory: 5828 grad_norm: 4.0097 loss: 1.9785 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9785 2023/06/05 13:34:25 - mmengine - INFO - Epoch(train) [111][1240/2569] lr: 4.0000e-03 eta: 7:30:04 time: 0.2612 data_time: 0.0071 memory: 5828 grad_norm: 4.0379 loss: 1.7961 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7961 2023/06/05 13:34:31 - mmengine - INFO - Epoch(train) [111][1260/2569] lr: 4.0000e-03 eta: 7:29:59 time: 0.2601 data_time: 0.0070 memory: 5828 grad_norm: 4.0149 loss: 1.7901 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7901 2023/06/05 13:34:36 - mmengine - INFO - Epoch(train) [111][1280/2569] lr: 4.0000e-03 eta: 7:29:54 time: 0.2628 data_time: 0.0070 memory: 5828 grad_norm: 4.0089 loss: 1.6477 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6477 2023/06/05 13:34:41 - mmengine - INFO - Epoch(train) [111][1300/2569] lr: 4.0000e-03 eta: 7:29:48 time: 0.2710 data_time: 0.0070 memory: 5828 grad_norm: 3.9994 loss: 1.6166 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6166 2023/06/05 13:34:47 - mmengine - INFO - Epoch(train) [111][1320/2569] lr: 4.0000e-03 eta: 7:29:43 time: 0.2696 data_time: 0.0086 memory: 5828 grad_norm: 3.9399 loss: 1.5385 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.5385 2023/06/05 13:34:52 - mmengine - INFO - Epoch(train) [111][1340/2569] lr: 4.0000e-03 eta: 7:29:38 time: 0.2696 data_time: 0.0072 memory: 5828 grad_norm: 3.9783 loss: 1.7934 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.7934 2023/06/05 13:34:57 - mmengine - INFO - Epoch(train) [111][1360/2569] lr: 4.0000e-03 eta: 7:29:32 time: 0.2653 data_time: 0.0073 memory: 5828 grad_norm: 4.0553 loss: 1.8464 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8464 2023/06/05 13:35:03 - mmengine - INFO - Epoch(train) [111][1380/2569] lr: 4.0000e-03 eta: 7:29:27 time: 0.2795 data_time: 0.0072 memory: 5828 grad_norm: 4.0558 loss: 1.7971 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7971 2023/06/05 13:35:08 - mmengine - INFO - Epoch(train) [111][1400/2569] lr: 4.0000e-03 eta: 7:29:22 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 3.9158 loss: 1.9724 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9724 2023/06/05 13:35:11 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:35:13 - mmengine - INFO - Epoch(train) [111][1420/2569] lr: 4.0000e-03 eta: 7:29:17 time: 0.2616 data_time: 0.0071 memory: 5828 grad_norm: 4.0695 loss: 1.9058 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9058 2023/06/05 13:35:19 - mmengine - INFO - Epoch(train) [111][1440/2569] lr: 4.0000e-03 eta: 7:29:11 time: 0.2725 data_time: 0.0071 memory: 5828 grad_norm: 4.0617 loss: 1.9806 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9806 2023/06/05 13:35:24 - mmengine - INFO - Epoch(train) [111][1460/2569] lr: 4.0000e-03 eta: 7:29:06 time: 0.2601 data_time: 0.0073 memory: 5828 grad_norm: 3.9895 loss: 1.6367 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6367 2023/06/05 13:35:29 - mmengine - INFO - Epoch(train) [111][1480/2569] lr: 4.0000e-03 eta: 7:29:01 time: 0.2597 data_time: 0.0071 memory: 5828 grad_norm: 4.0380 loss: 1.7364 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7364 2023/06/05 13:35:35 - mmengine - INFO - Epoch(train) [111][1500/2569] lr: 4.0000e-03 eta: 7:28:55 time: 0.2611 data_time: 0.0070 memory: 5828 grad_norm: 4.0238 loss: 1.9852 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9852 2023/06/05 13:35:40 - mmengine - INFO - Epoch(train) [111][1520/2569] lr: 4.0000e-03 eta: 7:28:50 time: 0.2674 data_time: 0.0070 memory: 5828 grad_norm: 4.0013 loss: 1.7836 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7836 2023/06/05 13:35:45 - mmengine - INFO - Epoch(train) [111][1540/2569] lr: 4.0000e-03 eta: 7:28:45 time: 0.2744 data_time: 0.0071 memory: 5828 grad_norm: 4.0328 loss: 1.9559 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9559 2023/06/05 13:35:51 - mmengine - INFO - Epoch(train) [111][1560/2569] lr: 4.0000e-03 eta: 7:28:39 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 4.0760 loss: 1.8116 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8116 2023/06/05 13:35:56 - mmengine - INFO - Epoch(train) [111][1580/2569] lr: 4.0000e-03 eta: 7:28:34 time: 0.2640 data_time: 0.0072 memory: 5828 grad_norm: 4.0737 loss: 1.9898 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9898 2023/06/05 13:36:01 - mmengine - INFO - Epoch(train) [111][1600/2569] lr: 4.0000e-03 eta: 7:28:29 time: 0.2720 data_time: 0.0071 memory: 5828 grad_norm: 3.9501 loss: 1.9214 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9214 2023/06/05 13:36:07 - mmengine - INFO - Epoch(train) [111][1620/2569] lr: 4.0000e-03 eta: 7:28:23 time: 0.2770 data_time: 0.0070 memory: 5828 grad_norm: 3.9324 loss: 1.8562 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8562 2023/06/05 13:36:12 - mmengine - INFO - Epoch(train) [111][1640/2569] lr: 4.0000e-03 eta: 7:28:18 time: 0.2685 data_time: 0.0070 memory: 5828 grad_norm: 4.0339 loss: 1.8878 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8878 2023/06/05 13:36:18 - mmengine - INFO - Epoch(train) [111][1660/2569] lr: 4.0000e-03 eta: 7:28:13 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 4.0039 loss: 1.5945 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5945 2023/06/05 13:36:23 - mmengine - INFO - Epoch(train) [111][1680/2569] lr: 4.0000e-03 eta: 7:28:08 time: 0.2754 data_time: 0.0074 memory: 5828 grad_norm: 4.1095 loss: 1.8928 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8928 2023/06/05 13:36:29 - mmengine - INFO - Epoch(train) [111][1700/2569] lr: 4.0000e-03 eta: 7:28:02 time: 0.2729 data_time: 0.0070 memory: 5828 grad_norm: 4.0323 loss: 1.7021 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7021 2023/06/05 13:36:34 - mmengine - INFO - Epoch(train) [111][1720/2569] lr: 4.0000e-03 eta: 7:27:57 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 4.0124 loss: 1.8534 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8534 2023/06/05 13:36:39 - mmengine - INFO - Epoch(train) [111][1740/2569] lr: 4.0000e-03 eta: 7:27:52 time: 0.2655 data_time: 0.0069 memory: 5828 grad_norm: 4.0280 loss: 1.6754 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6754 2023/06/05 13:36:45 - mmengine - INFO - Epoch(train) [111][1760/2569] lr: 4.0000e-03 eta: 7:27:46 time: 0.2619 data_time: 0.0071 memory: 5828 grad_norm: 4.0150 loss: 1.3717 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3717 2023/06/05 13:36:50 - mmengine - INFO - Epoch(train) [111][1780/2569] lr: 4.0000e-03 eta: 7:27:41 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 4.0616 loss: 2.0153 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0153 2023/06/05 13:36:55 - mmengine - INFO - Epoch(train) [111][1800/2569] lr: 4.0000e-03 eta: 7:27:36 time: 0.2649 data_time: 0.0078 memory: 5828 grad_norm: 3.9752 loss: 1.7448 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7448 2023/06/05 13:37:01 - mmengine - INFO - Epoch(train) [111][1820/2569] lr: 4.0000e-03 eta: 7:27:30 time: 0.2674 data_time: 0.0070 memory: 5828 grad_norm: 4.0096 loss: 1.7706 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7706 2023/06/05 13:37:06 - mmengine - INFO - Epoch(train) [111][1840/2569] lr: 4.0000e-03 eta: 7:27:25 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 4.0440 loss: 1.7935 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7935 2023/06/05 13:37:11 - mmengine - INFO - Epoch(train) [111][1860/2569] lr: 4.0000e-03 eta: 7:27:20 time: 0.2622 data_time: 0.0070 memory: 5828 grad_norm: 3.9261 loss: 1.8455 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8455 2023/06/05 13:37:17 - mmengine - INFO - Epoch(train) [111][1880/2569] lr: 4.0000e-03 eta: 7:27:14 time: 0.2750 data_time: 0.0072 memory: 5828 grad_norm: 3.9638 loss: 1.8170 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8170 2023/06/05 13:37:22 - mmengine - INFO - Epoch(train) [111][1900/2569] lr: 4.0000e-03 eta: 7:27:09 time: 0.2735 data_time: 0.0071 memory: 5828 grad_norm: 3.9375 loss: 1.9843 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.9843 2023/06/05 13:37:27 - mmengine - INFO - Epoch(train) [111][1920/2569] lr: 4.0000e-03 eta: 7:27:04 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 3.9399 loss: 1.8143 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8143 2023/06/05 13:37:33 - mmengine - INFO - Epoch(train) [111][1940/2569] lr: 4.0000e-03 eta: 7:26:58 time: 0.2631 data_time: 0.0072 memory: 5828 grad_norm: 4.0951 loss: 1.9002 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9002 2023/06/05 13:37:38 - mmengine - INFO - Epoch(train) [111][1960/2569] lr: 4.0000e-03 eta: 7:26:53 time: 0.2710 data_time: 0.0082 memory: 5828 grad_norm: 4.0168 loss: 2.0226 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0226 2023/06/05 13:37:43 - mmengine - INFO - Epoch(train) [111][1980/2569] lr: 4.0000e-03 eta: 7:26:48 time: 0.2604 data_time: 0.0077 memory: 5828 grad_norm: 4.0342 loss: 1.6173 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6173 2023/06/05 13:37:49 - mmengine - INFO - Epoch(train) [111][2000/2569] lr: 4.0000e-03 eta: 7:26:42 time: 0.2609 data_time: 0.0068 memory: 5828 grad_norm: 4.0476 loss: 1.8998 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8998 2023/06/05 13:37:54 - mmengine - INFO - Epoch(train) [111][2020/2569] lr: 4.0000e-03 eta: 7:26:37 time: 0.2614 data_time: 0.0070 memory: 5828 grad_norm: 3.9120 loss: 1.8057 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8057 2023/06/05 13:37:59 - mmengine - INFO - Epoch(train) [111][2040/2569] lr: 4.0000e-03 eta: 7:26:32 time: 0.2667 data_time: 0.0070 memory: 5828 grad_norm: 3.9829 loss: 1.7764 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7764 2023/06/05 13:38:05 - mmengine - INFO - Epoch(train) [111][2060/2569] lr: 4.0000e-03 eta: 7:26:26 time: 0.2673 data_time: 0.0072 memory: 5828 grad_norm: 4.0611 loss: 1.8613 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8613 2023/06/05 13:38:10 - mmengine - INFO - Epoch(train) [111][2080/2569] lr: 4.0000e-03 eta: 7:26:21 time: 0.2752 data_time: 0.0071 memory: 5828 grad_norm: 4.0730 loss: 1.9934 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9934 2023/06/05 13:38:15 - mmengine - INFO - Epoch(train) [111][2100/2569] lr: 4.0000e-03 eta: 7:26:16 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 4.0296 loss: 1.8360 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8360 2023/06/05 13:38:21 - mmengine - INFO - Epoch(train) [111][2120/2569] lr: 4.0000e-03 eta: 7:26:11 time: 0.2725 data_time: 0.0071 memory: 5828 grad_norm: 4.0195 loss: 1.7284 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7284 2023/06/05 13:38:26 - mmengine - INFO - Epoch(train) [111][2140/2569] lr: 4.0000e-03 eta: 7:26:05 time: 0.2607 data_time: 0.0072 memory: 5828 grad_norm: 3.9962 loss: 2.0782 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0782 2023/06/05 13:38:31 - mmengine - INFO - Epoch(train) [111][2160/2569] lr: 4.0000e-03 eta: 7:26:00 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 3.9983 loss: 1.7597 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7597 2023/06/05 13:38:37 - mmengine - INFO - Epoch(train) [111][2180/2569] lr: 4.0000e-03 eta: 7:25:55 time: 0.2708 data_time: 0.0077 memory: 5828 grad_norm: 3.9742 loss: 1.8356 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8356 2023/06/05 13:38:42 - mmengine - INFO - Epoch(train) [111][2200/2569] lr: 4.0000e-03 eta: 7:25:49 time: 0.2624 data_time: 0.0070 memory: 5828 grad_norm: 4.0510 loss: 1.9058 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9058 2023/06/05 13:38:47 - mmengine - INFO - Epoch(train) [111][2220/2569] lr: 4.0000e-03 eta: 7:25:44 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 4.0515 loss: 1.7478 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7478 2023/06/05 13:38:53 - mmengine - INFO - Epoch(train) [111][2240/2569] lr: 4.0000e-03 eta: 7:25:39 time: 0.2646 data_time: 0.0076 memory: 5828 grad_norm: 4.0393 loss: 2.0694 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0694 2023/06/05 13:38:58 - mmengine - INFO - Epoch(train) [111][2260/2569] lr: 4.0000e-03 eta: 7:25:33 time: 0.2681 data_time: 0.0079 memory: 5828 grad_norm: 4.0753 loss: 1.9404 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9404 2023/06/05 13:39:04 - mmengine - INFO - Epoch(train) [111][2280/2569] lr: 4.0000e-03 eta: 7:25:28 time: 0.2677 data_time: 0.0070 memory: 5828 grad_norm: 3.9088 loss: 1.6217 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6217 2023/06/05 13:39:09 - mmengine - INFO - Epoch(train) [111][2300/2569] lr: 4.0000e-03 eta: 7:25:23 time: 0.2713 data_time: 0.0071 memory: 5828 grad_norm: 3.9426 loss: 1.7249 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7249 2023/06/05 13:39:14 - mmengine - INFO - Epoch(train) [111][2320/2569] lr: 4.0000e-03 eta: 7:25:18 time: 0.2741 data_time: 0.0072 memory: 5828 grad_norm: 4.0381 loss: 1.5194 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5194 2023/06/05 13:39:20 - mmengine - INFO - Epoch(train) [111][2340/2569] lr: 4.0000e-03 eta: 7:25:12 time: 0.2716 data_time: 0.0072 memory: 5828 grad_norm: 4.0596 loss: 1.9546 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9546 2023/06/05 13:39:25 - mmengine - INFO - Epoch(train) [111][2360/2569] lr: 4.0000e-03 eta: 7:25:07 time: 0.2633 data_time: 0.0071 memory: 5828 grad_norm: 4.0433 loss: 1.6640 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6640 2023/06/05 13:39:31 - mmengine - INFO - Epoch(train) [111][2380/2569] lr: 4.0000e-03 eta: 7:25:02 time: 0.2761 data_time: 0.0071 memory: 5828 grad_norm: 4.1142 loss: 1.7258 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7258 2023/06/05 13:39:36 - mmengine - INFO - Epoch(train) [111][2400/2569] lr: 4.0000e-03 eta: 7:24:56 time: 0.2729 data_time: 0.0074 memory: 5828 grad_norm: 4.0868 loss: 2.0169 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0169 2023/06/05 13:39:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:39:41 - mmengine - INFO - Epoch(train) [111][2420/2569] lr: 4.0000e-03 eta: 7:24:51 time: 0.2621 data_time: 0.0071 memory: 5828 grad_norm: 4.0763 loss: 1.8083 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8083 2023/06/05 13:39:47 - mmengine - INFO - Epoch(train) [111][2440/2569] lr: 4.0000e-03 eta: 7:24:46 time: 0.2737 data_time: 0.0070 memory: 5828 grad_norm: 4.0019 loss: 1.8919 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8919 2023/06/05 13:39:52 - mmengine - INFO - Epoch(train) [111][2460/2569] lr: 4.0000e-03 eta: 7:24:40 time: 0.2659 data_time: 0.0070 memory: 5828 grad_norm: 4.0201 loss: 2.0342 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.0342 2023/06/05 13:39:58 - mmengine - INFO - Epoch(train) [111][2480/2569] lr: 4.0000e-03 eta: 7:24:35 time: 0.2691 data_time: 0.0070 memory: 5828 grad_norm: 4.0320 loss: 1.6110 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6110 2023/06/05 13:40:03 - mmengine - INFO - Epoch(train) [111][2500/2569] lr: 4.0000e-03 eta: 7:24:30 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 4.0391 loss: 1.6851 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6851 2023/06/05 13:40:08 - mmengine - INFO - Epoch(train) [111][2520/2569] lr: 4.0000e-03 eta: 7:24:25 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 4.0353 loss: 1.9754 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9754 2023/06/05 13:40:14 - mmengine - INFO - Epoch(train) [111][2540/2569] lr: 4.0000e-03 eta: 7:24:19 time: 0.2673 data_time: 0.0070 memory: 5828 grad_norm: 3.9768 loss: 1.9737 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9737 2023/06/05 13:40:19 - mmengine - INFO - Epoch(train) [111][2560/2569] lr: 4.0000e-03 eta: 7:24:14 time: 0.2580 data_time: 0.0075 memory: 5828 grad_norm: 4.0360 loss: 1.9824 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9824 2023/06/05 13:40:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:40:21 - mmengine - INFO - Epoch(train) [111][2569/2569] lr: 4.0000e-03 eta: 7:24:11 time: 0.2569 data_time: 0.0071 memory: 5828 grad_norm: 4.0196 loss: 1.7927 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.7927 2023/06/05 13:40:28 - mmengine - INFO - Epoch(train) [112][ 20/2569] lr: 4.0000e-03 eta: 7:24:07 time: 0.3356 data_time: 0.0727 memory: 5828 grad_norm: 3.9749 loss: 1.9922 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9922 2023/06/05 13:40:33 - mmengine - INFO - Epoch(train) [112][ 40/2569] lr: 4.0000e-03 eta: 7:24:01 time: 0.2740 data_time: 0.0079 memory: 5828 grad_norm: 4.0459 loss: 1.5048 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5048 2023/06/05 13:40:39 - mmengine - INFO - Epoch(train) [112][ 60/2569] lr: 4.0000e-03 eta: 7:23:56 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 4.0591 loss: 1.9555 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.9555 2023/06/05 13:40:44 - mmengine - INFO - Epoch(train) [112][ 80/2569] lr: 4.0000e-03 eta: 7:23:51 time: 0.2748 data_time: 0.0072 memory: 5828 grad_norm: 4.0251 loss: 1.8498 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8498 2023/06/05 13:40:49 - mmengine - INFO - Epoch(train) [112][ 100/2569] lr: 4.0000e-03 eta: 7:23:45 time: 0.2603 data_time: 0.0071 memory: 5828 grad_norm: 4.0266 loss: 1.7687 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7687 2023/06/05 13:40:55 - mmengine - INFO - Epoch(train) [112][ 120/2569] lr: 4.0000e-03 eta: 7:23:40 time: 0.2654 data_time: 0.0073 memory: 5828 grad_norm: 4.0388 loss: 1.6805 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6805 2023/06/05 13:41:00 - mmengine - INFO - Epoch(train) [112][ 140/2569] lr: 4.0000e-03 eta: 7:23:35 time: 0.2603 data_time: 0.0072 memory: 5828 grad_norm: 4.0664 loss: 1.7437 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7437 2023/06/05 13:41:05 - mmengine - INFO - Epoch(train) [112][ 160/2569] lr: 4.0000e-03 eta: 7:23:29 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 3.9321 loss: 1.8987 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8987 2023/06/05 13:41:11 - mmengine - INFO - Epoch(train) [112][ 180/2569] lr: 4.0000e-03 eta: 7:23:24 time: 0.2660 data_time: 0.0074 memory: 5828 grad_norm: 4.0136 loss: 1.8545 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8545 2023/06/05 13:41:16 - mmengine - INFO - Epoch(train) [112][ 200/2569] lr: 4.0000e-03 eta: 7:23:19 time: 0.2773 data_time: 0.0073 memory: 5828 grad_norm: 4.0624 loss: 1.9108 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9108 2023/06/05 13:41:21 - mmengine - INFO - Epoch(train) [112][ 220/2569] lr: 4.0000e-03 eta: 7:23:13 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 4.0612 loss: 1.7145 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7145 2023/06/05 13:41:27 - mmengine - INFO - Epoch(train) [112][ 240/2569] lr: 4.0000e-03 eta: 7:23:08 time: 0.2697 data_time: 0.0076 memory: 5828 grad_norm: 4.0187 loss: 1.7198 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7198 2023/06/05 13:41:32 - mmengine - INFO - Epoch(train) [112][ 260/2569] lr: 4.0000e-03 eta: 7:23:03 time: 0.2722 data_time: 0.0078 memory: 5828 grad_norm: 4.0724 loss: 1.7598 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7598 2023/06/05 13:41:38 - mmengine - INFO - Epoch(train) [112][ 280/2569] lr: 4.0000e-03 eta: 7:22:58 time: 0.2667 data_time: 0.0070 memory: 5828 grad_norm: 4.1142 loss: 1.7232 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7232 2023/06/05 13:41:43 - mmengine - INFO - Epoch(train) [112][ 300/2569] lr: 4.0000e-03 eta: 7:22:52 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 4.0472 loss: 1.7631 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7631 2023/06/05 13:41:48 - mmengine - INFO - Epoch(train) [112][ 320/2569] lr: 4.0000e-03 eta: 7:22:47 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 3.9946 loss: 1.5178 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.5178 2023/06/05 13:41:53 - mmengine - INFO - Epoch(train) [112][ 340/2569] lr: 4.0000e-03 eta: 7:22:42 time: 0.2621 data_time: 0.0077 memory: 5828 grad_norm: 4.1911 loss: 1.8256 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8256 2023/06/05 13:41:59 - mmengine - INFO - Epoch(train) [112][ 360/2569] lr: 4.0000e-03 eta: 7:22:36 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 4.0081 loss: 1.7415 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7415 2023/06/05 13:42:04 - mmengine - INFO - Epoch(train) [112][ 380/2569] lr: 4.0000e-03 eta: 7:22:31 time: 0.2634 data_time: 0.0078 memory: 5828 grad_norm: 4.0356 loss: 1.8767 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8767 2023/06/05 13:42:10 - mmengine - INFO - Epoch(train) [112][ 400/2569] lr: 4.0000e-03 eta: 7:22:26 time: 0.2750 data_time: 0.0081 memory: 5828 grad_norm: 3.9974 loss: 1.6971 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6971 2023/06/05 13:42:15 - mmengine - INFO - Epoch(train) [112][ 420/2569] lr: 4.0000e-03 eta: 7:22:20 time: 0.2690 data_time: 0.0075 memory: 5828 grad_norm: 4.0443 loss: 1.5909 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5909 2023/06/05 13:42:20 - mmengine - INFO - Epoch(train) [112][ 440/2569] lr: 4.0000e-03 eta: 7:22:15 time: 0.2722 data_time: 0.0076 memory: 5828 grad_norm: 4.0953 loss: 1.9358 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9358 2023/06/05 13:42:26 - mmengine - INFO - Epoch(train) [112][ 460/2569] lr: 4.0000e-03 eta: 7:22:10 time: 0.2601 data_time: 0.0086 memory: 5828 grad_norm: 4.0126 loss: 1.7868 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7868 2023/06/05 13:42:31 - mmengine - INFO - Epoch(train) [112][ 480/2569] lr: 4.0000e-03 eta: 7:22:04 time: 0.2736 data_time: 0.0070 memory: 5828 grad_norm: 4.0892 loss: 2.0469 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0469 2023/06/05 13:42:36 - mmengine - INFO - Epoch(train) [112][ 500/2569] lr: 4.0000e-03 eta: 7:21:59 time: 0.2635 data_time: 0.0076 memory: 5828 grad_norm: 4.1404 loss: 1.7131 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7131 2023/06/05 13:42:42 - mmengine - INFO - Epoch(train) [112][ 520/2569] lr: 4.0000e-03 eta: 7:21:54 time: 0.2761 data_time: 0.0073 memory: 5828 grad_norm: 4.0906 loss: 1.9707 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9707 2023/06/05 13:42:47 - mmengine - INFO - Epoch(train) [112][ 540/2569] lr: 4.0000e-03 eta: 7:21:49 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 4.0310 loss: 1.5810 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5810 2023/06/05 13:42:52 - mmengine - INFO - Epoch(train) [112][ 560/2569] lr: 4.0000e-03 eta: 7:21:43 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 4.0416 loss: 2.0192 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0192 2023/06/05 13:42:58 - mmengine - INFO - Epoch(train) [112][ 580/2569] lr: 4.0000e-03 eta: 7:21:38 time: 0.2627 data_time: 0.0070 memory: 5828 grad_norm: 4.0795 loss: 1.5654 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.5654 2023/06/05 13:43:03 - mmengine - INFO - Epoch(train) [112][ 600/2569] lr: 4.0000e-03 eta: 7:21:32 time: 0.2613 data_time: 0.0070 memory: 5828 grad_norm: 4.1190 loss: 1.8671 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8671 2023/06/05 13:43:08 - mmengine - INFO - Epoch(train) [112][ 620/2569] lr: 4.0000e-03 eta: 7:21:27 time: 0.2625 data_time: 0.0070 memory: 5828 grad_norm: 4.0114 loss: 1.8177 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8177 2023/06/05 13:43:13 - mmengine - INFO - Epoch(train) [112][ 640/2569] lr: 4.0000e-03 eta: 7:21:22 time: 0.2636 data_time: 0.0071 memory: 5828 grad_norm: 4.1069 loss: 1.7777 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7777 2023/06/05 13:43:19 - mmengine - INFO - Epoch(train) [112][ 660/2569] lr: 4.0000e-03 eta: 7:21:16 time: 0.2698 data_time: 0.0071 memory: 5828 grad_norm: 4.0838 loss: 1.6750 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6750 2023/06/05 13:43:24 - mmengine - INFO - Epoch(train) [112][ 680/2569] lr: 4.0000e-03 eta: 7:21:11 time: 0.2611 data_time: 0.0071 memory: 5828 grad_norm: 3.9848 loss: 1.9977 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9977 2023/06/05 13:43:29 - mmengine - INFO - Epoch(train) [112][ 700/2569] lr: 4.0000e-03 eta: 7:21:06 time: 0.2669 data_time: 0.0070 memory: 5828 grad_norm: 4.0876 loss: 2.1611 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1611 2023/06/05 13:43:35 - mmengine - INFO - Epoch(train) [112][ 720/2569] lr: 4.0000e-03 eta: 7:21:01 time: 0.2677 data_time: 0.0077 memory: 5828 grad_norm: 4.0699 loss: 1.8256 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8256 2023/06/05 13:43:40 - mmengine - INFO - Epoch(train) [112][ 740/2569] lr: 4.0000e-03 eta: 7:20:55 time: 0.2766 data_time: 0.0068 memory: 5828 grad_norm: 4.0164 loss: 1.9907 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9907 2023/06/05 13:43:46 - mmengine - INFO - Epoch(train) [112][ 760/2569] lr: 4.0000e-03 eta: 7:20:50 time: 0.2657 data_time: 0.0073 memory: 5828 grad_norm: 4.0332 loss: 1.9011 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9011 2023/06/05 13:43:51 - mmengine - INFO - Epoch(train) [112][ 780/2569] lr: 4.0000e-03 eta: 7:20:45 time: 0.2689 data_time: 0.0075 memory: 5828 grad_norm: 4.0957 loss: 2.0602 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0602 2023/06/05 13:43:56 - mmengine - INFO - Epoch(train) [112][ 800/2569] lr: 4.0000e-03 eta: 7:20:39 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 4.1377 loss: 2.0389 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0389 2023/06/05 13:44:02 - mmengine - INFO - Epoch(train) [112][ 820/2569] lr: 4.0000e-03 eta: 7:20:34 time: 0.2618 data_time: 0.0069 memory: 5828 grad_norm: 4.1025 loss: 1.8321 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8321 2023/06/05 13:44:07 - mmengine - INFO - Epoch(train) [112][ 840/2569] lr: 4.0000e-03 eta: 7:20:29 time: 0.2660 data_time: 0.0079 memory: 5828 grad_norm: 4.0571 loss: 1.8029 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8029 2023/06/05 13:44:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:44:12 - mmengine - INFO - Epoch(train) [112][ 860/2569] lr: 4.0000e-03 eta: 7:20:23 time: 0.2685 data_time: 0.0077 memory: 5828 grad_norm: 4.1006 loss: 1.6757 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6757 2023/06/05 13:44:18 - mmengine - INFO - Epoch(train) [112][ 880/2569] lr: 4.0000e-03 eta: 7:20:18 time: 0.2670 data_time: 0.0069 memory: 5828 grad_norm: 4.0317 loss: 1.7812 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7812 2023/06/05 13:44:23 - mmengine - INFO - Epoch(train) [112][ 900/2569] lr: 4.0000e-03 eta: 7:20:13 time: 0.2674 data_time: 0.0077 memory: 5828 grad_norm: 4.0491 loss: 1.6232 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.6232 2023/06/05 13:44:28 - mmengine - INFO - Epoch(train) [112][ 920/2569] lr: 4.0000e-03 eta: 7:20:07 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 4.0660 loss: 1.7618 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7618 2023/06/05 13:44:34 - mmengine - INFO - Epoch(train) [112][ 940/2569] lr: 4.0000e-03 eta: 7:20:02 time: 0.2617 data_time: 0.0075 memory: 5828 grad_norm: 3.9962 loss: 2.0403 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0403 2023/06/05 13:44:39 - mmengine - INFO - Epoch(train) [112][ 960/2569] lr: 4.0000e-03 eta: 7:19:57 time: 0.2831 data_time: 0.0070 memory: 5828 grad_norm: 4.0513 loss: 1.9975 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9975 2023/06/05 13:44:45 - mmengine - INFO - Epoch(train) [112][ 980/2569] lr: 4.0000e-03 eta: 7:19:52 time: 0.2726 data_time: 0.0074 memory: 5828 grad_norm: 4.1198 loss: 1.7521 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7521 2023/06/05 13:44:50 - mmengine - INFO - Epoch(train) [112][1000/2569] lr: 4.0000e-03 eta: 7:19:46 time: 0.2667 data_time: 0.0070 memory: 5828 grad_norm: 4.0864 loss: 1.6862 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6862 2023/06/05 13:44:55 - mmengine - INFO - Epoch(train) [112][1020/2569] lr: 4.0000e-03 eta: 7:19:41 time: 0.2646 data_time: 0.0072 memory: 5828 grad_norm: 4.0552 loss: 1.8991 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8991 2023/06/05 13:45:01 - mmengine - INFO - Epoch(train) [112][1040/2569] lr: 4.0000e-03 eta: 7:19:36 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 4.1120 loss: 1.8044 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8044 2023/06/05 13:45:06 - mmengine - INFO - Epoch(train) [112][1060/2569] lr: 4.0000e-03 eta: 7:19:30 time: 0.2634 data_time: 0.0073 memory: 5828 grad_norm: 4.0255 loss: 1.9521 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9521 2023/06/05 13:45:11 - mmengine - INFO - Epoch(train) [112][1080/2569] lr: 4.0000e-03 eta: 7:19:25 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 4.0617 loss: 2.0301 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0301 2023/06/05 13:45:16 - mmengine - INFO - Epoch(train) [112][1100/2569] lr: 4.0000e-03 eta: 7:19:20 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 4.0429 loss: 1.9380 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9380 2023/06/05 13:45:22 - mmengine - INFO - Epoch(train) [112][1120/2569] lr: 4.0000e-03 eta: 7:19:14 time: 0.2772 data_time: 0.0073 memory: 5828 grad_norm: 4.0686 loss: 1.8421 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8421 2023/06/05 13:45:27 - mmengine - INFO - Epoch(train) [112][1140/2569] lr: 4.0000e-03 eta: 7:19:09 time: 0.2632 data_time: 0.0071 memory: 5828 grad_norm: 4.0086 loss: 1.7965 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7965 2023/06/05 13:45:32 - mmengine - INFO - Epoch(train) [112][1160/2569] lr: 4.0000e-03 eta: 7:19:04 time: 0.2613 data_time: 0.0071 memory: 5828 grad_norm: 4.1422 loss: 1.6286 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6286 2023/06/05 13:45:38 - mmengine - INFO - Epoch(train) [112][1180/2569] lr: 4.0000e-03 eta: 7:18:58 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 4.0870 loss: 1.8023 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8023 2023/06/05 13:45:43 - mmengine - INFO - Epoch(train) [112][1200/2569] lr: 4.0000e-03 eta: 7:18:53 time: 0.2673 data_time: 0.0076 memory: 5828 grad_norm: 4.0802 loss: 1.8226 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8226 2023/06/05 13:45:48 - mmengine - INFO - Epoch(train) [112][1220/2569] lr: 4.0000e-03 eta: 7:18:48 time: 0.2678 data_time: 0.0072 memory: 5828 grad_norm: 4.0344 loss: 1.8400 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8400 2023/06/05 13:45:54 - mmengine - INFO - Epoch(train) [112][1240/2569] lr: 4.0000e-03 eta: 7:18:42 time: 0.2678 data_time: 0.0070 memory: 5828 grad_norm: 4.0996 loss: 1.8049 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8049 2023/06/05 13:45:59 - mmengine - INFO - Epoch(train) [112][1260/2569] lr: 4.0000e-03 eta: 7:18:37 time: 0.2661 data_time: 0.0072 memory: 5828 grad_norm: 4.0150 loss: 1.7874 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.7874 2023/06/05 13:46:04 - mmengine - INFO - Epoch(train) [112][1280/2569] lr: 4.0000e-03 eta: 7:18:32 time: 0.2670 data_time: 0.0071 memory: 5828 grad_norm: 4.0278 loss: 2.3957 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.3957 2023/06/05 13:46:10 - mmengine - INFO - Epoch(train) [112][1300/2569] lr: 4.0000e-03 eta: 7:18:26 time: 0.2753 data_time: 0.0071 memory: 5828 grad_norm: 4.0727 loss: 1.8823 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8823 2023/06/05 13:46:15 - mmengine - INFO - Epoch(train) [112][1320/2569] lr: 4.0000e-03 eta: 7:18:21 time: 0.2738 data_time: 0.0071 memory: 5828 grad_norm: 4.0397 loss: 1.8140 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8140 2023/06/05 13:46:21 - mmengine - INFO - Epoch(train) [112][1340/2569] lr: 4.0000e-03 eta: 7:18:16 time: 0.2694 data_time: 0.0071 memory: 5828 grad_norm: 4.1413 loss: 2.1614 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1614 2023/06/05 13:46:26 - mmengine - INFO - Epoch(train) [112][1360/2569] lr: 4.0000e-03 eta: 7:18:11 time: 0.2730 data_time: 0.0071 memory: 5828 grad_norm: 4.0993 loss: 1.9456 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9456 2023/06/05 13:46:32 - mmengine - INFO - Epoch(train) [112][1380/2569] lr: 4.0000e-03 eta: 7:18:05 time: 0.2660 data_time: 0.0069 memory: 5828 grad_norm: 4.0715 loss: 1.7261 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7261 2023/06/05 13:46:37 - mmengine - INFO - Epoch(train) [112][1400/2569] lr: 4.0000e-03 eta: 7:18:00 time: 0.2822 data_time: 0.0072 memory: 5828 grad_norm: 4.0595 loss: 1.8492 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8492 2023/06/05 13:46:43 - mmengine - INFO - Epoch(train) [112][1420/2569] lr: 4.0000e-03 eta: 7:17:55 time: 0.2614 data_time: 0.0071 memory: 5828 grad_norm: 4.0738 loss: 1.7437 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7437 2023/06/05 13:46:48 - mmengine - INFO - Epoch(train) [112][1440/2569] lr: 4.0000e-03 eta: 7:17:49 time: 0.2689 data_time: 0.0072 memory: 5828 grad_norm: 4.0302 loss: 1.9204 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9204 2023/06/05 13:46:53 - mmengine - INFO - Epoch(train) [112][1460/2569] lr: 4.0000e-03 eta: 7:17:44 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 3.9550 loss: 1.8836 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8836 2023/06/05 13:46:59 - mmengine - INFO - Epoch(train) [112][1480/2569] lr: 4.0000e-03 eta: 7:17:39 time: 0.2663 data_time: 0.0071 memory: 5828 grad_norm: 4.0381 loss: 2.0771 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0771 2023/06/05 13:47:04 - mmengine - INFO - Epoch(train) [112][1500/2569] lr: 4.0000e-03 eta: 7:17:33 time: 0.2644 data_time: 0.0073 memory: 5828 grad_norm: 4.1686 loss: 1.8201 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8201 2023/06/05 13:47:09 - mmengine - INFO - Epoch(train) [112][1520/2569] lr: 4.0000e-03 eta: 7:17:28 time: 0.2620 data_time: 0.0071 memory: 5828 grad_norm: 4.1193 loss: 1.8170 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8170 2023/06/05 13:47:15 - mmengine - INFO - Epoch(train) [112][1540/2569] lr: 4.0000e-03 eta: 7:17:23 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 4.1041 loss: 1.7125 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7125 2023/06/05 13:47:20 - mmengine - INFO - Epoch(train) [112][1560/2569] lr: 4.0000e-03 eta: 7:17:17 time: 0.2670 data_time: 0.0070 memory: 5828 grad_norm: 4.1080 loss: 1.9828 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9828 2023/06/05 13:47:25 - mmengine - INFO - Epoch(train) [112][1580/2569] lr: 4.0000e-03 eta: 7:17:12 time: 0.2698 data_time: 0.0071 memory: 5828 grad_norm: 4.0758 loss: 1.9259 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9259 2023/06/05 13:47:31 - mmengine - INFO - Epoch(train) [112][1600/2569] lr: 4.0000e-03 eta: 7:17:07 time: 0.2722 data_time: 0.0070 memory: 5828 grad_norm: 4.0029 loss: 1.7635 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7635 2023/06/05 13:47:36 - mmengine - INFO - Epoch(train) [112][1620/2569] lr: 4.0000e-03 eta: 7:17:02 time: 0.2678 data_time: 0.0071 memory: 5828 grad_norm: 4.0530 loss: 1.7788 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7788 2023/06/05 13:47:41 - mmengine - INFO - Epoch(train) [112][1640/2569] lr: 4.0000e-03 eta: 7:16:56 time: 0.2657 data_time: 0.0070 memory: 5828 grad_norm: 4.0731 loss: 1.7302 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7302 2023/06/05 13:47:47 - mmengine - INFO - Epoch(train) [112][1660/2569] lr: 4.0000e-03 eta: 7:16:51 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 4.0150 loss: 1.9583 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9583 2023/06/05 13:47:52 - mmengine - INFO - Epoch(train) [112][1680/2569] lr: 4.0000e-03 eta: 7:16:46 time: 0.2793 data_time: 0.0072 memory: 5828 grad_norm: 4.0758 loss: 1.8604 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8604 2023/06/05 13:47:58 - mmengine - INFO - Epoch(train) [112][1700/2569] lr: 4.0000e-03 eta: 7:16:40 time: 0.2607 data_time: 0.0071 memory: 5828 grad_norm: 4.0953 loss: 1.7104 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7104 2023/06/05 13:48:03 - mmengine - INFO - Epoch(train) [112][1720/2569] lr: 4.0000e-03 eta: 7:16:35 time: 0.2668 data_time: 0.0070 memory: 5828 grad_norm: 4.1532 loss: 1.7045 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7045 2023/06/05 13:48:08 - mmengine - INFO - Epoch(train) [112][1740/2569] lr: 4.0000e-03 eta: 7:16:30 time: 0.2626 data_time: 0.0076 memory: 5828 grad_norm: 3.9790 loss: 1.8221 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8221 2023/06/05 13:48:14 - mmengine - INFO - Epoch(train) [112][1760/2569] lr: 4.0000e-03 eta: 7:16:24 time: 0.2803 data_time: 0.0071 memory: 5828 grad_norm: 4.1088 loss: 1.8468 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8468 2023/06/05 13:48:19 - mmengine - INFO - Epoch(train) [112][1780/2569] lr: 4.0000e-03 eta: 7:16:19 time: 0.2609 data_time: 0.0072 memory: 5828 grad_norm: 4.0550 loss: 1.8354 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8354 2023/06/05 13:48:25 - mmengine - INFO - Epoch(train) [112][1800/2569] lr: 4.0000e-03 eta: 7:16:14 time: 0.2742 data_time: 0.0071 memory: 5828 grad_norm: 4.0590 loss: 2.1898 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1898 2023/06/05 13:48:30 - mmengine - INFO - Epoch(train) [112][1820/2569] lr: 4.0000e-03 eta: 7:16:08 time: 0.2600 data_time: 0.0070 memory: 5828 grad_norm: 4.0950 loss: 1.6788 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6788 2023/06/05 13:48:35 - mmengine - INFO - Epoch(train) [112][1840/2569] lr: 4.0000e-03 eta: 7:16:03 time: 0.2678 data_time: 0.0073 memory: 5828 grad_norm: 4.1691 loss: 1.8224 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8224 2023/06/05 13:48:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:48:40 - mmengine - INFO - Epoch(train) [112][1860/2569] lr: 4.0000e-03 eta: 7:15:58 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 4.2021 loss: 1.9306 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9306 2023/06/05 13:48:46 - mmengine - INFO - Epoch(train) [112][1880/2569] lr: 4.0000e-03 eta: 7:15:53 time: 0.2743 data_time: 0.0073 memory: 5828 grad_norm: 4.1478 loss: 1.6802 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6802 2023/06/05 13:48:51 - mmengine - INFO - Epoch(train) [112][1900/2569] lr: 4.0000e-03 eta: 7:15:47 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 4.0481 loss: 1.7379 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7379 2023/06/05 13:48:57 - mmengine - INFO - Epoch(train) [112][1920/2569] lr: 4.0000e-03 eta: 7:15:42 time: 0.2722 data_time: 0.0069 memory: 5828 grad_norm: 4.1406 loss: 1.8332 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.8332 2023/06/05 13:49:02 - mmengine - INFO - Epoch(train) [112][1940/2569] lr: 4.0000e-03 eta: 7:15:37 time: 0.2601 data_time: 0.0073 memory: 5828 grad_norm: 4.0807 loss: 2.0321 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0321 2023/06/05 13:49:07 - mmengine - INFO - Epoch(train) [112][1960/2569] lr: 4.0000e-03 eta: 7:15:31 time: 0.2691 data_time: 0.0075 memory: 5828 grad_norm: 4.1306 loss: 2.0166 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0166 2023/06/05 13:49:12 - mmengine - INFO - Epoch(train) [112][1980/2569] lr: 4.0000e-03 eta: 7:15:26 time: 0.2616 data_time: 0.0075 memory: 5828 grad_norm: 4.0982 loss: 1.6976 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6976 2023/06/05 13:49:18 - mmengine - INFO - Epoch(train) [112][2000/2569] lr: 4.0000e-03 eta: 7:15:21 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 4.0462 loss: 1.7958 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7958 2023/06/05 13:49:23 - mmengine - INFO - Epoch(train) [112][2020/2569] lr: 4.0000e-03 eta: 7:15:15 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 4.0894 loss: 1.8950 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8950 2023/06/05 13:49:29 - mmengine - INFO - Epoch(train) [112][2040/2569] lr: 4.0000e-03 eta: 7:15:10 time: 0.2731 data_time: 0.0071 memory: 5828 grad_norm: 4.0884 loss: 2.1436 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1436 2023/06/05 13:49:34 - mmengine - INFO - Epoch(train) [112][2060/2569] lr: 4.0000e-03 eta: 7:15:05 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 4.0586 loss: 1.9670 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9670 2023/06/05 13:49:39 - mmengine - INFO - Epoch(train) [112][2080/2569] lr: 4.0000e-03 eta: 7:14:59 time: 0.2718 data_time: 0.0072 memory: 5828 grad_norm: 4.0915 loss: 1.9256 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9256 2023/06/05 13:49:45 - mmengine - INFO - Epoch(train) [112][2100/2569] lr: 4.0000e-03 eta: 7:14:54 time: 0.2714 data_time: 0.0070 memory: 5828 grad_norm: 4.0656 loss: 2.0174 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0174 2023/06/05 13:49:50 - mmengine - INFO - Epoch(train) [112][2120/2569] lr: 4.0000e-03 eta: 7:14:49 time: 0.2610 data_time: 0.0073 memory: 5828 grad_norm: 4.0838 loss: 1.8339 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8339 2023/06/05 13:49:55 - mmengine - INFO - Epoch(train) [112][2140/2569] lr: 4.0000e-03 eta: 7:14:44 time: 0.2697 data_time: 0.0070 memory: 5828 grad_norm: 4.1558 loss: 2.1688 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1688 2023/06/05 13:50:01 - mmengine - INFO - Epoch(train) [112][2160/2569] lr: 4.0000e-03 eta: 7:14:38 time: 0.2668 data_time: 0.0071 memory: 5828 grad_norm: 4.0668 loss: 1.7867 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7867 2023/06/05 13:50:06 - mmengine - INFO - Epoch(train) [112][2180/2569] lr: 4.0000e-03 eta: 7:14:33 time: 0.2657 data_time: 0.0071 memory: 5828 grad_norm: 4.0006 loss: 1.6622 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6622 2023/06/05 13:50:11 - mmengine - INFO - Epoch(train) [112][2200/2569] lr: 4.0000e-03 eta: 7:14:28 time: 0.2661 data_time: 0.0072 memory: 5828 grad_norm: 4.1201 loss: 2.0172 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0172 2023/06/05 13:50:17 - mmengine - INFO - Epoch(train) [112][2220/2569] lr: 4.0000e-03 eta: 7:14:22 time: 0.2628 data_time: 0.0070 memory: 5828 grad_norm: 4.1127 loss: 1.6202 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6202 2023/06/05 13:50:22 - mmengine - INFO - Epoch(train) [112][2240/2569] lr: 4.0000e-03 eta: 7:14:17 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 4.1788 loss: 1.9216 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9216 2023/06/05 13:50:27 - mmengine - INFO - Epoch(train) [112][2260/2569] lr: 4.0000e-03 eta: 7:14:12 time: 0.2613 data_time: 0.0071 memory: 5828 grad_norm: 4.1073 loss: 2.0390 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0390 2023/06/05 13:50:33 - mmengine - INFO - Epoch(train) [112][2280/2569] lr: 4.0000e-03 eta: 7:14:06 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 4.0398 loss: 1.8896 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8896 2023/06/05 13:50:38 - mmengine - INFO - Epoch(train) [112][2300/2569] lr: 4.0000e-03 eta: 7:14:01 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 4.1066 loss: 1.8378 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8378 2023/06/05 13:50:43 - mmengine - INFO - Epoch(train) [112][2320/2569] lr: 4.0000e-03 eta: 7:13:56 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 4.0043 loss: 1.5220 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5220 2023/06/05 13:50:49 - mmengine - INFO - Epoch(train) [112][2340/2569] lr: 4.0000e-03 eta: 7:13:50 time: 0.2661 data_time: 0.0070 memory: 5828 grad_norm: 4.1008 loss: 1.5808 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5808 2023/06/05 13:50:54 - mmengine - INFO - Epoch(train) [112][2360/2569] lr: 4.0000e-03 eta: 7:13:45 time: 0.2630 data_time: 0.0076 memory: 5828 grad_norm: 4.1813 loss: 1.7329 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7329 2023/06/05 13:50:59 - mmengine - INFO - Epoch(train) [112][2380/2569] lr: 4.0000e-03 eta: 7:13:40 time: 0.2764 data_time: 0.0078 memory: 5828 grad_norm: 4.0157 loss: 1.8475 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8475 2023/06/05 13:51:05 - mmengine - INFO - Epoch(train) [112][2400/2569] lr: 4.0000e-03 eta: 7:13:34 time: 0.2667 data_time: 0.0078 memory: 5828 grad_norm: 4.1144 loss: 1.9391 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9391 2023/06/05 13:51:10 - mmengine - INFO - Epoch(train) [112][2420/2569] lr: 4.0000e-03 eta: 7:13:29 time: 0.2709 data_time: 0.0074 memory: 5828 grad_norm: 4.0626 loss: 1.7748 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7748 2023/06/05 13:51:16 - mmengine - INFO - Epoch(train) [112][2440/2569] lr: 4.0000e-03 eta: 7:13:24 time: 0.2732 data_time: 0.0076 memory: 5828 grad_norm: 4.1306 loss: 1.8605 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8605 2023/06/05 13:51:21 - mmengine - INFO - Epoch(train) [112][2460/2569] lr: 4.0000e-03 eta: 7:13:18 time: 0.2666 data_time: 0.0074 memory: 5828 grad_norm: 4.1690 loss: 2.0105 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0105 2023/06/05 13:51:26 - mmengine - INFO - Epoch(train) [112][2480/2569] lr: 4.0000e-03 eta: 7:13:13 time: 0.2623 data_time: 0.0071 memory: 5828 grad_norm: 4.0937 loss: 1.8481 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8481 2023/06/05 13:51:32 - mmengine - INFO - Epoch(train) [112][2500/2569] lr: 4.0000e-03 eta: 7:13:08 time: 0.2666 data_time: 0.0072 memory: 5828 grad_norm: 4.1745 loss: 1.8210 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8210 2023/06/05 13:51:37 - mmengine - INFO - Epoch(train) [112][2520/2569] lr: 4.0000e-03 eta: 7:13:02 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 4.1871 loss: 1.9609 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9609 2023/06/05 13:51:42 - mmengine - INFO - Epoch(train) [112][2540/2569] lr: 4.0000e-03 eta: 7:12:57 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 4.0414 loss: 1.9143 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9143 2023/06/05 13:51:47 - mmengine - INFO - Epoch(train) [112][2560/2569] lr: 4.0000e-03 eta: 7:12:52 time: 0.2680 data_time: 0.0074 memory: 5828 grad_norm: 4.0438 loss: 1.7277 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7277 2023/06/05 13:51:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:51:50 - mmengine - INFO - Epoch(train) [112][2569/2569] lr: 4.0000e-03 eta: 7:12:49 time: 0.2614 data_time: 0.0070 memory: 5828 grad_norm: 4.1529 loss: 1.8499 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.8499 2023/06/05 13:51:50 - mmengine - INFO - Saving checkpoint at 112 epochs 2023/06/05 13:51:58 - mmengine - INFO - Epoch(train) [113][ 20/2569] lr: 4.0000e-03 eta: 7:12:44 time: 0.3008 data_time: 0.0458 memory: 5828 grad_norm: 4.1441 loss: 1.7654 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7654 2023/06/05 13:52:03 - mmengine - INFO - Epoch(train) [113][ 40/2569] lr: 4.0000e-03 eta: 7:12:39 time: 0.2671 data_time: 0.0078 memory: 5828 grad_norm: 4.0949 loss: 1.5420 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5420 2023/06/05 13:52:08 - mmengine - INFO - Epoch(train) [113][ 60/2569] lr: 4.0000e-03 eta: 7:12:34 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 4.1362 loss: 1.9610 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9610 2023/06/05 13:52:14 - mmengine - INFO - Epoch(train) [113][ 80/2569] lr: 4.0000e-03 eta: 7:12:28 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 4.0525 loss: 1.6743 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6743 2023/06/05 13:52:19 - mmengine - INFO - Epoch(train) [113][ 100/2569] lr: 4.0000e-03 eta: 7:12:23 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 4.0697 loss: 1.6304 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6304 2023/06/05 13:52:24 - mmengine - INFO - Epoch(train) [113][ 120/2569] lr: 4.0000e-03 eta: 7:12:18 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 4.0324 loss: 1.8787 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8787 2023/06/05 13:52:30 - mmengine - INFO - Epoch(train) [113][ 140/2569] lr: 4.0000e-03 eta: 7:12:12 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 4.1416 loss: 2.0083 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0083 2023/06/05 13:52:35 - mmengine - INFO - Epoch(train) [113][ 160/2569] lr: 4.0000e-03 eta: 7:12:07 time: 0.2651 data_time: 0.0070 memory: 5828 grad_norm: 4.1148 loss: 2.1250 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1250 2023/06/05 13:52:40 - mmengine - INFO - Epoch(train) [113][ 180/2569] lr: 4.0000e-03 eta: 7:12:02 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 4.0799 loss: 1.6586 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6586 2023/06/05 13:52:45 - mmengine - INFO - Epoch(train) [113][ 200/2569] lr: 4.0000e-03 eta: 7:11:56 time: 0.2594 data_time: 0.0075 memory: 5828 grad_norm: 4.0614 loss: 1.6829 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.6829 2023/06/05 13:52:51 - mmengine - INFO - Epoch(train) [113][ 220/2569] lr: 4.0000e-03 eta: 7:11:51 time: 0.2697 data_time: 0.0075 memory: 5828 grad_norm: 4.1516 loss: 1.8745 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8745 2023/06/05 13:52:56 - mmengine - INFO - Epoch(train) [113][ 240/2569] lr: 4.0000e-03 eta: 7:11:46 time: 0.2678 data_time: 0.0076 memory: 5828 grad_norm: 4.1841 loss: 1.8707 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8707 2023/06/05 13:53:01 - mmengine - INFO - Epoch(train) [113][ 260/2569] lr: 4.0000e-03 eta: 7:11:40 time: 0.2609 data_time: 0.0076 memory: 5828 grad_norm: 4.1611 loss: 1.8387 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8387 2023/06/05 13:53:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:53:07 - mmengine - INFO - Epoch(train) [113][ 280/2569] lr: 4.0000e-03 eta: 7:11:35 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 4.0818 loss: 1.8746 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8746 2023/06/05 13:53:12 - mmengine - INFO - Epoch(train) [113][ 300/2569] lr: 4.0000e-03 eta: 7:11:30 time: 0.2644 data_time: 0.0077 memory: 5828 grad_norm: 4.0994 loss: 1.8042 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8042 2023/06/05 13:53:17 - mmengine - INFO - Epoch(train) [113][ 320/2569] lr: 4.0000e-03 eta: 7:11:24 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 4.0575 loss: 1.9857 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9857 2023/06/05 13:53:23 - mmengine - INFO - Epoch(train) [113][ 340/2569] lr: 4.0000e-03 eta: 7:11:19 time: 0.2737 data_time: 0.0076 memory: 5828 grad_norm: 4.1332 loss: 1.9645 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 1.9645 2023/06/05 13:53:28 - mmengine - INFO - Epoch(train) [113][ 360/2569] lr: 4.0000e-03 eta: 7:11:14 time: 0.2591 data_time: 0.0076 memory: 5828 grad_norm: 4.1274 loss: 1.7177 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7177 2023/06/05 13:53:34 - mmengine - INFO - Epoch(train) [113][ 380/2569] lr: 4.0000e-03 eta: 7:11:08 time: 0.2767 data_time: 0.0073 memory: 5828 grad_norm: 4.1408 loss: 1.6304 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6304 2023/06/05 13:53:39 - mmengine - INFO - Epoch(train) [113][ 400/2569] lr: 4.0000e-03 eta: 7:11:03 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 4.0511 loss: 1.8260 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8260 2023/06/05 13:53:44 - mmengine - INFO - Epoch(train) [113][ 420/2569] lr: 4.0000e-03 eta: 7:10:58 time: 0.2678 data_time: 0.0071 memory: 5828 grad_norm: 4.1619 loss: 1.7806 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7806 2023/06/05 13:53:50 - mmengine - INFO - Epoch(train) [113][ 440/2569] lr: 4.0000e-03 eta: 7:10:52 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 4.1581 loss: 1.8318 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8318 2023/06/05 13:53:55 - mmengine - INFO - Epoch(train) [113][ 460/2569] lr: 4.0000e-03 eta: 7:10:47 time: 0.2704 data_time: 0.0071 memory: 5828 grad_norm: 4.0242 loss: 1.8633 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8633 2023/06/05 13:54:00 - mmengine - INFO - Epoch(train) [113][ 480/2569] lr: 4.0000e-03 eta: 7:10:42 time: 0.2751 data_time: 0.0071 memory: 5828 grad_norm: 4.1133 loss: 1.8999 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8999 2023/06/05 13:54:06 - mmengine - INFO - Epoch(train) [113][ 500/2569] lr: 4.0000e-03 eta: 7:10:37 time: 0.2624 data_time: 0.0071 memory: 5828 grad_norm: 4.1160 loss: 1.9236 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9236 2023/06/05 13:54:11 - mmengine - INFO - Epoch(train) [113][ 520/2569] lr: 4.0000e-03 eta: 7:10:31 time: 0.2713 data_time: 0.0072 memory: 5828 grad_norm: 4.1507 loss: 1.5408 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5408 2023/06/05 13:54:16 - mmengine - INFO - Epoch(train) [113][ 540/2569] lr: 4.0000e-03 eta: 7:10:26 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 4.1227 loss: 1.9797 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9797 2023/06/05 13:54:22 - mmengine - INFO - Epoch(train) [113][ 560/2569] lr: 4.0000e-03 eta: 7:10:21 time: 0.2665 data_time: 0.0074 memory: 5828 grad_norm: 4.0985 loss: 1.8190 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8190 2023/06/05 13:54:27 - mmengine - INFO - Epoch(train) [113][ 580/2569] lr: 4.0000e-03 eta: 7:10:15 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 4.1181 loss: 1.5864 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5864 2023/06/05 13:54:32 - mmengine - INFO - Epoch(train) [113][ 600/2569] lr: 4.0000e-03 eta: 7:10:10 time: 0.2665 data_time: 0.0074 memory: 5828 grad_norm: 4.1570 loss: 1.9057 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9057 2023/06/05 13:54:38 - mmengine - INFO - Epoch(train) [113][ 620/2569] lr: 4.0000e-03 eta: 7:10:05 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 4.1095 loss: 1.5386 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5386 2023/06/05 13:54:43 - mmengine - INFO - Epoch(train) [113][ 640/2569] lr: 4.0000e-03 eta: 7:09:59 time: 0.2630 data_time: 0.0071 memory: 5828 grad_norm: 4.0467 loss: 1.6395 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6395 2023/06/05 13:54:48 - mmengine - INFO - Epoch(train) [113][ 660/2569] lr: 4.0000e-03 eta: 7:09:54 time: 0.2606 data_time: 0.0071 memory: 5828 grad_norm: 4.0632 loss: 1.8141 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8141 2023/06/05 13:54:53 - mmengine - INFO - Epoch(train) [113][ 680/2569] lr: 4.0000e-03 eta: 7:09:49 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 4.1489 loss: 1.8246 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8246 2023/06/05 13:54:59 - mmengine - INFO - Epoch(train) [113][ 700/2569] lr: 4.0000e-03 eta: 7:09:43 time: 0.2656 data_time: 0.0082 memory: 5828 grad_norm: 4.1170 loss: 2.1270 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1270 2023/06/05 13:55:04 - mmengine - INFO - Epoch(train) [113][ 720/2569] lr: 4.0000e-03 eta: 7:09:38 time: 0.2595 data_time: 0.0070 memory: 5828 grad_norm: 4.1733 loss: 1.6614 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6614 2023/06/05 13:55:09 - mmengine - INFO - Epoch(train) [113][ 740/2569] lr: 4.0000e-03 eta: 7:09:33 time: 0.2715 data_time: 0.0073 memory: 5828 grad_norm: 4.0769 loss: 1.6456 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6456 2023/06/05 13:55:15 - mmengine - INFO - Epoch(train) [113][ 760/2569] lr: 4.0000e-03 eta: 7:09:27 time: 0.2659 data_time: 0.0070 memory: 5828 grad_norm: 4.1148 loss: 1.7894 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7894 2023/06/05 13:55:20 - mmengine - INFO - Epoch(train) [113][ 780/2569] lr: 4.0000e-03 eta: 7:09:22 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 4.1453 loss: 1.9933 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9933 2023/06/05 13:55:25 - mmengine - INFO - Epoch(train) [113][ 800/2569] lr: 4.0000e-03 eta: 7:09:17 time: 0.2672 data_time: 0.0072 memory: 5828 grad_norm: 4.1010 loss: 1.8456 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8456 2023/06/05 13:55:31 - mmengine - INFO - Epoch(train) [113][ 820/2569] lr: 4.0000e-03 eta: 7:09:11 time: 0.2669 data_time: 0.0069 memory: 5828 grad_norm: 4.1475 loss: 2.0058 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0058 2023/06/05 13:55:36 - mmengine - INFO - Epoch(train) [113][ 840/2569] lr: 4.0000e-03 eta: 7:09:06 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 4.1365 loss: 2.1237 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1237 2023/06/05 13:55:41 - mmengine - INFO - Epoch(train) [113][ 860/2569] lr: 4.0000e-03 eta: 7:09:01 time: 0.2652 data_time: 0.0074 memory: 5828 grad_norm: 4.0482 loss: 1.8240 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8240 2023/06/05 13:55:47 - mmengine - INFO - Epoch(train) [113][ 880/2569] lr: 4.0000e-03 eta: 7:08:55 time: 0.2680 data_time: 0.0070 memory: 5828 grad_norm: 4.0843 loss: 1.8485 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8485 2023/06/05 13:55:52 - mmengine - INFO - Epoch(train) [113][ 900/2569] lr: 4.0000e-03 eta: 7:08:50 time: 0.2694 data_time: 0.0070 memory: 5828 grad_norm: 4.1166 loss: 1.9373 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9373 2023/06/05 13:55:57 - mmengine - INFO - Epoch(train) [113][ 920/2569] lr: 4.0000e-03 eta: 7:08:45 time: 0.2682 data_time: 0.0070 memory: 5828 grad_norm: 4.0618 loss: 1.9398 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9398 2023/06/05 13:56:03 - mmengine - INFO - Epoch(train) [113][ 940/2569] lr: 4.0000e-03 eta: 7:08:39 time: 0.2673 data_time: 0.0072 memory: 5828 grad_norm: 4.1452 loss: 1.8403 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8403 2023/06/05 13:56:08 - mmengine - INFO - Epoch(train) [113][ 960/2569] lr: 4.0000e-03 eta: 7:08:34 time: 0.2715 data_time: 0.0074 memory: 5828 grad_norm: 4.2206 loss: 1.7283 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7283 2023/06/05 13:56:14 - mmengine - INFO - Epoch(train) [113][ 980/2569] lr: 4.0000e-03 eta: 7:08:29 time: 0.2693 data_time: 0.0071 memory: 5828 grad_norm: 4.1599 loss: 2.0406 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0406 2023/06/05 13:56:19 - mmengine - INFO - Epoch(train) [113][1000/2569] lr: 4.0000e-03 eta: 7:08:24 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 4.1262 loss: 1.9919 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9919 2023/06/05 13:56:24 - mmengine - INFO - Epoch(train) [113][1020/2569] lr: 4.0000e-03 eta: 7:08:18 time: 0.2687 data_time: 0.0081 memory: 5828 grad_norm: 4.0583 loss: 1.9738 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9738 2023/06/05 13:56:29 - mmengine - INFO - Epoch(train) [113][1040/2569] lr: 4.0000e-03 eta: 7:08:13 time: 0.2612 data_time: 0.0076 memory: 5828 grad_norm: 4.1565 loss: 1.9349 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9349 2023/06/05 13:56:35 - mmengine - INFO - Epoch(train) [113][1060/2569] lr: 4.0000e-03 eta: 7:08:08 time: 0.2624 data_time: 0.0071 memory: 5828 grad_norm: 4.0838 loss: 1.8857 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8857 2023/06/05 13:56:40 - mmengine - INFO - Epoch(train) [113][1080/2569] lr: 4.0000e-03 eta: 7:08:02 time: 0.2623 data_time: 0.0079 memory: 5828 grad_norm: 4.0589 loss: 2.0732 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0732 2023/06/05 13:56:45 - mmengine - INFO - Epoch(train) [113][1100/2569] lr: 4.0000e-03 eta: 7:07:57 time: 0.2713 data_time: 0.0072 memory: 5828 grad_norm: 4.1966 loss: 1.6491 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6491 2023/06/05 13:56:51 - mmengine - INFO - Epoch(train) [113][1120/2569] lr: 4.0000e-03 eta: 7:07:52 time: 0.2712 data_time: 0.0081 memory: 5828 grad_norm: 4.1788 loss: 1.6476 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6476 2023/06/05 13:56:56 - mmengine - INFO - Epoch(train) [113][1140/2569] lr: 4.0000e-03 eta: 7:07:46 time: 0.2715 data_time: 0.0072 memory: 5828 grad_norm: 4.1202 loss: 1.8207 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8207 2023/06/05 13:57:02 - mmengine - INFO - Epoch(train) [113][1160/2569] lr: 4.0000e-03 eta: 7:07:41 time: 0.2724 data_time: 0.0076 memory: 5828 grad_norm: 4.1225 loss: 1.8258 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8258 2023/06/05 13:57:07 - mmengine - INFO - Epoch(train) [113][1180/2569] lr: 4.0000e-03 eta: 7:07:36 time: 0.2662 data_time: 0.0074 memory: 5828 grad_norm: 4.1903 loss: 1.7529 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7529 2023/06/05 13:57:13 - mmengine - INFO - Epoch(train) [113][1200/2569] lr: 4.0000e-03 eta: 7:07:30 time: 0.2725 data_time: 0.0071 memory: 5828 grad_norm: 4.2288 loss: 1.6997 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6997 2023/06/05 13:57:18 - mmengine - INFO - Epoch(train) [113][1220/2569] lr: 4.0000e-03 eta: 7:07:25 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 4.1170 loss: 2.1544 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1544 2023/06/05 13:57:23 - mmengine - INFO - Epoch(train) [113][1240/2569] lr: 4.0000e-03 eta: 7:07:20 time: 0.2768 data_time: 0.0073 memory: 5828 grad_norm: 4.1635 loss: 1.5726 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.5726 2023/06/05 13:57:29 - mmengine - INFO - Epoch(train) [113][1260/2569] lr: 4.0000e-03 eta: 7:07:15 time: 0.2670 data_time: 0.0077 memory: 5828 grad_norm: 4.0659 loss: 2.0103 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0103 2023/06/05 13:57:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 13:57:34 - mmengine - INFO - Epoch(train) [113][1280/2569] lr: 4.0000e-03 eta: 7:07:09 time: 0.2665 data_time: 0.0079 memory: 5828 grad_norm: 4.1295 loss: 2.3367 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3367 2023/06/05 13:57:39 - mmengine - INFO - Epoch(train) [113][1300/2569] lr: 4.0000e-03 eta: 7:07:04 time: 0.2613 data_time: 0.0072 memory: 5828 grad_norm: 4.1336 loss: 1.6179 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6179 2023/06/05 13:57:45 - mmengine - INFO - Epoch(train) [113][1320/2569] lr: 4.0000e-03 eta: 7:06:59 time: 0.2601 data_time: 0.0076 memory: 5828 grad_norm: 4.1779 loss: 1.7399 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7399 2023/06/05 13:57:50 - mmengine - INFO - Epoch(train) [113][1340/2569] lr: 4.0000e-03 eta: 7:06:53 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 4.0644 loss: 2.1050 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1050 2023/06/05 13:57:55 - mmengine - INFO - Epoch(train) [113][1360/2569] lr: 4.0000e-03 eta: 7:06:48 time: 0.2621 data_time: 0.0077 memory: 5828 grad_norm: 4.1702 loss: 2.0755 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0755 2023/06/05 13:58:01 - mmengine - INFO - Epoch(train) [113][1380/2569] lr: 4.0000e-03 eta: 7:06:43 time: 0.2731 data_time: 0.0073 memory: 5828 grad_norm: 4.0825 loss: 1.4453 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4453 2023/06/05 13:58:06 - mmengine - INFO - Epoch(train) [113][1400/2569] lr: 4.0000e-03 eta: 7:06:37 time: 0.2645 data_time: 0.0076 memory: 5828 grad_norm: 4.1494 loss: 2.0146 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0146 2023/06/05 13:58:11 - mmengine - INFO - Epoch(train) [113][1420/2569] lr: 4.0000e-03 eta: 7:06:32 time: 0.2696 data_time: 0.0072 memory: 5828 grad_norm: 4.1303 loss: 1.9477 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9477 2023/06/05 13:58:17 - mmengine - INFO - Epoch(train) [113][1440/2569] lr: 4.0000e-03 eta: 7:06:27 time: 0.2684 data_time: 0.0071 memory: 5828 grad_norm: 4.0460 loss: 1.9141 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9141 2023/06/05 13:58:22 - mmengine - INFO - Epoch(train) [113][1460/2569] lr: 4.0000e-03 eta: 7:06:21 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 4.1227 loss: 1.8641 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8641 2023/06/05 13:58:27 - mmengine - INFO - Epoch(train) [113][1480/2569] lr: 4.0000e-03 eta: 7:06:16 time: 0.2721 data_time: 0.0071 memory: 5828 grad_norm: 4.1355 loss: 1.5577 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5577 2023/06/05 13:58:33 - mmengine - INFO - Epoch(train) [113][1500/2569] lr: 4.0000e-03 eta: 7:06:11 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 4.0766 loss: 1.9733 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9733 2023/06/05 13:58:38 - mmengine - INFO - Epoch(train) [113][1520/2569] lr: 4.0000e-03 eta: 7:06:05 time: 0.2705 data_time: 0.0072 memory: 5828 grad_norm: 4.0743 loss: 2.0961 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0961 2023/06/05 13:58:43 - mmengine - INFO - Epoch(train) [113][1540/2569] lr: 4.0000e-03 eta: 7:06:00 time: 0.2619 data_time: 0.0075 memory: 5828 grad_norm: 4.1272 loss: 1.7000 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7000 2023/06/05 13:58:49 - mmengine - INFO - Epoch(train) [113][1560/2569] lr: 4.0000e-03 eta: 7:05:55 time: 0.2600 data_time: 0.0071 memory: 5828 grad_norm: 4.1480 loss: 1.6912 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6912 2023/06/05 13:58:54 - mmengine - INFO - Epoch(train) [113][1580/2569] lr: 4.0000e-03 eta: 7:05:49 time: 0.2668 data_time: 0.0071 memory: 5828 grad_norm: 4.1448 loss: 1.6342 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6342 2023/06/05 13:58:59 - mmengine - INFO - Epoch(train) [113][1600/2569] lr: 4.0000e-03 eta: 7:05:44 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 4.1305 loss: 1.8955 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8955 2023/06/05 13:59:05 - mmengine - INFO - Epoch(train) [113][1620/2569] lr: 4.0000e-03 eta: 7:05:39 time: 0.2652 data_time: 0.0070 memory: 5828 grad_norm: 4.0760 loss: 1.7476 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7476 2023/06/05 13:59:10 - mmengine - INFO - Epoch(train) [113][1640/2569] lr: 4.0000e-03 eta: 7:05:34 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 4.1028 loss: 1.6352 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6352 2023/06/05 13:59:15 - mmengine - INFO - Epoch(train) [113][1660/2569] lr: 4.0000e-03 eta: 7:05:28 time: 0.2598 data_time: 0.0071 memory: 5828 grad_norm: 4.1924 loss: 1.6430 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6430 2023/06/05 13:59:21 - mmengine - INFO - Epoch(train) [113][1680/2569] lr: 4.0000e-03 eta: 7:05:23 time: 0.2710 data_time: 0.0071 memory: 5828 grad_norm: 4.1433 loss: 1.8460 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8460 2023/06/05 13:59:26 - mmengine - INFO - Epoch(train) [113][1700/2569] lr: 4.0000e-03 eta: 7:05:18 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 4.0434 loss: 1.6212 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6212 2023/06/05 13:59:31 - mmengine - INFO - Epoch(train) [113][1720/2569] lr: 4.0000e-03 eta: 7:05:12 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 4.1236 loss: 1.5313 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5313 2023/06/05 13:59:37 - mmengine - INFO - Epoch(train) [113][1740/2569] lr: 4.0000e-03 eta: 7:05:07 time: 0.2602 data_time: 0.0070 memory: 5828 grad_norm: 4.1432 loss: 1.8950 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8950 2023/06/05 13:59:42 - mmengine - INFO - Epoch(train) [113][1760/2569] lr: 4.0000e-03 eta: 7:05:02 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 4.0890 loss: 1.6014 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6014 2023/06/05 13:59:47 - mmengine - INFO - Epoch(train) [113][1780/2569] lr: 4.0000e-03 eta: 7:04:56 time: 0.2665 data_time: 0.0075 memory: 5828 grad_norm: 4.2202 loss: 1.7687 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.7687 2023/06/05 13:59:53 - mmengine - INFO - Epoch(train) [113][1800/2569] lr: 4.0000e-03 eta: 7:04:51 time: 0.2658 data_time: 0.0074 memory: 5828 grad_norm: 4.1014 loss: 1.8617 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8617 2023/06/05 13:59:58 - mmengine - INFO - Epoch(train) [113][1820/2569] lr: 4.0000e-03 eta: 7:04:46 time: 0.2687 data_time: 0.0074 memory: 5828 grad_norm: 4.1299 loss: 1.4655 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4655 2023/06/05 14:00:03 - mmengine - INFO - Epoch(train) [113][1840/2569] lr: 4.0000e-03 eta: 7:04:40 time: 0.2655 data_time: 0.0074 memory: 5828 grad_norm: 4.1704 loss: 1.9068 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9068 2023/06/05 14:00:09 - mmengine - INFO - Epoch(train) [113][1860/2569] lr: 4.0000e-03 eta: 7:04:35 time: 0.2614 data_time: 0.0076 memory: 5828 grad_norm: 4.1897 loss: 1.9637 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9637 2023/06/05 14:00:14 - mmengine - INFO - Epoch(train) [113][1880/2569] lr: 4.0000e-03 eta: 7:04:30 time: 0.2704 data_time: 0.0075 memory: 5828 grad_norm: 4.1403 loss: 1.7665 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7665 2023/06/05 14:00:20 - mmengine - INFO - Epoch(train) [113][1900/2569] lr: 4.0000e-03 eta: 7:04:24 time: 0.2721 data_time: 0.0076 memory: 5828 grad_norm: 4.2026 loss: 1.8407 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8407 2023/06/05 14:00:25 - mmengine - INFO - Epoch(train) [113][1920/2569] lr: 4.0000e-03 eta: 7:04:19 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 4.1022 loss: 1.6207 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6207 2023/06/05 14:00:30 - mmengine - INFO - Epoch(train) [113][1940/2569] lr: 4.0000e-03 eta: 7:04:14 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 4.2191 loss: 1.6974 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6974 2023/06/05 14:00:35 - mmengine - INFO - Epoch(train) [113][1960/2569] lr: 4.0000e-03 eta: 7:04:08 time: 0.2604 data_time: 0.0076 memory: 5828 grad_norm: 4.1824 loss: 1.8092 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8092 2023/06/05 14:00:41 - mmengine - INFO - Epoch(train) [113][1980/2569] lr: 4.0000e-03 eta: 7:04:03 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 4.1151 loss: 1.7265 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7265 2023/06/05 14:00:46 - mmengine - INFO - Epoch(train) [113][2000/2569] lr: 4.0000e-03 eta: 7:03:58 time: 0.2605 data_time: 0.0071 memory: 5828 grad_norm: 4.1616 loss: 1.7329 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7329 2023/06/05 14:00:51 - mmengine - INFO - Epoch(train) [113][2020/2569] lr: 4.0000e-03 eta: 7:03:52 time: 0.2740 data_time: 0.0071 memory: 5828 grad_norm: 4.1739 loss: 1.6690 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6690 2023/06/05 14:00:57 - mmengine - INFO - Epoch(train) [113][2040/2569] lr: 4.0000e-03 eta: 7:03:47 time: 0.2719 data_time: 0.0075 memory: 5828 grad_norm: 4.2071 loss: 1.7879 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7879 2023/06/05 14:01:02 - mmengine - INFO - Epoch(train) [113][2060/2569] lr: 4.0000e-03 eta: 7:03:42 time: 0.2792 data_time: 0.0074 memory: 5828 grad_norm: 4.1588 loss: 1.6048 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6048 2023/06/05 14:01:08 - mmengine - INFO - Epoch(train) [113][2080/2569] lr: 4.0000e-03 eta: 7:03:37 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 4.2512 loss: 1.8709 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8709 2023/06/05 14:01:13 - mmengine - INFO - Epoch(train) [113][2100/2569] lr: 4.0000e-03 eta: 7:03:31 time: 0.2746 data_time: 0.0073 memory: 5828 grad_norm: 4.0928 loss: 1.9386 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9386 2023/06/05 14:01:18 - mmengine - INFO - Epoch(train) [113][2120/2569] lr: 4.0000e-03 eta: 7:03:26 time: 0.2604 data_time: 0.0074 memory: 5828 grad_norm: 4.0913 loss: 1.7365 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7365 2023/06/05 14:01:24 - mmengine - INFO - Epoch(train) [113][2140/2569] lr: 4.0000e-03 eta: 7:03:21 time: 0.2634 data_time: 0.0070 memory: 5828 grad_norm: 4.1001 loss: 2.1081 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1081 2023/06/05 14:01:29 - mmengine - INFO - Epoch(train) [113][2160/2569] lr: 4.0000e-03 eta: 7:03:15 time: 0.2662 data_time: 0.0077 memory: 5828 grad_norm: 4.1319 loss: 1.7572 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7572 2023/06/05 14:01:35 - mmengine - INFO - Epoch(train) [113][2180/2569] lr: 4.0000e-03 eta: 7:03:10 time: 0.2758 data_time: 0.0074 memory: 5828 grad_norm: 4.1170 loss: 1.8812 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8812 2023/06/05 14:01:40 - mmengine - INFO - Epoch(train) [113][2200/2569] lr: 4.0000e-03 eta: 7:03:05 time: 0.2643 data_time: 0.0071 memory: 5828 grad_norm: 4.2104 loss: 1.8719 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8719 2023/06/05 14:01:45 - mmengine - INFO - Epoch(train) [113][2220/2569] lr: 4.0000e-03 eta: 7:02:59 time: 0.2770 data_time: 0.0073 memory: 5828 grad_norm: 4.1389 loss: 1.8796 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8796 2023/06/05 14:01:51 - mmengine - INFO - Epoch(train) [113][2240/2569] lr: 4.0000e-03 eta: 7:02:54 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 4.1779 loss: 1.8301 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8301 2023/06/05 14:01:56 - mmengine - INFO - Epoch(train) [113][2260/2569] lr: 4.0000e-03 eta: 7:02:49 time: 0.2628 data_time: 0.0073 memory: 5828 grad_norm: 4.1758 loss: 1.9493 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9493 2023/06/05 14:01:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:02:02 - mmengine - INFO - Epoch(train) [113][2280/2569] lr: 4.0000e-03 eta: 7:02:44 time: 0.2782 data_time: 0.0072 memory: 5828 grad_norm: 4.0227 loss: 1.9310 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9310 2023/06/05 14:02:07 - mmengine - INFO - Epoch(train) [113][2300/2569] lr: 4.0000e-03 eta: 7:02:38 time: 0.2606 data_time: 0.0085 memory: 5828 grad_norm: 4.1598 loss: 1.5338 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5338 2023/06/05 14:02:12 - mmengine - INFO - Epoch(train) [113][2320/2569] lr: 4.0000e-03 eta: 7:02:33 time: 0.2716 data_time: 0.0082 memory: 5828 grad_norm: 4.1336 loss: 2.0029 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0029 2023/06/05 14:02:18 - mmengine - INFO - Epoch(train) [113][2340/2569] lr: 4.0000e-03 eta: 7:02:28 time: 0.2678 data_time: 0.0073 memory: 5828 grad_norm: 4.1539 loss: 1.7013 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7013 2023/06/05 14:02:23 - mmengine - INFO - Epoch(train) [113][2360/2569] lr: 4.0000e-03 eta: 7:02:22 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 4.2235 loss: 1.7258 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7258 2023/06/05 14:02:28 - mmengine - INFO - Epoch(train) [113][2380/2569] lr: 4.0000e-03 eta: 7:02:17 time: 0.2674 data_time: 0.0081 memory: 5828 grad_norm: 4.1242 loss: 1.4867 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4867 2023/06/05 14:02:34 - mmengine - INFO - Epoch(train) [113][2400/2569] lr: 4.0000e-03 eta: 7:02:12 time: 0.2672 data_time: 0.0069 memory: 5828 grad_norm: 4.0416 loss: 1.7671 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7671 2023/06/05 14:02:39 - mmengine - INFO - Epoch(train) [113][2420/2569] lr: 4.0000e-03 eta: 7:02:06 time: 0.2634 data_time: 0.0084 memory: 5828 grad_norm: 4.1576 loss: 1.7565 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7565 2023/06/05 14:02:44 - mmengine - INFO - Epoch(train) [113][2440/2569] lr: 4.0000e-03 eta: 7:02:01 time: 0.2636 data_time: 0.0084 memory: 5828 grad_norm: 4.1405 loss: 1.8761 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8761 2023/06/05 14:02:50 - mmengine - INFO - Epoch(train) [113][2460/2569] lr: 4.0000e-03 eta: 7:01:56 time: 0.2676 data_time: 0.0075 memory: 5828 grad_norm: 4.1770 loss: 1.8121 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8121 2023/06/05 14:02:55 - mmengine - INFO - Epoch(train) [113][2480/2569] lr: 4.0000e-03 eta: 7:01:50 time: 0.2666 data_time: 0.0076 memory: 5828 grad_norm: 4.1114 loss: 1.6995 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.6995 2023/06/05 14:03:00 - mmengine - INFO - Epoch(train) [113][2500/2569] lr: 4.0000e-03 eta: 7:01:45 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 4.2353 loss: 1.9561 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9561 2023/06/05 14:03:05 - mmengine - INFO - Epoch(train) [113][2520/2569] lr: 4.0000e-03 eta: 7:01:40 time: 0.2632 data_time: 0.0071 memory: 5828 grad_norm: 4.1446 loss: 1.5508 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5508 2023/06/05 14:03:11 - mmengine - INFO - Epoch(train) [113][2540/2569] lr: 4.0000e-03 eta: 7:01:34 time: 0.2739 data_time: 0.0071 memory: 5828 grad_norm: 4.1166 loss: 1.6604 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6604 2023/06/05 14:03:16 - mmengine - INFO - Epoch(train) [113][2560/2569] lr: 4.0000e-03 eta: 7:01:29 time: 0.2622 data_time: 0.0074 memory: 5828 grad_norm: 4.0790 loss: 1.7687 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7687 2023/06/05 14:03:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:03:19 - mmengine - INFO - Epoch(train) [113][2569/2569] lr: 4.0000e-03 eta: 7:01:27 time: 0.2632 data_time: 0.0070 memory: 5828 grad_norm: 4.1025 loss: 1.5548 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5548 2023/06/05 14:03:26 - mmengine - INFO - Epoch(train) [114][ 20/2569] lr: 4.0000e-03 eta: 7:01:22 time: 0.3473 data_time: 0.0488 memory: 5828 grad_norm: 4.0656 loss: 1.6489 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6489 2023/06/05 14:03:31 - mmengine - INFO - Epoch(train) [114][ 40/2569] lr: 4.0000e-03 eta: 7:01:17 time: 0.2764 data_time: 0.0075 memory: 5828 grad_norm: 4.1561 loss: 1.8217 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8217 2023/06/05 14:03:36 - mmengine - INFO - Epoch(train) [114][ 60/2569] lr: 4.0000e-03 eta: 7:01:11 time: 0.2665 data_time: 0.0073 memory: 5828 grad_norm: 4.1573 loss: 1.8244 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8244 2023/06/05 14:03:42 - mmengine - INFO - Epoch(train) [114][ 80/2569] lr: 4.0000e-03 eta: 7:01:06 time: 0.2769 data_time: 0.0073 memory: 5828 grad_norm: 4.1707 loss: 1.9806 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9806 2023/06/05 14:03:47 - mmengine - INFO - Epoch(train) [114][ 100/2569] lr: 4.0000e-03 eta: 7:01:01 time: 0.2672 data_time: 0.0072 memory: 5828 grad_norm: 4.1976 loss: 1.9192 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9192 2023/06/05 14:03:53 - mmengine - INFO - Epoch(train) [114][ 120/2569] lr: 4.0000e-03 eta: 7:00:55 time: 0.2683 data_time: 0.0076 memory: 5828 grad_norm: 4.1698 loss: 1.8564 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8564 2023/06/05 14:03:58 - mmengine - INFO - Epoch(train) [114][ 140/2569] lr: 4.0000e-03 eta: 7:00:50 time: 0.2617 data_time: 0.0077 memory: 5828 grad_norm: 4.1526 loss: 1.7472 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7472 2023/06/05 14:04:03 - mmengine - INFO - Epoch(train) [114][ 160/2569] lr: 4.0000e-03 eta: 7:00:45 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 4.2615 loss: 1.8154 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8154 2023/06/05 14:04:09 - mmengine - INFO - Epoch(train) [114][ 180/2569] lr: 4.0000e-03 eta: 7:00:39 time: 0.2721 data_time: 0.0074 memory: 5828 grad_norm: 4.1461 loss: 1.8263 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8263 2023/06/05 14:04:14 - mmengine - INFO - Epoch(train) [114][ 200/2569] lr: 4.0000e-03 eta: 7:00:34 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 4.1631 loss: 1.8629 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8629 2023/06/05 14:04:19 - mmengine - INFO - Epoch(train) [114][ 220/2569] lr: 4.0000e-03 eta: 7:00:29 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 4.1478 loss: 1.9069 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9069 2023/06/05 14:04:24 - mmengine - INFO - Epoch(train) [114][ 240/2569] lr: 4.0000e-03 eta: 7:00:23 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 4.1029 loss: 1.7788 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7788 2023/06/05 14:04:30 - mmengine - INFO - Epoch(train) [114][ 260/2569] lr: 4.0000e-03 eta: 7:00:18 time: 0.2665 data_time: 0.0072 memory: 5828 grad_norm: 4.1224 loss: 1.9725 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9725 2023/06/05 14:04:35 - mmengine - INFO - Epoch(train) [114][ 280/2569] lr: 4.0000e-03 eta: 7:00:13 time: 0.2704 data_time: 0.0071 memory: 5828 grad_norm: 4.2357 loss: 2.2640 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.2640 2023/06/05 14:04:41 - mmengine - INFO - Epoch(train) [114][ 300/2569] lr: 4.0000e-03 eta: 7:00:07 time: 0.2661 data_time: 0.0071 memory: 5828 grad_norm: 4.1931 loss: 1.6783 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6783 2023/06/05 14:04:46 - mmengine - INFO - Epoch(train) [114][ 320/2569] lr: 4.0000e-03 eta: 7:00:02 time: 0.2669 data_time: 0.0071 memory: 5828 grad_norm: 4.1399 loss: 1.7931 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7931 2023/06/05 14:04:51 - mmengine - INFO - Epoch(train) [114][ 340/2569] lr: 4.0000e-03 eta: 6:59:57 time: 0.2676 data_time: 0.0069 memory: 5828 grad_norm: 4.1864 loss: 1.8172 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8172 2023/06/05 14:04:56 - mmengine - INFO - Epoch(train) [114][ 360/2569] lr: 4.0000e-03 eta: 6:59:52 time: 0.2610 data_time: 0.0070 memory: 5828 grad_norm: 4.1226 loss: 1.6890 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6890 2023/06/05 14:05:02 - mmengine - INFO - Epoch(train) [114][ 380/2569] lr: 4.0000e-03 eta: 6:59:46 time: 0.2655 data_time: 0.0074 memory: 5828 grad_norm: 4.1190 loss: 2.1564 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1564 2023/06/05 14:05:07 - mmengine - INFO - Epoch(train) [114][ 400/2569] lr: 4.0000e-03 eta: 6:59:41 time: 0.2618 data_time: 0.0071 memory: 5828 grad_norm: 4.2164 loss: 1.6749 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6749 2023/06/05 14:05:12 - mmengine - INFO - Epoch(train) [114][ 420/2569] lr: 4.0000e-03 eta: 6:59:35 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 4.2261 loss: 2.0647 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0647 2023/06/05 14:05:18 - mmengine - INFO - Epoch(train) [114][ 440/2569] lr: 4.0000e-03 eta: 6:59:30 time: 0.2623 data_time: 0.0071 memory: 5828 grad_norm: 4.1794 loss: 2.0817 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0817 2023/06/05 14:05:23 - mmengine - INFO - Epoch(train) [114][ 460/2569] lr: 4.0000e-03 eta: 6:59:25 time: 0.2724 data_time: 0.0070 memory: 5828 grad_norm: 4.1475 loss: 1.9409 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9409 2023/06/05 14:05:28 - mmengine - INFO - Epoch(train) [114][ 480/2569] lr: 4.0000e-03 eta: 6:59:20 time: 0.2640 data_time: 0.0070 memory: 5828 grad_norm: 4.1222 loss: 1.8520 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8520 2023/06/05 14:05:34 - mmengine - INFO - Epoch(train) [114][ 500/2569] lr: 4.0000e-03 eta: 6:59:14 time: 0.2675 data_time: 0.0070 memory: 5828 grad_norm: 4.1113 loss: 1.9027 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9027 2023/06/05 14:05:39 - mmengine - INFO - Epoch(train) [114][ 520/2569] lr: 4.0000e-03 eta: 6:59:09 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 4.2255 loss: 2.1978 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1978 2023/06/05 14:05:44 - mmengine - INFO - Epoch(train) [114][ 540/2569] lr: 4.0000e-03 eta: 6:59:04 time: 0.2704 data_time: 0.0071 memory: 5828 grad_norm: 4.2210 loss: 1.7571 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7571 2023/06/05 14:05:50 - mmengine - INFO - Epoch(train) [114][ 560/2569] lr: 4.0000e-03 eta: 6:58:58 time: 0.2672 data_time: 0.0072 memory: 5828 grad_norm: 4.2373 loss: 2.0356 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0356 2023/06/05 14:05:55 - mmengine - INFO - Epoch(train) [114][ 580/2569] lr: 4.0000e-03 eta: 6:58:53 time: 0.2697 data_time: 0.0069 memory: 5828 grad_norm: 4.1701 loss: 1.7332 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7332 2023/06/05 14:06:00 - mmengine - INFO - Epoch(train) [114][ 600/2569] lr: 4.0000e-03 eta: 6:58:48 time: 0.2612 data_time: 0.0070 memory: 5828 grad_norm: 4.2039 loss: 2.0447 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0447 2023/06/05 14:06:06 - mmengine - INFO - Epoch(train) [114][ 620/2569] lr: 4.0000e-03 eta: 6:58:42 time: 0.2678 data_time: 0.0070 memory: 5828 grad_norm: 4.2307 loss: 1.8303 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8303 2023/06/05 14:06:11 - mmengine - INFO - Epoch(train) [114][ 640/2569] lr: 4.0000e-03 eta: 6:58:37 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 4.1646 loss: 1.9463 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9463 2023/06/05 14:06:16 - mmengine - INFO - Epoch(train) [114][ 660/2569] lr: 4.0000e-03 eta: 6:58:32 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 4.1401 loss: 1.8093 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8093 2023/06/05 14:06:22 - mmengine - INFO - Epoch(train) [114][ 680/2569] lr: 4.0000e-03 eta: 6:58:26 time: 0.2745 data_time: 0.0070 memory: 5828 grad_norm: 4.2562 loss: 1.8449 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.8449 2023/06/05 14:06:27 - mmengine - INFO - Epoch(train) [114][ 700/2569] lr: 4.0000e-03 eta: 6:58:21 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 4.1904 loss: 1.6946 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6946 2023/06/05 14:06:28 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:06:33 - mmengine - INFO - Epoch(train) [114][ 720/2569] lr: 4.0000e-03 eta: 6:58:16 time: 0.2737 data_time: 0.0069 memory: 5828 grad_norm: 4.1719 loss: 1.5606 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5606 2023/06/05 14:06:38 - mmengine - INFO - Epoch(train) [114][ 740/2569] lr: 4.0000e-03 eta: 6:58:10 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 4.1572 loss: 1.8480 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8480 2023/06/05 14:06:43 - mmengine - INFO - Epoch(train) [114][ 760/2569] lr: 4.0000e-03 eta: 6:58:05 time: 0.2739 data_time: 0.0070 memory: 5828 grad_norm: 4.1314 loss: 1.8160 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8160 2023/06/05 14:06:49 - mmengine - INFO - Epoch(train) [114][ 780/2569] lr: 4.0000e-03 eta: 6:58:00 time: 0.2651 data_time: 0.0072 memory: 5828 grad_norm: 4.2206 loss: 2.0458 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0458 2023/06/05 14:06:54 - mmengine - INFO - Epoch(train) [114][ 800/2569] lr: 4.0000e-03 eta: 6:57:55 time: 0.2729 data_time: 0.0073 memory: 5828 grad_norm: 4.1580 loss: 1.7027 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7027 2023/06/05 14:06:59 - mmengine - INFO - Epoch(train) [114][ 820/2569] lr: 4.0000e-03 eta: 6:57:49 time: 0.2641 data_time: 0.0071 memory: 5828 grad_norm: 4.2161 loss: 1.7899 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7899 2023/06/05 14:07:05 - mmengine - INFO - Epoch(train) [114][ 840/2569] lr: 4.0000e-03 eta: 6:57:44 time: 0.2651 data_time: 0.0071 memory: 5828 grad_norm: 4.1556 loss: 1.6400 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6400 2023/06/05 14:07:10 - mmengine - INFO - Epoch(train) [114][ 860/2569] lr: 4.0000e-03 eta: 6:57:39 time: 0.2610 data_time: 0.0072 memory: 5828 grad_norm: 4.1665 loss: 1.6371 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6371 2023/06/05 14:07:15 - mmengine - INFO - Epoch(train) [114][ 880/2569] lr: 4.0000e-03 eta: 6:57:33 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 4.1802 loss: 1.8642 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8642 2023/06/05 14:07:21 - mmengine - INFO - Epoch(train) [114][ 900/2569] lr: 4.0000e-03 eta: 6:57:28 time: 0.2604 data_time: 0.0068 memory: 5828 grad_norm: 4.2003 loss: 1.6988 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6988 2023/06/05 14:07:26 - mmengine - INFO - Epoch(train) [114][ 920/2569] lr: 4.0000e-03 eta: 6:57:23 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 4.1588 loss: 1.8465 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8465 2023/06/05 14:07:31 - mmengine - INFO - Epoch(train) [114][ 940/2569] lr: 4.0000e-03 eta: 6:57:17 time: 0.2605 data_time: 0.0071 memory: 5828 grad_norm: 4.2554 loss: 1.9901 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9901 2023/06/05 14:07:36 - mmengine - INFO - Epoch(train) [114][ 960/2569] lr: 4.0000e-03 eta: 6:57:12 time: 0.2687 data_time: 0.0072 memory: 5828 grad_norm: 4.2371 loss: 2.2600 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2600 2023/06/05 14:07:42 - mmengine - INFO - Epoch(train) [114][ 980/2569] lr: 4.0000e-03 eta: 6:57:07 time: 0.2669 data_time: 0.0070 memory: 5828 grad_norm: 4.2918 loss: 1.7293 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7293 2023/06/05 14:07:47 - mmengine - INFO - Epoch(train) [114][1000/2569] lr: 4.0000e-03 eta: 6:57:01 time: 0.2748 data_time: 0.0071 memory: 5828 grad_norm: 4.1552 loss: 1.7777 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7777 2023/06/05 14:07:52 - mmengine - INFO - Epoch(train) [114][1020/2569] lr: 4.0000e-03 eta: 6:56:56 time: 0.2615 data_time: 0.0071 memory: 5828 grad_norm: 4.2873 loss: 1.7087 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7087 2023/06/05 14:07:58 - mmengine - INFO - Epoch(train) [114][1040/2569] lr: 4.0000e-03 eta: 6:56:51 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 4.1623 loss: 2.0449 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0449 2023/06/05 14:08:03 - mmengine - INFO - Epoch(train) [114][1060/2569] lr: 4.0000e-03 eta: 6:56:45 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 4.0798 loss: 1.7550 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7550 2023/06/05 14:08:09 - mmengine - INFO - Epoch(train) [114][1080/2569] lr: 4.0000e-03 eta: 6:56:40 time: 0.2729 data_time: 0.0071 memory: 5828 grad_norm: 4.1010 loss: 1.7941 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7941 2023/06/05 14:08:14 - mmengine - INFO - Epoch(train) [114][1100/2569] lr: 4.0000e-03 eta: 6:56:35 time: 0.2724 data_time: 0.0070 memory: 5828 grad_norm: 4.2524 loss: 1.7271 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7271 2023/06/05 14:08:19 - mmengine - INFO - Epoch(train) [114][1120/2569] lr: 4.0000e-03 eta: 6:56:29 time: 0.2623 data_time: 0.0076 memory: 5828 grad_norm: 4.2509 loss: 1.9746 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.9746 2023/06/05 14:08:25 - mmengine - INFO - Epoch(train) [114][1140/2569] lr: 4.0000e-03 eta: 6:56:24 time: 0.2686 data_time: 0.0076 memory: 5828 grad_norm: 4.1416 loss: 1.9696 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9696 2023/06/05 14:08:30 - mmengine - INFO - Epoch(train) [114][1160/2569] lr: 4.0000e-03 eta: 6:56:19 time: 0.2615 data_time: 0.0071 memory: 5828 grad_norm: 4.1612 loss: 1.6546 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6546 2023/06/05 14:08:35 - mmengine - INFO - Epoch(train) [114][1180/2569] lr: 4.0000e-03 eta: 6:56:13 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 4.2004 loss: 1.9961 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9961 2023/06/05 14:08:41 - mmengine - INFO - Epoch(train) [114][1200/2569] lr: 4.0000e-03 eta: 6:56:08 time: 0.2734 data_time: 0.0071 memory: 5828 grad_norm: 4.1749 loss: 1.6815 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6815 2023/06/05 14:08:46 - mmengine - INFO - Epoch(train) [114][1220/2569] lr: 4.0000e-03 eta: 6:56:03 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 4.2165 loss: 1.6020 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6020 2023/06/05 14:08:51 - mmengine - INFO - Epoch(train) [114][1240/2569] lr: 4.0000e-03 eta: 6:55:58 time: 0.2753 data_time: 0.0075 memory: 5828 grad_norm: 4.2576 loss: 1.4814 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4814 2023/06/05 14:08:57 - mmengine - INFO - Epoch(train) [114][1260/2569] lr: 4.0000e-03 eta: 6:55:52 time: 0.2785 data_time: 0.0077 memory: 5828 grad_norm: 4.2310 loss: 1.8418 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8418 2023/06/05 14:09:02 - mmengine - INFO - Epoch(train) [114][1280/2569] lr: 4.0000e-03 eta: 6:55:47 time: 0.2613 data_time: 0.0071 memory: 5828 grad_norm: 4.1565 loss: 2.0448 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0448 2023/06/05 14:09:08 - mmengine - INFO - Epoch(train) [114][1300/2569] lr: 4.0000e-03 eta: 6:55:42 time: 0.2670 data_time: 0.0071 memory: 5828 grad_norm: 4.2269 loss: 2.0607 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0607 2023/06/05 14:09:13 - mmengine - INFO - Epoch(train) [114][1320/2569] lr: 4.0000e-03 eta: 6:55:36 time: 0.2659 data_time: 0.0079 memory: 5828 grad_norm: 4.1413 loss: 1.6622 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6622 2023/06/05 14:09:18 - mmengine - INFO - Epoch(train) [114][1340/2569] lr: 4.0000e-03 eta: 6:55:31 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 4.1795 loss: 2.1687 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1687 2023/06/05 14:09:24 - mmengine - INFO - Epoch(train) [114][1360/2569] lr: 4.0000e-03 eta: 6:55:26 time: 0.2669 data_time: 0.0072 memory: 5828 grad_norm: 4.2724 loss: 1.7589 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7589 2023/06/05 14:09:29 - mmengine - INFO - Epoch(train) [114][1380/2569] lr: 4.0000e-03 eta: 6:55:20 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 4.1535 loss: 1.7358 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7358 2023/06/05 14:09:34 - mmengine - INFO - Epoch(train) [114][1400/2569] lr: 4.0000e-03 eta: 6:55:15 time: 0.2618 data_time: 0.0070 memory: 5828 grad_norm: 4.1882 loss: 1.9397 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9397 2023/06/05 14:09:40 - mmengine - INFO - Epoch(train) [114][1420/2569] lr: 4.0000e-03 eta: 6:55:10 time: 0.2723 data_time: 0.0073 memory: 5828 grad_norm: 4.2040 loss: 1.7735 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7735 2023/06/05 14:09:45 - mmengine - INFO - Epoch(train) [114][1440/2569] lr: 4.0000e-03 eta: 6:55:04 time: 0.2594 data_time: 0.0075 memory: 5828 grad_norm: 4.1940 loss: 1.9418 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9418 2023/06/05 14:09:50 - mmengine - INFO - Epoch(train) [114][1460/2569] lr: 4.0000e-03 eta: 6:54:59 time: 0.2763 data_time: 0.0071 memory: 5828 grad_norm: 4.1760 loss: 1.8006 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8006 2023/06/05 14:09:56 - mmengine - INFO - Epoch(train) [114][1480/2569] lr: 4.0000e-03 eta: 6:54:54 time: 0.2664 data_time: 0.0071 memory: 5828 grad_norm: 4.1635 loss: 1.7274 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7274 2023/06/05 14:10:01 - mmengine - INFO - Epoch(train) [114][1500/2569] lr: 4.0000e-03 eta: 6:54:48 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 4.1593 loss: 1.8078 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8078 2023/06/05 14:10:06 - mmengine - INFO - Epoch(train) [114][1520/2569] lr: 4.0000e-03 eta: 6:54:43 time: 0.2709 data_time: 0.0082 memory: 5828 grad_norm: 4.1854 loss: 1.7997 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7997 2023/06/05 14:10:12 - mmengine - INFO - Epoch(train) [114][1540/2569] lr: 4.0000e-03 eta: 6:54:38 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 4.1914 loss: 2.1002 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1002 2023/06/05 14:10:17 - mmengine - INFO - Epoch(train) [114][1560/2569] lr: 4.0000e-03 eta: 6:54:33 time: 0.2745 data_time: 0.0071 memory: 5828 grad_norm: 4.3423 loss: 2.0694 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0694 2023/06/05 14:10:23 - mmengine - INFO - Epoch(train) [114][1580/2569] lr: 4.0000e-03 eta: 6:54:27 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 4.2293 loss: 1.6351 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6351 2023/06/05 14:10:28 - mmengine - INFO - Epoch(train) [114][1600/2569] lr: 4.0000e-03 eta: 6:54:22 time: 0.2659 data_time: 0.0072 memory: 5828 grad_norm: 4.2478 loss: 1.6738 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6738 2023/06/05 14:10:33 - mmengine - INFO - Epoch(train) [114][1620/2569] lr: 4.0000e-03 eta: 6:54:17 time: 0.2662 data_time: 0.0074 memory: 5828 grad_norm: 4.1756 loss: 2.1859 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1859 2023/06/05 14:10:38 - mmengine - INFO - Epoch(train) [114][1640/2569] lr: 4.0000e-03 eta: 6:54:11 time: 0.2611 data_time: 0.0070 memory: 5828 grad_norm: 4.2377 loss: 1.6606 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6606 2023/06/05 14:10:44 - mmengine - INFO - Epoch(train) [114][1660/2569] lr: 4.0000e-03 eta: 6:54:06 time: 0.2615 data_time: 0.0074 memory: 5828 grad_norm: 4.1473 loss: 1.9025 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9025 2023/06/05 14:10:49 - mmengine - INFO - Epoch(train) [114][1680/2569] lr: 4.0000e-03 eta: 6:54:01 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 4.3202 loss: 1.8713 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8713 2023/06/05 14:10:54 - mmengine - INFO - Epoch(train) [114][1700/2569] lr: 4.0000e-03 eta: 6:53:55 time: 0.2723 data_time: 0.0079 memory: 5828 grad_norm: 4.1777 loss: 1.7458 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7458 2023/06/05 14:10:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:11:00 - mmengine - INFO - Epoch(train) [114][1720/2569] lr: 4.0000e-03 eta: 6:53:50 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 4.1503 loss: 1.7330 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7330 2023/06/05 14:11:05 - mmengine - INFO - Epoch(train) [114][1740/2569] lr: 4.0000e-03 eta: 6:53:45 time: 0.2849 data_time: 0.0072 memory: 5828 grad_norm: 4.1462 loss: 1.8471 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8471 2023/06/05 14:11:11 - mmengine - INFO - Epoch(train) [114][1760/2569] lr: 4.0000e-03 eta: 6:53:39 time: 0.2594 data_time: 0.0075 memory: 5828 grad_norm: 4.1993 loss: 2.1579 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1579 2023/06/05 14:11:16 - mmengine - INFO - Epoch(train) [114][1780/2569] lr: 4.0000e-03 eta: 6:53:34 time: 0.2681 data_time: 0.0074 memory: 5828 grad_norm: 4.2479 loss: 1.9139 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9139 2023/06/05 14:11:22 - mmengine - INFO - Epoch(train) [114][1800/2569] lr: 4.0000e-03 eta: 6:53:29 time: 0.2744 data_time: 0.0069 memory: 5828 grad_norm: 4.0783 loss: 1.7759 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7759 2023/06/05 14:11:27 - mmengine - INFO - Epoch(train) [114][1820/2569] lr: 4.0000e-03 eta: 6:53:24 time: 0.2704 data_time: 0.0071 memory: 5828 grad_norm: 4.3153 loss: 1.9815 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9815 2023/06/05 14:11:32 - mmengine - INFO - Epoch(train) [114][1840/2569] lr: 4.0000e-03 eta: 6:53:18 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 4.1105 loss: 1.6667 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6667 2023/06/05 14:11:38 - mmengine - INFO - Epoch(train) [114][1860/2569] lr: 4.0000e-03 eta: 6:53:13 time: 0.2720 data_time: 0.0073 memory: 5828 grad_norm: 4.2483 loss: 1.7736 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7736 2023/06/05 14:11:43 - mmengine - INFO - Epoch(train) [114][1880/2569] lr: 4.0000e-03 eta: 6:53:08 time: 0.2683 data_time: 0.0076 memory: 5828 grad_norm: 4.1999 loss: 1.3921 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3921 2023/06/05 14:11:49 - mmengine - INFO - Epoch(train) [114][1900/2569] lr: 4.0000e-03 eta: 6:53:02 time: 0.2755 data_time: 0.0072 memory: 5828 grad_norm: 4.1856 loss: 1.9428 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9428 2023/06/05 14:11:54 - mmengine - INFO - Epoch(train) [114][1920/2569] lr: 4.0000e-03 eta: 6:52:57 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 4.2191 loss: 2.0374 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0374 2023/06/05 14:11:59 - mmengine - INFO - Epoch(train) [114][1940/2569] lr: 4.0000e-03 eta: 6:52:52 time: 0.2710 data_time: 0.0071 memory: 5828 grad_norm: 4.2010 loss: 1.7045 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7045 2023/06/05 14:12:05 - mmengine - INFO - Epoch(train) [114][1960/2569] lr: 4.0000e-03 eta: 6:52:46 time: 0.2700 data_time: 0.0072 memory: 5828 grad_norm: 4.1706 loss: 1.8351 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8351 2023/06/05 14:12:10 - mmengine - INFO - Epoch(train) [114][1980/2569] lr: 4.0000e-03 eta: 6:52:41 time: 0.2761 data_time: 0.0072 memory: 5828 grad_norm: 4.1076 loss: 1.6291 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6291 2023/06/05 14:12:16 - mmengine - INFO - Epoch(train) [114][2000/2569] lr: 4.0000e-03 eta: 6:52:36 time: 0.2725 data_time: 0.0081 memory: 5828 grad_norm: 4.1498 loss: 1.8737 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8737 2023/06/05 14:12:21 - mmengine - INFO - Epoch(train) [114][2020/2569] lr: 4.0000e-03 eta: 6:52:31 time: 0.2694 data_time: 0.0081 memory: 5828 grad_norm: 4.2203 loss: 1.7693 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7693 2023/06/05 14:12:26 - mmengine - INFO - Epoch(train) [114][2040/2569] lr: 4.0000e-03 eta: 6:52:25 time: 0.2622 data_time: 0.0076 memory: 5828 grad_norm: 4.3161 loss: 1.7438 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7438 2023/06/05 14:12:32 - mmengine - INFO - Epoch(train) [114][2060/2569] lr: 4.0000e-03 eta: 6:52:20 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 4.2218 loss: 1.6421 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6421 2023/06/05 14:12:37 - mmengine - INFO - Epoch(train) [114][2080/2569] lr: 4.0000e-03 eta: 6:52:15 time: 0.2623 data_time: 0.0071 memory: 5828 grad_norm: 4.1721 loss: 1.7887 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7887 2023/06/05 14:12:42 - mmengine - INFO - Epoch(train) [114][2100/2569] lr: 4.0000e-03 eta: 6:52:09 time: 0.2665 data_time: 0.0075 memory: 5828 grad_norm: 4.1493 loss: 1.4578 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4578 2023/06/05 14:12:48 - mmengine - INFO - Epoch(train) [114][2120/2569] lr: 4.0000e-03 eta: 6:52:04 time: 0.2745 data_time: 0.0075 memory: 5828 grad_norm: 4.2060 loss: 1.8022 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8022 2023/06/05 14:12:53 - mmengine - INFO - Epoch(train) [114][2140/2569] lr: 4.0000e-03 eta: 6:51:59 time: 0.2614 data_time: 0.0070 memory: 5828 grad_norm: 4.1245 loss: 1.6807 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6807 2023/06/05 14:12:58 - mmengine - INFO - Epoch(train) [114][2160/2569] lr: 4.0000e-03 eta: 6:51:53 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 4.2169 loss: 1.8883 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8883 2023/06/05 14:13:04 - mmengine - INFO - Epoch(train) [114][2180/2569] lr: 4.0000e-03 eta: 6:51:48 time: 0.2601 data_time: 0.0071 memory: 5828 grad_norm: 4.1905 loss: 1.7281 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7281 2023/06/05 14:13:09 - mmengine - INFO - Epoch(train) [114][2200/2569] lr: 4.0000e-03 eta: 6:51:43 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 4.1913 loss: 2.0764 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0764 2023/06/05 14:13:14 - mmengine - INFO - Epoch(train) [114][2220/2569] lr: 4.0000e-03 eta: 6:51:37 time: 0.2642 data_time: 0.0072 memory: 5828 grad_norm: 4.3139 loss: 1.9456 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.9456 2023/06/05 14:13:20 - mmengine - INFO - Epoch(train) [114][2240/2569] lr: 4.0000e-03 eta: 6:51:32 time: 0.2655 data_time: 0.0071 memory: 5828 grad_norm: 4.2217 loss: 1.9754 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9754 2023/06/05 14:13:25 - mmengine - INFO - Epoch(train) [114][2260/2569] lr: 4.0000e-03 eta: 6:51:27 time: 0.2783 data_time: 0.0071 memory: 5828 grad_norm: 4.2282 loss: 1.6729 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6729 2023/06/05 14:13:31 - mmengine - INFO - Epoch(train) [114][2280/2569] lr: 4.0000e-03 eta: 6:51:21 time: 0.2702 data_time: 0.0073 memory: 5828 grad_norm: 4.2620 loss: 1.8224 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8224 2023/06/05 14:13:36 - mmengine - INFO - Epoch(train) [114][2300/2569] lr: 4.0000e-03 eta: 6:51:16 time: 0.2823 data_time: 0.0071 memory: 5828 grad_norm: 4.2869 loss: 1.9589 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.9589 2023/06/05 14:13:42 - mmengine - INFO - Epoch(train) [114][2320/2569] lr: 4.0000e-03 eta: 6:51:11 time: 0.2676 data_time: 0.0078 memory: 5828 grad_norm: 4.1177 loss: 1.9509 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9509 2023/06/05 14:13:47 - mmengine - INFO - Epoch(train) [114][2340/2569] lr: 4.0000e-03 eta: 6:51:06 time: 0.2784 data_time: 0.0069 memory: 5828 grad_norm: 4.2329 loss: 1.8865 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8865 2023/06/05 14:13:53 - mmengine - INFO - Epoch(train) [114][2360/2569] lr: 4.0000e-03 eta: 6:51:00 time: 0.2756 data_time: 0.0069 memory: 5828 grad_norm: 4.2491 loss: 1.8811 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8811 2023/06/05 14:13:58 - mmengine - INFO - Epoch(train) [114][2380/2569] lr: 4.0000e-03 eta: 6:50:55 time: 0.2743 data_time: 0.0070 memory: 5828 grad_norm: 4.2035 loss: 1.6348 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6348 2023/06/05 14:14:04 - mmengine - INFO - Epoch(train) [114][2400/2569] lr: 4.0000e-03 eta: 6:50:50 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 4.1791 loss: 1.6790 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6790 2023/06/05 14:14:09 - mmengine - INFO - Epoch(train) [114][2420/2569] lr: 4.0000e-03 eta: 6:50:45 time: 0.2680 data_time: 0.0072 memory: 5828 grad_norm: 4.1669 loss: 1.9986 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9986 2023/06/05 14:14:14 - mmengine - INFO - Epoch(train) [114][2440/2569] lr: 4.0000e-03 eta: 6:50:39 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 4.1945 loss: 1.9369 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9369 2023/06/05 14:14:20 - mmengine - INFO - Epoch(train) [114][2460/2569] lr: 4.0000e-03 eta: 6:50:34 time: 0.2791 data_time: 0.0076 memory: 5828 grad_norm: 4.2645 loss: 1.8957 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8957 2023/06/05 14:14:25 - mmengine - INFO - Epoch(train) [114][2480/2569] lr: 4.0000e-03 eta: 6:50:29 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 4.2409 loss: 2.0241 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0241 2023/06/05 14:14:31 - mmengine - INFO - Epoch(train) [114][2500/2569] lr: 4.0000e-03 eta: 6:50:23 time: 0.2713 data_time: 0.0069 memory: 5828 grad_norm: 4.2101 loss: 1.9828 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9828 2023/06/05 14:14:36 - mmengine - INFO - Epoch(train) [114][2520/2569] lr: 4.0000e-03 eta: 6:50:18 time: 0.2678 data_time: 0.0073 memory: 5828 grad_norm: 4.2482 loss: 1.9816 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9816 2023/06/05 14:14:41 - mmengine - INFO - Epoch(train) [114][2540/2569] lr: 4.0000e-03 eta: 6:50:13 time: 0.2663 data_time: 0.0073 memory: 5828 grad_norm: 4.3069 loss: 1.6482 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6482 2023/06/05 14:14:47 - mmengine - INFO - Epoch(train) [114][2560/2569] lr: 4.0000e-03 eta: 6:50:07 time: 0.2596 data_time: 0.0073 memory: 5828 grad_norm: 4.2288 loss: 1.7521 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7521 2023/06/05 14:14:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:14:49 - mmengine - INFO - Epoch(train) [114][2569/2569] lr: 4.0000e-03 eta: 6:50:05 time: 0.2565 data_time: 0.0070 memory: 5828 grad_norm: 4.2411 loss: 1.7026 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.7026 2023/06/05 14:14:56 - mmengine - INFO - Epoch(train) [115][ 20/2569] lr: 4.0000e-03 eta: 6:50:00 time: 0.3455 data_time: 0.0551 memory: 5828 grad_norm: 4.2010 loss: 1.8525 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8525 2023/06/05 14:15:01 - mmengine - INFO - Epoch(train) [115][ 40/2569] lr: 4.0000e-03 eta: 6:49:55 time: 0.2613 data_time: 0.0072 memory: 5828 grad_norm: 4.1899 loss: 1.8505 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8505 2023/06/05 14:15:07 - mmengine - INFO - Epoch(train) [115][ 60/2569] lr: 4.0000e-03 eta: 6:49:50 time: 0.2771 data_time: 0.0074 memory: 5828 grad_norm: 4.2581 loss: 1.9233 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9233 2023/06/05 14:15:12 - mmengine - INFO - Epoch(train) [115][ 80/2569] lr: 4.0000e-03 eta: 6:49:44 time: 0.2601 data_time: 0.0073 memory: 5828 grad_norm: 4.1815 loss: 1.9254 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9254 2023/06/05 14:15:17 - mmengine - INFO - Epoch(train) [115][ 100/2569] lr: 4.0000e-03 eta: 6:49:39 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 4.1767 loss: 1.7758 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7758 2023/06/05 14:15:22 - mmengine - INFO - Epoch(train) [115][ 120/2569] lr: 4.0000e-03 eta: 6:49:34 time: 0.2664 data_time: 0.0072 memory: 5828 grad_norm: 4.2601 loss: 1.5843 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.5843 2023/06/05 14:15:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:15:28 - mmengine - INFO - Epoch(train) [115][ 140/2569] lr: 4.0000e-03 eta: 6:49:28 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 4.3119 loss: 1.8433 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8433 2023/06/05 14:15:33 - mmengine - INFO - Epoch(train) [115][ 160/2569] lr: 4.0000e-03 eta: 6:49:23 time: 0.2697 data_time: 0.0070 memory: 5828 grad_norm: 4.2645 loss: 1.9881 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9881 2023/06/05 14:15:38 - mmengine - INFO - Epoch(train) [115][ 180/2569] lr: 4.0000e-03 eta: 6:49:18 time: 0.2698 data_time: 0.0072 memory: 5828 grad_norm: 4.2579 loss: 2.0998 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0998 2023/06/05 14:15:44 - mmengine - INFO - Epoch(train) [115][ 200/2569] lr: 4.0000e-03 eta: 6:49:12 time: 0.2823 data_time: 0.0076 memory: 5828 grad_norm: 4.1611 loss: 1.9251 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9251 2023/06/05 14:15:49 - mmengine - INFO - Epoch(train) [115][ 220/2569] lr: 4.0000e-03 eta: 6:49:07 time: 0.2688 data_time: 0.0069 memory: 5828 grad_norm: 4.1751 loss: 1.6988 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6988 2023/06/05 14:15:55 - mmengine - INFO - Epoch(train) [115][ 240/2569] lr: 4.0000e-03 eta: 6:49:02 time: 0.2727 data_time: 0.0077 memory: 5828 grad_norm: 4.2187 loss: 1.7276 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7276 2023/06/05 14:16:00 - mmengine - INFO - Epoch(train) [115][ 260/2569] lr: 4.0000e-03 eta: 6:48:56 time: 0.2604 data_time: 0.0072 memory: 5828 grad_norm: 4.1927 loss: 1.8979 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8979 2023/06/05 14:16:06 - mmengine - INFO - Epoch(train) [115][ 280/2569] lr: 4.0000e-03 eta: 6:48:51 time: 0.2717 data_time: 0.0075 memory: 5828 grad_norm: 4.1515 loss: 2.1060 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1060 2023/06/05 14:16:11 - mmengine - INFO - Epoch(train) [115][ 300/2569] lr: 4.0000e-03 eta: 6:48:46 time: 0.2661 data_time: 0.0071 memory: 5828 grad_norm: 4.1785 loss: 1.8151 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8151 2023/06/05 14:16:16 - mmengine - INFO - Epoch(train) [115][ 320/2569] lr: 4.0000e-03 eta: 6:48:41 time: 0.2713 data_time: 0.0071 memory: 5828 grad_norm: 4.2508 loss: 1.8639 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8639 2023/06/05 14:16:22 - mmengine - INFO - Epoch(train) [115][ 340/2569] lr: 4.0000e-03 eta: 6:48:35 time: 0.2726 data_time: 0.0072 memory: 5828 grad_norm: 4.1868 loss: 1.7074 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7074 2023/06/05 14:16:27 - mmengine - INFO - Epoch(train) [115][ 360/2569] lr: 4.0000e-03 eta: 6:48:30 time: 0.2666 data_time: 0.0075 memory: 5828 grad_norm: 4.2370 loss: 1.7669 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7669 2023/06/05 14:16:33 - mmengine - INFO - Epoch(train) [115][ 380/2569] lr: 4.0000e-03 eta: 6:48:25 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 4.2351 loss: 1.8628 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8628 2023/06/05 14:16:38 - mmengine - INFO - Epoch(train) [115][ 400/2569] lr: 4.0000e-03 eta: 6:48:19 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 4.1708 loss: 1.8848 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8848 2023/06/05 14:16:43 - mmengine - INFO - Epoch(train) [115][ 420/2569] lr: 4.0000e-03 eta: 6:48:14 time: 0.2605 data_time: 0.0070 memory: 5828 grad_norm: 4.1770 loss: 1.6263 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6263 2023/06/05 14:16:48 - mmengine - INFO - Epoch(train) [115][ 440/2569] lr: 4.0000e-03 eta: 6:48:09 time: 0.2643 data_time: 0.0071 memory: 5828 grad_norm: 4.2315 loss: 2.1850 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1850 2023/06/05 14:16:54 - mmengine - INFO - Epoch(train) [115][ 460/2569] lr: 4.0000e-03 eta: 6:48:03 time: 0.2671 data_time: 0.0071 memory: 5828 grad_norm: 4.2485 loss: 1.9537 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9537 2023/06/05 14:16:59 - mmengine - INFO - Epoch(train) [115][ 480/2569] lr: 4.0000e-03 eta: 6:47:58 time: 0.2709 data_time: 0.0072 memory: 5828 grad_norm: 4.2051 loss: 1.8418 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8418 2023/06/05 14:17:04 - mmengine - INFO - Epoch(train) [115][ 500/2569] lr: 4.0000e-03 eta: 6:47:53 time: 0.2604 data_time: 0.0075 memory: 5828 grad_norm: 4.2081 loss: 1.9331 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9331 2023/06/05 14:17:10 - mmengine - INFO - Epoch(train) [115][ 520/2569] lr: 4.0000e-03 eta: 6:47:47 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 4.2715 loss: 1.9985 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9985 2023/06/05 14:17:15 - mmengine - INFO - Epoch(train) [115][ 540/2569] lr: 4.0000e-03 eta: 6:47:42 time: 0.2613 data_time: 0.0073 memory: 5828 grad_norm: 4.1588 loss: 1.6424 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6424 2023/06/05 14:17:20 - mmengine - INFO - Epoch(train) [115][ 560/2569] lr: 4.0000e-03 eta: 6:47:37 time: 0.2716 data_time: 0.0074 memory: 5828 grad_norm: 4.2974 loss: 2.0460 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0460 2023/06/05 14:17:25 - mmengine - INFO - Epoch(train) [115][ 580/2569] lr: 4.0000e-03 eta: 6:47:31 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 4.2365 loss: 1.7865 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7865 2023/06/05 14:17:31 - mmengine - INFO - Epoch(train) [115][ 600/2569] lr: 4.0000e-03 eta: 6:47:26 time: 0.2703 data_time: 0.0071 memory: 5828 grad_norm: 4.2581 loss: 1.6401 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6401 2023/06/05 14:17:36 - mmengine - INFO - Epoch(train) [115][ 620/2569] lr: 4.0000e-03 eta: 6:47:21 time: 0.2749 data_time: 0.0080 memory: 5828 grad_norm: 4.2346 loss: 1.7707 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7707 2023/06/05 14:17:42 - mmengine - INFO - Epoch(train) [115][ 640/2569] lr: 4.0000e-03 eta: 6:47:15 time: 0.2754 data_time: 0.0073 memory: 5828 grad_norm: 4.3071 loss: 1.8408 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8408 2023/06/05 14:17:47 - mmengine - INFO - Epoch(train) [115][ 660/2569] lr: 4.0000e-03 eta: 6:47:10 time: 0.2687 data_time: 0.0074 memory: 5828 grad_norm: 4.2270 loss: 1.9559 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9559 2023/06/05 14:17:53 - mmengine - INFO - Epoch(train) [115][ 680/2569] lr: 4.0000e-03 eta: 6:47:05 time: 0.2769 data_time: 0.0072 memory: 5828 grad_norm: 4.1542 loss: 1.8304 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8304 2023/06/05 14:17:58 - mmengine - INFO - Epoch(train) [115][ 700/2569] lr: 4.0000e-03 eta: 6:47:00 time: 0.2681 data_time: 0.0073 memory: 5828 grad_norm: 4.2364 loss: 1.7978 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7978 2023/06/05 14:18:04 - mmengine - INFO - Epoch(train) [115][ 720/2569] lr: 4.0000e-03 eta: 6:46:54 time: 0.2714 data_time: 0.0070 memory: 5828 grad_norm: 4.1931 loss: 2.0286 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0286 2023/06/05 14:18:09 - mmengine - INFO - Epoch(train) [115][ 740/2569] lr: 4.0000e-03 eta: 6:46:49 time: 0.2734 data_time: 0.0071 memory: 5828 grad_norm: 4.3736 loss: 1.7072 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7072 2023/06/05 14:18:14 - mmengine - INFO - Epoch(train) [115][ 760/2569] lr: 4.0000e-03 eta: 6:46:44 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 4.3197 loss: 1.6945 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.6945 2023/06/05 14:18:20 - mmengine - INFO - Epoch(train) [115][ 780/2569] lr: 4.0000e-03 eta: 6:46:38 time: 0.2610 data_time: 0.0073 memory: 5828 grad_norm: 4.1490 loss: 1.9592 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9592 2023/06/05 14:18:25 - mmengine - INFO - Epoch(train) [115][ 800/2569] lr: 4.0000e-03 eta: 6:46:33 time: 0.2754 data_time: 0.0072 memory: 5828 grad_norm: 4.3475 loss: 1.7506 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7506 2023/06/05 14:18:30 - mmengine - INFO - Epoch(train) [115][ 820/2569] lr: 4.0000e-03 eta: 6:46:28 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 4.2593 loss: 1.8209 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8209 2023/06/05 14:18:36 - mmengine - INFO - Epoch(train) [115][ 840/2569] lr: 4.0000e-03 eta: 6:46:22 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 4.2773 loss: 1.9626 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9626 2023/06/05 14:18:41 - mmengine - INFO - Epoch(train) [115][ 860/2569] lr: 4.0000e-03 eta: 6:46:17 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 4.2344 loss: 1.9019 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9019 2023/06/05 14:18:46 - mmengine - INFO - Epoch(train) [115][ 880/2569] lr: 4.0000e-03 eta: 6:46:12 time: 0.2679 data_time: 0.0075 memory: 5828 grad_norm: 4.2580 loss: 1.7850 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7850 2023/06/05 14:18:52 - mmengine - INFO - Epoch(train) [115][ 900/2569] lr: 4.0000e-03 eta: 6:46:06 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 4.3079 loss: 1.7625 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7625 2023/06/05 14:18:57 - mmengine - INFO - Epoch(train) [115][ 920/2569] lr: 4.0000e-03 eta: 6:46:01 time: 0.2679 data_time: 0.0071 memory: 5828 grad_norm: 4.2431 loss: 1.7597 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.7597 2023/06/05 14:19:02 - mmengine - INFO - Epoch(train) [115][ 940/2569] lr: 4.0000e-03 eta: 6:45:56 time: 0.2644 data_time: 0.0071 memory: 5828 grad_norm: 4.3299 loss: 1.7888 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 1.7888 2023/06/05 14:19:08 - mmengine - INFO - Epoch(train) [115][ 960/2569] lr: 4.0000e-03 eta: 6:45:50 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 4.2287 loss: 1.8571 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.8571 2023/06/05 14:19:13 - mmengine - INFO - Epoch(train) [115][ 980/2569] lr: 4.0000e-03 eta: 6:45:45 time: 0.2692 data_time: 0.0071 memory: 5828 grad_norm: 4.2324 loss: 2.0388 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0388 2023/06/05 14:19:18 - mmengine - INFO - Epoch(train) [115][1000/2569] lr: 4.0000e-03 eta: 6:45:40 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 4.3180 loss: 1.7940 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7940 2023/06/05 14:19:24 - mmengine - INFO - Epoch(train) [115][1020/2569] lr: 4.0000e-03 eta: 6:45:34 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 4.2293 loss: 1.7686 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7686 2023/06/05 14:19:29 - mmengine - INFO - Epoch(train) [115][1040/2569] lr: 4.0000e-03 eta: 6:45:29 time: 0.2721 data_time: 0.0073 memory: 5828 grad_norm: 4.2116 loss: 1.9021 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9021 2023/06/05 14:19:34 - mmengine - INFO - Epoch(train) [115][1060/2569] lr: 4.0000e-03 eta: 6:45:24 time: 0.2623 data_time: 0.0071 memory: 5828 grad_norm: 4.2746 loss: 1.6364 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6364 2023/06/05 14:19:40 - mmengine - INFO - Epoch(train) [115][1080/2569] lr: 4.0000e-03 eta: 6:45:19 time: 0.2744 data_time: 0.0075 memory: 5828 grad_norm: 4.2353 loss: 1.6935 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6935 2023/06/05 14:19:45 - mmengine - INFO - Epoch(train) [115][1100/2569] lr: 4.0000e-03 eta: 6:45:13 time: 0.2604 data_time: 0.0075 memory: 5828 grad_norm: 4.2967 loss: 1.5810 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5810 2023/06/05 14:19:50 - mmengine - INFO - Epoch(train) [115][1120/2569] lr: 4.0000e-03 eta: 6:45:08 time: 0.2693 data_time: 0.0070 memory: 5828 grad_norm: 4.3764 loss: 1.7004 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7004 2023/06/05 14:19:54 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:19:56 - mmengine - INFO - Epoch(train) [115][1140/2569] lr: 4.0000e-03 eta: 6:45:03 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 4.3774 loss: 1.8281 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8281 2023/06/05 14:20:01 - mmengine - INFO - Epoch(train) [115][1160/2569] lr: 4.0000e-03 eta: 6:44:57 time: 0.2669 data_time: 0.0076 memory: 5828 grad_norm: 4.2075 loss: 1.8288 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8288 2023/06/05 14:20:06 - mmengine - INFO - Epoch(train) [115][1180/2569] lr: 4.0000e-03 eta: 6:44:52 time: 0.2685 data_time: 0.0074 memory: 5828 grad_norm: 4.2809 loss: 1.9610 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9610 2023/06/05 14:20:12 - mmengine - INFO - Epoch(train) [115][1200/2569] lr: 4.0000e-03 eta: 6:44:47 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 4.2008 loss: 1.9370 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.9370 2023/06/05 14:20:17 - mmengine - INFO - Epoch(train) [115][1220/2569] lr: 4.0000e-03 eta: 6:44:41 time: 0.2679 data_time: 0.0071 memory: 5828 grad_norm: 4.2683 loss: 2.0455 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0455 2023/06/05 14:20:22 - mmengine - INFO - Epoch(train) [115][1240/2569] lr: 4.0000e-03 eta: 6:44:36 time: 0.2663 data_time: 0.0072 memory: 5828 grad_norm: 4.2749 loss: 1.9965 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9965 2023/06/05 14:20:28 - mmengine - INFO - Epoch(train) [115][1260/2569] lr: 4.0000e-03 eta: 6:44:31 time: 0.2735 data_time: 0.0072 memory: 5828 grad_norm: 4.3129 loss: 1.5381 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5381 2023/06/05 14:20:33 - mmengine - INFO - Epoch(train) [115][1280/2569] lr: 4.0000e-03 eta: 6:44:25 time: 0.2670 data_time: 0.0071 memory: 5828 grad_norm: 4.3061 loss: 1.6391 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6391 2023/06/05 14:20:39 - mmengine - INFO - Epoch(train) [115][1300/2569] lr: 4.0000e-03 eta: 6:44:20 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 4.1994 loss: 1.7352 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7352 2023/06/05 14:20:44 - mmengine - INFO - Epoch(train) [115][1320/2569] lr: 4.0000e-03 eta: 6:44:15 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 4.2205 loss: 1.9349 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9349 2023/06/05 14:20:49 - mmengine - INFO - Epoch(train) [115][1340/2569] lr: 4.0000e-03 eta: 6:44:09 time: 0.2653 data_time: 0.0071 memory: 5828 grad_norm: 4.1763 loss: 1.8872 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8872 2023/06/05 14:20:55 - mmengine - INFO - Epoch(train) [115][1360/2569] lr: 4.0000e-03 eta: 6:44:04 time: 0.2637 data_time: 0.0076 memory: 5828 grad_norm: 4.2691 loss: 1.9108 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9108 2023/06/05 14:21:00 - mmengine - INFO - Epoch(train) [115][1380/2569] lr: 4.0000e-03 eta: 6:43:59 time: 0.2639 data_time: 0.0069 memory: 5828 grad_norm: 4.2144 loss: 1.8011 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8011 2023/06/05 14:21:05 - mmengine - INFO - Epoch(train) [115][1400/2569] lr: 4.0000e-03 eta: 6:43:53 time: 0.2609 data_time: 0.0070 memory: 5828 grad_norm: 4.3320 loss: 1.9183 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9183 2023/06/05 14:21:11 - mmengine - INFO - Epoch(train) [115][1420/2569] lr: 4.0000e-03 eta: 6:43:48 time: 0.2733 data_time: 0.0073 memory: 5828 grad_norm: 4.2260 loss: 1.9925 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9925 2023/06/05 14:21:16 - mmengine - INFO - Epoch(train) [115][1440/2569] lr: 4.0000e-03 eta: 6:43:43 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 4.2444 loss: 1.7845 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7845 2023/06/05 14:21:21 - mmengine - INFO - Epoch(train) [115][1460/2569] lr: 4.0000e-03 eta: 6:43:38 time: 0.2734 data_time: 0.0072 memory: 5828 grad_norm: 4.2375 loss: 1.7235 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7235 2023/06/05 14:21:27 - mmengine - INFO - Epoch(train) [115][1480/2569] lr: 4.0000e-03 eta: 6:43:32 time: 0.2733 data_time: 0.0074 memory: 5828 grad_norm: 4.3055 loss: 2.0294 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0294 2023/06/05 14:21:32 - mmengine - INFO - Epoch(train) [115][1500/2569] lr: 4.0000e-03 eta: 6:43:27 time: 0.2684 data_time: 0.0070 memory: 5828 grad_norm: 4.2974 loss: 1.8221 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8221 2023/06/05 14:21:38 - mmengine - INFO - Epoch(train) [115][1520/2569] lr: 4.0000e-03 eta: 6:43:22 time: 0.2884 data_time: 0.0071 memory: 5828 grad_norm: 4.3063 loss: 1.8518 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8518 2023/06/05 14:21:43 - mmengine - INFO - Epoch(train) [115][1540/2569] lr: 4.0000e-03 eta: 6:43:16 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 4.2235 loss: 2.1192 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1192 2023/06/05 14:21:49 - mmengine - INFO - Epoch(train) [115][1560/2569] lr: 4.0000e-03 eta: 6:43:11 time: 0.2695 data_time: 0.0070 memory: 5828 grad_norm: 4.2764 loss: 1.5555 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5555 2023/06/05 14:21:54 - mmengine - INFO - Epoch(train) [115][1580/2569] lr: 4.0000e-03 eta: 6:43:06 time: 0.2619 data_time: 0.0072 memory: 5828 grad_norm: 4.2336 loss: 1.4739 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4739 2023/06/05 14:22:00 - mmengine - INFO - Epoch(train) [115][1600/2569] lr: 4.0000e-03 eta: 6:43:01 time: 0.2801 data_time: 0.0072 memory: 5828 grad_norm: 4.2853 loss: 1.7082 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7082 2023/06/05 14:22:05 - mmengine - INFO - Epoch(train) [115][1620/2569] lr: 4.0000e-03 eta: 6:42:55 time: 0.2613 data_time: 0.0073 memory: 5828 grad_norm: 4.1855 loss: 1.9610 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9610 2023/06/05 14:22:10 - mmengine - INFO - Epoch(train) [115][1640/2569] lr: 4.0000e-03 eta: 6:42:50 time: 0.2718 data_time: 0.0073 memory: 5828 grad_norm: 4.2778 loss: 1.7810 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7810 2023/06/05 14:22:16 - mmengine - INFO - Epoch(train) [115][1660/2569] lr: 4.0000e-03 eta: 6:42:45 time: 0.2706 data_time: 0.0072 memory: 5828 grad_norm: 4.2169 loss: 1.8896 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8896 2023/06/05 14:22:21 - mmengine - INFO - Epoch(train) [115][1680/2569] lr: 4.0000e-03 eta: 6:42:39 time: 0.2674 data_time: 0.0070 memory: 5828 grad_norm: 4.2403 loss: 1.9224 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 1.9224 2023/06/05 14:22:26 - mmengine - INFO - Epoch(train) [115][1700/2569] lr: 4.0000e-03 eta: 6:42:34 time: 0.2659 data_time: 0.0070 memory: 5828 grad_norm: 4.2596 loss: 1.6657 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6657 2023/06/05 14:22:32 - mmengine - INFO - Epoch(train) [115][1720/2569] lr: 4.0000e-03 eta: 6:42:29 time: 0.2768 data_time: 0.0070 memory: 5828 grad_norm: 4.2393 loss: 1.9006 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9006 2023/06/05 14:22:37 - mmengine - INFO - Epoch(train) [115][1740/2569] lr: 4.0000e-03 eta: 6:42:23 time: 0.2652 data_time: 0.0070 memory: 5828 grad_norm: 4.2757 loss: 1.6807 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6807 2023/06/05 14:22:43 - mmengine - INFO - Epoch(train) [115][1760/2569] lr: 4.0000e-03 eta: 6:42:18 time: 0.2669 data_time: 0.0072 memory: 5828 grad_norm: 4.3327 loss: 1.6977 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6977 2023/06/05 14:22:48 - mmengine - INFO - Epoch(train) [115][1780/2569] lr: 4.0000e-03 eta: 6:42:13 time: 0.2740 data_time: 0.0071 memory: 5828 grad_norm: 4.1882 loss: 1.8120 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8120 2023/06/05 14:22:53 - mmengine - INFO - Epoch(train) [115][1800/2569] lr: 4.0000e-03 eta: 6:42:08 time: 0.2676 data_time: 0.0071 memory: 5828 grad_norm: 4.2449 loss: 1.5714 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5714 2023/06/05 14:22:59 - mmengine - INFO - Epoch(train) [115][1820/2569] lr: 4.0000e-03 eta: 6:42:02 time: 0.2719 data_time: 0.0070 memory: 5828 grad_norm: 4.1894 loss: 1.7230 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7230 2023/06/05 14:23:04 - mmengine - INFO - Epoch(train) [115][1840/2569] lr: 4.0000e-03 eta: 6:41:57 time: 0.2789 data_time: 0.0068 memory: 5828 grad_norm: 4.2195 loss: 1.9063 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9063 2023/06/05 14:23:10 - mmengine - INFO - Epoch(train) [115][1860/2569] lr: 4.0000e-03 eta: 6:41:52 time: 0.2685 data_time: 0.0070 memory: 5828 grad_norm: 4.2066 loss: 1.7207 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7207 2023/06/05 14:23:15 - mmengine - INFO - Epoch(train) [115][1880/2569] lr: 4.0000e-03 eta: 6:41:46 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 4.2907 loss: 1.7090 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7090 2023/06/05 14:23:21 - mmengine - INFO - Epoch(train) [115][1900/2569] lr: 4.0000e-03 eta: 6:41:41 time: 0.2687 data_time: 0.0068 memory: 5828 grad_norm: 4.3184 loss: 1.5589 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5589 2023/06/05 14:23:26 - mmengine - INFO - Epoch(train) [115][1920/2569] lr: 4.0000e-03 eta: 6:41:36 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 4.3756 loss: 2.0608 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0608 2023/06/05 14:23:31 - mmengine - INFO - Epoch(train) [115][1940/2569] lr: 4.0000e-03 eta: 6:41:30 time: 0.2722 data_time: 0.0075 memory: 5828 grad_norm: 4.1772 loss: 1.5682 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5682 2023/06/05 14:23:37 - mmengine - INFO - Epoch(train) [115][1960/2569] lr: 4.0000e-03 eta: 6:41:25 time: 0.2611 data_time: 0.0070 memory: 5828 grad_norm: 4.2980 loss: 2.1058 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1058 2023/06/05 14:23:42 - mmengine - INFO - Epoch(train) [115][1980/2569] lr: 4.0000e-03 eta: 6:41:20 time: 0.2603 data_time: 0.0074 memory: 5828 grad_norm: 4.2397 loss: 1.6942 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6942 2023/06/05 14:23:47 - mmengine - INFO - Epoch(train) [115][2000/2569] lr: 4.0000e-03 eta: 6:41:14 time: 0.2683 data_time: 0.0083 memory: 5828 grad_norm: 4.2592 loss: 2.1248 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1248 2023/06/05 14:23:53 - mmengine - INFO - Epoch(train) [115][2020/2569] lr: 4.0000e-03 eta: 6:41:09 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 4.2588 loss: 1.6172 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6172 2023/06/05 14:23:58 - mmengine - INFO - Epoch(train) [115][2040/2569] lr: 4.0000e-03 eta: 6:41:04 time: 0.2612 data_time: 0.0074 memory: 5828 grad_norm: 4.3030 loss: 1.9552 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9552 2023/06/05 14:24:03 - mmengine - INFO - Epoch(train) [115][2060/2569] lr: 4.0000e-03 eta: 6:40:58 time: 0.2709 data_time: 0.0071 memory: 5828 grad_norm: 4.2153 loss: 1.6809 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6809 2023/06/05 14:24:08 - mmengine - INFO - Epoch(train) [115][2080/2569] lr: 4.0000e-03 eta: 6:40:53 time: 0.2644 data_time: 0.0078 memory: 5828 grad_norm: 4.2830 loss: 1.5594 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5594 2023/06/05 14:24:14 - mmengine - INFO - Epoch(train) [115][2100/2569] lr: 4.0000e-03 eta: 6:40:48 time: 0.2665 data_time: 0.0075 memory: 5828 grad_norm: 4.2854 loss: 1.7570 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7570 2023/06/05 14:24:19 - mmengine - INFO - Epoch(train) [115][2120/2569] lr: 4.0000e-03 eta: 6:40:43 time: 0.2658 data_time: 0.0074 memory: 5828 grad_norm: 4.2146 loss: 1.7492 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7492 2023/06/05 14:24:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:24:25 - mmengine - INFO - Epoch(train) [115][2140/2569] lr: 4.0000e-03 eta: 6:40:37 time: 0.2714 data_time: 0.0071 memory: 5828 grad_norm: 4.3207 loss: 2.1087 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1087 2023/06/05 14:24:30 - mmengine - INFO - Epoch(train) [115][2160/2569] lr: 4.0000e-03 eta: 6:40:32 time: 0.2654 data_time: 0.0074 memory: 5828 grad_norm: 4.2609 loss: 1.8331 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8331 2023/06/05 14:24:35 - mmengine - INFO - Epoch(train) [115][2180/2569] lr: 4.0000e-03 eta: 6:40:27 time: 0.2728 data_time: 0.0070 memory: 5828 grad_norm: 4.2954 loss: 1.5664 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5664 2023/06/05 14:24:41 - mmengine - INFO - Epoch(train) [115][2200/2569] lr: 4.0000e-03 eta: 6:40:21 time: 0.2626 data_time: 0.0076 memory: 5828 grad_norm: 4.2206 loss: 1.7567 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7567 2023/06/05 14:24:46 - mmengine - INFO - Epoch(train) [115][2220/2569] lr: 4.0000e-03 eta: 6:40:16 time: 0.2717 data_time: 0.0080 memory: 5828 grad_norm: 4.2917 loss: 1.8656 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8656 2023/06/05 14:24:51 - mmengine - INFO - Epoch(train) [115][2240/2569] lr: 4.0000e-03 eta: 6:40:11 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 4.2722 loss: 2.0560 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0560 2023/06/05 14:24:57 - mmengine - INFO - Epoch(train) [115][2260/2569] lr: 4.0000e-03 eta: 6:40:05 time: 0.2645 data_time: 0.0077 memory: 5828 grad_norm: 4.3526 loss: 1.7157 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7157 2023/06/05 14:25:02 - mmengine - INFO - Epoch(train) [115][2280/2569] lr: 4.0000e-03 eta: 6:40:00 time: 0.2701 data_time: 0.0071 memory: 5828 grad_norm: 4.3222 loss: 1.9959 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9959 2023/06/05 14:25:07 - mmengine - INFO - Epoch(train) [115][2300/2569] lr: 4.0000e-03 eta: 6:39:55 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 4.2407 loss: 1.5046 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5046 2023/06/05 14:25:13 - mmengine - INFO - Epoch(train) [115][2320/2569] lr: 4.0000e-03 eta: 6:39:49 time: 0.2667 data_time: 0.0075 memory: 5828 grad_norm: 4.3181 loss: 1.9997 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9997 2023/06/05 14:25:18 - mmengine - INFO - Epoch(train) [115][2340/2569] lr: 4.0000e-03 eta: 6:39:44 time: 0.2678 data_time: 0.0069 memory: 5828 grad_norm: 4.2426 loss: 1.5268 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.5268 2023/06/05 14:25:23 - mmengine - INFO - Epoch(train) [115][2360/2569] lr: 4.0000e-03 eta: 6:39:39 time: 0.2672 data_time: 0.0072 memory: 5828 grad_norm: 4.2356 loss: 1.7346 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7346 2023/06/05 14:25:29 - mmengine - INFO - Epoch(train) [115][2380/2569] lr: 4.0000e-03 eta: 6:39:33 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 4.3057 loss: 2.0200 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0200 2023/06/05 14:25:34 - mmengine - INFO - Epoch(train) [115][2400/2569] lr: 4.0000e-03 eta: 6:39:28 time: 0.2676 data_time: 0.0073 memory: 5828 grad_norm: 4.3715 loss: 1.9722 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9722 2023/06/05 14:25:40 - mmengine - INFO - Epoch(train) [115][2420/2569] lr: 4.0000e-03 eta: 6:39:23 time: 0.2739 data_time: 0.0073 memory: 5828 grad_norm: 4.2243 loss: 1.6524 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6524 2023/06/05 14:25:45 - mmengine - INFO - Epoch(train) [115][2440/2569] lr: 4.0000e-03 eta: 6:39:18 time: 0.2667 data_time: 0.0075 memory: 5828 grad_norm: 4.4037 loss: 1.7645 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7645 2023/06/05 14:25:50 - mmengine - INFO - Epoch(train) [115][2460/2569] lr: 4.0000e-03 eta: 6:39:12 time: 0.2652 data_time: 0.0069 memory: 5828 grad_norm: 4.3572 loss: 2.1858 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1858 2023/06/05 14:25:56 - mmengine - INFO - Epoch(train) [115][2480/2569] lr: 4.0000e-03 eta: 6:39:07 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 4.2574 loss: 1.5655 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5655 2023/06/05 14:26:01 - mmengine - INFO - Epoch(train) [115][2500/2569] lr: 4.0000e-03 eta: 6:39:02 time: 0.2601 data_time: 0.0073 memory: 5828 grad_norm: 4.2681 loss: 1.9752 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9752 2023/06/05 14:26:06 - mmengine - INFO - Epoch(train) [115][2520/2569] lr: 4.0000e-03 eta: 6:38:56 time: 0.2716 data_time: 0.0074 memory: 5828 grad_norm: 4.3085 loss: 1.7022 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7022 2023/06/05 14:26:12 - mmengine - INFO - Epoch(train) [115][2540/2569] lr: 4.0000e-03 eta: 6:38:51 time: 0.2604 data_time: 0.0073 memory: 5828 grad_norm: 4.1452 loss: 1.7835 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7835 2023/06/05 14:26:17 - mmengine - INFO - Epoch(train) [115][2560/2569] lr: 4.0000e-03 eta: 6:38:46 time: 0.2793 data_time: 0.0073 memory: 5828 grad_norm: 4.2350 loss: 2.0044 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0044 2023/06/05 14:26:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:26:19 - mmengine - INFO - Epoch(train) [115][2569/2569] lr: 4.0000e-03 eta: 6:38:43 time: 0.2579 data_time: 0.0071 memory: 5828 grad_norm: 4.2949 loss: 2.1679 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 2.1679 2023/06/05 14:26:23 - mmengine - INFO - Epoch(val) [115][ 20/260] eta: 0:00:45 time: 0.1883 data_time: 0.1291 memory: 1238 2023/06/05 14:26:26 - mmengine - INFO - Epoch(val) [115][ 40/260] eta: 0:00:36 time: 0.1406 data_time: 0.0818 memory: 1238 2023/06/05 14:26:29 - mmengine - INFO - Epoch(val) [115][ 60/260] eta: 0:00:32 time: 0.1580 data_time: 0.0994 memory: 1238 2023/06/05 14:26:32 - mmengine - INFO - Epoch(val) [115][ 80/260] eta: 0:00:27 time: 0.1307 data_time: 0.0716 memory: 1238 2023/06/05 14:26:35 - mmengine - INFO - Epoch(val) [115][100/260] eta: 0:00:24 time: 0.1584 data_time: 0.0995 memory: 1238 2023/06/05 14:26:37 - mmengine - INFO - Epoch(val) [115][120/260] eta: 0:00:20 time: 0.1164 data_time: 0.0573 memory: 1238 2023/06/05 14:26:40 - mmengine - INFO - Epoch(val) [115][140/260] eta: 0:00:17 time: 0.1361 data_time: 0.0775 memory: 1238 2023/06/05 14:26:43 - mmengine - INFO - Epoch(val) [115][160/260] eta: 0:00:14 time: 0.1483 data_time: 0.0895 memory: 1238 2023/06/05 14:26:46 - mmengine - INFO - Epoch(val) [115][180/260] eta: 0:00:11 time: 0.1417 data_time: 0.0832 memory: 1238 2023/06/05 14:26:48 - mmengine - INFO - Epoch(val) [115][200/260] eta: 0:00:08 time: 0.1327 data_time: 0.0741 memory: 1238 2023/06/05 14:26:51 - mmengine - INFO - Epoch(val) [115][220/260] eta: 0:00:05 time: 0.1480 data_time: 0.0892 memory: 1238 2023/06/05 14:26:54 - mmengine - INFO - Epoch(val) [115][240/260] eta: 0:00:02 time: 0.1359 data_time: 0.0774 memory: 1238 2023/06/05 14:26:57 - mmengine - INFO - Epoch(val) [115][260/260] eta: 0:00:00 time: 0.1310 data_time: 0.0743 memory: 1238 2023/06/05 14:27:04 - mmengine - INFO - Epoch(val) [115][260/260] acc/top1: 0.6176 acc/top5: 0.8309 acc/mean1: 0.6102 data_time: 0.0846 time: 0.1432 2023/06/05 14:27:04 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_110.pth is removed 2023/06/05 14:27:06 - mmengine - INFO - The best checkpoint with 0.6176 acc/top1 at 115 epoch is saved to best_acc_top1_epoch_115.pth. 2023/06/05 14:27:12 - mmengine - INFO - Epoch(train) [116][ 20/2569] lr: 4.0000e-03 eta: 6:38:38 time: 0.3050 data_time: 0.0510 memory: 5828 grad_norm: 4.1775 loss: 1.6561 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6561 2023/06/05 14:27:17 - mmengine - INFO - Epoch(train) [116][ 40/2569] lr: 4.0000e-03 eta: 6:38:33 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 4.2981 loss: 1.9310 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9310 2023/06/05 14:27:22 - mmengine - INFO - Epoch(train) [116][ 60/2569] lr: 4.0000e-03 eta: 6:38:27 time: 0.2662 data_time: 0.0071 memory: 5828 grad_norm: 4.3057 loss: 1.7926 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7926 2023/06/05 14:27:28 - mmengine - INFO - Epoch(train) [116][ 80/2569] lr: 4.0000e-03 eta: 6:38:22 time: 0.2694 data_time: 0.0073 memory: 5828 grad_norm: 4.2743 loss: 1.8737 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8737 2023/06/05 14:27:33 - mmengine - INFO - Epoch(train) [116][ 100/2569] lr: 4.0000e-03 eta: 6:38:17 time: 0.2697 data_time: 0.0073 memory: 5828 grad_norm: 4.3135 loss: 1.9539 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9539 2023/06/05 14:27:38 - mmengine - INFO - Epoch(train) [116][ 120/2569] lr: 4.0000e-03 eta: 6:38:12 time: 0.2629 data_time: 0.0071 memory: 5828 grad_norm: 4.3194 loss: 1.6679 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6679 2023/06/05 14:27:44 - mmengine - INFO - Epoch(train) [116][ 140/2569] lr: 4.0000e-03 eta: 6:38:06 time: 0.2719 data_time: 0.0071 memory: 5828 grad_norm: 4.4066 loss: 1.7695 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7695 2023/06/05 14:27:49 - mmengine - INFO - Epoch(train) [116][ 160/2569] lr: 4.0000e-03 eta: 6:38:01 time: 0.2698 data_time: 0.0073 memory: 5828 grad_norm: 4.2508 loss: 1.8721 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8721 2023/06/05 14:27:55 - mmengine - INFO - Epoch(train) [116][ 180/2569] lr: 4.0000e-03 eta: 6:37:56 time: 0.2659 data_time: 0.0077 memory: 5828 grad_norm: 4.2447 loss: 1.5886 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5886 2023/06/05 14:28:00 - mmengine - INFO - Epoch(train) [116][ 200/2569] lr: 4.0000e-03 eta: 6:37:50 time: 0.2838 data_time: 0.0072 memory: 5828 grad_norm: 4.3441 loss: 1.6783 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6783 2023/06/05 14:28:06 - mmengine - INFO - Epoch(train) [116][ 220/2569] lr: 4.0000e-03 eta: 6:37:45 time: 0.2681 data_time: 0.0073 memory: 5828 grad_norm: 4.3041 loss: 1.8388 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8388 2023/06/05 14:28:11 - mmengine - INFO - Epoch(train) [116][ 240/2569] lr: 4.0000e-03 eta: 6:37:40 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 4.3131 loss: 1.8379 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.8379 2023/06/05 14:28:16 - mmengine - INFO - Epoch(train) [116][ 260/2569] lr: 4.0000e-03 eta: 6:37:34 time: 0.2649 data_time: 0.0070 memory: 5828 grad_norm: 4.3221 loss: 1.8044 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8044 2023/06/05 14:28:22 - mmengine - INFO - Epoch(train) [116][ 280/2569] lr: 4.0000e-03 eta: 6:37:29 time: 0.2657 data_time: 0.0072 memory: 5828 grad_norm: 4.3788 loss: 1.9903 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9903 2023/06/05 14:28:27 - mmengine - INFO - Epoch(train) [116][ 300/2569] lr: 4.0000e-03 eta: 6:37:24 time: 0.2648 data_time: 0.0071 memory: 5828 grad_norm: 4.2592 loss: 1.5689 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5689 2023/06/05 14:28:32 - mmengine - INFO - Epoch(train) [116][ 320/2569] lr: 4.0000e-03 eta: 6:37:18 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 4.2451 loss: 1.7417 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7417 2023/06/05 14:28:38 - mmengine - INFO - Epoch(train) [116][ 340/2569] lr: 4.0000e-03 eta: 6:37:13 time: 0.2703 data_time: 0.0073 memory: 5828 grad_norm: 4.1684 loss: 1.9707 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.9707 2023/06/05 14:28:43 - mmengine - INFO - Epoch(train) [116][ 360/2569] lr: 4.0000e-03 eta: 6:37:08 time: 0.2717 data_time: 0.0070 memory: 5828 grad_norm: 4.3125 loss: 1.9744 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9744 2023/06/05 14:28:49 - mmengine - INFO - Epoch(train) [116][ 380/2569] lr: 4.0000e-03 eta: 6:37:03 time: 0.2720 data_time: 0.0071 memory: 5828 grad_norm: 4.2245 loss: 2.0132 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0132 2023/06/05 14:28:54 - mmengine - INFO - Epoch(train) [116][ 400/2569] lr: 4.0000e-03 eta: 6:36:57 time: 0.2620 data_time: 0.0076 memory: 5828 grad_norm: 4.3015 loss: 1.9905 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9905 2023/06/05 14:28:59 - mmengine - INFO - Epoch(train) [116][ 420/2569] lr: 4.0000e-03 eta: 6:36:52 time: 0.2665 data_time: 0.0071 memory: 5828 grad_norm: 4.3129 loss: 1.8831 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8831 2023/06/05 14:29:04 - mmengine - INFO - Epoch(train) [116][ 440/2569] lr: 4.0000e-03 eta: 6:36:47 time: 0.2636 data_time: 0.0071 memory: 5828 grad_norm: 4.2699 loss: 1.6278 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6278 2023/06/05 14:29:10 - mmengine - INFO - Epoch(train) [116][ 460/2569] lr: 4.0000e-03 eta: 6:36:41 time: 0.2661 data_time: 0.0072 memory: 5828 grad_norm: 4.3645 loss: 1.8951 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8951 2023/06/05 14:29:15 - mmengine - INFO - Epoch(train) [116][ 480/2569] lr: 4.0000e-03 eta: 6:36:36 time: 0.2749 data_time: 0.0077 memory: 5828 grad_norm: 4.3977 loss: 1.9653 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9653 2023/06/05 14:29:21 - mmengine - INFO - Epoch(train) [116][ 500/2569] lr: 4.0000e-03 eta: 6:36:31 time: 0.2669 data_time: 0.0072 memory: 5828 grad_norm: 4.2321 loss: 1.8358 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8358 2023/06/05 14:29:26 - mmengine - INFO - Epoch(train) [116][ 520/2569] lr: 4.0000e-03 eta: 6:36:25 time: 0.2773 data_time: 0.0073 memory: 5828 grad_norm: 4.2984 loss: 1.6065 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6065 2023/06/05 14:29:32 - mmengine - INFO - Epoch(train) [116][ 540/2569] lr: 4.0000e-03 eta: 6:36:20 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 4.3328 loss: 1.8246 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8246 2023/06/05 14:29:37 - mmengine - INFO - Epoch(train) [116][ 560/2569] lr: 4.0000e-03 eta: 6:36:15 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 4.3205 loss: 2.0162 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0162 2023/06/05 14:29:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:29:42 - mmengine - INFO - Epoch(train) [116][ 580/2569] lr: 4.0000e-03 eta: 6:36:09 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 4.4374 loss: 1.5985 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5985 2023/06/05 14:29:47 - mmengine - INFO - Epoch(train) [116][ 600/2569] lr: 4.0000e-03 eta: 6:36:04 time: 0.2617 data_time: 0.0071 memory: 5828 grad_norm: 4.3182 loss: 1.6468 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6468 2023/06/05 14:29:53 - mmengine - INFO - Epoch(train) [116][ 620/2569] lr: 4.0000e-03 eta: 6:35:59 time: 0.2728 data_time: 0.0071 memory: 5828 grad_norm: 4.3395 loss: 1.8962 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8962 2023/06/05 14:29:58 - mmengine - INFO - Epoch(train) [116][ 640/2569] lr: 4.0000e-03 eta: 6:35:53 time: 0.2629 data_time: 0.0070 memory: 5828 grad_norm: 4.3434 loss: 2.1461 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1461 2023/06/05 14:30:03 - mmengine - INFO - Epoch(train) [116][ 660/2569] lr: 4.0000e-03 eta: 6:35:48 time: 0.2616 data_time: 0.0070 memory: 5828 grad_norm: 4.2533 loss: 1.3834 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3834 2023/06/05 14:30:09 - mmengine - INFO - Epoch(train) [116][ 680/2569] lr: 4.0000e-03 eta: 6:35:43 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 4.2662 loss: 1.8210 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8210 2023/06/05 14:30:14 - mmengine - INFO - Epoch(train) [116][ 700/2569] lr: 4.0000e-03 eta: 6:35:37 time: 0.2608 data_time: 0.0069 memory: 5828 grad_norm: 4.3306 loss: 1.8312 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.8312 2023/06/05 14:30:19 - mmengine - INFO - Epoch(train) [116][ 720/2569] lr: 4.0000e-03 eta: 6:35:32 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 4.3178 loss: 1.8736 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8736 2023/06/05 14:30:24 - mmengine - INFO - Epoch(train) [116][ 740/2569] lr: 4.0000e-03 eta: 6:35:27 time: 0.2630 data_time: 0.0072 memory: 5828 grad_norm: 4.3840 loss: 1.9406 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9406 2023/06/05 14:30:30 - mmengine - INFO - Epoch(train) [116][ 760/2569] lr: 4.0000e-03 eta: 6:35:21 time: 0.2695 data_time: 0.0072 memory: 5828 grad_norm: 4.2970 loss: 1.9784 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9784 2023/06/05 14:30:35 - mmengine - INFO - Epoch(train) [116][ 780/2569] lr: 4.0000e-03 eta: 6:35:16 time: 0.2625 data_time: 0.0071 memory: 5828 grad_norm: 4.3105 loss: 1.6155 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.6155 2023/06/05 14:30:40 - mmengine - INFO - Epoch(train) [116][ 800/2569] lr: 4.0000e-03 eta: 6:35:11 time: 0.2632 data_time: 0.0069 memory: 5828 grad_norm: 4.3569 loss: 1.8658 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8658 2023/06/05 14:30:46 - mmengine - INFO - Epoch(train) [116][ 820/2569] lr: 4.0000e-03 eta: 6:35:05 time: 0.2671 data_time: 0.0071 memory: 5828 grad_norm: 4.3135 loss: 1.5868 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5868 2023/06/05 14:30:51 - mmengine - INFO - Epoch(train) [116][ 840/2569] lr: 4.0000e-03 eta: 6:35:00 time: 0.2684 data_time: 0.0071 memory: 5828 grad_norm: 4.2218 loss: 2.0548 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0548 2023/06/05 14:30:56 - mmengine - INFO - Epoch(train) [116][ 860/2569] lr: 4.0000e-03 eta: 6:34:55 time: 0.2675 data_time: 0.0071 memory: 5828 grad_norm: 4.3065 loss: 1.7445 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7445 2023/06/05 14:31:02 - mmengine - INFO - Epoch(train) [116][ 880/2569] lr: 4.0000e-03 eta: 6:34:50 time: 0.2658 data_time: 0.0070 memory: 5828 grad_norm: 4.2655 loss: 1.7444 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7444 2023/06/05 14:31:07 - mmengine - INFO - Epoch(train) [116][ 900/2569] lr: 4.0000e-03 eta: 6:34:44 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 4.2286 loss: 1.6240 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6240 2023/06/05 14:31:12 - mmengine - INFO - Epoch(train) [116][ 920/2569] lr: 4.0000e-03 eta: 6:34:39 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 4.2662 loss: 1.7895 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7895 2023/06/05 14:31:18 - mmengine - INFO - Epoch(train) [116][ 940/2569] lr: 4.0000e-03 eta: 6:34:34 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 4.3483 loss: 1.9559 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9559 2023/06/05 14:31:23 - mmengine - INFO - Epoch(train) [116][ 960/2569] lr: 4.0000e-03 eta: 6:34:28 time: 0.2703 data_time: 0.0072 memory: 5828 grad_norm: 4.2853 loss: 1.7599 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7599 2023/06/05 14:31:29 - mmengine - INFO - Epoch(train) [116][ 980/2569] lr: 4.0000e-03 eta: 6:34:23 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 4.3495 loss: 1.8727 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8727 2023/06/05 14:31:34 - mmengine - INFO - Epoch(train) [116][1000/2569] lr: 4.0000e-03 eta: 6:34:18 time: 0.2819 data_time: 0.0075 memory: 5828 grad_norm: 4.3899 loss: 1.9284 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9284 2023/06/05 14:31:40 - mmengine - INFO - Epoch(train) [116][1020/2569] lr: 4.0000e-03 eta: 6:34:12 time: 0.2664 data_time: 0.0075 memory: 5828 grad_norm: 4.3035 loss: 2.1300 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1300 2023/06/05 14:31:45 - mmengine - INFO - Epoch(train) [116][1040/2569] lr: 4.0000e-03 eta: 6:34:07 time: 0.2832 data_time: 0.0069 memory: 5828 grad_norm: 4.3426 loss: 1.9170 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9170 2023/06/05 14:31:51 - mmengine - INFO - Epoch(train) [116][1060/2569] lr: 4.0000e-03 eta: 6:34:02 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 4.3227 loss: 1.8733 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8733 2023/06/05 14:31:56 - mmengine - INFO - Epoch(train) [116][1080/2569] lr: 4.0000e-03 eta: 6:33:57 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 4.3250 loss: 1.8014 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8014 2023/06/05 14:32:01 - mmengine - INFO - Epoch(train) [116][1100/2569] lr: 4.0000e-03 eta: 6:33:51 time: 0.2608 data_time: 0.0070 memory: 5828 grad_norm: 4.3262 loss: 1.5528 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5528 2023/06/05 14:32:06 - mmengine - INFO - Epoch(train) [116][1120/2569] lr: 4.0000e-03 eta: 6:33:46 time: 0.2664 data_time: 0.0072 memory: 5828 grad_norm: 4.2964 loss: 1.7948 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7948 2023/06/05 14:32:12 - mmengine - INFO - Epoch(train) [116][1140/2569] lr: 4.0000e-03 eta: 6:33:41 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 4.2972 loss: 1.9166 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9166 2023/06/05 14:32:17 - mmengine - INFO - Epoch(train) [116][1160/2569] lr: 4.0000e-03 eta: 6:33:35 time: 0.2601 data_time: 0.0069 memory: 5828 grad_norm: 4.2914 loss: 1.9505 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.9505 2023/06/05 14:32:22 - mmengine - INFO - Epoch(train) [116][1180/2569] lr: 4.0000e-03 eta: 6:33:30 time: 0.2630 data_time: 0.0080 memory: 5828 grad_norm: 4.3531 loss: 1.9703 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9703 2023/06/05 14:32:27 - mmengine - INFO - Epoch(train) [116][1200/2569] lr: 4.0000e-03 eta: 6:33:25 time: 0.2625 data_time: 0.0070 memory: 5828 grad_norm: 4.2258 loss: 2.0046 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0046 2023/06/05 14:32:33 - mmengine - INFO - Epoch(train) [116][1220/2569] lr: 4.0000e-03 eta: 6:33:19 time: 0.2663 data_time: 0.0075 memory: 5828 grad_norm: 4.2993 loss: 1.9284 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.9284 2023/06/05 14:32:38 - mmengine - INFO - Epoch(train) [116][1240/2569] lr: 4.0000e-03 eta: 6:33:14 time: 0.2615 data_time: 0.0071 memory: 5828 grad_norm: 4.2494 loss: 1.9459 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9459 2023/06/05 14:32:43 - mmengine - INFO - Epoch(train) [116][1260/2569] lr: 4.0000e-03 eta: 6:33:09 time: 0.2724 data_time: 0.0073 memory: 5828 grad_norm: 4.3343 loss: 1.6638 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6638 2023/06/05 14:32:49 - mmengine - INFO - Epoch(train) [116][1280/2569] lr: 4.0000e-03 eta: 6:33:03 time: 0.2652 data_time: 0.0070 memory: 5828 grad_norm: 4.2954 loss: 1.5806 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5806 2023/06/05 14:32:54 - mmengine - INFO - Epoch(train) [116][1300/2569] lr: 4.0000e-03 eta: 6:32:58 time: 0.2760 data_time: 0.0073 memory: 5828 grad_norm: 4.3141 loss: 1.7308 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7308 2023/06/05 14:33:00 - mmengine - INFO - Epoch(train) [116][1320/2569] lr: 4.0000e-03 eta: 6:32:53 time: 0.2722 data_time: 0.0072 memory: 5828 grad_norm: 4.2597 loss: 1.5230 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5230 2023/06/05 14:33:05 - mmengine - INFO - Epoch(train) [116][1340/2569] lr: 4.0000e-03 eta: 6:32:47 time: 0.2748 data_time: 0.0073 memory: 5828 grad_norm: 4.2958 loss: 1.6177 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 1.6177 2023/06/05 14:33:11 - mmengine - INFO - Epoch(train) [116][1360/2569] lr: 4.0000e-03 eta: 6:32:42 time: 0.2755 data_time: 0.0072 memory: 5828 grad_norm: 4.3303 loss: 1.6041 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6041 2023/06/05 14:33:16 - mmengine - INFO - Epoch(train) [116][1380/2569] lr: 4.0000e-03 eta: 6:32:37 time: 0.2732 data_time: 0.0072 memory: 5828 grad_norm: 4.3283 loss: 1.9625 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9625 2023/06/05 14:33:22 - mmengine - INFO - Epoch(train) [116][1400/2569] lr: 4.0000e-03 eta: 6:32:32 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 4.3297 loss: 1.8729 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8729 2023/06/05 14:33:27 - mmengine - INFO - Epoch(train) [116][1420/2569] lr: 4.0000e-03 eta: 6:32:26 time: 0.2656 data_time: 0.0072 memory: 5828 grad_norm: 4.3462 loss: 1.6812 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 1.6812 2023/06/05 14:33:32 - mmengine - INFO - Epoch(train) [116][1440/2569] lr: 4.0000e-03 eta: 6:32:21 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 4.3718 loss: 1.8523 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8523 2023/06/05 14:33:38 - mmengine - INFO - Epoch(train) [116][1460/2569] lr: 4.0000e-03 eta: 6:32:16 time: 0.2684 data_time: 0.0071 memory: 5828 grad_norm: 4.3151 loss: 1.9092 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9092 2023/06/05 14:33:43 - mmengine - INFO - Epoch(train) [116][1480/2569] lr: 4.0000e-03 eta: 6:32:10 time: 0.2726 data_time: 0.0074 memory: 5828 grad_norm: 4.3416 loss: 1.6501 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6501 2023/06/05 14:33:48 - mmengine - INFO - Epoch(train) [116][1500/2569] lr: 4.0000e-03 eta: 6:32:05 time: 0.2622 data_time: 0.0078 memory: 5828 grad_norm: 4.3761 loss: 1.5812 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5812 2023/06/05 14:33:54 - mmengine - INFO - Epoch(train) [116][1520/2569] lr: 4.0000e-03 eta: 6:32:00 time: 0.2753 data_time: 0.0075 memory: 5828 grad_norm: 4.5237 loss: 1.9874 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9874 2023/06/05 14:33:59 - mmengine - INFO - Epoch(train) [116][1540/2569] lr: 4.0000e-03 eta: 6:31:54 time: 0.2710 data_time: 0.0074 memory: 5828 grad_norm: 4.3058 loss: 1.7698 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7698 2023/06/05 14:34:05 - mmengine - INFO - Epoch(train) [116][1560/2569] lr: 4.0000e-03 eta: 6:31:49 time: 0.2704 data_time: 0.0074 memory: 5828 grad_norm: 4.3130 loss: 1.8030 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.8030 2023/06/05 14:34:06 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:34:10 - mmengine - INFO - Epoch(train) [116][1580/2569] lr: 4.0000e-03 eta: 6:31:44 time: 0.2637 data_time: 0.0069 memory: 5828 grad_norm: 4.3711 loss: 1.5225 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5225 2023/06/05 14:34:15 - mmengine - INFO - Epoch(train) [116][1600/2569] lr: 4.0000e-03 eta: 6:31:38 time: 0.2702 data_time: 0.0069 memory: 5828 grad_norm: 4.1973 loss: 1.8988 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8988 2023/06/05 14:34:21 - mmengine - INFO - Epoch(train) [116][1620/2569] lr: 4.0000e-03 eta: 6:31:33 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 4.3810 loss: 1.9236 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9236 2023/06/05 14:34:26 - mmengine - INFO - Epoch(train) [116][1640/2569] lr: 4.0000e-03 eta: 6:31:28 time: 0.2606 data_time: 0.0069 memory: 5828 grad_norm: 4.3262 loss: 1.6812 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6812 2023/06/05 14:34:31 - mmengine - INFO - Epoch(train) [116][1660/2569] lr: 4.0000e-03 eta: 6:31:22 time: 0.2673 data_time: 0.0071 memory: 5828 grad_norm: 4.2943 loss: 1.7338 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7338 2023/06/05 14:34:37 - mmengine - INFO - Epoch(train) [116][1680/2569] lr: 4.0000e-03 eta: 6:31:17 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 4.4021 loss: 1.8364 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8364 2023/06/05 14:34:42 - mmengine - INFO - Epoch(train) [116][1700/2569] lr: 4.0000e-03 eta: 6:31:12 time: 0.2705 data_time: 0.0070 memory: 5828 grad_norm: 4.3159 loss: 1.7610 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 1.7610 2023/06/05 14:34:47 - mmengine - INFO - Epoch(train) [116][1720/2569] lr: 4.0000e-03 eta: 6:31:07 time: 0.2660 data_time: 0.0071 memory: 5828 grad_norm: 4.3247 loss: 2.0417 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0417 2023/06/05 14:34:53 - mmengine - INFO - Epoch(train) [116][1740/2569] lr: 4.0000e-03 eta: 6:31:01 time: 0.2747 data_time: 0.0072 memory: 5828 grad_norm: 4.2841 loss: 1.7760 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7760 2023/06/05 14:34:58 - mmengine - INFO - Epoch(train) [116][1760/2569] lr: 4.0000e-03 eta: 6:30:56 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 4.4163 loss: 1.5720 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5720 2023/06/05 14:35:04 - mmengine - INFO - Epoch(train) [116][1780/2569] lr: 4.0000e-03 eta: 6:30:51 time: 0.2681 data_time: 0.0074 memory: 5828 grad_norm: 4.3406 loss: 1.9901 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9901 2023/06/05 14:35:09 - mmengine - INFO - Epoch(train) [116][1800/2569] lr: 4.0000e-03 eta: 6:30:45 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 4.2534 loss: 1.7985 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7985 2023/06/05 14:35:14 - mmengine - INFO - Epoch(train) [116][1820/2569] lr: 4.0000e-03 eta: 6:30:40 time: 0.2640 data_time: 0.0070 memory: 5828 grad_norm: 4.3331 loss: 1.7519 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7519 2023/06/05 14:35:19 - mmengine - INFO - Epoch(train) [116][1840/2569] lr: 4.0000e-03 eta: 6:30:35 time: 0.2620 data_time: 0.0068 memory: 5828 grad_norm: 4.3069 loss: 1.6357 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6357 2023/06/05 14:35:25 - mmengine - INFO - Epoch(train) [116][1860/2569] lr: 4.0000e-03 eta: 6:30:29 time: 0.2664 data_time: 0.0070 memory: 5828 grad_norm: 4.2555 loss: 1.9577 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9577 2023/06/05 14:35:30 - mmengine - INFO - Epoch(train) [116][1880/2569] lr: 4.0000e-03 eta: 6:30:24 time: 0.2696 data_time: 0.0071 memory: 5828 grad_norm: 4.2345 loss: 1.5913 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5913 2023/06/05 14:35:35 - mmengine - INFO - Epoch(train) [116][1900/2569] lr: 4.0000e-03 eta: 6:30:19 time: 0.2618 data_time: 0.0076 memory: 5828 grad_norm: 4.3043 loss: 1.4743 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4743 2023/06/05 14:35:41 - mmengine - INFO - Epoch(train) [116][1920/2569] lr: 4.0000e-03 eta: 6:30:13 time: 0.2648 data_time: 0.0073 memory: 5828 grad_norm: 4.2607 loss: 1.4683 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4683 2023/06/05 14:35:46 - mmengine - INFO - Epoch(train) [116][1940/2569] lr: 4.0000e-03 eta: 6:30:08 time: 0.2613 data_time: 0.0072 memory: 5828 grad_norm: 4.3382 loss: 1.7644 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7644 2023/06/05 14:35:51 - mmengine - INFO - Epoch(train) [116][1960/2569] lr: 4.0000e-03 eta: 6:30:03 time: 0.2706 data_time: 0.0070 memory: 5828 grad_norm: 4.2784 loss: 1.7436 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7436 2023/06/05 14:35:57 - mmengine - INFO - Epoch(train) [116][1980/2569] lr: 4.0000e-03 eta: 6:29:57 time: 0.2674 data_time: 0.0070 memory: 5828 grad_norm: 4.4502 loss: 1.8030 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8030 2023/06/05 14:36:02 - mmengine - INFO - Epoch(train) [116][2000/2569] lr: 4.0000e-03 eta: 6:29:52 time: 0.2707 data_time: 0.0071 memory: 5828 grad_norm: 4.3006 loss: 1.7872 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7872 2023/06/05 14:36:08 - mmengine - INFO - Epoch(train) [116][2020/2569] lr: 4.0000e-03 eta: 6:29:47 time: 0.2695 data_time: 0.0071 memory: 5828 grad_norm: 4.4079 loss: 1.8839 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8839 2023/06/05 14:36:13 - mmengine - INFO - Epoch(train) [116][2040/2569] lr: 4.0000e-03 eta: 6:29:41 time: 0.2716 data_time: 0.0077 memory: 5828 grad_norm: 4.3161 loss: 1.9924 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9924 2023/06/05 14:36:18 - mmengine - INFO - Epoch(train) [116][2060/2569] lr: 4.0000e-03 eta: 6:29:36 time: 0.2607 data_time: 0.0073 memory: 5828 grad_norm: 4.3090 loss: 1.7016 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7016 2023/06/05 14:36:24 - mmengine - INFO - Epoch(train) [116][2080/2569] lr: 4.0000e-03 eta: 6:29:31 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 4.3571 loss: 2.1787 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1787 2023/06/05 14:36:29 - mmengine - INFO - Epoch(train) [116][2100/2569] lr: 4.0000e-03 eta: 6:29:25 time: 0.2630 data_time: 0.0070 memory: 5828 grad_norm: 4.3104 loss: 2.2054 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2054 2023/06/05 14:36:34 - mmengine - INFO - Epoch(train) [116][2120/2569] lr: 4.0000e-03 eta: 6:29:20 time: 0.2745 data_time: 0.0072 memory: 5828 grad_norm: 4.3439 loss: 2.1382 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1382 2023/06/05 14:36:40 - mmengine - INFO - Epoch(train) [116][2140/2569] lr: 4.0000e-03 eta: 6:29:15 time: 0.2823 data_time: 0.0076 memory: 5828 grad_norm: 4.3586 loss: 1.8417 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8417 2023/06/05 14:36:45 - mmengine - INFO - Epoch(train) [116][2160/2569] lr: 4.0000e-03 eta: 6:29:10 time: 0.2691 data_time: 0.0077 memory: 5828 grad_norm: 4.2991 loss: 1.6483 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6483 2023/06/05 14:36:51 - mmengine - INFO - Epoch(train) [116][2180/2569] lr: 4.0000e-03 eta: 6:29:04 time: 0.2693 data_time: 0.0073 memory: 5828 grad_norm: 4.2892 loss: 1.6993 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6993 2023/06/05 14:36:56 - mmengine - INFO - Epoch(train) [116][2200/2569] lr: 4.0000e-03 eta: 6:28:59 time: 0.2652 data_time: 0.0077 memory: 5828 grad_norm: 4.3156 loss: 1.9218 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9218 2023/06/05 14:37:02 - mmengine - INFO - Epoch(train) [116][2220/2569] lr: 4.0000e-03 eta: 6:28:54 time: 0.2732 data_time: 0.0074 memory: 5828 grad_norm: 4.3191 loss: 1.6618 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6618 2023/06/05 14:37:07 - mmengine - INFO - Epoch(train) [116][2240/2569] lr: 4.0000e-03 eta: 6:28:48 time: 0.2615 data_time: 0.0073 memory: 5828 grad_norm: 4.3704 loss: 1.5748 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5748 2023/06/05 14:37:12 - mmengine - INFO - Epoch(train) [116][2260/2569] lr: 4.0000e-03 eta: 6:28:43 time: 0.2662 data_time: 0.0076 memory: 5828 grad_norm: 4.2929 loss: 1.7908 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7908 2023/06/05 14:37:17 - mmengine - INFO - Epoch(train) [116][2280/2569] lr: 4.0000e-03 eta: 6:28:38 time: 0.2615 data_time: 0.0074 memory: 5828 grad_norm: 4.3918 loss: 1.7095 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7095 2023/06/05 14:37:23 - mmengine - INFO - Epoch(train) [116][2300/2569] lr: 4.0000e-03 eta: 6:28:32 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 4.3602 loss: 1.5589 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5589 2023/06/05 14:37:28 - mmengine - INFO - Epoch(train) [116][2320/2569] lr: 4.0000e-03 eta: 6:28:27 time: 0.2684 data_time: 0.0074 memory: 5828 grad_norm: 4.3905 loss: 1.9488 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9488 2023/06/05 14:37:33 - mmengine - INFO - Epoch(train) [116][2340/2569] lr: 4.0000e-03 eta: 6:28:22 time: 0.2660 data_time: 0.0072 memory: 5828 grad_norm: 4.3412 loss: 1.8121 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8121 2023/06/05 14:37:39 - mmengine - INFO - Epoch(train) [116][2360/2569] lr: 4.0000e-03 eta: 6:28:16 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 4.2676 loss: 1.6124 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6124 2023/06/05 14:37:44 - mmengine - INFO - Epoch(train) [116][2380/2569] lr: 4.0000e-03 eta: 6:28:11 time: 0.2619 data_time: 0.0072 memory: 5828 grad_norm: 4.3205 loss: 1.8992 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8992 2023/06/05 14:37:49 - mmengine - INFO - Epoch(train) [116][2400/2569] lr: 4.0000e-03 eta: 6:28:06 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 4.4308 loss: 2.2874 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2874 2023/06/05 14:37:55 - mmengine - INFO - Epoch(train) [116][2420/2569] lr: 4.0000e-03 eta: 6:28:00 time: 0.2661 data_time: 0.0071 memory: 5828 grad_norm: 4.2679 loss: 2.0360 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0360 2023/06/05 14:38:00 - mmengine - INFO - Epoch(train) [116][2440/2569] lr: 4.0000e-03 eta: 6:27:55 time: 0.2695 data_time: 0.0074 memory: 5828 grad_norm: 4.3794 loss: 1.4783 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4783 2023/06/05 14:38:05 - mmengine - INFO - Epoch(train) [116][2460/2569] lr: 4.0000e-03 eta: 6:27:50 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 4.3593 loss: 1.7455 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7455 2023/06/05 14:38:11 - mmengine - INFO - Epoch(train) [116][2480/2569] lr: 4.0000e-03 eta: 6:27:44 time: 0.2607 data_time: 0.0072 memory: 5828 grad_norm: 4.2753 loss: 1.6182 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6182 2023/06/05 14:38:16 - mmengine - INFO - Epoch(train) [116][2500/2569] lr: 4.0000e-03 eta: 6:27:39 time: 0.2679 data_time: 0.0071 memory: 5828 grad_norm: 4.2898 loss: 1.7512 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7512 2023/06/05 14:38:21 - mmengine - INFO - Epoch(train) [116][2520/2569] lr: 4.0000e-03 eta: 6:27:34 time: 0.2609 data_time: 0.0071 memory: 5828 grad_norm: 4.2422 loss: 1.6444 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6444 2023/06/05 14:38:27 - mmengine - INFO - Epoch(train) [116][2540/2569] lr: 4.0000e-03 eta: 6:27:29 time: 0.2682 data_time: 0.0071 memory: 5828 grad_norm: 4.3051 loss: 1.5429 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.5429 2023/06/05 14:38:32 - mmengine - INFO - Epoch(train) [116][2560/2569] lr: 4.0000e-03 eta: 6:27:23 time: 0.2606 data_time: 0.0071 memory: 5828 grad_norm: 4.3752 loss: 1.9230 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9230 2023/06/05 14:38:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:38:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:38:34 - mmengine - INFO - Epoch(train) [116][2569/2569] lr: 4.0000e-03 eta: 6:27:21 time: 0.2525 data_time: 0.0071 memory: 5828 grad_norm: 4.3326 loss: 1.5791 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.5791 2023/06/05 14:38:34 - mmengine - INFO - Saving checkpoint at 116 epochs 2023/06/05 14:38:42 - mmengine - INFO - Epoch(train) [117][ 20/2569] lr: 4.0000e-03 eta: 6:27:16 time: 0.3145 data_time: 0.0543 memory: 5828 grad_norm: 4.2604 loss: 1.8840 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8840 2023/06/05 14:38:48 - mmengine - INFO - Epoch(train) [117][ 40/2569] lr: 4.0000e-03 eta: 6:27:10 time: 0.2666 data_time: 0.0072 memory: 5828 grad_norm: 4.3753 loss: 1.8455 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8455 2023/06/05 14:38:53 - mmengine - INFO - Epoch(train) [117][ 60/2569] lr: 4.0000e-03 eta: 6:27:05 time: 0.2639 data_time: 0.0069 memory: 5828 grad_norm: 4.3180 loss: 1.7785 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7785 2023/06/05 14:38:58 - mmengine - INFO - Epoch(train) [117][ 80/2569] lr: 4.0000e-03 eta: 6:27:00 time: 0.2694 data_time: 0.0072 memory: 5828 grad_norm: 4.2528 loss: 1.5544 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5544 2023/06/05 14:39:04 - mmengine - INFO - Epoch(train) [117][ 100/2569] lr: 4.0000e-03 eta: 6:26:54 time: 0.2608 data_time: 0.0072 memory: 5828 grad_norm: 4.3638 loss: 1.6473 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6473 2023/06/05 14:39:09 - mmengine - INFO - Epoch(train) [117][ 120/2569] lr: 4.0000e-03 eta: 6:26:49 time: 0.2704 data_time: 0.0075 memory: 5828 grad_norm: 4.2986 loss: 1.7932 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7932 2023/06/05 14:39:14 - mmengine - INFO - Epoch(train) [117][ 140/2569] lr: 4.0000e-03 eta: 6:26:44 time: 0.2608 data_time: 0.0074 memory: 5828 grad_norm: 4.3653 loss: 1.8291 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8291 2023/06/05 14:39:19 - mmengine - INFO - Epoch(train) [117][ 160/2569] lr: 4.0000e-03 eta: 6:26:38 time: 0.2631 data_time: 0.0075 memory: 5828 grad_norm: 4.3015 loss: 1.6391 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6391 2023/06/05 14:39:25 - mmengine - INFO - Epoch(train) [117][ 180/2569] lr: 4.0000e-03 eta: 6:26:33 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 4.3875 loss: 1.7777 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7777 2023/06/05 14:39:30 - mmengine - INFO - Epoch(train) [117][ 200/2569] lr: 4.0000e-03 eta: 6:26:28 time: 0.2653 data_time: 0.0073 memory: 5828 grad_norm: 4.3170 loss: 1.8667 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8667 2023/06/05 14:39:35 - mmengine - INFO - Epoch(train) [117][ 220/2569] lr: 4.0000e-03 eta: 6:26:22 time: 0.2661 data_time: 0.0074 memory: 5828 grad_norm: 4.3035 loss: 1.6525 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6525 2023/06/05 14:39:41 - mmengine - INFO - Epoch(train) [117][ 240/2569] lr: 4.0000e-03 eta: 6:26:17 time: 0.2613 data_time: 0.0073 memory: 5828 grad_norm: 4.4247 loss: 1.7196 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7196 2023/06/05 14:39:46 - mmengine - INFO - Epoch(train) [117][ 260/2569] lr: 4.0000e-03 eta: 6:26:12 time: 0.2600 data_time: 0.0071 memory: 5828 grad_norm: 4.3502 loss: 1.8520 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8520 2023/06/05 14:39:51 - mmengine - INFO - Epoch(train) [117][ 280/2569] lr: 4.0000e-03 eta: 6:26:06 time: 0.2680 data_time: 0.0068 memory: 5828 grad_norm: 4.3539 loss: 1.7687 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7687 2023/06/05 14:39:56 - mmengine - INFO - Epoch(train) [117][ 300/2569] lr: 4.0000e-03 eta: 6:26:01 time: 0.2607 data_time: 0.0071 memory: 5828 grad_norm: 4.3633 loss: 1.9605 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9605 2023/06/05 14:40:02 - mmengine - INFO - Epoch(train) [117][ 320/2569] lr: 4.0000e-03 eta: 6:25:56 time: 0.2759 data_time: 0.0074 memory: 5828 grad_norm: 4.2493 loss: 1.3527 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3527 2023/06/05 14:40:07 - mmengine - INFO - Epoch(train) [117][ 340/2569] lr: 4.0000e-03 eta: 6:25:50 time: 0.2615 data_time: 0.0070 memory: 5828 grad_norm: 4.2834 loss: 1.7869 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7869 2023/06/05 14:40:13 - mmengine - INFO - Epoch(train) [117][ 360/2569] lr: 4.0000e-03 eta: 6:25:45 time: 0.2721 data_time: 0.0068 memory: 5828 grad_norm: 4.3720 loss: 1.8595 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8595 2023/06/05 14:40:18 - mmengine - INFO - Epoch(train) [117][ 380/2569] lr: 4.0000e-03 eta: 6:25:40 time: 0.2699 data_time: 0.0071 memory: 5828 grad_norm: 4.3239 loss: 1.9166 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9166 2023/06/05 14:40:23 - mmengine - INFO - Epoch(train) [117][ 400/2569] lr: 4.0000e-03 eta: 6:25:35 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 4.3048 loss: 1.5408 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5408 2023/06/05 14:40:29 - mmengine - INFO - Epoch(train) [117][ 420/2569] lr: 4.0000e-03 eta: 6:25:29 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 4.3474 loss: 1.7255 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7255 2023/06/05 14:40:34 - mmengine - INFO - Epoch(train) [117][ 440/2569] lr: 4.0000e-03 eta: 6:25:24 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 4.3157 loss: 1.4918 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4918 2023/06/05 14:40:39 - mmengine - INFO - Epoch(train) [117][ 460/2569] lr: 4.0000e-03 eta: 6:25:19 time: 0.2706 data_time: 0.0076 memory: 5828 grad_norm: 4.3427 loss: 1.9825 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9825 2023/06/05 14:40:45 - mmengine - INFO - Epoch(train) [117][ 480/2569] lr: 4.0000e-03 eta: 6:25:13 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 4.3359 loss: 1.8182 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8182 2023/06/05 14:40:50 - mmengine - INFO - Epoch(train) [117][ 500/2569] lr: 4.0000e-03 eta: 6:25:08 time: 0.2793 data_time: 0.0076 memory: 5828 grad_norm: 4.2474 loss: 1.6785 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6785 2023/06/05 14:40:56 - mmengine - INFO - Epoch(train) [117][ 520/2569] lr: 4.0000e-03 eta: 6:25:03 time: 0.2652 data_time: 0.0074 memory: 5828 grad_norm: 4.2501 loss: 1.6050 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6050 2023/06/05 14:41:01 - mmengine - INFO - Epoch(train) [117][ 540/2569] lr: 4.0000e-03 eta: 6:24:57 time: 0.2740 data_time: 0.0072 memory: 5828 grad_norm: 4.4025 loss: 1.4193 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4193 2023/06/05 14:41:07 - mmengine - INFO - Epoch(train) [117][ 560/2569] lr: 4.0000e-03 eta: 6:24:52 time: 0.2707 data_time: 0.0069 memory: 5828 grad_norm: 4.2769 loss: 1.5394 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.5394 2023/06/05 14:41:12 - mmengine - INFO - Epoch(train) [117][ 580/2569] lr: 4.0000e-03 eta: 6:24:47 time: 0.2788 data_time: 0.0072 memory: 5828 grad_norm: 4.3660 loss: 1.6336 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.6336 2023/06/05 14:41:17 - mmengine - INFO - Epoch(train) [117][ 600/2569] lr: 4.0000e-03 eta: 6:24:41 time: 0.2620 data_time: 0.0071 memory: 5828 grad_norm: 4.4677 loss: 1.5091 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5091 2023/06/05 14:41:23 - mmengine - INFO - Epoch(train) [117][ 620/2569] lr: 4.0000e-03 eta: 6:24:36 time: 0.2764 data_time: 0.0071 memory: 5828 grad_norm: 4.4484 loss: 1.9311 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9311 2023/06/05 14:41:28 - mmengine - INFO - Epoch(train) [117][ 640/2569] lr: 4.0000e-03 eta: 6:24:31 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 4.4404 loss: 1.8362 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8362 2023/06/05 14:41:34 - mmengine - INFO - Epoch(train) [117][ 660/2569] lr: 4.0000e-03 eta: 6:24:26 time: 0.2699 data_time: 0.0075 memory: 5828 grad_norm: 4.3468 loss: 1.7941 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7941 2023/06/05 14:41:39 - mmengine - INFO - Epoch(train) [117][ 680/2569] lr: 4.0000e-03 eta: 6:24:20 time: 0.2674 data_time: 0.0078 memory: 5828 grad_norm: 4.3668 loss: 1.6614 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6614 2023/06/05 14:41:45 - mmengine - INFO - Epoch(train) [117][ 700/2569] lr: 4.0000e-03 eta: 6:24:15 time: 0.2732 data_time: 0.0073 memory: 5828 grad_norm: 4.4010 loss: 1.9723 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.9723 2023/06/05 14:41:50 - mmengine - INFO - Epoch(train) [117][ 720/2569] lr: 4.0000e-03 eta: 6:24:10 time: 0.2630 data_time: 0.0076 memory: 5828 grad_norm: 4.3690 loss: 1.6687 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6687 2023/06/05 14:41:56 - mmengine - INFO - Epoch(train) [117][ 740/2569] lr: 4.0000e-03 eta: 6:24:04 time: 0.2863 data_time: 0.0072 memory: 5828 grad_norm: 4.3182 loss: 2.0293 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0293 2023/06/05 14:42:01 - mmengine - INFO - Epoch(train) [117][ 760/2569] lr: 4.0000e-03 eta: 6:23:59 time: 0.2682 data_time: 0.0072 memory: 5828 grad_norm: 4.4598 loss: 1.8042 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8042 2023/06/05 14:42:06 - mmengine - INFO - Epoch(train) [117][ 780/2569] lr: 4.0000e-03 eta: 6:23:54 time: 0.2779 data_time: 0.0073 memory: 5828 grad_norm: 4.3545 loss: 2.0587 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0587 2023/06/05 14:42:12 - mmengine - INFO - Epoch(train) [117][ 800/2569] lr: 4.0000e-03 eta: 6:23:49 time: 0.2659 data_time: 0.0070 memory: 5828 grad_norm: 4.3165 loss: 1.8930 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8930 2023/06/05 14:42:17 - mmengine - INFO - Epoch(train) [117][ 820/2569] lr: 4.0000e-03 eta: 6:23:43 time: 0.2708 data_time: 0.0079 memory: 5828 grad_norm: 4.4268 loss: 1.7736 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7736 2023/06/05 14:42:23 - mmengine - INFO - Epoch(train) [117][ 840/2569] lr: 4.0000e-03 eta: 6:23:38 time: 0.2672 data_time: 0.0072 memory: 5828 grad_norm: 4.3235 loss: 1.6229 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6229 2023/06/05 14:42:28 - mmengine - INFO - Epoch(train) [117][ 860/2569] lr: 4.0000e-03 eta: 6:23:33 time: 0.2670 data_time: 0.0070 memory: 5828 grad_norm: 4.4128 loss: 1.8441 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8441 2023/06/05 14:42:33 - mmengine - INFO - Epoch(train) [117][ 880/2569] lr: 4.0000e-03 eta: 6:23:27 time: 0.2656 data_time: 0.0072 memory: 5828 grad_norm: 4.3701 loss: 1.8650 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8650 2023/06/05 14:42:39 - mmengine - INFO - Epoch(train) [117][ 900/2569] lr: 4.0000e-03 eta: 6:23:22 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 4.3640 loss: 1.8357 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8357 2023/06/05 14:42:44 - mmengine - INFO - Epoch(train) [117][ 920/2569] lr: 4.0000e-03 eta: 6:23:17 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 4.3425 loss: 1.8904 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8904 2023/06/05 14:42:49 - mmengine - INFO - Epoch(train) [117][ 940/2569] lr: 4.0000e-03 eta: 6:23:11 time: 0.2709 data_time: 0.0076 memory: 5828 grad_norm: 4.4381 loss: 1.6051 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6051 2023/06/05 14:42:55 - mmengine - INFO - Epoch(train) [117][ 960/2569] lr: 4.0000e-03 eta: 6:23:06 time: 0.2689 data_time: 0.0074 memory: 5828 grad_norm: 4.3700 loss: 1.6021 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6021 2023/06/05 14:43:00 - mmengine - INFO - Epoch(train) [117][ 980/2569] lr: 4.0000e-03 eta: 6:23:01 time: 0.2620 data_time: 0.0074 memory: 5828 grad_norm: 4.3671 loss: 1.6062 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6062 2023/06/05 14:43:04 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:43:05 - mmengine - INFO - Epoch(train) [117][1000/2569] lr: 4.0000e-03 eta: 6:22:55 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 4.3664 loss: 1.9398 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9398 2023/06/05 14:43:11 - mmengine - INFO - Epoch(train) [117][1020/2569] lr: 4.0000e-03 eta: 6:22:50 time: 0.2697 data_time: 0.0074 memory: 5828 grad_norm: 4.3664 loss: 2.0215 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0215 2023/06/05 14:43:16 - mmengine - INFO - Epoch(train) [117][1040/2569] lr: 4.0000e-03 eta: 6:22:45 time: 0.2730 data_time: 0.0072 memory: 5828 grad_norm: 4.4225 loss: 1.7954 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7954 2023/06/05 14:43:21 - mmengine - INFO - Epoch(train) [117][1060/2569] lr: 4.0000e-03 eta: 6:22:40 time: 0.2685 data_time: 0.0077 memory: 5828 grad_norm: 4.2944 loss: 2.0507 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0507 2023/06/05 14:43:27 - mmengine - INFO - Epoch(train) [117][1080/2569] lr: 4.0000e-03 eta: 6:22:34 time: 0.2668 data_time: 0.0078 memory: 5828 grad_norm: 4.3951 loss: 2.0008 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0008 2023/06/05 14:43:32 - mmengine - INFO - Epoch(train) [117][1100/2569] lr: 4.0000e-03 eta: 6:22:29 time: 0.2677 data_time: 0.0076 memory: 5828 grad_norm: 4.3804 loss: 2.0115 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0115 2023/06/05 14:43:37 - mmengine - INFO - Epoch(train) [117][1120/2569] lr: 4.0000e-03 eta: 6:22:24 time: 0.2607 data_time: 0.0073 memory: 5828 grad_norm: 4.3247 loss: 1.8698 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8698 2023/06/05 14:43:43 - mmengine - INFO - Epoch(train) [117][1140/2569] lr: 4.0000e-03 eta: 6:22:18 time: 0.2615 data_time: 0.0069 memory: 5828 grad_norm: 4.3591 loss: 1.6202 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6202 2023/06/05 14:43:48 - mmengine - INFO - Epoch(train) [117][1160/2569] lr: 4.0000e-03 eta: 6:22:13 time: 0.2617 data_time: 0.0069 memory: 5828 grad_norm: 4.3996 loss: 1.7546 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.7546 2023/06/05 14:43:53 - mmengine - INFO - Epoch(train) [117][1180/2569] lr: 4.0000e-03 eta: 6:22:07 time: 0.2613 data_time: 0.0073 memory: 5828 grad_norm: 4.4127 loss: 1.6836 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6836 2023/06/05 14:43:58 - mmengine - INFO - Epoch(train) [117][1200/2569] lr: 4.0000e-03 eta: 6:22:02 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 4.3930 loss: 1.8517 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8517 2023/06/05 14:44:04 - mmengine - INFO - Epoch(train) [117][1220/2569] lr: 4.0000e-03 eta: 6:21:57 time: 0.2831 data_time: 0.0074 memory: 5828 grad_norm: 4.2836 loss: 2.0261 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0261 2023/06/05 14:44:10 - mmengine - INFO - Epoch(train) [117][1240/2569] lr: 4.0000e-03 eta: 6:21:52 time: 0.2816 data_time: 0.0073 memory: 5828 grad_norm: 4.4625 loss: 1.6886 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6886 2023/06/05 14:44:15 - mmengine - INFO - Epoch(train) [117][1260/2569] lr: 4.0000e-03 eta: 6:21:46 time: 0.2668 data_time: 0.0076 memory: 5828 grad_norm: 4.3757 loss: 1.8171 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8171 2023/06/05 14:44:21 - mmengine - INFO - Epoch(train) [117][1280/2569] lr: 4.0000e-03 eta: 6:21:41 time: 0.2719 data_time: 0.0071 memory: 5828 grad_norm: 4.3290 loss: 1.4628 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4628 2023/06/05 14:44:26 - mmengine - INFO - Epoch(train) [117][1300/2569] lr: 4.0000e-03 eta: 6:21:36 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 4.3400 loss: 1.9322 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9322 2023/06/05 14:44:31 - mmengine - INFO - Epoch(train) [117][1320/2569] lr: 4.0000e-03 eta: 6:21:30 time: 0.2734 data_time: 0.0081 memory: 5828 grad_norm: 4.4367 loss: 1.9064 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9064 2023/06/05 14:44:37 - mmengine - INFO - Epoch(train) [117][1340/2569] lr: 4.0000e-03 eta: 6:21:25 time: 0.2678 data_time: 0.0073 memory: 5828 grad_norm: 4.3632 loss: 1.6272 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6272 2023/06/05 14:44:42 - mmengine - INFO - Epoch(train) [117][1360/2569] lr: 4.0000e-03 eta: 6:21:20 time: 0.2717 data_time: 0.0074 memory: 5828 grad_norm: 4.3987 loss: 1.8327 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8327 2023/06/05 14:44:48 - mmengine - INFO - Epoch(train) [117][1380/2569] lr: 4.0000e-03 eta: 6:21:15 time: 0.2677 data_time: 0.0077 memory: 5828 grad_norm: 4.3857 loss: 1.9028 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9028 2023/06/05 14:44:53 - mmengine - INFO - Epoch(train) [117][1400/2569] lr: 4.0000e-03 eta: 6:21:09 time: 0.2629 data_time: 0.0074 memory: 5828 grad_norm: 4.4035 loss: 1.9006 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9006 2023/06/05 14:44:58 - mmengine - INFO - Epoch(train) [117][1420/2569] lr: 4.0000e-03 eta: 6:21:04 time: 0.2697 data_time: 0.0074 memory: 5828 grad_norm: 4.4145 loss: 1.7085 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7085 2023/06/05 14:45:03 - mmengine - INFO - Epoch(train) [117][1440/2569] lr: 4.0000e-03 eta: 6:20:59 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 4.2573 loss: 1.5461 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5461 2023/06/05 14:45:09 - mmengine - INFO - Epoch(train) [117][1460/2569] lr: 4.0000e-03 eta: 6:20:53 time: 0.2709 data_time: 0.0072 memory: 5828 grad_norm: 4.3928 loss: 1.9667 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9667 2023/06/05 14:45:14 - mmengine - INFO - Epoch(train) [117][1480/2569] lr: 4.0000e-03 eta: 6:20:48 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 4.3585 loss: 1.7860 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7860 2023/06/05 14:45:19 - mmengine - INFO - Epoch(train) [117][1500/2569] lr: 4.0000e-03 eta: 6:20:43 time: 0.2660 data_time: 0.0072 memory: 5828 grad_norm: 4.4098 loss: 1.7334 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7334 2023/06/05 14:45:25 - mmengine - INFO - Epoch(train) [117][1520/2569] lr: 4.0000e-03 eta: 6:20:37 time: 0.2618 data_time: 0.0071 memory: 5828 grad_norm: 4.2496 loss: 1.9242 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9242 2023/06/05 14:45:30 - mmengine - INFO - Epoch(train) [117][1540/2569] lr: 4.0000e-03 eta: 6:20:32 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 4.3298 loss: 1.9074 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9074 2023/06/05 14:45:35 - mmengine - INFO - Epoch(train) [117][1560/2569] lr: 4.0000e-03 eta: 6:20:27 time: 0.2671 data_time: 0.0070 memory: 5828 grad_norm: 4.3827 loss: 2.0130 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0130 2023/06/05 14:45:41 - mmengine - INFO - Epoch(train) [117][1580/2569] lr: 4.0000e-03 eta: 6:20:21 time: 0.2684 data_time: 0.0071 memory: 5828 grad_norm: 4.3583 loss: 1.7470 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7470 2023/06/05 14:45:46 - mmengine - INFO - Epoch(train) [117][1600/2569] lr: 4.0000e-03 eta: 6:20:16 time: 0.2626 data_time: 0.0073 memory: 5828 grad_norm: 4.3768 loss: 1.6312 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6312 2023/06/05 14:45:51 - mmengine - INFO - Epoch(train) [117][1620/2569] lr: 4.0000e-03 eta: 6:20:11 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 4.3979 loss: 1.8474 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8474 2023/06/05 14:45:57 - mmengine - INFO - Epoch(train) [117][1640/2569] lr: 4.0000e-03 eta: 6:20:05 time: 0.2686 data_time: 0.0070 memory: 5828 grad_norm: 4.3533 loss: 1.4978 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4978 2023/06/05 14:46:02 - mmengine - INFO - Epoch(train) [117][1660/2569] lr: 4.0000e-03 eta: 6:20:00 time: 0.2682 data_time: 0.0072 memory: 5828 grad_norm: 4.3708 loss: 1.8850 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8850 2023/06/05 14:46:08 - mmengine - INFO - Epoch(train) [117][1680/2569] lr: 4.0000e-03 eta: 6:19:55 time: 0.2770 data_time: 0.0072 memory: 5828 grad_norm: 4.3877 loss: 1.6785 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6785 2023/06/05 14:46:13 - mmengine - INFO - Epoch(train) [117][1700/2569] lr: 4.0000e-03 eta: 6:19:49 time: 0.2720 data_time: 0.0076 memory: 5828 grad_norm: 4.4181 loss: 2.0241 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0241 2023/06/05 14:46:18 - mmengine - INFO - Epoch(train) [117][1720/2569] lr: 4.0000e-03 eta: 6:19:44 time: 0.2699 data_time: 0.0070 memory: 5828 grad_norm: 4.3398 loss: 1.7532 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7532 2023/06/05 14:46:24 - mmengine - INFO - Epoch(train) [117][1740/2569] lr: 4.0000e-03 eta: 6:19:39 time: 0.2593 data_time: 0.0076 memory: 5828 grad_norm: 4.3783 loss: 1.9860 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9860 2023/06/05 14:46:29 - mmengine - INFO - Epoch(train) [117][1760/2569] lr: 4.0000e-03 eta: 6:19:33 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 4.3915 loss: 1.8801 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8801 2023/06/05 14:46:34 - mmengine - INFO - Epoch(train) [117][1780/2569] lr: 4.0000e-03 eta: 6:19:28 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 4.3537 loss: 1.6454 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6454 2023/06/05 14:46:40 - mmengine - INFO - Epoch(train) [117][1800/2569] lr: 4.0000e-03 eta: 6:19:23 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 4.4135 loss: 1.9228 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9228 2023/06/05 14:46:45 - mmengine - INFO - Epoch(train) [117][1820/2569] lr: 4.0000e-03 eta: 6:19:17 time: 0.2660 data_time: 0.0071 memory: 5828 grad_norm: 4.4050 loss: 1.8799 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8799 2023/06/05 14:46:50 - mmengine - INFO - Epoch(train) [117][1840/2569] lr: 4.0000e-03 eta: 6:19:12 time: 0.2676 data_time: 0.0071 memory: 5828 grad_norm: 4.3966 loss: 1.7114 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7114 2023/06/05 14:46:56 - mmengine - INFO - Epoch(train) [117][1860/2569] lr: 4.0000e-03 eta: 6:19:07 time: 0.2757 data_time: 0.0070 memory: 5828 grad_norm: 4.3805 loss: 1.7857 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7857 2023/06/05 14:47:01 - mmengine - INFO - Epoch(train) [117][1880/2569] lr: 4.0000e-03 eta: 6:19:02 time: 0.2653 data_time: 0.0070 memory: 5828 grad_norm: 4.4388 loss: 2.1304 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1304 2023/06/05 14:47:06 - mmengine - INFO - Epoch(train) [117][1900/2569] lr: 4.0000e-03 eta: 6:18:56 time: 0.2618 data_time: 0.0071 memory: 5828 grad_norm: 4.3922 loss: 1.7251 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7251 2023/06/05 14:47:12 - mmengine - INFO - Epoch(train) [117][1920/2569] lr: 4.0000e-03 eta: 6:18:51 time: 0.2653 data_time: 0.0071 memory: 5828 grad_norm: 4.4785 loss: 1.6540 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6540 2023/06/05 14:47:17 - mmengine - INFO - Epoch(train) [117][1940/2569] lr: 4.0000e-03 eta: 6:18:46 time: 0.2638 data_time: 0.0071 memory: 5828 grad_norm: 4.4380 loss: 1.8763 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8763 2023/06/05 14:47:23 - mmengine - INFO - Epoch(train) [117][1960/2569] lr: 4.0000e-03 eta: 6:18:40 time: 0.2790 data_time: 0.0072 memory: 5828 grad_norm: 4.3533 loss: 1.7516 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7516 2023/06/05 14:47:28 - mmengine - INFO - Epoch(train) [117][1980/2569] lr: 4.0000e-03 eta: 6:18:35 time: 0.2607 data_time: 0.0075 memory: 5828 grad_norm: 4.3501 loss: 1.8062 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8062 2023/06/05 14:47:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:47:33 - mmengine - INFO - Epoch(train) [117][2000/2569] lr: 4.0000e-03 eta: 6:18:30 time: 0.2617 data_time: 0.0071 memory: 5828 grad_norm: 4.3990 loss: 1.7805 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7805 2023/06/05 14:47:38 - mmengine - INFO - Epoch(train) [117][2020/2569] lr: 4.0000e-03 eta: 6:18:24 time: 0.2625 data_time: 0.0071 memory: 5828 grad_norm: 4.4057 loss: 1.5735 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5735 2023/06/05 14:47:43 - mmengine - INFO - Epoch(train) [117][2040/2569] lr: 4.0000e-03 eta: 6:18:19 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 4.3518 loss: 1.7802 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.7802 2023/06/05 14:47:49 - mmengine - INFO - Epoch(train) [117][2060/2569] lr: 4.0000e-03 eta: 6:18:14 time: 0.2614 data_time: 0.0070 memory: 5828 grad_norm: 4.4197 loss: 1.7556 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7556 2023/06/05 14:47:54 - mmengine - INFO - Epoch(train) [117][2080/2569] lr: 4.0000e-03 eta: 6:18:08 time: 0.2632 data_time: 0.0076 memory: 5828 grad_norm: 4.3576 loss: 1.7990 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7990 2023/06/05 14:48:00 - mmengine - INFO - Epoch(train) [117][2100/2569] lr: 4.0000e-03 eta: 6:18:03 time: 0.2765 data_time: 0.0075 memory: 5828 grad_norm: 4.3391 loss: 1.8016 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8016 2023/06/05 14:48:05 - mmengine - INFO - Epoch(train) [117][2120/2569] lr: 4.0000e-03 eta: 6:17:58 time: 0.2734 data_time: 0.0074 memory: 5828 grad_norm: 4.4067 loss: 1.8847 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8847 2023/06/05 14:48:10 - mmengine - INFO - Epoch(train) [117][2140/2569] lr: 4.0000e-03 eta: 6:17:52 time: 0.2701 data_time: 0.0069 memory: 5828 grad_norm: 4.3679 loss: 1.6592 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6592 2023/06/05 14:48:16 - mmengine - INFO - Epoch(train) [117][2160/2569] lr: 4.0000e-03 eta: 6:17:47 time: 0.2601 data_time: 0.0077 memory: 5828 grad_norm: 4.4769 loss: 1.9175 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9175 2023/06/05 14:48:21 - mmengine - INFO - Epoch(train) [117][2180/2569] lr: 4.0000e-03 eta: 6:17:42 time: 0.2622 data_time: 0.0071 memory: 5828 grad_norm: 4.3039 loss: 1.4509 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4509 2023/06/05 14:48:26 - mmengine - INFO - Epoch(train) [117][2200/2569] lr: 4.0000e-03 eta: 6:17:36 time: 0.2649 data_time: 0.0072 memory: 5828 grad_norm: 4.4488 loss: 2.0723 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0723 2023/06/05 14:48:32 - mmengine - INFO - Epoch(train) [117][2220/2569] lr: 4.0000e-03 eta: 6:17:31 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 4.5332 loss: 1.6398 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6398 2023/06/05 14:48:37 - mmengine - INFO - Epoch(train) [117][2240/2569] lr: 4.0000e-03 eta: 6:17:26 time: 0.2750 data_time: 0.0072 memory: 5828 grad_norm: 4.4598 loss: 1.8830 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8830 2023/06/05 14:48:42 - mmengine - INFO - Epoch(train) [117][2260/2569] lr: 4.0000e-03 eta: 6:17:20 time: 0.2637 data_time: 0.0070 memory: 5828 grad_norm: 4.3865 loss: 1.6586 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6586 2023/06/05 14:48:48 - mmengine - INFO - Epoch(train) [117][2280/2569] lr: 4.0000e-03 eta: 6:17:15 time: 0.2669 data_time: 0.0077 memory: 5828 grad_norm: 4.5405 loss: 2.0184 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0184 2023/06/05 14:48:53 - mmengine - INFO - Epoch(train) [117][2300/2569] lr: 4.0000e-03 eta: 6:17:10 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 4.4319 loss: 1.9249 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9249 2023/06/05 14:48:58 - mmengine - INFO - Epoch(train) [117][2320/2569] lr: 4.0000e-03 eta: 6:17:04 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 4.3975 loss: 1.9296 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9296 2023/06/05 14:49:04 - mmengine - INFO - Epoch(train) [117][2340/2569] lr: 4.0000e-03 eta: 6:16:59 time: 0.2729 data_time: 0.0068 memory: 5828 grad_norm: 4.4688 loss: 1.6793 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6793 2023/06/05 14:49:09 - mmengine - INFO - Epoch(train) [117][2360/2569] lr: 4.0000e-03 eta: 6:16:54 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 4.3321 loss: 1.8220 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8220 2023/06/05 14:49:15 - mmengine - INFO - Epoch(train) [117][2380/2569] lr: 4.0000e-03 eta: 6:16:49 time: 0.2785 data_time: 0.0073 memory: 5828 grad_norm: 4.4206 loss: 1.8479 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8479 2023/06/05 14:49:20 - mmengine - INFO - Epoch(train) [117][2400/2569] lr: 4.0000e-03 eta: 6:16:43 time: 0.2609 data_time: 0.0072 memory: 5828 grad_norm: 4.3848 loss: 1.6265 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6265 2023/06/05 14:49:25 - mmengine - INFO - Epoch(train) [117][2420/2569] lr: 4.0000e-03 eta: 6:16:38 time: 0.2743 data_time: 0.0069 memory: 5828 grad_norm: 4.4142 loss: 2.2028 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2028 2023/06/05 14:49:30 - mmengine - INFO - Epoch(train) [117][2440/2569] lr: 4.0000e-03 eta: 6:16:33 time: 0.2593 data_time: 0.0071 memory: 5828 grad_norm: 4.3985 loss: 1.8480 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8480 2023/06/05 14:49:36 - mmengine - INFO - Epoch(train) [117][2460/2569] lr: 4.0000e-03 eta: 6:16:27 time: 0.2701 data_time: 0.0073 memory: 5828 grad_norm: 4.4751 loss: 1.9627 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9627 2023/06/05 14:49:41 - mmengine - INFO - Epoch(train) [117][2480/2569] lr: 4.0000e-03 eta: 6:16:22 time: 0.2706 data_time: 0.0075 memory: 5828 grad_norm: 4.4319 loss: 1.9627 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9627 2023/06/05 14:49:47 - mmengine - INFO - Epoch(train) [117][2500/2569] lr: 4.0000e-03 eta: 6:16:17 time: 0.2626 data_time: 0.0070 memory: 5828 grad_norm: 4.4683 loss: 1.9079 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9079 2023/06/05 14:49:52 - mmengine - INFO - Epoch(train) [117][2520/2569] lr: 4.0000e-03 eta: 6:16:11 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 4.4059 loss: 1.5191 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5191 2023/06/05 14:49:57 - mmengine - INFO - Epoch(train) [117][2540/2569] lr: 4.0000e-03 eta: 6:16:06 time: 0.2607 data_time: 0.0077 memory: 5828 grad_norm: 4.4639 loss: 1.4647 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4647 2023/06/05 14:50:02 - mmengine - INFO - Epoch(train) [117][2560/2569] lr: 4.0000e-03 eta: 6:16:01 time: 0.2640 data_time: 0.0077 memory: 5828 grad_norm: 4.4123 loss: 1.9210 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9210 2023/06/05 14:50:05 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:50:05 - mmengine - INFO - Epoch(train) [117][2569/2569] lr: 4.0000e-03 eta: 6:15:58 time: 0.2529 data_time: 0.0073 memory: 5828 grad_norm: 4.4645 loss: 1.6995 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.6995 2023/06/05 14:50:11 - mmengine - INFO - Epoch(train) [118][ 20/2569] lr: 4.0000e-03 eta: 6:15:53 time: 0.3307 data_time: 0.0535 memory: 5828 grad_norm: 4.3346 loss: 1.5889 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5889 2023/06/05 14:50:17 - mmengine - INFO - Epoch(train) [118][ 40/2569] lr: 4.0000e-03 eta: 6:15:48 time: 0.2742 data_time: 0.0072 memory: 5828 grad_norm: 4.3400 loss: 2.0726 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0726 2023/06/05 14:50:22 - mmengine - INFO - Epoch(train) [118][ 60/2569] lr: 4.0000e-03 eta: 6:15:43 time: 0.2714 data_time: 0.0078 memory: 5828 grad_norm: 4.3660 loss: 2.1720 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.1720 2023/06/05 14:50:28 - mmengine - INFO - Epoch(train) [118][ 80/2569] lr: 4.0000e-03 eta: 6:15:37 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 4.4288 loss: 1.7458 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7458 2023/06/05 14:50:33 - mmengine - INFO - Epoch(train) [118][ 100/2569] lr: 4.0000e-03 eta: 6:15:32 time: 0.2619 data_time: 0.0072 memory: 5828 grad_norm: 4.3736 loss: 2.2128 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2128 2023/06/05 14:50:38 - mmengine - INFO - Epoch(train) [118][ 120/2569] lr: 4.0000e-03 eta: 6:15:27 time: 0.2664 data_time: 0.0072 memory: 5828 grad_norm: 4.4298 loss: 1.7348 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7348 2023/06/05 14:50:44 - mmengine - INFO - Epoch(train) [118][ 140/2569] lr: 4.0000e-03 eta: 6:15:21 time: 0.2717 data_time: 0.0074 memory: 5828 grad_norm: 4.3619 loss: 1.8415 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8415 2023/06/05 14:50:49 - mmengine - INFO - Epoch(train) [118][ 160/2569] lr: 4.0000e-03 eta: 6:15:16 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 4.3741 loss: 1.9562 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9562 2023/06/05 14:50:54 - mmengine - INFO - Epoch(train) [118][ 180/2569] lr: 4.0000e-03 eta: 6:15:11 time: 0.2731 data_time: 0.0071 memory: 5828 grad_norm: 4.4609 loss: 1.8517 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8517 2023/06/05 14:51:00 - mmengine - INFO - Epoch(train) [118][ 200/2569] lr: 4.0000e-03 eta: 6:15:06 time: 0.2732 data_time: 0.0073 memory: 5828 grad_norm: 4.4220 loss: 1.9846 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9846 2023/06/05 14:51:05 - mmengine - INFO - Epoch(train) [118][ 220/2569] lr: 4.0000e-03 eta: 6:15:00 time: 0.2713 data_time: 0.0070 memory: 5828 grad_norm: 4.4010 loss: 1.5628 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5628 2023/06/05 14:51:11 - mmengine - INFO - Epoch(train) [118][ 240/2569] lr: 4.0000e-03 eta: 6:14:55 time: 0.2633 data_time: 0.0073 memory: 5828 grad_norm: 4.3732 loss: 1.6327 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6327 2023/06/05 14:51:16 - mmengine - INFO - Epoch(train) [118][ 260/2569] lr: 4.0000e-03 eta: 6:14:50 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 4.4148 loss: 1.8310 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8310 2023/06/05 14:51:21 - mmengine - INFO - Epoch(train) [118][ 280/2569] lr: 4.0000e-03 eta: 6:14:44 time: 0.2751 data_time: 0.0072 memory: 5828 grad_norm: 4.3735 loss: 1.4092 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4092 2023/06/05 14:51:27 - mmengine - INFO - Epoch(train) [118][ 300/2569] lr: 4.0000e-03 eta: 6:14:39 time: 0.2673 data_time: 0.0070 memory: 5828 grad_norm: 4.4523 loss: 1.7720 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7720 2023/06/05 14:51:32 - mmengine - INFO - Epoch(train) [118][ 320/2569] lr: 4.0000e-03 eta: 6:14:34 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 4.4117 loss: 1.6499 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6499 2023/06/05 14:51:37 - mmengine - INFO - Epoch(train) [118][ 340/2569] lr: 4.0000e-03 eta: 6:14:28 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 4.4678 loss: 2.1418 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.1418 2023/06/05 14:51:43 - mmengine - INFO - Epoch(train) [118][ 360/2569] lr: 4.0000e-03 eta: 6:14:23 time: 0.2729 data_time: 0.0074 memory: 5828 grad_norm: 4.3922 loss: 1.7117 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7117 2023/06/05 14:51:48 - mmengine - INFO - Epoch(train) [118][ 380/2569] lr: 4.0000e-03 eta: 6:14:18 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 4.4303 loss: 1.7696 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7696 2023/06/05 14:51:54 - mmengine - INFO - Epoch(train) [118][ 400/2569] lr: 4.0000e-03 eta: 6:14:12 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 4.4778 loss: 1.9129 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9129 2023/06/05 14:51:59 - mmengine - INFO - Epoch(train) [118][ 420/2569] lr: 4.0000e-03 eta: 6:14:07 time: 0.2665 data_time: 0.0073 memory: 5828 grad_norm: 4.4103 loss: 1.5878 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5878 2023/06/05 14:52:01 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:52:05 - mmengine - INFO - Epoch(train) [118][ 440/2569] lr: 4.0000e-03 eta: 6:14:02 time: 0.2812 data_time: 0.0074 memory: 5828 grad_norm: 4.4571 loss: 1.7954 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7954 2023/06/05 14:52:10 - mmengine - INFO - Epoch(train) [118][ 460/2569] lr: 4.0000e-03 eta: 6:13:57 time: 0.2762 data_time: 0.0073 memory: 5828 grad_norm: 4.4289 loss: 1.6827 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6827 2023/06/05 14:52:16 - mmengine - INFO - Epoch(train) [118][ 480/2569] lr: 4.0000e-03 eta: 6:13:51 time: 0.2723 data_time: 0.0075 memory: 5828 grad_norm: 4.3810 loss: 1.8784 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8784 2023/06/05 14:52:21 - mmengine - INFO - Epoch(train) [118][ 500/2569] lr: 4.0000e-03 eta: 6:13:46 time: 0.2712 data_time: 0.0073 memory: 5828 grad_norm: 4.3601 loss: 1.9193 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9193 2023/06/05 14:52:27 - mmengine - INFO - Epoch(train) [118][ 520/2569] lr: 4.0000e-03 eta: 6:13:41 time: 0.2843 data_time: 0.0072 memory: 5828 grad_norm: 4.4051 loss: 1.5601 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5601 2023/06/05 14:52:32 - mmengine - INFO - Epoch(train) [118][ 540/2569] lr: 4.0000e-03 eta: 6:13:35 time: 0.2695 data_time: 0.0075 memory: 5828 grad_norm: 4.4390 loss: 1.5141 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5141 2023/06/05 14:52:37 - mmengine - INFO - Epoch(train) [118][ 560/2569] lr: 4.0000e-03 eta: 6:13:30 time: 0.2644 data_time: 0.0078 memory: 5828 grad_norm: 4.3983 loss: 1.8158 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8158 2023/06/05 14:52:43 - mmengine - INFO - Epoch(train) [118][ 580/2569] lr: 4.0000e-03 eta: 6:13:25 time: 0.2690 data_time: 0.0080 memory: 5828 grad_norm: 4.4503 loss: 1.8077 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8077 2023/06/05 14:52:48 - mmengine - INFO - Epoch(train) [118][ 600/2569] lr: 4.0000e-03 eta: 6:13:20 time: 0.2658 data_time: 0.0079 memory: 5828 grad_norm: 4.4431 loss: 1.9607 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9607 2023/06/05 14:52:54 - mmengine - INFO - Epoch(train) [118][ 620/2569] lr: 4.0000e-03 eta: 6:13:14 time: 0.2697 data_time: 0.0070 memory: 5828 grad_norm: 4.3841 loss: 1.7448 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7448 2023/06/05 14:52:59 - mmengine - INFO - Epoch(train) [118][ 640/2569] lr: 4.0000e-03 eta: 6:13:09 time: 0.2640 data_time: 0.0071 memory: 5828 grad_norm: 4.3659 loss: 2.1611 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1611 2023/06/05 14:53:04 - mmengine - INFO - Epoch(train) [118][ 660/2569] lr: 4.0000e-03 eta: 6:13:04 time: 0.2670 data_time: 0.0071 memory: 5828 grad_norm: 4.4649 loss: 1.8361 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8361 2023/06/05 14:53:10 - mmengine - INFO - Epoch(train) [118][ 680/2569] lr: 4.0000e-03 eta: 6:12:58 time: 0.2680 data_time: 0.0072 memory: 5828 grad_norm: 4.4224 loss: 1.7801 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7801 2023/06/05 14:53:15 - mmengine - INFO - Epoch(train) [118][ 700/2569] lr: 4.0000e-03 eta: 6:12:53 time: 0.2697 data_time: 0.0071 memory: 5828 grad_norm: 4.4902 loss: 1.9238 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9238 2023/06/05 14:53:20 - mmengine - INFO - Epoch(train) [118][ 720/2569] lr: 4.0000e-03 eta: 6:12:48 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 4.3810 loss: 1.7904 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7904 2023/06/05 14:53:25 - mmengine - INFO - Epoch(train) [118][ 740/2569] lr: 4.0000e-03 eta: 6:12:42 time: 0.2642 data_time: 0.0080 memory: 5828 grad_norm: 4.5600 loss: 1.6670 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6670 2023/06/05 14:53:31 - mmengine - INFO - Epoch(train) [118][ 760/2569] lr: 4.0000e-03 eta: 6:12:37 time: 0.2622 data_time: 0.0074 memory: 5828 grad_norm: 4.4556 loss: 1.5907 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5907 2023/06/05 14:53:36 - mmengine - INFO - Epoch(train) [118][ 780/2569] lr: 4.0000e-03 eta: 6:12:32 time: 0.2698 data_time: 0.0072 memory: 5828 grad_norm: 4.5264 loss: 1.7850 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7850 2023/06/05 14:53:41 - mmengine - INFO - Epoch(train) [118][ 800/2569] lr: 4.0000e-03 eta: 6:12:26 time: 0.2653 data_time: 0.0072 memory: 5828 grad_norm: 4.5397 loss: 1.9256 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.9256 2023/06/05 14:53:47 - mmengine - INFO - Epoch(train) [118][ 820/2569] lr: 4.0000e-03 eta: 6:12:21 time: 0.2652 data_time: 0.0071 memory: 5828 grad_norm: 4.4229 loss: 1.9196 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9196 2023/06/05 14:53:52 - mmengine - INFO - Epoch(train) [118][ 840/2569] lr: 4.0000e-03 eta: 6:12:16 time: 0.2629 data_time: 0.0073 memory: 5828 grad_norm: 4.4117 loss: 2.1602 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1602 2023/06/05 14:53:57 - mmengine - INFO - Epoch(train) [118][ 860/2569] lr: 4.0000e-03 eta: 6:12:10 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 4.3831 loss: 1.4679 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.4679 2023/06/05 14:54:03 - mmengine - INFO - Epoch(train) [118][ 880/2569] lr: 4.0000e-03 eta: 6:12:05 time: 0.2789 data_time: 0.0071 memory: 5828 grad_norm: 4.3993 loss: 1.6092 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6092 2023/06/05 14:54:08 - mmengine - INFO - Epoch(train) [118][ 900/2569] lr: 4.0000e-03 eta: 6:12:00 time: 0.2610 data_time: 0.0073 memory: 5828 grad_norm: 4.5251 loss: 1.7312 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7312 2023/06/05 14:54:14 - mmengine - INFO - Epoch(train) [118][ 920/2569] lr: 4.0000e-03 eta: 6:11:54 time: 0.2734 data_time: 0.0072 memory: 5828 grad_norm: 4.4359 loss: 1.8588 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8588 2023/06/05 14:54:19 - mmengine - INFO - Epoch(train) [118][ 940/2569] lr: 4.0000e-03 eta: 6:11:49 time: 0.2654 data_time: 0.0074 memory: 5828 grad_norm: 4.4520 loss: 1.7334 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7334 2023/06/05 14:54:24 - mmengine - INFO - Epoch(train) [118][ 960/2569] lr: 4.0000e-03 eta: 6:11:44 time: 0.2654 data_time: 0.0077 memory: 5828 grad_norm: 4.3402 loss: 1.8828 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8828 2023/06/05 14:54:30 - mmengine - INFO - Epoch(train) [118][ 980/2569] lr: 4.0000e-03 eta: 6:11:38 time: 0.2613 data_time: 0.0077 memory: 5828 grad_norm: 4.4569 loss: 1.5517 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5517 2023/06/05 14:54:35 - mmengine - INFO - Epoch(train) [118][1000/2569] lr: 4.0000e-03 eta: 6:11:33 time: 0.2667 data_time: 0.0077 memory: 5828 grad_norm: 4.4643 loss: 1.9446 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9446 2023/06/05 14:54:40 - mmengine - INFO - Epoch(train) [118][1020/2569] lr: 4.0000e-03 eta: 6:11:28 time: 0.2603 data_time: 0.0073 memory: 5828 grad_norm: 4.4327 loss: 1.7174 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7174 2023/06/05 14:54:46 - mmengine - INFO - Epoch(train) [118][1040/2569] lr: 4.0000e-03 eta: 6:11:22 time: 0.2730 data_time: 0.0071 memory: 5828 grad_norm: 4.6216 loss: 1.9619 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9619 2023/06/05 14:54:51 - mmengine - INFO - Epoch(train) [118][1060/2569] lr: 4.0000e-03 eta: 6:11:17 time: 0.2601 data_time: 0.0071 memory: 5828 grad_norm: 4.4663 loss: 1.9164 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9164 2023/06/05 14:54:56 - mmengine - INFO - Epoch(train) [118][1080/2569] lr: 4.0000e-03 eta: 6:11:12 time: 0.2618 data_time: 0.0070 memory: 5828 grad_norm: 4.3590 loss: 1.8533 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8533 2023/06/05 14:55:01 - mmengine - INFO - Epoch(train) [118][1100/2569] lr: 4.0000e-03 eta: 6:11:06 time: 0.2668 data_time: 0.0068 memory: 5828 grad_norm: 4.4821 loss: 1.7705 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.7705 2023/06/05 14:55:07 - mmengine - INFO - Epoch(train) [118][1120/2569] lr: 4.0000e-03 eta: 6:11:01 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 4.5507 loss: 1.9641 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.9641 2023/06/05 14:55:12 - mmengine - INFO - Epoch(train) [118][1140/2569] lr: 4.0000e-03 eta: 6:10:56 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 4.4592 loss: 1.7160 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7160 2023/06/05 14:55:17 - mmengine - INFO - Epoch(train) [118][1160/2569] lr: 4.0000e-03 eta: 6:10:51 time: 0.2630 data_time: 0.0068 memory: 5828 grad_norm: 4.4550 loss: 1.9938 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9938 2023/06/05 14:55:23 - mmengine - INFO - Epoch(train) [118][1180/2569] lr: 4.0000e-03 eta: 6:10:45 time: 0.2747 data_time: 0.0070 memory: 5828 grad_norm: 4.5614 loss: 1.7601 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7601 2023/06/05 14:55:28 - mmengine - INFO - Epoch(train) [118][1200/2569] lr: 4.0000e-03 eta: 6:10:40 time: 0.2649 data_time: 0.0069 memory: 5828 grad_norm: 4.3952 loss: 2.0566 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0566 2023/06/05 14:55:34 - mmengine - INFO - Epoch(train) [118][1220/2569] lr: 4.0000e-03 eta: 6:10:35 time: 0.2718 data_time: 0.0073 memory: 5828 grad_norm: 4.4428 loss: 1.7640 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7640 2023/06/05 14:55:39 - mmengine - INFO - Epoch(train) [118][1240/2569] lr: 4.0000e-03 eta: 6:10:29 time: 0.2616 data_time: 0.0077 memory: 5828 grad_norm: 4.4071 loss: 1.6477 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6477 2023/06/05 14:55:44 - mmengine - INFO - Epoch(train) [118][1260/2569] lr: 4.0000e-03 eta: 6:10:24 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 4.4998 loss: 1.9839 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9839 2023/06/05 14:55:50 - mmengine - INFO - Epoch(train) [118][1280/2569] lr: 4.0000e-03 eta: 6:10:19 time: 0.2677 data_time: 0.0070 memory: 5828 grad_norm: 4.4343 loss: 2.0184 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0184 2023/06/05 14:55:55 - mmengine - INFO - Epoch(train) [118][1300/2569] lr: 4.0000e-03 eta: 6:10:13 time: 0.2684 data_time: 0.0070 memory: 5828 grad_norm: 4.4576 loss: 1.8582 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8582 2023/06/05 14:56:01 - mmengine - INFO - Epoch(train) [118][1320/2569] lr: 4.0000e-03 eta: 6:10:08 time: 0.2780 data_time: 0.0070 memory: 5828 grad_norm: 4.4031 loss: 1.7740 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7740 2023/06/05 14:56:06 - mmengine - INFO - Epoch(train) [118][1340/2569] lr: 4.0000e-03 eta: 6:10:03 time: 0.2673 data_time: 0.0072 memory: 5828 grad_norm: 4.4291 loss: 1.4351 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4351 2023/06/05 14:56:11 - mmengine - INFO - Epoch(train) [118][1360/2569] lr: 4.0000e-03 eta: 6:09:57 time: 0.2764 data_time: 0.0070 memory: 5828 grad_norm: 4.4347 loss: 1.8316 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8316 2023/06/05 14:56:17 - mmengine - INFO - Epoch(train) [118][1380/2569] lr: 4.0000e-03 eta: 6:09:52 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 4.5066 loss: 1.8672 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8672 2023/06/05 14:56:22 - mmengine - INFO - Epoch(train) [118][1400/2569] lr: 4.0000e-03 eta: 6:09:47 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 4.3974 loss: 1.7283 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7283 2023/06/05 14:56:28 - mmengine - INFO - Epoch(train) [118][1420/2569] lr: 4.0000e-03 eta: 6:09:42 time: 0.2780 data_time: 0.0071 memory: 5828 grad_norm: 4.3860 loss: 1.5820 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5820 2023/06/05 14:56:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 14:56:33 - mmengine - INFO - Epoch(train) [118][1440/2569] lr: 4.0000e-03 eta: 6:09:36 time: 0.2659 data_time: 0.0070 memory: 5828 grad_norm: 4.4543 loss: 1.7176 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7176 2023/06/05 14:56:38 - mmengine - INFO - Epoch(train) [118][1460/2569] lr: 4.0000e-03 eta: 6:09:31 time: 0.2702 data_time: 0.0072 memory: 5828 grad_norm: 4.3893 loss: 1.9051 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9051 2023/06/05 14:56:44 - mmengine - INFO - Epoch(train) [118][1480/2569] lr: 4.0000e-03 eta: 6:09:26 time: 0.2716 data_time: 0.0071 memory: 5828 grad_norm: 4.3401 loss: 1.4769 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.4769 2023/06/05 14:56:49 - mmengine - INFO - Epoch(train) [118][1500/2569] lr: 4.0000e-03 eta: 6:09:20 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 4.4002 loss: 1.6311 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6311 2023/06/05 14:56:55 - mmengine - INFO - Epoch(train) [118][1520/2569] lr: 4.0000e-03 eta: 6:09:15 time: 0.2670 data_time: 0.0072 memory: 5828 grad_norm: 4.5624 loss: 1.6766 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6766 2023/06/05 14:57:00 - mmengine - INFO - Epoch(train) [118][1540/2569] lr: 4.0000e-03 eta: 6:09:10 time: 0.2703 data_time: 0.0078 memory: 5828 grad_norm: 4.4171 loss: 1.9034 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9034 2023/06/05 14:57:06 - mmengine - INFO - Epoch(train) [118][1560/2569] lr: 4.0000e-03 eta: 6:09:05 time: 0.2935 data_time: 0.0073 memory: 5828 grad_norm: 4.4438 loss: 2.0004 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0004 2023/06/05 14:57:11 - mmengine - INFO - Epoch(train) [118][1580/2569] lr: 4.0000e-03 eta: 6:08:59 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 4.4526 loss: 1.9092 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9092 2023/06/05 14:57:17 - mmengine - INFO - Epoch(train) [118][1600/2569] lr: 4.0000e-03 eta: 6:08:54 time: 0.2754 data_time: 0.0077 memory: 5828 grad_norm: 4.3513 loss: 1.6558 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6558 2023/06/05 14:57:22 - mmengine - INFO - Epoch(train) [118][1620/2569] lr: 4.0000e-03 eta: 6:08:49 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 4.3892 loss: 2.0450 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.0450 2023/06/05 14:57:27 - mmengine - INFO - Epoch(train) [118][1640/2569] lr: 4.0000e-03 eta: 6:08:43 time: 0.2660 data_time: 0.0072 memory: 5828 grad_norm: 4.3791 loss: 1.9253 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9253 2023/06/05 14:57:32 - mmengine - INFO - Epoch(train) [118][1660/2569] lr: 4.0000e-03 eta: 6:08:38 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 4.4256 loss: 1.4716 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4716 2023/06/05 14:57:38 - mmengine - INFO - Epoch(train) [118][1680/2569] lr: 4.0000e-03 eta: 6:08:33 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 4.3986 loss: 1.6714 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6714 2023/06/05 14:57:43 - mmengine - INFO - Epoch(train) [118][1700/2569] lr: 4.0000e-03 eta: 6:08:27 time: 0.2600 data_time: 0.0074 memory: 5828 grad_norm: 4.4405 loss: 1.8984 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8984 2023/06/05 14:57:49 - mmengine - INFO - Epoch(train) [118][1720/2569] lr: 4.0000e-03 eta: 6:08:22 time: 0.2732 data_time: 0.0071 memory: 5828 grad_norm: 4.4632 loss: 1.9306 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9306 2023/06/05 14:57:54 - mmengine - INFO - Epoch(train) [118][1740/2569] lr: 4.0000e-03 eta: 6:08:17 time: 0.2666 data_time: 0.0071 memory: 5828 grad_norm: 4.3297 loss: 1.7256 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7256 2023/06/05 14:57:59 - mmengine - INFO - Epoch(train) [118][1760/2569] lr: 4.0000e-03 eta: 6:08:11 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 4.3816 loss: 1.8277 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8277 2023/06/05 14:58:04 - mmengine - INFO - Epoch(train) [118][1780/2569] lr: 4.0000e-03 eta: 6:08:06 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 4.3759 loss: 1.9191 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9191 2023/06/05 14:58:10 - mmengine - INFO - Epoch(train) [118][1800/2569] lr: 4.0000e-03 eta: 6:08:01 time: 0.2606 data_time: 0.0074 memory: 5828 grad_norm: 4.4737 loss: 1.7731 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7731 2023/06/05 14:58:15 - mmengine - INFO - Epoch(train) [118][1820/2569] lr: 4.0000e-03 eta: 6:07:55 time: 0.2646 data_time: 0.0072 memory: 5828 grad_norm: 4.3811 loss: 1.8723 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8723 2023/06/05 14:58:20 - mmengine - INFO - Epoch(train) [118][1840/2569] lr: 4.0000e-03 eta: 6:07:50 time: 0.2690 data_time: 0.0074 memory: 5828 grad_norm: 4.3738 loss: 1.9395 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9395 2023/06/05 14:58:26 - mmengine - INFO - Epoch(train) [118][1860/2569] lr: 4.0000e-03 eta: 6:07:45 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 4.3528 loss: 1.8824 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8824 2023/06/05 14:58:31 - mmengine - INFO - Epoch(train) [118][1880/2569] lr: 4.0000e-03 eta: 6:07:39 time: 0.2720 data_time: 0.0071 memory: 5828 grad_norm: 4.4423 loss: 2.0261 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0261 2023/06/05 14:58:36 - mmengine - INFO - Epoch(train) [118][1900/2569] lr: 4.0000e-03 eta: 6:07:34 time: 0.2685 data_time: 0.0071 memory: 5828 grad_norm: 4.5402 loss: 1.6975 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6975 2023/06/05 14:58:42 - mmengine - INFO - Epoch(train) [118][1920/2569] lr: 4.0000e-03 eta: 6:07:29 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 4.5126 loss: 1.9287 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9287 2023/06/05 14:58:47 - mmengine - INFO - Epoch(train) [118][1940/2569] lr: 4.0000e-03 eta: 6:07:23 time: 0.2656 data_time: 0.0069 memory: 5828 grad_norm: 4.3973 loss: 1.8182 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8182 2023/06/05 14:58:52 - mmengine - INFO - Epoch(train) [118][1960/2569] lr: 4.0000e-03 eta: 6:07:18 time: 0.2661 data_time: 0.0071 memory: 5828 grad_norm: 4.4553 loss: 1.8104 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8104 2023/06/05 14:58:58 - mmengine - INFO - Epoch(train) [118][1980/2569] lr: 4.0000e-03 eta: 6:07:13 time: 0.2638 data_time: 0.0071 memory: 5828 grad_norm: 4.3714 loss: 1.9983 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9983 2023/06/05 14:59:03 - mmengine - INFO - Epoch(train) [118][2000/2569] lr: 4.0000e-03 eta: 6:07:07 time: 0.2596 data_time: 0.0070 memory: 5828 grad_norm: 4.4834 loss: 1.7597 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7597 2023/06/05 14:59:08 - mmengine - INFO - Epoch(train) [118][2020/2569] lr: 4.0000e-03 eta: 6:07:02 time: 0.2632 data_time: 0.0071 memory: 5828 grad_norm: 4.4083 loss: 1.5877 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5877 2023/06/05 14:59:13 - mmengine - INFO - Epoch(train) [118][2040/2569] lr: 4.0000e-03 eta: 6:06:57 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 4.4537 loss: 1.9915 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9915 2023/06/05 14:59:19 - mmengine - INFO - Epoch(train) [118][2060/2569] lr: 4.0000e-03 eta: 6:06:51 time: 0.2736 data_time: 0.0069 memory: 5828 grad_norm: 4.3606 loss: 1.7919 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7919 2023/06/05 14:59:24 - mmengine - INFO - Epoch(train) [118][2080/2569] lr: 4.0000e-03 eta: 6:06:46 time: 0.2728 data_time: 0.0070 memory: 5828 grad_norm: 4.4316 loss: 2.0771 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0771 2023/06/05 14:59:30 - mmengine - INFO - Epoch(train) [118][2100/2569] lr: 4.0000e-03 eta: 6:06:41 time: 0.2655 data_time: 0.0073 memory: 5828 grad_norm: 4.3458 loss: 1.8780 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8780 2023/06/05 14:59:35 - mmengine - INFO - Epoch(train) [118][2120/2569] lr: 4.0000e-03 eta: 6:06:36 time: 0.2689 data_time: 0.0072 memory: 5828 grad_norm: 4.4210 loss: 1.7260 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7260 2023/06/05 14:59:40 - mmengine - INFO - Epoch(train) [118][2140/2569] lr: 4.0000e-03 eta: 6:06:30 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 4.5706 loss: 1.7196 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7196 2023/06/05 14:59:46 - mmengine - INFO - Epoch(train) [118][2160/2569] lr: 4.0000e-03 eta: 6:06:25 time: 0.2680 data_time: 0.0070 memory: 5828 grad_norm: 4.4695 loss: 1.6081 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6081 2023/06/05 14:59:51 - mmengine - INFO - Epoch(train) [118][2180/2569] lr: 4.0000e-03 eta: 6:06:20 time: 0.2719 data_time: 0.0070 memory: 5828 grad_norm: 4.3785 loss: 1.7301 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7301 2023/06/05 14:59:57 - mmengine - INFO - Epoch(train) [118][2200/2569] lr: 4.0000e-03 eta: 6:06:14 time: 0.2694 data_time: 0.0072 memory: 5828 grad_norm: 4.4049 loss: 1.5043 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5043 2023/06/05 15:00:02 - mmengine - INFO - Epoch(train) [118][2220/2569] lr: 4.0000e-03 eta: 6:06:09 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 4.4129 loss: 1.8512 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8512 2023/06/05 15:00:07 - mmengine - INFO - Epoch(train) [118][2240/2569] lr: 4.0000e-03 eta: 6:06:04 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 4.4086 loss: 1.8553 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8553 2023/06/05 15:00:13 - mmengine - INFO - Epoch(train) [118][2260/2569] lr: 4.0000e-03 eta: 6:05:58 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 4.4142 loss: 1.8661 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8661 2023/06/05 15:00:18 - mmengine - INFO - Epoch(train) [118][2280/2569] lr: 4.0000e-03 eta: 6:05:53 time: 0.2712 data_time: 0.0071 memory: 5828 grad_norm: 4.4033 loss: 1.8975 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8975 2023/06/05 15:00:23 - mmengine - INFO - Epoch(train) [118][2300/2569] lr: 4.0000e-03 eta: 6:05:48 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 4.4053 loss: 1.6433 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6433 2023/06/05 15:00:29 - mmengine - INFO - Epoch(train) [118][2320/2569] lr: 4.0000e-03 eta: 6:05:42 time: 0.2884 data_time: 0.0068 memory: 5828 grad_norm: 4.4978 loss: 1.9463 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9463 2023/06/05 15:00:34 - mmengine - INFO - Epoch(train) [118][2340/2569] lr: 4.0000e-03 eta: 6:05:37 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 4.3881 loss: 1.8973 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8973 2023/06/05 15:00:40 - mmengine - INFO - Epoch(train) [118][2360/2569] lr: 4.0000e-03 eta: 6:05:32 time: 0.2676 data_time: 0.0070 memory: 5828 grad_norm: 4.4301 loss: 1.7119 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7119 2023/06/05 15:00:45 - mmengine - INFO - Epoch(train) [118][2380/2569] lr: 4.0000e-03 eta: 6:05:27 time: 0.2678 data_time: 0.0072 memory: 5828 grad_norm: 4.4003 loss: 2.0797 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0797 2023/06/05 15:00:50 - mmengine - INFO - Epoch(train) [118][2400/2569] lr: 4.0000e-03 eta: 6:05:21 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 4.4056 loss: 2.0484 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0484 2023/06/05 15:00:56 - mmengine - INFO - Epoch(train) [118][2420/2569] lr: 4.0000e-03 eta: 6:05:16 time: 0.2622 data_time: 0.0071 memory: 5828 grad_norm: 4.3959 loss: 1.8475 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8475 2023/06/05 15:00:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:01:01 - mmengine - INFO - Epoch(train) [118][2440/2569] lr: 4.0000e-03 eta: 6:05:11 time: 0.2664 data_time: 0.0070 memory: 5828 grad_norm: 4.4147 loss: 1.6674 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6674 2023/06/05 15:01:06 - mmengine - INFO - Epoch(train) [118][2460/2569] lr: 4.0000e-03 eta: 6:05:05 time: 0.2596 data_time: 0.0076 memory: 5828 grad_norm: 4.5045 loss: 1.5071 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5071 2023/06/05 15:01:12 - mmengine - INFO - Epoch(train) [118][2480/2569] lr: 4.0000e-03 eta: 6:05:00 time: 0.2730 data_time: 0.0073 memory: 5828 grad_norm: 4.4661 loss: 1.8348 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8348 2023/06/05 15:01:17 - mmengine - INFO - Epoch(train) [118][2500/2569] lr: 4.0000e-03 eta: 6:04:55 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 4.4219 loss: 1.5401 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5401 2023/06/05 15:01:22 - mmengine - INFO - Epoch(train) [118][2520/2569] lr: 4.0000e-03 eta: 6:04:49 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 4.4189 loss: 1.9359 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9359 2023/06/05 15:01:28 - mmengine - INFO - Epoch(train) [118][2540/2569] lr: 4.0000e-03 eta: 6:04:44 time: 0.2652 data_time: 0.0071 memory: 5828 grad_norm: 4.5086 loss: 1.7186 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7186 2023/06/05 15:01:33 - mmengine - INFO - Epoch(train) [118][2560/2569] lr: 4.0000e-03 eta: 6:04:39 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 4.5965 loss: 1.7566 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7566 2023/06/05 15:01:35 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:01:35 - mmengine - INFO - Epoch(train) [118][2569/2569] lr: 4.0000e-03 eta: 6:04:36 time: 0.2563 data_time: 0.0069 memory: 5828 grad_norm: 4.4796 loss: 1.9214 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.9214 2023/06/05 15:01:42 - mmengine - INFO - Epoch(train) [119][ 20/2569] lr: 4.0000e-03 eta: 6:04:31 time: 0.3525 data_time: 0.0584 memory: 5828 grad_norm: 4.4430 loss: 1.7261 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7261 2023/06/05 15:01:48 - mmengine - INFO - Epoch(train) [119][ 40/2569] lr: 4.0000e-03 eta: 6:04:26 time: 0.2643 data_time: 0.0069 memory: 5828 grad_norm: 4.3574 loss: 1.9869 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9869 2023/06/05 15:01:53 - mmengine - INFO - Epoch(train) [119][ 60/2569] lr: 4.0000e-03 eta: 6:04:21 time: 0.2629 data_time: 0.0075 memory: 5828 grad_norm: 4.3100 loss: 1.5148 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5148 2023/06/05 15:01:58 - mmengine - INFO - Epoch(train) [119][ 80/2569] lr: 4.0000e-03 eta: 6:04:15 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 4.4636 loss: 2.0028 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0028 2023/06/05 15:02:03 - mmengine - INFO - Epoch(train) [119][ 100/2569] lr: 4.0000e-03 eta: 6:04:10 time: 0.2665 data_time: 0.0074 memory: 5828 grad_norm: 4.5403 loss: 1.5168 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5168 2023/06/05 15:02:09 - mmengine - INFO - Epoch(train) [119][ 120/2569] lr: 4.0000e-03 eta: 6:04:05 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 4.4613 loss: 1.6822 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6822 2023/06/05 15:02:14 - mmengine - INFO - Epoch(train) [119][ 140/2569] lr: 4.0000e-03 eta: 6:03:59 time: 0.2608 data_time: 0.0077 memory: 5828 grad_norm: 4.3974 loss: 1.4461 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4461 2023/06/05 15:02:19 - mmengine - INFO - Epoch(train) [119][ 160/2569] lr: 4.0000e-03 eta: 6:03:54 time: 0.2625 data_time: 0.0077 memory: 5828 grad_norm: 4.3244 loss: 1.6540 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6540 2023/06/05 15:02:25 - mmengine - INFO - Epoch(train) [119][ 180/2569] lr: 4.0000e-03 eta: 6:03:49 time: 0.2666 data_time: 0.0077 memory: 5828 grad_norm: 4.4848 loss: 1.8286 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8286 2023/06/05 15:02:30 - mmengine - INFO - Epoch(train) [119][ 200/2569] lr: 4.0000e-03 eta: 6:03:43 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 4.5460 loss: 1.9967 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9967 2023/06/05 15:02:35 - mmengine - INFO - Epoch(train) [119][ 220/2569] lr: 4.0000e-03 eta: 6:03:38 time: 0.2682 data_time: 0.0079 memory: 5828 grad_norm: 4.4321 loss: 2.2548 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.2548 2023/06/05 15:02:41 - mmengine - INFO - Epoch(train) [119][ 240/2569] lr: 4.0000e-03 eta: 6:03:33 time: 0.2657 data_time: 0.0075 memory: 5828 grad_norm: 4.4335 loss: 1.8425 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.8425 2023/06/05 15:02:46 - mmengine - INFO - Epoch(train) [119][ 260/2569] lr: 4.0000e-03 eta: 6:03:27 time: 0.2594 data_time: 0.0078 memory: 5828 grad_norm: 4.4720 loss: 1.5680 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5680 2023/06/05 15:02:51 - mmengine - INFO - Epoch(train) [119][ 280/2569] lr: 4.0000e-03 eta: 6:03:22 time: 0.2613 data_time: 0.0072 memory: 5828 grad_norm: 4.4138 loss: 1.9446 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9446 2023/06/05 15:02:56 - mmengine - INFO - Epoch(train) [119][ 300/2569] lr: 4.0000e-03 eta: 6:03:17 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 4.4061 loss: 1.6023 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6023 2023/06/05 15:03:02 - mmengine - INFO - Epoch(train) [119][ 320/2569] lr: 4.0000e-03 eta: 6:03:11 time: 0.2645 data_time: 0.0069 memory: 5828 grad_norm: 4.5046 loss: 1.8467 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8467 2023/06/05 15:03:07 - mmengine - INFO - Epoch(train) [119][ 340/2569] lr: 4.0000e-03 eta: 6:03:06 time: 0.2668 data_time: 0.0083 memory: 5828 grad_norm: 4.4122 loss: 1.6185 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6185 2023/06/05 15:03:13 - mmengine - INFO - Epoch(train) [119][ 360/2569] lr: 4.0000e-03 eta: 6:03:01 time: 0.2741 data_time: 0.0072 memory: 5828 grad_norm: 4.4580 loss: 1.6663 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6663 2023/06/05 15:03:18 - mmengine - INFO - Epoch(train) [119][ 380/2569] lr: 4.0000e-03 eta: 6:02:55 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 4.6211 loss: 1.8968 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8968 2023/06/05 15:03:23 - mmengine - INFO - Epoch(train) [119][ 400/2569] lr: 4.0000e-03 eta: 6:02:50 time: 0.2726 data_time: 0.0074 memory: 5828 grad_norm: 4.4066 loss: 1.5842 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5842 2023/06/05 15:03:29 - mmengine - INFO - Epoch(train) [119][ 420/2569] lr: 4.0000e-03 eta: 6:02:45 time: 0.2602 data_time: 0.0074 memory: 5828 grad_norm: 4.4313 loss: 2.0389 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0389 2023/06/05 15:03:34 - mmengine - INFO - Epoch(train) [119][ 440/2569] lr: 4.0000e-03 eta: 6:02:39 time: 0.2640 data_time: 0.0072 memory: 5828 grad_norm: 4.5552 loss: 1.6940 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6940 2023/06/05 15:03:39 - mmengine - INFO - Epoch(train) [119][ 460/2569] lr: 4.0000e-03 eta: 6:02:34 time: 0.2630 data_time: 0.0073 memory: 5828 grad_norm: 4.5038 loss: 1.7711 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7711 2023/06/05 15:03:45 - mmengine - INFO - Epoch(train) [119][ 480/2569] lr: 4.0000e-03 eta: 6:02:29 time: 0.2710 data_time: 0.0069 memory: 5828 grad_norm: 4.5278 loss: 1.7957 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7957 2023/06/05 15:03:50 - mmengine - INFO - Epoch(train) [119][ 500/2569] lr: 4.0000e-03 eta: 6:02:23 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 4.5001 loss: 1.7728 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7728 2023/06/05 15:03:55 - mmengine - INFO - Epoch(train) [119][ 520/2569] lr: 4.0000e-03 eta: 6:02:18 time: 0.2732 data_time: 0.0074 memory: 5828 grad_norm: 4.3843 loss: 1.7455 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7455 2023/06/05 15:04:01 - mmengine - INFO - Epoch(train) [119][ 540/2569] lr: 4.0000e-03 eta: 6:02:13 time: 0.2603 data_time: 0.0071 memory: 5828 grad_norm: 4.4120 loss: 1.6282 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6282 2023/06/05 15:04:06 - mmengine - INFO - Epoch(train) [119][ 560/2569] lr: 4.0000e-03 eta: 6:02:07 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 4.4741 loss: 1.4911 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4911 2023/06/05 15:04:11 - mmengine - INFO - Epoch(train) [119][ 580/2569] lr: 4.0000e-03 eta: 6:02:02 time: 0.2609 data_time: 0.0071 memory: 5828 grad_norm: 4.5560 loss: 1.8616 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8616 2023/06/05 15:04:16 - mmengine - INFO - Epoch(train) [119][ 600/2569] lr: 4.0000e-03 eta: 6:01:57 time: 0.2676 data_time: 0.0073 memory: 5828 grad_norm: 4.4053 loss: 1.7815 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7815 2023/06/05 15:04:22 - mmengine - INFO - Epoch(train) [119][ 620/2569] lr: 4.0000e-03 eta: 6:01:51 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 4.5112 loss: 1.7533 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7533 2023/06/05 15:04:27 - mmengine - INFO - Epoch(train) [119][ 640/2569] lr: 4.0000e-03 eta: 6:01:46 time: 0.2727 data_time: 0.0070 memory: 5828 grad_norm: 4.5581 loss: 1.7220 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7220 2023/06/05 15:04:32 - mmengine - INFO - Epoch(train) [119][ 660/2569] lr: 4.0000e-03 eta: 6:01:41 time: 0.2609 data_time: 0.0071 memory: 5828 grad_norm: 4.5454 loss: 1.8501 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8501 2023/06/05 15:04:38 - mmengine - INFO - Epoch(train) [119][ 680/2569] lr: 4.0000e-03 eta: 6:01:36 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 4.4246 loss: 1.6826 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6826 2023/06/05 15:04:43 - mmengine - INFO - Epoch(train) [119][ 700/2569] lr: 4.0000e-03 eta: 6:01:30 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 4.4519 loss: 1.7609 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7609 2023/06/05 15:04:48 - mmengine - INFO - Epoch(train) [119][ 720/2569] lr: 4.0000e-03 eta: 6:01:25 time: 0.2610 data_time: 0.0072 memory: 5828 grad_norm: 4.4975 loss: 2.0084 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0084 2023/06/05 15:04:54 - mmengine - INFO - Epoch(train) [119][ 740/2569] lr: 4.0000e-03 eta: 6:01:20 time: 0.2670 data_time: 0.0077 memory: 5828 grad_norm: 4.4678 loss: 1.9939 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9939 2023/06/05 15:04:59 - mmengine - INFO - Epoch(train) [119][ 760/2569] lr: 4.0000e-03 eta: 6:01:14 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 4.4590 loss: 1.9391 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9391 2023/06/05 15:05:04 - mmengine - INFO - Epoch(train) [119][ 780/2569] lr: 4.0000e-03 eta: 6:01:09 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 4.5157 loss: 1.6116 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6116 2023/06/05 15:05:10 - mmengine - INFO - Epoch(train) [119][ 800/2569] lr: 4.0000e-03 eta: 6:01:04 time: 0.2682 data_time: 0.0072 memory: 5828 grad_norm: 4.5893 loss: 1.9318 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9318 2023/06/05 15:05:15 - mmengine - INFO - Epoch(train) [119][ 820/2569] lr: 4.0000e-03 eta: 6:00:58 time: 0.2675 data_time: 0.0072 memory: 5828 grad_norm: 4.5389 loss: 1.9618 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9618 2023/06/05 15:05:20 - mmengine - INFO - Epoch(train) [119][ 840/2569] lr: 4.0000e-03 eta: 6:00:53 time: 0.2661 data_time: 0.0075 memory: 5828 grad_norm: 4.5424 loss: 1.6627 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6627 2023/06/05 15:05:25 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:05:26 - mmengine - INFO - Epoch(train) [119][ 860/2569] lr: 4.0000e-03 eta: 6:00:48 time: 0.2672 data_time: 0.0075 memory: 5828 grad_norm: 4.5422 loss: 1.8167 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8167 2023/06/05 15:05:31 - mmengine - INFO - Epoch(train) [119][ 880/2569] lr: 4.0000e-03 eta: 6:00:42 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 4.4814 loss: 1.7765 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7765 2023/06/05 15:05:36 - mmengine - INFO - Epoch(train) [119][ 900/2569] lr: 4.0000e-03 eta: 6:00:37 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 4.5169 loss: 1.8126 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8126 2023/06/05 15:05:42 - mmengine - INFO - Epoch(train) [119][ 920/2569] lr: 4.0000e-03 eta: 6:00:32 time: 0.2650 data_time: 0.0071 memory: 5828 grad_norm: 4.4713 loss: 1.6865 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6865 2023/06/05 15:05:47 - mmengine - INFO - Epoch(train) [119][ 940/2569] lr: 4.0000e-03 eta: 6:00:26 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 4.4945 loss: 1.7281 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7281 2023/06/05 15:05:52 - mmengine - INFO - Epoch(train) [119][ 960/2569] lr: 4.0000e-03 eta: 6:00:21 time: 0.2669 data_time: 0.0072 memory: 5828 grad_norm: 4.5055 loss: 1.8154 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8154 2023/06/05 15:05:58 - mmengine - INFO - Epoch(train) [119][ 980/2569] lr: 4.0000e-03 eta: 6:00:16 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 4.4076 loss: 1.8629 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8629 2023/06/05 15:06:03 - mmengine - INFO - Epoch(train) [119][1000/2569] lr: 4.0000e-03 eta: 6:00:10 time: 0.2715 data_time: 0.0070 memory: 5828 grad_norm: 4.4932 loss: 1.9147 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9147 2023/06/05 15:06:08 - mmengine - INFO - Epoch(train) [119][1020/2569] lr: 4.0000e-03 eta: 6:00:05 time: 0.2675 data_time: 0.0075 memory: 5828 grad_norm: 4.5595 loss: 1.7830 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7830 2023/06/05 15:06:14 - mmengine - INFO - Epoch(train) [119][1040/2569] lr: 4.0000e-03 eta: 6:00:00 time: 0.2668 data_time: 0.0070 memory: 5828 grad_norm: 4.4621 loss: 1.7969 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7969 2023/06/05 15:06:19 - mmengine - INFO - Epoch(train) [119][1060/2569] lr: 4.0000e-03 eta: 5:59:54 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 4.4383 loss: 1.7583 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7583 2023/06/05 15:06:24 - mmengine - INFO - Epoch(train) [119][1080/2569] lr: 4.0000e-03 eta: 5:59:49 time: 0.2684 data_time: 0.0071 memory: 5828 grad_norm: 4.5340 loss: 1.9247 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9247 2023/06/05 15:06:30 - mmengine - INFO - Epoch(train) [119][1100/2569] lr: 4.0000e-03 eta: 5:59:44 time: 0.2720 data_time: 0.0070 memory: 5828 grad_norm: 4.5919 loss: 1.8755 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8755 2023/06/05 15:06:35 - mmengine - INFO - Epoch(train) [119][1120/2569] lr: 4.0000e-03 eta: 5:59:38 time: 0.2619 data_time: 0.0072 memory: 5828 grad_norm: 4.4942 loss: 1.6165 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6165 2023/06/05 15:06:40 - mmengine - INFO - Epoch(train) [119][1140/2569] lr: 4.0000e-03 eta: 5:59:33 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 4.4966 loss: 1.7958 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7958 2023/06/05 15:06:46 - mmengine - INFO - Epoch(train) [119][1160/2569] lr: 4.0000e-03 eta: 5:59:28 time: 0.2720 data_time: 0.0072 memory: 5828 grad_norm: 4.4482 loss: 1.7311 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7311 2023/06/05 15:06:51 - mmengine - INFO - Epoch(train) [119][1180/2569] lr: 4.0000e-03 eta: 5:59:22 time: 0.2641 data_time: 0.0076 memory: 5828 grad_norm: 4.5215 loss: 1.7169 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7169 2023/06/05 15:06:57 - mmengine - INFO - Epoch(train) [119][1200/2569] lr: 4.0000e-03 eta: 5:59:17 time: 0.2688 data_time: 0.0072 memory: 5828 grad_norm: 4.5032 loss: 1.4181 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4181 2023/06/05 15:07:02 - mmengine - INFO - Epoch(train) [119][1220/2569] lr: 4.0000e-03 eta: 5:59:12 time: 0.2657 data_time: 0.0070 memory: 5828 grad_norm: 4.4932 loss: 2.0428 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0428 2023/06/05 15:07:07 - mmengine - INFO - Epoch(train) [119][1240/2569] lr: 4.0000e-03 eta: 5:59:07 time: 0.2683 data_time: 0.0071 memory: 5828 grad_norm: 4.4002 loss: 1.9822 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9822 2023/06/05 15:07:13 - mmengine - INFO - Epoch(train) [119][1260/2569] lr: 4.0000e-03 eta: 5:59:01 time: 0.2657 data_time: 0.0074 memory: 5828 grad_norm: 4.5234 loss: 1.9065 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9065 2023/06/05 15:07:18 - mmengine - INFO - Epoch(train) [119][1280/2569] lr: 4.0000e-03 eta: 5:58:56 time: 0.2608 data_time: 0.0072 memory: 5828 grad_norm: 4.5702 loss: 1.9876 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9876 2023/06/05 15:07:23 - mmengine - INFO - Epoch(train) [119][1300/2569] lr: 4.0000e-03 eta: 5:58:51 time: 0.2781 data_time: 0.0079 memory: 5828 grad_norm: 4.4440 loss: 1.8251 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8251 2023/06/05 15:07:29 - mmengine - INFO - Epoch(train) [119][1320/2569] lr: 4.0000e-03 eta: 5:58:45 time: 0.2682 data_time: 0.0078 memory: 5828 grad_norm: 4.4835 loss: 1.9263 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9263 2023/06/05 15:07:34 - mmengine - INFO - Epoch(train) [119][1340/2569] lr: 4.0000e-03 eta: 5:58:40 time: 0.2644 data_time: 0.0070 memory: 5828 grad_norm: 4.5694 loss: 1.9282 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9282 2023/06/05 15:07:39 - mmengine - INFO - Epoch(train) [119][1360/2569] lr: 4.0000e-03 eta: 5:58:35 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 4.4522 loss: 2.1049 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.1049 2023/06/05 15:07:45 - mmengine - INFO - Epoch(train) [119][1380/2569] lr: 4.0000e-03 eta: 5:58:29 time: 0.2717 data_time: 0.0071 memory: 5828 grad_norm: 4.4815 loss: 1.8513 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8513 2023/06/05 15:07:50 - mmengine - INFO - Epoch(train) [119][1400/2569] lr: 4.0000e-03 eta: 5:58:24 time: 0.2752 data_time: 0.0073 memory: 5828 grad_norm: 4.4964 loss: 2.0107 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0107 2023/06/05 15:07:56 - mmengine - INFO - Epoch(train) [119][1420/2569] lr: 4.0000e-03 eta: 5:58:19 time: 0.2699 data_time: 0.0072 memory: 5828 grad_norm: 4.4711 loss: 1.7110 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7110 2023/06/05 15:08:01 - mmengine - INFO - Epoch(train) [119][1440/2569] lr: 4.0000e-03 eta: 5:58:13 time: 0.2602 data_time: 0.0072 memory: 5828 grad_norm: 4.4801 loss: 1.7790 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7790 2023/06/05 15:08:06 - mmengine - INFO - Epoch(train) [119][1460/2569] lr: 4.0000e-03 eta: 5:58:08 time: 0.2712 data_time: 0.0073 memory: 5828 grad_norm: 4.5260 loss: 1.7949 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7949 2023/06/05 15:08:12 - mmengine - INFO - Epoch(train) [119][1480/2569] lr: 4.0000e-03 eta: 5:58:03 time: 0.2629 data_time: 0.0078 memory: 5828 grad_norm: 4.5442 loss: 1.5470 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5470 2023/06/05 15:08:17 - mmengine - INFO - Epoch(train) [119][1500/2569] lr: 4.0000e-03 eta: 5:57:57 time: 0.2665 data_time: 0.0071 memory: 5828 grad_norm: 4.4176 loss: 1.7189 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7189 2023/06/05 15:08:22 - mmengine - INFO - Epoch(train) [119][1520/2569] lr: 4.0000e-03 eta: 5:57:52 time: 0.2639 data_time: 0.0072 memory: 5828 grad_norm: 4.5451 loss: 1.8589 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8589 2023/06/05 15:08:27 - mmengine - INFO - Epoch(train) [119][1540/2569] lr: 4.0000e-03 eta: 5:57:47 time: 0.2610 data_time: 0.0071 memory: 5828 grad_norm: 4.5555 loss: 1.7384 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7384 2023/06/05 15:08:33 - mmengine - INFO - Epoch(train) [119][1560/2569] lr: 4.0000e-03 eta: 5:57:41 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 4.6347 loss: 2.0372 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0372 2023/06/05 15:08:38 - mmengine - INFO - Epoch(train) [119][1580/2569] lr: 4.0000e-03 eta: 5:57:36 time: 0.2752 data_time: 0.0073 memory: 5828 grad_norm: 4.5297 loss: 1.6536 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.6536 2023/06/05 15:08:43 - mmengine - INFO - Epoch(train) [119][1600/2569] lr: 4.0000e-03 eta: 5:57:31 time: 0.2607 data_time: 0.0072 memory: 5828 grad_norm: 4.5031 loss: 1.8265 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8265 2023/06/05 15:08:49 - mmengine - INFO - Epoch(train) [119][1620/2569] lr: 4.0000e-03 eta: 5:57:25 time: 0.2683 data_time: 0.0074 memory: 5828 grad_norm: 4.4700 loss: 1.7904 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7904 2023/06/05 15:08:54 - mmengine - INFO - Epoch(train) [119][1640/2569] lr: 4.0000e-03 eta: 5:57:20 time: 0.2602 data_time: 0.0071 memory: 5828 grad_norm: 4.4903 loss: 1.8862 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8862 2023/06/05 15:08:59 - mmengine - INFO - Epoch(train) [119][1660/2569] lr: 4.0000e-03 eta: 5:57:15 time: 0.2725 data_time: 0.0070 memory: 5828 grad_norm: 4.4582 loss: 1.7626 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7626 2023/06/05 15:09:05 - mmengine - INFO - Epoch(train) [119][1680/2569] lr: 4.0000e-03 eta: 5:57:09 time: 0.2616 data_time: 0.0072 memory: 5828 grad_norm: 4.4379 loss: 2.0639 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.0639 2023/06/05 15:09:10 - mmengine - INFO - Epoch(train) [119][1700/2569] lr: 4.0000e-03 eta: 5:57:04 time: 0.2620 data_time: 0.0074 memory: 5828 grad_norm: 4.5494 loss: 2.0922 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0922 2023/06/05 15:09:15 - mmengine - INFO - Epoch(train) [119][1720/2569] lr: 4.0000e-03 eta: 5:56:59 time: 0.2605 data_time: 0.0072 memory: 5828 grad_norm: 4.5512 loss: 1.7055 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7055 2023/06/05 15:09:21 - mmengine - INFO - Epoch(train) [119][1740/2569] lr: 4.0000e-03 eta: 5:56:53 time: 0.2723 data_time: 0.0071 memory: 5828 grad_norm: 4.4655 loss: 1.6148 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6148 2023/06/05 15:09:26 - mmengine - INFO - Epoch(train) [119][1760/2569] lr: 4.0000e-03 eta: 5:56:48 time: 0.2640 data_time: 0.0069 memory: 5828 grad_norm: 4.5297 loss: 1.9354 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9354 2023/06/05 15:09:31 - mmengine - INFO - Epoch(train) [119][1780/2569] lr: 4.0000e-03 eta: 5:56:43 time: 0.2665 data_time: 0.0072 memory: 5828 grad_norm: 4.4982 loss: 1.6500 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6500 2023/06/05 15:09:37 - mmengine - INFO - Epoch(train) [119][1800/2569] lr: 4.0000e-03 eta: 5:56:38 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 4.4925 loss: 1.9124 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9124 2023/06/05 15:09:42 - mmengine - INFO - Epoch(train) [119][1820/2569] lr: 4.0000e-03 eta: 5:56:32 time: 0.2631 data_time: 0.0069 memory: 5828 grad_norm: 4.5619 loss: 1.9662 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9662 2023/06/05 15:09:47 - mmengine - INFO - Epoch(train) [119][1840/2569] lr: 4.0000e-03 eta: 5:56:27 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 4.4599 loss: 1.7425 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7425 2023/06/05 15:09:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:09:53 - mmengine - INFO - Epoch(train) [119][1860/2569] lr: 4.0000e-03 eta: 5:56:22 time: 0.2701 data_time: 0.0071 memory: 5828 grad_norm: 4.4392 loss: 1.8109 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.8109 2023/06/05 15:09:58 - mmengine - INFO - Epoch(train) [119][1880/2569] lr: 4.0000e-03 eta: 5:56:16 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 4.5426 loss: 1.7609 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7609 2023/06/05 15:10:03 - mmengine - INFO - Epoch(train) [119][1900/2569] lr: 4.0000e-03 eta: 5:56:11 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 4.5645 loss: 1.7031 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7031 2023/06/05 15:10:09 - mmengine - INFO - Epoch(train) [119][1920/2569] lr: 4.0000e-03 eta: 5:56:06 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 4.4822 loss: 1.8311 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8311 2023/06/05 15:10:14 - mmengine - INFO - Epoch(train) [119][1940/2569] lr: 4.0000e-03 eta: 5:56:00 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 4.4880 loss: 1.8002 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8002 2023/06/05 15:10:19 - mmengine - INFO - Epoch(train) [119][1960/2569] lr: 4.0000e-03 eta: 5:55:55 time: 0.2731 data_time: 0.0070 memory: 5828 grad_norm: 4.4786 loss: 1.8649 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8649 2023/06/05 15:10:25 - mmengine - INFO - Epoch(train) [119][1980/2569] lr: 4.0000e-03 eta: 5:55:50 time: 0.2695 data_time: 0.0073 memory: 5828 grad_norm: 4.4851 loss: 1.5201 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5201 2023/06/05 15:10:30 - mmengine - INFO - Epoch(train) [119][2000/2569] lr: 4.0000e-03 eta: 5:55:44 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 4.5268 loss: 1.9408 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9408 2023/06/05 15:10:36 - mmengine - INFO - Epoch(train) [119][2020/2569] lr: 4.0000e-03 eta: 5:55:39 time: 0.2717 data_time: 0.0072 memory: 5828 grad_norm: 4.5017 loss: 1.9824 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9824 2023/06/05 15:10:41 - mmengine - INFO - Epoch(train) [119][2040/2569] lr: 4.0000e-03 eta: 5:55:34 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 4.4981 loss: 1.6907 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6907 2023/06/05 15:10:46 - mmengine - INFO - Epoch(train) [119][2060/2569] lr: 4.0000e-03 eta: 5:55:28 time: 0.2725 data_time: 0.0076 memory: 5828 grad_norm: 4.5429 loss: 1.8140 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8140 2023/06/05 15:10:52 - mmengine - INFO - Epoch(train) [119][2080/2569] lr: 4.0000e-03 eta: 5:55:23 time: 0.2612 data_time: 0.0068 memory: 5828 grad_norm: 4.6053 loss: 2.1690 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1690 2023/06/05 15:10:57 - mmengine - INFO - Epoch(train) [119][2100/2569] lr: 4.0000e-03 eta: 5:55:18 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 4.6106 loss: 2.0080 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0080 2023/06/05 15:11:02 - mmengine - INFO - Epoch(train) [119][2120/2569] lr: 4.0000e-03 eta: 5:55:12 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 4.5502 loss: 1.9920 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9920 2023/06/05 15:11:08 - mmengine - INFO - Epoch(train) [119][2140/2569] lr: 4.0000e-03 eta: 5:55:07 time: 0.2755 data_time: 0.0072 memory: 5828 grad_norm: 4.5308 loss: 1.9096 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9096 2023/06/05 15:11:13 - mmengine - INFO - Epoch(train) [119][2160/2569] lr: 4.0000e-03 eta: 5:55:02 time: 0.2653 data_time: 0.0072 memory: 5828 grad_norm: 4.5503 loss: 1.8388 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8388 2023/06/05 15:11:19 - mmengine - INFO - Epoch(train) [119][2180/2569] lr: 4.0000e-03 eta: 5:54:57 time: 0.2636 data_time: 0.0071 memory: 5828 grad_norm: 4.5322 loss: 1.7383 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7383 2023/06/05 15:11:24 - mmengine - INFO - Epoch(train) [119][2200/2569] lr: 4.0000e-03 eta: 5:54:51 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 4.5809 loss: 1.9294 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9294 2023/06/05 15:11:29 - mmengine - INFO - Epoch(train) [119][2220/2569] lr: 4.0000e-03 eta: 5:54:46 time: 0.2664 data_time: 0.0071 memory: 5828 grad_norm: 4.5488 loss: 1.7832 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7832 2023/06/05 15:11:35 - mmengine - INFO - Epoch(train) [119][2240/2569] lr: 4.0000e-03 eta: 5:54:41 time: 0.2724 data_time: 0.0072 memory: 5828 grad_norm: 4.5314 loss: 1.9828 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9828 2023/06/05 15:11:40 - mmengine - INFO - Epoch(train) [119][2260/2569] lr: 4.0000e-03 eta: 5:54:35 time: 0.2656 data_time: 0.0072 memory: 5828 grad_norm: 4.5476 loss: 1.7442 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7442 2023/06/05 15:11:45 - mmengine - INFO - Epoch(train) [119][2280/2569] lr: 4.0000e-03 eta: 5:54:30 time: 0.2748 data_time: 0.0073 memory: 5828 grad_norm: 4.4663 loss: 1.8775 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8775 2023/06/05 15:11:51 - mmengine - INFO - Epoch(train) [119][2300/2569] lr: 4.0000e-03 eta: 5:54:25 time: 0.2714 data_time: 0.0081 memory: 5828 grad_norm: 4.5512 loss: 1.5845 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5845 2023/06/05 15:11:56 - mmengine - INFO - Epoch(train) [119][2320/2569] lr: 4.0000e-03 eta: 5:54:19 time: 0.2701 data_time: 0.0079 memory: 5828 grad_norm: 4.4125 loss: 1.7231 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7231 2023/06/05 15:12:02 - mmengine - INFO - Epoch(train) [119][2340/2569] lr: 4.0000e-03 eta: 5:54:14 time: 0.2613 data_time: 0.0069 memory: 5828 grad_norm: 4.4964 loss: 1.5352 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5352 2023/06/05 15:12:07 - mmengine - INFO - Epoch(train) [119][2360/2569] lr: 4.0000e-03 eta: 5:54:09 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 4.4324 loss: 2.1552 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.1552 2023/06/05 15:12:12 - mmengine - INFO - Epoch(train) [119][2380/2569] lr: 4.0000e-03 eta: 5:54:03 time: 0.2735 data_time: 0.0073 memory: 5828 grad_norm: 4.4386 loss: 1.5713 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.5713 2023/06/05 15:12:18 - mmengine - INFO - Epoch(train) [119][2400/2569] lr: 4.0000e-03 eta: 5:53:58 time: 0.2655 data_time: 0.0072 memory: 5828 grad_norm: 4.5453 loss: 1.8932 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8932 2023/06/05 15:12:23 - mmengine - INFO - Epoch(train) [119][2420/2569] lr: 4.0000e-03 eta: 5:53:53 time: 0.2684 data_time: 0.0083 memory: 5828 grad_norm: 4.4382 loss: 1.4777 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4777 2023/06/05 15:12:28 - mmengine - INFO - Epoch(train) [119][2440/2569] lr: 4.0000e-03 eta: 5:53:48 time: 0.2659 data_time: 0.0076 memory: 5828 grad_norm: 4.4773 loss: 1.5999 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5999 2023/06/05 15:12:34 - mmengine - INFO - Epoch(train) [119][2460/2569] lr: 4.0000e-03 eta: 5:53:42 time: 0.2618 data_time: 0.0070 memory: 5828 grad_norm: 4.4266 loss: 2.0192 top1_acc: 0.0000 top5_acc: 0.7500 loss_cls: 2.0192 2023/06/05 15:12:39 - mmengine - INFO - Epoch(train) [119][2480/2569] lr: 4.0000e-03 eta: 5:53:37 time: 0.2615 data_time: 0.0071 memory: 5828 grad_norm: 4.5793 loss: 1.9687 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9687 2023/06/05 15:12:44 - mmengine - INFO - Epoch(train) [119][2500/2569] lr: 4.0000e-03 eta: 5:53:31 time: 0.2605 data_time: 0.0075 memory: 5828 grad_norm: 4.5233 loss: 1.7575 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7575 2023/06/05 15:12:50 - mmengine - INFO - Epoch(train) [119][2520/2569] lr: 4.0000e-03 eta: 5:53:26 time: 0.2684 data_time: 0.0069 memory: 5828 grad_norm: 4.5223 loss: 1.3144 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3144 2023/06/05 15:12:55 - mmengine - INFO - Epoch(train) [119][2540/2569] lr: 4.0000e-03 eta: 5:53:21 time: 0.2718 data_time: 0.0070 memory: 5828 grad_norm: 4.4535 loss: 1.7630 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7630 2023/06/05 15:13:00 - mmengine - INFO - Epoch(train) [119][2560/2569] lr: 4.0000e-03 eta: 5:53:16 time: 0.2603 data_time: 0.0070 memory: 5828 grad_norm: 4.4756 loss: 1.9074 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9074 2023/06/05 15:13:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:13:02 - mmengine - INFO - Epoch(train) [119][2569/2569] lr: 4.0000e-03 eta: 5:53:13 time: 0.2535 data_time: 0.0068 memory: 5828 grad_norm: 4.5026 loss: 1.9935 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.9935 2023/06/05 15:13:09 - mmengine - INFO - Epoch(train) [120][ 20/2569] lr: 4.0000e-03 eta: 5:53:08 time: 0.3347 data_time: 0.0479 memory: 5828 grad_norm: 4.4460 loss: 1.8126 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8126 2023/06/05 15:13:15 - mmengine - INFO - Epoch(train) [120][ 40/2569] lr: 4.0000e-03 eta: 5:53:03 time: 0.2742 data_time: 0.0073 memory: 5828 grad_norm: 4.4809 loss: 2.0063 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0063 2023/06/05 15:13:20 - mmengine - INFO - Epoch(train) [120][ 60/2569] lr: 4.0000e-03 eta: 5:52:58 time: 0.2667 data_time: 0.0079 memory: 5828 grad_norm: 4.3946 loss: 1.7945 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7945 2023/06/05 15:13:25 - mmengine - INFO - Epoch(train) [120][ 80/2569] lr: 4.0000e-03 eta: 5:52:52 time: 0.2734 data_time: 0.0073 memory: 5828 grad_norm: 4.5576 loss: 1.6902 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6902 2023/06/05 15:13:31 - mmengine - INFO - Epoch(train) [120][ 100/2569] lr: 4.0000e-03 eta: 5:52:47 time: 0.2737 data_time: 0.0070 memory: 5828 grad_norm: 4.4877 loss: 1.7632 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7632 2023/06/05 15:13:36 - mmengine - INFO - Epoch(train) [120][ 120/2569] lr: 4.0000e-03 eta: 5:52:42 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 4.5359 loss: 1.7880 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7880 2023/06/05 15:13:42 - mmengine - INFO - Epoch(train) [120][ 140/2569] lr: 4.0000e-03 eta: 5:52:36 time: 0.2753 data_time: 0.0072 memory: 5828 grad_norm: 4.5787 loss: 1.8539 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8539 2023/06/05 15:13:47 - mmengine - INFO - Epoch(train) [120][ 160/2569] lr: 4.0000e-03 eta: 5:52:31 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 4.6481 loss: 1.6685 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6685 2023/06/05 15:13:53 - mmengine - INFO - Epoch(train) [120][ 180/2569] lr: 4.0000e-03 eta: 5:52:26 time: 0.2823 data_time: 0.0071 memory: 5828 grad_norm: 4.5420 loss: 1.9377 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9377 2023/06/05 15:13:58 - mmengine - INFO - Epoch(train) [120][ 200/2569] lr: 4.0000e-03 eta: 5:52:20 time: 0.2629 data_time: 0.0079 memory: 5828 grad_norm: 4.5154 loss: 1.7772 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7772 2023/06/05 15:14:03 - mmengine - INFO - Epoch(train) [120][ 220/2569] lr: 4.0000e-03 eta: 5:52:15 time: 0.2690 data_time: 0.0079 memory: 5828 grad_norm: 4.5864 loss: 1.9959 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9959 2023/06/05 15:14:09 - mmengine - INFO - Epoch(train) [120][ 240/2569] lr: 4.0000e-03 eta: 5:52:10 time: 0.2802 data_time: 0.0074 memory: 5828 grad_norm: 4.5185 loss: 1.6530 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6530 2023/06/05 15:14:14 - mmengine - INFO - Epoch(train) [120][ 260/2569] lr: 4.0000e-03 eta: 5:52:05 time: 0.2738 data_time: 0.0072 memory: 5828 grad_norm: 4.4876 loss: 1.7906 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7906 2023/06/05 15:14:20 - mmengine - INFO - Epoch(train) [120][ 280/2569] lr: 4.0000e-03 eta: 5:51:59 time: 0.2679 data_time: 0.0071 memory: 5828 grad_norm: 4.4935 loss: 1.6303 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6303 2023/06/05 15:14:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:14:25 - mmengine - INFO - Epoch(train) [120][ 300/2569] lr: 4.0000e-03 eta: 5:51:54 time: 0.2655 data_time: 0.0070 memory: 5828 grad_norm: 4.5863 loss: 1.8133 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8133 2023/06/05 15:14:30 - mmengine - INFO - Epoch(train) [120][ 320/2569] lr: 4.0000e-03 eta: 5:51:49 time: 0.2631 data_time: 0.0071 memory: 5828 grad_norm: 4.4257 loss: 1.8221 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8221 2023/06/05 15:14:36 - mmengine - INFO - Epoch(train) [120][ 340/2569] lr: 4.0000e-03 eta: 5:51:43 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 4.6115 loss: 1.8701 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8701 2023/06/05 15:14:41 - mmengine - INFO - Epoch(train) [120][ 360/2569] lr: 4.0000e-03 eta: 5:51:38 time: 0.2716 data_time: 0.0071 memory: 5828 grad_norm: 4.6131 loss: 1.8079 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8079 2023/06/05 15:14:46 - mmengine - INFO - Epoch(train) [120][ 380/2569] lr: 4.0000e-03 eta: 5:51:33 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 4.6131 loss: 2.0420 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.0420 2023/06/05 15:14:52 - mmengine - INFO - Epoch(train) [120][ 400/2569] lr: 4.0000e-03 eta: 5:51:27 time: 0.2695 data_time: 0.0073 memory: 5828 grad_norm: 4.6058 loss: 1.8405 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8405 2023/06/05 15:14:57 - mmengine - INFO - Epoch(train) [120][ 420/2569] lr: 4.0000e-03 eta: 5:51:22 time: 0.2611 data_time: 0.0073 memory: 5828 grad_norm: 4.5197 loss: 1.4682 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4682 2023/06/05 15:15:02 - mmengine - INFO - Epoch(train) [120][ 440/2569] lr: 4.0000e-03 eta: 5:51:17 time: 0.2657 data_time: 0.0073 memory: 5828 grad_norm: 4.5594 loss: 1.9092 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9092 2023/06/05 15:15:08 - mmengine - INFO - Epoch(train) [120][ 460/2569] lr: 4.0000e-03 eta: 5:51:11 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 4.5388 loss: 2.1267 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.1267 2023/06/05 15:15:13 - mmengine - INFO - Epoch(train) [120][ 480/2569] lr: 4.0000e-03 eta: 5:51:06 time: 0.2711 data_time: 0.0072 memory: 5828 grad_norm: 4.6009 loss: 1.7997 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7997 2023/06/05 15:15:18 - mmengine - INFO - Epoch(train) [120][ 500/2569] lr: 4.0000e-03 eta: 5:51:01 time: 0.2609 data_time: 0.0074 memory: 5828 grad_norm: 4.4845 loss: 1.9180 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9180 2023/06/05 15:15:24 - mmengine - INFO - Epoch(train) [120][ 520/2569] lr: 4.0000e-03 eta: 5:50:55 time: 0.2741 data_time: 0.0072 memory: 5828 grad_norm: 4.4863 loss: 2.0361 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0361 2023/06/05 15:15:29 - mmengine - INFO - Epoch(train) [120][ 540/2569] lr: 4.0000e-03 eta: 5:50:50 time: 0.2617 data_time: 0.0071 memory: 5828 grad_norm: 4.5468 loss: 1.8903 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.8903 2023/06/05 15:15:35 - mmengine - INFO - Epoch(train) [120][ 560/2569] lr: 4.0000e-03 eta: 5:50:45 time: 0.2717 data_time: 0.0075 memory: 5828 grad_norm: 4.5734 loss: 1.8596 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.8596 2023/06/05 15:15:40 - mmengine - INFO - Epoch(train) [120][ 580/2569] lr: 4.0000e-03 eta: 5:50:39 time: 0.2628 data_time: 0.0073 memory: 5828 grad_norm: 4.5046 loss: 1.8081 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8081 2023/06/05 15:15:45 - mmengine - INFO - Epoch(train) [120][ 600/2569] lr: 4.0000e-03 eta: 5:50:34 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 4.5843 loss: 1.6283 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6283 2023/06/05 15:15:51 - mmengine - INFO - Epoch(train) [120][ 620/2569] lr: 4.0000e-03 eta: 5:50:29 time: 0.2669 data_time: 0.0075 memory: 5828 grad_norm: 4.5711 loss: 1.8143 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8143 2023/06/05 15:15:56 - mmengine - INFO - Epoch(train) [120][ 640/2569] lr: 4.0000e-03 eta: 5:50:23 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 4.5695 loss: 1.6695 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6695 2023/06/05 15:16:01 - mmengine - INFO - Epoch(train) [120][ 660/2569] lr: 4.0000e-03 eta: 5:50:18 time: 0.2774 data_time: 0.0073 memory: 5828 grad_norm: 4.4865 loss: 1.9529 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9529 2023/06/05 15:16:07 - mmengine - INFO - Epoch(train) [120][ 680/2569] lr: 4.0000e-03 eta: 5:50:13 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 4.5835 loss: 1.5912 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5912 2023/06/05 15:16:12 - mmengine - INFO - Epoch(train) [120][ 700/2569] lr: 4.0000e-03 eta: 5:50:08 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 4.5361 loss: 1.7727 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7727 2023/06/05 15:16:17 - mmengine - INFO - Epoch(train) [120][ 720/2569] lr: 4.0000e-03 eta: 5:50:02 time: 0.2696 data_time: 0.0072 memory: 5828 grad_norm: 4.4804 loss: 1.7447 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7447 2023/06/05 15:16:23 - mmengine - INFO - Epoch(train) [120][ 740/2569] lr: 4.0000e-03 eta: 5:49:57 time: 0.2637 data_time: 0.0080 memory: 5828 grad_norm: 4.5641 loss: 1.5652 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5652 2023/06/05 15:16:28 - mmengine - INFO - Epoch(train) [120][ 760/2569] lr: 4.0000e-03 eta: 5:49:52 time: 0.2660 data_time: 0.0077 memory: 5828 grad_norm: 4.5548 loss: 1.7601 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7601 2023/06/05 15:16:33 - mmengine - INFO - Epoch(train) [120][ 780/2569] lr: 4.0000e-03 eta: 5:49:46 time: 0.2612 data_time: 0.0074 memory: 5828 grad_norm: 4.4578 loss: 1.5292 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5292 2023/06/05 15:16:39 - mmengine - INFO - Epoch(train) [120][ 800/2569] lr: 4.0000e-03 eta: 5:49:41 time: 0.2725 data_time: 0.0075 memory: 5828 grad_norm: 4.4921 loss: 1.6593 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6593 2023/06/05 15:16:44 - mmengine - INFO - Epoch(train) [120][ 820/2569] lr: 4.0000e-03 eta: 5:49:36 time: 0.2622 data_time: 0.0071 memory: 5828 grad_norm: 4.6044 loss: 1.6582 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6582 2023/06/05 15:16:49 - mmengine - INFO - Epoch(train) [120][ 840/2569] lr: 4.0000e-03 eta: 5:49:30 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 4.4916 loss: 1.7247 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7247 2023/06/05 15:16:55 - mmengine - INFO - Epoch(train) [120][ 860/2569] lr: 4.0000e-03 eta: 5:49:25 time: 0.2639 data_time: 0.0071 memory: 5828 grad_norm: 4.4925 loss: 1.8676 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8676 2023/06/05 15:17:00 - mmengine - INFO - Epoch(train) [120][ 880/2569] lr: 4.0000e-03 eta: 5:49:20 time: 0.2637 data_time: 0.0070 memory: 5828 grad_norm: 4.6012 loss: 1.9302 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9302 2023/06/05 15:17:05 - mmengine - INFO - Epoch(train) [120][ 900/2569] lr: 4.0000e-03 eta: 5:49:14 time: 0.2637 data_time: 0.0071 memory: 5828 grad_norm: 4.6378 loss: 1.8331 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8331 2023/06/05 15:17:11 - mmengine - INFO - Epoch(train) [120][ 920/2569] lr: 4.0000e-03 eta: 5:49:09 time: 0.2785 data_time: 0.0071 memory: 5828 grad_norm: 4.6181 loss: 1.8115 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8115 2023/06/05 15:17:16 - mmengine - INFO - Epoch(train) [120][ 940/2569] lr: 4.0000e-03 eta: 5:49:04 time: 0.2682 data_time: 0.0075 memory: 5828 grad_norm: 4.5653 loss: 1.7514 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7514 2023/06/05 15:17:21 - mmengine - INFO - Epoch(train) [120][ 960/2569] lr: 4.0000e-03 eta: 5:48:58 time: 0.2646 data_time: 0.0071 memory: 5828 grad_norm: 4.5563 loss: 1.7004 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7004 2023/06/05 15:17:27 - mmengine - INFO - Epoch(train) [120][ 980/2569] lr: 4.0000e-03 eta: 5:48:53 time: 0.2612 data_time: 0.0070 memory: 5828 grad_norm: 4.7504 loss: 2.0068 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0068 2023/06/05 15:17:32 - mmengine - INFO - Epoch(train) [120][1000/2569] lr: 4.0000e-03 eta: 5:48:48 time: 0.2657 data_time: 0.0071 memory: 5828 grad_norm: 4.5149 loss: 1.9833 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9833 2023/06/05 15:17:37 - mmengine - INFO - Epoch(train) [120][1020/2569] lr: 4.0000e-03 eta: 5:48:42 time: 0.2673 data_time: 0.0072 memory: 5828 grad_norm: 4.5066 loss: 2.0312 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0312 2023/06/05 15:17:43 - mmengine - INFO - Epoch(train) [120][1040/2569] lr: 4.0000e-03 eta: 5:48:37 time: 0.2695 data_time: 0.0070 memory: 5828 grad_norm: 4.5570 loss: 1.9600 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9600 2023/06/05 15:17:48 - mmengine - INFO - Epoch(train) [120][1060/2569] lr: 4.0000e-03 eta: 5:48:32 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 4.5263 loss: 1.4599 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4599 2023/06/05 15:17:53 - mmengine - INFO - Epoch(train) [120][1080/2569] lr: 4.0000e-03 eta: 5:48:26 time: 0.2669 data_time: 0.0072 memory: 5828 grad_norm: 4.5284 loss: 1.6964 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6964 2023/06/05 15:17:59 - mmengine - INFO - Epoch(train) [120][1100/2569] lr: 4.0000e-03 eta: 5:48:21 time: 0.2729 data_time: 0.0073 memory: 5828 grad_norm: 4.5393 loss: 1.7527 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7527 2023/06/05 15:18:04 - mmengine - INFO - Epoch(train) [120][1120/2569] lr: 4.0000e-03 eta: 5:48:16 time: 0.2626 data_time: 0.0071 memory: 5828 grad_norm: 4.4984 loss: 1.7544 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.7544 2023/06/05 15:18:10 - mmengine - INFO - Epoch(train) [120][1140/2569] lr: 4.0000e-03 eta: 5:48:10 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 4.5061 loss: 1.7020 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7020 2023/06/05 15:18:15 - mmengine - INFO - Epoch(train) [120][1160/2569] lr: 4.0000e-03 eta: 5:48:05 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 4.4183 loss: 1.7344 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7344 2023/06/05 15:18:20 - mmengine - INFO - Epoch(train) [120][1180/2569] lr: 4.0000e-03 eta: 5:48:00 time: 0.2632 data_time: 0.0068 memory: 5828 grad_norm: 4.5799 loss: 1.8353 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8353 2023/06/05 15:18:25 - mmengine - INFO - Epoch(train) [120][1200/2569] lr: 4.0000e-03 eta: 5:47:54 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 4.6173 loss: 1.9399 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9399 2023/06/05 15:18:31 - mmengine - INFO - Epoch(train) [120][1220/2569] lr: 4.0000e-03 eta: 5:47:49 time: 0.2737 data_time: 0.0071 memory: 5828 grad_norm: 4.5232 loss: 1.6787 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6787 2023/06/05 15:18:36 - mmengine - INFO - Epoch(train) [120][1240/2569] lr: 4.0000e-03 eta: 5:47:44 time: 0.2680 data_time: 0.0070 memory: 5828 grad_norm: 4.5453 loss: 1.8510 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8510 2023/06/05 15:18:42 - mmengine - INFO - Epoch(train) [120][1260/2569] lr: 4.0000e-03 eta: 5:47:39 time: 0.2738 data_time: 0.0074 memory: 5828 grad_norm: 4.5114 loss: 1.9043 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9043 2023/06/05 15:18:47 - mmengine - INFO - Epoch(train) [120][1280/2569] lr: 4.0000e-03 eta: 5:47:33 time: 0.2795 data_time: 0.0073 memory: 5828 grad_norm: 4.4953 loss: 1.7403 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7403 2023/06/05 15:18:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:18:53 - mmengine - INFO - Epoch(train) [120][1300/2569] lr: 4.0000e-03 eta: 5:47:28 time: 0.2624 data_time: 0.0082 memory: 5828 grad_norm: 4.6017 loss: 1.6545 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6545 2023/06/05 15:18:58 - mmengine - INFO - Epoch(train) [120][1320/2569] lr: 4.0000e-03 eta: 5:47:23 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 4.5033 loss: 1.8674 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8674 2023/06/05 15:19:03 - mmengine - INFO - Epoch(train) [120][1340/2569] lr: 4.0000e-03 eta: 5:47:17 time: 0.2623 data_time: 0.0071 memory: 5828 grad_norm: 4.5269 loss: 1.6213 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6213 2023/06/05 15:19:09 - mmengine - INFO - Epoch(train) [120][1360/2569] lr: 4.0000e-03 eta: 5:47:12 time: 0.2696 data_time: 0.0076 memory: 5828 grad_norm: 4.5252 loss: 1.7055 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7055 2023/06/05 15:19:14 - mmengine - INFO - Epoch(train) [120][1380/2569] lr: 4.0000e-03 eta: 5:47:07 time: 0.2743 data_time: 0.0073 memory: 5828 grad_norm: 4.6369 loss: 1.5718 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5718 2023/06/05 15:19:19 - mmengine - INFO - Epoch(train) [120][1400/2569] lr: 4.0000e-03 eta: 5:47:01 time: 0.2661 data_time: 0.0074 memory: 5828 grad_norm: 4.5552 loss: 1.9236 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9236 2023/06/05 15:19:25 - mmengine - INFO - Epoch(train) [120][1420/2569] lr: 4.0000e-03 eta: 5:46:56 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 4.6400 loss: 1.7296 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7296 2023/06/05 15:19:30 - mmengine - INFO - Epoch(train) [120][1440/2569] lr: 4.0000e-03 eta: 5:46:51 time: 0.2716 data_time: 0.0075 memory: 5828 grad_norm: 4.5728 loss: 1.5820 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5820 2023/06/05 15:19:36 - mmengine - INFO - Epoch(train) [120][1460/2569] lr: 4.0000e-03 eta: 5:46:46 time: 0.2749 data_time: 0.0071 memory: 5828 grad_norm: 4.5266 loss: 1.9765 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9765 2023/06/05 15:19:41 - mmengine - INFO - Epoch(train) [120][1480/2569] lr: 4.0000e-03 eta: 5:46:40 time: 0.2757 data_time: 0.0074 memory: 5828 grad_norm: 4.5275 loss: 1.8301 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8301 2023/06/05 15:19:47 - mmengine - INFO - Epoch(train) [120][1500/2569] lr: 4.0000e-03 eta: 5:46:35 time: 0.2686 data_time: 0.0076 memory: 5828 grad_norm: 4.5002 loss: 1.6919 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6919 2023/06/05 15:19:52 - mmengine - INFO - Epoch(train) [120][1520/2569] lr: 4.0000e-03 eta: 5:46:30 time: 0.2664 data_time: 0.0071 memory: 5828 grad_norm: 4.5999 loss: 2.0757 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0757 2023/06/05 15:19:57 - mmengine - INFO - Epoch(train) [120][1540/2569] lr: 4.0000e-03 eta: 5:46:24 time: 0.2745 data_time: 0.0071 memory: 5828 grad_norm: 4.5567 loss: 1.7255 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7255 2023/06/05 15:20:03 - mmengine - INFO - Epoch(train) [120][1560/2569] lr: 4.0000e-03 eta: 5:46:19 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 4.4989 loss: 2.2897 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2897 2023/06/05 15:20:08 - mmengine - INFO - Epoch(train) [120][1580/2569] lr: 4.0000e-03 eta: 5:46:14 time: 0.2638 data_time: 0.0071 memory: 5828 grad_norm: 4.5119 loss: 1.4704 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4704 2023/06/05 15:20:13 - mmengine - INFO - Epoch(train) [120][1600/2569] lr: 4.0000e-03 eta: 5:46:08 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 4.5562 loss: 2.0715 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0715 2023/06/05 15:20:19 - mmengine - INFO - Epoch(train) [120][1620/2569] lr: 4.0000e-03 eta: 5:46:03 time: 0.2753 data_time: 0.0072 memory: 5828 grad_norm: 4.5682 loss: 1.9553 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9553 2023/06/05 15:20:24 - mmengine - INFO - Epoch(train) [120][1640/2569] lr: 4.0000e-03 eta: 5:45:58 time: 0.2610 data_time: 0.0072 memory: 5828 grad_norm: 4.5633 loss: 1.6725 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6725 2023/06/05 15:20:29 - mmengine - INFO - Epoch(train) [120][1660/2569] lr: 4.0000e-03 eta: 5:45:52 time: 0.2615 data_time: 0.0073 memory: 5828 grad_norm: 4.6293 loss: 1.9872 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9872 2023/06/05 15:20:34 - mmengine - INFO - Epoch(train) [120][1680/2569] lr: 4.0000e-03 eta: 5:45:47 time: 0.2602 data_time: 0.0072 memory: 5828 grad_norm: 4.5320 loss: 1.9003 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.9003 2023/06/05 15:20:40 - mmengine - INFO - Epoch(train) [120][1700/2569] lr: 4.0000e-03 eta: 5:45:42 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 4.5685 loss: 1.6452 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6452 2023/06/05 15:20:45 - mmengine - INFO - Epoch(train) [120][1720/2569] lr: 4.0000e-03 eta: 5:45:36 time: 0.2727 data_time: 0.0072 memory: 5828 grad_norm: 4.4656 loss: 1.8407 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8407 2023/06/05 15:20:50 - mmengine - INFO - Epoch(train) [120][1740/2569] lr: 4.0000e-03 eta: 5:45:31 time: 0.2607 data_time: 0.0071 memory: 5828 grad_norm: 4.5519 loss: 1.7943 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7943 2023/06/05 15:20:56 - mmengine - INFO - Epoch(train) [120][1760/2569] lr: 4.0000e-03 eta: 5:45:26 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 4.6372 loss: 1.6225 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6225 2023/06/05 15:21:01 - mmengine - INFO - Epoch(train) [120][1780/2569] lr: 4.0000e-03 eta: 5:45:20 time: 0.2660 data_time: 0.0074 memory: 5828 grad_norm: 4.4491 loss: 1.6635 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6635 2023/06/05 15:21:06 - mmengine - INFO - Epoch(train) [120][1800/2569] lr: 4.0000e-03 eta: 5:45:15 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 4.6196 loss: 1.8328 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8328 2023/06/05 15:21:12 - mmengine - INFO - Epoch(train) [120][1820/2569] lr: 4.0000e-03 eta: 5:45:10 time: 0.2604 data_time: 0.0074 memory: 5828 grad_norm: 4.5667 loss: 1.8102 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8102 2023/06/05 15:21:17 - mmengine - INFO - Epoch(train) [120][1840/2569] lr: 4.0000e-03 eta: 5:45:04 time: 0.2821 data_time: 0.0073 memory: 5828 grad_norm: 4.5179 loss: 1.6626 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6626 2023/06/05 15:21:22 - mmengine - INFO - Epoch(train) [120][1860/2569] lr: 4.0000e-03 eta: 5:44:59 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 4.5265 loss: 1.9487 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9487 2023/06/05 15:21:28 - mmengine - INFO - Epoch(train) [120][1880/2569] lr: 4.0000e-03 eta: 5:44:54 time: 0.2731 data_time: 0.0074 memory: 5828 grad_norm: 4.6082 loss: 2.1231 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1231 2023/06/05 15:21:33 - mmengine - INFO - Epoch(train) [120][1900/2569] lr: 4.0000e-03 eta: 5:44:48 time: 0.2606 data_time: 0.0069 memory: 5828 grad_norm: 4.5912 loss: 1.9810 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9810 2023/06/05 15:21:39 - mmengine - INFO - Epoch(train) [120][1920/2569] lr: 4.0000e-03 eta: 5:44:43 time: 0.2744 data_time: 0.0076 memory: 5828 grad_norm: 4.6193 loss: 1.5719 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5719 2023/06/05 15:21:44 - mmengine - INFO - Epoch(train) [120][1940/2569] lr: 4.0000e-03 eta: 5:44:38 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 4.6038 loss: 1.7604 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7604 2023/06/05 15:21:49 - mmengine - INFO - Epoch(train) [120][1960/2569] lr: 4.0000e-03 eta: 5:44:33 time: 0.2712 data_time: 0.0070 memory: 5828 grad_norm: 4.5913 loss: 1.4104 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4104 2023/06/05 15:21:55 - mmengine - INFO - Epoch(train) [120][1980/2569] lr: 4.0000e-03 eta: 5:44:27 time: 0.2677 data_time: 0.0075 memory: 5828 grad_norm: 4.5721 loss: 1.6783 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6783 2023/06/05 15:22:00 - mmengine - INFO - Epoch(train) [120][2000/2569] lr: 4.0000e-03 eta: 5:44:22 time: 0.2636 data_time: 0.0071 memory: 5828 grad_norm: 4.5450 loss: 1.7460 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7460 2023/06/05 15:22:06 - mmengine - INFO - Epoch(train) [120][2020/2569] lr: 4.0000e-03 eta: 5:44:17 time: 0.2713 data_time: 0.0070 memory: 5828 grad_norm: 4.6622 loss: 1.4145 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4145 2023/06/05 15:22:11 - mmengine - INFO - Epoch(train) [120][2040/2569] lr: 4.0000e-03 eta: 5:44:11 time: 0.2711 data_time: 0.0071 memory: 5828 grad_norm: 4.6172 loss: 1.6858 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6858 2023/06/05 15:22:16 - mmengine - INFO - Epoch(train) [120][2060/2569] lr: 4.0000e-03 eta: 5:44:06 time: 0.2624 data_time: 0.0070 memory: 5828 grad_norm: 4.5803 loss: 1.8528 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8528 2023/06/05 15:22:21 - mmengine - INFO - Epoch(train) [120][2080/2569] lr: 4.0000e-03 eta: 5:44:01 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 4.5045 loss: 1.9930 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9930 2023/06/05 15:22:27 - mmengine - INFO - Epoch(train) [120][2100/2569] lr: 4.0000e-03 eta: 5:43:55 time: 0.2732 data_time: 0.0071 memory: 5828 grad_norm: 4.4937 loss: 1.7190 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7190 2023/06/05 15:22:32 - mmengine - INFO - Epoch(train) [120][2120/2569] lr: 4.0000e-03 eta: 5:43:50 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 4.4508 loss: 1.5641 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5641 2023/06/05 15:22:38 - mmengine - INFO - Epoch(train) [120][2140/2569] lr: 4.0000e-03 eta: 5:43:45 time: 0.2697 data_time: 0.0071 memory: 5828 grad_norm: 4.6338 loss: 1.8055 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8055 2023/06/05 15:22:43 - mmengine - INFO - Epoch(train) [120][2160/2569] lr: 4.0000e-03 eta: 5:43:40 time: 0.2797 data_time: 0.0072 memory: 5828 grad_norm: 4.5039 loss: 2.0981 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0981 2023/06/05 15:22:49 - mmengine - INFO - Epoch(train) [120][2180/2569] lr: 4.0000e-03 eta: 5:43:34 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 4.4983 loss: 1.5833 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5833 2023/06/05 15:22:54 - mmengine - INFO - Epoch(train) [120][2200/2569] lr: 4.0000e-03 eta: 5:43:29 time: 0.2671 data_time: 0.0080 memory: 5828 grad_norm: 4.6247 loss: 1.9968 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9968 2023/06/05 15:22:59 - mmengine - INFO - Epoch(train) [120][2220/2569] lr: 4.0000e-03 eta: 5:43:24 time: 0.2686 data_time: 0.0073 memory: 5828 grad_norm: 4.5803 loss: 1.9285 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9285 2023/06/05 15:23:05 - mmengine - INFO - Epoch(train) [120][2240/2569] lr: 4.0000e-03 eta: 5:43:18 time: 0.2813 data_time: 0.0071 memory: 5828 grad_norm: 4.4867 loss: 2.0059 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0059 2023/06/05 15:23:10 - mmengine - INFO - Epoch(train) [120][2260/2569] lr: 4.0000e-03 eta: 5:43:13 time: 0.2644 data_time: 0.0070 memory: 5828 grad_norm: 4.6439 loss: 1.7664 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7664 2023/06/05 15:23:16 - mmengine - INFO - Epoch(train) [120][2280/2569] lr: 4.0000e-03 eta: 5:43:08 time: 0.2715 data_time: 0.0074 memory: 5828 grad_norm: 4.5656 loss: 1.9425 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9425 2023/06/05 15:23:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:23:21 - mmengine - INFO - Epoch(train) [120][2300/2569] lr: 4.0000e-03 eta: 5:43:02 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 4.6346 loss: 2.0733 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0733 2023/06/05 15:23:26 - mmengine - INFO - Epoch(train) [120][2320/2569] lr: 4.0000e-03 eta: 5:42:57 time: 0.2675 data_time: 0.0072 memory: 5828 grad_norm: 4.6425 loss: 1.8133 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8133 2023/06/05 15:23:32 - mmengine - INFO - Epoch(train) [120][2340/2569] lr: 4.0000e-03 eta: 5:42:52 time: 0.2650 data_time: 0.0070 memory: 5828 grad_norm: 4.7012 loss: 1.8543 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8543 2023/06/05 15:23:37 - mmengine - INFO - Epoch(train) [120][2360/2569] lr: 4.0000e-03 eta: 5:42:46 time: 0.2696 data_time: 0.0073 memory: 5828 grad_norm: 4.6268 loss: 1.9674 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9674 2023/06/05 15:23:43 - mmengine - INFO - Epoch(train) [120][2380/2569] lr: 4.0000e-03 eta: 5:42:41 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 4.6042 loss: 1.6107 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 1.6107 2023/06/05 15:23:48 - mmengine - INFO - Epoch(train) [120][2400/2569] lr: 4.0000e-03 eta: 5:42:36 time: 0.2686 data_time: 0.0070 memory: 5828 grad_norm: 4.4705 loss: 1.4931 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4931 2023/06/05 15:23:53 - mmengine - INFO - Epoch(train) [120][2420/2569] lr: 4.0000e-03 eta: 5:42:30 time: 0.2681 data_time: 0.0070 memory: 5828 grad_norm: 4.5863 loss: 1.7713 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7713 2023/06/05 15:23:59 - mmengine - INFO - Epoch(train) [120][2440/2569] lr: 4.0000e-03 eta: 5:42:25 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 4.5293 loss: 1.7569 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7569 2023/06/05 15:24:04 - mmengine - INFO - Epoch(train) [120][2460/2569] lr: 4.0000e-03 eta: 5:42:20 time: 0.2664 data_time: 0.0071 memory: 5828 grad_norm: 4.4826 loss: 1.7459 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7459 2023/06/05 15:24:10 - mmengine - INFO - Epoch(train) [120][2480/2569] lr: 4.0000e-03 eta: 5:42:15 time: 0.2835 data_time: 0.0073 memory: 5828 grad_norm: 4.5558 loss: 1.7913 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7913 2023/06/05 15:24:15 - mmengine - INFO - Epoch(train) [120][2500/2569] lr: 4.0000e-03 eta: 5:42:09 time: 0.2650 data_time: 0.0071 memory: 5828 grad_norm: 4.5624 loss: 1.7820 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7820 2023/06/05 15:24:20 - mmengine - INFO - Epoch(train) [120][2520/2569] lr: 4.0000e-03 eta: 5:42:04 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 4.6130 loss: 2.0313 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0313 2023/06/05 15:24:26 - mmengine - INFO - Epoch(train) [120][2540/2569] lr: 4.0000e-03 eta: 5:41:59 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 4.4996 loss: 2.0090 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0090 2023/06/05 15:24:31 - mmengine - INFO - Epoch(train) [120][2560/2569] lr: 4.0000e-03 eta: 5:41:53 time: 0.2824 data_time: 0.0071 memory: 5828 grad_norm: 4.5445 loss: 2.0798 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0798 2023/06/05 15:24:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:24:34 - mmengine - INFO - Epoch(train) [120][2569/2569] lr: 4.0000e-03 eta: 5:41:51 time: 0.2839 data_time: 0.0070 memory: 5828 grad_norm: 4.6533 loss: 2.0156 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 2.0156 2023/06/05 15:24:34 - mmengine - INFO - Saving checkpoint at 120 epochs 2023/06/05 15:24:40 - mmengine - INFO - Epoch(val) [120][ 20/260] eta: 0:00:43 time: 0.1823 data_time: 0.1232 memory: 1238 2023/06/05 15:24:43 - mmengine - INFO - Epoch(val) [120][ 40/260] eta: 0:00:35 time: 0.1433 data_time: 0.0846 memory: 1238 2023/06/05 15:24:46 - mmengine - INFO - Epoch(val) [120][ 60/260] eta: 0:00:31 time: 0.1488 data_time: 0.0901 memory: 1238 2023/06/05 15:24:48 - mmengine - INFO - Epoch(val) [120][ 80/260] eta: 0:00:26 time: 0.1256 data_time: 0.0666 memory: 1238 2023/06/05 15:24:51 - mmengine - INFO - Epoch(val) [120][100/260] eta: 0:00:23 time: 0.1428 data_time: 0.0843 memory: 1238 2023/06/05 15:24:54 - mmengine - INFO - Epoch(val) [120][120/260] eta: 0:00:20 time: 0.1427 data_time: 0.0839 memory: 1238 2023/06/05 15:24:56 - mmengine - INFO - Epoch(val) [120][140/260] eta: 0:00:17 time: 0.1264 data_time: 0.0675 memory: 1238 2023/06/05 15:24:59 - mmengine - INFO - Epoch(val) [120][160/260] eta: 0:00:14 time: 0.1488 data_time: 0.0900 memory: 1238 2023/06/05 15:25:02 - mmengine - INFO - Epoch(val) [120][180/260] eta: 0:00:11 time: 0.1254 data_time: 0.0666 memory: 1238 2023/06/05 15:25:05 - mmengine - INFO - Epoch(val) [120][200/260] eta: 0:00:08 time: 0.1441 data_time: 0.0855 memory: 1238 2023/06/05 15:25:08 - mmengine - INFO - Epoch(val) [120][220/260] eta: 0:00:05 time: 0.1488 data_time: 0.0903 memory: 1238 2023/06/05 15:25:10 - mmengine - INFO - Epoch(val) [120][240/260] eta: 0:00:02 time: 0.1247 data_time: 0.0672 memory: 1238 2023/06/05 15:25:12 - mmengine - INFO - Epoch(val) [120][260/260] eta: 0:00:00 time: 0.1082 data_time: 0.0526 memory: 1238 2023/06/05 15:25:19 - mmengine - INFO - Epoch(val) [120][260/260] acc/top1: 0.6182 acc/top5: 0.8304 acc/mean1: 0.6114 data_time: 0.0807 time: 0.1390 2023/06/05 15:25:19 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_115.pth is removed 2023/06/05 15:25:21 - mmengine - INFO - The best checkpoint with 0.6182 acc/top1 at 120 epoch is saved to best_acc_top1_epoch_120.pth. 2023/06/05 15:25:27 - mmengine - INFO - Epoch(train) [121][ 20/2569] lr: 4.0000e-03 eta: 5:41:46 time: 0.2988 data_time: 0.0463 memory: 5828 grad_norm: 4.5955 loss: 1.6515 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6515 2023/06/05 15:25:32 - mmengine - INFO - Epoch(train) [121][ 40/2569] lr: 4.0000e-03 eta: 5:41:40 time: 0.2632 data_time: 0.0067 memory: 5828 grad_norm: 4.4975 loss: 1.5357 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5357 2023/06/05 15:25:37 - mmengine - INFO - Epoch(train) [121][ 60/2569] lr: 4.0000e-03 eta: 5:41:35 time: 0.2720 data_time: 0.0074 memory: 5828 grad_norm: 4.5927 loss: 1.7550 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7550 2023/06/05 15:25:43 - mmengine - INFO - Epoch(train) [121][ 80/2569] lr: 4.0000e-03 eta: 5:41:30 time: 0.2702 data_time: 0.0071 memory: 5828 grad_norm: 4.6010 loss: 1.9302 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9302 2023/06/05 15:25:48 - mmengine - INFO - Epoch(train) [121][ 100/2569] lr: 4.0000e-03 eta: 5:41:25 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 4.6408 loss: 1.9565 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9565 2023/06/05 15:25:53 - mmengine - INFO - Epoch(train) [121][ 120/2569] lr: 4.0000e-03 eta: 5:41:19 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 4.6446 loss: 1.6145 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6145 2023/06/05 15:25:59 - mmengine - INFO - Epoch(train) [121][ 140/2569] lr: 4.0000e-03 eta: 5:41:14 time: 0.2709 data_time: 0.0068 memory: 5828 grad_norm: 4.5433 loss: 1.4146 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4146 2023/06/05 15:26:04 - mmengine - INFO - Epoch(train) [121][ 160/2569] lr: 4.0000e-03 eta: 5:41:09 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 4.6216 loss: 1.3304 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3304 2023/06/05 15:26:09 - mmengine - INFO - Epoch(train) [121][ 180/2569] lr: 4.0000e-03 eta: 5:41:03 time: 0.2680 data_time: 0.0075 memory: 5828 grad_norm: 4.5798 loss: 1.9044 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9044 2023/06/05 15:26:15 - mmengine - INFO - Epoch(train) [121][ 200/2569] lr: 4.0000e-03 eta: 5:40:58 time: 0.2620 data_time: 0.0071 memory: 5828 grad_norm: 4.6370 loss: 1.7972 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7972 2023/06/05 15:26:20 - mmengine - INFO - Epoch(train) [121][ 220/2569] lr: 4.0000e-03 eta: 5:40:53 time: 0.2743 data_time: 0.0072 memory: 5828 grad_norm: 4.5384 loss: 1.8058 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8058 2023/06/05 15:26:25 - mmengine - INFO - Epoch(train) [121][ 240/2569] lr: 4.0000e-03 eta: 5:40:47 time: 0.2611 data_time: 0.0072 memory: 5828 grad_norm: 4.6245 loss: 1.5799 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5799 2023/06/05 15:26:31 - mmengine - INFO - Epoch(train) [121][ 260/2569] lr: 4.0000e-03 eta: 5:40:42 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 4.5134 loss: 1.8187 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8187 2023/06/05 15:26:36 - mmengine - INFO - Epoch(train) [121][ 280/2569] lr: 4.0000e-03 eta: 5:40:37 time: 0.2626 data_time: 0.0072 memory: 5828 grad_norm: 4.6226 loss: 1.7687 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7687 2023/06/05 15:26:41 - mmengine - INFO - Epoch(train) [121][ 300/2569] lr: 4.0000e-03 eta: 5:40:31 time: 0.2721 data_time: 0.0075 memory: 5828 grad_norm: 4.5897 loss: 2.0868 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0868 2023/06/05 15:26:47 - mmengine - INFO - Epoch(train) [121][ 320/2569] lr: 4.0000e-03 eta: 5:40:26 time: 0.2668 data_time: 0.0074 memory: 5828 grad_norm: 4.6802 loss: 2.0614 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0614 2023/06/05 15:26:52 - mmengine - INFO - Epoch(train) [121][ 340/2569] lr: 4.0000e-03 eta: 5:40:21 time: 0.2727 data_time: 0.0072 memory: 5828 grad_norm: 4.6167 loss: 1.5954 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5954 2023/06/05 15:26:58 - mmengine - INFO - Epoch(train) [121][ 360/2569] lr: 4.0000e-03 eta: 5:40:15 time: 0.2733 data_time: 0.0072 memory: 5828 grad_norm: 4.4869 loss: 1.5876 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.5876 2023/06/05 15:27:03 - mmengine - INFO - Epoch(train) [121][ 380/2569] lr: 4.0000e-03 eta: 5:40:10 time: 0.2626 data_time: 0.0071 memory: 5828 grad_norm: 4.5856 loss: 1.9172 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9172 2023/06/05 15:27:08 - mmengine - INFO - Epoch(train) [121][ 400/2569] lr: 4.0000e-03 eta: 5:40:05 time: 0.2713 data_time: 0.0070 memory: 5828 grad_norm: 4.5919 loss: 1.6661 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6661 2023/06/05 15:27:14 - mmengine - INFO - Epoch(train) [121][ 420/2569] lr: 4.0000e-03 eta: 5:39:59 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 4.5111 loss: 1.7245 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7245 2023/06/05 15:27:19 - mmengine - INFO - Epoch(train) [121][ 440/2569] lr: 4.0000e-03 eta: 5:39:54 time: 0.2670 data_time: 0.0070 memory: 5828 grad_norm: 4.5928 loss: 1.6297 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6297 2023/06/05 15:27:24 - mmengine - INFO - Epoch(train) [121][ 460/2569] lr: 4.0000e-03 eta: 5:39:49 time: 0.2675 data_time: 0.0079 memory: 5828 grad_norm: 4.6077 loss: 1.8552 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8552 2023/06/05 15:27:30 - mmengine - INFO - Epoch(train) [121][ 480/2569] lr: 4.0000e-03 eta: 5:39:44 time: 0.2745 data_time: 0.0072 memory: 5828 grad_norm: 4.5796 loss: 1.8853 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8853 2023/06/05 15:27:35 - mmengine - INFO - Epoch(train) [121][ 500/2569] lr: 4.0000e-03 eta: 5:39:38 time: 0.2736 data_time: 0.0077 memory: 5828 grad_norm: 4.5151 loss: 1.6966 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6966 2023/06/05 15:27:41 - mmengine - INFO - Epoch(train) [121][ 520/2569] lr: 4.0000e-03 eta: 5:39:33 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 4.5907 loss: 1.7792 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7792 2023/06/05 15:27:46 - mmengine - INFO - Epoch(train) [121][ 540/2569] lr: 4.0000e-03 eta: 5:39:28 time: 0.2658 data_time: 0.0078 memory: 5828 grad_norm: 4.5831 loss: 1.6866 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6866 2023/06/05 15:27:51 - mmengine - INFO - Epoch(train) [121][ 560/2569] lr: 4.0000e-03 eta: 5:39:22 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 4.6314 loss: 1.6709 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6709 2023/06/05 15:27:57 - mmengine - INFO - Epoch(train) [121][ 580/2569] lr: 4.0000e-03 eta: 5:39:17 time: 0.2690 data_time: 0.0073 memory: 5828 grad_norm: 4.5589 loss: 1.5722 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5722 2023/06/05 15:28:02 - mmengine - INFO - Epoch(train) [121][ 600/2569] lr: 4.0000e-03 eta: 5:39:12 time: 0.2622 data_time: 0.0070 memory: 5828 grad_norm: 4.6052 loss: 2.2840 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.2840 2023/06/05 15:28:07 - mmengine - INFO - Epoch(train) [121][ 620/2569] lr: 4.0000e-03 eta: 5:39:06 time: 0.2705 data_time: 0.0069 memory: 5828 grad_norm: 4.6775 loss: 1.7199 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7199 2023/06/05 15:28:13 - mmengine - INFO - Epoch(train) [121][ 640/2569] lr: 4.0000e-03 eta: 5:39:01 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 4.5694 loss: 1.8996 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8996 2023/06/05 15:28:18 - mmengine - INFO - Epoch(train) [121][ 660/2569] lr: 4.0000e-03 eta: 5:38:56 time: 0.2629 data_time: 0.0077 memory: 5828 grad_norm: 4.6103 loss: 1.7481 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7481 2023/06/05 15:28:23 - mmengine - INFO - Epoch(train) [121][ 680/2569] lr: 4.0000e-03 eta: 5:38:50 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 4.6147 loss: 1.6886 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.6886 2023/06/05 15:28:28 - mmengine - INFO - Epoch(train) [121][ 700/2569] lr: 4.0000e-03 eta: 5:38:45 time: 0.2626 data_time: 0.0073 memory: 5828 grad_norm: 4.5606 loss: 1.7134 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7134 2023/06/05 15:28:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:28:34 - mmengine - INFO - Epoch(train) [121][ 720/2569] lr: 4.0000e-03 eta: 5:38:40 time: 0.2674 data_time: 0.0074 memory: 5828 grad_norm: 4.7024 loss: 2.2089 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2089 2023/06/05 15:28:39 - mmengine - INFO - Epoch(train) [121][ 740/2569] lr: 4.0000e-03 eta: 5:38:34 time: 0.2638 data_time: 0.0071 memory: 5828 grad_norm: 4.5543 loss: 1.5277 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5277 2023/06/05 15:28:45 - mmengine - INFO - Epoch(train) [121][ 760/2569] lr: 4.0000e-03 eta: 5:38:29 time: 0.2776 data_time: 0.0072 memory: 5828 grad_norm: 4.6073 loss: 1.7980 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.7980 2023/06/05 15:28:50 - mmengine - INFO - Epoch(train) [121][ 780/2569] lr: 4.0000e-03 eta: 5:38:24 time: 0.2653 data_time: 0.0072 memory: 5828 grad_norm: 4.4343 loss: 1.6694 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6694 2023/06/05 15:28:55 - mmengine - INFO - Epoch(train) [121][ 800/2569] lr: 4.0000e-03 eta: 5:38:18 time: 0.2682 data_time: 0.0075 memory: 5828 grad_norm: 4.6041 loss: 1.9418 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.9418 2023/06/05 15:29:01 - mmengine - INFO - Epoch(train) [121][ 820/2569] lr: 4.0000e-03 eta: 5:38:13 time: 0.2700 data_time: 0.0071 memory: 5828 grad_norm: 4.6779 loss: 1.8054 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8054 2023/06/05 15:29:06 - mmengine - INFO - Epoch(train) [121][ 840/2569] lr: 4.0000e-03 eta: 5:38:08 time: 0.2716 data_time: 0.0072 memory: 5828 grad_norm: 4.5688 loss: 1.8661 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8661 2023/06/05 15:29:12 - mmengine - INFO - Epoch(train) [121][ 860/2569] lr: 4.0000e-03 eta: 5:38:03 time: 0.2736 data_time: 0.0074 memory: 5828 grad_norm: 4.6146 loss: 1.6623 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6623 2023/06/05 15:29:17 - mmengine - INFO - Epoch(train) [121][ 880/2569] lr: 4.0000e-03 eta: 5:37:57 time: 0.2614 data_time: 0.0070 memory: 5828 grad_norm: 4.4593 loss: 1.7821 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7821 2023/06/05 15:29:22 - mmengine - INFO - Epoch(train) [121][ 900/2569] lr: 4.0000e-03 eta: 5:37:52 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 4.5810 loss: 1.6673 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6673 2023/06/05 15:29:27 - mmengine - INFO - Epoch(train) [121][ 920/2569] lr: 4.0000e-03 eta: 5:37:46 time: 0.2597 data_time: 0.0073 memory: 5828 grad_norm: 4.5911 loss: 2.1466 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.1466 2023/06/05 15:29:33 - mmengine - INFO - Epoch(train) [121][ 940/2569] lr: 4.0000e-03 eta: 5:37:41 time: 0.2661 data_time: 0.0076 memory: 5828 grad_norm: 4.5773 loss: 1.8906 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8906 2023/06/05 15:29:38 - mmengine - INFO - Epoch(train) [121][ 960/2569] lr: 4.0000e-03 eta: 5:37:36 time: 0.2606 data_time: 0.0070 memory: 5828 grad_norm: 4.5547 loss: 1.8769 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8769 2023/06/05 15:29:43 - mmengine - INFO - Epoch(train) [121][ 980/2569] lr: 4.0000e-03 eta: 5:37:30 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 4.5292 loss: 2.0145 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0145 2023/06/05 15:29:49 - mmengine - INFO - Epoch(train) [121][1000/2569] lr: 4.0000e-03 eta: 5:37:25 time: 0.2720 data_time: 0.0071 memory: 5828 grad_norm: 4.5906 loss: 2.1286 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1286 2023/06/05 15:29:54 - mmengine - INFO - Epoch(train) [121][1020/2569] lr: 4.0000e-03 eta: 5:37:20 time: 0.2672 data_time: 0.0070 memory: 5828 grad_norm: 4.5768 loss: 2.0261 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0261 2023/06/05 15:29:59 - mmengine - INFO - Epoch(train) [121][1040/2569] lr: 4.0000e-03 eta: 5:37:15 time: 0.2704 data_time: 0.0072 memory: 5828 grad_norm: 4.5775 loss: 1.9434 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9434 2023/06/05 15:30:05 - mmengine - INFO - Epoch(train) [121][1060/2569] lr: 4.0000e-03 eta: 5:37:09 time: 0.2661 data_time: 0.0069 memory: 5828 grad_norm: 4.5598 loss: 1.4701 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4701 2023/06/05 15:30:10 - mmengine - INFO - Epoch(train) [121][1080/2569] lr: 4.0000e-03 eta: 5:37:04 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 4.6082 loss: 2.0750 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0750 2023/06/05 15:30:16 - mmengine - INFO - Epoch(train) [121][1100/2569] lr: 4.0000e-03 eta: 5:36:59 time: 0.2732 data_time: 0.0071 memory: 5828 grad_norm: 4.5986 loss: 1.7743 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7743 2023/06/05 15:30:21 - mmengine - INFO - Epoch(train) [121][1120/2569] lr: 4.0000e-03 eta: 5:36:53 time: 0.2687 data_time: 0.0072 memory: 5828 grad_norm: 4.5511 loss: 1.6399 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6399 2023/06/05 15:30:26 - mmengine - INFO - Epoch(train) [121][1140/2569] lr: 4.0000e-03 eta: 5:36:48 time: 0.2636 data_time: 0.0072 memory: 5828 grad_norm: 4.5371 loss: 2.1174 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1174 2023/06/05 15:30:31 - mmengine - INFO - Epoch(train) [121][1160/2569] lr: 4.0000e-03 eta: 5:36:43 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 4.5161 loss: 1.6862 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6862 2023/06/05 15:30:37 - mmengine - INFO - Epoch(train) [121][1180/2569] lr: 4.0000e-03 eta: 5:36:37 time: 0.2691 data_time: 0.0070 memory: 5828 grad_norm: 4.6188 loss: 1.8825 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8825 2023/06/05 15:30:42 - mmengine - INFO - Epoch(train) [121][1200/2569] lr: 4.0000e-03 eta: 5:36:32 time: 0.2622 data_time: 0.0071 memory: 5828 grad_norm: 4.6795 loss: 1.7996 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7996 2023/06/05 15:30:47 - mmengine - INFO - Epoch(train) [121][1220/2569] lr: 4.0000e-03 eta: 5:36:27 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 4.6087 loss: 1.7649 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7649 2023/06/05 15:30:53 - mmengine - INFO - Epoch(train) [121][1240/2569] lr: 4.0000e-03 eta: 5:36:21 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 4.5942 loss: 1.9471 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9471 2023/06/05 15:30:58 - mmengine - INFO - Epoch(train) [121][1260/2569] lr: 4.0000e-03 eta: 5:36:16 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 4.6201 loss: 1.8385 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8385 2023/06/05 15:31:03 - mmengine - INFO - Epoch(train) [121][1280/2569] lr: 4.0000e-03 eta: 5:36:11 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 4.5873 loss: 1.6374 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6374 2023/06/05 15:31:09 - mmengine - INFO - Epoch(train) [121][1300/2569] lr: 4.0000e-03 eta: 5:36:05 time: 0.2763 data_time: 0.0071 memory: 5828 grad_norm: 4.5243 loss: 1.4647 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4647 2023/06/05 15:31:14 - mmengine - INFO - Epoch(train) [121][1320/2569] lr: 4.0000e-03 eta: 5:36:00 time: 0.2781 data_time: 0.0074 memory: 5828 grad_norm: 4.5643 loss: 1.9659 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9659 2023/06/05 15:31:20 - mmengine - INFO - Epoch(train) [121][1340/2569] lr: 4.0000e-03 eta: 5:35:55 time: 0.2676 data_time: 0.0071 memory: 5828 grad_norm: 4.5266 loss: 1.8830 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8830 2023/06/05 15:31:25 - mmengine - INFO - Epoch(train) [121][1360/2569] lr: 4.0000e-03 eta: 5:35:50 time: 0.2724 data_time: 0.0073 memory: 5828 grad_norm: 4.5578 loss: 1.7078 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7078 2023/06/05 15:31:31 - mmengine - INFO - Epoch(train) [121][1380/2569] lr: 4.0000e-03 eta: 5:35:44 time: 0.2607 data_time: 0.0074 memory: 5828 grad_norm: 4.5626 loss: 2.0941 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0941 2023/06/05 15:31:36 - mmengine - INFO - Epoch(train) [121][1400/2569] lr: 4.0000e-03 eta: 5:35:39 time: 0.2736 data_time: 0.0095 memory: 5828 grad_norm: 4.6371 loss: 2.1159 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1159 2023/06/05 15:31:41 - mmengine - INFO - Epoch(train) [121][1420/2569] lr: 4.0000e-03 eta: 5:35:34 time: 0.2664 data_time: 0.0076 memory: 5828 grad_norm: 4.6292 loss: 1.9306 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9306 2023/06/05 15:31:47 - mmengine - INFO - Epoch(train) [121][1440/2569] lr: 4.0000e-03 eta: 5:35:28 time: 0.2738 data_time: 0.0084 memory: 5828 grad_norm: 4.5545 loss: 1.6346 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6346 2023/06/05 15:31:52 - mmengine - INFO - Epoch(train) [121][1460/2569] lr: 4.0000e-03 eta: 5:35:23 time: 0.2695 data_time: 0.0093 memory: 5828 grad_norm: 4.6753 loss: 1.6962 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6962 2023/06/05 15:31:58 - mmengine - INFO - Epoch(train) [121][1480/2569] lr: 4.0000e-03 eta: 5:35:18 time: 0.2683 data_time: 0.0074 memory: 5828 grad_norm: 4.7348 loss: 1.8782 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8782 2023/06/05 15:32:03 - mmengine - INFO - Epoch(train) [121][1500/2569] lr: 4.0000e-03 eta: 5:35:12 time: 0.2649 data_time: 0.0072 memory: 5828 grad_norm: 4.7417 loss: 1.6733 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6733 2023/06/05 15:32:08 - mmengine - INFO - Epoch(train) [121][1520/2569] lr: 4.0000e-03 eta: 5:35:07 time: 0.2619 data_time: 0.0071 memory: 5828 grad_norm: 4.6713 loss: 1.9336 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9336 2023/06/05 15:32:14 - mmengine - INFO - Epoch(train) [121][1540/2569] lr: 4.0000e-03 eta: 5:35:02 time: 0.2707 data_time: 0.0078 memory: 5828 grad_norm: 4.6381 loss: 1.7944 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7944 2023/06/05 15:32:19 - mmengine - INFO - Epoch(train) [121][1560/2569] lr: 4.0000e-03 eta: 5:34:56 time: 0.2699 data_time: 0.0070 memory: 5828 grad_norm: 4.4889 loss: 1.6427 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6427 2023/06/05 15:32:24 - mmengine - INFO - Epoch(train) [121][1580/2569] lr: 4.0000e-03 eta: 5:34:51 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 4.6260 loss: 1.8387 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8387 2023/06/05 15:32:30 - mmengine - INFO - Epoch(train) [121][1600/2569] lr: 4.0000e-03 eta: 5:34:46 time: 0.2664 data_time: 0.0070 memory: 5828 grad_norm: 4.6528 loss: 2.1530 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1530 2023/06/05 15:32:35 - mmengine - INFO - Epoch(train) [121][1620/2569] lr: 4.0000e-03 eta: 5:34:40 time: 0.2680 data_time: 0.0074 memory: 5828 grad_norm: 4.5439 loss: 1.7436 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7436 2023/06/05 15:32:40 - mmengine - INFO - Epoch(train) [121][1640/2569] lr: 4.0000e-03 eta: 5:34:35 time: 0.2649 data_time: 0.0070 memory: 5828 grad_norm: 4.6057 loss: 1.7585 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7585 2023/06/05 15:32:46 - mmengine - INFO - Epoch(train) [121][1660/2569] lr: 4.0000e-03 eta: 5:34:30 time: 0.2716 data_time: 0.0073 memory: 5828 grad_norm: 4.6282 loss: 1.7901 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7901 2023/06/05 15:32:51 - mmengine - INFO - Epoch(train) [121][1680/2569] lr: 4.0000e-03 eta: 5:34:25 time: 0.2799 data_time: 0.0072 memory: 5828 grad_norm: 4.6677 loss: 2.0073 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0073 2023/06/05 15:32:57 - mmengine - INFO - Epoch(train) [121][1700/2569] lr: 4.0000e-03 eta: 5:34:19 time: 0.2623 data_time: 0.0074 memory: 5828 grad_norm: 4.6162 loss: 1.7658 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7658 2023/06/05 15:33:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:33:02 - mmengine - INFO - Epoch(train) [121][1720/2569] lr: 4.0000e-03 eta: 5:34:14 time: 0.2696 data_time: 0.0075 memory: 5828 grad_norm: 4.5821 loss: 1.9183 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9183 2023/06/05 15:33:08 - mmengine - INFO - Epoch(train) [121][1740/2569] lr: 4.0000e-03 eta: 5:34:09 time: 0.2779 data_time: 0.0070 memory: 5828 grad_norm: 4.6053 loss: 1.9106 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9106 2023/06/05 15:33:13 - mmengine - INFO - Epoch(train) [121][1760/2569] lr: 4.0000e-03 eta: 5:34:03 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 4.5802 loss: 1.8033 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8033 2023/06/05 15:33:18 - mmengine - INFO - Epoch(train) [121][1780/2569] lr: 4.0000e-03 eta: 5:33:58 time: 0.2763 data_time: 0.0071 memory: 5828 grad_norm: 4.5232 loss: 1.7335 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7335 2023/06/05 15:33:24 - mmengine - INFO - Epoch(train) [121][1800/2569] lr: 4.0000e-03 eta: 5:33:53 time: 0.2708 data_time: 0.0075 memory: 5828 grad_norm: 4.5392 loss: 2.1814 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1814 2023/06/05 15:33:29 - mmengine - INFO - Epoch(train) [121][1820/2569] lr: 4.0000e-03 eta: 5:33:47 time: 0.2782 data_time: 0.0070 memory: 5828 grad_norm: 4.5357 loss: 1.8594 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8594 2023/06/05 15:33:35 - mmengine - INFO - Epoch(train) [121][1840/2569] lr: 4.0000e-03 eta: 5:33:42 time: 0.2690 data_time: 0.0070 memory: 5828 grad_norm: 4.6827 loss: 1.6208 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6208 2023/06/05 15:33:40 - mmengine - INFO - Epoch(train) [121][1860/2569] lr: 4.0000e-03 eta: 5:33:37 time: 0.2797 data_time: 0.0071 memory: 5828 grad_norm: 4.5064 loss: 1.5891 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5891 2023/06/05 15:33:46 - mmengine - INFO - Epoch(train) [121][1880/2569] lr: 4.0000e-03 eta: 5:33:32 time: 0.2771 data_time: 0.0070 memory: 5828 grad_norm: 4.5909 loss: 1.6781 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6781 2023/06/05 15:33:51 - mmengine - INFO - Epoch(train) [121][1900/2569] lr: 4.0000e-03 eta: 5:33:26 time: 0.2680 data_time: 0.0069 memory: 5828 grad_norm: 4.6176 loss: 2.1369 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1369 2023/06/05 15:33:57 - mmengine - INFO - Epoch(train) [121][1920/2569] lr: 4.0000e-03 eta: 5:33:21 time: 0.2733 data_time: 0.0073 memory: 5828 grad_norm: 4.6112 loss: 1.7513 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7513 2023/06/05 15:34:02 - mmengine - INFO - Epoch(train) [121][1940/2569] lr: 4.0000e-03 eta: 5:33:16 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 4.6505 loss: 1.8450 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8450 2023/06/05 15:34:07 - mmengine - INFO - Epoch(train) [121][1960/2569] lr: 4.0000e-03 eta: 5:33:10 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 4.5874 loss: 1.8531 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8531 2023/06/05 15:34:13 - mmengine - INFO - Epoch(train) [121][1980/2569] lr: 4.0000e-03 eta: 5:33:05 time: 0.2698 data_time: 0.0072 memory: 5828 grad_norm: 4.5978 loss: 1.7221 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7221 2023/06/05 15:34:18 - mmengine - INFO - Epoch(train) [121][2000/2569] lr: 4.0000e-03 eta: 5:33:00 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 4.5600 loss: 1.6634 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6634 2023/06/05 15:34:24 - mmengine - INFO - Epoch(train) [121][2020/2569] lr: 4.0000e-03 eta: 5:32:54 time: 0.2792 data_time: 0.0078 memory: 5828 grad_norm: 4.6277 loss: 1.8154 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8154 2023/06/05 15:34:29 - mmengine - INFO - Epoch(train) [121][2040/2569] lr: 4.0000e-03 eta: 5:32:49 time: 0.2728 data_time: 0.0072 memory: 5828 grad_norm: 4.7055 loss: 2.0685 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0685 2023/06/05 15:34:35 - mmengine - INFO - Epoch(train) [121][2060/2569] lr: 4.0000e-03 eta: 5:32:44 time: 0.2693 data_time: 0.0077 memory: 5828 grad_norm: 4.4942 loss: 1.7504 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7504 2023/06/05 15:34:40 - mmengine - INFO - Epoch(train) [121][2080/2569] lr: 4.0000e-03 eta: 5:32:39 time: 0.2685 data_time: 0.0113 memory: 5828 grad_norm: 4.6142 loss: 1.8093 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8093 2023/06/05 15:34:46 - mmengine - INFO - Epoch(train) [121][2100/2569] lr: 4.0000e-03 eta: 5:32:33 time: 0.2764 data_time: 0.0072 memory: 5828 grad_norm: 4.6415 loss: 1.9036 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9036 2023/06/05 15:34:51 - mmengine - INFO - Epoch(train) [121][2120/2569] lr: 4.0000e-03 eta: 5:32:28 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 4.5774 loss: 2.0357 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0357 2023/06/05 15:34:56 - mmengine - INFO - Epoch(train) [121][2140/2569] lr: 4.0000e-03 eta: 5:32:23 time: 0.2722 data_time: 0.0073 memory: 5828 grad_norm: 4.6761 loss: 1.6969 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6969 2023/06/05 15:35:02 - mmengine - INFO - Epoch(train) [121][2160/2569] lr: 4.0000e-03 eta: 5:32:17 time: 0.2722 data_time: 0.0071 memory: 5828 grad_norm: 4.5580 loss: 1.8043 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.8043 2023/06/05 15:35:07 - mmengine - INFO - Epoch(train) [121][2180/2569] lr: 4.0000e-03 eta: 5:32:12 time: 0.2695 data_time: 0.0071 memory: 5828 grad_norm: 4.6447 loss: 1.5101 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5101 2023/06/05 15:35:13 - mmengine - INFO - Epoch(train) [121][2200/2569] lr: 4.0000e-03 eta: 5:32:07 time: 0.2701 data_time: 0.0070 memory: 5828 grad_norm: 4.6874 loss: 1.7306 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7306 2023/06/05 15:35:18 - mmengine - INFO - Epoch(train) [121][2220/2569] lr: 4.0000e-03 eta: 5:32:01 time: 0.2654 data_time: 0.0070 memory: 5828 grad_norm: 4.5944 loss: 1.7750 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.7750 2023/06/05 15:35:23 - mmengine - INFO - Epoch(train) [121][2240/2569] lr: 4.0000e-03 eta: 5:31:56 time: 0.2757 data_time: 0.0073 memory: 5828 grad_norm: 4.7005 loss: 1.5856 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5856 2023/06/05 15:35:29 - mmengine - INFO - Epoch(train) [121][2260/2569] lr: 4.0000e-03 eta: 5:31:51 time: 0.2664 data_time: 0.0070 memory: 5828 grad_norm: 4.6982 loss: 1.7893 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7893 2023/06/05 15:35:34 - mmengine - INFO - Epoch(train) [121][2280/2569] lr: 4.0000e-03 eta: 5:31:46 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 4.6274 loss: 1.4060 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4060 2023/06/05 15:35:39 - mmengine - INFO - Epoch(train) [121][2300/2569] lr: 4.0000e-03 eta: 5:31:40 time: 0.2664 data_time: 0.0072 memory: 5828 grad_norm: 4.6334 loss: 1.8157 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8157 2023/06/05 15:35:45 - mmengine - INFO - Epoch(train) [121][2320/2569] lr: 4.0000e-03 eta: 5:31:35 time: 0.2676 data_time: 0.0073 memory: 5828 grad_norm: 4.6703 loss: 1.9281 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9281 2023/06/05 15:35:50 - mmengine - INFO - Epoch(train) [121][2340/2569] lr: 4.0000e-03 eta: 5:31:30 time: 0.2746 data_time: 0.0076 memory: 5828 grad_norm: 4.6346 loss: 1.6028 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6028 2023/06/05 15:35:56 - mmengine - INFO - Epoch(train) [121][2360/2569] lr: 4.0000e-03 eta: 5:31:24 time: 0.2668 data_time: 0.0074 memory: 5828 grad_norm: 4.6667 loss: 1.7624 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7624 2023/06/05 15:36:01 - mmengine - INFO - Epoch(train) [121][2380/2569] lr: 4.0000e-03 eta: 5:31:19 time: 0.2779 data_time: 0.0075 memory: 5828 grad_norm: 4.5595 loss: 1.8729 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8729 2023/06/05 15:36:07 - mmengine - INFO - Epoch(train) [121][2400/2569] lr: 4.0000e-03 eta: 5:31:14 time: 0.2616 data_time: 0.0075 memory: 5828 grad_norm: 4.5610 loss: 1.7530 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7530 2023/06/05 15:36:12 - mmengine - INFO - Epoch(train) [121][2420/2569] lr: 4.0000e-03 eta: 5:31:08 time: 0.2670 data_time: 0.0076 memory: 5828 grad_norm: 4.5126 loss: 1.4460 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4460 2023/06/05 15:36:17 - mmengine - INFO - Epoch(train) [121][2440/2569] lr: 4.0000e-03 eta: 5:31:03 time: 0.2688 data_time: 0.0071 memory: 5828 grad_norm: 4.5404 loss: 1.9833 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9833 2023/06/05 15:36:23 - mmengine - INFO - Epoch(train) [121][2460/2569] lr: 4.0000e-03 eta: 5:30:58 time: 0.2676 data_time: 0.0070 memory: 5828 grad_norm: 4.5748 loss: 1.9006 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9006 2023/06/05 15:36:28 - mmengine - INFO - Epoch(train) [121][2480/2569] lr: 4.0000e-03 eta: 5:30:52 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 4.5563 loss: 1.9063 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9063 2023/06/05 15:36:33 - mmengine - INFO - Epoch(train) [121][2500/2569] lr: 4.0000e-03 eta: 5:30:47 time: 0.2712 data_time: 0.0073 memory: 5828 grad_norm: 4.7118 loss: 1.8964 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8964 2023/06/05 15:36:39 - mmengine - INFO - Epoch(train) [121][2520/2569] lr: 4.0000e-03 eta: 5:30:42 time: 0.2641 data_time: 0.0071 memory: 5828 grad_norm: 4.6785 loss: 1.7126 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7126 2023/06/05 15:36:44 - mmengine - INFO - Epoch(train) [121][2540/2569] lr: 4.0000e-03 eta: 5:30:36 time: 0.2636 data_time: 0.0071 memory: 5828 grad_norm: 4.6680 loss: 1.9215 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9215 2023/06/05 15:36:49 - mmengine - INFO - Epoch(train) [121][2560/2569] lr: 4.0000e-03 eta: 5:30:31 time: 0.2657 data_time: 0.0073 memory: 5828 grad_norm: 4.6925 loss: 1.8509 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8509 2023/06/05 15:36:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:36:52 - mmengine - INFO - Epoch(train) [121][2569/2569] lr: 4.0000e-03 eta: 5:30:29 time: 0.2599 data_time: 0.0070 memory: 5828 grad_norm: 4.6979 loss: 1.8086 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8086 2023/06/05 15:36:58 - mmengine - INFO - Epoch(train) [122][ 20/2569] lr: 4.0000e-03 eta: 5:30:24 time: 0.3397 data_time: 0.0587 memory: 5828 grad_norm: 4.6163 loss: 1.6330 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6330 2023/06/05 15:37:04 - mmengine - INFO - Epoch(train) [122][ 40/2569] lr: 4.0000e-03 eta: 5:30:18 time: 0.2869 data_time: 0.0075 memory: 5828 grad_norm: 4.7383 loss: 1.8363 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8363 2023/06/05 15:37:10 - mmengine - INFO - Epoch(train) [122][ 60/2569] lr: 4.0000e-03 eta: 5:30:13 time: 0.2685 data_time: 0.0078 memory: 5828 grad_norm: 4.6721 loss: 1.6847 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6847 2023/06/05 15:37:15 - mmengine - INFO - Epoch(train) [122][ 80/2569] lr: 4.0000e-03 eta: 5:30:08 time: 0.2781 data_time: 0.0076 memory: 5828 grad_norm: 4.7176 loss: 1.7464 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7464 2023/06/05 15:37:20 - mmengine - INFO - Epoch(train) [122][ 100/2569] lr: 4.0000e-03 eta: 5:30:03 time: 0.2619 data_time: 0.0076 memory: 5828 grad_norm: 4.6129 loss: 2.0247 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0247 2023/06/05 15:37:26 - mmengine - INFO - Epoch(train) [122][ 120/2569] lr: 4.0000e-03 eta: 5:29:57 time: 0.2702 data_time: 0.0088 memory: 5828 grad_norm: 4.5428 loss: 1.9644 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9644 2023/06/05 15:37:31 - mmengine - INFO - Epoch(train) [122][ 140/2569] lr: 4.0000e-03 eta: 5:29:52 time: 0.2613 data_time: 0.0072 memory: 5828 grad_norm: 4.6974 loss: 1.5696 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5696 2023/06/05 15:37:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:37:36 - mmengine - INFO - Epoch(train) [122][ 160/2569] lr: 4.0000e-03 eta: 5:29:47 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 4.6910 loss: 1.4712 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4712 2023/06/05 15:37:42 - mmengine - INFO - Epoch(train) [122][ 180/2569] lr: 4.0000e-03 eta: 5:29:41 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 4.6788 loss: 1.8055 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8055 2023/06/05 15:37:47 - mmengine - INFO - Epoch(train) [122][ 200/2569] lr: 4.0000e-03 eta: 5:29:36 time: 0.2684 data_time: 0.0074 memory: 5828 grad_norm: 4.6513 loss: 2.1779 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1779 2023/06/05 15:37:52 - mmengine - INFO - Epoch(train) [122][ 220/2569] lr: 4.0000e-03 eta: 5:29:31 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 4.6642 loss: 1.8111 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8111 2023/06/05 15:37:58 - mmengine - INFO - Epoch(train) [122][ 240/2569] lr: 4.0000e-03 eta: 5:29:25 time: 0.2643 data_time: 0.0077 memory: 5828 grad_norm: 4.5885 loss: 1.5942 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5942 2023/06/05 15:38:03 - mmengine - INFO - Epoch(train) [122][ 260/2569] lr: 4.0000e-03 eta: 5:29:20 time: 0.2743 data_time: 0.0076 memory: 5828 grad_norm: 4.6138 loss: 1.4685 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4685 2023/06/05 15:38:08 - mmengine - INFO - Epoch(train) [122][ 280/2569] lr: 4.0000e-03 eta: 5:29:15 time: 0.2645 data_time: 0.0076 memory: 5828 grad_norm: 4.6843 loss: 1.9742 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9742 2023/06/05 15:38:14 - mmengine - INFO - Epoch(train) [122][ 300/2569] lr: 4.0000e-03 eta: 5:29:09 time: 0.2731 data_time: 0.0073 memory: 5828 grad_norm: 4.6941 loss: 1.9305 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9305 2023/06/05 15:38:19 - mmengine - INFO - Epoch(train) [122][ 320/2569] lr: 4.0000e-03 eta: 5:29:04 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 4.6354 loss: 1.8439 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8439 2023/06/05 15:38:25 - mmengine - INFO - Epoch(train) [122][ 340/2569] lr: 4.0000e-03 eta: 5:28:59 time: 0.2748 data_time: 0.0073 memory: 5828 grad_norm: 4.6311 loss: 1.8568 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8568 2023/06/05 15:38:30 - mmengine - INFO - Epoch(train) [122][ 360/2569] lr: 4.0000e-03 eta: 5:28:53 time: 0.2691 data_time: 0.0074 memory: 5828 grad_norm: 4.5988 loss: 1.4833 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4833 2023/06/05 15:38:36 - mmengine - INFO - Epoch(train) [122][ 380/2569] lr: 4.0000e-03 eta: 5:28:48 time: 0.2765 data_time: 0.0074 memory: 5828 grad_norm: 4.6200 loss: 1.5099 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5099 2023/06/05 15:38:41 - mmengine - INFO - Epoch(train) [122][ 400/2569] lr: 4.0000e-03 eta: 5:28:43 time: 0.2693 data_time: 0.0073 memory: 5828 grad_norm: 4.7036 loss: 1.4852 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4852 2023/06/05 15:38:46 - mmengine - INFO - Epoch(train) [122][ 420/2569] lr: 4.0000e-03 eta: 5:28:38 time: 0.2771 data_time: 0.0070 memory: 5828 grad_norm: 4.6332 loss: 1.9217 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9217 2023/06/05 15:38:52 - mmengine - INFO - Epoch(train) [122][ 440/2569] lr: 4.0000e-03 eta: 5:28:32 time: 0.2679 data_time: 0.0070 memory: 5828 grad_norm: 4.6617 loss: 1.7442 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7442 2023/06/05 15:38:57 - mmengine - INFO - Epoch(train) [122][ 460/2569] lr: 4.0000e-03 eta: 5:28:27 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 4.6528 loss: 1.8982 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8982 2023/06/05 15:39:03 - mmengine - INFO - Epoch(train) [122][ 480/2569] lr: 4.0000e-03 eta: 5:28:22 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 4.8046 loss: 1.8651 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8651 2023/06/05 15:39:08 - mmengine - INFO - Epoch(train) [122][ 500/2569] lr: 4.0000e-03 eta: 5:28:16 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 4.8073 loss: 1.6157 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6157 2023/06/05 15:39:13 - mmengine - INFO - Epoch(train) [122][ 520/2569] lr: 4.0000e-03 eta: 5:28:11 time: 0.2712 data_time: 0.0079 memory: 5828 grad_norm: 4.5521 loss: 1.6890 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6890 2023/06/05 15:39:19 - mmengine - INFO - Epoch(train) [122][ 540/2569] lr: 4.0000e-03 eta: 5:28:06 time: 0.2631 data_time: 0.0069 memory: 5828 grad_norm: 4.7114 loss: 1.6701 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6701 2023/06/05 15:39:24 - mmengine - INFO - Epoch(train) [122][ 560/2569] lr: 4.0000e-03 eta: 5:28:00 time: 0.2607 data_time: 0.0073 memory: 5828 grad_norm: 4.7234 loss: 1.6580 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6580 2023/06/05 15:39:29 - mmengine - INFO - Epoch(train) [122][ 580/2569] lr: 4.0000e-03 eta: 5:27:55 time: 0.2675 data_time: 0.0069 memory: 5828 grad_norm: 4.5874 loss: 2.0315 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0315 2023/06/05 15:39:35 - mmengine - INFO - Epoch(train) [122][ 600/2569] lr: 4.0000e-03 eta: 5:27:50 time: 0.2672 data_time: 0.0069 memory: 5828 grad_norm: 4.6134 loss: 1.8567 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8567 2023/06/05 15:39:40 - mmengine - INFO - Epoch(train) [122][ 620/2569] lr: 4.0000e-03 eta: 5:27:44 time: 0.2659 data_time: 0.0070 memory: 5828 grad_norm: 4.5321 loss: 1.9467 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9467 2023/06/05 15:39:45 - mmengine - INFO - Epoch(train) [122][ 640/2569] lr: 4.0000e-03 eta: 5:27:39 time: 0.2626 data_time: 0.0072 memory: 5828 grad_norm: 4.6546 loss: 1.9527 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9527 2023/06/05 15:39:51 - mmengine - INFO - Epoch(train) [122][ 660/2569] lr: 4.0000e-03 eta: 5:27:34 time: 0.2682 data_time: 0.0078 memory: 5828 grad_norm: 4.5801 loss: 1.5394 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5394 2023/06/05 15:39:56 - mmengine - INFO - Epoch(train) [122][ 680/2569] lr: 4.0000e-03 eta: 5:27:28 time: 0.2695 data_time: 0.0074 memory: 5828 grad_norm: 4.6717 loss: 2.0249 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0249 2023/06/05 15:40:01 - mmengine - INFO - Epoch(train) [122][ 700/2569] lr: 4.0000e-03 eta: 5:27:23 time: 0.2737 data_time: 0.0075 memory: 5828 grad_norm: 4.7737 loss: 1.9369 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9369 2023/06/05 15:40:07 - mmengine - INFO - Epoch(train) [122][ 720/2569] lr: 4.0000e-03 eta: 5:27:18 time: 0.2792 data_time: 0.0073 memory: 5828 grad_norm: 4.7511 loss: 1.5361 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5361 2023/06/05 15:40:12 - mmengine - INFO - Epoch(train) [122][ 740/2569] lr: 4.0000e-03 eta: 5:27:13 time: 0.2692 data_time: 0.0074 memory: 5828 grad_norm: 4.7469 loss: 1.7671 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.7671 2023/06/05 15:40:18 - mmengine - INFO - Epoch(train) [122][ 760/2569] lr: 4.0000e-03 eta: 5:27:07 time: 0.2715 data_time: 0.0072 memory: 5828 grad_norm: 4.6175 loss: 1.8012 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8012 2023/06/05 15:40:23 - mmengine - INFO - Epoch(train) [122][ 780/2569] lr: 4.0000e-03 eta: 5:27:02 time: 0.2733 data_time: 0.0071 memory: 5828 grad_norm: 4.6586 loss: 1.7531 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7531 2023/06/05 15:40:29 - mmengine - INFO - Epoch(train) [122][ 800/2569] lr: 4.0000e-03 eta: 5:26:57 time: 0.2716 data_time: 0.0078 memory: 5828 grad_norm: 4.6179 loss: 1.6847 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6847 2023/06/05 15:40:34 - mmengine - INFO - Epoch(train) [122][ 820/2569] lr: 4.0000e-03 eta: 5:26:51 time: 0.2629 data_time: 0.0073 memory: 5828 grad_norm: 4.6128 loss: 1.7133 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7133 2023/06/05 15:40:39 - mmengine - INFO - Epoch(train) [122][ 840/2569] lr: 4.0000e-03 eta: 5:26:46 time: 0.2667 data_time: 0.0090 memory: 5828 grad_norm: 4.7009 loss: 1.6673 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6673 2023/06/05 15:40:45 - mmengine - INFO - Epoch(train) [122][ 860/2569] lr: 4.0000e-03 eta: 5:26:41 time: 0.2625 data_time: 0.0069 memory: 5828 grad_norm: 4.6422 loss: 1.5424 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5424 2023/06/05 15:40:50 - mmengine - INFO - Epoch(train) [122][ 880/2569] lr: 4.0000e-03 eta: 5:26:35 time: 0.2636 data_time: 0.0072 memory: 5828 grad_norm: 4.6577 loss: 1.9108 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9108 2023/06/05 15:40:55 - mmengine - INFO - Epoch(train) [122][ 900/2569] lr: 4.0000e-03 eta: 5:26:30 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 4.7222 loss: 2.2892 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2892 2023/06/05 15:41:01 - mmengine - INFO - Epoch(train) [122][ 920/2569] lr: 4.0000e-03 eta: 5:26:25 time: 0.2720 data_time: 0.0076 memory: 5828 grad_norm: 4.6551 loss: 1.9153 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9153 2023/06/05 15:41:06 - mmengine - INFO - Epoch(train) [122][ 940/2569] lr: 4.0000e-03 eta: 5:26:19 time: 0.2668 data_time: 0.0070 memory: 5828 grad_norm: 4.6436 loss: 1.8565 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8565 2023/06/05 15:41:11 - mmengine - INFO - Epoch(train) [122][ 960/2569] lr: 4.0000e-03 eta: 5:26:14 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 4.6123 loss: 1.8814 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8814 2023/06/05 15:41:17 - mmengine - INFO - Epoch(train) [122][ 980/2569] lr: 4.0000e-03 eta: 5:26:09 time: 0.2719 data_time: 0.0077 memory: 5828 grad_norm: 4.7438 loss: 1.7198 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7198 2023/06/05 15:41:22 - mmengine - INFO - Epoch(train) [122][1000/2569] lr: 4.0000e-03 eta: 5:26:03 time: 0.2724 data_time: 0.0072 memory: 5828 grad_norm: 4.6723 loss: 1.5287 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5287 2023/06/05 15:41:27 - mmengine - INFO - Epoch(train) [122][1020/2569] lr: 4.0000e-03 eta: 5:25:58 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 4.7193 loss: 1.7587 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7587 2023/06/05 15:41:33 - mmengine - INFO - Epoch(train) [122][1040/2569] lr: 4.0000e-03 eta: 5:25:53 time: 0.2745 data_time: 0.0071 memory: 5828 grad_norm: 4.6019 loss: 1.4494 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4494 2023/06/05 15:41:38 - mmengine - INFO - Epoch(train) [122][1060/2569] lr: 4.0000e-03 eta: 5:25:47 time: 0.2610 data_time: 0.0079 memory: 5828 grad_norm: 4.7193 loss: 1.9214 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9214 2023/06/05 15:41:44 - mmengine - INFO - Epoch(train) [122][1080/2569] lr: 4.0000e-03 eta: 5:25:42 time: 0.2661 data_time: 0.0071 memory: 5828 grad_norm: 4.6624 loss: 1.4456 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4456 2023/06/05 15:41:49 - mmengine - INFO - Epoch(train) [122][1100/2569] lr: 4.0000e-03 eta: 5:25:37 time: 0.2648 data_time: 0.0070 memory: 5828 grad_norm: 4.6506 loss: 2.0662 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0662 2023/06/05 15:41:54 - mmengine - INFO - Epoch(train) [122][1120/2569] lr: 4.0000e-03 eta: 5:25:32 time: 0.2676 data_time: 0.0074 memory: 5828 grad_norm: 4.7343 loss: 1.7928 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7928 2023/06/05 15:42:00 - mmengine - INFO - Epoch(train) [122][1140/2569] lr: 4.0000e-03 eta: 5:25:26 time: 0.2700 data_time: 0.0071 memory: 5828 grad_norm: 4.6189 loss: 1.7043 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7043 2023/06/05 15:42:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:42:05 - mmengine - INFO - Epoch(train) [122][1160/2569] lr: 4.0000e-03 eta: 5:25:21 time: 0.2615 data_time: 0.0073 memory: 5828 grad_norm: 4.6948 loss: 1.5754 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5754 2023/06/05 15:42:10 - mmengine - INFO - Epoch(train) [122][1180/2569] lr: 4.0000e-03 eta: 5:25:16 time: 0.2792 data_time: 0.0075 memory: 5828 grad_norm: 4.5765 loss: 1.5554 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5554 2023/06/05 15:42:16 - mmengine - INFO - Epoch(train) [122][1200/2569] lr: 4.0000e-03 eta: 5:25:10 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 4.6663 loss: 1.9412 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9412 2023/06/05 15:42:21 - mmengine - INFO - Epoch(train) [122][1220/2569] lr: 4.0000e-03 eta: 5:25:05 time: 0.2736 data_time: 0.0072 memory: 5828 grad_norm: 4.6918 loss: 2.0156 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0156 2023/06/05 15:42:27 - mmengine - INFO - Epoch(train) [122][1240/2569] lr: 4.0000e-03 eta: 5:25:00 time: 0.2716 data_time: 0.0074 memory: 5828 grad_norm: 4.8833 loss: 1.8853 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8853 2023/06/05 15:42:32 - mmengine - INFO - Epoch(train) [122][1260/2569] lr: 4.0000e-03 eta: 5:24:54 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 4.6635 loss: 1.7119 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7119 2023/06/05 15:42:37 - mmengine - INFO - Epoch(train) [122][1280/2569] lr: 4.0000e-03 eta: 5:24:49 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 4.7562 loss: 1.7603 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7603 2023/06/05 15:42:42 - mmengine - INFO - Epoch(train) [122][1300/2569] lr: 4.0000e-03 eta: 5:24:44 time: 0.2607 data_time: 0.0076 memory: 5828 grad_norm: 4.7415 loss: 1.8069 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8069 2023/06/05 15:42:48 - mmengine - INFO - Epoch(train) [122][1320/2569] lr: 4.0000e-03 eta: 5:24:38 time: 0.2647 data_time: 0.0072 memory: 5828 grad_norm: 4.6162 loss: 1.7012 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7012 2023/06/05 15:42:53 - mmengine - INFO - Epoch(train) [122][1340/2569] lr: 4.0000e-03 eta: 5:24:33 time: 0.2624 data_time: 0.0092 memory: 5828 grad_norm: 4.6928 loss: 1.8201 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8201 2023/06/05 15:42:58 - mmengine - INFO - Epoch(train) [122][1360/2569] lr: 4.0000e-03 eta: 5:24:28 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 4.7360 loss: 1.6357 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6357 2023/06/05 15:43:04 - mmengine - INFO - Epoch(train) [122][1380/2569] lr: 4.0000e-03 eta: 5:24:22 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 4.7096 loss: 1.7314 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7314 2023/06/05 15:43:09 - mmengine - INFO - Epoch(train) [122][1400/2569] lr: 4.0000e-03 eta: 5:24:17 time: 0.2678 data_time: 0.0074 memory: 5828 grad_norm: 4.7322 loss: 1.5368 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5368 2023/06/05 15:43:14 - mmengine - INFO - Epoch(train) [122][1420/2569] lr: 4.0000e-03 eta: 5:24:12 time: 0.2642 data_time: 0.0071 memory: 5828 grad_norm: 4.6579 loss: 2.0423 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0423 2023/06/05 15:43:20 - mmengine - INFO - Epoch(train) [122][1440/2569] lr: 4.0000e-03 eta: 5:24:06 time: 0.2658 data_time: 0.0073 memory: 5828 grad_norm: 4.6648 loss: 2.0240 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0240 2023/06/05 15:43:25 - mmengine - INFO - Epoch(train) [122][1460/2569] lr: 4.0000e-03 eta: 5:24:01 time: 0.2646 data_time: 0.0072 memory: 5828 grad_norm: 4.7192 loss: 1.6241 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6241 2023/06/05 15:43:30 - mmengine - INFO - Epoch(train) [122][1480/2569] lr: 4.0000e-03 eta: 5:23:56 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 4.6756 loss: 1.6547 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6547 2023/06/05 15:43:36 - mmengine - INFO - Epoch(train) [122][1500/2569] lr: 4.0000e-03 eta: 5:23:50 time: 0.2642 data_time: 0.0071 memory: 5828 grad_norm: 4.6680 loss: 1.8250 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8250 2023/06/05 15:43:41 - mmengine - INFO - Epoch(train) [122][1520/2569] lr: 4.0000e-03 eta: 5:23:45 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 4.6478 loss: 1.7948 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7948 2023/06/05 15:43:46 - mmengine - INFO - Epoch(train) [122][1540/2569] lr: 4.0000e-03 eta: 5:23:40 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 4.6278 loss: 1.5741 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5741 2023/06/05 15:43:52 - mmengine - INFO - Epoch(train) [122][1560/2569] lr: 4.0000e-03 eta: 5:23:34 time: 0.2658 data_time: 0.0076 memory: 5828 grad_norm: 4.6685 loss: 2.0418 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0418 2023/06/05 15:43:57 - mmengine - INFO - Epoch(train) [122][1580/2569] lr: 4.0000e-03 eta: 5:23:29 time: 0.2690 data_time: 0.0068 memory: 5828 grad_norm: 4.7197 loss: 1.8088 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8088 2023/06/05 15:44:02 - mmengine - INFO - Epoch(train) [122][1600/2569] lr: 4.0000e-03 eta: 5:23:24 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 4.7353 loss: 1.7745 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7745 2023/06/05 15:44:08 - mmengine - INFO - Epoch(train) [122][1620/2569] lr: 4.0000e-03 eta: 5:23:18 time: 0.2713 data_time: 0.0072 memory: 5828 grad_norm: 4.6332 loss: 1.7749 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7749 2023/06/05 15:44:13 - mmengine - INFO - Epoch(train) [122][1640/2569] lr: 4.0000e-03 eta: 5:23:13 time: 0.2626 data_time: 0.0071 memory: 5828 grad_norm: 4.8059 loss: 1.8195 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8195 2023/06/05 15:44:18 - mmengine - INFO - Epoch(train) [122][1660/2569] lr: 4.0000e-03 eta: 5:23:08 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 4.7193 loss: 1.7608 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7608 2023/06/05 15:44:24 - mmengine - INFO - Epoch(train) [122][1680/2569] lr: 4.0000e-03 eta: 5:23:02 time: 0.2669 data_time: 0.0072 memory: 5828 grad_norm: 4.7065 loss: 1.8885 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8885 2023/06/05 15:44:29 - mmengine - INFO - Epoch(train) [122][1700/2569] lr: 4.0000e-03 eta: 5:22:57 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 4.6764 loss: 1.9302 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9302 2023/06/05 15:44:35 - mmengine - INFO - Epoch(train) [122][1720/2569] lr: 4.0000e-03 eta: 5:22:52 time: 0.2743 data_time: 0.0071 memory: 5828 grad_norm: 4.6474 loss: 1.8448 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8448 2023/06/05 15:44:40 - mmengine - INFO - Epoch(train) [122][1740/2569] lr: 4.0000e-03 eta: 5:22:47 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 4.6647 loss: 2.2073 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2073 2023/06/05 15:44:45 - mmengine - INFO - Epoch(train) [122][1760/2569] lr: 4.0000e-03 eta: 5:22:41 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 4.7132 loss: 1.6573 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6573 2023/06/05 15:44:50 - mmengine - INFO - Epoch(train) [122][1780/2569] lr: 4.0000e-03 eta: 5:22:36 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 4.6466 loss: 1.9325 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9325 2023/06/05 15:44:56 - mmengine - INFO - Epoch(train) [122][1800/2569] lr: 4.0000e-03 eta: 5:22:31 time: 0.2685 data_time: 0.0079 memory: 5828 grad_norm: 4.7254 loss: 2.0119 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0119 2023/06/05 15:45:01 - mmengine - INFO - Epoch(train) [122][1820/2569] lr: 4.0000e-03 eta: 5:22:25 time: 0.2612 data_time: 0.0077 memory: 5828 grad_norm: 4.7005 loss: 1.7164 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7164 2023/06/05 15:45:06 - mmengine - INFO - Epoch(train) [122][1840/2569] lr: 4.0000e-03 eta: 5:22:20 time: 0.2652 data_time: 0.0074 memory: 5828 grad_norm: 4.6729 loss: 1.9830 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9830 2023/06/05 15:45:12 - mmengine - INFO - Epoch(train) [122][1860/2569] lr: 4.0000e-03 eta: 5:22:15 time: 0.2681 data_time: 0.0073 memory: 5828 grad_norm: 4.6462 loss: 1.7844 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7844 2023/06/05 15:45:17 - mmengine - INFO - Epoch(train) [122][1880/2569] lr: 4.0000e-03 eta: 5:22:09 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 4.6064 loss: 1.6203 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6203 2023/06/05 15:45:22 - mmengine - INFO - Epoch(train) [122][1900/2569] lr: 4.0000e-03 eta: 5:22:04 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 4.6944 loss: 2.1686 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1686 2023/06/05 15:45:28 - mmengine - INFO - Epoch(train) [122][1920/2569] lr: 4.0000e-03 eta: 5:21:59 time: 0.2738 data_time: 0.0074 memory: 5828 grad_norm: 4.6973 loss: 1.9464 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9464 2023/06/05 15:45:33 - mmengine - INFO - Epoch(train) [122][1940/2569] lr: 4.0000e-03 eta: 5:21:53 time: 0.2614 data_time: 0.0078 memory: 5828 grad_norm: 4.6625 loss: 1.5677 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.5677 2023/06/05 15:45:39 - mmengine - INFO - Epoch(train) [122][1960/2569] lr: 4.0000e-03 eta: 5:21:48 time: 0.2719 data_time: 0.0069 memory: 5828 grad_norm: 4.7040 loss: 2.0348 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0348 2023/06/05 15:45:44 - mmengine - INFO - Epoch(train) [122][1980/2569] lr: 4.0000e-03 eta: 5:21:43 time: 0.2649 data_time: 0.0077 memory: 5828 grad_norm: 4.7493 loss: 1.8692 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8692 2023/06/05 15:45:49 - mmengine - INFO - Epoch(train) [122][2000/2569] lr: 4.0000e-03 eta: 5:21:37 time: 0.2699 data_time: 0.0069 memory: 5828 grad_norm: 4.6297 loss: 2.0445 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0445 2023/06/05 15:45:55 - mmengine - INFO - Epoch(train) [122][2020/2569] lr: 4.0000e-03 eta: 5:21:32 time: 0.2608 data_time: 0.0070 memory: 5828 grad_norm: 4.6117 loss: 1.6173 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6173 2023/06/05 15:46:00 - mmengine - INFO - Epoch(train) [122][2040/2569] lr: 4.0000e-03 eta: 5:21:27 time: 0.2668 data_time: 0.0067 memory: 5828 grad_norm: 4.5990 loss: 1.8797 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8797 2023/06/05 15:46:05 - mmengine - INFO - Epoch(train) [122][2060/2569] lr: 4.0000e-03 eta: 5:21:21 time: 0.2689 data_time: 0.0070 memory: 5828 grad_norm: 4.7828 loss: 1.6058 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6058 2023/06/05 15:46:11 - mmengine - INFO - Epoch(train) [122][2080/2569] lr: 4.0000e-03 eta: 5:21:16 time: 0.2642 data_time: 0.0072 memory: 5828 grad_norm: 4.6634 loss: 1.7282 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7282 2023/06/05 15:46:16 - mmengine - INFO - Epoch(train) [122][2100/2569] lr: 4.0000e-03 eta: 5:21:11 time: 0.2660 data_time: 0.0070 memory: 5828 grad_norm: 4.6146 loss: 1.5637 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5637 2023/06/05 15:46:21 - mmengine - INFO - Epoch(train) [122][2120/2569] lr: 4.0000e-03 eta: 5:21:05 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 4.6953 loss: 1.5346 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5346 2023/06/05 15:46:27 - mmengine - INFO - Epoch(train) [122][2140/2569] lr: 4.0000e-03 eta: 5:21:00 time: 0.2662 data_time: 0.0081 memory: 5828 grad_norm: 4.7026 loss: 1.6139 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6139 2023/06/05 15:46:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:46:32 - mmengine - INFO - Epoch(train) [122][2160/2569] lr: 4.0000e-03 eta: 5:20:55 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 4.7791 loss: 1.8048 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8048 2023/06/05 15:46:37 - mmengine - INFO - Epoch(train) [122][2180/2569] lr: 4.0000e-03 eta: 5:20:49 time: 0.2617 data_time: 0.0076 memory: 5828 grad_norm: 4.6834 loss: 1.4156 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.4156 2023/06/05 15:46:43 - mmengine - INFO - Epoch(train) [122][2200/2569] lr: 4.0000e-03 eta: 5:20:44 time: 0.2743 data_time: 0.0080 memory: 5828 grad_norm: 4.6643 loss: 1.8551 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8551 2023/06/05 15:46:48 - mmengine - INFO - Epoch(train) [122][2220/2569] lr: 4.0000e-03 eta: 5:20:39 time: 0.2630 data_time: 0.0073 memory: 5828 grad_norm: 4.6845 loss: 1.7171 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7171 2023/06/05 15:46:53 - mmengine - INFO - Epoch(train) [122][2240/2569] lr: 4.0000e-03 eta: 5:20:34 time: 0.2725 data_time: 0.0074 memory: 5828 grad_norm: 4.7842 loss: 1.6950 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6950 2023/06/05 15:46:59 - mmengine - INFO - Epoch(train) [122][2260/2569] lr: 4.0000e-03 eta: 5:20:28 time: 0.2624 data_time: 0.0074 memory: 5828 grad_norm: 4.7161 loss: 1.7187 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.7187 2023/06/05 15:47:04 - mmengine - INFO - Epoch(train) [122][2280/2569] lr: 4.0000e-03 eta: 5:20:23 time: 0.2729 data_time: 0.0072 memory: 5828 grad_norm: 4.7304 loss: 2.1504 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1504 2023/06/05 15:47:10 - mmengine - INFO - Epoch(train) [122][2300/2569] lr: 4.0000e-03 eta: 5:20:18 time: 0.2677 data_time: 0.0076 memory: 5828 grad_norm: 4.7191 loss: 1.7735 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7735 2023/06/05 15:47:15 - mmengine - INFO - Epoch(train) [122][2320/2569] lr: 4.0000e-03 eta: 5:20:12 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 4.7342 loss: 1.6624 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6624 2023/06/05 15:47:20 - mmengine - INFO - Epoch(train) [122][2340/2569] lr: 4.0000e-03 eta: 5:20:07 time: 0.2628 data_time: 0.0070 memory: 5828 grad_norm: 4.6823 loss: 1.8920 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8920 2023/06/05 15:47:25 - mmengine - INFO - Epoch(train) [122][2360/2569] lr: 4.0000e-03 eta: 5:20:02 time: 0.2669 data_time: 0.0077 memory: 5828 grad_norm: 4.7440 loss: 1.8558 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8558 2023/06/05 15:47:31 - mmengine - INFO - Epoch(train) [122][2380/2569] lr: 4.0000e-03 eta: 5:19:56 time: 0.2605 data_time: 0.0070 memory: 5828 grad_norm: 4.7096 loss: 1.7890 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7890 2023/06/05 15:47:36 - mmengine - INFO - Epoch(train) [122][2400/2569] lr: 4.0000e-03 eta: 5:19:51 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 4.6922 loss: 1.6709 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6709 2023/06/05 15:47:42 - mmengine - INFO - Epoch(train) [122][2420/2569] lr: 4.0000e-03 eta: 5:19:46 time: 0.2789 data_time: 0.0070 memory: 5828 grad_norm: 4.7368 loss: 1.4216 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4216 2023/06/05 15:47:47 - mmengine - INFO - Epoch(train) [122][2440/2569] lr: 4.0000e-03 eta: 5:19:40 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 4.7694 loss: 1.9761 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 1.9761 2023/06/05 15:47:52 - mmengine - INFO - Epoch(train) [122][2460/2569] lr: 4.0000e-03 eta: 5:19:35 time: 0.2733 data_time: 0.0069 memory: 5828 grad_norm: 4.7499 loss: 2.0585 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0585 2023/06/05 15:47:58 - mmengine - INFO - Epoch(train) [122][2480/2569] lr: 4.0000e-03 eta: 5:19:30 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 4.7302 loss: 1.8108 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8108 2023/06/05 15:48:03 - mmengine - INFO - Epoch(train) [122][2500/2569] lr: 4.0000e-03 eta: 5:19:24 time: 0.2709 data_time: 0.0070 memory: 5828 grad_norm: 4.7076 loss: 1.6874 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6874 2023/06/05 15:48:08 - mmengine - INFO - Epoch(train) [122][2520/2569] lr: 4.0000e-03 eta: 5:19:19 time: 0.2616 data_time: 0.0069 memory: 5828 grad_norm: 4.6661 loss: 1.6617 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6617 2023/06/05 15:48:14 - mmengine - INFO - Epoch(train) [122][2540/2569] lr: 4.0000e-03 eta: 5:19:14 time: 0.2713 data_time: 0.0071 memory: 5828 grad_norm: 4.7535 loss: 1.6877 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6877 2023/06/05 15:48:19 - mmengine - INFO - Epoch(train) [122][2560/2569] lr: 4.0000e-03 eta: 5:19:08 time: 0.2596 data_time: 0.0070 memory: 5828 grad_norm: 4.6966 loss: 1.3435 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3435 2023/06/05 15:48:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:48:21 - mmengine - INFO - Epoch(train) [122][2569/2569] lr: 4.0000e-03 eta: 5:19:06 time: 0.2538 data_time: 0.0065 memory: 5828 grad_norm: 4.7192 loss: 1.4884 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4884 2023/06/05 15:48:28 - mmengine - INFO - Epoch(train) [123][ 20/2569] lr: 4.0000e-03 eta: 5:19:01 time: 0.3366 data_time: 0.0497 memory: 5828 grad_norm: 4.7270 loss: 1.8467 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8467 2023/06/05 15:48:33 - mmengine - INFO - Epoch(train) [123][ 40/2569] lr: 4.0000e-03 eta: 5:18:56 time: 0.2709 data_time: 0.0070 memory: 5828 grad_norm: 4.6193 loss: 1.7662 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7662 2023/06/05 15:48:39 - mmengine - INFO - Epoch(train) [123][ 60/2569] lr: 4.0000e-03 eta: 5:18:50 time: 0.2630 data_time: 0.0075 memory: 5828 grad_norm: 4.6628 loss: 1.6352 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6352 2023/06/05 15:48:44 - mmengine - INFO - Epoch(train) [123][ 80/2569] lr: 4.0000e-03 eta: 5:18:45 time: 0.2730 data_time: 0.0073 memory: 5828 grad_norm: 4.8422 loss: 1.7597 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7597 2023/06/05 15:48:49 - mmengine - INFO - Epoch(train) [123][ 100/2569] lr: 4.0000e-03 eta: 5:18:40 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 4.6760 loss: 1.9943 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9943 2023/06/05 15:48:55 - mmengine - INFO - Epoch(train) [123][ 120/2569] lr: 4.0000e-03 eta: 5:18:34 time: 0.2729 data_time: 0.0074 memory: 5828 grad_norm: 4.6805 loss: 1.9167 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9167 2023/06/05 15:49:00 - mmengine - INFO - Epoch(train) [123][ 140/2569] lr: 4.0000e-03 eta: 5:18:29 time: 0.2642 data_time: 0.0075 memory: 5828 grad_norm: 4.7614 loss: 1.7879 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7879 2023/06/05 15:49:06 - mmengine - INFO - Epoch(train) [123][ 160/2569] lr: 4.0000e-03 eta: 5:18:24 time: 0.2721 data_time: 0.0071 memory: 5828 grad_norm: 4.7199 loss: 1.4642 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4642 2023/06/05 15:49:11 - mmengine - INFO - Epoch(train) [123][ 180/2569] lr: 4.0000e-03 eta: 5:18:18 time: 0.2618 data_time: 0.0071 memory: 5828 grad_norm: 4.6285 loss: 1.5822 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5822 2023/06/05 15:49:16 - mmengine - INFO - Epoch(train) [123][ 200/2569] lr: 4.0000e-03 eta: 5:18:13 time: 0.2714 data_time: 0.0072 memory: 5828 grad_norm: 4.6973 loss: 1.7857 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7857 2023/06/05 15:49:22 - mmengine - INFO - Epoch(train) [123][ 220/2569] lr: 4.0000e-03 eta: 5:18:08 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 4.6631 loss: 1.5513 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5513 2023/06/05 15:49:27 - mmengine - INFO - Epoch(train) [123][ 240/2569] lr: 4.0000e-03 eta: 5:18:02 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 4.6766 loss: 1.6716 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6716 2023/06/05 15:49:32 - mmengine - INFO - Epoch(train) [123][ 260/2569] lr: 4.0000e-03 eta: 5:17:57 time: 0.2629 data_time: 0.0070 memory: 5828 grad_norm: 4.6424 loss: 1.4220 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4220 2023/06/05 15:49:38 - mmengine - INFO - Epoch(train) [123][ 280/2569] lr: 4.0000e-03 eta: 5:17:52 time: 0.2682 data_time: 0.0071 memory: 5828 grad_norm: 4.7124 loss: 2.0497 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0497 2023/06/05 15:49:43 - mmengine - INFO - Epoch(train) [123][ 300/2569] lr: 4.0000e-03 eta: 5:17:47 time: 0.2768 data_time: 0.0072 memory: 5828 grad_norm: 4.6847 loss: 1.7019 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7019 2023/06/05 15:49:49 - mmengine - INFO - Epoch(train) [123][ 320/2569] lr: 4.0000e-03 eta: 5:17:41 time: 0.2781 data_time: 0.0072 memory: 5828 grad_norm: 4.7243 loss: 1.8367 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8367 2023/06/05 15:49:54 - mmengine - INFO - Epoch(train) [123][ 340/2569] lr: 4.0000e-03 eta: 5:17:36 time: 0.2695 data_time: 0.0071 memory: 5828 grad_norm: 4.6907 loss: 1.7498 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7498 2023/06/05 15:49:59 - mmengine - INFO - Epoch(train) [123][ 360/2569] lr: 4.0000e-03 eta: 5:17:31 time: 0.2683 data_time: 0.0074 memory: 5828 grad_norm: 4.7258 loss: 1.6932 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6932 2023/06/05 15:50:05 - mmengine - INFO - Epoch(train) [123][ 380/2569] lr: 4.0000e-03 eta: 5:17:25 time: 0.2650 data_time: 0.0071 memory: 5828 grad_norm: 4.8083 loss: 1.9011 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9011 2023/06/05 15:50:10 - mmengine - INFO - Epoch(train) [123][ 400/2569] lr: 4.0000e-03 eta: 5:17:20 time: 0.2606 data_time: 0.0077 memory: 5828 grad_norm: 4.6636 loss: 1.6115 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6115 2023/06/05 15:50:15 - mmengine - INFO - Epoch(train) [123][ 420/2569] lr: 4.0000e-03 eta: 5:17:15 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 4.6460 loss: 1.7501 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7501 2023/06/05 15:50:21 - mmengine - INFO - Epoch(train) [123][ 440/2569] lr: 4.0000e-03 eta: 5:17:09 time: 0.2666 data_time: 0.0072 memory: 5828 grad_norm: 4.6490 loss: 1.7788 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7788 2023/06/05 15:50:26 - mmengine - INFO - Epoch(train) [123][ 460/2569] lr: 4.0000e-03 eta: 5:17:04 time: 0.2758 data_time: 0.0074 memory: 5828 grad_norm: 4.6856 loss: 1.8880 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8880 2023/06/05 15:50:32 - mmengine - INFO - Epoch(train) [123][ 480/2569] lr: 4.0000e-03 eta: 5:16:59 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 4.6977 loss: 2.0556 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0556 2023/06/05 15:50:37 - mmengine - INFO - Epoch(train) [123][ 500/2569] lr: 4.0000e-03 eta: 5:16:53 time: 0.2622 data_time: 0.0071 memory: 5828 grad_norm: 4.6679 loss: 1.5222 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5222 2023/06/05 15:50:42 - mmengine - INFO - Epoch(train) [123][ 520/2569] lr: 4.0000e-03 eta: 5:16:48 time: 0.2720 data_time: 0.0080 memory: 5828 grad_norm: 4.7753 loss: 1.8468 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8468 2023/06/05 15:50:48 - mmengine - INFO - Epoch(train) [123][ 540/2569] lr: 4.0000e-03 eta: 5:16:43 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 4.7203 loss: 1.5377 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5377 2023/06/05 15:50:53 - mmengine - INFO - Epoch(train) [123][ 560/2569] lr: 4.0000e-03 eta: 5:16:37 time: 0.2659 data_time: 0.0080 memory: 5828 grad_norm: 4.7118 loss: 2.0185 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0185 2023/06/05 15:50:58 - mmengine - INFO - Epoch(train) [123][ 580/2569] lr: 4.0000e-03 eta: 5:16:32 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 4.7620 loss: 1.7880 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.7880 2023/06/05 15:50:59 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:51:03 - mmengine - INFO - Epoch(train) [123][ 600/2569] lr: 4.0000e-03 eta: 5:16:27 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 4.6728 loss: 2.0439 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0439 2023/06/05 15:51:09 - mmengine - INFO - Epoch(train) [123][ 620/2569] lr: 4.0000e-03 eta: 5:16:21 time: 0.2712 data_time: 0.0072 memory: 5828 grad_norm: 4.7211 loss: 1.7558 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7558 2023/06/05 15:51:14 - mmengine - INFO - Epoch(train) [123][ 640/2569] lr: 4.0000e-03 eta: 5:16:16 time: 0.2696 data_time: 0.0083 memory: 5828 grad_norm: 4.7946 loss: 1.7224 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7224 2023/06/05 15:51:20 - mmengine - INFO - Epoch(train) [123][ 660/2569] lr: 4.0000e-03 eta: 5:16:11 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 4.6947 loss: 2.0302 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0302 2023/06/05 15:51:25 - mmengine - INFO - Epoch(train) [123][ 680/2569] lr: 4.0000e-03 eta: 5:16:05 time: 0.2698 data_time: 0.0076 memory: 5828 grad_norm: 4.7581 loss: 2.0355 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0355 2023/06/05 15:51:30 - mmengine - INFO - Epoch(train) [123][ 700/2569] lr: 4.0000e-03 eta: 5:16:00 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 4.7754 loss: 1.7994 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 1.7994 2023/06/05 15:51:36 - mmengine - INFO - Epoch(train) [123][ 720/2569] lr: 4.0000e-03 eta: 5:15:55 time: 0.2728 data_time: 0.0070 memory: 5828 grad_norm: 4.6202 loss: 1.7950 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7950 2023/06/05 15:51:41 - mmengine - INFO - Epoch(train) [123][ 740/2569] lr: 4.0000e-03 eta: 5:15:50 time: 0.2637 data_time: 0.0071 memory: 5828 grad_norm: 4.7272 loss: 1.7902 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7902 2023/06/05 15:51:46 - mmengine - INFO - Epoch(train) [123][ 760/2569] lr: 4.0000e-03 eta: 5:15:44 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 4.7920 loss: 1.9690 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9690 2023/06/05 15:51:52 - mmengine - INFO - Epoch(train) [123][ 780/2569] lr: 4.0000e-03 eta: 5:15:39 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 4.6205 loss: 1.7841 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7841 2023/06/05 15:51:57 - mmengine - INFO - Epoch(train) [123][ 800/2569] lr: 4.0000e-03 eta: 5:15:34 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 4.8152 loss: 1.5410 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5410 2023/06/05 15:52:02 - mmengine - INFO - Epoch(train) [123][ 820/2569] lr: 4.0000e-03 eta: 5:15:28 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 4.7238 loss: 1.5600 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5600 2023/06/05 15:52:08 - mmengine - INFO - Epoch(train) [123][ 840/2569] lr: 4.0000e-03 eta: 5:15:23 time: 0.2752 data_time: 0.0072 memory: 5828 grad_norm: 4.7520 loss: 1.9298 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9298 2023/06/05 15:52:13 - mmengine - INFO - Epoch(train) [123][ 860/2569] lr: 4.0000e-03 eta: 5:15:18 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 4.9094 loss: 1.6111 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6111 2023/06/05 15:52:19 - mmengine - INFO - Epoch(train) [123][ 880/2569] lr: 4.0000e-03 eta: 5:15:12 time: 0.2686 data_time: 0.0073 memory: 5828 grad_norm: 4.7320 loss: 1.8161 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8161 2023/06/05 15:52:24 - mmengine - INFO - Epoch(train) [123][ 900/2569] lr: 4.0000e-03 eta: 5:15:07 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 4.7637 loss: 1.6564 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6564 2023/06/05 15:52:30 - mmengine - INFO - Epoch(train) [123][ 920/2569] lr: 4.0000e-03 eta: 5:15:02 time: 0.2819 data_time: 0.0069 memory: 5828 grad_norm: 4.6779 loss: 1.5119 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5119 2023/06/05 15:52:35 - mmengine - INFO - Epoch(train) [123][ 940/2569] lr: 4.0000e-03 eta: 5:14:56 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 4.7034 loss: 1.6320 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6320 2023/06/05 15:52:41 - mmengine - INFO - Epoch(train) [123][ 960/2569] lr: 4.0000e-03 eta: 5:14:51 time: 0.2802 data_time: 0.0073 memory: 5828 grad_norm: 4.6660 loss: 1.9096 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9096 2023/06/05 15:52:46 - mmengine - INFO - Epoch(train) [123][ 980/2569] lr: 4.0000e-03 eta: 5:14:46 time: 0.2609 data_time: 0.0072 memory: 5828 grad_norm: 4.7396 loss: 2.0257 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0257 2023/06/05 15:52:51 - mmengine - INFO - Epoch(train) [123][1000/2569] lr: 4.0000e-03 eta: 5:14:40 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 4.6269 loss: 1.8129 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8129 2023/06/05 15:52:56 - mmengine - INFO - Epoch(train) [123][1020/2569] lr: 4.0000e-03 eta: 5:14:35 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 4.7464 loss: 1.8879 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8879 2023/06/05 15:53:02 - mmengine - INFO - Epoch(train) [123][1040/2569] lr: 4.0000e-03 eta: 5:14:30 time: 0.2636 data_time: 0.0070 memory: 5828 grad_norm: 4.6894 loss: 1.6515 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6515 2023/06/05 15:53:07 - mmengine - INFO - Epoch(train) [123][1060/2569] lr: 4.0000e-03 eta: 5:14:24 time: 0.2666 data_time: 0.0071 memory: 5828 grad_norm: 4.6910 loss: 1.6162 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6162 2023/06/05 15:53:12 - mmengine - INFO - Epoch(train) [123][1080/2569] lr: 4.0000e-03 eta: 5:14:19 time: 0.2613 data_time: 0.0071 memory: 5828 grad_norm: 4.7331 loss: 1.9043 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9043 2023/06/05 15:53:18 - mmengine - INFO - Epoch(train) [123][1100/2569] lr: 4.0000e-03 eta: 5:14:14 time: 0.2724 data_time: 0.0073 memory: 5828 grad_norm: 4.7795 loss: 1.6120 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6120 2023/06/05 15:53:23 - mmengine - INFO - Epoch(train) [123][1120/2569] lr: 4.0000e-03 eta: 5:14:08 time: 0.2626 data_time: 0.0077 memory: 5828 grad_norm: 4.7690 loss: 1.7425 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7425 2023/06/05 15:53:28 - mmengine - INFO - Epoch(train) [123][1140/2569] lr: 4.0000e-03 eta: 5:14:03 time: 0.2735 data_time: 0.0075 memory: 5828 grad_norm: 4.7080 loss: 1.8073 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8073 2023/06/05 15:53:34 - mmengine - INFO - Epoch(train) [123][1160/2569] lr: 4.0000e-03 eta: 5:13:58 time: 0.2752 data_time: 0.0073 memory: 5828 grad_norm: 4.6548 loss: 1.8093 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8093 2023/06/05 15:53:39 - mmengine - INFO - Epoch(train) [123][1180/2569] lr: 4.0000e-03 eta: 5:13:53 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 4.7081 loss: 1.9637 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9637 2023/06/05 15:53:45 - mmengine - INFO - Epoch(train) [123][1200/2569] lr: 4.0000e-03 eta: 5:13:47 time: 0.2670 data_time: 0.0074 memory: 5828 grad_norm: 4.6327 loss: 1.9620 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9620 2023/06/05 15:53:50 - mmengine - INFO - Epoch(train) [123][1220/2569] lr: 4.0000e-03 eta: 5:13:42 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 4.6876 loss: 1.9089 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9089 2023/06/05 15:53:55 - mmengine - INFO - Epoch(train) [123][1240/2569] lr: 4.0000e-03 eta: 5:13:37 time: 0.2704 data_time: 0.0071 memory: 5828 grad_norm: 4.9055 loss: 1.9518 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9518 2023/06/05 15:54:01 - mmengine - INFO - Epoch(train) [123][1260/2569] lr: 4.0000e-03 eta: 5:13:31 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 4.7437 loss: 1.7856 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7856 2023/06/05 15:54:06 - mmengine - INFO - Epoch(train) [123][1280/2569] lr: 4.0000e-03 eta: 5:13:26 time: 0.2724 data_time: 0.0079 memory: 5828 grad_norm: 4.7353 loss: 2.0617 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0617 2023/06/05 15:54:11 - mmengine - INFO - Epoch(train) [123][1300/2569] lr: 4.0000e-03 eta: 5:13:21 time: 0.2666 data_time: 0.0077 memory: 5828 grad_norm: 4.6563 loss: 1.9714 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9714 2023/06/05 15:54:17 - mmengine - INFO - Epoch(train) [123][1320/2569] lr: 4.0000e-03 eta: 5:13:15 time: 0.2678 data_time: 0.0071 memory: 5828 grad_norm: 4.7139 loss: 1.6795 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6795 2023/06/05 15:54:22 - mmengine - INFO - Epoch(train) [123][1340/2569] lr: 4.0000e-03 eta: 5:13:10 time: 0.2765 data_time: 0.0072 memory: 5828 grad_norm: 4.7969 loss: 2.1409 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1409 2023/06/05 15:54:28 - mmengine - INFO - Epoch(train) [123][1360/2569] lr: 4.0000e-03 eta: 5:13:05 time: 0.2654 data_time: 0.0071 memory: 5828 grad_norm: 4.8081 loss: 1.7115 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7115 2023/06/05 15:54:33 - mmengine - INFO - Epoch(train) [123][1380/2569] lr: 4.0000e-03 eta: 5:12:59 time: 0.2623 data_time: 0.0071 memory: 5828 grad_norm: 4.7220 loss: 1.9771 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9771 2023/06/05 15:54:38 - mmengine - INFO - Epoch(train) [123][1400/2569] lr: 4.0000e-03 eta: 5:12:54 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 4.7622 loss: 2.2540 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.2540 2023/06/05 15:54:44 - mmengine - INFO - Epoch(train) [123][1420/2569] lr: 4.0000e-03 eta: 5:12:49 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 4.6876 loss: 1.7912 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7912 2023/06/05 15:54:49 - mmengine - INFO - Epoch(train) [123][1440/2569] lr: 4.0000e-03 eta: 5:12:43 time: 0.2683 data_time: 0.0074 memory: 5828 grad_norm: 4.7551 loss: 1.6909 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6909 2023/06/05 15:54:54 - mmengine - INFO - Epoch(train) [123][1460/2569] lr: 4.0000e-03 eta: 5:12:38 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 4.7082 loss: 1.7528 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7528 2023/06/05 15:55:00 - mmengine - INFO - Epoch(train) [123][1480/2569] lr: 4.0000e-03 eta: 5:12:33 time: 0.2690 data_time: 0.0079 memory: 5828 grad_norm: 4.6980 loss: 1.5909 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5909 2023/06/05 15:55:05 - mmengine - INFO - Epoch(train) [123][1500/2569] lr: 4.0000e-03 eta: 5:12:27 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 4.8146 loss: 1.8772 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8772 2023/06/05 15:55:11 - mmengine - INFO - Epoch(train) [123][1520/2569] lr: 4.0000e-03 eta: 5:12:22 time: 0.2792 data_time: 0.0072 memory: 5828 grad_norm: 4.7489 loss: 1.6168 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6168 2023/06/05 15:55:16 - mmengine - INFO - Epoch(train) [123][1540/2569] lr: 4.0000e-03 eta: 5:12:17 time: 0.2667 data_time: 0.0079 memory: 5828 grad_norm: 4.7179 loss: 1.6009 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6009 2023/06/05 15:55:21 - mmengine - INFO - Epoch(train) [123][1560/2569] lr: 4.0000e-03 eta: 5:12:12 time: 0.2607 data_time: 0.0075 memory: 5828 grad_norm: 4.6586 loss: 1.6899 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6899 2023/06/05 15:55:27 - mmengine - INFO - Epoch(train) [123][1580/2569] lr: 4.0000e-03 eta: 5:12:06 time: 0.2750 data_time: 0.0074 memory: 5828 grad_norm: 4.8027 loss: 1.8265 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8265 2023/06/05 15:55:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:55:32 - mmengine - INFO - Epoch(train) [123][1600/2569] lr: 4.0000e-03 eta: 5:12:01 time: 0.2698 data_time: 0.0070 memory: 5828 grad_norm: 4.6532 loss: 1.5232 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5232 2023/06/05 15:55:37 - mmengine - INFO - Epoch(train) [123][1620/2569] lr: 4.0000e-03 eta: 5:11:56 time: 0.2680 data_time: 0.0075 memory: 5828 grad_norm: 4.7071 loss: 2.0412 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0412 2023/06/05 15:55:43 - mmengine - INFO - Epoch(train) [123][1640/2569] lr: 4.0000e-03 eta: 5:11:50 time: 0.2672 data_time: 0.0071 memory: 5828 grad_norm: 4.7372 loss: 1.7096 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7096 2023/06/05 15:55:48 - mmengine - INFO - Epoch(train) [123][1660/2569] lr: 4.0000e-03 eta: 5:11:45 time: 0.2793 data_time: 0.0072 memory: 5828 grad_norm: 4.7945 loss: 1.6601 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6601 2023/06/05 15:55:54 - mmengine - INFO - Epoch(train) [123][1680/2569] lr: 4.0000e-03 eta: 5:11:40 time: 0.2654 data_time: 0.0077 memory: 5828 grad_norm: 4.7467 loss: 1.7165 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7165 2023/06/05 15:55:59 - mmengine - INFO - Epoch(train) [123][1700/2569] lr: 4.0000e-03 eta: 5:11:34 time: 0.2763 data_time: 0.0069 memory: 5828 grad_norm: 4.6655 loss: 1.6834 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6834 2023/06/05 15:56:04 - mmengine - INFO - Epoch(train) [123][1720/2569] lr: 4.0000e-03 eta: 5:11:29 time: 0.2631 data_time: 0.0070 memory: 5828 grad_norm: 4.6001 loss: 1.7520 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7520 2023/06/05 15:56:10 - mmengine - INFO - Epoch(train) [123][1740/2569] lr: 4.0000e-03 eta: 5:11:24 time: 0.2782 data_time: 0.0070 memory: 5828 grad_norm: 4.7326 loss: 2.0064 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0064 2023/06/05 15:56:15 - mmengine - INFO - Epoch(train) [123][1760/2569] lr: 4.0000e-03 eta: 5:11:19 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 4.8245 loss: 2.0177 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0177 2023/06/05 15:56:21 - mmengine - INFO - Epoch(train) [123][1780/2569] lr: 4.0000e-03 eta: 5:11:13 time: 0.2783 data_time: 0.0071 memory: 5828 grad_norm: 4.6814 loss: 1.7431 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7431 2023/06/05 15:56:26 - mmengine - INFO - Epoch(train) [123][1800/2569] lr: 4.0000e-03 eta: 5:11:08 time: 0.2663 data_time: 0.0069 memory: 5828 grad_norm: 4.7646 loss: 1.9746 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9746 2023/06/05 15:56:32 - mmengine - INFO - Epoch(train) [123][1820/2569] lr: 4.0000e-03 eta: 5:11:03 time: 0.2701 data_time: 0.0070 memory: 5828 grad_norm: 4.6534 loss: 1.7636 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7636 2023/06/05 15:56:37 - mmengine - INFO - Epoch(train) [123][1840/2569] lr: 4.0000e-03 eta: 5:10:57 time: 0.2630 data_time: 0.0075 memory: 5828 grad_norm: 4.6260 loss: 1.8659 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8659 2023/06/05 15:56:42 - mmengine - INFO - Epoch(train) [123][1860/2569] lr: 4.0000e-03 eta: 5:10:52 time: 0.2652 data_time: 0.0074 memory: 5828 grad_norm: 4.7452 loss: 2.0374 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0374 2023/06/05 15:56:48 - mmengine - INFO - Epoch(train) [123][1880/2569] lr: 4.0000e-03 eta: 5:10:47 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 4.7015 loss: 1.7916 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7916 2023/06/05 15:56:53 - mmengine - INFO - Epoch(train) [123][1900/2569] lr: 4.0000e-03 eta: 5:10:41 time: 0.2703 data_time: 0.0073 memory: 5828 grad_norm: 4.8394 loss: 2.0473 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0473 2023/06/05 15:56:58 - mmengine - INFO - Epoch(train) [123][1920/2569] lr: 4.0000e-03 eta: 5:10:36 time: 0.2658 data_time: 0.0075 memory: 5828 grad_norm: 4.7585 loss: 1.6962 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6962 2023/06/05 15:57:04 - mmengine - INFO - Epoch(train) [123][1940/2569] lr: 4.0000e-03 eta: 5:10:31 time: 0.2691 data_time: 0.0071 memory: 5828 grad_norm: 4.7871 loss: 1.8098 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8098 2023/06/05 15:57:09 - mmengine - INFO - Epoch(train) [123][1960/2569] lr: 4.0000e-03 eta: 5:10:25 time: 0.2702 data_time: 0.0073 memory: 5828 grad_norm: 4.6457 loss: 1.9101 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9101 2023/06/05 15:57:15 - mmengine - INFO - Epoch(train) [123][1980/2569] lr: 4.0000e-03 eta: 5:10:20 time: 0.2783 data_time: 0.0072 memory: 5828 grad_norm: 4.7682 loss: 1.6033 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6033 2023/06/05 15:57:20 - mmengine - INFO - Epoch(train) [123][2000/2569] lr: 4.0000e-03 eta: 5:10:15 time: 0.2620 data_time: 0.0071 memory: 5828 grad_norm: 4.7583 loss: 1.4470 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4470 2023/06/05 15:57:25 - mmengine - INFO - Epoch(train) [123][2020/2569] lr: 4.0000e-03 eta: 5:10:09 time: 0.2754 data_time: 0.0073 memory: 5828 grad_norm: 4.8238 loss: 1.8201 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8201 2023/06/05 15:57:31 - mmengine - INFO - Epoch(train) [123][2040/2569] lr: 4.0000e-03 eta: 5:10:04 time: 0.2670 data_time: 0.0072 memory: 5828 grad_norm: 4.7575 loss: 1.8996 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8996 2023/06/05 15:57:36 - mmengine - INFO - Epoch(train) [123][2060/2569] lr: 4.0000e-03 eta: 5:09:59 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 4.7573 loss: 1.8719 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.8719 2023/06/05 15:57:42 - mmengine - INFO - Epoch(train) [123][2080/2569] lr: 4.0000e-03 eta: 5:09:54 time: 0.2717 data_time: 0.0069 memory: 5828 grad_norm: 4.7543 loss: 1.7110 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7110 2023/06/05 15:57:47 - mmengine - INFO - Epoch(train) [123][2100/2569] lr: 4.0000e-03 eta: 5:09:48 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 4.6684 loss: 1.9689 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9689 2023/06/05 15:57:52 - mmengine - INFO - Epoch(train) [123][2120/2569] lr: 4.0000e-03 eta: 5:09:43 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 4.7316 loss: 1.9317 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9317 2023/06/05 15:57:58 - mmengine - INFO - Epoch(train) [123][2140/2569] lr: 4.0000e-03 eta: 5:09:38 time: 0.2661 data_time: 0.0068 memory: 5828 grad_norm: 4.6866 loss: 1.9878 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9878 2023/06/05 15:58:03 - mmengine - INFO - Epoch(train) [123][2160/2569] lr: 4.0000e-03 eta: 5:09:32 time: 0.2692 data_time: 0.0072 memory: 5828 grad_norm: 4.7558 loss: 1.7458 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7458 2023/06/05 15:58:08 - mmengine - INFO - Epoch(train) [123][2180/2569] lr: 4.0000e-03 eta: 5:09:27 time: 0.2707 data_time: 0.0071 memory: 5828 grad_norm: 4.7315 loss: 1.9275 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9275 2023/06/05 15:58:14 - mmengine - INFO - Epoch(train) [123][2200/2569] lr: 4.0000e-03 eta: 5:09:22 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 4.7281 loss: 1.8404 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8404 2023/06/05 15:58:19 - mmengine - INFO - Epoch(train) [123][2220/2569] lr: 4.0000e-03 eta: 5:09:16 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 4.7311 loss: 1.7802 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7802 2023/06/05 15:58:24 - mmengine - INFO - Epoch(train) [123][2240/2569] lr: 4.0000e-03 eta: 5:09:11 time: 0.2711 data_time: 0.0075 memory: 5828 grad_norm: 4.7016 loss: 1.7680 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7680 2023/06/05 15:58:30 - mmengine - INFO - Epoch(train) [123][2260/2569] lr: 4.0000e-03 eta: 5:09:06 time: 0.2746 data_time: 0.0071 memory: 5828 grad_norm: 4.7395 loss: 1.7540 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7540 2023/06/05 15:58:35 - mmengine - INFO - Epoch(train) [123][2280/2569] lr: 4.0000e-03 eta: 5:09:00 time: 0.2706 data_time: 0.0072 memory: 5828 grad_norm: 4.8223 loss: 1.7999 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7999 2023/06/05 15:58:40 - mmengine - INFO - Epoch(train) [123][2300/2569] lr: 4.0000e-03 eta: 5:08:55 time: 0.2633 data_time: 0.0071 memory: 5828 grad_norm: 4.8563 loss: 2.0032 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0032 2023/06/05 15:58:46 - mmengine - INFO - Epoch(train) [123][2320/2569] lr: 4.0000e-03 eta: 5:08:50 time: 0.2678 data_time: 0.0072 memory: 5828 grad_norm: 4.6626 loss: 1.8397 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8397 2023/06/05 15:58:51 - mmengine - INFO - Epoch(train) [123][2340/2569] lr: 4.0000e-03 eta: 5:08:44 time: 0.2653 data_time: 0.0072 memory: 5828 grad_norm: 4.6691 loss: 1.6860 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6860 2023/06/05 15:58:57 - mmengine - INFO - Epoch(train) [123][2360/2569] lr: 4.0000e-03 eta: 5:08:39 time: 0.2716 data_time: 0.0075 memory: 5828 grad_norm: 4.7644 loss: 2.0134 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0134 2023/06/05 15:59:02 - mmengine - INFO - Epoch(train) [123][2380/2569] lr: 4.0000e-03 eta: 5:08:34 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 4.7974 loss: 2.0271 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0271 2023/06/05 15:59:07 - mmengine - INFO - Epoch(train) [123][2400/2569] lr: 4.0000e-03 eta: 5:08:28 time: 0.2667 data_time: 0.0069 memory: 5828 grad_norm: 4.6918 loss: 1.5339 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5339 2023/06/05 15:59:12 - mmengine - INFO - Epoch(train) [123][2420/2569] lr: 4.0000e-03 eta: 5:08:23 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 4.7644 loss: 1.7227 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7227 2023/06/05 15:59:18 - mmengine - INFO - Epoch(train) [123][2440/2569] lr: 4.0000e-03 eta: 5:08:18 time: 0.2740 data_time: 0.0072 memory: 5828 grad_norm: 4.7892 loss: 1.6478 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6478 2023/06/05 15:59:23 - mmengine - INFO - Epoch(train) [123][2460/2569] lr: 4.0000e-03 eta: 5:08:12 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 4.7099 loss: 1.7566 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7566 2023/06/05 15:59:29 - mmengine - INFO - Epoch(train) [123][2480/2569] lr: 4.0000e-03 eta: 5:08:07 time: 0.2710 data_time: 0.0070 memory: 5828 grad_norm: 4.7243 loss: 1.9241 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9241 2023/06/05 15:59:34 - mmengine - INFO - Epoch(train) [123][2500/2569] lr: 4.0000e-03 eta: 5:08:02 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 4.7570 loss: 1.8335 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8335 2023/06/05 15:59:39 - mmengine - INFO - Epoch(train) [123][2520/2569] lr: 4.0000e-03 eta: 5:07:56 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 4.8094 loss: 1.6755 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6755 2023/06/05 15:59:44 - mmengine - INFO - Epoch(train) [123][2540/2569] lr: 4.0000e-03 eta: 5:07:51 time: 0.2636 data_time: 0.0077 memory: 5828 grad_norm: 4.7823 loss: 1.8405 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8405 2023/06/05 15:59:50 - mmengine - INFO - Epoch(train) [123][2560/2569] lr: 4.0000e-03 eta: 5:07:46 time: 0.2600 data_time: 0.0078 memory: 5828 grad_norm: 4.7233 loss: 1.7890 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7890 2023/06/05 15:59:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:59:52 - mmengine - INFO - Epoch(train) [123][2569/2569] lr: 4.0000e-03 eta: 5:07:43 time: 0.2584 data_time: 0.0073 memory: 5828 grad_norm: 4.7856 loss: 1.8712 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.8712 2023/06/05 15:59:57 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 15:59:59 - mmengine - INFO - Epoch(train) [124][ 20/2569] lr: 4.0000e-03 eta: 5:07:38 time: 0.3412 data_time: 0.0509 memory: 5828 grad_norm: 4.6564 loss: 1.8521 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8521 2023/06/05 16:00:04 - mmengine - INFO - Epoch(train) [124][ 40/2569] lr: 4.0000e-03 eta: 5:07:33 time: 0.2686 data_time: 0.0074 memory: 5828 grad_norm: 4.7362 loss: 1.6673 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6673 2023/06/05 16:00:10 - mmengine - INFO - Epoch(train) [124][ 60/2569] lr: 4.0000e-03 eta: 5:07:28 time: 0.2739 data_time: 0.0071 memory: 5828 grad_norm: 4.7549 loss: 1.6754 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6754 2023/06/05 16:00:15 - mmengine - INFO - Epoch(train) [124][ 80/2569] lr: 4.0000e-03 eta: 5:07:22 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 4.8018 loss: 2.0023 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0023 2023/06/05 16:00:20 - mmengine - INFO - Epoch(train) [124][ 100/2569] lr: 4.0000e-03 eta: 5:07:17 time: 0.2745 data_time: 0.0072 memory: 5828 grad_norm: 4.6552 loss: 1.7235 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7235 2023/06/05 16:00:26 - mmengine - INFO - Epoch(train) [124][ 120/2569] lr: 4.0000e-03 eta: 5:07:12 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 4.7338 loss: 1.8113 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8113 2023/06/05 16:00:31 - mmengine - INFO - Epoch(train) [124][ 140/2569] lr: 4.0000e-03 eta: 5:07:07 time: 0.2712 data_time: 0.0073 memory: 5828 grad_norm: 4.7600 loss: 2.0560 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.0560 2023/06/05 16:00:37 - mmengine - INFO - Epoch(train) [124][ 160/2569] lr: 4.0000e-03 eta: 5:07:01 time: 0.2635 data_time: 0.0072 memory: 5828 grad_norm: 4.7595 loss: 1.6166 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6166 2023/06/05 16:00:42 - mmengine - INFO - Epoch(train) [124][ 180/2569] lr: 4.0000e-03 eta: 5:06:56 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 4.7200 loss: 1.3463 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3463 2023/06/05 16:00:47 - mmengine - INFO - Epoch(train) [124][ 200/2569] lr: 4.0000e-03 eta: 5:06:51 time: 0.2693 data_time: 0.0074 memory: 5828 grad_norm: 4.7430 loss: 1.5169 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5169 2023/06/05 16:00:53 - mmengine - INFO - Epoch(train) [124][ 220/2569] lr: 4.0000e-03 eta: 5:06:45 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 4.6992 loss: 1.8416 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8416 2023/06/05 16:00:58 - mmengine - INFO - Epoch(train) [124][ 240/2569] lr: 4.0000e-03 eta: 5:06:40 time: 0.2665 data_time: 0.0073 memory: 5828 grad_norm: 4.6874 loss: 1.7633 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7633 2023/06/05 16:01:03 - mmengine - INFO - Epoch(train) [124][ 260/2569] lr: 4.0000e-03 eta: 5:06:35 time: 0.2633 data_time: 0.0073 memory: 5828 grad_norm: 4.7473 loss: 1.5195 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5195 2023/06/05 16:01:08 - mmengine - INFO - Epoch(train) [124][ 280/2569] lr: 4.0000e-03 eta: 5:06:29 time: 0.2658 data_time: 0.0079 memory: 5828 grad_norm: 4.7494 loss: 1.7040 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7040 2023/06/05 16:01:14 - mmengine - INFO - Epoch(train) [124][ 300/2569] lr: 4.0000e-03 eta: 5:06:24 time: 0.2641 data_time: 0.0071 memory: 5828 grad_norm: 4.6197 loss: 1.7820 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7820 2023/06/05 16:01:19 - mmengine - INFO - Epoch(train) [124][ 320/2569] lr: 4.0000e-03 eta: 5:06:19 time: 0.2795 data_time: 0.0072 memory: 5828 grad_norm: 4.6368 loss: 1.6914 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6914 2023/06/05 16:01:25 - mmengine - INFO - Epoch(train) [124][ 340/2569] lr: 4.0000e-03 eta: 5:06:13 time: 0.2703 data_time: 0.0072 memory: 5828 grad_norm: 4.6531 loss: 1.9569 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9569 2023/06/05 16:01:30 - mmengine - INFO - Epoch(train) [124][ 360/2569] lr: 4.0000e-03 eta: 5:06:08 time: 0.2791 data_time: 0.0072 memory: 5828 grad_norm: 4.7505 loss: 1.5345 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5345 2023/06/05 16:01:36 - mmengine - INFO - Epoch(train) [124][ 380/2569] lr: 4.0000e-03 eta: 5:06:03 time: 0.2698 data_time: 0.0071 memory: 5828 grad_norm: 4.7739 loss: 1.7979 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7979 2023/06/05 16:01:41 - mmengine - INFO - Epoch(train) [124][ 400/2569] lr: 4.0000e-03 eta: 5:05:57 time: 0.2673 data_time: 0.0074 memory: 5828 grad_norm: 4.6962 loss: 1.8129 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8129 2023/06/05 16:01:47 - mmengine - INFO - Epoch(train) [124][ 420/2569] lr: 4.0000e-03 eta: 5:05:52 time: 0.2727 data_time: 0.0072 memory: 5828 grad_norm: 4.8187 loss: 1.8152 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8152 2023/06/05 16:01:52 - mmengine - INFO - Epoch(train) [124][ 440/2569] lr: 4.0000e-03 eta: 5:05:47 time: 0.2684 data_time: 0.0069 memory: 5828 grad_norm: 4.7635 loss: 1.4781 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4781 2023/06/05 16:01:57 - mmengine - INFO - Epoch(train) [124][ 460/2569] lr: 4.0000e-03 eta: 5:05:41 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 4.6971 loss: 1.6377 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6377 2023/06/05 16:02:03 - mmengine - INFO - Epoch(train) [124][ 480/2569] lr: 4.0000e-03 eta: 5:05:36 time: 0.2707 data_time: 0.0082 memory: 5828 grad_norm: 4.7628 loss: 1.8978 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8978 2023/06/05 16:02:08 - mmengine - INFO - Epoch(train) [124][ 500/2569] lr: 4.0000e-03 eta: 5:05:31 time: 0.2657 data_time: 0.0077 memory: 5828 grad_norm: 4.6885 loss: 1.4940 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4940 2023/06/05 16:02:14 - mmengine - INFO - Epoch(train) [124][ 520/2569] lr: 4.0000e-03 eta: 5:05:26 time: 0.2735 data_time: 0.0068 memory: 5828 grad_norm: 4.6008 loss: 1.8992 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8992 2023/06/05 16:02:19 - mmengine - INFO - Epoch(train) [124][ 540/2569] lr: 4.0000e-03 eta: 5:05:20 time: 0.2702 data_time: 0.0077 memory: 5828 grad_norm: 4.8331 loss: 1.8684 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8684 2023/06/05 16:02:25 - mmengine - INFO - Epoch(train) [124][ 560/2569] lr: 4.0000e-03 eta: 5:05:15 time: 0.2768 data_time: 0.0073 memory: 5828 grad_norm: 4.7757 loss: 1.4967 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4967 2023/06/05 16:02:30 - mmengine - INFO - Epoch(train) [124][ 580/2569] lr: 4.0000e-03 eta: 5:05:10 time: 0.2622 data_time: 0.0071 memory: 5828 grad_norm: 4.6804 loss: 1.5112 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5112 2023/06/05 16:02:35 - mmengine - INFO - Epoch(train) [124][ 600/2569] lr: 4.0000e-03 eta: 5:05:04 time: 0.2723 data_time: 0.0075 memory: 5828 grad_norm: 4.8006 loss: 1.7324 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7324 2023/06/05 16:02:41 - mmengine - INFO - Epoch(train) [124][ 620/2569] lr: 4.0000e-03 eta: 5:04:59 time: 0.2696 data_time: 0.0087 memory: 5828 grad_norm: 4.6979 loss: 1.5399 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5399 2023/06/05 16:02:46 - mmengine - INFO - Epoch(train) [124][ 640/2569] lr: 4.0000e-03 eta: 5:04:54 time: 0.2730 data_time: 0.0083 memory: 5828 grad_norm: 4.7822 loss: 1.7253 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7253 2023/06/05 16:02:52 - mmengine - INFO - Epoch(train) [124][ 660/2569] lr: 4.0000e-03 eta: 5:04:48 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 4.7976 loss: 1.8568 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8568 2023/06/05 16:02:57 - mmengine - INFO - Epoch(train) [124][ 680/2569] lr: 4.0000e-03 eta: 5:04:43 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 4.8271 loss: 1.8349 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8349 2023/06/05 16:03:02 - mmengine - INFO - Epoch(train) [124][ 700/2569] lr: 4.0000e-03 eta: 5:04:38 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 4.7224 loss: 1.7947 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7947 2023/06/05 16:03:08 - mmengine - INFO - Epoch(train) [124][ 720/2569] lr: 4.0000e-03 eta: 5:04:32 time: 0.2648 data_time: 0.0073 memory: 5828 grad_norm: 4.7137 loss: 1.8683 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8683 2023/06/05 16:03:13 - mmengine - INFO - Epoch(train) [124][ 740/2569] lr: 4.0000e-03 eta: 5:04:27 time: 0.2675 data_time: 0.0071 memory: 5828 grad_norm: 4.8229 loss: 2.0596 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0596 2023/06/05 16:03:18 - mmengine - INFO - Epoch(train) [124][ 760/2569] lr: 4.0000e-03 eta: 5:04:22 time: 0.2694 data_time: 0.0074 memory: 5828 grad_norm: 4.7905 loss: 1.6857 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6857 2023/06/05 16:03:24 - mmengine - INFO - Epoch(train) [124][ 780/2569] lr: 4.0000e-03 eta: 5:04:17 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 4.8602 loss: 1.5064 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5064 2023/06/05 16:03:29 - mmengine - INFO - Epoch(train) [124][ 800/2569] lr: 4.0000e-03 eta: 5:04:11 time: 0.2792 data_time: 0.0074 memory: 5828 grad_norm: 4.8168 loss: 1.6746 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6746 2023/06/05 16:03:35 - mmengine - INFO - Epoch(train) [124][ 820/2569] lr: 4.0000e-03 eta: 5:04:06 time: 0.2692 data_time: 0.0071 memory: 5828 grad_norm: 4.6768 loss: 1.7203 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7203 2023/06/05 16:03:40 - mmengine - INFO - Epoch(train) [124][ 840/2569] lr: 4.0000e-03 eta: 5:04:01 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 4.8539 loss: 2.0922 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0922 2023/06/05 16:03:46 - mmengine - INFO - Epoch(train) [124][ 860/2569] lr: 4.0000e-03 eta: 5:03:55 time: 0.2735 data_time: 0.0073 memory: 5828 grad_norm: 4.8629 loss: 1.8718 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8718 2023/06/05 16:03:51 - mmengine - INFO - Epoch(train) [124][ 880/2569] lr: 4.0000e-03 eta: 5:03:50 time: 0.2637 data_time: 0.0072 memory: 5828 grad_norm: 4.7681 loss: 1.5251 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5251 2023/06/05 16:03:56 - mmengine - INFO - Epoch(train) [124][ 900/2569] lr: 4.0000e-03 eta: 5:03:45 time: 0.2714 data_time: 0.0080 memory: 5828 grad_norm: 4.8061 loss: 1.8294 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8294 2023/06/05 16:04:02 - mmengine - INFO - Epoch(train) [124][ 920/2569] lr: 4.0000e-03 eta: 5:03:39 time: 0.2636 data_time: 0.0071 memory: 5828 grad_norm: 4.6869 loss: 1.7870 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7870 2023/06/05 16:04:07 - mmengine - INFO - Epoch(train) [124][ 940/2569] lr: 4.0000e-03 eta: 5:03:34 time: 0.2768 data_time: 0.0073 memory: 5828 grad_norm: 4.8092 loss: 1.9202 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9202 2023/06/05 16:04:12 - mmengine - INFO - Epoch(train) [124][ 960/2569] lr: 4.0000e-03 eta: 5:03:29 time: 0.2616 data_time: 0.0072 memory: 5828 grad_norm: 4.8184 loss: 1.8503 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8503 2023/06/05 16:04:18 - mmengine - INFO - Epoch(train) [124][ 980/2569] lr: 4.0000e-03 eta: 5:03:23 time: 0.2733 data_time: 0.0072 memory: 5828 grad_norm: 4.8503 loss: 1.8233 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8233 2023/06/05 16:04:23 - mmengine - INFO - Epoch(train) [124][1000/2569] lr: 4.0000e-03 eta: 5:03:18 time: 0.2660 data_time: 0.0068 memory: 5828 grad_norm: 4.7093 loss: 1.7511 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7511 2023/06/05 16:04:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:04:28 - mmengine - INFO - Epoch(train) [124][1020/2569] lr: 4.0000e-03 eta: 5:03:13 time: 0.2662 data_time: 0.0069 memory: 5828 grad_norm: 4.7240 loss: 1.6568 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6568 2023/06/05 16:04:34 - mmengine - INFO - Epoch(train) [124][1040/2569] lr: 4.0000e-03 eta: 5:03:07 time: 0.2731 data_time: 0.0071 memory: 5828 grad_norm: 4.7699 loss: 1.6813 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6813 2023/06/05 16:04:39 - mmengine - INFO - Epoch(train) [124][1060/2569] lr: 4.0000e-03 eta: 5:03:02 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 4.8341 loss: 1.8866 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8866 2023/06/05 16:04:44 - mmengine - INFO - Epoch(train) [124][1080/2569] lr: 4.0000e-03 eta: 5:02:57 time: 0.2636 data_time: 0.0076 memory: 5828 grad_norm: 4.7921 loss: 1.4824 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4824 2023/06/05 16:04:50 - mmengine - INFO - Epoch(train) [124][1100/2569] lr: 4.0000e-03 eta: 5:02:51 time: 0.2630 data_time: 0.0075 memory: 5828 grad_norm: 4.8122 loss: 1.5473 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5473 2023/06/05 16:04:55 - mmengine - INFO - Epoch(train) [124][1120/2569] lr: 4.0000e-03 eta: 5:02:46 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 4.7907 loss: 1.7689 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7689 2023/06/05 16:05:00 - mmengine - INFO - Epoch(train) [124][1140/2569] lr: 4.0000e-03 eta: 5:02:41 time: 0.2620 data_time: 0.0076 memory: 5828 grad_norm: 4.7744 loss: 1.8599 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8599 2023/06/05 16:05:06 - mmengine - INFO - Epoch(train) [124][1160/2569] lr: 4.0000e-03 eta: 5:02:35 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 4.7725 loss: 2.0575 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0575 2023/06/05 16:05:11 - mmengine - INFO - Epoch(train) [124][1180/2569] lr: 4.0000e-03 eta: 5:02:30 time: 0.2661 data_time: 0.0073 memory: 5828 grad_norm: 4.6776 loss: 1.5925 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5925 2023/06/05 16:05:16 - mmengine - INFO - Epoch(train) [124][1200/2569] lr: 4.0000e-03 eta: 5:02:25 time: 0.2669 data_time: 0.0071 memory: 5828 grad_norm: 4.7750 loss: 1.8140 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8140 2023/06/05 16:05:22 - mmengine - INFO - Epoch(train) [124][1220/2569] lr: 4.0000e-03 eta: 5:02:20 time: 0.2728 data_time: 0.0077 memory: 5828 grad_norm: 4.7930 loss: 1.6252 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.6252 2023/06/05 16:05:27 - mmengine - INFO - Epoch(train) [124][1240/2569] lr: 4.0000e-03 eta: 5:02:14 time: 0.2626 data_time: 0.0075 memory: 5828 grad_norm: 4.7883 loss: 1.7367 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7367 2023/06/05 16:05:33 - mmengine - INFO - Epoch(train) [124][1260/2569] lr: 4.0000e-03 eta: 5:02:09 time: 0.2734 data_time: 0.0080 memory: 5828 grad_norm: 4.7230 loss: 1.7474 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7474 2023/06/05 16:05:38 - mmengine - INFO - Epoch(train) [124][1280/2569] lr: 4.0000e-03 eta: 5:02:04 time: 0.2783 data_time: 0.0075 memory: 5828 grad_norm: 4.6887 loss: 2.2337 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.2337 2023/06/05 16:05:43 - mmengine - INFO - Epoch(train) [124][1300/2569] lr: 4.0000e-03 eta: 5:01:58 time: 0.2647 data_time: 0.0069 memory: 5828 grad_norm: 4.8549 loss: 2.0540 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0540 2023/06/05 16:05:49 - mmengine - INFO - Epoch(train) [124][1320/2569] lr: 4.0000e-03 eta: 5:01:53 time: 0.2808 data_time: 0.0071 memory: 5828 grad_norm: 4.7420 loss: 2.0585 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0585 2023/06/05 16:05:54 - mmengine - INFO - Epoch(train) [124][1340/2569] lr: 4.0000e-03 eta: 5:01:48 time: 0.2629 data_time: 0.0075 memory: 5828 grad_norm: 4.7583 loss: 1.8291 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8291 2023/06/05 16:06:00 - mmengine - INFO - Epoch(train) [124][1360/2569] lr: 4.0000e-03 eta: 5:01:42 time: 0.2614 data_time: 0.0080 memory: 5828 grad_norm: 4.8429 loss: 1.6763 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6763 2023/06/05 16:06:05 - mmengine - INFO - Epoch(train) [124][1380/2569] lr: 4.0000e-03 eta: 5:01:37 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 4.6587 loss: 1.5245 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5245 2023/06/05 16:06:10 - mmengine - INFO - Epoch(train) [124][1400/2569] lr: 4.0000e-03 eta: 5:01:32 time: 0.2666 data_time: 0.0072 memory: 5828 grad_norm: 4.8344 loss: 1.7608 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7608 2023/06/05 16:06:16 - mmengine - INFO - Epoch(train) [124][1420/2569] lr: 4.0000e-03 eta: 5:01:26 time: 0.2690 data_time: 0.0076 memory: 5828 grad_norm: 4.7438 loss: 1.9871 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9871 2023/06/05 16:06:21 - mmengine - INFO - Epoch(train) [124][1440/2569] lr: 4.0000e-03 eta: 5:01:21 time: 0.2627 data_time: 0.0076 memory: 5828 grad_norm: 4.8305 loss: 1.9009 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9009 2023/06/05 16:06:26 - mmengine - INFO - Epoch(train) [124][1460/2569] lr: 4.0000e-03 eta: 5:01:16 time: 0.2729 data_time: 0.0075 memory: 5828 grad_norm: 4.6665 loss: 2.0176 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0176 2023/06/05 16:06:32 - mmengine - INFO - Epoch(train) [124][1480/2569] lr: 4.0000e-03 eta: 5:01:10 time: 0.2672 data_time: 0.0075 memory: 5828 grad_norm: 4.7295 loss: 1.5114 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5114 2023/06/05 16:06:37 - mmengine - INFO - Epoch(train) [124][1500/2569] lr: 4.0000e-03 eta: 5:01:05 time: 0.2776 data_time: 0.0076 memory: 5828 grad_norm: 4.7328 loss: 1.8718 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8718 2023/06/05 16:06:43 - mmengine - INFO - Epoch(train) [124][1520/2569] lr: 4.0000e-03 eta: 5:01:00 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 4.9030 loss: 1.6251 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.6251 2023/06/05 16:06:48 - mmengine - INFO - Epoch(train) [124][1540/2569] lr: 4.0000e-03 eta: 5:00:55 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 4.8184 loss: 1.7861 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7861 2023/06/05 16:06:53 - mmengine - INFO - Epoch(train) [124][1560/2569] lr: 4.0000e-03 eta: 5:00:49 time: 0.2728 data_time: 0.0074 memory: 5828 grad_norm: 4.7533 loss: 2.0492 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0492 2023/06/05 16:06:59 - mmengine - INFO - Epoch(train) [124][1580/2569] lr: 4.0000e-03 eta: 5:00:44 time: 0.2607 data_time: 0.0070 memory: 5828 grad_norm: 4.8627 loss: 1.7957 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7957 2023/06/05 16:07:04 - mmengine - INFO - Epoch(train) [124][1600/2569] lr: 4.0000e-03 eta: 5:00:39 time: 0.2727 data_time: 0.0072 memory: 5828 grad_norm: 4.9015 loss: 1.6745 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6745 2023/06/05 16:07:09 - mmengine - INFO - Epoch(train) [124][1620/2569] lr: 4.0000e-03 eta: 5:00:33 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 4.8025 loss: 1.8528 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8528 2023/06/05 16:07:15 - mmengine - INFO - Epoch(train) [124][1640/2569] lr: 4.0000e-03 eta: 5:00:28 time: 0.2647 data_time: 0.0072 memory: 5828 grad_norm: 4.7938 loss: 2.0978 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0978 2023/06/05 16:07:20 - mmengine - INFO - Epoch(train) [124][1660/2569] lr: 4.0000e-03 eta: 5:00:23 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 4.9257 loss: 1.7824 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7824 2023/06/05 16:07:25 - mmengine - INFO - Epoch(train) [124][1680/2569] lr: 4.0000e-03 eta: 5:00:17 time: 0.2649 data_time: 0.0073 memory: 5828 grad_norm: 4.7276 loss: 1.3730 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3730 2023/06/05 16:07:31 - mmengine - INFO - Epoch(train) [124][1700/2569] lr: 4.0000e-03 eta: 5:00:12 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 4.7746 loss: 1.3640 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.3640 2023/06/05 16:07:36 - mmengine - INFO - Epoch(train) [124][1720/2569] lr: 4.0000e-03 eta: 5:00:07 time: 0.2662 data_time: 0.0074 memory: 5828 grad_norm: 4.7389 loss: 1.7273 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7273 2023/06/05 16:07:41 - mmengine - INFO - Epoch(train) [124][1740/2569] lr: 4.0000e-03 eta: 5:00:01 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 4.8296 loss: 1.7468 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7468 2023/06/05 16:07:46 - mmengine - INFO - Epoch(train) [124][1760/2569] lr: 4.0000e-03 eta: 4:59:56 time: 0.2620 data_time: 0.0071 memory: 5828 grad_norm: 4.7325 loss: 1.8388 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8388 2023/06/05 16:07:52 - mmengine - INFO - Epoch(train) [124][1780/2569] lr: 4.0000e-03 eta: 4:59:51 time: 0.2694 data_time: 0.0073 memory: 5828 grad_norm: 4.7570 loss: 1.6163 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6163 2023/06/05 16:07:57 - mmengine - INFO - Epoch(train) [124][1800/2569] lr: 4.0000e-03 eta: 4:59:45 time: 0.2727 data_time: 0.0072 memory: 5828 grad_norm: 4.8600 loss: 1.8464 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8464 2023/06/05 16:08:03 - mmengine - INFO - Epoch(train) [124][1820/2569] lr: 4.0000e-03 eta: 4:59:40 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 4.7484 loss: 1.5739 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5739 2023/06/05 16:08:08 - mmengine - INFO - Epoch(train) [124][1840/2569] lr: 4.0000e-03 eta: 4:59:35 time: 0.2694 data_time: 0.0077 memory: 5828 grad_norm: 4.7334 loss: 1.7855 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7855 2023/06/05 16:08:13 - mmengine - INFO - Epoch(train) [124][1860/2569] lr: 4.0000e-03 eta: 4:59:29 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 4.7752 loss: 2.0578 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0578 2023/06/05 16:08:19 - mmengine - INFO - Epoch(train) [124][1880/2569] lr: 4.0000e-03 eta: 4:59:24 time: 0.2680 data_time: 0.0074 memory: 5828 grad_norm: 4.8165 loss: 1.7604 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7604 2023/06/05 16:08:24 - mmengine - INFO - Epoch(train) [124][1900/2569] lr: 4.0000e-03 eta: 4:59:19 time: 0.2784 data_time: 0.0074 memory: 5828 grad_norm: 4.8054 loss: 2.0229 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.0229 2023/06/05 16:08:30 - mmengine - INFO - Epoch(train) [124][1920/2569] lr: 4.0000e-03 eta: 4:59:13 time: 0.2799 data_time: 0.0075 memory: 5828 grad_norm: 4.7967 loss: 1.8933 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8933 2023/06/05 16:08:35 - mmengine - INFO - Epoch(train) [124][1940/2569] lr: 4.0000e-03 eta: 4:59:08 time: 0.2619 data_time: 0.0078 memory: 5828 grad_norm: 4.7507 loss: 1.6348 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6348 2023/06/05 16:08:41 - mmengine - INFO - Epoch(train) [124][1960/2569] lr: 4.0000e-03 eta: 4:59:03 time: 0.2703 data_time: 0.0073 memory: 5828 grad_norm: 4.7609 loss: 1.9388 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9388 2023/06/05 16:08:46 - mmengine - INFO - Epoch(train) [124][1980/2569] lr: 4.0000e-03 eta: 4:58:58 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 4.8754 loss: 1.7021 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7021 2023/06/05 16:08:51 - mmengine - INFO - Epoch(train) [124][2000/2569] lr: 4.0000e-03 eta: 4:58:52 time: 0.2696 data_time: 0.0075 memory: 5828 grad_norm: 4.7611 loss: 1.9162 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9162 2023/06/05 16:08:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:08:57 - mmengine - INFO - Epoch(train) [124][2020/2569] lr: 4.0000e-03 eta: 4:58:47 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 4.7751 loss: 2.0766 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0766 2023/06/05 16:09:02 - mmengine - INFO - Epoch(train) [124][2040/2569] lr: 4.0000e-03 eta: 4:58:42 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 4.8370 loss: 1.8500 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8500 2023/06/05 16:09:07 - mmengine - INFO - Epoch(train) [124][2060/2569] lr: 4.0000e-03 eta: 4:58:36 time: 0.2787 data_time: 0.0078 memory: 5828 grad_norm: 4.8383 loss: 1.8967 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8967 2023/06/05 16:09:13 - mmengine - INFO - Epoch(train) [124][2080/2569] lr: 4.0000e-03 eta: 4:58:31 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 4.8178 loss: 1.9478 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9478 2023/06/05 16:09:18 - mmengine - INFO - Epoch(train) [124][2100/2569] lr: 4.0000e-03 eta: 4:58:26 time: 0.2814 data_time: 0.0070 memory: 5828 grad_norm: 4.7679 loss: 2.2269 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.2269 2023/06/05 16:09:24 - mmengine - INFO - Epoch(train) [124][2120/2569] lr: 4.0000e-03 eta: 4:58:20 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 4.7670 loss: 1.7990 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7990 2023/06/05 16:09:29 - mmengine - INFO - Epoch(train) [124][2140/2569] lr: 4.0000e-03 eta: 4:58:15 time: 0.2796 data_time: 0.0071 memory: 5828 grad_norm: 4.7028 loss: 1.6108 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6108 2023/06/05 16:09:35 - mmengine - INFO - Epoch(train) [124][2160/2569] lr: 4.0000e-03 eta: 4:58:10 time: 0.2615 data_time: 0.0074 memory: 5828 grad_norm: 4.8261 loss: 2.1816 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 2.1816 2023/06/05 16:09:40 - mmengine - INFO - Epoch(train) [124][2180/2569] lr: 4.0000e-03 eta: 4:58:04 time: 0.2834 data_time: 0.0076 memory: 5828 grad_norm: 4.8078 loss: 1.6307 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.6307 2023/06/05 16:09:46 - mmengine - INFO - Epoch(train) [124][2200/2569] lr: 4.0000e-03 eta: 4:57:59 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 4.8008 loss: 1.7101 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.7101 2023/06/05 16:09:51 - mmengine - INFO - Epoch(train) [124][2220/2569] lr: 4.0000e-03 eta: 4:57:54 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 4.8061 loss: 1.6994 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6994 2023/06/05 16:09:56 - mmengine - INFO - Epoch(train) [124][2240/2569] lr: 4.0000e-03 eta: 4:57:49 time: 0.2678 data_time: 0.0073 memory: 5828 grad_norm: 4.8530 loss: 1.6778 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6778 2023/06/05 16:10:02 - mmengine - INFO - Epoch(train) [124][2260/2569] lr: 4.0000e-03 eta: 4:57:43 time: 0.2750 data_time: 0.0072 memory: 5828 grad_norm: 4.7674 loss: 1.7031 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7031 2023/06/05 16:10:07 - mmengine - INFO - Epoch(train) [124][2280/2569] lr: 4.0000e-03 eta: 4:57:38 time: 0.2689 data_time: 0.0074 memory: 5828 grad_norm: 4.7009 loss: 1.7053 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7053 2023/06/05 16:10:12 - mmengine - INFO - Epoch(train) [124][2300/2569] lr: 4.0000e-03 eta: 4:57:33 time: 0.2645 data_time: 0.0075 memory: 5828 grad_norm: 4.7197 loss: 1.6147 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6147 2023/06/05 16:10:18 - mmengine - INFO - Epoch(train) [124][2320/2569] lr: 4.0000e-03 eta: 4:57:27 time: 0.2754 data_time: 0.0071 memory: 5828 grad_norm: 4.7405 loss: 1.5407 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5407 2023/06/05 16:10:23 - mmengine - INFO - Epoch(train) [124][2340/2569] lr: 4.0000e-03 eta: 4:57:22 time: 0.2622 data_time: 0.0074 memory: 5828 grad_norm: 4.7251 loss: 1.8069 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8069 2023/06/05 16:10:29 - mmengine - INFO - Epoch(train) [124][2360/2569] lr: 4.0000e-03 eta: 4:57:17 time: 0.2992 data_time: 0.0072 memory: 5828 grad_norm: 4.7359 loss: 1.9735 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9735 2023/06/05 16:10:35 - mmengine - INFO - Epoch(train) [124][2380/2569] lr: 4.0000e-03 eta: 4:57:11 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 4.8175 loss: 2.0054 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0054 2023/06/05 16:10:40 - mmengine - INFO - Epoch(train) [124][2400/2569] lr: 4.0000e-03 eta: 4:57:06 time: 0.2631 data_time: 0.0075 memory: 5828 grad_norm: 4.6826 loss: 1.9022 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9022 2023/06/05 16:10:45 - mmengine - INFO - Epoch(train) [124][2420/2569] lr: 4.0000e-03 eta: 4:57:01 time: 0.2673 data_time: 0.0072 memory: 5828 grad_norm: 4.8539 loss: 1.6962 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6962 2023/06/05 16:10:51 - mmengine - INFO - Epoch(train) [124][2440/2569] lr: 4.0000e-03 eta: 4:56:55 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 4.8081 loss: 1.7114 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7114 2023/06/05 16:10:56 - mmengine - INFO - Epoch(train) [124][2460/2569] lr: 4.0000e-03 eta: 4:56:50 time: 0.2635 data_time: 0.0075 memory: 5828 grad_norm: 4.7244 loss: 1.6251 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6251 2023/06/05 16:11:01 - mmengine - INFO - Epoch(train) [124][2480/2569] lr: 4.0000e-03 eta: 4:56:45 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 4.7923 loss: 2.0045 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0045 2023/06/05 16:11:07 - mmengine - INFO - Epoch(train) [124][2500/2569] lr: 4.0000e-03 eta: 4:56:40 time: 0.2756 data_time: 0.0074 memory: 5828 grad_norm: 4.7897 loss: 1.7941 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7941 2023/06/05 16:11:12 - mmengine - INFO - Epoch(train) [124][2520/2569] lr: 4.0000e-03 eta: 4:56:34 time: 0.2694 data_time: 0.0074 memory: 5828 grad_norm: 4.8461 loss: 1.8327 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8327 2023/06/05 16:11:17 - mmengine - INFO - Epoch(train) [124][2540/2569] lr: 4.0000e-03 eta: 4:56:29 time: 0.2623 data_time: 0.0080 memory: 5828 grad_norm: 4.8839 loss: 2.1380 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.1380 2023/06/05 16:11:23 - mmengine - INFO - Epoch(train) [124][2560/2569] lr: 4.0000e-03 eta: 4:56:24 time: 0.2648 data_time: 0.0079 memory: 5828 grad_norm: 4.9050 loss: 1.9176 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9176 2023/06/05 16:11:25 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:11:25 - mmengine - INFO - Epoch(train) [124][2569/2569] lr: 4.0000e-03 eta: 4:56:21 time: 0.2594 data_time: 0.0071 memory: 5828 grad_norm: 4.9179 loss: 1.9791 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.9791 2023/06/05 16:11:25 - mmengine - INFO - Saving checkpoint at 124 epochs 2023/06/05 16:11:33 - mmengine - INFO - Epoch(train) [125][ 20/2569] lr: 4.0000e-03 eta: 4:56:16 time: 0.2953 data_time: 0.0419 memory: 5828 grad_norm: 4.7366 loss: 1.8383 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8383 2023/06/05 16:11:38 - mmengine - INFO - Epoch(train) [125][ 40/2569] lr: 4.0000e-03 eta: 4:56:11 time: 0.2722 data_time: 0.0071 memory: 5828 grad_norm: 4.7554 loss: 1.5713 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5713 2023/06/05 16:11:44 - mmengine - INFO - Epoch(train) [125][ 60/2569] lr: 4.0000e-03 eta: 4:56:05 time: 0.2717 data_time: 0.0072 memory: 5828 grad_norm: 4.8790 loss: 1.6288 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.6288 2023/06/05 16:11:49 - mmengine - INFO - Epoch(train) [125][ 80/2569] lr: 4.0000e-03 eta: 4:56:00 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 4.8191 loss: 1.8353 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8353 2023/06/05 16:11:54 - mmengine - INFO - Epoch(train) [125][ 100/2569] lr: 4.0000e-03 eta: 4:55:55 time: 0.2720 data_time: 0.0076 memory: 5828 grad_norm: 4.8422 loss: 1.8997 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8997 2023/06/05 16:12:00 - mmengine - INFO - Epoch(train) [125][ 120/2569] lr: 4.0000e-03 eta: 4:55:49 time: 0.2650 data_time: 0.0073 memory: 5828 grad_norm: 4.8661 loss: 1.7634 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7634 2023/06/05 16:12:05 - mmengine - INFO - Epoch(train) [125][ 140/2569] lr: 4.0000e-03 eta: 4:55:44 time: 0.2644 data_time: 0.0073 memory: 5828 grad_norm: 4.8986 loss: 1.4950 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4950 2023/06/05 16:12:10 - mmengine - INFO - Epoch(train) [125][ 160/2569] lr: 4.0000e-03 eta: 4:55:39 time: 0.2695 data_time: 0.0072 memory: 5828 grad_norm: 4.8109 loss: 2.1241 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1241 2023/06/05 16:12:16 - mmengine - INFO - Epoch(train) [125][ 180/2569] lr: 4.0000e-03 eta: 4:55:33 time: 0.2675 data_time: 0.0071 memory: 5828 grad_norm: 4.8611 loss: 1.6498 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6498 2023/06/05 16:12:21 - mmengine - INFO - Epoch(train) [125][ 200/2569] lr: 4.0000e-03 eta: 4:55:28 time: 0.2757 data_time: 0.0067 memory: 5828 grad_norm: 4.8263 loss: 1.7943 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7943 2023/06/05 16:12:27 - mmengine - INFO - Epoch(train) [125][ 220/2569] lr: 4.0000e-03 eta: 4:55:23 time: 0.2729 data_time: 0.0071 memory: 5828 grad_norm: 4.8260 loss: 1.8872 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8872 2023/06/05 16:12:32 - mmengine - INFO - Epoch(train) [125][ 240/2569] lr: 4.0000e-03 eta: 4:55:17 time: 0.2635 data_time: 0.0075 memory: 5828 grad_norm: 4.9496 loss: 1.5489 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5489 2023/06/05 16:12:37 - mmengine - INFO - Epoch(train) [125][ 260/2569] lr: 4.0000e-03 eta: 4:55:12 time: 0.2620 data_time: 0.0078 memory: 5828 grad_norm: 4.8534 loss: 1.8204 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8204 2023/06/05 16:12:43 - mmengine - INFO - Epoch(train) [125][ 280/2569] lr: 4.0000e-03 eta: 4:55:07 time: 0.2629 data_time: 0.0070 memory: 5828 grad_norm: 4.7901 loss: 1.7866 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7866 2023/06/05 16:12:48 - mmengine - INFO - Epoch(train) [125][ 300/2569] lr: 4.0000e-03 eta: 4:55:01 time: 0.2700 data_time: 0.0072 memory: 5828 grad_norm: 4.8913 loss: 1.8122 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8122 2023/06/05 16:12:53 - mmengine - INFO - Epoch(train) [125][ 320/2569] lr: 4.0000e-03 eta: 4:54:56 time: 0.2689 data_time: 0.0074 memory: 5828 grad_norm: 4.8189 loss: 1.8277 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8277 2023/06/05 16:12:59 - mmengine - INFO - Epoch(train) [125][ 340/2569] lr: 4.0000e-03 eta: 4:54:51 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 4.8244 loss: 1.6202 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6202 2023/06/05 16:13:04 - mmengine - INFO - Epoch(train) [125][ 360/2569] lr: 4.0000e-03 eta: 4:54:46 time: 0.2652 data_time: 0.0071 memory: 5828 grad_norm: 4.7976 loss: 1.8530 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8530 2023/06/05 16:13:09 - mmengine - INFO - Epoch(train) [125][ 380/2569] lr: 4.0000e-03 eta: 4:54:40 time: 0.2643 data_time: 0.0069 memory: 5828 grad_norm: 4.8023 loss: 1.9268 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.9268 2023/06/05 16:13:15 - mmengine - INFO - Epoch(train) [125][ 400/2569] lr: 4.0000e-03 eta: 4:54:35 time: 0.2723 data_time: 0.0075 memory: 5828 grad_norm: 4.8578 loss: 1.6790 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6790 2023/06/05 16:13:20 - mmengine - INFO - Epoch(train) [125][ 420/2569] lr: 4.0000e-03 eta: 4:54:30 time: 0.2667 data_time: 0.0075 memory: 5828 grad_norm: 4.8102 loss: 1.7795 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7795 2023/06/05 16:13:25 - mmengine - INFO - Epoch(train) [125][ 440/2569] lr: 4.0000e-03 eta: 4:54:24 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 4.7468 loss: 2.0729 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0729 2023/06/05 16:13:26 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:13:31 - mmengine - INFO - Epoch(train) [125][ 460/2569] lr: 4.0000e-03 eta: 4:54:19 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 4.7871 loss: 1.8951 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8951 2023/06/05 16:13:36 - mmengine - INFO - Epoch(train) [125][ 480/2569] lr: 4.0000e-03 eta: 4:54:14 time: 0.2750 data_time: 0.0077 memory: 5828 grad_norm: 4.7732 loss: 1.8446 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8446 2023/06/05 16:13:42 - mmengine - INFO - Epoch(train) [125][ 500/2569] lr: 4.0000e-03 eta: 4:54:08 time: 0.2698 data_time: 0.0074 memory: 5828 grad_norm: 4.8597 loss: 1.6542 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6542 2023/06/05 16:13:47 - mmengine - INFO - Epoch(train) [125][ 520/2569] lr: 4.0000e-03 eta: 4:54:03 time: 0.2708 data_time: 0.0071 memory: 5828 grad_norm: 4.7286 loss: 1.9992 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9992 2023/06/05 16:13:52 - mmengine - INFO - Epoch(train) [125][ 540/2569] lr: 4.0000e-03 eta: 4:53:58 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 4.8845 loss: 1.8256 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8256 2023/06/05 16:13:58 - mmengine - INFO - Epoch(train) [125][ 560/2569] lr: 4.0000e-03 eta: 4:53:52 time: 0.2668 data_time: 0.0076 memory: 5828 grad_norm: 4.8172 loss: 1.9862 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9862 2023/06/05 16:14:03 - mmengine - INFO - Epoch(train) [125][ 580/2569] lr: 4.0000e-03 eta: 4:53:47 time: 0.2670 data_time: 0.0071 memory: 5828 grad_norm: 4.6821 loss: 1.6859 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6859 2023/06/05 16:14:09 - mmengine - INFO - Epoch(train) [125][ 600/2569] lr: 4.0000e-03 eta: 4:53:42 time: 0.2717 data_time: 0.0071 memory: 5828 grad_norm: 4.8061 loss: 1.8528 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8528 2023/06/05 16:14:14 - mmengine - INFO - Epoch(train) [125][ 620/2569] lr: 4.0000e-03 eta: 4:53:36 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 4.7730 loss: 1.8705 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8705 2023/06/05 16:14:19 - mmengine - INFO - Epoch(train) [125][ 640/2569] lr: 4.0000e-03 eta: 4:53:31 time: 0.2675 data_time: 0.0075 memory: 5828 grad_norm: 4.8142 loss: 1.5614 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5614 2023/06/05 16:14:25 - mmengine - INFO - Epoch(train) [125][ 660/2569] lr: 4.0000e-03 eta: 4:53:26 time: 0.2640 data_time: 0.0070 memory: 5828 grad_norm: 4.8205 loss: 1.8633 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8633 2023/06/05 16:14:30 - mmengine - INFO - Epoch(train) [125][ 680/2569] lr: 4.0000e-03 eta: 4:53:20 time: 0.2722 data_time: 0.0070 memory: 5828 grad_norm: 4.8026 loss: 1.9423 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9423 2023/06/05 16:14:35 - mmengine - INFO - Epoch(train) [125][ 700/2569] lr: 4.0000e-03 eta: 4:53:15 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 4.9082 loss: 1.9509 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9509 2023/06/05 16:14:40 - mmengine - INFO - Epoch(train) [125][ 720/2569] lr: 4.0000e-03 eta: 4:53:10 time: 0.2599 data_time: 0.0078 memory: 5828 grad_norm: 4.7643 loss: 1.9693 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9693 2023/06/05 16:14:46 - mmengine - INFO - Epoch(train) [125][ 740/2569] lr: 4.0000e-03 eta: 4:53:04 time: 0.2668 data_time: 0.0069 memory: 5828 grad_norm: 4.6811 loss: 1.6387 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6387 2023/06/05 16:14:51 - mmengine - INFO - Epoch(train) [125][ 760/2569] lr: 4.0000e-03 eta: 4:52:59 time: 0.2640 data_time: 0.0070 memory: 5828 grad_norm: 4.7087 loss: 1.6618 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6618 2023/06/05 16:14:57 - mmengine - INFO - Epoch(train) [125][ 780/2569] lr: 4.0000e-03 eta: 4:52:54 time: 0.2744 data_time: 0.0069 memory: 5828 grad_norm: 4.8054 loss: 1.8453 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8453 2023/06/05 16:15:02 - mmengine - INFO - Epoch(train) [125][ 800/2569] lr: 4.0000e-03 eta: 4:52:49 time: 0.2696 data_time: 0.0070 memory: 5828 grad_norm: 4.8581 loss: 1.3484 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3484 2023/06/05 16:15:07 - mmengine - INFO - Epoch(train) [125][ 820/2569] lr: 4.0000e-03 eta: 4:52:43 time: 0.2726 data_time: 0.0071 memory: 5828 grad_norm: 4.8061 loss: 1.6850 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6850 2023/06/05 16:15:13 - mmengine - INFO - Epoch(train) [125][ 840/2569] lr: 4.0000e-03 eta: 4:52:38 time: 0.2640 data_time: 0.0071 memory: 5828 grad_norm: 4.8441 loss: 1.9924 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9924 2023/06/05 16:15:18 - mmengine - INFO - Epoch(train) [125][ 860/2569] lr: 4.0000e-03 eta: 4:52:33 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 4.8239 loss: 1.5711 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5711 2023/06/05 16:15:23 - mmengine - INFO - Epoch(train) [125][ 880/2569] lr: 4.0000e-03 eta: 4:52:27 time: 0.2672 data_time: 0.0072 memory: 5828 grad_norm: 4.9018 loss: 1.7601 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7601 2023/06/05 16:15:29 - mmengine - INFO - Epoch(train) [125][ 900/2569] lr: 4.0000e-03 eta: 4:52:22 time: 0.2704 data_time: 0.0072 memory: 5828 grad_norm: 4.9700 loss: 1.7222 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7222 2023/06/05 16:15:34 - mmengine - INFO - Epoch(train) [125][ 920/2569] lr: 4.0000e-03 eta: 4:52:17 time: 0.2662 data_time: 0.0071 memory: 5828 grad_norm: 4.7984 loss: 1.7237 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7237 2023/06/05 16:15:39 - mmengine - INFO - Epoch(train) [125][ 940/2569] lr: 4.0000e-03 eta: 4:52:11 time: 0.2608 data_time: 0.0070 memory: 5828 grad_norm: 4.8813 loss: 1.8526 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8526 2023/06/05 16:15:45 - mmengine - INFO - Epoch(train) [125][ 960/2569] lr: 4.0000e-03 eta: 4:52:06 time: 0.2745 data_time: 0.0071 memory: 5828 grad_norm: 4.7912 loss: 1.9841 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9841 2023/06/05 16:15:50 - mmengine - INFO - Epoch(train) [125][ 980/2569] lr: 4.0000e-03 eta: 4:52:01 time: 0.2694 data_time: 0.0073 memory: 5828 grad_norm: 4.8836 loss: 1.9495 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9495 2023/06/05 16:15:56 - mmengine - INFO - Epoch(train) [125][1000/2569] lr: 4.0000e-03 eta: 4:51:55 time: 0.2679 data_time: 0.0071 memory: 5828 grad_norm: 4.7532 loss: 1.7345 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7345 2023/06/05 16:16:01 - mmengine - INFO - Epoch(train) [125][1020/2569] lr: 4.0000e-03 eta: 4:51:50 time: 0.2716 data_time: 0.0071 memory: 5828 grad_norm: 4.7892 loss: 1.9586 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9586 2023/06/05 16:16:07 - mmengine - INFO - Epoch(train) [125][1040/2569] lr: 4.0000e-03 eta: 4:51:45 time: 0.2694 data_time: 0.0074 memory: 5828 grad_norm: 4.9034 loss: 1.5307 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5307 2023/06/05 16:16:12 - mmengine - INFO - Epoch(train) [125][1060/2569] lr: 4.0000e-03 eta: 4:51:39 time: 0.2742 data_time: 0.0073 memory: 5828 grad_norm: 4.8021 loss: 2.0446 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0446 2023/06/05 16:16:17 - mmengine - INFO - Epoch(train) [125][1080/2569] lr: 4.0000e-03 eta: 4:51:34 time: 0.2641 data_time: 0.0076 memory: 5828 grad_norm: 4.7369 loss: 1.7839 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7839 2023/06/05 16:16:23 - mmengine - INFO - Epoch(train) [125][1100/2569] lr: 4.0000e-03 eta: 4:51:29 time: 0.2684 data_time: 0.0074 memory: 5828 grad_norm: 4.8335 loss: 1.7242 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7242 2023/06/05 16:16:28 - mmengine - INFO - Epoch(train) [125][1120/2569] lr: 4.0000e-03 eta: 4:51:23 time: 0.2616 data_time: 0.0085 memory: 5828 grad_norm: 4.7996 loss: 1.9551 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.9551 2023/06/05 16:16:33 - mmengine - INFO - Epoch(train) [125][1140/2569] lr: 4.0000e-03 eta: 4:51:18 time: 0.2730 data_time: 0.0078 memory: 5828 grad_norm: 4.8418 loss: 1.7155 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7155 2023/06/05 16:16:39 - mmengine - INFO - Epoch(train) [125][1160/2569] lr: 4.0000e-03 eta: 4:51:13 time: 0.2674 data_time: 0.0074 memory: 5828 grad_norm: 4.8519 loss: 1.6388 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6388 2023/06/05 16:16:44 - mmengine - INFO - Epoch(train) [125][1180/2569] lr: 4.0000e-03 eta: 4:51:07 time: 0.2675 data_time: 0.0075 memory: 5828 grad_norm: 4.7629 loss: 1.8162 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8162 2023/06/05 16:16:49 - mmengine - INFO - Epoch(train) [125][1200/2569] lr: 4.0000e-03 eta: 4:51:02 time: 0.2669 data_time: 0.0075 memory: 5828 grad_norm: 4.7911 loss: 2.0109 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0109 2023/06/05 16:16:55 - mmengine - INFO - Epoch(train) [125][1220/2569] lr: 4.0000e-03 eta: 4:50:57 time: 0.2663 data_time: 0.0073 memory: 5828 grad_norm: 4.9121 loss: 1.6954 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.6954 2023/06/05 16:17:00 - mmengine - INFO - Epoch(train) [125][1240/2569] lr: 4.0000e-03 eta: 4:50:52 time: 0.2611 data_time: 0.0076 memory: 5828 grad_norm: 4.7842 loss: 1.7122 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7122 2023/06/05 16:17:05 - mmengine - INFO - Epoch(train) [125][1260/2569] lr: 4.0000e-03 eta: 4:50:46 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 4.8718 loss: 2.0159 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0159 2023/06/05 16:17:11 - mmengine - INFO - Epoch(train) [125][1280/2569] lr: 4.0000e-03 eta: 4:50:41 time: 0.2669 data_time: 0.0078 memory: 5828 grad_norm: 4.8867 loss: 1.5358 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5358 2023/06/05 16:17:16 - mmengine - INFO - Epoch(train) [125][1300/2569] lr: 4.0000e-03 eta: 4:50:36 time: 0.2697 data_time: 0.0073 memory: 5828 grad_norm: 4.8421 loss: 1.8833 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8833 2023/06/05 16:17:22 - mmengine - INFO - Epoch(train) [125][1320/2569] lr: 4.0000e-03 eta: 4:50:30 time: 0.2736 data_time: 0.0072 memory: 5828 grad_norm: 4.8259 loss: 1.7693 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7693 2023/06/05 16:17:27 - mmengine - INFO - Epoch(train) [125][1340/2569] lr: 4.0000e-03 eta: 4:50:25 time: 0.2671 data_time: 0.0069 memory: 5828 grad_norm: 4.7138 loss: 1.8429 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8429 2023/06/05 16:17:32 - mmengine - INFO - Epoch(train) [125][1360/2569] lr: 4.0000e-03 eta: 4:50:20 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 4.7248 loss: 1.9035 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9035 2023/06/05 16:17:38 - mmengine - INFO - Epoch(train) [125][1380/2569] lr: 4.0000e-03 eta: 4:50:14 time: 0.2774 data_time: 0.0071 memory: 5828 grad_norm: 4.9063 loss: 2.0784 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0784 2023/06/05 16:17:43 - mmengine - INFO - Epoch(train) [125][1400/2569] lr: 4.0000e-03 eta: 4:50:09 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 4.8116 loss: 1.9679 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 1.9679 2023/06/05 16:17:49 - mmengine - INFO - Epoch(train) [125][1420/2569] lr: 4.0000e-03 eta: 4:50:04 time: 0.2695 data_time: 0.0074 memory: 5828 grad_norm: 4.7511 loss: 1.4979 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4979 2023/06/05 16:17:54 - mmengine - INFO - Epoch(train) [125][1440/2569] lr: 4.0000e-03 eta: 4:49:58 time: 0.2621 data_time: 0.0072 memory: 5828 grad_norm: 4.7974 loss: 1.8394 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8394 2023/06/05 16:17:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:17:59 - mmengine - INFO - Epoch(train) [125][1460/2569] lr: 4.0000e-03 eta: 4:49:53 time: 0.2641 data_time: 0.0071 memory: 5828 grad_norm: 4.8046 loss: 1.9290 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9290 2023/06/05 16:18:05 - mmengine - INFO - Epoch(train) [125][1480/2569] lr: 4.0000e-03 eta: 4:49:48 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 4.8849 loss: 1.9782 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9782 2023/06/05 16:18:10 - mmengine - INFO - Epoch(train) [125][1500/2569] lr: 4.0000e-03 eta: 4:49:42 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 4.8339 loss: 1.7931 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7931 2023/06/05 16:18:15 - mmengine - INFO - Epoch(train) [125][1520/2569] lr: 4.0000e-03 eta: 4:49:37 time: 0.2751 data_time: 0.0073 memory: 5828 grad_norm: 4.8961 loss: 1.8824 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8824 2023/06/05 16:18:21 - mmengine - INFO - Epoch(train) [125][1540/2569] lr: 4.0000e-03 eta: 4:49:32 time: 0.2723 data_time: 0.0070 memory: 5828 grad_norm: 4.9644 loss: 1.7576 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7576 2023/06/05 16:18:26 - mmengine - INFO - Epoch(train) [125][1560/2569] lr: 4.0000e-03 eta: 4:49:26 time: 0.2717 data_time: 0.0075 memory: 5828 grad_norm: 4.7733 loss: 1.8659 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8659 2023/06/05 16:18:32 - mmengine - INFO - Epoch(train) [125][1580/2569] lr: 4.0000e-03 eta: 4:49:21 time: 0.2728 data_time: 0.0074 memory: 5828 grad_norm: 4.7563 loss: 1.8604 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8604 2023/06/05 16:18:37 - mmengine - INFO - Epoch(train) [125][1600/2569] lr: 4.0000e-03 eta: 4:49:16 time: 0.2767 data_time: 0.0076 memory: 5828 grad_norm: 4.8410 loss: 1.8042 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8042 2023/06/05 16:18:43 - mmengine - INFO - Epoch(train) [125][1620/2569] lr: 4.0000e-03 eta: 4:49:11 time: 0.2663 data_time: 0.0072 memory: 5828 grad_norm: 4.8076 loss: 1.7885 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7885 2023/06/05 16:18:48 - mmengine - INFO - Epoch(train) [125][1640/2569] lr: 4.0000e-03 eta: 4:49:05 time: 0.2690 data_time: 0.0075 memory: 5828 grad_norm: 4.8833 loss: 1.6082 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6082 2023/06/05 16:18:54 - mmengine - INFO - Epoch(train) [125][1660/2569] lr: 4.0000e-03 eta: 4:49:00 time: 0.2774 data_time: 0.0075 memory: 5828 grad_norm: 4.8493 loss: 1.9218 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9218 2023/06/05 16:18:59 - mmengine - INFO - Epoch(train) [125][1680/2569] lr: 4.0000e-03 eta: 4:48:55 time: 0.2646 data_time: 0.0077 memory: 5828 grad_norm: 4.8975 loss: 1.9826 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9826 2023/06/05 16:19:04 - mmengine - INFO - Epoch(train) [125][1700/2569] lr: 4.0000e-03 eta: 4:48:49 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 4.7216 loss: 1.7133 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7133 2023/06/05 16:19:09 - mmengine - INFO - Epoch(train) [125][1720/2569] lr: 4.0000e-03 eta: 4:48:44 time: 0.2681 data_time: 0.0079 memory: 5828 grad_norm: 4.8828 loss: 1.8041 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8041 2023/06/05 16:19:15 - mmengine - INFO - Epoch(train) [125][1740/2569] lr: 4.0000e-03 eta: 4:48:39 time: 0.2714 data_time: 0.0079 memory: 5828 grad_norm: 4.8528 loss: 1.8934 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8934 2023/06/05 16:19:20 - mmengine - INFO - Epoch(train) [125][1760/2569] lr: 4.0000e-03 eta: 4:48:33 time: 0.2647 data_time: 0.0072 memory: 5828 grad_norm: 4.8423 loss: 1.8914 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8914 2023/06/05 16:19:25 - mmengine - INFO - Epoch(train) [125][1780/2569] lr: 4.0000e-03 eta: 4:48:28 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 4.7943 loss: 1.7389 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7389 2023/06/05 16:19:31 - mmengine - INFO - Epoch(train) [125][1800/2569] lr: 4.0000e-03 eta: 4:48:23 time: 0.2691 data_time: 0.0072 memory: 5828 grad_norm: 4.9080 loss: 2.1557 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1557 2023/06/05 16:19:36 - mmengine - INFO - Epoch(train) [125][1820/2569] lr: 4.0000e-03 eta: 4:48:17 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 4.9411 loss: 1.6451 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6451 2023/06/05 16:19:42 - mmengine - INFO - Epoch(train) [125][1840/2569] lr: 4.0000e-03 eta: 4:48:12 time: 0.2711 data_time: 0.0072 memory: 5828 grad_norm: 4.7345 loss: 1.5739 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5739 2023/06/05 16:19:47 - mmengine - INFO - Epoch(train) [125][1860/2569] lr: 4.0000e-03 eta: 4:48:07 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 4.8263 loss: 1.8580 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8580 2023/06/05 16:19:52 - mmengine - INFO - Epoch(train) [125][1880/2569] lr: 4.0000e-03 eta: 4:48:01 time: 0.2619 data_time: 0.0075 memory: 5828 grad_norm: 4.8604 loss: 1.9155 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9155 2023/06/05 16:19:57 - mmengine - INFO - Epoch(train) [125][1900/2569] lr: 4.0000e-03 eta: 4:47:56 time: 0.2614 data_time: 0.0071 memory: 5828 grad_norm: 4.8168 loss: 1.8837 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8837 2023/06/05 16:20:03 - mmengine - INFO - Epoch(train) [125][1920/2569] lr: 4.0000e-03 eta: 4:47:51 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 4.9024 loss: 1.6912 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6912 2023/06/05 16:20:08 - mmengine - INFO - Epoch(train) [125][1940/2569] lr: 4.0000e-03 eta: 4:47:45 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 4.8520 loss: 1.4522 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4522 2023/06/05 16:20:14 - mmengine - INFO - Epoch(train) [125][1960/2569] lr: 4.0000e-03 eta: 4:47:40 time: 0.2799 data_time: 0.0076 memory: 5828 grad_norm: 4.7946 loss: 1.8472 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8472 2023/06/05 16:20:19 - mmengine - INFO - Epoch(train) [125][1980/2569] lr: 4.0000e-03 eta: 4:47:35 time: 0.2747 data_time: 0.0073 memory: 5828 grad_norm: 4.8363 loss: 1.8078 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8078 2023/06/05 16:20:25 - mmengine - INFO - Epoch(train) [125][2000/2569] lr: 4.0000e-03 eta: 4:47:30 time: 0.2777 data_time: 0.0180 memory: 5828 grad_norm: 4.8011 loss: 1.6908 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6908 2023/06/05 16:20:30 - mmengine - INFO - Epoch(train) [125][2020/2569] lr: 4.0000e-03 eta: 4:47:24 time: 0.2672 data_time: 0.0070 memory: 5828 grad_norm: 4.7981 loss: 1.7478 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7478 2023/06/05 16:20:35 - mmengine - INFO - Epoch(train) [125][2040/2569] lr: 4.0000e-03 eta: 4:47:19 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 4.9068 loss: 1.6499 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6499 2023/06/05 16:20:41 - mmengine - INFO - Epoch(train) [125][2060/2569] lr: 4.0000e-03 eta: 4:47:14 time: 0.2794 data_time: 0.0071 memory: 5828 grad_norm: 4.8442 loss: 1.8516 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8516 2023/06/05 16:20:46 - mmengine - INFO - Epoch(train) [125][2080/2569] lr: 4.0000e-03 eta: 4:47:08 time: 0.2714 data_time: 0.0071 memory: 5828 grad_norm: 4.8379 loss: 1.8142 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8142 2023/06/05 16:20:52 - mmengine - INFO - Epoch(train) [125][2100/2569] lr: 4.0000e-03 eta: 4:47:03 time: 0.2740 data_time: 0.0071 memory: 5828 grad_norm: 4.7948 loss: 1.7693 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7693 2023/06/05 16:20:58 - mmengine - INFO - Epoch(train) [125][2120/2569] lr: 4.0000e-03 eta: 4:46:58 time: 0.2805 data_time: 0.0076 memory: 5828 grad_norm: 4.8926 loss: 1.6129 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6129 2023/06/05 16:21:03 - mmengine - INFO - Epoch(train) [125][2140/2569] lr: 4.0000e-03 eta: 4:46:52 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 4.8405 loss: 1.5653 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5653 2023/06/05 16:21:08 - mmengine - INFO - Epoch(train) [125][2160/2569] lr: 4.0000e-03 eta: 4:46:47 time: 0.2609 data_time: 0.0087 memory: 5828 grad_norm: 4.8085 loss: 1.7180 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7180 2023/06/05 16:21:14 - mmengine - INFO - Epoch(train) [125][2180/2569] lr: 4.0000e-03 eta: 4:46:42 time: 0.2689 data_time: 0.0074 memory: 5828 grad_norm: 4.8287 loss: 2.0608 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0608 2023/06/05 16:21:19 - mmengine - INFO - Epoch(train) [125][2200/2569] lr: 4.0000e-03 eta: 4:46:36 time: 0.2697 data_time: 0.0076 memory: 5828 grad_norm: 4.9217 loss: 2.0110 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0110 2023/06/05 16:21:24 - mmengine - INFO - Epoch(train) [125][2220/2569] lr: 4.0000e-03 eta: 4:46:31 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 4.7913 loss: 1.4277 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4277 2023/06/05 16:21:29 - mmengine - INFO - Epoch(train) [125][2240/2569] lr: 4.0000e-03 eta: 4:46:26 time: 0.2628 data_time: 0.0070 memory: 5828 grad_norm: 4.8368 loss: 1.6160 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6160 2023/06/05 16:21:35 - mmengine - INFO - Epoch(train) [125][2260/2569] lr: 4.0000e-03 eta: 4:46:21 time: 0.2700 data_time: 0.0072 memory: 5828 grad_norm: 4.8409 loss: 1.8045 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8045 2023/06/05 16:21:40 - mmengine - INFO - Epoch(train) [125][2280/2569] lr: 4.0000e-03 eta: 4:46:15 time: 0.2725 data_time: 0.0073 memory: 5828 grad_norm: 4.9350 loss: 1.6919 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6919 2023/06/05 16:21:46 - mmengine - INFO - Epoch(train) [125][2300/2569] lr: 4.0000e-03 eta: 4:46:10 time: 0.2611 data_time: 0.0070 memory: 5828 grad_norm: 4.9343 loss: 1.9543 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9543 2023/06/05 16:21:51 - mmengine - INFO - Epoch(train) [125][2320/2569] lr: 4.0000e-03 eta: 4:46:05 time: 0.2803 data_time: 0.0073 memory: 5828 grad_norm: 4.9310 loss: 1.8152 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8152 2023/06/05 16:21:57 - mmengine - INFO - Epoch(train) [125][2340/2569] lr: 4.0000e-03 eta: 4:45:59 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 4.9181 loss: 1.5976 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5976 2023/06/05 16:22:02 - mmengine - INFO - Epoch(train) [125][2360/2569] lr: 4.0000e-03 eta: 4:45:54 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 4.8108 loss: 1.6419 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6419 2023/06/05 16:22:07 - mmengine - INFO - Epoch(train) [125][2380/2569] lr: 4.0000e-03 eta: 4:45:49 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 4.7737 loss: 1.6364 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6364 2023/06/05 16:22:13 - mmengine - INFO - Epoch(train) [125][2400/2569] lr: 4.0000e-03 eta: 4:45:43 time: 0.2660 data_time: 0.0070 memory: 5828 grad_norm: 4.7985 loss: 1.6388 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6388 2023/06/05 16:22:18 - mmengine - INFO - Epoch(train) [125][2420/2569] lr: 4.0000e-03 eta: 4:45:38 time: 0.2724 data_time: 0.0072 memory: 5828 grad_norm: 4.8981 loss: 2.0245 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0245 2023/06/05 16:22:23 - mmengine - INFO - Epoch(train) [125][2440/2569] lr: 4.0000e-03 eta: 4:45:33 time: 0.2611 data_time: 0.0072 memory: 5828 grad_norm: 4.8124 loss: 1.8381 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8381 2023/06/05 16:22:24 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:22:29 - mmengine - INFO - Epoch(train) [125][2460/2569] lr: 4.0000e-03 eta: 4:45:27 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 4.9891 loss: 1.9939 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9939 2023/06/05 16:22:34 - mmengine - INFO - Epoch(train) [125][2480/2569] lr: 4.0000e-03 eta: 4:45:22 time: 0.2694 data_time: 0.0073 memory: 5828 grad_norm: 4.8438 loss: 1.8576 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8576 2023/06/05 16:22:39 - mmengine - INFO - Epoch(train) [125][2500/2569] lr: 4.0000e-03 eta: 4:45:17 time: 0.2726 data_time: 0.0076 memory: 5828 grad_norm: 4.8287 loss: 1.6777 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6777 2023/06/05 16:22:45 - mmengine - INFO - Epoch(train) [125][2520/2569] lr: 4.0000e-03 eta: 4:45:11 time: 0.2653 data_time: 0.0077 memory: 5828 grad_norm: 4.9517 loss: 1.6946 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6946 2023/06/05 16:22:50 - mmengine - INFO - Epoch(train) [125][2540/2569] lr: 4.0000e-03 eta: 4:45:06 time: 0.2714 data_time: 0.0073 memory: 5828 grad_norm: 4.9303 loss: 1.7549 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7549 2023/06/05 16:22:55 - mmengine - INFO - Epoch(train) [125][2560/2569] lr: 4.0000e-03 eta: 4:45:01 time: 0.2605 data_time: 0.0078 memory: 5828 grad_norm: 4.8738 loss: 1.7969 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7969 2023/06/05 16:22:58 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:22:58 - mmengine - INFO - Epoch(train) [125][2569/2569] lr: 4.0000e-03 eta: 4:44:58 time: 0.2600 data_time: 0.0073 memory: 5828 grad_norm: 5.0124 loss: 2.1657 top1_acc: 0.1667 top5_acc: 0.5000 loss_cls: 2.1657 2023/06/05 16:23:01 - mmengine - INFO - Epoch(val) [125][ 20/260] eta: 0:00:44 time: 0.1869 data_time: 0.1279 memory: 1238 2023/06/05 16:23:04 - mmengine - INFO - Epoch(val) [125][ 40/260] eta: 0:00:36 time: 0.1412 data_time: 0.0823 memory: 1238 2023/06/05 16:23:07 - mmengine - INFO - Epoch(val) [125][ 60/260] eta: 0:00:31 time: 0.1441 data_time: 0.0852 memory: 1238 2023/06/05 16:23:10 - mmengine - INFO - Epoch(val) [125][ 80/260] eta: 0:00:26 time: 0.1171 data_time: 0.0583 memory: 1238 2023/06/05 16:23:12 - mmengine - INFO - Epoch(val) [125][100/260] eta: 0:00:23 time: 0.1437 data_time: 0.0852 memory: 1238 2023/06/05 16:23:15 - mmengine - INFO - Epoch(val) [125][120/260] eta: 0:00:20 time: 0.1309 data_time: 0.0724 memory: 1238 2023/06/05 16:23:18 - mmengine - INFO - Epoch(val) [125][140/260] eta: 0:00:17 time: 0.1477 data_time: 0.0892 memory: 1238 2023/06/05 16:23:21 - mmengine - INFO - Epoch(val) [125][160/260] eta: 0:00:14 time: 0.1347 data_time: 0.0758 memory: 1238 2023/06/05 16:23:23 - mmengine - INFO - Epoch(val) [125][180/260] eta: 0:00:11 time: 0.1184 data_time: 0.0599 memory: 1238 2023/06/05 16:23:26 - mmengine - INFO - Epoch(val) [125][200/260] eta: 0:00:08 time: 0.1570 data_time: 0.0981 memory: 1238 2023/06/05 16:23:28 - mmengine - INFO - Epoch(val) [125][220/260] eta: 0:00:05 time: 0.1107 data_time: 0.0524 memory: 1238 2023/06/05 16:23:31 - mmengine - INFO - Epoch(val) [125][240/260] eta: 0:00:02 time: 0.1442 data_time: 0.0857 memory: 1238 2023/06/05 16:23:34 - mmengine - INFO - Epoch(val) [125][260/260] eta: 0:00:00 time: 0.1183 data_time: 0.0607 memory: 1238 2023/06/05 16:23:42 - mmengine - INFO - Epoch(val) [125][260/260] acc/top1: 0.6208 acc/top5: 0.8321 acc/mean1: 0.6140 data_time: 0.0792 time: 0.1377 2023/06/05 16:23:42 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_120.pth is removed 2023/06/05 16:23:44 - mmengine - INFO - The best checkpoint with 0.6208 acc/top1 at 125 epoch is saved to best_acc_top1_epoch_125.pth. 2023/06/05 16:23:50 - mmengine - INFO - Epoch(train) [126][ 20/2569] lr: 4.0000e-03 eta: 4:44:53 time: 0.3247 data_time: 0.0674 memory: 5828 grad_norm: 4.8249 loss: 1.8985 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8985 2023/06/05 16:23:56 - mmengine - INFO - Epoch(train) [126][ 40/2569] lr: 4.0000e-03 eta: 4:44:48 time: 0.2645 data_time: 0.0078 memory: 5828 grad_norm: 4.9597 loss: 1.9839 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9839 2023/06/05 16:24:01 - mmengine - INFO - Epoch(train) [126][ 60/2569] lr: 4.0000e-03 eta: 4:44:43 time: 0.2675 data_time: 0.0075 memory: 5828 grad_norm: 4.8831 loss: 1.9649 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9649 2023/06/05 16:24:06 - mmengine - INFO - Epoch(train) [126][ 80/2569] lr: 4.0000e-03 eta: 4:44:37 time: 0.2654 data_time: 0.0071 memory: 5828 grad_norm: 4.8474 loss: 1.9941 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9941 2023/06/05 16:24:12 - mmengine - INFO - Epoch(train) [126][ 100/2569] lr: 4.0000e-03 eta: 4:44:32 time: 0.2774 data_time: 0.0074 memory: 5828 grad_norm: 4.8119 loss: 1.6526 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6526 2023/06/05 16:24:17 - mmengine - INFO - Epoch(train) [126][ 120/2569] lr: 4.0000e-03 eta: 4:44:27 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 4.8275 loss: 1.8148 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8148 2023/06/05 16:24:23 - mmengine - INFO - Epoch(train) [126][ 140/2569] lr: 4.0000e-03 eta: 4:44:21 time: 0.2661 data_time: 0.0077 memory: 5828 grad_norm: 4.8940 loss: 1.8234 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8234 2023/06/05 16:24:28 - mmengine - INFO - Epoch(train) [126][ 160/2569] lr: 4.0000e-03 eta: 4:44:16 time: 0.2683 data_time: 0.0077 memory: 5828 grad_norm: 4.7679 loss: 1.8655 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8655 2023/06/05 16:24:33 - mmengine - INFO - Epoch(train) [126][ 180/2569] lr: 4.0000e-03 eta: 4:44:11 time: 0.2682 data_time: 0.0076 memory: 5828 grad_norm: 4.8583 loss: 1.7361 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7361 2023/06/05 16:24:39 - mmengine - INFO - Epoch(train) [126][ 200/2569] lr: 4.0000e-03 eta: 4:44:05 time: 0.2652 data_time: 0.0071 memory: 5828 grad_norm: 4.8702 loss: 1.7854 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7854 2023/06/05 16:24:44 - mmengine - INFO - Epoch(train) [126][ 220/2569] lr: 4.0000e-03 eta: 4:44:00 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 4.9140 loss: 1.9176 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9176 2023/06/05 16:24:49 - mmengine - INFO - Epoch(train) [126][ 240/2569] lr: 4.0000e-03 eta: 4:43:55 time: 0.2671 data_time: 0.0076 memory: 5828 grad_norm: 4.8793 loss: 1.7034 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7034 2023/06/05 16:24:55 - mmengine - INFO - Epoch(train) [126][ 260/2569] lr: 4.0000e-03 eta: 4:43:49 time: 0.2736 data_time: 0.0071 memory: 5828 grad_norm: 4.8737 loss: 1.6675 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.6675 2023/06/05 16:25:00 - mmengine - INFO - Epoch(train) [126][ 280/2569] lr: 4.0000e-03 eta: 4:43:44 time: 0.2712 data_time: 0.0076 memory: 5828 grad_norm: 4.9206 loss: 1.9075 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9075 2023/06/05 16:25:06 - mmengine - INFO - Epoch(train) [126][ 300/2569] lr: 4.0000e-03 eta: 4:43:39 time: 0.2730 data_time: 0.0074 memory: 5828 grad_norm: 4.9469 loss: 1.9211 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.9211 2023/06/05 16:25:11 - mmengine - INFO - Epoch(train) [126][ 320/2569] lr: 4.0000e-03 eta: 4:43:33 time: 0.2712 data_time: 0.0074 memory: 5828 grad_norm: 5.0425 loss: 1.9213 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9213 2023/06/05 16:25:16 - mmengine - INFO - Epoch(train) [126][ 340/2569] lr: 4.0000e-03 eta: 4:43:28 time: 0.2640 data_time: 0.0077 memory: 5828 grad_norm: 4.8482 loss: 1.4809 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4809 2023/06/05 16:25:22 - mmengine - INFO - Epoch(train) [126][ 360/2569] lr: 4.0000e-03 eta: 4:43:23 time: 0.2692 data_time: 0.0071 memory: 5828 grad_norm: 4.9671 loss: 1.6815 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6815 2023/06/05 16:25:27 - mmengine - INFO - Epoch(train) [126][ 380/2569] lr: 4.0000e-03 eta: 4:43:18 time: 0.2671 data_time: 0.0071 memory: 5828 grad_norm: 4.8449 loss: 2.1161 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.1161 2023/06/05 16:25:32 - mmengine - INFO - Epoch(train) [126][ 400/2569] lr: 4.0000e-03 eta: 4:43:12 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 4.8642 loss: 1.9133 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9133 2023/06/05 16:25:38 - mmengine - INFO - Epoch(train) [126][ 420/2569] lr: 4.0000e-03 eta: 4:43:07 time: 0.2693 data_time: 0.0070 memory: 5828 grad_norm: 4.8862 loss: 1.9635 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9635 2023/06/05 16:25:43 - mmengine - INFO - Epoch(train) [126][ 440/2569] lr: 4.0000e-03 eta: 4:43:02 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 4.8577 loss: 1.4786 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4786 2023/06/05 16:25:49 - mmengine - INFO - Epoch(train) [126][ 460/2569] lr: 4.0000e-03 eta: 4:42:56 time: 0.2763 data_time: 0.0075 memory: 5828 grad_norm: 4.9461 loss: 1.7761 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7761 2023/06/05 16:25:54 - mmengine - INFO - Epoch(train) [126][ 480/2569] lr: 4.0000e-03 eta: 4:42:51 time: 0.2680 data_time: 0.0075 memory: 5828 grad_norm: 4.9826 loss: 2.0552 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0552 2023/06/05 16:25:59 - mmengine - INFO - Epoch(train) [126][ 500/2569] lr: 4.0000e-03 eta: 4:42:46 time: 0.2687 data_time: 0.0085 memory: 5828 grad_norm: 4.9664 loss: 1.8014 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8014 2023/06/05 16:26:05 - mmengine - INFO - Epoch(train) [126][ 520/2569] lr: 4.0000e-03 eta: 4:42:40 time: 0.2691 data_time: 0.0077 memory: 5828 grad_norm: 4.9234 loss: 1.7543 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7543 2023/06/05 16:26:10 - mmengine - INFO - Epoch(train) [126][ 540/2569] lr: 4.0000e-03 eta: 4:42:35 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 4.8595 loss: 1.9352 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9352 2023/06/05 16:26:16 - mmengine - INFO - Epoch(train) [126][ 560/2569] lr: 4.0000e-03 eta: 4:42:30 time: 0.2709 data_time: 0.0073 memory: 5828 grad_norm: 4.8616 loss: 2.0018 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0018 2023/06/05 16:26:21 - mmengine - INFO - Epoch(train) [126][ 580/2569] lr: 4.0000e-03 eta: 4:42:24 time: 0.2731 data_time: 0.0072 memory: 5828 grad_norm: 4.7741 loss: 1.5892 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5892 2023/06/05 16:26:26 - mmengine - INFO - Epoch(train) [126][ 600/2569] lr: 4.0000e-03 eta: 4:42:19 time: 0.2654 data_time: 0.0070 memory: 5828 grad_norm: 4.9253 loss: 1.7152 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7152 2023/06/05 16:26:32 - mmengine - INFO - Epoch(train) [126][ 620/2569] lr: 4.0000e-03 eta: 4:42:14 time: 0.2640 data_time: 0.0071 memory: 5828 grad_norm: 4.8706 loss: 1.8927 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8927 2023/06/05 16:26:37 - mmengine - INFO - Epoch(train) [126][ 640/2569] lr: 4.0000e-03 eta: 4:42:08 time: 0.2738 data_time: 0.0071 memory: 5828 grad_norm: 4.8306 loss: 1.7302 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7302 2023/06/05 16:26:42 - mmengine - INFO - Epoch(train) [126][ 660/2569] lr: 4.0000e-03 eta: 4:42:03 time: 0.2614 data_time: 0.0070 memory: 5828 grad_norm: 4.8765 loss: 1.9445 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9445 2023/06/05 16:26:48 - mmengine - INFO - Epoch(train) [126][ 680/2569] lr: 4.0000e-03 eta: 4:41:58 time: 0.2735 data_time: 0.0079 memory: 5828 grad_norm: 4.8729 loss: 1.8304 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8304 2023/06/05 16:26:53 - mmengine - INFO - Epoch(train) [126][ 700/2569] lr: 4.0000e-03 eta: 4:41:52 time: 0.2639 data_time: 0.0071 memory: 5828 grad_norm: 4.8569 loss: 1.9306 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9306 2023/06/05 16:26:59 - mmengine - INFO - Epoch(train) [126][ 720/2569] lr: 4.0000e-03 eta: 4:41:47 time: 0.2762 data_time: 0.0069 memory: 5828 grad_norm: 4.9640 loss: 2.0271 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 2.0271 2023/06/05 16:27:04 - mmengine - INFO - Epoch(train) [126][ 740/2569] lr: 4.0000e-03 eta: 4:41:42 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 4.8235 loss: 1.9587 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.9587 2023/06/05 16:27:09 - mmengine - INFO - Epoch(train) [126][ 760/2569] lr: 4.0000e-03 eta: 4:41:37 time: 0.2775 data_time: 0.0067 memory: 5828 grad_norm: 4.8529 loss: 1.5259 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.5259 2023/06/05 16:27:15 - mmengine - INFO - Epoch(train) [126][ 780/2569] lr: 4.0000e-03 eta: 4:41:31 time: 0.2673 data_time: 0.0070 memory: 5828 grad_norm: 4.9045 loss: 1.8928 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8928 2023/06/05 16:27:20 - mmengine - INFO - Epoch(train) [126][ 800/2569] lr: 4.0000e-03 eta: 4:41:26 time: 0.2668 data_time: 0.0075 memory: 5828 grad_norm: 4.9445 loss: 1.9886 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9886 2023/06/05 16:27:26 - mmengine - INFO - Epoch(train) [126][ 820/2569] lr: 4.0000e-03 eta: 4:41:21 time: 0.2677 data_time: 0.0070 memory: 5828 grad_norm: 4.8913 loss: 2.0713 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0713 2023/06/05 16:27:31 - mmengine - INFO - Epoch(train) [126][ 840/2569] lr: 4.0000e-03 eta: 4:41:15 time: 0.2682 data_time: 0.0069 memory: 5828 grad_norm: 4.8717 loss: 1.9104 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9104 2023/06/05 16:27:36 - mmengine - INFO - Epoch(train) [126][ 860/2569] lr: 4.0000e-03 eta: 4:41:10 time: 0.2732 data_time: 0.0071 memory: 5828 grad_norm: 4.9690 loss: 1.7458 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7458 2023/06/05 16:27:41 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:27:42 - mmengine - INFO - Epoch(train) [126][ 880/2569] lr: 4.0000e-03 eta: 4:41:05 time: 0.2792 data_time: 0.0072 memory: 5828 grad_norm: 4.8615 loss: 1.8763 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8763 2023/06/05 16:27:47 - mmengine - INFO - Epoch(train) [126][ 900/2569] lr: 4.0000e-03 eta: 4:40:59 time: 0.2733 data_time: 0.0071 memory: 5828 grad_norm: 4.9124 loss: 1.5361 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5361 2023/06/05 16:27:53 - mmengine - INFO - Epoch(train) [126][ 920/2569] lr: 4.0000e-03 eta: 4:40:54 time: 0.2706 data_time: 0.0070 memory: 5828 grad_norm: 4.9501 loss: 1.7655 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7655 2023/06/05 16:27:58 - mmengine - INFO - Epoch(train) [126][ 940/2569] lr: 4.0000e-03 eta: 4:40:49 time: 0.2613 data_time: 0.0075 memory: 5828 grad_norm: 4.8029 loss: 1.7128 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7128 2023/06/05 16:28:04 - mmengine - INFO - Epoch(train) [126][ 960/2569] lr: 4.0000e-03 eta: 4:40:43 time: 0.2730 data_time: 0.0070 memory: 5828 grad_norm: 4.8119 loss: 1.5558 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5558 2023/06/05 16:28:09 - mmengine - INFO - Epoch(train) [126][ 980/2569] lr: 4.0000e-03 eta: 4:40:38 time: 0.2799 data_time: 0.0074 memory: 5828 grad_norm: 4.8923 loss: 1.4838 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4838 2023/06/05 16:28:15 - mmengine - INFO - Epoch(train) [126][1000/2569] lr: 4.0000e-03 eta: 4:40:33 time: 0.2736 data_time: 0.0075 memory: 5828 grad_norm: 4.8384 loss: 1.6644 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6644 2023/06/05 16:28:20 - mmengine - INFO - Epoch(train) [126][1020/2569] lr: 4.0000e-03 eta: 4:40:28 time: 0.2616 data_time: 0.0070 memory: 5828 grad_norm: 4.9635 loss: 1.7520 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7520 2023/06/05 16:28:25 - mmengine - INFO - Epoch(train) [126][1040/2569] lr: 4.0000e-03 eta: 4:40:22 time: 0.2711 data_time: 0.0073 memory: 5828 grad_norm: 4.9081 loss: 1.4236 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4236 2023/06/05 16:28:31 - mmengine - INFO - Epoch(train) [126][1060/2569] lr: 4.0000e-03 eta: 4:40:17 time: 0.2682 data_time: 0.0074 memory: 5828 grad_norm: 4.8324 loss: 1.5880 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5880 2023/06/05 16:28:36 - mmengine - INFO - Epoch(train) [126][1080/2569] lr: 4.0000e-03 eta: 4:40:12 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 4.8445 loss: 1.5756 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5756 2023/06/05 16:28:41 - mmengine - INFO - Epoch(train) [126][1100/2569] lr: 4.0000e-03 eta: 4:40:06 time: 0.2653 data_time: 0.0071 memory: 5828 grad_norm: 4.8535 loss: 1.5886 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5886 2023/06/05 16:28:47 - mmengine - INFO - Epoch(train) [126][1120/2569] lr: 4.0000e-03 eta: 4:40:01 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 4.8041 loss: 1.4906 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4906 2023/06/05 16:28:52 - mmengine - INFO - Epoch(train) [126][1140/2569] lr: 4.0000e-03 eta: 4:39:56 time: 0.2725 data_time: 0.0071 memory: 5828 grad_norm: 4.9123 loss: 1.6124 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6124 2023/06/05 16:28:57 - mmengine - INFO - Epoch(train) [126][1160/2569] lr: 4.0000e-03 eta: 4:39:50 time: 0.2615 data_time: 0.0078 memory: 5828 grad_norm: 4.9526 loss: 1.7912 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7912 2023/06/05 16:29:03 - mmengine - INFO - Epoch(train) [126][1180/2569] lr: 4.0000e-03 eta: 4:39:45 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 4.9419 loss: 1.8522 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8522 2023/06/05 16:29:08 - mmengine - INFO - Epoch(train) [126][1200/2569] lr: 4.0000e-03 eta: 4:39:40 time: 0.2698 data_time: 0.0076 memory: 5828 grad_norm: 4.8682 loss: 1.6830 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6830 2023/06/05 16:29:13 - mmengine - INFO - Epoch(train) [126][1220/2569] lr: 4.0000e-03 eta: 4:39:34 time: 0.2613 data_time: 0.0072 memory: 5828 grad_norm: 4.8989 loss: 1.4950 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4950 2023/06/05 16:29:19 - mmengine - INFO - Epoch(train) [126][1240/2569] lr: 4.0000e-03 eta: 4:39:29 time: 0.2669 data_time: 0.0071 memory: 5828 grad_norm: 4.8858 loss: 1.7663 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7663 2023/06/05 16:29:24 - mmengine - INFO - Epoch(train) [126][1260/2569] lr: 4.0000e-03 eta: 4:39:24 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 4.8291 loss: 1.9647 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9647 2023/06/05 16:29:29 - mmengine - INFO - Epoch(train) [126][1280/2569] lr: 4.0000e-03 eta: 4:39:18 time: 0.2674 data_time: 0.0074 memory: 5828 grad_norm: 4.7742 loss: 1.5821 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5821 2023/06/05 16:29:35 - mmengine - INFO - Epoch(train) [126][1300/2569] lr: 4.0000e-03 eta: 4:39:13 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 4.8322 loss: 1.5644 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5644 2023/06/05 16:29:40 - mmengine - INFO - Epoch(train) [126][1320/2569] lr: 4.0000e-03 eta: 4:39:08 time: 0.2676 data_time: 0.0074 memory: 5828 grad_norm: 4.9715 loss: 1.6579 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6579 2023/06/05 16:29:45 - mmengine - INFO - Epoch(train) [126][1340/2569] lr: 4.0000e-03 eta: 4:39:02 time: 0.2612 data_time: 0.0074 memory: 5828 grad_norm: 4.9177 loss: 1.9171 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9171 2023/06/05 16:29:51 - mmengine - INFO - Epoch(train) [126][1360/2569] lr: 4.0000e-03 eta: 4:38:57 time: 0.2755 data_time: 0.0074 memory: 5828 grad_norm: 4.9245 loss: 1.6612 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6612 2023/06/05 16:29:56 - mmengine - INFO - Epoch(train) [126][1380/2569] lr: 4.0000e-03 eta: 4:38:52 time: 0.2767 data_time: 0.0069 memory: 5828 grad_norm: 4.9364 loss: 1.9854 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9854 2023/06/05 16:30:02 - mmengine - INFO - Epoch(train) [126][1400/2569] lr: 4.0000e-03 eta: 4:38:46 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 4.9138 loss: 2.0742 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0742 2023/06/05 16:30:07 - mmengine - INFO - Epoch(train) [126][1420/2569] lr: 4.0000e-03 eta: 4:38:41 time: 0.2719 data_time: 0.0072 memory: 5828 grad_norm: 4.8504 loss: 1.7103 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7103 2023/06/05 16:30:13 - mmengine - INFO - Epoch(train) [126][1440/2569] lr: 4.0000e-03 eta: 4:38:36 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 4.9020 loss: 1.5620 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5620 2023/06/05 16:30:18 - mmengine - INFO - Epoch(train) [126][1460/2569] lr: 4.0000e-03 eta: 4:38:31 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 4.8937 loss: 2.0455 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0455 2023/06/05 16:30:23 - mmengine - INFO - Epoch(train) [126][1480/2569] lr: 4.0000e-03 eta: 4:38:25 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 4.9178 loss: 1.8426 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8426 2023/06/05 16:30:28 - mmengine - INFO - Epoch(train) [126][1500/2569] lr: 4.0000e-03 eta: 4:38:20 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 4.8530 loss: 1.7820 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7820 2023/06/05 16:30:34 - mmengine - INFO - Epoch(train) [126][1520/2569] lr: 4.0000e-03 eta: 4:38:15 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 4.9284 loss: 1.9260 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9260 2023/06/05 16:30:39 - mmengine - INFO - Epoch(train) [126][1540/2569] lr: 4.0000e-03 eta: 4:38:09 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 4.8205 loss: 1.5142 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5142 2023/06/05 16:30:44 - mmengine - INFO - Epoch(train) [126][1560/2569] lr: 4.0000e-03 eta: 4:38:04 time: 0.2678 data_time: 0.0072 memory: 5828 grad_norm: 4.9081 loss: 1.8103 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8103 2023/06/05 16:30:50 - mmengine - INFO - Epoch(train) [126][1580/2569] lr: 4.0000e-03 eta: 4:37:59 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 4.9896 loss: 1.7035 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7035 2023/06/05 16:30:55 - mmengine - INFO - Epoch(train) [126][1600/2569] lr: 4.0000e-03 eta: 4:37:53 time: 0.2665 data_time: 0.0072 memory: 5828 grad_norm: 4.9130 loss: 1.7663 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7663 2023/06/05 16:31:00 - mmengine - INFO - Epoch(train) [126][1620/2569] lr: 4.0000e-03 eta: 4:37:48 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 4.9041 loss: 1.5425 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5425 2023/06/05 16:31:06 - mmengine - INFO - Epoch(train) [126][1640/2569] lr: 4.0000e-03 eta: 4:37:43 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 4.9107 loss: 1.8042 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8042 2023/06/05 16:31:11 - mmengine - INFO - Epoch(train) [126][1660/2569] lr: 4.0000e-03 eta: 4:37:37 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 4.9383 loss: 2.0048 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0048 2023/06/05 16:31:16 - mmengine - INFO - Epoch(train) [126][1680/2569] lr: 4.0000e-03 eta: 4:37:32 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 4.8691 loss: 1.9410 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.9410 2023/06/05 16:31:22 - mmengine - INFO - Epoch(train) [126][1700/2569] lr: 4.0000e-03 eta: 4:37:27 time: 0.2668 data_time: 0.0071 memory: 5828 grad_norm: 4.8456 loss: 1.6167 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6167 2023/06/05 16:31:27 - mmengine - INFO - Epoch(train) [126][1720/2569] lr: 4.0000e-03 eta: 4:37:21 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 4.7755 loss: 1.5826 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5826 2023/06/05 16:31:32 - mmengine - INFO - Epoch(train) [126][1740/2569] lr: 4.0000e-03 eta: 4:37:16 time: 0.2657 data_time: 0.0075 memory: 5828 grad_norm: 4.8956 loss: 2.0263 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0263 2023/06/05 16:31:38 - mmengine - INFO - Epoch(train) [126][1760/2569] lr: 4.0000e-03 eta: 4:37:11 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 4.8861 loss: 1.3736 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3736 2023/06/05 16:31:43 - mmengine - INFO - Epoch(train) [126][1780/2569] lr: 4.0000e-03 eta: 4:37:05 time: 0.2723 data_time: 0.0074 memory: 5828 grad_norm: 4.9003 loss: 1.8291 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8291 2023/06/05 16:31:48 - mmengine - INFO - Epoch(train) [126][1800/2569] lr: 4.0000e-03 eta: 4:37:00 time: 0.2624 data_time: 0.0079 memory: 5828 grad_norm: 4.8099 loss: 1.8388 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8388 2023/06/05 16:31:54 - mmengine - INFO - Epoch(train) [126][1820/2569] lr: 4.0000e-03 eta: 4:36:55 time: 0.2631 data_time: 0.0080 memory: 5828 grad_norm: 4.9704 loss: 2.1134 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 2.1134 2023/06/05 16:31:59 - mmengine - INFO - Epoch(train) [126][1840/2569] lr: 4.0000e-03 eta: 4:36:49 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 4.9431 loss: 1.3401 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3401 2023/06/05 16:32:04 - mmengine - INFO - Epoch(train) [126][1860/2569] lr: 4.0000e-03 eta: 4:36:44 time: 0.2708 data_time: 0.0077 memory: 5828 grad_norm: 4.9187 loss: 1.5726 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5726 2023/06/05 16:32:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:32:10 - mmengine - INFO - Epoch(train) [126][1880/2569] lr: 4.0000e-03 eta: 4:36:39 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 4.8855 loss: 2.0199 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0199 2023/06/05 16:32:15 - mmengine - INFO - Epoch(train) [126][1900/2569] lr: 4.0000e-03 eta: 4:36:33 time: 0.2723 data_time: 0.0073 memory: 5828 grad_norm: 4.8725 loss: 1.9256 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9256 2023/06/05 16:32:20 - mmengine - INFO - Epoch(train) [126][1920/2569] lr: 4.0000e-03 eta: 4:36:28 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 4.8633 loss: 1.9120 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9120 2023/06/05 16:32:26 - mmengine - INFO - Epoch(train) [126][1940/2569] lr: 4.0000e-03 eta: 4:36:23 time: 0.2642 data_time: 0.0074 memory: 5828 grad_norm: 4.8244 loss: 1.6507 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6507 2023/06/05 16:32:31 - mmengine - INFO - Epoch(train) [126][1960/2569] lr: 4.0000e-03 eta: 4:36:17 time: 0.2648 data_time: 0.0070 memory: 5828 grad_norm: 4.8636 loss: 1.7959 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7959 2023/06/05 16:32:36 - mmengine - INFO - Epoch(train) [126][1980/2569] lr: 4.0000e-03 eta: 4:36:12 time: 0.2737 data_time: 0.0072 memory: 5828 grad_norm: 4.9720 loss: 1.6042 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6042 2023/06/05 16:32:42 - mmengine - INFO - Epoch(train) [126][2000/2569] lr: 4.0000e-03 eta: 4:36:07 time: 0.2733 data_time: 0.0075 memory: 5828 grad_norm: 4.9400 loss: 1.6507 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6507 2023/06/05 16:32:47 - mmengine - INFO - Epoch(train) [126][2020/2569] lr: 4.0000e-03 eta: 4:36:01 time: 0.2756 data_time: 0.0072 memory: 5828 grad_norm: 4.8525 loss: 1.8497 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8497 2023/06/05 16:32:53 - mmengine - INFO - Epoch(train) [126][2040/2569] lr: 4.0000e-03 eta: 4:35:56 time: 0.2734 data_time: 0.0074 memory: 5828 grad_norm: 4.8924 loss: 1.5618 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5618 2023/06/05 16:32:59 - mmengine - INFO - Epoch(train) [126][2060/2569] lr: 4.0000e-03 eta: 4:35:51 time: 0.2819 data_time: 0.0075 memory: 5828 grad_norm: 4.8732 loss: 1.7994 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7994 2023/06/05 16:33:04 - mmengine - INFO - Epoch(train) [126][2080/2569] lr: 4.0000e-03 eta: 4:35:46 time: 0.2727 data_time: 0.0070 memory: 5828 grad_norm: 4.8576 loss: 1.7510 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7510 2023/06/05 16:33:09 - mmengine - INFO - Epoch(train) [126][2100/2569] lr: 4.0000e-03 eta: 4:35:40 time: 0.2683 data_time: 0.0070 memory: 5828 grad_norm: 4.9851 loss: 1.5540 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5540 2023/06/05 16:33:15 - mmengine - INFO - Epoch(train) [126][2120/2569] lr: 4.0000e-03 eta: 4:35:35 time: 0.2702 data_time: 0.0074 memory: 5828 grad_norm: 4.8557 loss: 1.7186 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7186 2023/06/05 16:33:20 - mmengine - INFO - Epoch(train) [126][2140/2569] lr: 4.0000e-03 eta: 4:35:30 time: 0.2711 data_time: 0.0073 memory: 5828 grad_norm: 4.7660 loss: 1.7111 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7111 2023/06/05 16:33:26 - mmengine - INFO - Epoch(train) [126][2160/2569] lr: 4.0000e-03 eta: 4:35:24 time: 0.2800 data_time: 0.0073 memory: 5828 grad_norm: 4.8863 loss: 2.0703 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0703 2023/06/05 16:33:31 - mmengine - INFO - Epoch(train) [126][2180/2569] lr: 4.0000e-03 eta: 4:35:19 time: 0.2649 data_time: 0.0070 memory: 5828 grad_norm: 4.8426 loss: 2.0600 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0600 2023/06/05 16:33:37 - mmengine - INFO - Epoch(train) [126][2200/2569] lr: 4.0000e-03 eta: 4:35:14 time: 0.2711 data_time: 0.0077 memory: 5828 grad_norm: 4.8524 loss: 1.6150 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6150 2023/06/05 16:33:42 - mmengine - INFO - Epoch(train) [126][2220/2569] lr: 4.0000e-03 eta: 4:35:08 time: 0.2670 data_time: 0.0080 memory: 5828 grad_norm: 4.9687 loss: 1.7401 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7401 2023/06/05 16:33:47 - mmengine - INFO - Epoch(train) [126][2240/2569] lr: 4.0000e-03 eta: 4:35:03 time: 0.2639 data_time: 0.0071 memory: 5828 grad_norm: 4.9236 loss: 1.7935 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7935 2023/06/05 16:33:53 - mmengine - INFO - Epoch(train) [126][2260/2569] lr: 4.0000e-03 eta: 4:34:58 time: 0.2736 data_time: 0.0070 memory: 5828 grad_norm: 4.9077 loss: 1.6090 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6090 2023/06/05 16:33:58 - mmengine - INFO - Epoch(train) [126][2280/2569] lr: 4.0000e-03 eta: 4:34:52 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 4.8960 loss: 1.7014 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7014 2023/06/05 16:34:04 - mmengine - INFO - Epoch(train) [126][2300/2569] lr: 4.0000e-03 eta: 4:34:47 time: 0.2723 data_time: 0.0072 memory: 5828 grad_norm: 4.8982 loss: 1.5926 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5926 2023/06/05 16:34:09 - mmengine - INFO - Epoch(train) [126][2320/2569] lr: 4.0000e-03 eta: 4:34:42 time: 0.2829 data_time: 0.0072 memory: 5828 grad_norm: 4.8913 loss: 1.7264 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7264 2023/06/05 16:34:14 - mmengine - INFO - Epoch(train) [126][2340/2569] lr: 4.0000e-03 eta: 4:34:37 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 4.8558 loss: 1.9224 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9224 2023/06/05 16:34:20 - mmengine - INFO - Epoch(train) [126][2360/2569] lr: 4.0000e-03 eta: 4:34:31 time: 0.2860 data_time: 0.0075 memory: 5828 grad_norm: 4.8564 loss: 2.0944 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0944 2023/06/05 16:34:26 - mmengine - INFO - Epoch(train) [126][2380/2569] lr: 4.0000e-03 eta: 4:34:26 time: 0.2668 data_time: 0.0071 memory: 5828 grad_norm: 4.8871 loss: 1.7262 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7262 2023/06/05 16:34:31 - mmengine - INFO - Epoch(train) [126][2400/2569] lr: 4.0000e-03 eta: 4:34:21 time: 0.2730 data_time: 0.0071 memory: 5828 grad_norm: 4.9605 loss: 1.6018 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6018 2023/06/05 16:34:36 - mmengine - INFO - Epoch(train) [126][2420/2569] lr: 4.0000e-03 eta: 4:34:15 time: 0.2613 data_time: 0.0071 memory: 5828 grad_norm: 4.9479 loss: 2.2710 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2710 2023/06/05 16:34:42 - mmengine - INFO - Epoch(train) [126][2440/2569] lr: 4.0000e-03 eta: 4:34:10 time: 0.2685 data_time: 0.0071 memory: 5828 grad_norm: 4.9339 loss: 1.9183 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9183 2023/06/05 16:34:47 - mmengine - INFO - Epoch(train) [126][2460/2569] lr: 4.0000e-03 eta: 4:34:05 time: 0.2633 data_time: 0.0072 memory: 5828 grad_norm: 4.8955 loss: 2.0395 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0395 2023/06/05 16:34:52 - mmengine - INFO - Epoch(train) [126][2480/2569] lr: 4.0000e-03 eta: 4:33:59 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 4.8797 loss: 1.4160 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4160 2023/06/05 16:34:58 - mmengine - INFO - Epoch(train) [126][2500/2569] lr: 4.0000e-03 eta: 4:33:54 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 4.8441 loss: 1.9332 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9332 2023/06/05 16:35:03 - mmengine - INFO - Epoch(train) [126][2520/2569] lr: 4.0000e-03 eta: 4:33:49 time: 0.2645 data_time: 0.0070 memory: 5828 grad_norm: 4.9621 loss: 1.6540 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6540 2023/06/05 16:35:08 - mmengine - INFO - Epoch(train) [126][2540/2569] lr: 4.0000e-03 eta: 4:33:43 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 4.9471 loss: 1.8094 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8094 2023/06/05 16:35:13 - mmengine - INFO - Epoch(train) [126][2560/2569] lr: 4.0000e-03 eta: 4:33:38 time: 0.2593 data_time: 0.0074 memory: 5828 grad_norm: 4.9267 loss: 1.8675 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8675 2023/06/05 16:35:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:35:16 - mmengine - INFO - Epoch(train) [126][2569/2569] lr: 4.0000e-03 eta: 4:33:36 time: 0.2535 data_time: 0.0071 memory: 5828 grad_norm: 4.9747 loss: 1.7871 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7871 2023/06/05 16:35:23 - mmengine - INFO - Epoch(train) [127][ 20/2569] lr: 4.0000e-03 eta: 4:33:31 time: 0.3453 data_time: 0.0455 memory: 5828 grad_norm: 4.8665 loss: 1.6524 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6524 2023/06/05 16:35:28 - mmengine - INFO - Epoch(train) [127][ 40/2569] lr: 4.0000e-03 eta: 4:33:25 time: 0.2690 data_time: 0.0070 memory: 5828 grad_norm: 4.9034 loss: 1.6233 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6233 2023/06/05 16:35:33 - mmengine - INFO - Epoch(train) [127][ 60/2569] lr: 4.0000e-03 eta: 4:33:20 time: 0.2731 data_time: 0.0070 memory: 5828 grad_norm: 4.9486 loss: 1.7772 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7772 2023/06/05 16:35:39 - mmengine - INFO - Epoch(train) [127][ 80/2569] lr: 4.0000e-03 eta: 4:33:15 time: 0.2709 data_time: 0.0071 memory: 5828 grad_norm: 4.9145 loss: 1.9531 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9531 2023/06/05 16:35:44 - mmengine - INFO - Epoch(train) [127][ 100/2569] lr: 4.0000e-03 eta: 4:33:09 time: 0.2640 data_time: 0.0069 memory: 5828 grad_norm: 4.8405 loss: 1.6347 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6347 2023/06/05 16:35:50 - mmengine - INFO - Epoch(train) [127][ 120/2569] lr: 4.0000e-03 eta: 4:33:04 time: 0.2682 data_time: 0.0069 memory: 5828 grad_norm: 4.8759 loss: 1.8283 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8283 2023/06/05 16:35:55 - mmengine - INFO - Epoch(train) [127][ 140/2569] lr: 4.0000e-03 eta: 4:32:59 time: 0.2621 data_time: 0.0071 memory: 5828 grad_norm: 4.8128 loss: 1.6937 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6937 2023/06/05 16:36:00 - mmengine - INFO - Epoch(train) [127][ 160/2569] lr: 4.0000e-03 eta: 4:32:53 time: 0.2631 data_time: 0.0069 memory: 5828 grad_norm: 4.9112 loss: 1.6696 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6696 2023/06/05 16:36:05 - mmengine - INFO - Epoch(train) [127][ 180/2569] lr: 4.0000e-03 eta: 4:32:48 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 4.9475 loss: 2.0008 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0008 2023/06/05 16:36:11 - mmengine - INFO - Epoch(train) [127][ 200/2569] lr: 4.0000e-03 eta: 4:32:43 time: 0.2704 data_time: 0.0073 memory: 5828 grad_norm: 4.9393 loss: 1.5607 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5607 2023/06/05 16:36:16 - mmengine - INFO - Epoch(train) [127][ 220/2569] lr: 4.0000e-03 eta: 4:32:37 time: 0.2721 data_time: 0.0073 memory: 5828 grad_norm: 4.9983 loss: 1.9070 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9070 2023/06/05 16:36:22 - mmengine - INFO - Epoch(train) [127][ 240/2569] lr: 4.0000e-03 eta: 4:32:32 time: 0.2694 data_time: 0.0075 memory: 5828 grad_norm: 4.8287 loss: 1.7070 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7070 2023/06/05 16:36:27 - mmengine - INFO - Epoch(train) [127][ 260/2569] lr: 4.0000e-03 eta: 4:32:27 time: 0.2666 data_time: 0.0070 memory: 5828 grad_norm: 4.9521 loss: 1.5989 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5989 2023/06/05 16:36:32 - mmengine - INFO - Epoch(train) [127][ 280/2569] lr: 4.0000e-03 eta: 4:32:21 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 4.8793 loss: 1.8578 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8578 2023/06/05 16:36:38 - mmengine - INFO - Epoch(train) [127][ 300/2569] lr: 4.0000e-03 eta: 4:32:16 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 4.8783 loss: 1.8170 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.8170 2023/06/05 16:36:39 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:36:43 - mmengine - INFO - Epoch(train) [127][ 320/2569] lr: 4.0000e-03 eta: 4:32:11 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 4.8338 loss: 1.9058 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9058 2023/06/05 16:36:49 - mmengine - INFO - Epoch(train) [127][ 340/2569] lr: 4.0000e-03 eta: 4:32:05 time: 0.2790 data_time: 0.0074 memory: 5828 grad_norm: 4.8033 loss: 1.6514 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6514 2023/06/05 16:36:54 - mmengine - INFO - Epoch(train) [127][ 360/2569] lr: 4.0000e-03 eta: 4:32:00 time: 0.2698 data_time: 0.0071 memory: 5828 grad_norm: 4.8558 loss: 1.7248 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7248 2023/06/05 16:37:00 - mmengine - INFO - Epoch(train) [127][ 380/2569] lr: 4.0000e-03 eta: 4:31:55 time: 0.2731 data_time: 0.0070 memory: 5828 grad_norm: 4.8682 loss: 1.8527 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8527 2023/06/05 16:37:05 - mmengine - INFO - Epoch(train) [127][ 400/2569] lr: 4.0000e-03 eta: 4:31:50 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 4.9323 loss: 1.6558 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6558 2023/06/05 16:37:10 - mmengine - INFO - Epoch(train) [127][ 420/2569] lr: 4.0000e-03 eta: 4:31:44 time: 0.2722 data_time: 0.0073 memory: 5828 grad_norm: 4.9229 loss: 1.5571 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5571 2023/06/05 16:37:16 - mmengine - INFO - Epoch(train) [127][ 440/2569] lr: 4.0000e-03 eta: 4:31:39 time: 0.2673 data_time: 0.0072 memory: 5828 grad_norm: 5.0127 loss: 1.6741 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6741 2023/06/05 16:37:21 - mmengine - INFO - Epoch(train) [127][ 460/2569] lr: 4.0000e-03 eta: 4:31:34 time: 0.2725 data_time: 0.0071 memory: 5828 grad_norm: 4.8428 loss: 2.0740 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0740 2023/06/05 16:37:27 - mmengine - INFO - Epoch(train) [127][ 480/2569] lr: 4.0000e-03 eta: 4:31:28 time: 0.2729 data_time: 0.0069 memory: 5828 grad_norm: 4.9992 loss: 1.6548 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6548 2023/06/05 16:37:32 - mmengine - INFO - Epoch(train) [127][ 500/2569] lr: 4.0000e-03 eta: 4:31:23 time: 0.2790 data_time: 0.0072 memory: 5828 grad_norm: 4.9429 loss: 1.7040 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7040 2023/06/05 16:37:38 - mmengine - INFO - Epoch(train) [127][ 520/2569] lr: 4.0000e-03 eta: 4:31:18 time: 0.2676 data_time: 0.0074 memory: 5828 grad_norm: 4.9091 loss: 2.1473 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1473 2023/06/05 16:37:43 - mmengine - INFO - Epoch(train) [127][ 540/2569] lr: 4.0000e-03 eta: 4:31:12 time: 0.2722 data_time: 0.0071 memory: 5828 grad_norm: 4.9803 loss: 2.0962 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0962 2023/06/05 16:37:48 - mmengine - INFO - Epoch(train) [127][ 560/2569] lr: 4.0000e-03 eta: 4:31:07 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 4.8864 loss: 1.8825 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8825 2023/06/05 16:37:54 - mmengine - INFO - Epoch(train) [127][ 580/2569] lr: 4.0000e-03 eta: 4:31:02 time: 0.2722 data_time: 0.0073 memory: 5828 grad_norm: 4.9040 loss: 1.6153 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6153 2023/06/05 16:37:59 - mmengine - INFO - Epoch(train) [127][ 600/2569] lr: 4.0000e-03 eta: 4:30:57 time: 0.2735 data_time: 0.0070 memory: 5828 grad_norm: 4.9162 loss: 1.9691 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9691 2023/06/05 16:38:05 - mmengine - INFO - Epoch(train) [127][ 620/2569] lr: 4.0000e-03 eta: 4:30:51 time: 0.2757 data_time: 0.0071 memory: 5828 grad_norm: 6.7456 loss: 1.8281 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8281 2023/06/05 16:38:10 - mmengine - INFO - Epoch(train) [127][ 640/2569] lr: 4.0000e-03 eta: 4:30:46 time: 0.2703 data_time: 0.0072 memory: 5828 grad_norm: 4.9915 loss: 1.8623 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8623 2023/06/05 16:38:16 - mmengine - INFO - Epoch(train) [127][ 660/2569] lr: 4.0000e-03 eta: 4:30:41 time: 0.2672 data_time: 0.0070 memory: 5828 grad_norm: 4.8776 loss: 1.6611 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6611 2023/06/05 16:38:21 - mmengine - INFO - Epoch(train) [127][ 680/2569] lr: 4.0000e-03 eta: 4:30:35 time: 0.2739 data_time: 0.0072 memory: 5828 grad_norm: 4.9347 loss: 1.9543 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9543 2023/06/05 16:38:26 - mmengine - INFO - Epoch(train) [127][ 700/2569] lr: 4.0000e-03 eta: 4:30:30 time: 0.2693 data_time: 0.0073 memory: 5828 grad_norm: 5.0004 loss: 1.5680 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5680 2023/06/05 16:38:32 - mmengine - INFO - Epoch(train) [127][ 720/2569] lr: 4.0000e-03 eta: 4:30:25 time: 0.2653 data_time: 0.0071 memory: 5828 grad_norm: 5.0275 loss: 1.7689 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7689 2023/06/05 16:38:37 - mmengine - INFO - Epoch(train) [127][ 740/2569] lr: 4.0000e-03 eta: 4:30:19 time: 0.2634 data_time: 0.0076 memory: 5828 grad_norm: 5.0058 loss: 1.7743 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7743 2023/06/05 16:38:43 - mmengine - INFO - Epoch(train) [127][ 760/2569] lr: 4.0000e-03 eta: 4:30:14 time: 0.2822 data_time: 0.0068 memory: 5828 grad_norm: 4.8799 loss: 1.9051 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9051 2023/06/05 16:38:48 - mmengine - INFO - Epoch(train) [127][ 780/2569] lr: 4.0000e-03 eta: 4:30:09 time: 0.2650 data_time: 0.0071 memory: 5828 grad_norm: 4.9607 loss: 1.3740 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.3740 2023/06/05 16:38:54 - mmengine - INFO - Epoch(train) [127][ 800/2569] lr: 4.0000e-03 eta: 4:30:03 time: 0.2749 data_time: 0.0072 memory: 5828 grad_norm: 4.8988 loss: 1.6190 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6190 2023/06/05 16:38:59 - mmengine - INFO - Epoch(train) [127][ 820/2569] lr: 4.0000e-03 eta: 4:29:58 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 4.9591 loss: 1.8782 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8782 2023/06/05 16:39:04 - mmengine - INFO - Epoch(train) [127][ 840/2569] lr: 4.0000e-03 eta: 4:29:53 time: 0.2746 data_time: 0.0074 memory: 5828 grad_norm: 4.9798 loss: 1.8392 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8392 2023/06/05 16:39:10 - mmengine - INFO - Epoch(train) [127][ 860/2569] lr: 4.0000e-03 eta: 4:29:48 time: 0.2745 data_time: 0.0072 memory: 5828 grad_norm: 4.9380 loss: 1.6780 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6780 2023/06/05 16:39:15 - mmengine - INFO - Epoch(train) [127][ 880/2569] lr: 4.0000e-03 eta: 4:29:42 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 4.8982 loss: 1.9907 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9907 2023/06/05 16:39:21 - mmengine - INFO - Epoch(train) [127][ 900/2569] lr: 4.0000e-03 eta: 4:29:37 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 4.9335 loss: 1.8363 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8363 2023/06/05 16:39:26 - mmengine - INFO - Epoch(train) [127][ 920/2569] lr: 4.0000e-03 eta: 4:29:32 time: 0.2654 data_time: 0.0071 memory: 5828 grad_norm: 5.0044 loss: 1.5306 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5306 2023/06/05 16:39:31 - mmengine - INFO - Epoch(train) [127][ 940/2569] lr: 4.0000e-03 eta: 4:29:26 time: 0.2802 data_time: 0.0070 memory: 5828 grad_norm: 4.9170 loss: 1.5842 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5842 2023/06/05 16:39:37 - mmengine - INFO - Epoch(train) [127][ 960/2569] lr: 4.0000e-03 eta: 4:29:21 time: 0.2621 data_time: 0.0076 memory: 5828 grad_norm: 4.9077 loss: 1.8164 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8164 2023/06/05 16:39:42 - mmengine - INFO - Epoch(train) [127][ 980/2569] lr: 4.0000e-03 eta: 4:29:16 time: 0.2731 data_time: 0.0073 memory: 5828 grad_norm: 5.0285 loss: 2.0016 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0016 2023/06/05 16:39:48 - mmengine - INFO - Epoch(train) [127][1000/2569] lr: 4.0000e-03 eta: 4:29:10 time: 0.2682 data_time: 0.0071 memory: 5828 grad_norm: 4.9255 loss: 1.4921 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4921 2023/06/05 16:39:53 - mmengine - INFO - Epoch(train) [127][1020/2569] lr: 4.0000e-03 eta: 4:29:05 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 4.9589 loss: 2.0952 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0952 2023/06/05 16:39:58 - mmengine - INFO - Epoch(train) [127][1040/2569] lr: 4.0000e-03 eta: 4:29:00 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 4.9551 loss: 1.8525 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8525 2023/06/05 16:40:04 - mmengine - INFO - Epoch(train) [127][1060/2569] lr: 4.0000e-03 eta: 4:28:54 time: 0.2768 data_time: 0.0076 memory: 5828 grad_norm: 4.8151 loss: 1.5921 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5921 2023/06/05 16:40:09 - mmengine - INFO - Epoch(train) [127][1080/2569] lr: 4.0000e-03 eta: 4:28:49 time: 0.2753 data_time: 0.0073 memory: 5828 grad_norm: 4.8955 loss: 1.6658 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6658 2023/06/05 16:40:15 - mmengine - INFO - Epoch(train) [127][1100/2569] lr: 4.0000e-03 eta: 4:28:44 time: 0.2852 data_time: 0.0071 memory: 5828 grad_norm: 4.9146 loss: 2.0095 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.0095 2023/06/05 16:40:20 - mmengine - INFO - Epoch(train) [127][1120/2569] lr: 4.0000e-03 eta: 4:28:38 time: 0.2642 data_time: 0.0071 memory: 5828 grad_norm: 4.9086 loss: 1.8674 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8674 2023/06/05 16:40:26 - mmengine - INFO - Epoch(train) [127][1140/2569] lr: 4.0000e-03 eta: 4:28:33 time: 0.2751 data_time: 0.0072 memory: 5828 grad_norm: 4.9281 loss: 1.7852 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7852 2023/06/05 16:40:31 - mmengine - INFO - Epoch(train) [127][1160/2569] lr: 4.0000e-03 eta: 4:28:28 time: 0.2675 data_time: 0.0071 memory: 5828 grad_norm: 4.9376 loss: 1.6998 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6998 2023/06/05 16:40:36 - mmengine - INFO - Epoch(train) [127][1180/2569] lr: 4.0000e-03 eta: 4:28:22 time: 0.2606 data_time: 0.0074 memory: 5828 grad_norm: 5.0523 loss: 1.9208 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9208 2023/06/05 16:40:42 - mmengine - INFO - Epoch(train) [127][1200/2569] lr: 4.0000e-03 eta: 4:28:17 time: 0.2634 data_time: 0.0073 memory: 5828 grad_norm: 4.9967 loss: 1.6589 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6589 2023/06/05 16:40:47 - mmengine - INFO - Epoch(train) [127][1220/2569] lr: 4.0000e-03 eta: 4:28:12 time: 0.2696 data_time: 0.0076 memory: 5828 grad_norm: 4.9973 loss: 1.7127 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7127 2023/06/05 16:40:52 - mmengine - INFO - Epoch(train) [127][1240/2569] lr: 4.0000e-03 eta: 4:28:07 time: 0.2742 data_time: 0.0071 memory: 5828 grad_norm: 4.9007 loss: 1.4252 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4252 2023/06/05 16:40:58 - mmengine - INFO - Epoch(train) [127][1260/2569] lr: 4.0000e-03 eta: 4:28:01 time: 0.2624 data_time: 0.0077 memory: 5828 grad_norm: 4.9545 loss: 1.8197 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8197 2023/06/05 16:41:03 - mmengine - INFO - Epoch(train) [127][1280/2569] lr: 4.0000e-03 eta: 4:27:56 time: 0.2673 data_time: 0.0074 memory: 5828 grad_norm: 5.0235 loss: 1.8921 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8921 2023/06/05 16:41:08 - mmengine - INFO - Epoch(train) [127][1300/2569] lr: 4.0000e-03 eta: 4:27:51 time: 0.2692 data_time: 0.0074 memory: 5828 grad_norm: 4.8631 loss: 1.7970 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7970 2023/06/05 16:41:10 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:41:14 - mmengine - INFO - Epoch(train) [127][1320/2569] lr: 4.0000e-03 eta: 4:27:45 time: 0.2776 data_time: 0.0075 memory: 5828 grad_norm: 4.9550 loss: 2.0240 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0240 2023/06/05 16:41:19 - mmengine - INFO - Epoch(train) [127][1340/2569] lr: 4.0000e-03 eta: 4:27:40 time: 0.2619 data_time: 0.0074 memory: 5828 grad_norm: 4.9777 loss: 1.9449 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9449 2023/06/05 16:41:25 - mmengine - INFO - Epoch(train) [127][1360/2569] lr: 4.0000e-03 eta: 4:27:35 time: 0.2783 data_time: 0.0075 memory: 5828 grad_norm: 4.9810 loss: 2.0460 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0460 2023/06/05 16:41:30 - mmengine - INFO - Epoch(train) [127][1380/2569] lr: 4.0000e-03 eta: 4:27:29 time: 0.2614 data_time: 0.0079 memory: 5828 grad_norm: 4.9977 loss: 1.7857 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7857 2023/06/05 16:41:36 - mmengine - INFO - Epoch(train) [127][1400/2569] lr: 4.0000e-03 eta: 4:27:24 time: 0.2748 data_time: 0.0076 memory: 5828 grad_norm: 4.9812 loss: 2.0600 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0600 2023/06/05 16:41:41 - mmengine - INFO - Epoch(train) [127][1420/2569] lr: 4.0000e-03 eta: 4:27:19 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 4.8586 loss: 1.6181 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6181 2023/06/05 16:41:46 - mmengine - INFO - Epoch(train) [127][1440/2569] lr: 4.0000e-03 eta: 4:27:13 time: 0.2738 data_time: 0.0072 memory: 5828 grad_norm: 4.9821 loss: 2.2153 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2153 2023/06/05 16:41:52 - mmengine - INFO - Epoch(train) [127][1460/2569] lr: 4.0000e-03 eta: 4:27:08 time: 0.2626 data_time: 0.0073 memory: 5828 grad_norm: 4.9957 loss: 1.9227 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9227 2023/06/05 16:41:57 - mmengine - INFO - Epoch(train) [127][1480/2569] lr: 4.0000e-03 eta: 4:27:03 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 4.8372 loss: 1.5323 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5323 2023/06/05 16:42:03 - mmengine - INFO - Epoch(train) [127][1500/2569] lr: 4.0000e-03 eta: 4:26:57 time: 0.2728 data_time: 0.0071 memory: 5828 grad_norm: 4.9637 loss: 1.7853 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7853 2023/06/05 16:42:08 - mmengine - INFO - Epoch(train) [127][1520/2569] lr: 4.0000e-03 eta: 4:26:52 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 5.0025 loss: 1.9439 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9439 2023/06/05 16:42:13 - mmengine - INFO - Epoch(train) [127][1540/2569] lr: 4.0000e-03 eta: 4:26:47 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 5.0665 loss: 1.7177 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7177 2023/06/05 16:42:19 - mmengine - INFO - Epoch(train) [127][1560/2569] lr: 4.0000e-03 eta: 4:26:41 time: 0.2689 data_time: 0.0069 memory: 5828 grad_norm: 5.0212 loss: 1.7377 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7377 2023/06/05 16:42:24 - mmengine - INFO - Epoch(train) [127][1580/2569] lr: 4.0000e-03 eta: 4:26:36 time: 0.2678 data_time: 0.0072 memory: 5828 grad_norm: 4.9923 loss: 1.7805 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7805 2023/06/05 16:42:29 - mmengine - INFO - Epoch(train) [127][1600/2569] lr: 4.0000e-03 eta: 4:26:31 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 4.9809 loss: 1.8499 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8499 2023/06/05 16:42:35 - mmengine - INFO - Epoch(train) [127][1620/2569] lr: 4.0000e-03 eta: 4:26:26 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 4.9622 loss: 1.8467 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8467 2023/06/05 16:42:40 - mmengine - INFO - Epoch(train) [127][1640/2569] lr: 4.0000e-03 eta: 4:26:20 time: 0.2620 data_time: 0.0074 memory: 5828 grad_norm: 4.9977 loss: 1.8502 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8502 2023/06/05 16:42:45 - mmengine - INFO - Epoch(train) [127][1660/2569] lr: 4.0000e-03 eta: 4:26:15 time: 0.2669 data_time: 0.0070 memory: 5828 grad_norm: 4.9929 loss: 1.6404 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6404 2023/06/05 16:42:51 - mmengine - INFO - Epoch(train) [127][1680/2569] lr: 4.0000e-03 eta: 4:26:10 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 4.9408 loss: 1.7225 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7225 2023/06/05 16:42:56 - mmengine - INFO - Epoch(train) [127][1700/2569] lr: 4.0000e-03 eta: 4:26:04 time: 0.2682 data_time: 0.0070 memory: 5828 grad_norm: 4.9790 loss: 1.6023 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6023 2023/06/05 16:43:01 - mmengine - INFO - Epoch(train) [127][1720/2569] lr: 4.0000e-03 eta: 4:25:59 time: 0.2704 data_time: 0.0072 memory: 5828 grad_norm: 4.9917 loss: 2.0052 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0052 2023/06/05 16:43:07 - mmengine - INFO - Epoch(train) [127][1740/2569] lr: 4.0000e-03 eta: 4:25:54 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 4.9864 loss: 1.9237 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9237 2023/06/05 16:43:12 - mmengine - INFO - Epoch(train) [127][1760/2569] lr: 4.0000e-03 eta: 4:25:48 time: 0.2683 data_time: 0.0070 memory: 5828 grad_norm: 4.9528 loss: 1.8349 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8349 2023/06/05 16:43:17 - mmengine - INFO - Epoch(train) [127][1780/2569] lr: 4.0000e-03 eta: 4:25:43 time: 0.2674 data_time: 0.0076 memory: 5828 grad_norm: 4.8541 loss: 1.6645 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6645 2023/06/05 16:43:23 - mmengine - INFO - Epoch(train) [127][1800/2569] lr: 4.0000e-03 eta: 4:25:38 time: 0.2760 data_time: 0.0073 memory: 5828 grad_norm: 4.9924 loss: 1.5938 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5938 2023/06/05 16:43:28 - mmengine - INFO - Epoch(train) [127][1820/2569] lr: 4.0000e-03 eta: 4:25:32 time: 0.2634 data_time: 0.0073 memory: 5828 grad_norm: 4.8753 loss: 2.0187 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0187 2023/06/05 16:43:34 - mmengine - INFO - Epoch(train) [127][1840/2569] lr: 4.0000e-03 eta: 4:25:27 time: 0.2734 data_time: 0.0075 memory: 5828 grad_norm: 4.8752 loss: 1.9301 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9301 2023/06/05 16:43:39 - mmengine - INFO - Epoch(train) [127][1860/2569] lr: 4.0000e-03 eta: 4:25:22 time: 0.2619 data_time: 0.0078 memory: 5828 grad_norm: 4.9935 loss: 1.6991 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6991 2023/06/05 16:43:44 - mmengine - INFO - Epoch(train) [127][1880/2569] lr: 4.0000e-03 eta: 4:25:16 time: 0.2630 data_time: 0.0073 memory: 5828 grad_norm: 4.8576 loss: 1.8570 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8570 2023/06/05 16:43:50 - mmengine - INFO - Epoch(train) [127][1900/2569] lr: 4.0000e-03 eta: 4:25:11 time: 0.2645 data_time: 0.0075 memory: 5828 grad_norm: 4.8852 loss: 1.7812 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7812 2023/06/05 16:43:55 - mmengine - INFO - Epoch(train) [127][1920/2569] lr: 4.0000e-03 eta: 4:25:06 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 4.8559 loss: 1.6685 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6685 2023/06/05 16:44:00 - mmengine - INFO - Epoch(train) [127][1940/2569] lr: 4.0000e-03 eta: 4:25:00 time: 0.2694 data_time: 0.0070 memory: 5828 grad_norm: 4.9394 loss: 1.8262 top1_acc: 0.0000 top5_acc: 0.6250 loss_cls: 1.8262 2023/06/05 16:44:06 - mmengine - INFO - Epoch(train) [127][1960/2569] lr: 4.0000e-03 eta: 4:24:55 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 4.9277 loss: 1.7356 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7356 2023/06/05 16:44:11 - mmengine - INFO - Epoch(train) [127][1980/2569] lr: 4.0000e-03 eta: 4:24:50 time: 0.2706 data_time: 0.0071 memory: 5828 grad_norm: 4.8985 loss: 1.8627 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8627 2023/06/05 16:44:16 - mmengine - INFO - Epoch(train) [127][2000/2569] lr: 4.0000e-03 eta: 4:24:44 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 4.9545 loss: 1.8884 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8884 2023/06/05 16:44:22 - mmengine - INFO - Epoch(train) [127][2020/2569] lr: 4.0000e-03 eta: 4:24:39 time: 0.2675 data_time: 0.0070 memory: 5828 grad_norm: 4.9040 loss: 1.7598 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.7598 2023/06/05 16:44:27 - mmengine - INFO - Epoch(train) [127][2040/2569] lr: 4.0000e-03 eta: 4:24:34 time: 0.2662 data_time: 0.0070 memory: 5828 grad_norm: 4.9601 loss: 1.9603 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9603 2023/06/05 16:44:32 - mmengine - INFO - Epoch(train) [127][2060/2569] lr: 4.0000e-03 eta: 4:24:28 time: 0.2655 data_time: 0.0069 memory: 5828 grad_norm: 4.8806 loss: 1.8004 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8004 2023/06/05 16:44:38 - mmengine - INFO - Epoch(train) [127][2080/2569] lr: 4.0000e-03 eta: 4:24:23 time: 0.2707 data_time: 0.0069 memory: 5828 grad_norm: 4.8307 loss: 1.8195 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8195 2023/06/05 16:44:43 - mmengine - INFO - Epoch(train) [127][2100/2569] lr: 4.0000e-03 eta: 4:24:18 time: 0.2632 data_time: 0.0067 memory: 5828 grad_norm: 4.8523 loss: 1.6447 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6447 2023/06/05 16:44:48 - mmengine - INFO - Epoch(train) [127][2120/2569] lr: 4.0000e-03 eta: 4:24:12 time: 0.2748 data_time: 0.0072 memory: 5828 grad_norm: 4.9441 loss: 1.8188 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8188 2023/06/05 16:44:54 - mmengine - INFO - Epoch(train) [127][2140/2569] lr: 4.0000e-03 eta: 4:24:07 time: 0.2643 data_time: 0.0077 memory: 5828 grad_norm: 4.8787 loss: 1.7650 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7650 2023/06/05 16:44:59 - mmengine - INFO - Epoch(train) [127][2160/2569] lr: 4.0000e-03 eta: 4:24:02 time: 0.2705 data_time: 0.0074 memory: 5828 grad_norm: 4.8827 loss: 2.1282 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1282 2023/06/05 16:45:05 - mmengine - INFO - Epoch(train) [127][2180/2569] lr: 4.0000e-03 eta: 4:23:56 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 4.9647 loss: 1.5799 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5799 2023/06/05 16:45:10 - mmengine - INFO - Epoch(train) [127][2200/2569] lr: 4.0000e-03 eta: 4:23:51 time: 0.2662 data_time: 0.0075 memory: 5828 grad_norm: 5.0539 loss: 1.6855 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.6855 2023/06/05 16:45:15 - mmengine - INFO - Epoch(train) [127][2220/2569] lr: 4.0000e-03 eta: 4:23:46 time: 0.2617 data_time: 0.0075 memory: 5828 grad_norm: 4.9779 loss: 1.6766 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6766 2023/06/05 16:45:21 - mmengine - INFO - Epoch(train) [127][2240/2569] lr: 4.0000e-03 eta: 4:23:41 time: 0.2703 data_time: 0.0073 memory: 5828 grad_norm: 4.9616 loss: 1.9594 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9594 2023/06/05 16:45:26 - mmengine - INFO - Epoch(train) [127][2260/2569] lr: 4.0000e-03 eta: 4:23:35 time: 0.2670 data_time: 0.0076 memory: 5828 grad_norm: 5.0100 loss: 1.6420 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6420 2023/06/05 16:45:31 - mmengine - INFO - Epoch(train) [127][2280/2569] lr: 4.0000e-03 eta: 4:23:30 time: 0.2712 data_time: 0.0071 memory: 5828 grad_norm: 4.8704 loss: 1.6330 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6330 2023/06/05 16:45:37 - mmengine - INFO - Epoch(train) [127][2300/2569] lr: 4.0000e-03 eta: 4:23:25 time: 0.2614 data_time: 0.0076 memory: 5828 grad_norm: 4.9603 loss: 1.8430 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8430 2023/06/05 16:45:38 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:45:42 - mmengine - INFO - Epoch(train) [127][2320/2569] lr: 4.0000e-03 eta: 4:23:19 time: 0.2669 data_time: 0.0071 memory: 5828 grad_norm: 4.9117 loss: 2.0594 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0594 2023/06/05 16:45:47 - mmengine - INFO - Epoch(train) [127][2340/2569] lr: 4.0000e-03 eta: 4:23:14 time: 0.2711 data_time: 0.0075 memory: 5828 grad_norm: 5.0052 loss: 1.8696 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8696 2023/06/05 16:45:53 - mmengine - INFO - Epoch(train) [127][2360/2569] lr: 4.0000e-03 eta: 4:23:09 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 4.9002 loss: 2.0183 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0183 2023/06/05 16:45:58 - mmengine - INFO - Epoch(train) [127][2380/2569] lr: 4.0000e-03 eta: 4:23:03 time: 0.2696 data_time: 0.0070 memory: 5828 grad_norm: 4.9619 loss: 2.0036 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0036 2023/06/05 16:46:03 - mmengine - INFO - Epoch(train) [127][2400/2569] lr: 4.0000e-03 eta: 4:22:58 time: 0.2678 data_time: 0.0073 memory: 5828 grad_norm: 4.9729 loss: 1.8815 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8815 2023/06/05 16:46:09 - mmengine - INFO - Epoch(train) [127][2420/2569] lr: 4.0000e-03 eta: 4:22:53 time: 0.2660 data_time: 0.0070 memory: 5828 grad_norm: 4.9123 loss: 1.8486 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8486 2023/06/05 16:46:14 - mmengine - INFO - Epoch(train) [127][2440/2569] lr: 4.0000e-03 eta: 4:22:47 time: 0.2692 data_time: 0.0071 memory: 5828 grad_norm: 5.0294 loss: 1.6653 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6653 2023/06/05 16:46:19 - mmengine - INFO - Epoch(train) [127][2460/2569] lr: 4.0000e-03 eta: 4:22:42 time: 0.2630 data_time: 0.0071 memory: 5828 grad_norm: 5.0126 loss: 1.7056 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7056 2023/06/05 16:46:25 - mmengine - INFO - Epoch(train) [127][2480/2569] lr: 4.0000e-03 eta: 4:22:37 time: 0.2708 data_time: 0.0071 memory: 5828 grad_norm: 4.9398 loss: 2.0246 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0246 2023/06/05 16:46:30 - mmengine - INFO - Epoch(train) [127][2500/2569] lr: 4.0000e-03 eta: 4:22:31 time: 0.2705 data_time: 0.0074 memory: 5828 grad_norm: 4.9571 loss: 2.1116 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1116 2023/06/05 16:46:36 - mmengine - INFO - Epoch(train) [127][2520/2569] lr: 4.0000e-03 eta: 4:22:26 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 4.9494 loss: 1.6480 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6480 2023/06/05 16:46:41 - mmengine - INFO - Epoch(train) [127][2540/2569] lr: 4.0000e-03 eta: 4:22:21 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 4.9939 loss: 1.9087 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9087 2023/06/05 16:46:46 - mmengine - INFO - Epoch(train) [127][2560/2569] lr: 4.0000e-03 eta: 4:22:15 time: 0.2644 data_time: 0.0077 memory: 5828 grad_norm: 4.8410 loss: 1.7054 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7054 2023/06/05 16:46:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:46:49 - mmengine - INFO - Epoch(train) [127][2569/2569] lr: 4.0000e-03 eta: 4:22:13 time: 0.2588 data_time: 0.0071 memory: 5828 grad_norm: 4.8968 loss: 1.8537 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8537 2023/06/05 16:46:55 - mmengine - INFO - Epoch(train) [128][ 20/2569] lr: 4.0000e-03 eta: 4:22:08 time: 0.3397 data_time: 0.0614 memory: 5828 grad_norm: 4.8772 loss: 1.8173 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8173 2023/06/05 16:47:01 - mmengine - INFO - Epoch(train) [128][ 40/2569] lr: 4.0000e-03 eta: 4:22:03 time: 0.2801 data_time: 0.0083 memory: 5828 grad_norm: 4.8692 loss: 1.7635 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7635 2023/06/05 16:47:06 - mmengine - INFO - Epoch(train) [128][ 60/2569] lr: 4.0000e-03 eta: 4:21:57 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 4.8945 loss: 1.7587 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7587 2023/06/05 16:47:12 - mmengine - INFO - Epoch(train) [128][ 80/2569] lr: 4.0000e-03 eta: 4:21:52 time: 0.2719 data_time: 0.0070 memory: 5828 grad_norm: 4.9140 loss: 1.7032 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7032 2023/06/05 16:47:17 - mmengine - INFO - Epoch(train) [128][ 100/2569] lr: 4.0000e-03 eta: 4:21:47 time: 0.2708 data_time: 0.0072 memory: 5828 grad_norm: 4.9934 loss: 1.6721 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6721 2023/06/05 16:47:22 - mmengine - INFO - Epoch(train) [128][ 120/2569] lr: 4.0000e-03 eta: 4:21:41 time: 0.2612 data_time: 0.0077 memory: 5828 grad_norm: 4.8655 loss: 1.6557 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6557 2023/06/05 16:47:28 - mmengine - INFO - Epoch(train) [128][ 140/2569] lr: 4.0000e-03 eta: 4:21:36 time: 0.2678 data_time: 0.0071 memory: 5828 grad_norm: 4.8745 loss: 1.9031 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9031 2023/06/05 16:47:33 - mmengine - INFO - Epoch(train) [128][ 160/2569] lr: 4.0000e-03 eta: 4:21:31 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 4.9642 loss: 1.8490 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8490 2023/06/05 16:47:38 - mmengine - INFO - Epoch(train) [128][ 180/2569] lr: 4.0000e-03 eta: 4:21:25 time: 0.2638 data_time: 0.0071 memory: 5828 grad_norm: 4.9672 loss: 1.7564 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7564 2023/06/05 16:47:44 - mmengine - INFO - Epoch(train) [128][ 200/2569] lr: 4.0000e-03 eta: 4:21:20 time: 0.2648 data_time: 0.0073 memory: 5828 grad_norm: 4.8837 loss: 1.5908 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5908 2023/06/05 16:47:49 - mmengine - INFO - Epoch(train) [128][ 220/2569] lr: 4.0000e-03 eta: 4:21:15 time: 0.2632 data_time: 0.0071 memory: 5828 grad_norm: 5.0078 loss: 2.0128 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0128 2023/06/05 16:47:54 - mmengine - INFO - Epoch(train) [128][ 240/2569] lr: 4.0000e-03 eta: 4:21:09 time: 0.2744 data_time: 0.0076 memory: 5828 grad_norm: 4.9015 loss: 1.4218 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4218 2023/06/05 16:48:00 - mmengine - INFO - Epoch(train) [128][ 260/2569] lr: 4.0000e-03 eta: 4:21:04 time: 0.2721 data_time: 0.0072 memory: 5828 grad_norm: 4.8986 loss: 1.9455 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9455 2023/06/05 16:48:05 - mmengine - INFO - Epoch(train) [128][ 280/2569] lr: 4.0000e-03 eta: 4:20:59 time: 0.2728 data_time: 0.0072 memory: 5828 grad_norm: 4.9290 loss: 2.1334 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1334 2023/06/05 16:48:11 - mmengine - INFO - Epoch(train) [128][ 300/2569] lr: 4.0000e-03 eta: 4:20:53 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 5.0360 loss: 1.8084 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8084 2023/06/05 16:48:16 - mmengine - INFO - Epoch(train) [128][ 320/2569] lr: 4.0000e-03 eta: 4:20:48 time: 0.2725 data_time: 0.0071 memory: 5828 grad_norm: 4.8685 loss: 1.7633 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7633 2023/06/05 16:48:21 - mmengine - INFO - Epoch(train) [128][ 340/2569] lr: 4.0000e-03 eta: 4:20:43 time: 0.2612 data_time: 0.0072 memory: 5828 grad_norm: 4.9721 loss: 1.7325 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7325 2023/06/05 16:48:27 - mmengine - INFO - Epoch(train) [128][ 360/2569] lr: 4.0000e-03 eta: 4:20:37 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 4.9586 loss: 1.6735 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6735 2023/06/05 16:48:32 - mmengine - INFO - Epoch(train) [128][ 380/2569] lr: 4.0000e-03 eta: 4:20:32 time: 0.2626 data_time: 0.0076 memory: 5828 grad_norm: 4.9358 loss: 1.6685 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6685 2023/06/05 16:48:37 - mmengine - INFO - Epoch(train) [128][ 400/2569] lr: 4.0000e-03 eta: 4:20:27 time: 0.2688 data_time: 0.0075 memory: 5828 grad_norm: 4.9622 loss: 1.7749 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7749 2023/06/05 16:48:43 - mmengine - INFO - Epoch(train) [128][ 420/2569] lr: 4.0000e-03 eta: 4:20:21 time: 0.2619 data_time: 0.0072 memory: 5828 grad_norm: 4.9405 loss: 1.7649 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7649 2023/06/05 16:48:48 - mmengine - INFO - Epoch(train) [128][ 440/2569] lr: 4.0000e-03 eta: 4:20:16 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 4.9861 loss: 1.7402 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7402 2023/06/05 16:48:53 - mmengine - INFO - Epoch(train) [128][ 460/2569] lr: 4.0000e-03 eta: 4:20:11 time: 0.2654 data_time: 0.0073 memory: 5828 grad_norm: 4.9632 loss: 1.8950 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8950 2023/06/05 16:48:59 - mmengine - INFO - Epoch(train) [128][ 480/2569] lr: 4.0000e-03 eta: 4:20:06 time: 0.2702 data_time: 0.0072 memory: 5828 grad_norm: 4.9780 loss: 1.6448 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.6448 2023/06/05 16:49:04 - mmengine - INFO - Epoch(train) [128][ 500/2569] lr: 4.0000e-03 eta: 4:20:00 time: 0.2738 data_time: 0.0149 memory: 5828 grad_norm: 4.9243 loss: 1.9577 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9577 2023/06/05 16:49:10 - mmengine - INFO - Epoch(train) [128][ 520/2569] lr: 4.0000e-03 eta: 4:19:55 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 4.9629 loss: 1.6119 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6119 2023/06/05 16:49:15 - mmengine - INFO - Epoch(train) [128][ 540/2569] lr: 4.0000e-03 eta: 4:19:50 time: 0.2717 data_time: 0.0074 memory: 5828 grad_norm: 4.8613 loss: 2.0118 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0118 2023/06/05 16:49:20 - mmengine - INFO - Epoch(train) [128][ 560/2569] lr: 4.0000e-03 eta: 4:19:44 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 5.0425 loss: 1.8990 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8990 2023/06/05 16:49:26 - mmengine - INFO - Epoch(train) [128][ 580/2569] lr: 4.0000e-03 eta: 4:19:39 time: 0.2678 data_time: 0.0074 memory: 5828 grad_norm: 5.0494 loss: 1.8962 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8962 2023/06/05 16:49:31 - mmengine - INFO - Epoch(train) [128][ 600/2569] lr: 4.0000e-03 eta: 4:19:34 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 4.9868 loss: 1.8025 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8025 2023/06/05 16:49:37 - mmengine - INFO - Epoch(train) [128][ 620/2569] lr: 4.0000e-03 eta: 4:19:28 time: 0.2730 data_time: 0.0073 memory: 5828 grad_norm: 5.0608 loss: 1.6124 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6124 2023/06/05 16:49:42 - mmengine - INFO - Epoch(train) [128][ 640/2569] lr: 4.0000e-03 eta: 4:19:23 time: 0.2706 data_time: 0.0073 memory: 5828 grad_norm: 5.0177 loss: 2.0347 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0347 2023/06/05 16:49:47 - mmengine - INFO - Epoch(train) [128][ 660/2569] lr: 4.0000e-03 eta: 4:19:18 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 5.0180 loss: 1.9254 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9254 2023/06/05 16:49:53 - mmengine - INFO - Epoch(train) [128][ 680/2569] lr: 4.0000e-03 eta: 4:19:12 time: 0.2725 data_time: 0.0072 memory: 5828 grad_norm: 4.9707 loss: 1.8834 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8834 2023/06/05 16:49:58 - mmengine - INFO - Epoch(train) [128][ 700/2569] lr: 4.0000e-03 eta: 4:19:07 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 4.9657 loss: 1.9600 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9600 2023/06/05 16:50:03 - mmengine - INFO - Epoch(train) [128][ 720/2569] lr: 4.0000e-03 eta: 4:19:02 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 4.9148 loss: 1.9587 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9587 2023/06/05 16:50:08 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:50:09 - mmengine - INFO - Epoch(train) [128][ 740/2569] lr: 4.0000e-03 eta: 4:18:56 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 5.0291 loss: 1.7371 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7371 2023/06/05 16:50:14 - mmengine - INFO - Epoch(train) [128][ 760/2569] lr: 4.0000e-03 eta: 4:18:51 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 4.9945 loss: 1.8938 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8938 2023/06/05 16:50:20 - mmengine - INFO - Epoch(train) [128][ 780/2569] lr: 4.0000e-03 eta: 4:18:46 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 4.9414 loss: 1.8647 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8647 2023/06/05 16:50:25 - mmengine - INFO - Epoch(train) [128][ 800/2569] lr: 4.0000e-03 eta: 4:18:40 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 4.9731 loss: 1.6824 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6824 2023/06/05 16:50:30 - mmengine - INFO - Epoch(train) [128][ 820/2569] lr: 4.0000e-03 eta: 4:18:35 time: 0.2624 data_time: 0.0071 memory: 5828 grad_norm: 4.9275 loss: 1.9528 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9528 2023/06/05 16:50:35 - mmengine - INFO - Epoch(train) [128][ 840/2569] lr: 4.0000e-03 eta: 4:18:30 time: 0.2637 data_time: 0.0076 memory: 5828 grad_norm: 4.9594 loss: 1.8830 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8830 2023/06/05 16:50:41 - mmengine - INFO - Epoch(train) [128][ 860/2569] lr: 4.0000e-03 eta: 4:18:24 time: 0.2630 data_time: 0.0073 memory: 5828 grad_norm: 4.9121 loss: 1.6654 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6654 2023/06/05 16:50:46 - mmengine - INFO - Epoch(train) [128][ 880/2569] lr: 4.0000e-03 eta: 4:18:19 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 5.1450 loss: 1.6633 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6633 2023/06/05 16:50:51 - mmengine - INFO - Epoch(train) [128][ 900/2569] lr: 4.0000e-03 eta: 4:18:14 time: 0.2669 data_time: 0.0072 memory: 5828 grad_norm: 5.0375 loss: 2.1442 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1442 2023/06/05 16:50:57 - mmengine - INFO - Epoch(train) [128][ 920/2569] lr: 4.0000e-03 eta: 4:18:08 time: 0.2626 data_time: 0.0077 memory: 5828 grad_norm: 4.9144 loss: 1.6147 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6147 2023/06/05 16:51:02 - mmengine - INFO - Epoch(train) [128][ 940/2569] lr: 4.0000e-03 eta: 4:18:03 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 4.9702 loss: 1.7811 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7811 2023/06/05 16:51:07 - mmengine - INFO - Epoch(train) [128][ 960/2569] lr: 4.0000e-03 eta: 4:17:58 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 4.8827 loss: 1.7883 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7883 2023/06/05 16:51:13 - mmengine - INFO - Epoch(train) [128][ 980/2569] lr: 4.0000e-03 eta: 4:17:52 time: 0.2715 data_time: 0.0072 memory: 5828 grad_norm: 4.9240 loss: 1.7741 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7741 2023/06/05 16:51:18 - mmengine - INFO - Epoch(train) [128][1000/2569] lr: 4.0000e-03 eta: 4:17:47 time: 0.2658 data_time: 0.0073 memory: 5828 grad_norm: 4.9126 loss: 1.6610 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6610 2023/06/05 16:51:23 - mmengine - INFO - Epoch(train) [128][1020/2569] lr: 4.0000e-03 eta: 4:17:42 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 4.9980 loss: 1.4202 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.4202 2023/06/05 16:51:29 - mmengine - INFO - Epoch(train) [128][1040/2569] lr: 4.0000e-03 eta: 4:17:36 time: 0.2682 data_time: 0.0075 memory: 5828 grad_norm: 5.0774 loss: 1.8694 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8694 2023/06/05 16:51:34 - mmengine - INFO - Epoch(train) [128][1060/2569] lr: 4.0000e-03 eta: 4:17:31 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 5.0681 loss: 1.8721 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8721 2023/06/05 16:51:40 - mmengine - INFO - Epoch(train) [128][1080/2569] lr: 4.0000e-03 eta: 4:17:26 time: 0.2736 data_time: 0.0070 memory: 5828 grad_norm: 5.0261 loss: 1.7517 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7517 2023/06/05 16:51:45 - mmengine - INFO - Epoch(train) [128][1100/2569] lr: 4.0000e-03 eta: 4:17:21 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 4.9893 loss: 1.3511 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3511 2023/06/05 16:51:50 - mmengine - INFO - Epoch(train) [128][1120/2569] lr: 4.0000e-03 eta: 4:17:15 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 4.9678 loss: 1.5681 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5681 2023/06/05 16:51:56 - mmengine - INFO - Epoch(train) [128][1140/2569] lr: 4.0000e-03 eta: 4:17:10 time: 0.2758 data_time: 0.0079 memory: 5828 grad_norm: 5.0588 loss: 1.7253 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7253 2023/06/05 16:52:01 - mmengine - INFO - Epoch(train) [128][1160/2569] lr: 4.0000e-03 eta: 4:17:05 time: 0.2629 data_time: 0.0075 memory: 5828 grad_norm: 4.9420 loss: 1.6704 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6704 2023/06/05 16:52:06 - mmengine - INFO - Epoch(train) [128][1180/2569] lr: 4.0000e-03 eta: 4:16:59 time: 0.2729 data_time: 0.0073 memory: 5828 grad_norm: 4.8999 loss: 1.8167 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.8167 2023/06/05 16:52:12 - mmengine - INFO - Epoch(train) [128][1200/2569] lr: 4.0000e-03 eta: 4:16:54 time: 0.2638 data_time: 0.0070 memory: 5828 grad_norm: 5.0372 loss: 1.5238 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5238 2023/06/05 16:52:17 - mmengine - INFO - Epoch(train) [128][1220/2569] lr: 4.0000e-03 eta: 4:16:49 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 4.9785 loss: 1.7221 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7221 2023/06/05 16:52:22 - mmengine - INFO - Epoch(train) [128][1240/2569] lr: 4.0000e-03 eta: 4:16:43 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 4.8853 loss: 1.7449 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7449 2023/06/05 16:52:28 - mmengine - INFO - Epoch(train) [128][1260/2569] lr: 4.0000e-03 eta: 4:16:38 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 5.0000 loss: 1.9109 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9109 2023/06/05 16:52:33 - mmengine - INFO - Epoch(train) [128][1280/2569] lr: 4.0000e-03 eta: 4:16:33 time: 0.2754 data_time: 0.0073 memory: 5828 grad_norm: 4.9822 loss: 1.8373 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8373 2023/06/05 16:52:38 - mmengine - INFO - Epoch(train) [128][1300/2569] lr: 4.0000e-03 eta: 4:16:27 time: 0.2718 data_time: 0.0074 memory: 5828 grad_norm: 4.9718 loss: 2.0052 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0052 2023/06/05 16:52:44 - mmengine - INFO - Epoch(train) [128][1320/2569] lr: 4.0000e-03 eta: 4:16:22 time: 0.2735 data_time: 0.0078 memory: 5828 grad_norm: 4.9932 loss: 1.5133 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5133 2023/06/05 16:52:49 - mmengine - INFO - Epoch(train) [128][1340/2569] lr: 4.0000e-03 eta: 4:16:17 time: 0.2767 data_time: 0.0075 memory: 5828 grad_norm: 4.9387 loss: 1.6459 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6459 2023/06/05 16:52:55 - mmengine - INFO - Epoch(train) [128][1360/2569] lr: 4.0000e-03 eta: 4:16:11 time: 0.2686 data_time: 0.0073 memory: 5828 grad_norm: 5.1413 loss: 1.8071 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8071 2023/06/05 16:53:00 - mmengine - INFO - Epoch(train) [128][1380/2569] lr: 4.0000e-03 eta: 4:16:06 time: 0.2691 data_time: 0.0071 memory: 5828 grad_norm: 4.9696 loss: 1.9140 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9140 2023/06/05 16:53:06 - mmengine - INFO - Epoch(train) [128][1400/2569] lr: 4.0000e-03 eta: 4:16:01 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 4.9791 loss: 1.9207 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9207 2023/06/05 16:53:11 - mmengine - INFO - Epoch(train) [128][1420/2569] lr: 4.0000e-03 eta: 4:15:55 time: 0.2670 data_time: 0.0070 memory: 5828 grad_norm: 4.8608 loss: 1.7265 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7265 2023/06/05 16:53:16 - mmengine - INFO - Epoch(train) [128][1440/2569] lr: 4.0000e-03 eta: 4:15:50 time: 0.2685 data_time: 0.0071 memory: 5828 grad_norm: 4.8368 loss: 1.5564 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5564 2023/06/05 16:53:22 - mmengine - INFO - Epoch(train) [128][1460/2569] lr: 4.0000e-03 eta: 4:15:45 time: 0.2657 data_time: 0.0071 memory: 5828 grad_norm: 4.9063 loss: 1.8222 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8222 2023/06/05 16:53:27 - mmengine - INFO - Epoch(train) [128][1480/2569] lr: 4.0000e-03 eta: 4:15:39 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 5.0555 loss: 1.9725 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9725 2023/06/05 16:53:32 - mmengine - INFO - Epoch(train) [128][1500/2569] lr: 4.0000e-03 eta: 4:15:34 time: 0.2757 data_time: 0.0071 memory: 5828 grad_norm: 5.0398 loss: 1.7499 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7499 2023/06/05 16:53:38 - mmengine - INFO - Epoch(train) [128][1520/2569] lr: 4.0000e-03 eta: 4:15:29 time: 0.2610 data_time: 0.0074 memory: 5828 grad_norm: 4.9702 loss: 2.1054 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1054 2023/06/05 16:53:43 - mmengine - INFO - Epoch(train) [128][1540/2569] lr: 4.0000e-03 eta: 4:15:24 time: 0.2735 data_time: 0.0073 memory: 5828 grad_norm: 5.0447 loss: 1.6939 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6939 2023/06/05 16:53:49 - mmengine - INFO - Epoch(train) [128][1560/2569] lr: 4.0000e-03 eta: 4:15:18 time: 0.2716 data_time: 0.0070 memory: 5828 grad_norm: 4.9481 loss: 1.8756 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8756 2023/06/05 16:53:54 - mmengine - INFO - Epoch(train) [128][1580/2569] lr: 4.0000e-03 eta: 4:15:13 time: 0.2707 data_time: 0.0072 memory: 5828 grad_norm: 4.9814 loss: 1.8881 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8881 2023/06/05 16:54:00 - mmengine - INFO - Epoch(train) [128][1600/2569] lr: 4.0000e-03 eta: 4:15:08 time: 0.2752 data_time: 0.0071 memory: 5828 grad_norm: 4.9249 loss: 1.9261 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9261 2023/06/05 16:54:05 - mmengine - INFO - Epoch(train) [128][1620/2569] lr: 4.0000e-03 eta: 4:15:02 time: 0.2667 data_time: 0.0070 memory: 5828 grad_norm: 5.0543 loss: 1.6379 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6379 2023/06/05 16:54:10 - mmengine - INFO - Epoch(train) [128][1640/2569] lr: 4.0000e-03 eta: 4:14:57 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 5.0755 loss: 1.6660 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6660 2023/06/05 16:54:15 - mmengine - INFO - Epoch(train) [128][1660/2569] lr: 4.0000e-03 eta: 4:14:52 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 4.9945 loss: 2.1414 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1414 2023/06/05 16:54:21 - mmengine - INFO - Epoch(train) [128][1680/2569] lr: 4.0000e-03 eta: 4:14:46 time: 0.2725 data_time: 0.0074 memory: 5828 grad_norm: 5.0236 loss: 1.7258 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7258 2023/06/05 16:54:26 - mmengine - INFO - Epoch(train) [128][1700/2569] lr: 4.0000e-03 eta: 4:14:41 time: 0.2717 data_time: 0.0070 memory: 5828 grad_norm: 4.9612 loss: 1.9053 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9053 2023/06/05 16:54:32 - mmengine - INFO - Epoch(train) [128][1720/2569] lr: 4.0000e-03 eta: 4:14:36 time: 0.2715 data_time: 0.0070 memory: 5828 grad_norm: 4.9983 loss: 1.8708 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8708 2023/06/05 16:54:36 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:54:37 - mmengine - INFO - Epoch(train) [128][1740/2569] lr: 4.0000e-03 eta: 4:14:30 time: 0.2677 data_time: 0.0075 memory: 5828 grad_norm: 5.1457 loss: 1.9828 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9828 2023/06/05 16:54:43 - mmengine - INFO - Epoch(train) [128][1760/2569] lr: 4.0000e-03 eta: 4:14:25 time: 0.2715 data_time: 0.0076 memory: 5828 grad_norm: 5.1312 loss: 1.7880 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7880 2023/06/05 16:54:48 - mmengine - INFO - Epoch(train) [128][1780/2569] lr: 4.0000e-03 eta: 4:14:20 time: 0.2686 data_time: 0.0069 memory: 5828 grad_norm: 4.9466 loss: 1.7435 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7435 2023/06/05 16:54:53 - mmengine - INFO - Epoch(train) [128][1800/2569] lr: 4.0000e-03 eta: 4:14:14 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 5.1256 loss: 1.8706 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8706 2023/06/05 16:54:59 - mmengine - INFO - Epoch(train) [128][1820/2569] lr: 4.0000e-03 eta: 4:14:09 time: 0.2649 data_time: 0.0071 memory: 5828 grad_norm: 5.0556 loss: 1.4942 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4942 2023/06/05 16:55:04 - mmengine - INFO - Epoch(train) [128][1840/2569] lr: 4.0000e-03 eta: 4:14:04 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 4.9997 loss: 1.9525 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9525 2023/06/05 16:55:09 - mmengine - INFO - Epoch(train) [128][1860/2569] lr: 4.0000e-03 eta: 4:13:58 time: 0.2798 data_time: 0.0070 memory: 5828 grad_norm: 5.0087 loss: 1.7683 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7683 2023/06/05 16:55:15 - mmengine - INFO - Epoch(train) [128][1880/2569] lr: 4.0000e-03 eta: 4:13:53 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 5.1492 loss: 1.8410 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8410 2023/06/05 16:55:20 - mmengine - INFO - Epoch(train) [128][1900/2569] lr: 4.0000e-03 eta: 4:13:48 time: 0.2757 data_time: 0.0070 memory: 5828 grad_norm: 4.9411 loss: 1.6667 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6667 2023/06/05 16:55:26 - mmengine - INFO - Epoch(train) [128][1920/2569] lr: 4.0000e-03 eta: 4:13:42 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 5.0833 loss: 1.6903 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6903 2023/06/05 16:55:31 - mmengine - INFO - Epoch(train) [128][1940/2569] lr: 4.0000e-03 eta: 4:13:37 time: 0.2678 data_time: 0.0072 memory: 5828 grad_norm: 4.9879 loss: 1.8323 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8323 2023/06/05 16:55:36 - mmengine - INFO - Epoch(train) [128][1960/2569] lr: 4.0000e-03 eta: 4:13:32 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 5.0402 loss: 2.0885 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0885 2023/06/05 16:55:42 - mmengine - INFO - Epoch(train) [128][1980/2569] lr: 4.0000e-03 eta: 4:13:27 time: 0.2703 data_time: 0.0072 memory: 5828 grad_norm: 5.0329 loss: 1.8970 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8970 2023/06/05 16:55:47 - mmengine - INFO - Epoch(train) [128][2000/2569] lr: 4.0000e-03 eta: 4:13:21 time: 0.2716 data_time: 0.0070 memory: 5828 grad_norm: 5.1280 loss: 1.8531 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8531 2023/06/05 16:55:52 - mmengine - INFO - Epoch(train) [128][2020/2569] lr: 4.0000e-03 eta: 4:13:16 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 5.0529 loss: 1.4894 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4894 2023/06/05 16:55:58 - mmengine - INFO - Epoch(train) [128][2040/2569] lr: 4.0000e-03 eta: 4:13:11 time: 0.2682 data_time: 0.0072 memory: 5828 grad_norm: 5.0879 loss: 1.7028 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7028 2023/06/05 16:56:03 - mmengine - INFO - Epoch(train) [128][2060/2569] lr: 4.0000e-03 eta: 4:13:05 time: 0.2628 data_time: 0.0070 memory: 5828 grad_norm: 4.9443 loss: 1.9183 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9183 2023/06/05 16:56:08 - mmengine - INFO - Epoch(train) [128][2080/2569] lr: 4.0000e-03 eta: 4:13:00 time: 0.2620 data_time: 0.0074 memory: 5828 grad_norm: 5.0444 loss: 1.8074 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8074 2023/06/05 16:56:14 - mmengine - INFO - Epoch(train) [128][2100/2569] lr: 4.0000e-03 eta: 4:12:55 time: 0.2701 data_time: 0.0069 memory: 5828 grad_norm: 5.0153 loss: 1.9754 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9754 2023/06/05 16:56:19 - mmengine - INFO - Epoch(train) [128][2120/2569] lr: 4.0000e-03 eta: 4:12:49 time: 0.2633 data_time: 0.0070 memory: 5828 grad_norm: 5.0363 loss: 1.7340 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7340 2023/06/05 16:56:24 - mmengine - INFO - Epoch(train) [128][2140/2569] lr: 4.0000e-03 eta: 4:12:44 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 4.9438 loss: 1.6554 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6554 2023/06/05 16:56:30 - mmengine - INFO - Epoch(train) [128][2160/2569] lr: 4.0000e-03 eta: 4:12:39 time: 0.2602 data_time: 0.0073 memory: 5828 grad_norm: 5.0253 loss: 1.6346 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6346 2023/06/05 16:56:35 - mmengine - INFO - Epoch(train) [128][2180/2569] lr: 4.0000e-03 eta: 4:12:33 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 5.1102 loss: 1.8987 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8987 2023/06/05 16:56:40 - mmengine - INFO - Epoch(train) [128][2200/2569] lr: 4.0000e-03 eta: 4:12:28 time: 0.2663 data_time: 0.0072 memory: 5828 grad_norm: 5.0513 loss: 1.8761 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8761 2023/06/05 16:56:46 - mmengine - INFO - Epoch(train) [128][2220/2569] lr: 4.0000e-03 eta: 4:12:23 time: 0.2789 data_time: 0.0072 memory: 5828 grad_norm: 5.0005 loss: 1.7127 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7127 2023/06/05 16:56:51 - mmengine - INFO - Epoch(train) [128][2240/2569] lr: 4.0000e-03 eta: 4:12:17 time: 0.2661 data_time: 0.0070 memory: 5828 grad_norm: 5.0628 loss: 1.5768 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5768 2023/06/05 16:56:56 - mmengine - INFO - Epoch(train) [128][2260/2569] lr: 4.0000e-03 eta: 4:12:12 time: 0.2705 data_time: 0.0071 memory: 5828 grad_norm: 5.0109 loss: 1.6680 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6680 2023/06/05 16:57:02 - mmengine - INFO - Epoch(train) [128][2280/2569] lr: 4.0000e-03 eta: 4:12:07 time: 0.2622 data_time: 0.0074 memory: 5828 grad_norm: 4.9521 loss: 2.1074 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1074 2023/06/05 16:57:07 - mmengine - INFO - Epoch(train) [128][2300/2569] lr: 4.0000e-03 eta: 4:12:01 time: 0.2666 data_time: 0.0071 memory: 5828 grad_norm: 4.8438 loss: 1.5749 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5749 2023/06/05 16:57:12 - mmengine - INFO - Epoch(train) [128][2320/2569] lr: 4.0000e-03 eta: 4:11:56 time: 0.2647 data_time: 0.0072 memory: 5828 grad_norm: 5.1096 loss: 1.8438 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.8438 2023/06/05 16:57:18 - mmengine - INFO - Epoch(train) [128][2340/2569] lr: 4.0000e-03 eta: 4:11:51 time: 0.2618 data_time: 0.0071 memory: 5828 grad_norm: 5.0438 loss: 1.7996 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7996 2023/06/05 16:57:23 - mmengine - INFO - Epoch(train) [128][2360/2569] lr: 4.0000e-03 eta: 4:11:45 time: 0.2636 data_time: 0.0076 memory: 5828 grad_norm: 5.0607 loss: 2.0153 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0153 2023/06/05 16:57:28 - mmengine - INFO - Epoch(train) [128][2380/2569] lr: 4.0000e-03 eta: 4:11:40 time: 0.2623 data_time: 0.0071 memory: 5828 grad_norm: 5.0320 loss: 1.6315 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6315 2023/06/05 16:57:33 - mmengine - INFO - Epoch(train) [128][2400/2569] lr: 4.0000e-03 eta: 4:11:35 time: 0.2634 data_time: 0.0070 memory: 5828 grad_norm: 5.0119 loss: 1.6399 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6399 2023/06/05 16:57:39 - mmengine - INFO - Epoch(train) [128][2420/2569] lr: 4.0000e-03 eta: 4:11:29 time: 0.2640 data_time: 0.0071 memory: 5828 grad_norm: 5.0570 loss: 1.7703 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7703 2023/06/05 16:57:44 - mmengine - INFO - Epoch(train) [128][2440/2569] lr: 4.0000e-03 eta: 4:11:24 time: 0.2648 data_time: 0.0073 memory: 5828 grad_norm: 5.1102 loss: 1.9174 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9174 2023/06/05 16:57:49 - mmengine - INFO - Epoch(train) [128][2460/2569] lr: 4.0000e-03 eta: 4:11:19 time: 0.2648 data_time: 0.0071 memory: 5828 grad_norm: 5.0875 loss: 1.8566 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8566 2023/06/05 16:57:55 - mmengine - INFO - Epoch(train) [128][2480/2569] lr: 4.0000e-03 eta: 4:11:13 time: 0.2698 data_time: 0.0071 memory: 5828 grad_norm: 5.0023 loss: 1.2276 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2276 2023/06/05 16:58:00 - mmengine - INFO - Epoch(train) [128][2500/2569] lr: 4.0000e-03 eta: 4:11:08 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 4.9794 loss: 1.5385 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.5385 2023/06/05 16:58:06 - mmengine - INFO - Epoch(train) [128][2520/2569] lr: 4.0000e-03 eta: 4:11:03 time: 0.2824 data_time: 0.0070 memory: 5828 grad_norm: 5.0841 loss: 1.9283 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9283 2023/06/05 16:58:11 - mmengine - INFO - Epoch(train) [128][2540/2569] lr: 4.0000e-03 eta: 4:10:57 time: 0.2636 data_time: 0.0071 memory: 5828 grad_norm: 5.0047 loss: 1.5535 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5535 2023/06/05 16:58:17 - mmengine - INFO - Epoch(train) [128][2560/2569] lr: 4.0000e-03 eta: 4:10:52 time: 0.2756 data_time: 0.0077 memory: 5828 grad_norm: 5.0034 loss: 1.7729 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7729 2023/06/05 16:58:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:58:19 - mmengine - INFO - Epoch(train) [128][2569/2569] lr: 4.0000e-03 eta: 4:10:50 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 4.9520 loss: 1.8940 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.8940 2023/06/05 16:58:19 - mmengine - INFO - Saving checkpoint at 128 epochs 2023/06/05 16:58:27 - mmengine - INFO - Epoch(train) [129][ 20/2569] lr: 4.0000e-03 eta: 4:10:45 time: 0.3090 data_time: 0.0460 memory: 5828 grad_norm: 4.9002 loss: 1.8401 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8401 2023/06/05 16:58:32 - mmengine - INFO - Epoch(train) [129][ 40/2569] lr: 4.0000e-03 eta: 4:10:39 time: 0.2669 data_time: 0.0075 memory: 5828 grad_norm: 4.9738 loss: 1.8538 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8538 2023/06/05 16:58:38 - mmengine - INFO - Epoch(train) [129][ 60/2569] lr: 4.0000e-03 eta: 4:10:34 time: 0.2703 data_time: 0.0070 memory: 5828 grad_norm: 4.8911 loss: 1.7368 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7368 2023/06/05 16:58:43 - mmengine - INFO - Epoch(train) [129][ 80/2569] lr: 4.0000e-03 eta: 4:10:29 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 4.9855 loss: 1.8977 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8977 2023/06/05 16:58:48 - mmengine - INFO - Epoch(train) [129][ 100/2569] lr: 4.0000e-03 eta: 4:10:23 time: 0.2650 data_time: 0.0074 memory: 5828 grad_norm: 5.0954 loss: 1.5089 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5089 2023/06/05 16:58:54 - mmengine - INFO - Epoch(train) [129][ 120/2569] lr: 4.0000e-03 eta: 4:10:18 time: 0.2715 data_time: 0.0074 memory: 5828 grad_norm: 4.9924 loss: 1.7352 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.7352 2023/06/05 16:58:59 - mmengine - INFO - Epoch(train) [129][ 140/2569] lr: 4.0000e-03 eta: 4:10:13 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 4.9945 loss: 1.7648 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7648 2023/06/05 16:59:05 - mmengine - INFO - Epoch(train) [129][ 160/2569] lr: 4.0000e-03 eta: 4:10:07 time: 0.2701 data_time: 0.0075 memory: 5828 grad_norm: 5.0021 loss: 1.5716 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5716 2023/06/05 16:59:07 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 16:59:10 - mmengine - INFO - Epoch(train) [129][ 180/2569] lr: 4.0000e-03 eta: 4:10:02 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 5.0161 loss: 1.8081 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8081 2023/06/05 16:59:15 - mmengine - INFO - Epoch(train) [129][ 200/2569] lr: 4.0000e-03 eta: 4:09:57 time: 0.2736 data_time: 0.0073 memory: 5828 grad_norm: 5.0349 loss: 1.7433 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7433 2023/06/05 16:59:21 - mmengine - INFO - Epoch(train) [129][ 220/2569] lr: 4.0000e-03 eta: 4:09:51 time: 0.2678 data_time: 0.0073 memory: 5828 grad_norm: 5.1022 loss: 1.7318 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7318 2023/06/05 16:59:26 - mmengine - INFO - Epoch(train) [129][ 240/2569] lr: 4.0000e-03 eta: 4:09:46 time: 0.2660 data_time: 0.0072 memory: 5828 grad_norm: 5.0044 loss: 1.7101 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7101 2023/06/05 16:59:32 - mmengine - INFO - Epoch(train) [129][ 260/2569] lr: 4.0000e-03 eta: 4:09:41 time: 0.2779 data_time: 0.0073 memory: 5828 grad_norm: 5.0346 loss: 1.4972 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4972 2023/06/05 16:59:37 - mmengine - INFO - Epoch(train) [129][ 280/2569] lr: 4.0000e-03 eta: 4:09:35 time: 0.2652 data_time: 0.0071 memory: 5828 grad_norm: 4.9814 loss: 1.6667 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6667 2023/06/05 16:59:42 - mmengine - INFO - Epoch(train) [129][ 300/2569] lr: 4.0000e-03 eta: 4:09:30 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 4.9838 loss: 1.7070 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7070 2023/06/05 16:59:48 - mmengine - INFO - Epoch(train) [129][ 320/2569] lr: 4.0000e-03 eta: 4:09:25 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 4.9549 loss: 1.5209 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5209 2023/06/05 16:59:53 - mmengine - INFO - Epoch(train) [129][ 340/2569] lr: 4.0000e-03 eta: 4:09:19 time: 0.2720 data_time: 0.0073 memory: 5828 grad_norm: 5.0578 loss: 1.7177 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7177 2023/06/05 16:59:58 - mmengine - INFO - Epoch(train) [129][ 360/2569] lr: 4.0000e-03 eta: 4:09:14 time: 0.2709 data_time: 0.0071 memory: 5828 grad_norm: 4.9554 loss: 1.9542 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9542 2023/06/05 17:00:04 - mmengine - INFO - Epoch(train) [129][ 380/2569] lr: 4.0000e-03 eta: 4:09:09 time: 0.2756 data_time: 0.0076 memory: 5828 grad_norm: 4.9555 loss: 1.8922 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8922 2023/06/05 17:00:09 - mmengine - INFO - Epoch(train) [129][ 400/2569] lr: 4.0000e-03 eta: 4:09:03 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 5.0362 loss: 1.7946 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7946 2023/06/05 17:00:15 - mmengine - INFO - Epoch(train) [129][ 420/2569] lr: 4.0000e-03 eta: 4:08:58 time: 0.2642 data_time: 0.0075 memory: 5828 grad_norm: 5.0782 loss: 2.2193 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.2193 2023/06/05 17:00:20 - mmengine - INFO - Epoch(train) [129][ 440/2569] lr: 4.0000e-03 eta: 4:08:53 time: 0.2675 data_time: 0.0070 memory: 5828 grad_norm: 5.1118 loss: 1.7530 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7530 2023/06/05 17:00:25 - mmengine - INFO - Epoch(train) [129][ 460/2569] lr: 4.0000e-03 eta: 4:08:48 time: 0.2639 data_time: 0.0071 memory: 5828 grad_norm: 5.0615 loss: 1.8629 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8629 2023/06/05 17:00:31 - mmengine - INFO - Epoch(train) [129][ 480/2569] lr: 4.0000e-03 eta: 4:08:42 time: 0.2691 data_time: 0.0071 memory: 5828 grad_norm: 4.9856 loss: 1.9791 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9791 2023/06/05 17:00:36 - mmengine - INFO - Epoch(train) [129][ 500/2569] lr: 4.0000e-03 eta: 4:08:37 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 4.9632 loss: 1.7507 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7507 2023/06/05 17:00:41 - mmengine - INFO - Epoch(train) [129][ 520/2569] lr: 4.0000e-03 eta: 4:08:32 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 4.8744 loss: 1.8383 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8383 2023/06/05 17:00:47 - mmengine - INFO - Epoch(train) [129][ 540/2569] lr: 4.0000e-03 eta: 4:08:26 time: 0.2729 data_time: 0.0071 memory: 5828 grad_norm: 4.9196 loss: 1.8037 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8037 2023/06/05 17:00:52 - mmengine - INFO - Epoch(train) [129][ 560/2569] lr: 4.0000e-03 eta: 4:08:21 time: 0.2671 data_time: 0.0071 memory: 5828 grad_norm: 4.9834 loss: 1.8924 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8924 2023/06/05 17:00:58 - mmengine - INFO - Epoch(train) [129][ 580/2569] lr: 4.0000e-03 eta: 4:08:16 time: 0.2787 data_time: 0.0073 memory: 5828 grad_norm: 5.0429 loss: 1.7262 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7262 2023/06/05 17:01:03 - mmengine - INFO - Epoch(train) [129][ 600/2569] lr: 4.0000e-03 eta: 4:08:10 time: 0.2722 data_time: 0.0073 memory: 5828 grad_norm: 5.0393 loss: 1.6545 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6545 2023/06/05 17:01:09 - mmengine - INFO - Epoch(train) [129][ 620/2569] lr: 4.0000e-03 eta: 4:08:05 time: 0.2641 data_time: 0.0069 memory: 5828 grad_norm: 5.1732 loss: 1.6961 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6961 2023/06/05 17:01:14 - mmengine - INFO - Epoch(train) [129][ 640/2569] lr: 4.0000e-03 eta: 4:08:00 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 5.0062 loss: 1.6982 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6982 2023/06/05 17:01:19 - mmengine - INFO - Epoch(train) [129][ 660/2569] lr: 4.0000e-03 eta: 4:07:54 time: 0.2627 data_time: 0.0067 memory: 5828 grad_norm: 5.0354 loss: 1.7181 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7181 2023/06/05 17:01:24 - mmengine - INFO - Epoch(train) [129][ 680/2569] lr: 4.0000e-03 eta: 4:07:49 time: 0.2649 data_time: 0.0070 memory: 5828 grad_norm: 5.0776 loss: 1.6582 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6582 2023/06/05 17:01:30 - mmengine - INFO - Epoch(train) [129][ 700/2569] lr: 4.0000e-03 eta: 4:07:44 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 4.9618 loss: 1.6706 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6706 2023/06/05 17:01:35 - mmengine - INFO - Epoch(train) [129][ 720/2569] lr: 4.0000e-03 eta: 4:07:38 time: 0.2633 data_time: 0.0069 memory: 5828 grad_norm: 5.0371 loss: 1.8248 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8248 2023/06/05 17:01:40 - mmengine - INFO - Epoch(train) [129][ 740/2569] lr: 4.0000e-03 eta: 4:07:33 time: 0.2637 data_time: 0.0071 memory: 5828 grad_norm: 5.1317 loss: 1.7450 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7450 2023/06/05 17:01:46 - mmengine - INFO - Epoch(train) [129][ 760/2569] lr: 4.0000e-03 eta: 4:07:28 time: 0.2640 data_time: 0.0071 memory: 5828 grad_norm: 5.0605 loss: 1.3708 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.3708 2023/06/05 17:01:51 - mmengine - INFO - Epoch(train) [129][ 780/2569] lr: 4.0000e-03 eta: 4:07:22 time: 0.2686 data_time: 0.0070 memory: 5828 grad_norm: 5.0202 loss: 1.6054 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6054 2023/06/05 17:01:56 - mmengine - INFO - Epoch(train) [129][ 800/2569] lr: 4.0000e-03 eta: 4:07:17 time: 0.2642 data_time: 0.0072 memory: 5828 grad_norm: 5.0651 loss: 1.6117 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6117 2023/06/05 17:02:02 - mmengine - INFO - Epoch(train) [129][ 820/2569] lr: 4.0000e-03 eta: 4:07:12 time: 0.2637 data_time: 0.0071 memory: 5828 grad_norm: 4.9894 loss: 1.7123 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7123 2023/06/05 17:02:07 - mmengine - INFO - Epoch(train) [129][ 840/2569] lr: 4.0000e-03 eta: 4:07:06 time: 0.2630 data_time: 0.0072 memory: 5828 grad_norm: 5.0100 loss: 1.8776 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8776 2023/06/05 17:02:12 - mmengine - INFO - Epoch(train) [129][ 860/2569] lr: 4.0000e-03 eta: 4:07:01 time: 0.2733 data_time: 0.0071 memory: 5828 grad_norm: 5.1307 loss: 1.7030 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7030 2023/06/05 17:02:18 - mmengine - INFO - Epoch(train) [129][ 880/2569] lr: 4.0000e-03 eta: 4:06:56 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 4.9527 loss: 1.7298 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7298 2023/06/05 17:02:23 - mmengine - INFO - Epoch(train) [129][ 900/2569] lr: 4.0000e-03 eta: 4:06:50 time: 0.2625 data_time: 0.0072 memory: 5828 grad_norm: 5.0417 loss: 1.6795 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6795 2023/06/05 17:02:28 - mmengine - INFO - Epoch(train) [129][ 920/2569] lr: 4.0000e-03 eta: 4:06:45 time: 0.2740 data_time: 0.0070 memory: 5828 grad_norm: 5.1494 loss: 1.5360 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5360 2023/06/05 17:02:34 - mmengine - INFO - Epoch(train) [129][ 940/2569] lr: 4.0000e-03 eta: 4:06:40 time: 0.2596 data_time: 0.0073 memory: 5828 grad_norm: 5.1207 loss: 1.7452 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7452 2023/06/05 17:02:39 - mmengine - INFO - Epoch(train) [129][ 960/2569] lr: 4.0000e-03 eta: 4:06:34 time: 0.2730 data_time: 0.0079 memory: 5828 grad_norm: 5.0938 loss: 1.9490 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9490 2023/06/05 17:02:44 - mmengine - INFO - Epoch(train) [129][ 980/2569] lr: 4.0000e-03 eta: 4:06:29 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 5.1496 loss: 1.7198 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.7198 2023/06/05 17:02:50 - mmengine - INFO - Epoch(train) [129][1000/2569] lr: 4.0000e-03 eta: 4:06:24 time: 0.2645 data_time: 0.0071 memory: 5828 grad_norm: 4.9510 loss: 1.7139 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7139 2023/06/05 17:02:55 - mmengine - INFO - Epoch(train) [129][1020/2569] lr: 4.0000e-03 eta: 4:06:18 time: 0.2635 data_time: 0.0070 memory: 5828 grad_norm: 4.9658 loss: 1.7029 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7029 2023/06/05 17:03:00 - mmengine - INFO - Epoch(train) [129][1040/2569] lr: 4.0000e-03 eta: 4:06:13 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 4.9952 loss: 1.7376 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7376 2023/06/05 17:03:05 - mmengine - INFO - Epoch(train) [129][1060/2569] lr: 4.0000e-03 eta: 4:06:08 time: 0.2628 data_time: 0.0071 memory: 5828 grad_norm: 5.0621 loss: 1.7275 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7275 2023/06/05 17:03:11 - mmengine - INFO - Epoch(train) [129][1080/2569] lr: 4.0000e-03 eta: 4:06:02 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 4.9931 loss: 1.7487 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7487 2023/06/05 17:03:16 - mmengine - INFO - Epoch(train) [129][1100/2569] lr: 4.0000e-03 eta: 4:05:57 time: 0.2690 data_time: 0.0072 memory: 5828 grad_norm: 5.0888 loss: 1.6867 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6867 2023/06/05 17:03:21 - mmengine - INFO - Epoch(train) [129][1120/2569] lr: 4.0000e-03 eta: 4:05:52 time: 0.2629 data_time: 0.0076 memory: 5828 grad_norm: 5.1160 loss: 1.5489 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5489 2023/06/05 17:03:27 - mmengine - INFO - Epoch(train) [129][1140/2569] lr: 4.0000e-03 eta: 4:05:46 time: 0.2728 data_time: 0.0074 memory: 5828 grad_norm: 5.0127 loss: 2.0026 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0026 2023/06/05 17:03:32 - mmengine - INFO - Epoch(train) [129][1160/2569] lr: 4.0000e-03 eta: 4:05:41 time: 0.2599 data_time: 0.0075 memory: 5828 grad_norm: 5.0780 loss: 1.7030 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7030 2023/06/05 17:03:34 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:03:37 - mmengine - INFO - Epoch(train) [129][1180/2569] lr: 4.0000e-03 eta: 4:05:36 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 5.0229 loss: 1.6167 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6167 2023/06/05 17:03:43 - mmengine - INFO - Epoch(train) [129][1200/2569] lr: 4.0000e-03 eta: 4:05:30 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 5.0351 loss: 1.7222 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7222 2023/06/05 17:03:48 - mmengine - INFO - Epoch(train) [129][1220/2569] lr: 4.0000e-03 eta: 4:05:25 time: 0.2664 data_time: 0.0078 memory: 5828 grad_norm: 5.0960 loss: 1.7290 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7290 2023/06/05 17:03:54 - mmengine - INFO - Epoch(train) [129][1240/2569] lr: 4.0000e-03 eta: 4:05:20 time: 0.2738 data_time: 0.0069 memory: 5828 grad_norm: 5.0372 loss: 1.6132 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6132 2023/06/05 17:03:59 - mmengine - INFO - Epoch(train) [129][1260/2569] lr: 4.0000e-03 eta: 4:05:14 time: 0.2619 data_time: 0.0078 memory: 5828 grad_norm: 5.0974 loss: 1.6391 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6391 2023/06/05 17:04:05 - mmengine - INFO - Epoch(train) [129][1280/2569] lr: 4.0000e-03 eta: 4:05:09 time: 0.2797 data_time: 0.0074 memory: 5828 grad_norm: 5.1581 loss: 1.9152 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9152 2023/06/05 17:04:10 - mmengine - INFO - Epoch(train) [129][1300/2569] lr: 4.0000e-03 eta: 4:05:04 time: 0.2653 data_time: 0.0073 memory: 5828 grad_norm: 5.0798 loss: 1.5101 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5101 2023/06/05 17:04:15 - mmengine - INFO - Epoch(train) [129][1320/2569] lr: 4.0000e-03 eta: 4:04:59 time: 0.2734 data_time: 0.0072 memory: 5828 grad_norm: 5.0529 loss: 1.8800 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8800 2023/06/05 17:04:21 - mmengine - INFO - Epoch(train) [129][1340/2569] lr: 4.0000e-03 eta: 4:04:53 time: 0.2746 data_time: 0.0072 memory: 5828 grad_norm: 5.0926 loss: 1.6875 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6875 2023/06/05 17:04:26 - mmengine - INFO - Epoch(train) [129][1360/2569] lr: 4.0000e-03 eta: 4:04:48 time: 0.2745 data_time: 0.0075 memory: 5828 grad_norm: 5.1012 loss: 2.0813 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 2.0813 2023/06/05 17:04:32 - mmengine - INFO - Epoch(train) [129][1380/2569] lr: 4.0000e-03 eta: 4:04:43 time: 0.2673 data_time: 0.0074 memory: 5828 grad_norm: 5.2187 loss: 1.6764 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6764 2023/06/05 17:04:37 - mmengine - INFO - Epoch(train) [129][1400/2569] lr: 4.0000e-03 eta: 4:04:37 time: 0.2775 data_time: 0.0074 memory: 5828 grad_norm: 5.0496 loss: 1.8830 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8830 2023/06/05 17:04:43 - mmengine - INFO - Epoch(train) [129][1420/2569] lr: 4.0000e-03 eta: 4:04:32 time: 0.2634 data_time: 0.0073 memory: 5828 grad_norm: 5.0294 loss: 1.6039 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6039 2023/06/05 17:04:48 - mmengine - INFO - Epoch(train) [129][1440/2569] lr: 4.0000e-03 eta: 4:04:27 time: 0.2775 data_time: 0.0072 memory: 5828 grad_norm: 5.0652 loss: 1.8186 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8186 2023/06/05 17:04:54 - mmengine - INFO - Epoch(train) [129][1460/2569] lr: 4.0000e-03 eta: 4:04:21 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 4.9977 loss: 1.7813 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7813 2023/06/05 17:04:59 - mmengine - INFO - Epoch(train) [129][1480/2569] lr: 4.0000e-03 eta: 4:04:16 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 5.0199 loss: 1.5904 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5904 2023/06/05 17:05:04 - mmengine - INFO - Epoch(train) [129][1500/2569] lr: 4.0000e-03 eta: 4:04:11 time: 0.2626 data_time: 0.0071 memory: 5828 grad_norm: 5.0923 loss: 2.0485 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0485 2023/06/05 17:05:10 - mmengine - INFO - Epoch(train) [129][1520/2569] lr: 4.0000e-03 eta: 4:04:05 time: 0.2773 data_time: 0.0076 memory: 5828 grad_norm: 5.1204 loss: 1.6371 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6371 2023/06/05 17:05:15 - mmengine - INFO - Epoch(train) [129][1540/2569] lr: 4.0000e-03 eta: 4:04:00 time: 0.2723 data_time: 0.0073 memory: 5828 grad_norm: 5.1289 loss: 1.5396 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5396 2023/06/05 17:05:20 - mmengine - INFO - Epoch(train) [129][1560/2569] lr: 4.0000e-03 eta: 4:03:55 time: 0.2624 data_time: 0.0071 memory: 5828 grad_norm: 4.9604 loss: 1.6263 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6263 2023/06/05 17:05:26 - mmengine - INFO - Epoch(train) [129][1580/2569] lr: 4.0000e-03 eta: 4:03:50 time: 0.2678 data_time: 0.0071 memory: 5828 grad_norm: 4.9958 loss: 1.8613 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8613 2023/06/05 17:05:31 - mmengine - INFO - Epoch(train) [129][1600/2569] lr: 4.0000e-03 eta: 4:03:44 time: 0.2726 data_time: 0.0072 memory: 5828 grad_norm: 5.0814 loss: 1.6909 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6909 2023/06/05 17:05:37 - mmengine - INFO - Epoch(train) [129][1620/2569] lr: 4.0000e-03 eta: 4:03:39 time: 0.2698 data_time: 0.0078 memory: 5828 grad_norm: 5.1483 loss: 2.3683 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.3683 2023/06/05 17:05:42 - mmengine - INFO - Epoch(train) [129][1640/2569] lr: 4.0000e-03 eta: 4:03:34 time: 0.2657 data_time: 0.0077 memory: 5828 grad_norm: 4.9559 loss: 1.7425 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7425 2023/06/05 17:05:47 - mmengine - INFO - Epoch(train) [129][1660/2569] lr: 4.0000e-03 eta: 4:03:28 time: 0.2659 data_time: 0.0072 memory: 5828 grad_norm: 5.1605 loss: 1.7661 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7661 2023/06/05 17:05:53 - mmengine - INFO - Epoch(train) [129][1680/2569] lr: 4.0000e-03 eta: 4:03:23 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 5.0577 loss: 1.8546 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8546 2023/06/05 17:05:58 - mmengine - INFO - Epoch(train) [129][1700/2569] lr: 4.0000e-03 eta: 4:03:18 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 5.0935 loss: 1.9069 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9069 2023/06/05 17:06:03 - mmengine - INFO - Epoch(train) [129][1720/2569] lr: 4.0000e-03 eta: 4:03:12 time: 0.2630 data_time: 0.0072 memory: 5828 grad_norm: 5.0458 loss: 1.7247 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7247 2023/06/05 17:06:09 - mmengine - INFO - Epoch(train) [129][1740/2569] lr: 4.0000e-03 eta: 4:03:07 time: 0.2644 data_time: 0.0082 memory: 5828 grad_norm: 5.0095 loss: 2.0222 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0222 2023/06/05 17:06:14 - mmengine - INFO - Epoch(train) [129][1760/2569] lr: 4.0000e-03 eta: 4:03:02 time: 0.2653 data_time: 0.0079 memory: 5828 grad_norm: 4.9794 loss: 1.9500 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9500 2023/06/05 17:06:19 - mmengine - INFO - Epoch(train) [129][1780/2569] lr: 4.0000e-03 eta: 4:02:56 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 5.0643 loss: 1.8994 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8994 2023/06/05 17:06:25 - mmengine - INFO - Epoch(train) [129][1800/2569] lr: 4.0000e-03 eta: 4:02:51 time: 0.2668 data_time: 0.0077 memory: 5828 grad_norm: 5.0180 loss: 1.6864 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6864 2023/06/05 17:06:30 - mmengine - INFO - Epoch(train) [129][1820/2569] lr: 4.0000e-03 eta: 4:02:46 time: 0.2652 data_time: 0.0071 memory: 5828 grad_norm: 5.0840 loss: 1.7258 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7258 2023/06/05 17:06:35 - mmengine - INFO - Epoch(train) [129][1840/2569] lr: 4.0000e-03 eta: 4:02:40 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 5.1606 loss: 2.0840 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0840 2023/06/05 17:06:41 - mmengine - INFO - Epoch(train) [129][1860/2569] lr: 4.0000e-03 eta: 4:02:35 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 5.0150 loss: 1.6274 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6274 2023/06/05 17:06:46 - mmengine - INFO - Epoch(train) [129][1880/2569] lr: 4.0000e-03 eta: 4:02:30 time: 0.2742 data_time: 0.0071 memory: 5828 grad_norm: 4.9896 loss: 1.9935 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9935 2023/06/05 17:06:51 - mmengine - INFO - Epoch(train) [129][1900/2569] lr: 4.0000e-03 eta: 4:02:24 time: 0.2679 data_time: 0.0071 memory: 5828 grad_norm: 4.9347 loss: 1.7187 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7187 2023/06/05 17:06:57 - mmengine - INFO - Epoch(train) [129][1920/2569] lr: 4.0000e-03 eta: 4:02:19 time: 0.2708 data_time: 0.0077 memory: 5828 grad_norm: 5.1141 loss: 1.8700 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8700 2023/06/05 17:07:02 - mmengine - INFO - Epoch(train) [129][1940/2569] lr: 4.0000e-03 eta: 4:02:14 time: 0.2651 data_time: 0.0081 memory: 5828 grad_norm: 4.9340 loss: 1.7804 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7804 2023/06/05 17:07:08 - mmengine - INFO - Epoch(train) [129][1960/2569] lr: 4.0000e-03 eta: 4:02:08 time: 0.2741 data_time: 0.0074 memory: 5828 grad_norm: 5.1659 loss: 1.5913 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5913 2023/06/05 17:07:13 - mmengine - INFO - Epoch(train) [129][1980/2569] lr: 4.0000e-03 eta: 4:02:03 time: 0.2713 data_time: 0.0074 memory: 5828 grad_norm: 5.0698 loss: 1.9799 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9799 2023/06/05 17:07:18 - mmengine - INFO - Epoch(train) [129][2000/2569] lr: 4.0000e-03 eta: 4:01:58 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 5.0341 loss: 1.8751 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8751 2023/06/05 17:07:24 - mmengine - INFO - Epoch(train) [129][2020/2569] lr: 4.0000e-03 eta: 4:01:52 time: 0.2720 data_time: 0.0072 memory: 5828 grad_norm: 5.0926 loss: 2.1109 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.1109 2023/06/05 17:07:29 - mmengine - INFO - Epoch(train) [129][2040/2569] lr: 4.0000e-03 eta: 4:01:47 time: 0.2635 data_time: 0.0072 memory: 5828 grad_norm: 4.9769 loss: 1.7415 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7415 2023/06/05 17:07:35 - mmengine - INFO - Epoch(train) [129][2060/2569] lr: 4.0000e-03 eta: 4:01:42 time: 0.2716 data_time: 0.0073 memory: 5828 grad_norm: 5.1042 loss: 1.8355 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8355 2023/06/05 17:07:40 - mmengine - INFO - Epoch(train) [129][2080/2569] lr: 4.0000e-03 eta: 4:01:36 time: 0.2616 data_time: 0.0071 memory: 5828 grad_norm: 5.0764 loss: 1.7675 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7675 2023/06/05 17:07:45 - mmengine - INFO - Epoch(train) [129][2100/2569] lr: 4.0000e-03 eta: 4:01:31 time: 0.2613 data_time: 0.0071 memory: 5828 grad_norm: 5.0708 loss: 2.0132 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0132 2023/06/05 17:07:50 - mmengine - INFO - Epoch(train) [129][2120/2569] lr: 4.0000e-03 eta: 4:01:26 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 5.0139 loss: 1.6092 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6092 2023/06/05 17:07:56 - mmengine - INFO - Epoch(train) [129][2140/2569] lr: 4.0000e-03 eta: 4:01:20 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 4.9402 loss: 1.7248 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7248 2023/06/05 17:08:01 - mmengine - INFO - Epoch(train) [129][2160/2569] lr: 4.0000e-03 eta: 4:01:15 time: 0.2617 data_time: 0.0078 memory: 5828 grad_norm: 5.0423 loss: 1.6239 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6239 2023/06/05 17:08:03 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:08:06 - mmengine - INFO - Epoch(train) [129][2180/2569] lr: 4.0000e-03 eta: 4:01:10 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 5.0074 loss: 1.7539 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7539 2023/06/05 17:08:12 - mmengine - INFO - Epoch(train) [129][2200/2569] lr: 4.0000e-03 eta: 4:01:04 time: 0.2729 data_time: 0.0074 memory: 5828 grad_norm: 5.1154 loss: 1.7829 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7829 2023/06/05 17:08:17 - mmengine - INFO - Epoch(train) [129][2220/2569] lr: 4.0000e-03 eta: 4:00:59 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 5.0154 loss: 1.6758 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6758 2023/06/05 17:08:22 - mmengine - INFO - Epoch(train) [129][2240/2569] lr: 4.0000e-03 eta: 4:00:54 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 5.0634 loss: 1.7465 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7465 2023/06/05 17:08:28 - mmengine - INFO - Epoch(train) [129][2260/2569] lr: 4.0000e-03 eta: 4:00:48 time: 0.2648 data_time: 0.0075 memory: 5828 grad_norm: 5.0867 loss: 2.0364 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0364 2023/06/05 17:08:33 - mmengine - INFO - Epoch(train) [129][2280/2569] lr: 4.0000e-03 eta: 4:00:43 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 4.9835 loss: 1.6326 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6326 2023/06/05 17:08:38 - mmengine - INFO - Epoch(train) [129][2300/2569] lr: 4.0000e-03 eta: 4:00:38 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 5.0936 loss: 1.8316 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8316 2023/06/05 17:08:44 - mmengine - INFO - Epoch(train) [129][2320/2569] lr: 4.0000e-03 eta: 4:00:32 time: 0.2746 data_time: 0.0075 memory: 5828 grad_norm: 5.0176 loss: 1.7731 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7731 2023/06/05 17:08:49 - mmengine - INFO - Epoch(train) [129][2340/2569] lr: 4.0000e-03 eta: 4:00:27 time: 0.2682 data_time: 0.0072 memory: 5828 grad_norm: 5.1242 loss: 1.7320 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7320 2023/06/05 17:08:54 - mmengine - INFO - Epoch(train) [129][2360/2569] lr: 4.0000e-03 eta: 4:00:22 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 5.0870 loss: 1.7834 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7834 2023/06/05 17:09:00 - mmengine - INFO - Epoch(train) [129][2380/2569] lr: 4.0000e-03 eta: 4:00:17 time: 0.2653 data_time: 0.0072 memory: 5828 grad_norm: 5.0994 loss: 1.6846 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6846 2023/06/05 17:09:05 - mmengine - INFO - Epoch(train) [129][2400/2569] lr: 4.0000e-03 eta: 4:00:11 time: 0.2665 data_time: 0.0080 memory: 5828 grad_norm: 5.1822 loss: 2.0508 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0508 2023/06/05 17:09:10 - mmengine - INFO - Epoch(train) [129][2420/2569] lr: 4.0000e-03 eta: 4:00:06 time: 0.2620 data_time: 0.0075 memory: 5828 grad_norm: 5.0230 loss: 1.7743 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7743 2023/06/05 17:09:16 - mmengine - INFO - Epoch(train) [129][2440/2569] lr: 4.0000e-03 eta: 4:00:01 time: 0.2673 data_time: 0.0077 memory: 5828 grad_norm: 4.9693 loss: 1.7113 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7113 2023/06/05 17:09:21 - mmengine - INFO - Epoch(train) [129][2460/2569] lr: 4.0000e-03 eta: 3:59:55 time: 0.2726 data_time: 0.0078 memory: 5828 grad_norm: 5.0797 loss: 1.8443 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.8443 2023/06/05 17:09:26 - mmengine - INFO - Epoch(train) [129][2480/2569] lr: 4.0000e-03 eta: 3:59:50 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 5.0941 loss: 2.0470 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0470 2023/06/05 17:09:32 - mmengine - INFO - Epoch(train) [129][2500/2569] lr: 4.0000e-03 eta: 3:59:45 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 5.1486 loss: 1.7290 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7290 2023/06/05 17:09:37 - mmengine - INFO - Epoch(train) [129][2520/2569] lr: 4.0000e-03 eta: 3:59:39 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 5.1718 loss: 1.9118 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9118 2023/06/05 17:09:43 - mmengine - INFO - Epoch(train) [129][2540/2569] lr: 4.0000e-03 eta: 3:59:34 time: 0.2750 data_time: 0.0071 memory: 5828 grad_norm: 4.9634 loss: 1.5886 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5886 2023/06/05 17:09:48 - mmengine - INFO - Epoch(train) [129][2560/2569] lr: 4.0000e-03 eta: 3:59:29 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 4.9932 loss: 1.4397 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4397 2023/06/05 17:09:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:09:50 - mmengine - INFO - Epoch(train) [129][2569/2569] lr: 4.0000e-03 eta: 3:59:26 time: 0.2608 data_time: 0.0071 memory: 5828 grad_norm: 5.0119 loss: 1.4859 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4859 2023/06/05 17:09:57 - mmengine - INFO - Epoch(train) [130][ 20/2569] lr: 4.0000e-03 eta: 3:59:21 time: 0.3442 data_time: 0.0511 memory: 5828 grad_norm: 5.0382 loss: 1.6380 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6380 2023/06/05 17:10:03 - mmengine - INFO - Epoch(train) [130][ 40/2569] lr: 4.0000e-03 eta: 3:59:16 time: 0.2749 data_time: 0.0071 memory: 5828 grad_norm: 5.0699 loss: 1.8548 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8548 2023/06/05 17:10:08 - mmengine - INFO - Epoch(train) [130][ 60/2569] lr: 4.0000e-03 eta: 3:59:11 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 5.1307 loss: 1.6662 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6662 2023/06/05 17:10:13 - mmengine - INFO - Epoch(train) [130][ 80/2569] lr: 4.0000e-03 eta: 3:59:05 time: 0.2730 data_time: 0.0072 memory: 5828 grad_norm: 4.9709 loss: 1.7809 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7809 2023/06/05 17:10:19 - mmengine - INFO - Epoch(train) [130][ 100/2569] lr: 4.0000e-03 eta: 3:59:00 time: 0.2724 data_time: 0.0072 memory: 5828 grad_norm: 5.0045 loss: 1.7946 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7946 2023/06/05 17:10:24 - mmengine - INFO - Epoch(train) [130][ 120/2569] lr: 4.0000e-03 eta: 3:58:55 time: 0.2714 data_time: 0.0072 memory: 5828 grad_norm: 5.0906 loss: 1.9108 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9108 2023/06/05 17:10:30 - mmengine - INFO - Epoch(train) [130][ 140/2569] lr: 4.0000e-03 eta: 3:58:49 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 5.0885 loss: 1.9027 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9027 2023/06/05 17:10:35 - mmengine - INFO - Epoch(train) [130][ 160/2569] lr: 4.0000e-03 eta: 3:58:44 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 5.0523 loss: 1.9467 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9467 2023/06/05 17:10:40 - mmengine - INFO - Epoch(train) [130][ 180/2569] lr: 4.0000e-03 eta: 3:58:39 time: 0.2686 data_time: 0.0070 memory: 5828 grad_norm: 5.1178 loss: 2.0633 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0633 2023/06/05 17:10:45 - mmengine - INFO - Epoch(train) [130][ 200/2569] lr: 4.0000e-03 eta: 3:58:33 time: 0.2681 data_time: 0.0074 memory: 5828 grad_norm: 5.0365 loss: 1.6460 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6460 2023/06/05 17:10:51 - mmengine - INFO - Epoch(train) [130][ 220/2569] lr: 4.0000e-03 eta: 3:58:28 time: 0.2650 data_time: 0.0073 memory: 5828 grad_norm: 5.1061 loss: 1.8882 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8882 2023/06/05 17:10:56 - mmengine - INFO - Epoch(train) [130][ 240/2569] lr: 4.0000e-03 eta: 3:58:23 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 5.0578 loss: 1.7106 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7106 2023/06/05 17:11:02 - mmengine - INFO - Epoch(train) [130][ 260/2569] lr: 4.0000e-03 eta: 3:58:17 time: 0.2759 data_time: 0.0071 memory: 5828 grad_norm: 5.0992 loss: 1.9400 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9400 2023/06/05 17:11:07 - mmengine - INFO - Epoch(train) [130][ 280/2569] lr: 4.0000e-03 eta: 3:58:12 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 5.0825 loss: 1.5778 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5778 2023/06/05 17:11:12 - mmengine - INFO - Epoch(train) [130][ 300/2569] lr: 4.0000e-03 eta: 3:58:07 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 5.2255 loss: 2.0251 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0251 2023/06/05 17:11:18 - mmengine - INFO - Epoch(train) [130][ 320/2569] lr: 4.0000e-03 eta: 3:58:01 time: 0.2724 data_time: 0.0073 memory: 5828 grad_norm: 5.1471 loss: 1.6946 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6946 2023/06/05 17:11:23 - mmengine - INFO - Epoch(train) [130][ 340/2569] lr: 4.0000e-03 eta: 3:57:56 time: 0.2658 data_time: 0.0074 memory: 5828 grad_norm: 4.9904 loss: 1.9885 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9885 2023/06/05 17:11:28 - mmengine - INFO - Epoch(train) [130][ 360/2569] lr: 4.0000e-03 eta: 3:57:51 time: 0.2702 data_time: 0.0079 memory: 5828 grad_norm: 5.1229 loss: 1.7052 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7052 2023/06/05 17:11:34 - mmengine - INFO - Epoch(train) [130][ 380/2569] lr: 4.0000e-03 eta: 3:57:45 time: 0.2623 data_time: 0.0068 memory: 5828 grad_norm: 5.1349 loss: 1.7150 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7150 2023/06/05 17:11:39 - mmengine - INFO - Epoch(train) [130][ 400/2569] lr: 4.0000e-03 eta: 3:57:40 time: 0.2702 data_time: 0.0072 memory: 5828 grad_norm: 5.1391 loss: 1.6689 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6689 2023/06/05 17:11:44 - mmengine - INFO - Epoch(train) [130][ 420/2569] lr: 4.0000e-03 eta: 3:57:35 time: 0.2651 data_time: 0.0076 memory: 5828 grad_norm: 5.1230 loss: 1.8946 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8946 2023/06/05 17:11:50 - mmengine - INFO - Epoch(train) [130][ 440/2569] lr: 4.0000e-03 eta: 3:57:29 time: 0.2669 data_time: 0.0080 memory: 5828 grad_norm: 5.1838 loss: 1.9876 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9876 2023/06/05 17:11:55 - mmengine - INFO - Epoch(train) [130][ 460/2569] lr: 4.0000e-03 eta: 3:57:24 time: 0.2697 data_time: 0.0072 memory: 5828 grad_norm: 5.0949 loss: 1.9533 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9533 2023/06/05 17:12:01 - mmengine - INFO - Epoch(train) [130][ 480/2569] lr: 4.0000e-03 eta: 3:57:19 time: 0.2710 data_time: 0.0077 memory: 5828 grad_norm: 5.0810 loss: 1.8029 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8029 2023/06/05 17:12:06 - mmengine - INFO - Epoch(train) [130][ 500/2569] lr: 4.0000e-03 eta: 3:57:13 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 5.1356 loss: 1.6892 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6892 2023/06/05 17:12:11 - mmengine - INFO - Epoch(train) [130][ 520/2569] lr: 4.0000e-03 eta: 3:57:08 time: 0.2742 data_time: 0.0077 memory: 5828 grad_norm: 5.0885 loss: 1.8740 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8740 2023/06/05 17:12:17 - mmengine - INFO - Epoch(train) [130][ 540/2569] lr: 4.0000e-03 eta: 3:57:03 time: 0.2633 data_time: 0.0076 memory: 5828 grad_norm: 5.1646 loss: 1.7869 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7869 2023/06/05 17:12:22 - mmengine - INFO - Epoch(train) [130][ 560/2569] lr: 4.0000e-03 eta: 3:56:57 time: 0.2785 data_time: 0.0073 memory: 5828 grad_norm: 5.0165 loss: 1.6599 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6599 2023/06/05 17:12:28 - mmengine - INFO - Epoch(train) [130][ 580/2569] lr: 4.0000e-03 eta: 3:56:52 time: 0.2664 data_time: 0.0081 memory: 5828 grad_norm: 5.1652 loss: 2.0173 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0173 2023/06/05 17:12:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:12:33 - mmengine - INFO - Epoch(train) [130][ 600/2569] lr: 4.0000e-03 eta: 3:56:47 time: 0.2683 data_time: 0.0070 memory: 5828 grad_norm: 5.1399 loss: 1.5749 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5749 2023/06/05 17:12:38 - mmengine - INFO - Epoch(train) [130][ 620/2569] lr: 4.0000e-03 eta: 3:56:42 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 5.0697 loss: 1.6201 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6201 2023/06/05 17:12:44 - mmengine - INFO - Epoch(train) [130][ 640/2569] lr: 4.0000e-03 eta: 3:56:36 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 5.0352 loss: 1.9261 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9261 2023/06/05 17:12:49 - mmengine - INFO - Epoch(train) [130][ 660/2569] lr: 4.0000e-03 eta: 3:56:31 time: 0.2822 data_time: 0.0077 memory: 5828 grad_norm: 5.0373 loss: 1.9258 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9258 2023/06/05 17:12:55 - mmengine - INFO - Epoch(train) [130][ 680/2569] lr: 4.0000e-03 eta: 3:56:26 time: 0.2701 data_time: 0.0072 memory: 5828 grad_norm: 5.1243 loss: 1.4357 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4357 2023/06/05 17:13:00 - mmengine - INFO - Epoch(train) [130][ 700/2569] lr: 4.0000e-03 eta: 3:56:20 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 5.0457 loss: 2.0278 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0278 2023/06/05 17:13:06 - mmengine - INFO - Epoch(train) [130][ 720/2569] lr: 4.0000e-03 eta: 3:56:15 time: 0.2682 data_time: 0.0074 memory: 5828 grad_norm: 5.0922 loss: 1.5954 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5954 2023/06/05 17:13:11 - mmengine - INFO - Epoch(train) [130][ 740/2569] lr: 4.0000e-03 eta: 3:56:10 time: 0.2739 data_time: 0.0073 memory: 5828 grad_norm: 5.1111 loss: 1.6561 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6561 2023/06/05 17:13:17 - mmengine - INFO - Epoch(train) [130][ 760/2569] lr: 4.0000e-03 eta: 3:56:04 time: 0.2770 data_time: 0.0072 memory: 5828 grad_norm: 4.9764 loss: 1.9075 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9075 2023/06/05 17:13:22 - mmengine - INFO - Epoch(train) [130][ 780/2569] lr: 4.0000e-03 eta: 3:55:59 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 5.0596 loss: 1.7067 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.7067 2023/06/05 17:13:27 - mmengine - INFO - Epoch(train) [130][ 800/2569] lr: 4.0000e-03 eta: 3:55:54 time: 0.2653 data_time: 0.0075 memory: 5828 grad_norm: 5.0892 loss: 1.3841 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.3841 2023/06/05 17:13:33 - mmengine - INFO - Epoch(train) [130][ 820/2569] lr: 4.0000e-03 eta: 3:55:48 time: 0.2681 data_time: 0.0074 memory: 5828 grad_norm: 5.1759 loss: 1.7869 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7869 2023/06/05 17:13:38 - mmengine - INFO - Epoch(train) [130][ 840/2569] lr: 4.0000e-03 eta: 3:55:43 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 5.0907 loss: 1.7018 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7018 2023/06/05 17:13:43 - mmengine - INFO - Epoch(train) [130][ 860/2569] lr: 4.0000e-03 eta: 3:55:38 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 5.1132 loss: 1.6378 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6378 2023/06/05 17:13:49 - mmengine - INFO - Epoch(train) [130][ 880/2569] lr: 4.0000e-03 eta: 3:55:32 time: 0.2668 data_time: 0.0074 memory: 5828 grad_norm: 5.1215 loss: 1.5513 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5513 2023/06/05 17:13:54 - mmengine - INFO - Epoch(train) [130][ 900/2569] lr: 4.0000e-03 eta: 3:55:27 time: 0.2621 data_time: 0.0077 memory: 5828 grad_norm: 5.0810 loss: 1.8091 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8091 2023/06/05 17:13:59 - mmengine - INFO - Epoch(train) [130][ 920/2569] lr: 4.0000e-03 eta: 3:55:22 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 5.1571 loss: 2.0564 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0564 2023/06/05 17:14:05 - mmengine - INFO - Epoch(train) [130][ 940/2569] lr: 4.0000e-03 eta: 3:55:16 time: 0.2677 data_time: 0.0076 memory: 5828 grad_norm: 5.0688 loss: 1.7387 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7387 2023/06/05 17:14:10 - mmengine - INFO - Epoch(train) [130][ 960/2569] lr: 4.0000e-03 eta: 3:55:11 time: 0.2739 data_time: 0.0073 memory: 5828 grad_norm: 5.0084 loss: 1.7642 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7642 2023/06/05 17:14:15 - mmengine - INFO - Epoch(train) [130][ 980/2569] lr: 4.0000e-03 eta: 3:55:06 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 5.0459 loss: 1.9113 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9113 2023/06/05 17:14:21 - mmengine - INFO - Epoch(train) [130][1000/2569] lr: 4.0000e-03 eta: 3:55:01 time: 0.2711 data_time: 0.0071 memory: 5828 grad_norm: 5.0015 loss: 1.4134 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4134 2023/06/05 17:14:26 - mmengine - INFO - Epoch(train) [130][1020/2569] lr: 4.0000e-03 eta: 3:54:55 time: 0.2747 data_time: 0.0071 memory: 5828 grad_norm: 5.1560 loss: 1.9118 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9118 2023/06/05 17:14:32 - mmengine - INFO - Epoch(train) [130][1040/2569] lr: 4.0000e-03 eta: 3:54:50 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 5.1091 loss: 1.9933 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9933 2023/06/05 17:14:37 - mmengine - INFO - Epoch(train) [130][1060/2569] lr: 4.0000e-03 eta: 3:54:45 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 5.0903 loss: 2.1206 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.1206 2023/06/05 17:14:42 - mmengine - INFO - Epoch(train) [130][1080/2569] lr: 4.0000e-03 eta: 3:54:39 time: 0.2629 data_time: 0.0076 memory: 5828 grad_norm: 5.0907 loss: 1.8676 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8676 2023/06/05 17:14:47 - mmengine - INFO - Epoch(train) [130][1100/2569] lr: 4.0000e-03 eta: 3:54:34 time: 0.2631 data_time: 0.0068 memory: 5828 grad_norm: 5.0453 loss: 1.3179 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.3179 2023/06/05 17:14:53 - mmengine - INFO - Epoch(train) [130][1120/2569] lr: 4.0000e-03 eta: 3:54:29 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 5.0631 loss: 2.0584 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0584 2023/06/05 17:14:58 - mmengine - INFO - Epoch(train) [130][1140/2569] lr: 4.0000e-03 eta: 3:54:23 time: 0.2764 data_time: 0.0072 memory: 5828 grad_norm: 5.1363 loss: 1.7738 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7738 2023/06/05 17:15:04 - mmengine - INFO - Epoch(train) [130][1160/2569] lr: 4.0000e-03 eta: 3:54:18 time: 0.2654 data_time: 0.0071 memory: 5828 grad_norm: 5.0297 loss: 1.8049 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8049 2023/06/05 17:15:09 - mmengine - INFO - Epoch(train) [130][1180/2569] lr: 4.0000e-03 eta: 3:54:13 time: 0.2739 data_time: 0.0071 memory: 5828 grad_norm: 5.1831 loss: 1.7148 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7148 2023/06/05 17:15:14 - mmengine - INFO - Epoch(train) [130][1200/2569] lr: 4.0000e-03 eta: 3:54:07 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 5.2437 loss: 1.6801 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.6801 2023/06/05 17:15:20 - mmengine - INFO - Epoch(train) [130][1220/2569] lr: 4.0000e-03 eta: 3:54:02 time: 0.2688 data_time: 0.0071 memory: 5828 grad_norm: 5.0928 loss: 2.0010 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0010 2023/06/05 17:15:25 - mmengine - INFO - Epoch(train) [130][1240/2569] lr: 4.0000e-03 eta: 3:53:57 time: 0.2687 data_time: 0.0072 memory: 5828 grad_norm: 5.2456 loss: 1.9715 top1_acc: 0.2500 top5_acc: 0.2500 loss_cls: 1.9715 2023/06/05 17:15:30 - mmengine - INFO - Epoch(train) [130][1260/2569] lr: 4.0000e-03 eta: 3:53:51 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 5.1834 loss: 1.7720 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7720 2023/06/05 17:15:36 - mmengine - INFO - Epoch(train) [130][1280/2569] lr: 4.0000e-03 eta: 3:53:46 time: 0.2711 data_time: 0.0074 memory: 5828 grad_norm: 5.1470 loss: 2.2500 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.2500 2023/06/05 17:15:41 - mmengine - INFO - Epoch(train) [130][1300/2569] lr: 4.0000e-03 eta: 3:53:41 time: 0.2738 data_time: 0.0072 memory: 5828 grad_norm: 5.0601 loss: 1.6195 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6195 2023/06/05 17:15:47 - mmengine - INFO - Epoch(train) [130][1320/2569] lr: 4.0000e-03 eta: 3:53:35 time: 0.2724 data_time: 0.0072 memory: 5828 grad_norm: 5.1026 loss: 1.8269 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8269 2023/06/05 17:15:52 - mmengine - INFO - Epoch(train) [130][1340/2569] lr: 4.0000e-03 eta: 3:53:30 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 4.9300 loss: 1.6513 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6513 2023/06/05 17:15:57 - mmengine - INFO - Epoch(train) [130][1360/2569] lr: 4.0000e-03 eta: 3:53:25 time: 0.2616 data_time: 0.0074 memory: 5828 grad_norm: 5.1184 loss: 1.7392 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7392 2023/06/05 17:16:03 - mmengine - INFO - Epoch(train) [130][1380/2569] lr: 4.0000e-03 eta: 3:53:19 time: 0.2747 data_time: 0.0071 memory: 5828 grad_norm: 5.0970 loss: 1.5589 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5589 2023/06/05 17:16:08 - mmengine - INFO - Epoch(train) [130][1400/2569] lr: 4.0000e-03 eta: 3:53:14 time: 0.2665 data_time: 0.0073 memory: 5828 grad_norm: 5.0918 loss: 1.7441 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7441 2023/06/05 17:16:14 - mmengine - INFO - Epoch(train) [130][1420/2569] lr: 4.0000e-03 eta: 3:53:09 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 5.1680 loss: 1.7384 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7384 2023/06/05 17:16:19 - mmengine - INFO - Epoch(train) [130][1440/2569] lr: 4.0000e-03 eta: 3:53:03 time: 0.2747 data_time: 0.0077 memory: 5828 grad_norm: 5.1518 loss: 1.5021 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5021 2023/06/05 17:16:24 - mmengine - INFO - Epoch(train) [130][1460/2569] lr: 4.0000e-03 eta: 3:52:58 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 5.1460 loss: 1.6972 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6972 2023/06/05 17:16:30 - mmengine - INFO - Epoch(train) [130][1480/2569] lr: 4.0000e-03 eta: 3:52:53 time: 0.2623 data_time: 0.0074 memory: 5828 grad_norm: 5.1328 loss: 1.8912 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8912 2023/06/05 17:16:35 - mmengine - INFO - Epoch(train) [130][1500/2569] lr: 4.0000e-03 eta: 3:52:47 time: 0.2725 data_time: 0.0072 memory: 5828 grad_norm: 5.1064 loss: 1.5573 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5573 2023/06/05 17:16:40 - mmengine - INFO - Epoch(train) [130][1520/2569] lr: 4.0000e-03 eta: 3:52:42 time: 0.2622 data_time: 0.0078 memory: 5828 grad_norm: 5.1333 loss: 1.8306 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8306 2023/06/05 17:16:46 - mmengine - INFO - Epoch(train) [130][1540/2569] lr: 4.0000e-03 eta: 3:52:37 time: 0.2657 data_time: 0.0083 memory: 5828 grad_norm: 5.1951 loss: 1.7902 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7902 2023/06/05 17:16:51 - mmengine - INFO - Epoch(train) [130][1560/2569] lr: 4.0000e-03 eta: 3:52:32 time: 0.2695 data_time: 0.0070 memory: 5828 grad_norm: 5.0812 loss: 1.9010 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9010 2023/06/05 17:16:57 - mmengine - INFO - Epoch(train) [130][1580/2569] lr: 4.0000e-03 eta: 3:52:26 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 5.1111 loss: 1.8648 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8648 2023/06/05 17:17:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:17:02 - mmengine - INFO - Epoch(train) [130][1600/2569] lr: 4.0000e-03 eta: 3:52:21 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 5.1263 loss: 1.8988 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8988 2023/06/05 17:17:07 - mmengine - INFO - Epoch(train) [130][1620/2569] lr: 4.0000e-03 eta: 3:52:16 time: 0.2713 data_time: 0.0071 memory: 5828 grad_norm: 5.0677 loss: 2.0507 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0507 2023/06/05 17:17:13 - mmengine - INFO - Epoch(train) [130][1640/2569] lr: 4.0000e-03 eta: 3:52:10 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 5.0261 loss: 1.6841 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6841 2023/06/05 17:17:18 - mmengine - INFO - Epoch(train) [130][1660/2569] lr: 4.0000e-03 eta: 3:52:05 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 5.0861 loss: 1.9973 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9973 2023/06/05 17:17:23 - mmengine - INFO - Epoch(train) [130][1680/2569] lr: 4.0000e-03 eta: 3:52:00 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 4.9843 loss: 1.6450 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6450 2023/06/05 17:17:28 - mmengine - INFO - Epoch(train) [130][1700/2569] lr: 4.0000e-03 eta: 3:51:54 time: 0.2617 data_time: 0.0070 memory: 5828 grad_norm: 5.0867 loss: 1.7469 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7469 2023/06/05 17:17:34 - mmengine - INFO - Epoch(train) [130][1720/2569] lr: 4.0000e-03 eta: 3:51:49 time: 0.2681 data_time: 0.0073 memory: 5828 grad_norm: 5.0913 loss: 1.5633 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5633 2023/06/05 17:17:39 - mmengine - INFO - Epoch(train) [130][1740/2569] lr: 4.0000e-03 eta: 3:51:44 time: 0.2622 data_time: 0.0071 memory: 5828 grad_norm: 5.1336 loss: 1.7608 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7608 2023/06/05 17:17:45 - mmengine - INFO - Epoch(train) [130][1760/2569] lr: 4.0000e-03 eta: 3:51:38 time: 0.2755 data_time: 0.0073 memory: 5828 grad_norm: 5.0809 loss: 1.6523 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6523 2023/06/05 17:17:50 - mmengine - INFO - Epoch(train) [130][1780/2569] lr: 4.0000e-03 eta: 3:51:33 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 5.1263 loss: 1.8505 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8505 2023/06/05 17:17:55 - mmengine - INFO - Epoch(train) [130][1800/2569] lr: 4.0000e-03 eta: 3:51:28 time: 0.2815 data_time: 0.0070 memory: 5828 grad_norm: 5.1697 loss: 1.9462 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9462 2023/06/05 17:18:01 - mmengine - INFO - Epoch(train) [130][1820/2569] lr: 4.0000e-03 eta: 3:51:22 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 5.0771 loss: 1.6190 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6190 2023/06/05 17:18:06 - mmengine - INFO - Epoch(train) [130][1840/2569] lr: 4.0000e-03 eta: 3:51:17 time: 0.2694 data_time: 0.0072 memory: 5828 grad_norm: 5.1678 loss: 1.8341 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8341 2023/06/05 17:18:12 - mmengine - INFO - Epoch(train) [130][1860/2569] lr: 4.0000e-03 eta: 3:51:12 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 5.0633 loss: 1.8197 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8197 2023/06/05 17:18:17 - mmengine - INFO - Epoch(train) [130][1880/2569] lr: 4.0000e-03 eta: 3:51:06 time: 0.2673 data_time: 0.0072 memory: 5828 grad_norm: 5.0632 loss: 1.8957 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8957 2023/06/05 17:18:22 - mmengine - INFO - Epoch(train) [130][1900/2569] lr: 4.0000e-03 eta: 3:51:01 time: 0.2677 data_time: 0.0075 memory: 5828 grad_norm: 5.0146 loss: 1.6457 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6457 2023/06/05 17:18:27 - mmengine - INFO - Epoch(train) [130][1920/2569] lr: 4.0000e-03 eta: 3:50:56 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 5.1888 loss: 1.7487 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.7487 2023/06/05 17:18:33 - mmengine - INFO - Epoch(train) [130][1940/2569] lr: 4.0000e-03 eta: 3:50:50 time: 0.2730 data_time: 0.0069 memory: 5828 grad_norm: 5.0907 loss: 1.5374 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5374 2023/06/05 17:18:38 - mmengine - INFO - Epoch(train) [130][1960/2569] lr: 4.0000e-03 eta: 3:50:45 time: 0.2605 data_time: 0.0071 memory: 5828 grad_norm: 5.0580 loss: 1.6598 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6598 2023/06/05 17:18:44 - mmengine - INFO - Epoch(train) [130][1980/2569] lr: 4.0000e-03 eta: 3:50:40 time: 0.2662 data_time: 0.0074 memory: 5828 grad_norm: 5.0660 loss: 1.6412 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6412 2023/06/05 17:18:49 - mmengine - INFO - Epoch(train) [130][2000/2569] lr: 4.0000e-03 eta: 3:50:34 time: 0.2661 data_time: 0.0072 memory: 5828 grad_norm: 5.0746 loss: 1.6726 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6726 2023/06/05 17:18:54 - mmengine - INFO - Epoch(train) [130][2020/2569] lr: 4.0000e-03 eta: 3:50:29 time: 0.2737 data_time: 0.0072 memory: 5828 grad_norm: 5.0923 loss: 1.8773 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8773 2023/06/05 17:19:00 - mmengine - INFO - Epoch(train) [130][2040/2569] lr: 4.0000e-03 eta: 3:50:24 time: 0.2666 data_time: 0.0074 memory: 5828 grad_norm: 5.1496 loss: 2.1135 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 2.1135 2023/06/05 17:19:05 - mmengine - INFO - Epoch(train) [130][2060/2569] lr: 4.0000e-03 eta: 3:50:18 time: 0.2780 data_time: 0.0073 memory: 5828 grad_norm: 5.1231 loss: 1.4861 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4861 2023/06/05 17:19:11 - mmengine - INFO - Epoch(train) [130][2080/2569] lr: 4.0000e-03 eta: 3:50:13 time: 0.2653 data_time: 0.0078 memory: 5828 grad_norm: 4.9502 loss: 1.6592 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6592 2023/06/05 17:19:16 - mmengine - INFO - Epoch(train) [130][2100/2569] lr: 4.0000e-03 eta: 3:50:08 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 5.0631 loss: 2.0427 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0427 2023/06/05 17:19:21 - mmengine - INFO - Epoch(train) [130][2120/2569] lr: 4.0000e-03 eta: 3:50:02 time: 0.2629 data_time: 0.0071 memory: 5828 grad_norm: 5.0110 loss: 1.7812 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7812 2023/06/05 17:19:27 - mmengine - INFO - Epoch(train) [130][2140/2569] lr: 4.0000e-03 eta: 3:49:57 time: 0.2668 data_time: 0.0071 memory: 5828 grad_norm: 5.1123 loss: 1.7812 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7812 2023/06/05 17:19:32 - mmengine - INFO - Epoch(train) [130][2160/2569] lr: 4.0000e-03 eta: 3:49:52 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 5.1511 loss: 1.7786 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7786 2023/06/05 17:19:37 - mmengine - INFO - Epoch(train) [130][2180/2569] lr: 4.0000e-03 eta: 3:49:46 time: 0.2695 data_time: 0.0077 memory: 5828 grad_norm: 5.1129 loss: 1.4679 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.4679 2023/06/05 17:19:43 - mmengine - INFO - Epoch(train) [130][2200/2569] lr: 4.0000e-03 eta: 3:49:41 time: 0.2723 data_time: 0.0072 memory: 5828 grad_norm: 5.1478 loss: 1.9156 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9156 2023/06/05 17:19:48 - mmengine - INFO - Epoch(train) [130][2220/2569] lr: 4.0000e-03 eta: 3:49:36 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 5.1141 loss: 1.9994 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9994 2023/06/05 17:19:53 - mmengine - INFO - Epoch(train) [130][2240/2569] lr: 4.0000e-03 eta: 3:49:31 time: 0.2703 data_time: 0.0074 memory: 5828 grad_norm: 5.0422 loss: 1.4463 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4463 2023/06/05 17:19:59 - mmengine - INFO - Epoch(train) [130][2260/2569] lr: 4.0000e-03 eta: 3:49:25 time: 0.2642 data_time: 0.0077 memory: 5828 grad_norm: 5.1934 loss: 1.7139 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7139 2023/06/05 17:20:04 - mmengine - INFO - Epoch(train) [130][2280/2569] lr: 4.0000e-03 eta: 3:49:20 time: 0.2675 data_time: 0.0071 memory: 5828 grad_norm: 4.9710 loss: 1.9025 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9025 2023/06/05 17:20:09 - mmengine - INFO - Epoch(train) [130][2300/2569] lr: 4.0000e-03 eta: 3:49:15 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 5.1504 loss: 1.9185 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9185 2023/06/05 17:20:15 - mmengine - INFO - Epoch(train) [130][2320/2569] lr: 4.0000e-03 eta: 3:49:09 time: 0.2657 data_time: 0.0073 memory: 5828 grad_norm: 5.0707 loss: 1.8334 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8334 2023/06/05 17:20:20 - mmengine - INFO - Epoch(train) [130][2340/2569] lr: 4.0000e-03 eta: 3:49:04 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 5.1053 loss: 1.7031 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7031 2023/06/05 17:20:25 - mmengine - INFO - Epoch(train) [130][2360/2569] lr: 4.0000e-03 eta: 3:48:59 time: 0.2651 data_time: 0.0071 memory: 5828 grad_norm: 5.0577 loss: 1.9925 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9925 2023/06/05 17:20:31 - mmengine - INFO - Epoch(train) [130][2380/2569] lr: 4.0000e-03 eta: 3:48:53 time: 0.2743 data_time: 0.0071 memory: 5828 grad_norm: 5.2514 loss: 1.8529 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8529 2023/06/05 17:20:36 - mmengine - INFO - Epoch(train) [130][2400/2569] lr: 4.0000e-03 eta: 3:48:48 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 5.0657 loss: 1.9664 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9664 2023/06/05 17:20:42 - mmengine - INFO - Epoch(train) [130][2420/2569] lr: 4.0000e-03 eta: 3:48:43 time: 0.2735 data_time: 0.0074 memory: 5828 grad_norm: 5.1667 loss: 1.8465 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8465 2023/06/05 17:20:47 - mmengine - INFO - Epoch(train) [130][2440/2569] lr: 4.0000e-03 eta: 3:48:37 time: 0.2704 data_time: 0.0072 memory: 5828 grad_norm: 5.1378 loss: 1.3814 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3814 2023/06/05 17:20:52 - mmengine - INFO - Epoch(train) [130][2460/2569] lr: 4.0000e-03 eta: 3:48:32 time: 0.2703 data_time: 0.0072 memory: 5828 grad_norm: 5.0621 loss: 1.9625 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9625 2023/06/05 17:20:58 - mmengine - INFO - Epoch(train) [130][2480/2569] lr: 4.0000e-03 eta: 3:48:27 time: 0.2799 data_time: 0.0076 memory: 5828 grad_norm: 5.0322 loss: 1.6481 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6481 2023/06/05 17:21:03 - mmengine - INFO - Epoch(train) [130][2500/2569] lr: 4.0000e-03 eta: 3:48:21 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 5.0027 loss: 1.4201 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.4201 2023/06/05 17:21:09 - mmengine - INFO - Epoch(train) [130][2520/2569] lr: 4.0000e-03 eta: 3:48:16 time: 0.2717 data_time: 0.0072 memory: 5828 grad_norm: 5.0958 loss: 1.6919 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6919 2023/06/05 17:21:14 - mmengine - INFO - Epoch(train) [130][2540/2569] lr: 4.0000e-03 eta: 3:48:11 time: 0.2627 data_time: 0.0073 memory: 5828 grad_norm: 5.1623 loss: 1.6250 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6250 2023/06/05 17:21:19 - mmengine - INFO - Epoch(train) [130][2560/2569] lr: 4.0000e-03 eta: 3:48:05 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 5.1198 loss: 1.5470 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5470 2023/06/05 17:21:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:21:22 - mmengine - INFO - Epoch(train) [130][2569/2569] lr: 4.0000e-03 eta: 3:48:03 time: 0.2548 data_time: 0.0073 memory: 5828 grad_norm: 5.1921 loss: 1.7722 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.7722 2023/06/05 17:21:25 - mmengine - INFO - Epoch(val) [130][ 20/260] eta: 0:00:42 time: 0.1761 data_time: 0.1174 memory: 1238 2023/06/05 17:21:28 - mmengine - INFO - Epoch(val) [130][ 40/260] eta: 0:00:34 time: 0.1362 data_time: 0.0779 memory: 1238 2023/06/05 17:21:31 - mmengine - INFO - Epoch(val) [130][ 60/260] eta: 0:00:30 time: 0.1498 data_time: 0.0910 memory: 1238 2023/06/05 17:21:33 - mmengine - INFO - Epoch(val) [130][ 80/260] eta: 0:00:26 time: 0.1193 data_time: 0.0609 memory: 1238 2023/06/05 17:21:36 - mmengine - INFO - Epoch(val) [130][100/260] eta: 0:00:23 time: 0.1496 data_time: 0.0908 memory: 1238 2023/06/05 17:21:39 - mmengine - INFO - Epoch(val) [130][120/260] eta: 0:00:20 time: 0.1265 data_time: 0.0676 memory: 1238 2023/06/05 17:21:41 - mmengine - INFO - Epoch(val) [130][140/260] eta: 0:00:17 time: 0.1352 data_time: 0.0767 memory: 1238 2023/06/05 17:21:44 - mmengine - INFO - Epoch(val) [130][160/260] eta: 0:00:13 time: 0.1203 data_time: 0.0614 memory: 1238 2023/06/05 17:21:47 - mmengine - INFO - Epoch(val) [130][180/260] eta: 0:00:11 time: 0.1748 data_time: 0.1160 memory: 1238 2023/06/05 17:21:50 - mmengine - INFO - Epoch(val) [130][200/260] eta: 0:00:08 time: 0.1333 data_time: 0.0746 memory: 1238 2023/06/05 17:21:53 - mmengine - INFO - Epoch(val) [130][220/260] eta: 0:00:05 time: 0.1478 data_time: 0.0894 memory: 1238 2023/06/05 17:21:56 - mmengine - INFO - Epoch(val) [130][240/260] eta: 0:00:02 time: 0.1310 data_time: 0.0720 memory: 1238 2023/06/05 17:21:58 - mmengine - INFO - Epoch(val) [130][260/260] eta: 0:00:00 time: 0.1383 data_time: 0.0818 memory: 1238 2023/06/05 17:22:11 - mmengine - INFO - Epoch(val) [130][260/260] acc/top1: 0.6206 acc/top5: 0.8317 acc/mean1: 0.6144 data_time: 0.0826 time: 0.1410 2023/06/05 17:22:18 - mmengine - INFO - Epoch(train) [131][ 20/2569] lr: 4.0000e-03 eta: 3:47:58 time: 0.3775 data_time: 0.0489 memory: 5828 grad_norm: 5.0556 loss: 1.4661 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4661 2023/06/05 17:22:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:22:23 - mmengine - INFO - Epoch(train) [131][ 40/2569] lr: 4.0000e-03 eta: 3:47:53 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 5.1017 loss: 1.5980 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5980 2023/06/05 17:22:29 - mmengine - INFO - Epoch(train) [131][ 60/2569] lr: 4.0000e-03 eta: 3:47:47 time: 0.2627 data_time: 0.0077 memory: 5828 grad_norm: 5.0991 loss: 1.8407 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8407 2023/06/05 17:22:34 - mmengine - INFO - Epoch(train) [131][ 80/2569] lr: 4.0000e-03 eta: 3:47:42 time: 0.2706 data_time: 0.0072 memory: 5828 grad_norm: 5.0423 loss: 1.8684 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8684 2023/06/05 17:22:40 - mmengine - INFO - Epoch(train) [131][ 100/2569] lr: 4.0000e-03 eta: 3:47:37 time: 0.2688 data_time: 0.0071 memory: 5828 grad_norm: 5.1477 loss: 1.8321 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8321 2023/06/05 17:22:45 - mmengine - INFO - Epoch(train) [131][ 120/2569] lr: 4.0000e-03 eta: 3:47:31 time: 0.2639 data_time: 0.0071 memory: 5828 grad_norm: 5.1906 loss: 1.7557 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7557 2023/06/05 17:22:50 - mmengine - INFO - Epoch(train) [131][ 140/2569] lr: 4.0000e-03 eta: 3:47:26 time: 0.2680 data_time: 0.0072 memory: 5828 grad_norm: 5.0883 loss: 1.5580 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5580 2023/06/05 17:22:56 - mmengine - INFO - Epoch(train) [131][ 160/2569] lr: 4.0000e-03 eta: 3:47:21 time: 0.2664 data_time: 0.0071 memory: 5828 grad_norm: 5.2217 loss: 1.8766 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8766 2023/06/05 17:23:01 - mmengine - INFO - Epoch(train) [131][ 180/2569] lr: 4.0000e-03 eta: 3:47:15 time: 0.2709 data_time: 0.0071 memory: 5828 grad_norm: 5.2006 loss: 1.8129 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8129 2023/06/05 17:23:06 - mmengine - INFO - Epoch(train) [131][ 200/2569] lr: 4.0000e-03 eta: 3:47:10 time: 0.2662 data_time: 0.0069 memory: 5828 grad_norm: 5.1183 loss: 1.7445 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7445 2023/06/05 17:23:12 - mmengine - INFO - Epoch(train) [131][ 220/2569] lr: 4.0000e-03 eta: 3:47:05 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 5.0512 loss: 1.4671 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4671 2023/06/05 17:23:17 - mmengine - INFO - Epoch(train) [131][ 240/2569] lr: 4.0000e-03 eta: 3:46:59 time: 0.2700 data_time: 0.0072 memory: 5828 grad_norm: 5.1792 loss: 1.9319 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9319 2023/06/05 17:23:23 - mmengine - INFO - Epoch(train) [131][ 260/2569] lr: 4.0000e-03 eta: 3:46:54 time: 0.2713 data_time: 0.0070 memory: 5828 grad_norm: 5.1403 loss: 2.0745 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0745 2023/06/05 17:23:28 - mmengine - INFO - Epoch(train) [131][ 280/2569] lr: 4.0000e-03 eta: 3:46:49 time: 0.2698 data_time: 0.0071 memory: 5828 grad_norm: 4.9937 loss: 1.4356 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4356 2023/06/05 17:23:33 - mmengine - INFO - Epoch(train) [131][ 300/2569] lr: 4.0000e-03 eta: 3:46:44 time: 0.2757 data_time: 0.0073 memory: 5828 grad_norm: 5.2360 loss: 1.6989 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6989 2023/06/05 17:23:39 - mmengine - INFO - Epoch(train) [131][ 320/2569] lr: 4.0000e-03 eta: 3:46:38 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 5.1774 loss: 1.9308 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9308 2023/06/05 17:23:44 - mmengine - INFO - Epoch(train) [131][ 340/2569] lr: 4.0000e-03 eta: 3:46:33 time: 0.2687 data_time: 0.0070 memory: 5828 grad_norm: 5.1331 loss: 1.6728 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6728 2023/06/05 17:23:49 - mmengine - INFO - Epoch(train) [131][ 360/2569] lr: 4.0000e-03 eta: 3:46:28 time: 0.2672 data_time: 0.0071 memory: 5828 grad_norm: 5.1567 loss: 1.8997 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8997 2023/06/05 17:23:55 - mmengine - INFO - Epoch(train) [131][ 380/2569] lr: 4.0000e-03 eta: 3:46:22 time: 0.2649 data_time: 0.0075 memory: 5828 grad_norm: 5.1979 loss: 1.8593 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8593 2023/06/05 17:24:00 - mmengine - INFO - Epoch(train) [131][ 400/2569] lr: 4.0000e-03 eta: 3:46:17 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 5.1591 loss: 1.7802 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7802 2023/06/05 17:24:06 - mmengine - INFO - Epoch(train) [131][ 420/2569] lr: 4.0000e-03 eta: 3:46:12 time: 0.2722 data_time: 0.0072 memory: 5828 grad_norm: 5.0949 loss: 1.6724 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6724 2023/06/05 17:24:11 - mmengine - INFO - Epoch(train) [131][ 440/2569] lr: 4.0000e-03 eta: 3:46:06 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 5.1558 loss: 1.6106 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6106 2023/06/05 17:24:16 - mmengine - INFO - Epoch(train) [131][ 460/2569] lr: 4.0000e-03 eta: 3:46:01 time: 0.2661 data_time: 0.0075 memory: 5828 grad_norm: 5.0637 loss: 1.8299 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8299 2023/06/05 17:24:21 - mmengine - INFO - Epoch(train) [131][ 480/2569] lr: 4.0000e-03 eta: 3:45:56 time: 0.2636 data_time: 0.0079 memory: 5828 grad_norm: 5.1514 loss: 1.7298 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7298 2023/06/05 17:24:27 - mmengine - INFO - Epoch(train) [131][ 500/2569] lr: 4.0000e-03 eta: 3:45:50 time: 0.2649 data_time: 0.0070 memory: 5828 grad_norm: 5.1432 loss: 1.5007 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5007 2023/06/05 17:24:32 - mmengine - INFO - Epoch(train) [131][ 520/2569] lr: 4.0000e-03 eta: 3:45:45 time: 0.2736 data_time: 0.0071 memory: 5828 grad_norm: 5.0856 loss: 1.8301 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8301 2023/06/05 17:24:38 - mmengine - INFO - Epoch(train) [131][ 540/2569] lr: 4.0000e-03 eta: 3:45:40 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 5.1306 loss: 1.8338 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8338 2023/06/05 17:24:43 - mmengine - INFO - Epoch(train) [131][ 560/2569] lr: 4.0000e-03 eta: 3:45:34 time: 0.2715 data_time: 0.0070 memory: 5828 grad_norm: 5.0573 loss: 1.6781 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6781 2023/06/05 17:24:48 - mmengine - INFO - Epoch(train) [131][ 580/2569] lr: 4.0000e-03 eta: 3:45:29 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 5.0612 loss: 1.6068 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6068 2023/06/05 17:24:54 - mmengine - INFO - Epoch(train) [131][ 600/2569] lr: 4.0000e-03 eta: 3:45:24 time: 0.2698 data_time: 0.0073 memory: 5828 grad_norm: 5.2119 loss: 1.6649 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6649 2023/06/05 17:24:59 - mmengine - INFO - Epoch(train) [131][ 620/2569] lr: 4.0000e-03 eta: 3:45:18 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 5.1156 loss: 2.0580 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0580 2023/06/05 17:25:04 - mmengine - INFO - Epoch(train) [131][ 640/2569] lr: 4.0000e-03 eta: 3:45:13 time: 0.2714 data_time: 0.0072 memory: 5828 grad_norm: 5.1210 loss: 1.7500 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7500 2023/06/05 17:25:10 - mmengine - INFO - Epoch(train) [131][ 660/2569] lr: 4.0000e-03 eta: 3:45:08 time: 0.2712 data_time: 0.0074 memory: 5828 grad_norm: 5.0906 loss: 1.4767 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4767 2023/06/05 17:25:15 - mmengine - INFO - Epoch(train) [131][ 680/2569] lr: 4.0000e-03 eta: 3:45:02 time: 0.2657 data_time: 0.0070 memory: 5828 grad_norm: 5.1747 loss: 1.9317 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9317 2023/06/05 17:25:21 - mmengine - INFO - Epoch(train) [131][ 700/2569] lr: 4.0000e-03 eta: 3:44:57 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 5.1527 loss: 1.6969 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6969 2023/06/05 17:25:26 - mmengine - INFO - Epoch(train) [131][ 720/2569] lr: 4.0000e-03 eta: 3:44:52 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 5.2493 loss: 1.5909 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5909 2023/06/05 17:25:31 - mmengine - INFO - Epoch(train) [131][ 740/2569] lr: 4.0000e-03 eta: 3:44:46 time: 0.2642 data_time: 0.0072 memory: 5828 grad_norm: 5.0919 loss: 2.0084 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0084 2023/06/05 17:25:37 - mmengine - INFO - Epoch(train) [131][ 760/2569] lr: 4.0000e-03 eta: 3:44:41 time: 0.2749 data_time: 0.0076 memory: 5828 grad_norm: 5.2356 loss: 2.1670 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 2.1670 2023/06/05 17:25:42 - mmengine - INFO - Epoch(train) [131][ 780/2569] lr: 4.0000e-03 eta: 3:44:36 time: 0.2677 data_time: 0.0073 memory: 5828 grad_norm: 5.1147 loss: 1.9531 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9531 2023/06/05 17:25:48 - mmengine - INFO - Epoch(train) [131][ 800/2569] lr: 4.0000e-03 eta: 3:44:30 time: 0.2727 data_time: 0.0073 memory: 5828 grad_norm: 5.1536 loss: 1.9572 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9572 2023/06/05 17:25:53 - mmengine - INFO - Epoch(train) [131][ 820/2569] lr: 4.0000e-03 eta: 3:44:25 time: 0.2704 data_time: 0.0073 memory: 5828 grad_norm: 4.9981 loss: 1.8418 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8418 2023/06/05 17:25:58 - mmengine - INFO - Epoch(train) [131][ 840/2569] lr: 4.0000e-03 eta: 3:44:20 time: 0.2717 data_time: 0.0074 memory: 5828 grad_norm: 5.2519 loss: 1.3763 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3763 2023/06/05 17:26:04 - mmengine - INFO - Epoch(train) [131][ 860/2569] lr: 4.0000e-03 eta: 3:44:14 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 5.1224 loss: 1.6139 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6139 2023/06/05 17:26:09 - mmengine - INFO - Epoch(train) [131][ 880/2569] lr: 4.0000e-03 eta: 3:44:09 time: 0.2785 data_time: 0.0072 memory: 5828 grad_norm: 5.0971 loss: 1.6514 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6514 2023/06/05 17:26:15 - mmengine - INFO - Epoch(train) [131][ 900/2569] lr: 4.0000e-03 eta: 3:44:04 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 5.0630 loss: 2.1200 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1200 2023/06/05 17:26:20 - mmengine - INFO - Epoch(train) [131][ 920/2569] lr: 4.0000e-03 eta: 3:43:59 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 5.1259 loss: 2.0049 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0049 2023/06/05 17:26:25 - mmengine - INFO - Epoch(train) [131][ 940/2569] lr: 4.0000e-03 eta: 3:43:53 time: 0.2609 data_time: 0.0072 memory: 5828 grad_norm: 5.1002 loss: 1.9261 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9261 2023/06/05 17:26:31 - mmengine - INFO - Epoch(train) [131][ 960/2569] lr: 4.0000e-03 eta: 3:43:48 time: 0.2750 data_time: 0.0071 memory: 5828 grad_norm: 5.1526 loss: 1.7541 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7541 2023/06/05 17:26:36 - mmengine - INFO - Epoch(train) [131][ 980/2569] lr: 4.0000e-03 eta: 3:43:43 time: 0.2639 data_time: 0.0072 memory: 5828 grad_norm: 5.1932 loss: 1.7840 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7840 2023/06/05 17:26:42 - mmengine - INFO - Epoch(train) [131][1000/2569] lr: 4.0000e-03 eta: 3:43:37 time: 0.2752 data_time: 0.0071 memory: 5828 grad_norm: 5.1699 loss: 1.5438 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5438 2023/06/05 17:26:47 - mmengine - INFO - Epoch(train) [131][1020/2569] lr: 4.0000e-03 eta: 3:43:32 time: 0.2763 data_time: 0.0072 memory: 5828 grad_norm: 5.2166 loss: 1.9756 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9756 2023/06/05 17:26:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:26:52 - mmengine - INFO - Epoch(train) [131][1040/2569] lr: 4.0000e-03 eta: 3:43:27 time: 0.2666 data_time: 0.0075 memory: 5828 grad_norm: 5.1500 loss: 1.8459 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8459 2023/06/05 17:26:58 - mmengine - INFO - Epoch(train) [131][1060/2569] lr: 4.0000e-03 eta: 3:43:21 time: 0.2697 data_time: 0.0070 memory: 5828 grad_norm: 5.1672 loss: 1.7003 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7003 2023/06/05 17:27:03 - mmengine - INFO - Epoch(train) [131][1080/2569] lr: 4.0000e-03 eta: 3:43:16 time: 0.2692 data_time: 0.0075 memory: 5828 grad_norm: 5.2034 loss: 1.9519 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9519 2023/06/05 17:27:09 - mmengine - INFO - Epoch(train) [131][1100/2569] lr: 4.0000e-03 eta: 3:43:11 time: 0.2693 data_time: 0.0071 memory: 5828 grad_norm: 5.0703 loss: 1.5479 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5479 2023/06/05 17:27:14 - mmengine - INFO - Epoch(train) [131][1120/2569] lr: 4.0000e-03 eta: 3:43:05 time: 0.2630 data_time: 0.0073 memory: 5828 grad_norm: 5.0496 loss: 1.7925 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7925 2023/06/05 17:27:19 - mmengine - INFO - Epoch(train) [131][1140/2569] lr: 4.0000e-03 eta: 3:43:00 time: 0.2696 data_time: 0.0073 memory: 5828 grad_norm: 5.0594 loss: 1.6412 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6412 2023/06/05 17:27:25 - mmengine - INFO - Epoch(train) [131][1160/2569] lr: 4.0000e-03 eta: 3:42:55 time: 0.2658 data_time: 0.0070 memory: 5828 grad_norm: 5.0606 loss: 1.3753 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.3753 2023/06/05 17:27:30 - mmengine - INFO - Epoch(train) [131][1180/2569] lr: 4.0000e-03 eta: 3:42:49 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 5.1040 loss: 1.5241 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5241 2023/06/05 17:27:35 - mmengine - INFO - Epoch(train) [131][1200/2569] lr: 4.0000e-03 eta: 3:42:44 time: 0.2714 data_time: 0.0077 memory: 5828 grad_norm: 5.1704 loss: 1.8687 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8687 2023/06/05 17:27:41 - mmengine - INFO - Epoch(train) [131][1220/2569] lr: 4.0000e-03 eta: 3:42:39 time: 0.2616 data_time: 0.0070 memory: 5828 grad_norm: 5.0839 loss: 1.8739 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8739 2023/06/05 17:27:46 - mmengine - INFO - Epoch(train) [131][1240/2569] lr: 4.0000e-03 eta: 3:42:33 time: 0.2665 data_time: 0.0073 memory: 5828 grad_norm: 5.1590 loss: 1.8058 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8058 2023/06/05 17:27:51 - mmengine - INFO - Epoch(train) [131][1260/2569] lr: 4.0000e-03 eta: 3:42:28 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 4.9803 loss: 1.8357 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8357 2023/06/05 17:27:57 - mmengine - INFO - Epoch(train) [131][1280/2569] lr: 4.0000e-03 eta: 3:42:23 time: 0.2607 data_time: 0.0072 memory: 5828 grad_norm: 5.1506 loss: 1.7800 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7800 2023/06/05 17:28:02 - mmengine - INFO - Epoch(train) [131][1300/2569] lr: 4.0000e-03 eta: 3:42:17 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 5.1534 loss: 2.0205 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0205 2023/06/05 17:28:07 - mmengine - INFO - Epoch(train) [131][1320/2569] lr: 4.0000e-03 eta: 3:42:12 time: 0.2752 data_time: 0.0075 memory: 5828 grad_norm: 5.2614 loss: 1.6030 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6030 2023/06/05 17:28:13 - mmengine - INFO - Epoch(train) [131][1340/2569] lr: 4.0000e-03 eta: 3:42:07 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 5.1884 loss: 1.6289 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6289 2023/06/05 17:28:18 - mmengine - INFO - Epoch(train) [131][1360/2569] lr: 4.0000e-03 eta: 3:42:01 time: 0.2634 data_time: 0.0078 memory: 5828 grad_norm: 5.2200 loss: 1.8208 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8208 2023/06/05 17:28:23 - mmengine - INFO - Epoch(train) [131][1380/2569] lr: 4.0000e-03 eta: 3:41:56 time: 0.2723 data_time: 0.0083 memory: 5828 grad_norm: 5.1617 loss: 1.9813 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9813 2023/06/05 17:28:29 - mmengine - INFO - Epoch(train) [131][1400/2569] lr: 4.0000e-03 eta: 3:41:51 time: 0.2611 data_time: 0.0075 memory: 5828 grad_norm: 5.1044 loss: 1.5345 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5345 2023/06/05 17:28:34 - mmengine - INFO - Epoch(train) [131][1420/2569] lr: 4.0000e-03 eta: 3:41:45 time: 0.2709 data_time: 0.0073 memory: 5828 grad_norm: 5.1100 loss: 1.5872 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5872 2023/06/05 17:28:40 - mmengine - INFO - Epoch(train) [131][1440/2569] lr: 4.0000e-03 eta: 3:41:40 time: 0.2761 data_time: 0.0073 memory: 5828 grad_norm: 5.1312 loss: 1.7299 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7299 2023/06/05 17:28:45 - mmengine - INFO - Epoch(train) [131][1460/2569] lr: 4.0000e-03 eta: 3:41:35 time: 0.2731 data_time: 0.0069 memory: 5828 grad_norm: 5.1167 loss: 1.5294 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5294 2023/06/05 17:28:51 - mmengine - INFO - Epoch(train) [131][1480/2569] lr: 4.0000e-03 eta: 3:41:30 time: 0.2767 data_time: 0.0071 memory: 5828 grad_norm: 5.1329 loss: 1.6538 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6538 2023/06/05 17:28:56 - mmengine - INFO - Epoch(train) [131][1500/2569] lr: 4.0000e-03 eta: 3:41:24 time: 0.2770 data_time: 0.0070 memory: 5828 grad_norm: 5.0273 loss: 1.7820 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7820 2023/06/05 17:29:01 - mmengine - INFO - Epoch(train) [131][1520/2569] lr: 4.0000e-03 eta: 3:41:19 time: 0.2630 data_time: 0.0071 memory: 5828 grad_norm: 5.2197 loss: 1.5782 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5782 2023/06/05 17:29:07 - mmengine - INFO - Epoch(train) [131][1540/2569] lr: 4.0000e-03 eta: 3:41:14 time: 0.2802 data_time: 0.0073 memory: 5828 grad_norm: 5.2295 loss: 1.8687 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8687 2023/06/05 17:29:12 - mmengine - INFO - Epoch(train) [131][1560/2569] lr: 4.0000e-03 eta: 3:41:08 time: 0.2678 data_time: 0.0077 memory: 5828 grad_norm: 5.1987 loss: 1.6599 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6599 2023/06/05 17:29:18 - mmengine - INFO - Epoch(train) [131][1580/2569] lr: 4.0000e-03 eta: 3:41:03 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 5.1734 loss: 1.5649 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5649 2023/06/05 17:29:23 - mmengine - INFO - Epoch(train) [131][1600/2569] lr: 4.0000e-03 eta: 3:40:58 time: 0.2761 data_time: 0.0073 memory: 5828 grad_norm: 5.1929 loss: 1.9241 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9241 2023/06/05 17:29:29 - mmengine - INFO - Epoch(train) [131][1620/2569] lr: 4.0000e-03 eta: 3:40:52 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 5.1072 loss: 1.9516 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9516 2023/06/05 17:29:34 - mmengine - INFO - Epoch(train) [131][1640/2569] lr: 4.0000e-03 eta: 3:40:47 time: 0.2714 data_time: 0.0073 memory: 5828 grad_norm: 5.1943 loss: 1.8714 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.8714 2023/06/05 17:29:40 - mmengine - INFO - Epoch(train) [131][1660/2569] lr: 4.0000e-03 eta: 3:40:42 time: 0.2705 data_time: 0.0075 memory: 5828 grad_norm: 5.1999 loss: 1.6927 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6927 2023/06/05 17:29:45 - mmengine - INFO - Epoch(train) [131][1680/2569] lr: 4.0000e-03 eta: 3:40:36 time: 0.2695 data_time: 0.0073 memory: 5828 grad_norm: 5.1254 loss: 1.4623 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4623 2023/06/05 17:29:50 - mmengine - INFO - Epoch(train) [131][1700/2569] lr: 4.0000e-03 eta: 3:40:31 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 5.1583 loss: 1.8964 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8964 2023/06/05 17:29:56 - mmengine - INFO - Epoch(train) [131][1720/2569] lr: 4.0000e-03 eta: 3:40:26 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 5.0777 loss: 1.5774 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5774 2023/06/05 17:30:01 - mmengine - INFO - Epoch(train) [131][1740/2569] lr: 4.0000e-03 eta: 3:40:20 time: 0.2692 data_time: 0.0072 memory: 5828 grad_norm: 5.0604 loss: 1.8298 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8298 2023/06/05 17:30:06 - mmengine - INFO - Epoch(train) [131][1760/2569] lr: 4.0000e-03 eta: 3:40:15 time: 0.2688 data_time: 0.0076 memory: 5828 grad_norm: 5.1570 loss: 1.6500 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6500 2023/06/05 17:30:12 - mmengine - INFO - Epoch(train) [131][1780/2569] lr: 4.0000e-03 eta: 3:40:10 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 5.2225 loss: 1.5259 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5259 2023/06/05 17:30:17 - mmengine - INFO - Epoch(train) [131][1800/2569] lr: 4.0000e-03 eta: 3:40:05 time: 0.2714 data_time: 0.0075 memory: 5828 grad_norm: 5.2100 loss: 1.8530 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8530 2023/06/05 17:30:23 - mmengine - INFO - Epoch(train) [131][1820/2569] lr: 4.0000e-03 eta: 3:39:59 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 5.1304 loss: 1.6034 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6034 2023/06/05 17:30:28 - mmengine - INFO - Epoch(train) [131][1840/2569] lr: 4.0000e-03 eta: 3:39:54 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 5.1162 loss: 1.6269 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6269 2023/06/05 17:30:33 - mmengine - INFO - Epoch(train) [131][1860/2569] lr: 4.0000e-03 eta: 3:39:49 time: 0.2757 data_time: 0.0074 memory: 5828 grad_norm: 5.2203 loss: 1.9976 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9976 2023/06/05 17:30:39 - mmengine - INFO - Epoch(train) [131][1880/2569] lr: 4.0000e-03 eta: 3:39:43 time: 0.2748 data_time: 0.0078 memory: 5828 grad_norm: 5.1668 loss: 1.8219 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8219 2023/06/05 17:30:44 - mmengine - INFO - Epoch(train) [131][1900/2569] lr: 4.0000e-03 eta: 3:39:38 time: 0.2696 data_time: 0.0073 memory: 5828 grad_norm: 5.1836 loss: 1.7301 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7301 2023/06/05 17:30:50 - mmengine - INFO - Epoch(train) [131][1920/2569] lr: 4.0000e-03 eta: 3:39:33 time: 0.2763 data_time: 0.0075 memory: 5828 grad_norm: 5.1922 loss: 1.5979 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5979 2023/06/05 17:30:55 - mmengine - INFO - Epoch(train) [131][1940/2569] lr: 4.0000e-03 eta: 3:39:27 time: 0.2666 data_time: 0.0078 memory: 5828 grad_norm: 5.2364 loss: 1.7741 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7741 2023/06/05 17:31:01 - mmengine - INFO - Epoch(train) [131][1960/2569] lr: 4.0000e-03 eta: 3:39:22 time: 0.2805 data_time: 0.0072 memory: 5828 grad_norm: 5.1802 loss: 1.7011 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7011 2023/06/05 17:31:06 - mmengine - INFO - Epoch(train) [131][1980/2569] lr: 4.0000e-03 eta: 3:39:17 time: 0.2694 data_time: 0.0075 memory: 5828 grad_norm: 5.1442 loss: 2.0179 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0179 2023/06/05 17:31:12 - mmengine - INFO - Epoch(train) [131][2000/2569] lr: 4.0000e-03 eta: 3:39:11 time: 0.2687 data_time: 0.0072 memory: 5828 grad_norm: 5.1936 loss: 1.5327 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5327 2023/06/05 17:31:17 - mmengine - INFO - Epoch(train) [131][2020/2569] lr: 4.0000e-03 eta: 3:39:06 time: 0.2775 data_time: 0.0075 memory: 5828 grad_norm: 5.1634 loss: 1.4239 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4239 2023/06/05 17:31:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:31:23 - mmengine - INFO - Epoch(train) [131][2040/2569] lr: 4.0000e-03 eta: 3:39:01 time: 0.2704 data_time: 0.0078 memory: 5828 grad_norm: 5.2465 loss: 1.9221 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9221 2023/06/05 17:31:28 - mmengine - INFO - Epoch(train) [131][2060/2569] lr: 4.0000e-03 eta: 3:38:55 time: 0.2761 data_time: 0.0081 memory: 5828 grad_norm: 5.2025 loss: 1.5777 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5777 2023/06/05 17:31:34 - mmengine - INFO - Epoch(train) [131][2080/2569] lr: 4.0000e-03 eta: 3:38:50 time: 0.2697 data_time: 0.0072 memory: 5828 grad_norm: 5.2577 loss: 1.6066 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6066 2023/06/05 17:31:39 - mmengine - INFO - Epoch(train) [131][2100/2569] lr: 4.0000e-03 eta: 3:38:45 time: 0.2656 data_time: 0.0072 memory: 5828 grad_norm: 5.1593 loss: 1.8991 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8991 2023/06/05 17:31:44 - mmengine - INFO - Epoch(train) [131][2120/2569] lr: 4.0000e-03 eta: 3:38:40 time: 0.2684 data_time: 0.0082 memory: 5828 grad_norm: 5.1852 loss: 1.8214 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8214 2023/06/05 17:31:50 - mmengine - INFO - Epoch(train) [131][2140/2569] lr: 4.0000e-03 eta: 3:38:34 time: 0.2701 data_time: 0.0076 memory: 5828 grad_norm: 5.0958 loss: 1.7864 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7864 2023/06/05 17:31:55 - mmengine - INFO - Epoch(train) [131][2160/2569] lr: 4.0000e-03 eta: 3:38:29 time: 0.2676 data_time: 0.0074 memory: 5828 grad_norm: 5.2873 loss: 1.6595 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6595 2023/06/05 17:32:00 - mmengine - INFO - Epoch(train) [131][2180/2569] lr: 4.0000e-03 eta: 3:38:24 time: 0.2713 data_time: 0.0076 memory: 5828 grad_norm: 5.1938 loss: 1.8075 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8075 2023/06/05 17:32:06 - mmengine - INFO - Epoch(train) [131][2200/2569] lr: 4.0000e-03 eta: 3:38:18 time: 0.2817 data_time: 0.0077 memory: 5828 grad_norm: 5.0790 loss: 1.8691 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8691 2023/06/05 17:32:12 - mmengine - INFO - Epoch(train) [131][2220/2569] lr: 4.0000e-03 eta: 3:38:13 time: 0.2720 data_time: 0.0071 memory: 5828 grad_norm: 5.1293 loss: 1.7925 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7925 2023/06/05 17:32:17 - mmengine - INFO - Epoch(train) [131][2240/2569] lr: 4.0000e-03 eta: 3:38:08 time: 0.2721 data_time: 0.0075 memory: 5828 grad_norm: 5.0899 loss: 1.5020 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5020 2023/06/05 17:32:23 - mmengine - INFO - Epoch(train) [131][2260/2569] lr: 4.0000e-03 eta: 3:38:02 time: 0.2840 data_time: 0.0077 memory: 5828 grad_norm: 5.1754 loss: 1.8545 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8545 2023/06/05 17:32:28 - mmengine - INFO - Epoch(train) [131][2280/2569] lr: 4.0000e-03 eta: 3:37:57 time: 0.2669 data_time: 0.0081 memory: 5828 grad_norm: 5.1797 loss: 1.7038 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7038 2023/06/05 17:32:33 - mmengine - INFO - Epoch(train) [131][2300/2569] lr: 4.0000e-03 eta: 3:37:52 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 5.0814 loss: 1.9872 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9872 2023/06/05 17:32:39 - mmengine - INFO - Epoch(train) [131][2320/2569] lr: 4.0000e-03 eta: 3:37:46 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 5.2676 loss: 1.4821 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4821 2023/06/05 17:32:44 - mmengine - INFO - Epoch(train) [131][2340/2569] lr: 4.0000e-03 eta: 3:37:41 time: 0.2721 data_time: 0.0072 memory: 5828 grad_norm: 5.2408 loss: 1.6708 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6708 2023/06/05 17:32:50 - mmengine - INFO - Epoch(train) [131][2360/2569] lr: 4.0000e-03 eta: 3:37:36 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 5.2027 loss: 1.9099 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.9099 2023/06/05 17:32:55 - mmengine - INFO - Epoch(train) [131][2380/2569] lr: 4.0000e-03 eta: 3:37:30 time: 0.2666 data_time: 0.0078 memory: 5828 grad_norm: 5.1651 loss: 1.6546 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6546 2023/06/05 17:33:00 - mmengine - INFO - Epoch(train) [131][2400/2569] lr: 4.0000e-03 eta: 3:37:25 time: 0.2718 data_time: 0.0072 memory: 5828 grad_norm: 5.1163 loss: 1.6713 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6713 2023/06/05 17:33:06 - mmengine - INFO - Epoch(train) [131][2420/2569] lr: 4.0000e-03 eta: 3:37:20 time: 0.2755 data_time: 0.0077 memory: 5828 grad_norm: 5.2887 loss: 1.7224 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7224 2023/06/05 17:33:11 - mmengine - INFO - Epoch(train) [131][2440/2569] lr: 4.0000e-03 eta: 3:37:15 time: 0.2666 data_time: 0.0080 memory: 5828 grad_norm: 5.0721 loss: 1.5700 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5700 2023/06/05 17:33:17 - mmengine - INFO - Epoch(train) [131][2460/2569] lr: 4.0000e-03 eta: 3:37:09 time: 0.2685 data_time: 0.0077 memory: 5828 grad_norm: 5.2562 loss: 1.6915 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6915 2023/06/05 17:33:22 - mmengine - INFO - Epoch(train) [131][2480/2569] lr: 4.0000e-03 eta: 3:37:04 time: 0.2670 data_time: 0.0078 memory: 5828 grad_norm: 5.1214 loss: 1.5145 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5145 2023/06/05 17:33:28 - mmengine - INFO - Epoch(train) [131][2500/2569] lr: 4.0000e-03 eta: 3:36:59 time: 0.2774 data_time: 0.0076 memory: 5828 grad_norm: 5.2319 loss: 1.8176 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8176 2023/06/05 17:33:33 - mmengine - INFO - Epoch(train) [131][2520/2569] lr: 4.0000e-03 eta: 3:36:53 time: 0.2698 data_time: 0.0075 memory: 5828 grad_norm: 5.1045 loss: 1.6425 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6425 2023/06/05 17:33:38 - mmengine - INFO - Epoch(train) [131][2540/2569] lr: 4.0000e-03 eta: 3:36:48 time: 0.2715 data_time: 0.0074 memory: 5828 grad_norm: 5.2215 loss: 1.8546 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.8546 2023/06/05 17:33:44 - mmengine - INFO - Epoch(train) [131][2560/2569] lr: 4.0000e-03 eta: 3:36:43 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 5.1951 loss: 1.7446 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7446 2023/06/05 17:33:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:33:46 - mmengine - INFO - Epoch(train) [131][2569/2569] lr: 4.0000e-03 eta: 3:36:40 time: 0.2552 data_time: 0.0072 memory: 5828 grad_norm: 5.3221 loss: 1.7912 top1_acc: 0.5000 top5_acc: 0.6667 loss_cls: 1.7912 2023/06/05 17:33:53 - mmengine - INFO - Epoch(train) [132][ 20/2569] lr: 4.0000e-03 eta: 3:36:35 time: 0.3364 data_time: 0.0565 memory: 5828 grad_norm: 5.1364 loss: 1.6443 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6443 2023/06/05 17:33:58 - mmengine - INFO - Epoch(train) [132][ 40/2569] lr: 4.0000e-03 eta: 3:36:30 time: 0.2668 data_time: 0.0075 memory: 5828 grad_norm: 5.2762 loss: 1.6176 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6176 2023/06/05 17:34:03 - mmengine - INFO - Epoch(train) [132][ 60/2569] lr: 4.0000e-03 eta: 3:36:24 time: 0.2690 data_time: 0.0076 memory: 5828 grad_norm: 5.2218 loss: 1.8762 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8762 2023/06/05 17:34:09 - mmengine - INFO - Epoch(train) [132][ 80/2569] lr: 4.0000e-03 eta: 3:36:19 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 5.1609 loss: 1.7342 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7342 2023/06/05 17:34:14 - mmengine - INFO - Epoch(train) [132][ 100/2569] lr: 4.0000e-03 eta: 3:36:14 time: 0.2650 data_time: 0.0076 memory: 5828 grad_norm: 5.2046 loss: 1.5867 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5867 2023/06/05 17:34:19 - mmengine - INFO - Epoch(train) [132][ 120/2569] lr: 4.0000e-03 eta: 3:36:08 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 5.2158 loss: 1.7148 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7148 2023/06/05 17:34:25 - mmengine - INFO - Epoch(train) [132][ 140/2569] lr: 4.0000e-03 eta: 3:36:03 time: 0.2673 data_time: 0.0077 memory: 5828 grad_norm: 5.2550 loss: 1.9736 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9736 2023/06/05 17:34:30 - mmengine - INFO - Epoch(train) [132][ 160/2569] lr: 4.0000e-03 eta: 3:35:58 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 5.1274 loss: 1.7763 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7763 2023/06/05 17:34:36 - mmengine - INFO - Epoch(train) [132][ 180/2569] lr: 4.0000e-03 eta: 3:35:52 time: 0.2744 data_time: 0.0079 memory: 5828 grad_norm: 4.9724 loss: 1.5591 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5591 2023/06/05 17:34:41 - mmengine - INFO - Epoch(train) [132][ 200/2569] lr: 4.0000e-03 eta: 3:35:47 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 5.2300 loss: 1.9575 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9575 2023/06/05 17:34:46 - mmengine - INFO - Epoch(train) [132][ 220/2569] lr: 4.0000e-03 eta: 3:35:42 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 5.1185 loss: 1.6539 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6539 2023/06/05 17:34:51 - mmengine - INFO - Epoch(train) [132][ 240/2569] lr: 4.0000e-03 eta: 3:35:36 time: 0.2624 data_time: 0.0077 memory: 5828 grad_norm: 5.0988 loss: 1.9779 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9779 2023/06/05 17:34:57 - mmengine - INFO - Epoch(train) [132][ 260/2569] lr: 4.0000e-03 eta: 3:35:31 time: 0.2680 data_time: 0.0077 memory: 5828 grad_norm: 5.1396 loss: 1.6958 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6958 2023/06/05 17:35:02 - mmengine - INFO - Epoch(train) [132][ 280/2569] lr: 4.0000e-03 eta: 3:35:26 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 5.1359 loss: 1.8905 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8905 2023/06/05 17:35:07 - mmengine - INFO - Epoch(train) [132][ 300/2569] lr: 4.0000e-03 eta: 3:35:21 time: 0.2687 data_time: 0.0072 memory: 5828 grad_norm: 5.1171 loss: 1.6537 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6537 2023/06/05 17:35:13 - mmengine - INFO - Epoch(train) [132][ 320/2569] lr: 4.0000e-03 eta: 3:35:15 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 5.1400 loss: 1.7915 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.7915 2023/06/05 17:35:18 - mmengine - INFO - Epoch(train) [132][ 340/2569] lr: 4.0000e-03 eta: 3:35:10 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 5.0660 loss: 1.8790 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8790 2023/06/05 17:35:23 - mmengine - INFO - Epoch(train) [132][ 360/2569] lr: 4.0000e-03 eta: 3:35:05 time: 0.2608 data_time: 0.0070 memory: 5828 grad_norm: 5.2455 loss: 1.6035 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6035 2023/06/05 17:35:29 - mmengine - INFO - Epoch(train) [132][ 380/2569] lr: 4.0000e-03 eta: 3:34:59 time: 0.2626 data_time: 0.0072 memory: 5828 grad_norm: 5.1237 loss: 1.6597 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6597 2023/06/05 17:35:34 - mmengine - INFO - Epoch(train) [132][ 400/2569] lr: 4.0000e-03 eta: 3:34:54 time: 0.2741 data_time: 0.0070 memory: 5828 grad_norm: 5.1286 loss: 1.5008 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5008 2023/06/05 17:35:40 - mmengine - INFO - Epoch(train) [132][ 420/2569] lr: 4.0000e-03 eta: 3:34:49 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 5.1302 loss: 1.9473 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9473 2023/06/05 17:35:45 - mmengine - INFO - Epoch(train) [132][ 440/2569] lr: 4.0000e-03 eta: 3:34:43 time: 0.2684 data_time: 0.0075 memory: 5828 grad_norm: 5.1799 loss: 1.6251 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6251 2023/06/05 17:35:50 - mmengine - INFO - Epoch(train) [132][ 460/2569] lr: 4.0000e-03 eta: 3:34:38 time: 0.2669 data_time: 0.0069 memory: 5828 grad_norm: 5.2530 loss: 1.6777 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6777 2023/06/05 17:35:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:35:56 - mmengine - INFO - Epoch(train) [132][ 480/2569] lr: 4.0000e-03 eta: 3:34:33 time: 0.2729 data_time: 0.0074 memory: 5828 grad_norm: 5.1604 loss: 1.8447 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8447 2023/06/05 17:36:01 - mmengine - INFO - Epoch(train) [132][ 500/2569] lr: 4.0000e-03 eta: 3:34:27 time: 0.2688 data_time: 0.0072 memory: 5828 grad_norm: 5.2492 loss: 1.4825 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4825 2023/06/05 17:36:06 - mmengine - INFO - Epoch(train) [132][ 520/2569] lr: 4.0000e-03 eta: 3:34:22 time: 0.2662 data_time: 0.0073 memory: 5828 grad_norm: 5.2551 loss: 1.7704 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7704 2023/06/05 17:36:12 - mmengine - INFO - Epoch(train) [132][ 540/2569] lr: 4.0000e-03 eta: 3:34:17 time: 0.2781 data_time: 0.0074 memory: 5828 grad_norm: 5.1977 loss: 1.8316 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8316 2023/06/05 17:36:17 - mmengine - INFO - Epoch(train) [132][ 560/2569] lr: 4.0000e-03 eta: 3:34:11 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 5.1983 loss: 1.7084 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7084 2023/06/05 17:36:23 - mmengine - INFO - Epoch(train) [132][ 580/2569] lr: 4.0000e-03 eta: 3:34:06 time: 0.2682 data_time: 0.0072 memory: 5828 grad_norm: 5.1459 loss: 1.7023 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7023 2023/06/05 17:36:28 - mmengine - INFO - Epoch(train) [132][ 600/2569] lr: 4.0000e-03 eta: 3:34:01 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 5.2206 loss: 1.9530 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9530 2023/06/05 17:36:33 - mmengine - INFO - Epoch(train) [132][ 620/2569] lr: 4.0000e-03 eta: 3:33:55 time: 0.2637 data_time: 0.0075 memory: 5828 grad_norm: 5.2074 loss: 1.8191 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8191 2023/06/05 17:36:39 - mmengine - INFO - Epoch(train) [132][ 640/2569] lr: 4.0000e-03 eta: 3:33:50 time: 0.2738 data_time: 0.0076 memory: 5828 grad_norm: 5.2568 loss: 1.8944 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8944 2023/06/05 17:36:44 - mmengine - INFO - Epoch(train) [132][ 660/2569] lr: 4.0000e-03 eta: 3:33:45 time: 0.2699 data_time: 0.0071 memory: 5828 grad_norm: 5.2210 loss: 1.6105 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6105 2023/06/05 17:36:50 - mmengine - INFO - Epoch(train) [132][ 680/2569] lr: 4.0000e-03 eta: 3:33:39 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 5.0463 loss: 1.7172 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7172 2023/06/05 17:36:55 - mmengine - INFO - Epoch(train) [132][ 700/2569] lr: 4.0000e-03 eta: 3:33:34 time: 0.2689 data_time: 0.0071 memory: 5828 grad_norm: 5.2135 loss: 2.0160 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0160 2023/06/05 17:37:01 - mmengine - INFO - Epoch(train) [132][ 720/2569] lr: 4.0000e-03 eta: 3:33:29 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 5.2849 loss: 1.6717 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6717 2023/06/05 17:37:06 - mmengine - INFO - Epoch(train) [132][ 740/2569] lr: 4.0000e-03 eta: 3:33:23 time: 0.2620 data_time: 0.0074 memory: 5828 grad_norm: 5.1272 loss: 1.8293 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8293 2023/06/05 17:37:11 - mmengine - INFO - Epoch(train) [132][ 760/2569] lr: 4.0000e-03 eta: 3:33:18 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 5.0838 loss: 1.4346 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.4346 2023/06/05 17:37:16 - mmengine - INFO - Epoch(train) [132][ 780/2569] lr: 4.0000e-03 eta: 3:33:13 time: 0.2668 data_time: 0.0071 memory: 5828 grad_norm: 5.1933 loss: 1.7475 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7475 2023/06/05 17:37:22 - mmengine - INFO - Epoch(train) [132][ 800/2569] lr: 4.0000e-03 eta: 3:33:07 time: 0.2729 data_time: 0.0071 memory: 5828 grad_norm: 5.1023 loss: 1.6240 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6240 2023/06/05 17:37:27 - mmengine - INFO - Epoch(train) [132][ 820/2569] lr: 4.0000e-03 eta: 3:33:02 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 5.2343 loss: 1.7675 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7675 2023/06/05 17:37:33 - mmengine - INFO - Epoch(train) [132][ 840/2569] lr: 4.0000e-03 eta: 3:32:57 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 5.2298 loss: 1.4517 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4517 2023/06/05 17:37:38 - mmengine - INFO - Epoch(train) [132][ 860/2569] lr: 4.0000e-03 eta: 3:32:51 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 5.3200 loss: 1.7534 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7534 2023/06/05 17:37:43 - mmengine - INFO - Epoch(train) [132][ 880/2569] lr: 4.0000e-03 eta: 3:32:46 time: 0.2690 data_time: 0.0072 memory: 5828 grad_norm: 5.2511 loss: 2.0063 top1_acc: 0.2500 top5_acc: 1.0000 loss_cls: 2.0063 2023/06/05 17:37:48 - mmengine - INFO - Epoch(train) [132][ 900/2569] lr: 4.0000e-03 eta: 3:32:41 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 5.2513 loss: 1.8890 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8890 2023/06/05 17:37:54 - mmengine - INFO - Epoch(train) [132][ 920/2569] lr: 4.0000e-03 eta: 3:32:36 time: 0.2771 data_time: 0.0072 memory: 5828 grad_norm: 5.1044 loss: 1.7285 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7285 2023/06/05 17:38:00 - mmengine - INFO - Epoch(train) [132][ 940/2569] lr: 4.0000e-03 eta: 3:32:30 time: 0.2733 data_time: 0.0071 memory: 5828 grad_norm: 5.2375 loss: 1.7385 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7385 2023/06/05 17:38:05 - mmengine - INFO - Epoch(train) [132][ 960/2569] lr: 4.0000e-03 eta: 3:32:25 time: 0.2673 data_time: 0.0071 memory: 5828 grad_norm: 5.1791 loss: 1.8221 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8221 2023/06/05 17:38:10 - mmengine - INFO - Epoch(train) [132][ 980/2569] lr: 4.0000e-03 eta: 3:32:20 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 5.2089 loss: 1.7464 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7464 2023/06/05 17:38:15 - mmengine - INFO - Epoch(train) [132][1000/2569] lr: 4.0000e-03 eta: 3:32:14 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 5.1816 loss: 1.5845 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5845 2023/06/05 17:38:21 - mmengine - INFO - Epoch(train) [132][1020/2569] lr: 4.0000e-03 eta: 3:32:09 time: 0.2794 data_time: 0.0071 memory: 5828 grad_norm: 5.2364 loss: 1.6303 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6303 2023/06/05 17:38:27 - mmengine - INFO - Epoch(train) [132][1040/2569] lr: 4.0000e-03 eta: 3:32:04 time: 0.2771 data_time: 0.0076 memory: 5828 grad_norm: 5.1297 loss: 1.8483 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8483 2023/06/05 17:38:32 - mmengine - INFO - Epoch(train) [132][1060/2569] lr: 4.0000e-03 eta: 3:31:58 time: 0.2674 data_time: 0.0079 memory: 5828 grad_norm: 5.1537 loss: 1.7022 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7022 2023/06/05 17:38:37 - mmengine - INFO - Epoch(train) [132][1080/2569] lr: 4.0000e-03 eta: 3:31:53 time: 0.2730 data_time: 0.0092 memory: 5828 grad_norm: 5.2514 loss: 1.6887 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6887 2023/06/05 17:38:43 - mmengine - INFO - Epoch(train) [132][1100/2569] lr: 4.0000e-03 eta: 3:31:48 time: 0.2739 data_time: 0.0083 memory: 5828 grad_norm: 5.1651 loss: 1.4613 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4613 2023/06/05 17:38:48 - mmengine - INFO - Epoch(train) [132][1120/2569] lr: 4.0000e-03 eta: 3:31:42 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 5.2670 loss: 1.5927 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5927 2023/06/05 17:38:54 - mmengine - INFO - Epoch(train) [132][1140/2569] lr: 4.0000e-03 eta: 3:31:37 time: 0.2819 data_time: 0.0076 memory: 5828 grad_norm: 5.2512 loss: 1.7620 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7620 2023/06/05 17:38:59 - mmengine - INFO - Epoch(train) [132][1160/2569] lr: 4.0000e-03 eta: 3:31:32 time: 0.2675 data_time: 0.0080 memory: 5828 grad_norm: 5.1192 loss: 1.4229 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.4229 2023/06/05 17:39:05 - mmengine - INFO - Epoch(train) [132][1180/2569] lr: 4.0000e-03 eta: 3:31:26 time: 0.2792 data_time: 0.0078 memory: 5828 grad_norm: 5.2047 loss: 1.5065 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5065 2023/06/05 17:39:10 - mmengine - INFO - Epoch(train) [132][1200/2569] lr: 4.0000e-03 eta: 3:31:21 time: 0.2629 data_time: 0.0093 memory: 5828 grad_norm: 5.1427 loss: 1.6559 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6559 2023/06/05 17:39:16 - mmengine - INFO - Epoch(train) [132][1220/2569] lr: 4.0000e-03 eta: 3:31:16 time: 0.2767 data_time: 0.0076 memory: 5828 grad_norm: 5.1744 loss: 1.5370 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5370 2023/06/05 17:39:21 - mmengine - INFO - Epoch(train) [132][1240/2569] lr: 4.0000e-03 eta: 3:31:10 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 5.2074 loss: 1.8782 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8782 2023/06/05 17:39:26 - mmengine - INFO - Epoch(train) [132][1260/2569] lr: 4.0000e-03 eta: 3:31:05 time: 0.2641 data_time: 0.0080 memory: 5828 grad_norm: 5.2601 loss: 2.0386 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0386 2023/06/05 17:39:32 - mmengine - INFO - Epoch(train) [132][1280/2569] lr: 4.0000e-03 eta: 3:31:00 time: 0.2742 data_time: 0.0083 memory: 5828 grad_norm: 5.2166 loss: 1.6128 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6128 2023/06/05 17:39:37 - mmengine - INFO - Epoch(train) [132][1300/2569] lr: 4.0000e-03 eta: 3:30:55 time: 0.2733 data_time: 0.0075 memory: 5828 grad_norm: 5.2108 loss: 1.6812 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6812 2023/06/05 17:39:43 - mmengine - INFO - Epoch(train) [132][1320/2569] lr: 4.0000e-03 eta: 3:30:49 time: 0.2720 data_time: 0.0072 memory: 5828 grad_norm: 5.1569 loss: 1.6465 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6465 2023/06/05 17:39:48 - mmengine - INFO - Epoch(train) [132][1340/2569] lr: 4.0000e-03 eta: 3:30:44 time: 0.2642 data_time: 0.0072 memory: 5828 grad_norm: 5.2472 loss: 1.6368 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6368 2023/06/05 17:39:53 - mmengine - INFO - Epoch(train) [132][1360/2569] lr: 4.0000e-03 eta: 3:30:39 time: 0.2608 data_time: 0.0069 memory: 5828 grad_norm: 5.1518 loss: 1.5577 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5577 2023/06/05 17:39:58 - mmengine - INFO - Epoch(train) [132][1380/2569] lr: 4.0000e-03 eta: 3:30:33 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 5.2259 loss: 1.9528 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9528 2023/06/05 17:40:04 - mmengine - INFO - Epoch(train) [132][1400/2569] lr: 4.0000e-03 eta: 3:30:28 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 5.1625 loss: 1.9824 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9824 2023/06/05 17:40:09 - mmengine - INFO - Epoch(train) [132][1420/2569] lr: 4.0000e-03 eta: 3:30:23 time: 0.2630 data_time: 0.0070 memory: 5828 grad_norm: 5.1910 loss: 1.9440 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9440 2023/06/05 17:40:14 - mmengine - INFO - Epoch(train) [132][1440/2569] lr: 4.0000e-03 eta: 3:30:17 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 5.0009 loss: 1.8973 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8973 2023/06/05 17:40:20 - mmengine - INFO - Epoch(train) [132][1460/2569] lr: 4.0000e-03 eta: 3:30:12 time: 0.2619 data_time: 0.0074 memory: 5828 grad_norm: 5.1699 loss: 1.6902 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6902 2023/06/05 17:40:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:40:25 - mmengine - INFO - Epoch(train) [132][1480/2569] lr: 4.0000e-03 eta: 3:30:07 time: 0.2676 data_time: 0.0070 memory: 5828 grad_norm: 5.1903 loss: 1.7310 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7310 2023/06/05 17:40:30 - mmengine - INFO - Epoch(train) [132][1500/2569] lr: 4.0000e-03 eta: 3:30:01 time: 0.2691 data_time: 0.0072 memory: 5828 grad_norm: 5.2163 loss: 1.6908 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6908 2023/06/05 17:40:36 - mmengine - INFO - Epoch(train) [132][1520/2569] lr: 4.0000e-03 eta: 3:29:56 time: 0.2628 data_time: 0.0071 memory: 5828 grad_norm: 5.1705 loss: 2.1168 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1168 2023/06/05 17:40:41 - mmengine - INFO - Epoch(train) [132][1540/2569] lr: 4.0000e-03 eta: 3:29:51 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 5.0649 loss: 1.5728 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5728 2023/06/05 17:40:46 - mmengine - INFO - Epoch(train) [132][1560/2569] lr: 4.0000e-03 eta: 3:29:45 time: 0.2725 data_time: 0.0070 memory: 5828 grad_norm: 5.2229 loss: 1.8477 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8477 2023/06/05 17:40:52 - mmengine - INFO - Epoch(train) [132][1580/2569] lr: 4.0000e-03 eta: 3:29:40 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 5.1135 loss: 1.7374 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7374 2023/06/05 17:40:57 - mmengine - INFO - Epoch(train) [132][1600/2569] lr: 4.0000e-03 eta: 3:29:35 time: 0.2735 data_time: 0.0074 memory: 5828 grad_norm: 5.2211 loss: 1.3148 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3148 2023/06/05 17:41:03 - mmengine - INFO - Epoch(train) [132][1620/2569] lr: 4.0000e-03 eta: 3:29:29 time: 0.2781 data_time: 0.0073 memory: 5828 grad_norm: 5.2638 loss: 1.7840 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7840 2023/06/05 17:41:08 - mmengine - INFO - Epoch(train) [132][1640/2569] lr: 4.0000e-03 eta: 3:29:24 time: 0.2867 data_time: 0.0075 memory: 5828 grad_norm: 5.1520 loss: 1.6290 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6290 2023/06/05 17:41:14 - mmengine - INFO - Epoch(train) [132][1660/2569] lr: 4.0000e-03 eta: 3:29:19 time: 0.2715 data_time: 0.0072 memory: 5828 grad_norm: 5.2149 loss: 1.6670 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6670 2023/06/05 17:41:20 - mmengine - INFO - Epoch(train) [132][1680/2569] lr: 4.0000e-03 eta: 3:29:13 time: 0.2874 data_time: 0.0072 memory: 5828 grad_norm: 5.1718 loss: 1.7333 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7333 2023/06/05 17:41:25 - mmengine - INFO - Epoch(train) [132][1700/2569] lr: 4.0000e-03 eta: 3:29:08 time: 0.2625 data_time: 0.0077 memory: 5828 grad_norm: 5.1875 loss: 1.7903 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7903 2023/06/05 17:41:30 - mmengine - INFO - Epoch(train) [132][1720/2569] lr: 4.0000e-03 eta: 3:29:03 time: 0.2686 data_time: 0.0072 memory: 5828 grad_norm: 5.1893 loss: 1.7462 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7462 2023/06/05 17:41:36 - mmengine - INFO - Epoch(train) [132][1740/2569] lr: 4.0000e-03 eta: 3:28:57 time: 0.2633 data_time: 0.0075 memory: 5828 grad_norm: 5.1449 loss: 1.8061 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8061 2023/06/05 17:41:41 - mmengine - INFO - Epoch(train) [132][1760/2569] lr: 4.0000e-03 eta: 3:28:52 time: 0.2702 data_time: 0.0072 memory: 5828 grad_norm: 5.2355 loss: 1.5415 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5415 2023/06/05 17:41:46 - mmengine - INFO - Epoch(train) [132][1780/2569] lr: 4.0000e-03 eta: 3:28:47 time: 0.2703 data_time: 0.0072 memory: 5828 grad_norm: 5.2066 loss: 1.4486 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4486 2023/06/05 17:41:52 - mmengine - INFO - Epoch(train) [132][1800/2569] lr: 4.0000e-03 eta: 3:28:42 time: 0.2653 data_time: 0.0072 memory: 5828 grad_norm: 5.2212 loss: 2.0140 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0140 2023/06/05 17:41:57 - mmengine - INFO - Epoch(train) [132][1820/2569] lr: 4.0000e-03 eta: 3:28:36 time: 0.2761 data_time: 0.0072 memory: 5828 grad_norm: 5.1000 loss: 1.8550 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8550 2023/06/05 17:42:03 - mmengine - INFO - Epoch(train) [132][1840/2569] lr: 4.0000e-03 eta: 3:28:31 time: 0.2625 data_time: 0.0076 memory: 5828 grad_norm: 5.0346 loss: 1.9295 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9295 2023/06/05 17:42:08 - mmengine - INFO - Epoch(train) [132][1860/2569] lr: 4.0000e-03 eta: 3:28:26 time: 0.2643 data_time: 0.0070 memory: 5828 grad_norm: 5.1869 loss: 1.6788 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6788 2023/06/05 17:42:13 - mmengine - INFO - Epoch(train) [132][1880/2569] lr: 4.0000e-03 eta: 3:28:20 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 5.1943 loss: 1.4057 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4057 2023/06/05 17:42:18 - mmengine - INFO - Epoch(train) [132][1900/2569] lr: 4.0000e-03 eta: 3:28:15 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 5.1755 loss: 1.5039 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5039 2023/06/05 17:42:24 - mmengine - INFO - Epoch(train) [132][1920/2569] lr: 4.0000e-03 eta: 3:28:10 time: 0.2780 data_time: 0.0076 memory: 5828 grad_norm: 5.2599 loss: 1.6909 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6909 2023/06/05 17:42:29 - mmengine - INFO - Epoch(train) [132][1940/2569] lr: 4.0000e-03 eta: 3:28:04 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 5.2046 loss: 1.4987 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4987 2023/06/05 17:42:35 - mmengine - INFO - Epoch(train) [132][1960/2569] lr: 4.0000e-03 eta: 3:27:59 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 5.2722 loss: 1.6628 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6628 2023/06/05 17:42:40 - mmengine - INFO - Epoch(train) [132][1980/2569] lr: 4.0000e-03 eta: 3:27:54 time: 0.2644 data_time: 0.0073 memory: 5828 grad_norm: 5.2231 loss: 1.8249 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8249 2023/06/05 17:42:45 - mmengine - INFO - Epoch(train) [132][2000/2569] lr: 4.0000e-03 eta: 3:27:48 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 5.3238 loss: 1.7835 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7835 2023/06/05 17:42:51 - mmengine - INFO - Epoch(train) [132][2020/2569] lr: 4.0000e-03 eta: 3:27:43 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 5.2819 loss: 1.6685 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6685 2023/06/05 17:42:56 - mmengine - INFO - Epoch(train) [132][2040/2569] lr: 4.0000e-03 eta: 3:27:38 time: 0.2786 data_time: 0.0076 memory: 5828 grad_norm: 5.1602 loss: 1.7325 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7325 2023/06/05 17:43:02 - mmengine - INFO - Epoch(train) [132][2060/2569] lr: 4.0000e-03 eta: 3:27:32 time: 0.2705 data_time: 0.0071 memory: 5828 grad_norm: 5.1692 loss: 2.1212 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1212 2023/06/05 17:43:07 - mmengine - INFO - Epoch(train) [132][2080/2569] lr: 4.0000e-03 eta: 3:27:27 time: 0.2678 data_time: 0.0073 memory: 5828 grad_norm: 5.1876 loss: 1.7603 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7603 2023/06/05 17:43:12 - mmengine - INFO - Epoch(train) [132][2100/2569] lr: 4.0000e-03 eta: 3:27:22 time: 0.2757 data_time: 0.0074 memory: 5828 grad_norm: 5.2040 loss: 1.3332 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3332 2023/06/05 17:43:18 - mmengine - INFO - Epoch(train) [132][2120/2569] lr: 4.0000e-03 eta: 3:27:16 time: 0.2811 data_time: 0.0072 memory: 5828 grad_norm: 5.1338 loss: 1.4633 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4633 2023/06/05 17:43:24 - mmengine - INFO - Epoch(train) [132][2140/2569] lr: 4.0000e-03 eta: 3:27:11 time: 0.2753 data_time: 0.0071 memory: 5828 grad_norm: 5.1983 loss: 2.0291 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0291 2023/06/05 17:43:29 - mmengine - INFO - Epoch(train) [132][2160/2569] lr: 4.0000e-03 eta: 3:27:06 time: 0.2765 data_time: 0.0072 memory: 5828 grad_norm: 5.2543 loss: 1.7604 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7604 2023/06/05 17:43:35 - mmengine - INFO - Epoch(train) [132][2180/2569] lr: 4.0000e-03 eta: 3:27:00 time: 0.2660 data_time: 0.0071 memory: 5828 grad_norm: 5.1010 loss: 1.9372 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9372 2023/06/05 17:43:40 - mmengine - INFO - Epoch(train) [132][2200/2569] lr: 4.0000e-03 eta: 3:26:55 time: 0.2716 data_time: 0.0070 memory: 5828 grad_norm: 5.2801 loss: 1.9569 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9569 2023/06/05 17:43:45 - mmengine - INFO - Epoch(train) [132][2220/2569] lr: 4.0000e-03 eta: 3:26:50 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 5.3068 loss: 1.8104 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8104 2023/06/05 17:43:51 - mmengine - INFO - Epoch(train) [132][2240/2569] lr: 4.0000e-03 eta: 3:26:45 time: 0.2733 data_time: 0.0071 memory: 5828 grad_norm: 5.1705 loss: 1.7942 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7942 2023/06/05 17:43:56 - mmengine - INFO - Epoch(train) [132][2260/2569] lr: 4.0000e-03 eta: 3:26:39 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 5.1996 loss: 1.9626 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9626 2023/06/05 17:44:01 - mmengine - INFO - Epoch(train) [132][2280/2569] lr: 4.0000e-03 eta: 3:26:34 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 5.1866 loss: 1.7297 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7297 2023/06/05 17:44:07 - mmengine - INFO - Epoch(train) [132][2300/2569] lr: 4.0000e-03 eta: 3:26:29 time: 0.2610 data_time: 0.0068 memory: 5828 grad_norm: 5.2141 loss: 1.7115 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7115 2023/06/05 17:44:12 - mmengine - INFO - Epoch(train) [132][2320/2569] lr: 4.0000e-03 eta: 3:26:23 time: 0.2711 data_time: 0.0072 memory: 5828 grad_norm: 5.3144 loss: 1.8010 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8010 2023/06/05 17:44:18 - mmengine - INFO - Epoch(train) [132][2340/2569] lr: 4.0000e-03 eta: 3:26:18 time: 0.2729 data_time: 0.0070 memory: 5828 grad_norm: 5.1968 loss: 1.8186 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8186 2023/06/05 17:44:23 - mmengine - INFO - Epoch(train) [132][2360/2569] lr: 4.0000e-03 eta: 3:26:13 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 5.1342 loss: 1.5043 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5043 2023/06/05 17:44:28 - mmengine - INFO - Epoch(train) [132][2380/2569] lr: 4.0000e-03 eta: 3:26:07 time: 0.2671 data_time: 0.0071 memory: 5828 grad_norm: 5.2737 loss: 1.8092 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8092 2023/06/05 17:44:33 - mmengine - INFO - Epoch(train) [132][2400/2569] lr: 4.0000e-03 eta: 3:26:02 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 5.3023 loss: 1.7501 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7501 2023/06/05 17:44:39 - mmengine - INFO - Epoch(train) [132][2420/2569] lr: 4.0000e-03 eta: 3:25:57 time: 0.2764 data_time: 0.0068 memory: 5828 grad_norm: 5.1387 loss: 1.7284 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.7284 2023/06/05 17:44:44 - mmengine - INFO - Epoch(train) [132][2440/2569] lr: 4.0000e-03 eta: 3:25:51 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 5.1555 loss: 1.7657 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7657 2023/06/05 17:44:50 - mmengine - INFO - Epoch(train) [132][2460/2569] lr: 4.0000e-03 eta: 3:25:46 time: 0.2698 data_time: 0.0072 memory: 5828 grad_norm: 5.2479 loss: 1.5784 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5784 2023/06/05 17:44:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:44:55 - mmengine - INFO - Epoch(train) [132][2480/2569] lr: 4.0000e-03 eta: 3:25:41 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 5.2576 loss: 1.7789 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7789 2023/06/05 17:45:00 - mmengine - INFO - Epoch(train) [132][2500/2569] lr: 4.0000e-03 eta: 3:25:35 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 5.1453 loss: 1.8939 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8939 2023/06/05 17:45:06 - mmengine - INFO - Epoch(train) [132][2520/2569] lr: 4.0000e-03 eta: 3:25:30 time: 0.2611 data_time: 0.0076 memory: 5828 grad_norm: 5.1026 loss: 1.8054 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8054 2023/06/05 17:45:11 - mmengine - INFO - Epoch(train) [132][2540/2569] lr: 4.0000e-03 eta: 3:25:25 time: 0.2713 data_time: 0.0072 memory: 5828 grad_norm: 5.2197 loss: 1.9145 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9145 2023/06/05 17:45:16 - mmengine - INFO - Epoch(train) [132][2560/2569] lr: 4.0000e-03 eta: 3:25:19 time: 0.2635 data_time: 0.0076 memory: 5828 grad_norm: 5.2238 loss: 1.9545 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9545 2023/06/05 17:45:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:45:19 - mmengine - INFO - Epoch(train) [132][2569/2569] lr: 4.0000e-03 eta: 3:25:17 time: 0.2593 data_time: 0.0074 memory: 5828 grad_norm: 5.2531 loss: 1.7563 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.7563 2023/06/05 17:45:19 - mmengine - INFO - Saving checkpoint at 132 epochs 2023/06/05 17:45:27 - mmengine - INFO - Epoch(train) [133][ 20/2569] lr: 4.0000e-03 eta: 3:25:12 time: 0.3072 data_time: 0.0448 memory: 5828 grad_norm: 5.2268 loss: 1.6917 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6917 2023/06/05 17:45:32 - mmengine - INFO - Epoch(train) [133][ 40/2569] lr: 4.0000e-03 eta: 3:25:06 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 5.2393 loss: 1.9360 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9360 2023/06/05 17:45:37 - mmengine - INFO - Epoch(train) [133][ 60/2569] lr: 4.0000e-03 eta: 3:25:01 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 5.1765 loss: 1.8319 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8319 2023/06/05 17:45:43 - mmengine - INFO - Epoch(train) [133][ 80/2569] lr: 4.0000e-03 eta: 3:24:56 time: 0.2606 data_time: 0.0072 memory: 5828 grad_norm: 5.1654 loss: 1.6475 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6475 2023/06/05 17:45:48 - mmengine - INFO - Epoch(train) [133][ 100/2569] lr: 4.0000e-03 eta: 3:24:50 time: 0.2720 data_time: 0.0071 memory: 5828 grad_norm: 5.1689 loss: 1.7367 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7367 2023/06/05 17:45:53 - mmengine - INFO - Epoch(train) [133][ 120/2569] lr: 4.0000e-03 eta: 3:24:45 time: 0.2712 data_time: 0.0072 memory: 5828 grad_norm: 5.3139 loss: 1.5442 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.5442 2023/06/05 17:45:59 - mmengine - INFO - Epoch(train) [133][ 140/2569] lr: 4.0000e-03 eta: 3:24:40 time: 0.2818 data_time: 0.0071 memory: 5828 grad_norm: 5.2006 loss: 2.1208 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1208 2023/06/05 17:46:04 - mmengine - INFO - Epoch(train) [133][ 160/2569] lr: 4.0000e-03 eta: 3:24:34 time: 0.2634 data_time: 0.0077 memory: 5828 grad_norm: 5.2661 loss: 1.7935 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7935 2023/06/05 17:46:10 - mmengine - INFO - Epoch(train) [133][ 180/2569] lr: 4.0000e-03 eta: 3:24:29 time: 0.2606 data_time: 0.0073 memory: 5828 grad_norm: 5.2134 loss: 1.6993 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6993 2023/06/05 17:46:15 - mmengine - INFO - Epoch(train) [133][ 200/2569] lr: 4.0000e-03 eta: 3:24:24 time: 0.2671 data_time: 0.0077 memory: 5828 grad_norm: 5.0108 loss: 1.6761 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6761 2023/06/05 17:46:20 - mmengine - INFO - Epoch(train) [133][ 220/2569] lr: 4.0000e-03 eta: 3:24:18 time: 0.2675 data_time: 0.0072 memory: 5828 grad_norm: 5.2922 loss: 1.7588 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7588 2023/06/05 17:46:26 - mmengine - INFO - Epoch(train) [133][ 240/2569] lr: 4.0000e-03 eta: 3:24:13 time: 0.2630 data_time: 0.0074 memory: 5828 grad_norm: 5.2915 loss: 1.8498 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8498 2023/06/05 17:46:31 - mmengine - INFO - Epoch(train) [133][ 260/2569] lr: 4.0000e-03 eta: 3:24:08 time: 0.2644 data_time: 0.0075 memory: 5828 grad_norm: 5.2539 loss: 1.7431 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7431 2023/06/05 17:46:36 - mmengine - INFO - Epoch(train) [133][ 280/2569] lr: 4.0000e-03 eta: 3:24:02 time: 0.2719 data_time: 0.0078 memory: 5828 grad_norm: 5.2380 loss: 1.7947 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7947 2023/06/05 17:46:42 - mmengine - INFO - Epoch(train) [133][ 300/2569] lr: 4.0000e-03 eta: 3:23:57 time: 0.2713 data_time: 0.0072 memory: 5828 grad_norm: 5.1686 loss: 1.8324 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8324 2023/06/05 17:46:47 - mmengine - INFO - Epoch(train) [133][ 320/2569] lr: 4.0000e-03 eta: 3:23:52 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 5.3204 loss: 1.7378 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7378 2023/06/05 17:46:53 - mmengine - INFO - Epoch(train) [133][ 340/2569] lr: 4.0000e-03 eta: 3:23:46 time: 0.2747 data_time: 0.0071 memory: 5828 grad_norm: 5.3226 loss: 1.9567 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9567 2023/06/05 17:46:58 - mmengine - INFO - Epoch(train) [133][ 360/2569] lr: 4.0000e-03 eta: 3:23:41 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 5.3305 loss: 1.8556 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8556 2023/06/05 17:47:03 - mmengine - INFO - Epoch(train) [133][ 380/2569] lr: 4.0000e-03 eta: 3:23:36 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 5.2940 loss: 1.5242 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5242 2023/06/05 17:47:09 - mmengine - INFO - Epoch(train) [133][ 400/2569] lr: 4.0000e-03 eta: 3:23:31 time: 0.2681 data_time: 0.0073 memory: 5828 grad_norm: 5.2742 loss: 1.7558 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7558 2023/06/05 17:47:14 - mmengine - INFO - Epoch(train) [133][ 420/2569] lr: 4.0000e-03 eta: 3:23:25 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 5.3041 loss: 1.8681 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8681 2023/06/05 17:47:19 - mmengine - INFO - Epoch(train) [133][ 440/2569] lr: 4.0000e-03 eta: 3:23:20 time: 0.2705 data_time: 0.0071 memory: 5828 grad_norm: 5.1801 loss: 1.5785 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5785 2023/06/05 17:47:25 - mmengine - INFO - Epoch(train) [133][ 460/2569] lr: 4.0000e-03 eta: 3:23:15 time: 0.2682 data_time: 0.0075 memory: 5828 grad_norm: 5.2303 loss: 2.1004 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.1004 2023/06/05 17:47:30 - mmengine - INFO - Epoch(train) [133][ 480/2569] lr: 4.0000e-03 eta: 3:23:09 time: 0.2640 data_time: 0.0075 memory: 5828 grad_norm: 5.3306 loss: 1.6709 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6709 2023/06/05 17:47:35 - mmengine - INFO - Epoch(train) [133][ 500/2569] lr: 4.0000e-03 eta: 3:23:04 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 5.1620 loss: 1.6403 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6403 2023/06/05 17:47:41 - mmengine - INFO - Epoch(train) [133][ 520/2569] lr: 4.0000e-03 eta: 3:22:59 time: 0.2616 data_time: 0.0072 memory: 5828 grad_norm: 5.2045 loss: 1.6017 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6017 2023/06/05 17:47:46 - mmengine - INFO - Epoch(train) [133][ 540/2569] lr: 4.0000e-03 eta: 3:22:53 time: 0.2634 data_time: 0.0073 memory: 5828 grad_norm: 5.2142 loss: 1.4747 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4747 2023/06/05 17:47:51 - mmengine - INFO - Epoch(train) [133][ 560/2569] lr: 4.0000e-03 eta: 3:22:48 time: 0.2676 data_time: 0.0071 memory: 5828 grad_norm: 5.2892 loss: 1.6131 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6131 2023/06/05 17:47:57 - mmengine - INFO - Epoch(train) [133][ 580/2569] lr: 4.0000e-03 eta: 3:22:43 time: 0.2745 data_time: 0.0071 memory: 5828 grad_norm: 5.2096 loss: 1.7831 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7831 2023/06/05 17:48:02 - mmengine - INFO - Epoch(train) [133][ 600/2569] lr: 4.0000e-03 eta: 3:22:37 time: 0.2707 data_time: 0.0072 memory: 5828 grad_norm: 5.1821 loss: 1.4672 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.4672 2023/06/05 17:48:08 - mmengine - INFO - Epoch(train) [133][ 620/2569] lr: 4.0000e-03 eta: 3:22:32 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 5.2732 loss: 2.0637 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0637 2023/06/05 17:48:13 - mmengine - INFO - Epoch(train) [133][ 640/2569] lr: 4.0000e-03 eta: 3:22:27 time: 0.2740 data_time: 0.0072 memory: 5828 grad_norm: 5.2741 loss: 1.7291 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7291 2023/06/05 17:48:19 - mmengine - INFO - Epoch(train) [133][ 660/2569] lr: 4.0000e-03 eta: 3:22:21 time: 0.2710 data_time: 0.0072 memory: 5828 grad_norm: 5.2274 loss: 1.7146 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7146 2023/06/05 17:48:24 - mmengine - INFO - Epoch(train) [133][ 680/2569] lr: 4.0000e-03 eta: 3:22:16 time: 0.2729 data_time: 0.0071 memory: 5828 grad_norm: 5.2946 loss: 1.6563 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6563 2023/06/05 17:48:29 - mmengine - INFO - Epoch(train) [133][ 700/2569] lr: 4.0000e-03 eta: 3:22:11 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 5.2624 loss: 1.6152 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6152 2023/06/05 17:48:35 - mmengine - INFO - Epoch(train) [133][ 720/2569] lr: 4.0000e-03 eta: 3:22:05 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 5.2544 loss: 1.7130 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7130 2023/06/05 17:48:40 - mmengine - INFO - Epoch(train) [133][ 740/2569] lr: 4.0000e-03 eta: 3:22:00 time: 0.2665 data_time: 0.0071 memory: 5828 grad_norm: 5.1319 loss: 1.9482 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9482 2023/06/05 17:48:45 - mmengine - INFO - Epoch(train) [133][ 760/2569] lr: 4.0000e-03 eta: 3:21:55 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 5.1051 loss: 1.9841 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9841 2023/06/05 17:48:51 - mmengine - INFO - Epoch(train) [133][ 780/2569] lr: 4.0000e-03 eta: 3:21:49 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 5.2836 loss: 1.7614 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7614 2023/06/05 17:48:56 - mmengine - INFO - Epoch(train) [133][ 800/2569] lr: 4.0000e-03 eta: 3:21:44 time: 0.2790 data_time: 0.0072 memory: 5828 grad_norm: 5.3387 loss: 1.7167 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7167 2023/06/05 17:49:02 - mmengine - INFO - Epoch(train) [133][ 820/2569] lr: 4.0000e-03 eta: 3:21:39 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 5.3231 loss: 1.9702 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9702 2023/06/05 17:49:07 - mmengine - INFO - Epoch(train) [133][ 840/2569] lr: 4.0000e-03 eta: 3:21:33 time: 0.2722 data_time: 0.0073 memory: 5828 grad_norm: 5.1999 loss: 1.7390 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7390 2023/06/05 17:49:12 - mmengine - INFO - Epoch(train) [133][ 860/2569] lr: 4.0000e-03 eta: 3:21:28 time: 0.2615 data_time: 0.0072 memory: 5828 grad_norm: 5.2525 loss: 1.7531 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7531 2023/06/05 17:49:18 - mmengine - INFO - Epoch(train) [133][ 880/2569] lr: 4.0000e-03 eta: 3:21:23 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 5.1133 loss: 1.8979 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8979 2023/06/05 17:49:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:49:23 - mmengine - INFO - Epoch(train) [133][ 900/2569] lr: 4.0000e-03 eta: 3:21:17 time: 0.2706 data_time: 0.0071 memory: 5828 grad_norm: 5.2479 loss: 1.6205 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6205 2023/06/05 17:49:28 - mmengine - INFO - Epoch(train) [133][ 920/2569] lr: 4.0000e-03 eta: 3:21:12 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 5.2366 loss: 1.8725 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8725 2023/06/05 17:49:34 - mmengine - INFO - Epoch(train) [133][ 940/2569] lr: 4.0000e-03 eta: 3:21:07 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 5.2843 loss: 1.8869 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8869 2023/06/05 17:49:39 - mmengine - INFO - Epoch(train) [133][ 960/2569] lr: 4.0000e-03 eta: 3:21:01 time: 0.2696 data_time: 0.0071 memory: 5828 grad_norm: 5.3478 loss: 1.7938 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7938 2023/06/05 17:49:44 - mmengine - INFO - Epoch(train) [133][ 980/2569] lr: 4.0000e-03 eta: 3:20:56 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 5.1984 loss: 1.7400 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7400 2023/06/05 17:49:50 - mmengine - INFO - Epoch(train) [133][1000/2569] lr: 4.0000e-03 eta: 3:20:51 time: 0.2681 data_time: 0.0073 memory: 5828 grad_norm: 5.0676 loss: 1.3371 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3371 2023/06/05 17:49:55 - mmengine - INFO - Epoch(train) [133][1020/2569] lr: 4.0000e-03 eta: 3:20:45 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 5.1512 loss: 1.7006 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7006 2023/06/05 17:50:01 - mmengine - INFO - Epoch(train) [133][1040/2569] lr: 4.0000e-03 eta: 3:20:40 time: 0.2687 data_time: 0.0075 memory: 5828 grad_norm: 5.2639 loss: 1.6161 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6161 2023/06/05 17:50:06 - mmengine - INFO - Epoch(train) [133][1060/2569] lr: 4.0000e-03 eta: 3:20:35 time: 0.2623 data_time: 0.0077 memory: 5828 grad_norm: 5.3415 loss: 1.6142 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6142 2023/06/05 17:50:11 - mmengine - INFO - Epoch(train) [133][1080/2569] lr: 4.0000e-03 eta: 3:20:30 time: 0.2718 data_time: 0.0088 memory: 5828 grad_norm: 5.2701 loss: 1.6374 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6374 2023/06/05 17:50:17 - mmengine - INFO - Epoch(train) [133][1100/2569] lr: 4.0000e-03 eta: 3:20:24 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 5.0742 loss: 1.4950 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4950 2023/06/05 17:50:22 - mmengine - INFO - Epoch(train) [133][1120/2569] lr: 4.0000e-03 eta: 3:20:19 time: 0.2808 data_time: 0.0070 memory: 5828 grad_norm: 5.3034 loss: 1.8622 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8622 2023/06/05 17:50:28 - mmengine - INFO - Epoch(train) [133][1140/2569] lr: 4.0000e-03 eta: 3:20:14 time: 0.2758 data_time: 0.0070 memory: 5828 grad_norm: 5.2385 loss: 1.7072 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7072 2023/06/05 17:50:33 - mmengine - INFO - Epoch(train) [133][1160/2569] lr: 4.0000e-03 eta: 3:20:08 time: 0.2737 data_time: 0.0070 memory: 5828 grad_norm: 5.2091 loss: 1.8700 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8700 2023/06/05 17:50:38 - mmengine - INFO - Epoch(train) [133][1180/2569] lr: 4.0000e-03 eta: 3:20:03 time: 0.2619 data_time: 0.0074 memory: 5828 grad_norm: 5.2590 loss: 1.9515 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9515 2023/06/05 17:50:44 - mmengine - INFO - Epoch(train) [133][1200/2569] lr: 4.0000e-03 eta: 3:19:58 time: 0.2733 data_time: 0.0073 memory: 5828 grad_norm: 5.1689 loss: 1.8079 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8079 2023/06/05 17:50:49 - mmengine - INFO - Epoch(train) [133][1220/2569] lr: 4.0000e-03 eta: 3:19:52 time: 0.2609 data_time: 0.0072 memory: 5828 grad_norm: 5.1777 loss: 2.0173 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 2.0173 2023/06/05 17:50:54 - mmengine - INFO - Epoch(train) [133][1240/2569] lr: 4.0000e-03 eta: 3:19:47 time: 0.2649 data_time: 0.0075 memory: 5828 grad_norm: 5.2489 loss: 1.7279 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7279 2023/06/05 17:51:00 - mmengine - INFO - Epoch(train) [133][1260/2569] lr: 4.0000e-03 eta: 3:19:42 time: 0.2602 data_time: 0.0070 memory: 5828 grad_norm: 5.2996 loss: 1.6792 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6792 2023/06/05 17:51:05 - mmengine - INFO - Epoch(train) [133][1280/2569] lr: 4.0000e-03 eta: 3:19:36 time: 0.2723 data_time: 0.0073 memory: 5828 grad_norm: 5.3368 loss: 1.7335 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7335 2023/06/05 17:51:10 - mmengine - INFO - Epoch(train) [133][1300/2569] lr: 4.0000e-03 eta: 3:19:31 time: 0.2664 data_time: 0.0072 memory: 5828 grad_norm: 5.1484 loss: 1.7222 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7222 2023/06/05 17:51:16 - mmengine - INFO - Epoch(train) [133][1320/2569] lr: 4.0000e-03 eta: 3:19:26 time: 0.2609 data_time: 0.0073 memory: 5828 grad_norm: 5.3083 loss: 1.8558 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8558 2023/06/05 17:51:21 - mmengine - INFO - Epoch(train) [133][1340/2569] lr: 4.0000e-03 eta: 3:19:20 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 5.2643 loss: 1.8369 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8369 2023/06/05 17:51:27 - mmengine - INFO - Epoch(train) [133][1360/2569] lr: 4.0000e-03 eta: 3:19:15 time: 0.2723 data_time: 0.0072 memory: 5828 grad_norm: 5.3002 loss: 1.4631 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4631 2023/06/05 17:51:32 - mmengine - INFO - Epoch(train) [133][1380/2569] lr: 4.0000e-03 eta: 3:19:10 time: 0.2840 data_time: 0.0073 memory: 5828 grad_norm: 5.0791 loss: 1.5024 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5024 2023/06/05 17:51:37 - mmengine - INFO - Epoch(train) [133][1400/2569] lr: 4.0000e-03 eta: 3:19:04 time: 0.2625 data_time: 0.0075 memory: 5828 grad_norm: 5.3071 loss: 1.9360 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9360 2023/06/05 17:51:43 - mmengine - INFO - Epoch(train) [133][1420/2569] lr: 4.0000e-03 eta: 3:18:59 time: 0.2720 data_time: 0.0070 memory: 5828 grad_norm: 5.1635 loss: 2.1185 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1185 2023/06/05 17:51:48 - mmengine - INFO - Epoch(train) [133][1440/2569] lr: 4.0000e-03 eta: 3:18:54 time: 0.2644 data_time: 0.0075 memory: 5828 grad_norm: 5.2348 loss: 1.6978 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6978 2023/06/05 17:51:54 - mmengine - INFO - Epoch(train) [133][1460/2569] lr: 4.0000e-03 eta: 3:18:48 time: 0.2919 data_time: 0.0072 memory: 5828 grad_norm: 5.1800 loss: 1.7970 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7970 2023/06/05 17:52:00 - mmengine - INFO - Epoch(train) [133][1480/2569] lr: 4.0000e-03 eta: 3:18:43 time: 0.2725 data_time: 0.0072 memory: 5828 grad_norm: 5.2905 loss: 1.7780 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7780 2023/06/05 17:52:05 - mmengine - INFO - Epoch(train) [133][1500/2569] lr: 4.0000e-03 eta: 3:18:38 time: 0.2685 data_time: 0.0076 memory: 5828 grad_norm: 5.3547 loss: 1.6714 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6714 2023/06/05 17:52:10 - mmengine - INFO - Epoch(train) [133][1520/2569] lr: 4.0000e-03 eta: 3:18:33 time: 0.2741 data_time: 0.0074 memory: 5828 grad_norm: 5.3308 loss: 1.5748 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5748 2023/06/05 17:52:16 - mmengine - INFO - Epoch(train) [133][1540/2569] lr: 4.0000e-03 eta: 3:18:27 time: 0.2637 data_time: 0.0074 memory: 5828 grad_norm: 5.1469 loss: 1.7935 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7935 2023/06/05 17:52:21 - mmengine - INFO - Epoch(train) [133][1560/2569] lr: 4.0000e-03 eta: 3:18:22 time: 0.2785 data_time: 0.0078 memory: 5828 grad_norm: 5.2776 loss: 1.6120 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6120 2023/06/05 17:52:27 - mmengine - INFO - Epoch(train) [133][1580/2569] lr: 4.0000e-03 eta: 3:18:17 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 5.1830 loss: 1.7278 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7278 2023/06/05 17:52:32 - mmengine - INFO - Epoch(train) [133][1600/2569] lr: 4.0000e-03 eta: 3:18:11 time: 0.2749 data_time: 0.0072 memory: 5828 grad_norm: 5.2071 loss: 1.9142 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9142 2023/06/05 17:52:38 - mmengine - INFO - Epoch(train) [133][1620/2569] lr: 4.0000e-03 eta: 3:18:06 time: 0.2693 data_time: 0.0083 memory: 5828 grad_norm: 5.0819 loss: 1.9007 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9007 2023/06/05 17:52:43 - mmengine - INFO - Epoch(train) [133][1640/2569] lr: 4.0000e-03 eta: 3:18:01 time: 0.2681 data_time: 0.0073 memory: 5828 grad_norm: 5.3129 loss: 1.8070 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8070 2023/06/05 17:52:48 - mmengine - INFO - Epoch(train) [133][1660/2569] lr: 4.0000e-03 eta: 3:17:55 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 5.3279 loss: 1.7799 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7799 2023/06/05 17:52:54 - mmengine - INFO - Epoch(train) [133][1680/2569] lr: 4.0000e-03 eta: 3:17:50 time: 0.2714 data_time: 0.0077 memory: 5828 grad_norm: 5.2663 loss: 1.8421 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.8421 2023/06/05 17:52:59 - mmengine - INFO - Epoch(train) [133][1700/2569] lr: 4.0000e-03 eta: 3:17:45 time: 0.2679 data_time: 0.0085 memory: 5828 grad_norm: 5.3902 loss: 1.8898 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8898 2023/06/05 17:53:05 - mmengine - INFO - Epoch(train) [133][1720/2569] lr: 4.0000e-03 eta: 3:17:39 time: 0.2694 data_time: 0.0078 memory: 5828 grad_norm: 5.2882 loss: 1.7544 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7544 2023/06/05 17:53:10 - mmengine - INFO - Epoch(train) [133][1740/2569] lr: 4.0000e-03 eta: 3:17:34 time: 0.2691 data_time: 0.0077 memory: 5828 grad_norm: 5.3432 loss: 1.7627 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7627 2023/06/05 17:53:16 - mmengine - INFO - Epoch(train) [133][1760/2569] lr: 4.0000e-03 eta: 3:17:29 time: 0.2800 data_time: 0.0071 memory: 5828 grad_norm: 5.2317 loss: 1.7784 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7784 2023/06/05 17:53:21 - mmengine - INFO - Epoch(train) [133][1780/2569] lr: 4.0000e-03 eta: 3:17:23 time: 0.2721 data_time: 0.0075 memory: 5828 grad_norm: 5.1656 loss: 2.1062 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1062 2023/06/05 17:53:26 - mmengine - INFO - Epoch(train) [133][1800/2569] lr: 4.0000e-03 eta: 3:17:18 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 5.0915 loss: 2.0455 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0455 2023/06/05 17:53:31 - mmengine - INFO - Epoch(train) [133][1820/2569] lr: 4.0000e-03 eta: 3:17:13 time: 0.2631 data_time: 0.0075 memory: 5828 grad_norm: 5.1383 loss: 1.6312 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6312 2023/06/05 17:53:37 - mmengine - INFO - Epoch(train) [133][1840/2569] lr: 4.0000e-03 eta: 3:17:07 time: 0.2689 data_time: 0.0090 memory: 5828 grad_norm: 5.2599 loss: 1.8457 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8457 2023/06/05 17:53:42 - mmengine - INFO - Epoch(train) [133][1860/2569] lr: 4.0000e-03 eta: 3:17:02 time: 0.2616 data_time: 0.0076 memory: 5828 grad_norm: 5.3859 loss: 1.7706 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7706 2023/06/05 17:53:48 - mmengine - INFO - Epoch(train) [133][1880/2569] lr: 4.0000e-03 eta: 3:16:57 time: 0.2730 data_time: 0.0074 memory: 5828 grad_norm: 5.2428 loss: 1.9056 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9056 2023/06/05 17:53:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:53:53 - mmengine - INFO - Epoch(train) [133][1900/2569] lr: 4.0000e-03 eta: 3:16:51 time: 0.2615 data_time: 0.0076 memory: 5828 grad_norm: 5.2283 loss: 1.5969 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5969 2023/06/05 17:53:58 - mmengine - INFO - Epoch(train) [133][1920/2569] lr: 4.0000e-03 eta: 3:16:46 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 5.2504 loss: 1.8964 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8964 2023/06/05 17:54:03 - mmengine - INFO - Epoch(train) [133][1940/2569] lr: 4.0000e-03 eta: 3:16:41 time: 0.2612 data_time: 0.0075 memory: 5828 grad_norm: 5.2903 loss: 1.5353 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5353 2023/06/05 17:54:09 - mmengine - INFO - Epoch(train) [133][1960/2569] lr: 4.0000e-03 eta: 3:16:35 time: 0.2676 data_time: 0.0074 memory: 5828 grad_norm: 5.2547 loss: 1.7275 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7275 2023/06/05 17:54:14 - mmengine - INFO - Epoch(train) [133][1980/2569] lr: 4.0000e-03 eta: 3:16:30 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 5.3045 loss: 1.8796 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8796 2023/06/05 17:54:19 - mmengine - INFO - Epoch(train) [133][2000/2569] lr: 4.0000e-03 eta: 3:16:25 time: 0.2655 data_time: 0.0071 memory: 5828 grad_norm: 5.3108 loss: 1.4666 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4666 2023/06/05 17:54:25 - mmengine - INFO - Epoch(train) [133][2020/2569] lr: 4.0000e-03 eta: 3:16:19 time: 0.2753 data_time: 0.0074 memory: 5828 grad_norm: 5.3356 loss: 1.7544 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7544 2023/06/05 17:54:30 - mmengine - INFO - Epoch(train) [133][2040/2569] lr: 4.0000e-03 eta: 3:16:14 time: 0.2696 data_time: 0.0071 memory: 5828 grad_norm: 5.2057 loss: 1.8910 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8910 2023/06/05 17:54:36 - mmengine - INFO - Epoch(train) [133][2060/2569] lr: 4.0000e-03 eta: 3:16:09 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 5.1784 loss: 1.6853 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6853 2023/06/05 17:54:41 - mmengine - INFO - Epoch(train) [133][2080/2569] lr: 4.0000e-03 eta: 3:16:04 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 5.2387 loss: 1.5467 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.5467 2023/06/05 17:54:46 - mmengine - INFO - Epoch(train) [133][2100/2569] lr: 4.0000e-03 eta: 3:15:58 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 5.1569 loss: 1.7869 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7869 2023/06/05 17:54:52 - mmengine - INFO - Epoch(train) [133][2120/2569] lr: 4.0000e-03 eta: 3:15:53 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 5.3005 loss: 1.6359 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6359 2023/06/05 17:54:57 - mmengine - INFO - Epoch(train) [133][2140/2569] lr: 4.0000e-03 eta: 3:15:48 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 5.2652 loss: 1.7941 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7941 2023/06/05 17:55:02 - mmengine - INFO - Epoch(train) [133][2160/2569] lr: 4.0000e-03 eta: 3:15:42 time: 0.2675 data_time: 0.0075 memory: 5828 grad_norm: 5.2923 loss: 1.8769 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8769 2023/06/05 17:55:08 - mmengine - INFO - Epoch(train) [133][2180/2569] lr: 4.0000e-03 eta: 3:15:37 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 5.3359 loss: 2.0889 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0889 2023/06/05 17:55:13 - mmengine - INFO - Epoch(train) [133][2200/2569] lr: 4.0000e-03 eta: 3:15:32 time: 0.2614 data_time: 0.0082 memory: 5828 grad_norm: 5.1978 loss: 1.7375 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7375 2023/06/05 17:55:18 - mmengine - INFO - Epoch(train) [133][2220/2569] lr: 4.0000e-03 eta: 3:15:26 time: 0.2724 data_time: 0.0093 memory: 5828 grad_norm: 5.2816 loss: 1.8472 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8472 2023/06/05 17:55:24 - mmengine - INFO - Epoch(train) [133][2240/2569] lr: 4.0000e-03 eta: 3:15:21 time: 0.2667 data_time: 0.0076 memory: 5828 grad_norm: 5.2590 loss: 1.7353 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.7353 2023/06/05 17:55:29 - mmengine - INFO - Epoch(train) [133][2260/2569] lr: 4.0000e-03 eta: 3:15:16 time: 0.2785 data_time: 0.0076 memory: 5828 grad_norm: 5.2959 loss: 1.5504 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5504 2023/06/05 17:55:35 - mmengine - INFO - Epoch(train) [133][2280/2569] lr: 4.0000e-03 eta: 3:15:10 time: 0.2691 data_time: 0.0074 memory: 5828 grad_norm: 5.2753 loss: 2.0108 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 2.0108 2023/06/05 17:55:40 - mmengine - INFO - Epoch(train) [133][2300/2569] lr: 4.0000e-03 eta: 3:15:05 time: 0.2731 data_time: 0.0071 memory: 5828 grad_norm: 5.1334 loss: 1.6988 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6988 2023/06/05 17:55:45 - mmengine - INFO - Epoch(train) [133][2320/2569] lr: 4.0000e-03 eta: 3:15:00 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 5.2244 loss: 1.5683 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5683 2023/06/05 17:55:51 - mmengine - INFO - Epoch(train) [133][2340/2569] lr: 4.0000e-03 eta: 3:14:54 time: 0.2606 data_time: 0.0077 memory: 5828 grad_norm: 5.3173 loss: 1.9429 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9429 2023/06/05 17:55:56 - mmengine - INFO - Epoch(train) [133][2360/2569] lr: 4.0000e-03 eta: 3:14:49 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 5.2920 loss: 1.7753 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7753 2023/06/05 17:56:01 - mmengine - INFO - Epoch(train) [133][2380/2569] lr: 4.0000e-03 eta: 3:14:44 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 5.2682 loss: 1.8649 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8649 2023/06/05 17:56:07 - mmengine - INFO - Epoch(train) [133][2400/2569] lr: 4.0000e-03 eta: 3:14:38 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 5.2099 loss: 1.6044 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.6044 2023/06/05 17:56:12 - mmengine - INFO - Epoch(train) [133][2420/2569] lr: 4.0000e-03 eta: 3:14:33 time: 0.2776 data_time: 0.0075 memory: 5828 grad_norm: 5.3571 loss: 1.7605 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7605 2023/06/05 17:56:18 - mmengine - INFO - Epoch(train) [133][2440/2569] lr: 4.0000e-03 eta: 3:14:28 time: 0.2791 data_time: 0.0069 memory: 5828 grad_norm: 5.3139 loss: 2.0976 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0976 2023/06/05 17:56:23 - mmengine - INFO - Epoch(train) [133][2460/2569] lr: 4.0000e-03 eta: 3:14:22 time: 0.2732 data_time: 0.0075 memory: 5828 grad_norm: 5.2897 loss: 1.6785 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6785 2023/06/05 17:56:29 - mmengine - INFO - Epoch(train) [133][2480/2569] lr: 4.0000e-03 eta: 3:14:17 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 5.1432 loss: 2.0714 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0714 2023/06/05 17:56:34 - mmengine - INFO - Epoch(train) [133][2500/2569] lr: 4.0000e-03 eta: 3:14:12 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 5.1342 loss: 1.7857 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7857 2023/06/05 17:56:39 - mmengine - INFO - Epoch(train) [133][2520/2569] lr: 4.0000e-03 eta: 3:14:06 time: 0.2743 data_time: 0.0073 memory: 5828 grad_norm: 5.1236 loss: 1.7904 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7904 2023/06/05 17:56:45 - mmengine - INFO - Epoch(train) [133][2540/2569] lr: 4.0000e-03 eta: 3:14:01 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 5.2175 loss: 1.5873 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5873 2023/06/05 17:56:50 - mmengine - INFO - Epoch(train) [133][2560/2569] lr: 4.0000e-03 eta: 3:13:56 time: 0.2710 data_time: 0.0076 memory: 5828 grad_norm: 5.2731 loss: 1.8639 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8639 2023/06/05 17:56:52 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:56:52 - mmengine - INFO - Epoch(train) [133][2569/2569] lr: 4.0000e-03 eta: 3:13:53 time: 0.2649 data_time: 0.0070 memory: 5828 grad_norm: 5.2879 loss: 2.0487 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 2.0487 2023/06/05 17:56:59 - mmengine - INFO - Epoch(train) [134][ 20/2569] lr: 4.0000e-03 eta: 3:13:48 time: 0.3308 data_time: 0.0533 memory: 5828 grad_norm: 5.2022 loss: 1.6560 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6560 2023/06/05 17:57:04 - mmengine - INFO - Epoch(train) [134][ 40/2569] lr: 4.0000e-03 eta: 3:13:43 time: 0.2630 data_time: 0.0078 memory: 5828 grad_norm: 5.2872 loss: 1.4080 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4080 2023/06/05 17:57:10 - mmengine - INFO - Epoch(train) [134][ 60/2569] lr: 4.0000e-03 eta: 3:13:38 time: 0.2733 data_time: 0.0071 memory: 5828 grad_norm: 5.2856 loss: 1.8451 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8451 2023/06/05 17:57:15 - mmengine - INFO - Epoch(train) [134][ 80/2569] lr: 4.0000e-03 eta: 3:13:32 time: 0.2723 data_time: 0.0073 memory: 5828 grad_norm: 5.2120 loss: 1.8000 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.8000 2023/06/05 17:57:21 - mmengine - INFO - Epoch(train) [134][ 100/2569] lr: 4.0000e-03 eta: 3:13:27 time: 0.2611 data_time: 0.0072 memory: 5828 grad_norm: 5.2217 loss: 2.0140 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0140 2023/06/05 17:57:26 - mmengine - INFO - Epoch(train) [134][ 120/2569] lr: 4.0000e-03 eta: 3:13:22 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 5.3274 loss: 1.8515 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8515 2023/06/05 17:57:31 - mmengine - INFO - Epoch(train) [134][ 140/2569] lr: 4.0000e-03 eta: 3:13:16 time: 0.2755 data_time: 0.0073 memory: 5828 grad_norm: 5.3731 loss: 1.3992 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3992 2023/06/05 17:57:37 - mmengine - INFO - Epoch(train) [134][ 160/2569] lr: 4.0000e-03 eta: 3:13:11 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 5.2498 loss: 1.4598 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4598 2023/06/05 17:57:42 - mmengine - INFO - Epoch(train) [134][ 180/2569] lr: 4.0000e-03 eta: 3:13:06 time: 0.2668 data_time: 0.0076 memory: 5828 grad_norm: 5.2102 loss: 1.7785 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7785 2023/06/05 17:57:47 - mmengine - INFO - Epoch(train) [134][ 200/2569] lr: 4.0000e-03 eta: 3:13:00 time: 0.2630 data_time: 0.0074 memory: 5828 grad_norm: 5.1529 loss: 1.8165 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8165 2023/06/05 17:57:53 - mmengine - INFO - Epoch(train) [134][ 220/2569] lr: 4.0000e-03 eta: 3:12:55 time: 0.2692 data_time: 0.0076 memory: 5828 grad_norm: 5.3952 loss: 2.0378 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0378 2023/06/05 17:57:58 - mmengine - INFO - Epoch(train) [134][ 240/2569] lr: 4.0000e-03 eta: 3:12:50 time: 0.2674 data_time: 0.0073 memory: 5828 grad_norm: 5.4712 loss: 1.8033 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8033 2023/06/05 17:58:04 - mmengine - INFO - Epoch(train) [134][ 260/2569] lr: 4.0000e-03 eta: 3:12:44 time: 0.2723 data_time: 0.0075 memory: 5828 grad_norm: 5.1847 loss: 1.4545 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4545 2023/06/05 17:58:09 - mmengine - INFO - Epoch(train) [134][ 280/2569] lr: 4.0000e-03 eta: 3:12:39 time: 0.2745 data_time: 0.0074 memory: 5828 grad_norm: 5.2469 loss: 1.5311 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5311 2023/06/05 17:58:14 - mmengine - INFO - Epoch(train) [134][ 300/2569] lr: 4.0000e-03 eta: 3:12:34 time: 0.2678 data_time: 0.0076 memory: 5828 grad_norm: 5.3569 loss: 1.8219 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8219 2023/06/05 17:58:20 - mmengine - INFO - Epoch(train) [134][ 320/2569] lr: 4.0000e-03 eta: 3:12:28 time: 0.2819 data_time: 0.0077 memory: 5828 grad_norm: 5.2200 loss: 2.0109 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0109 2023/06/05 17:58:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 17:58:25 - mmengine - INFO - Epoch(train) [134][ 340/2569] lr: 4.0000e-03 eta: 3:12:23 time: 0.2616 data_time: 0.0076 memory: 5828 grad_norm: 5.1477 loss: 1.6711 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6711 2023/06/05 17:58:31 - mmengine - INFO - Epoch(train) [134][ 360/2569] lr: 4.0000e-03 eta: 3:12:18 time: 0.2686 data_time: 0.0073 memory: 5828 grad_norm: 5.3414 loss: 1.9161 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9161 2023/06/05 17:58:36 - mmengine - INFO - Epoch(train) [134][ 380/2569] lr: 4.0000e-03 eta: 3:12:12 time: 0.2681 data_time: 0.0077 memory: 5828 grad_norm: 5.1836 loss: 2.0686 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0686 2023/06/05 17:58:42 - mmengine - INFO - Epoch(train) [134][ 400/2569] lr: 4.0000e-03 eta: 3:12:07 time: 0.2728 data_time: 0.0072 memory: 5828 grad_norm: 5.2896 loss: 1.7255 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7255 2023/06/05 17:58:47 - mmengine - INFO - Epoch(train) [134][ 420/2569] lr: 4.0000e-03 eta: 3:12:02 time: 0.2635 data_time: 0.0081 memory: 5828 grad_norm: 5.1788 loss: 1.8575 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.8575 2023/06/05 17:58:52 - mmengine - INFO - Epoch(train) [134][ 440/2569] lr: 4.0000e-03 eta: 3:11:56 time: 0.2752 data_time: 0.0074 memory: 5828 grad_norm: 5.3491 loss: 1.8560 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8560 2023/06/05 17:58:58 - mmengine - INFO - Epoch(train) [134][ 460/2569] lr: 4.0000e-03 eta: 3:11:51 time: 0.2692 data_time: 0.0070 memory: 5828 grad_norm: 5.2253 loss: 1.8753 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8753 2023/06/05 17:59:03 - mmengine - INFO - Epoch(train) [134][ 480/2569] lr: 4.0000e-03 eta: 3:11:46 time: 0.2673 data_time: 0.0070 memory: 5828 grad_norm: 5.3620 loss: 2.0554 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0554 2023/06/05 17:59:08 - mmengine - INFO - Epoch(train) [134][ 500/2569] lr: 4.0000e-03 eta: 3:11:40 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 5.2108 loss: 1.6227 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6227 2023/06/05 17:59:14 - mmengine - INFO - Epoch(train) [134][ 520/2569] lr: 4.0000e-03 eta: 3:11:35 time: 0.2650 data_time: 0.0077 memory: 5828 grad_norm: 5.2191 loss: 1.6479 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6479 2023/06/05 17:59:19 - mmengine - INFO - Epoch(train) [134][ 540/2569] lr: 4.0000e-03 eta: 3:11:30 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 5.2430 loss: 1.7000 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7000 2023/06/05 17:59:24 - mmengine - INFO - Epoch(train) [134][ 560/2569] lr: 4.0000e-03 eta: 3:11:24 time: 0.2666 data_time: 0.0072 memory: 5828 grad_norm: 5.2576 loss: 1.6806 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6806 2023/06/05 17:59:30 - mmengine - INFO - Epoch(train) [134][ 580/2569] lr: 4.0000e-03 eta: 3:11:19 time: 0.2755 data_time: 0.0075 memory: 5828 grad_norm: 5.3550 loss: 2.0558 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0558 2023/06/05 17:59:35 - mmengine - INFO - Epoch(train) [134][ 600/2569] lr: 4.0000e-03 eta: 3:11:14 time: 0.2757 data_time: 0.0073 memory: 5828 grad_norm: 5.2134 loss: 1.7591 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7591 2023/06/05 17:59:41 - mmengine - INFO - Epoch(train) [134][ 620/2569] lr: 4.0000e-03 eta: 3:11:09 time: 0.2748 data_time: 0.0071 memory: 5828 grad_norm: 5.2881 loss: 1.7939 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7939 2023/06/05 17:59:46 - mmengine - INFO - Epoch(train) [134][ 640/2569] lr: 4.0000e-03 eta: 3:11:03 time: 0.2616 data_time: 0.0076 memory: 5828 grad_norm: 5.3343 loss: 1.6146 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6146 2023/06/05 17:59:52 - mmengine - INFO - Epoch(train) [134][ 660/2569] lr: 4.0000e-03 eta: 3:10:58 time: 0.2640 data_time: 0.0069 memory: 5828 grad_norm: 5.2968 loss: 1.9094 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9094 2023/06/05 17:59:57 - mmengine - INFO - Epoch(train) [134][ 680/2569] lr: 4.0000e-03 eta: 3:10:53 time: 0.2713 data_time: 0.0074 memory: 5828 grad_norm: 5.1140 loss: 1.8977 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8977 2023/06/05 18:00:02 - mmengine - INFO - Epoch(train) [134][ 700/2569] lr: 4.0000e-03 eta: 3:10:47 time: 0.2660 data_time: 0.0074 memory: 5828 grad_norm: 5.2546 loss: 1.6557 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6557 2023/06/05 18:00:08 - mmengine - INFO - Epoch(train) [134][ 720/2569] lr: 4.0000e-03 eta: 3:10:42 time: 0.2659 data_time: 0.0073 memory: 5828 grad_norm: 5.1855 loss: 1.7325 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7325 2023/06/05 18:00:13 - mmengine - INFO - Epoch(train) [134][ 740/2569] lr: 4.0000e-03 eta: 3:10:37 time: 0.2703 data_time: 0.0075 memory: 5828 grad_norm: 5.1779 loss: 1.6663 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6663 2023/06/05 18:00:18 - mmengine - INFO - Epoch(train) [134][ 760/2569] lr: 4.0000e-03 eta: 3:10:31 time: 0.2609 data_time: 0.0073 memory: 5828 grad_norm: 5.2631 loss: 1.9662 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9662 2023/06/05 18:00:24 - mmengine - INFO - Epoch(train) [134][ 780/2569] lr: 4.0000e-03 eta: 3:10:26 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 5.2057 loss: 1.6712 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6712 2023/06/05 18:00:29 - mmengine - INFO - Epoch(train) [134][ 800/2569] lr: 4.0000e-03 eta: 3:10:21 time: 0.2602 data_time: 0.0071 memory: 5828 grad_norm: 5.2616 loss: 2.0025 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0025 2023/06/05 18:00:34 - mmengine - INFO - Epoch(train) [134][ 820/2569] lr: 4.0000e-03 eta: 3:10:15 time: 0.2693 data_time: 0.0075 memory: 5828 grad_norm: 5.2059 loss: 1.6161 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6161 2023/06/05 18:00:40 - mmengine - INFO - Epoch(train) [134][ 840/2569] lr: 4.0000e-03 eta: 3:10:10 time: 0.2695 data_time: 0.0076 memory: 5828 grad_norm: 5.2719 loss: 1.5616 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5616 2023/06/05 18:00:45 - mmengine - INFO - Epoch(train) [134][ 860/2569] lr: 4.0000e-03 eta: 3:10:05 time: 0.2631 data_time: 0.0072 memory: 5828 grad_norm: 5.2813 loss: 1.6585 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6585 2023/06/05 18:00:50 - mmengine - INFO - Epoch(train) [134][ 880/2569] lr: 4.0000e-03 eta: 3:09:59 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 5.2235 loss: 1.3904 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3904 2023/06/05 18:00:55 - mmengine - INFO - Epoch(train) [134][ 900/2569] lr: 4.0000e-03 eta: 3:09:54 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 5.2963 loss: 1.5887 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5887 2023/06/05 18:01:01 - mmengine - INFO - Epoch(train) [134][ 920/2569] lr: 4.0000e-03 eta: 3:09:49 time: 0.2685 data_time: 0.0076 memory: 5828 grad_norm: 5.2165 loss: 1.9433 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9433 2023/06/05 18:01:06 - mmengine - INFO - Epoch(train) [134][ 940/2569] lr: 4.0000e-03 eta: 3:09:43 time: 0.2647 data_time: 0.0075 memory: 5828 grad_norm: 5.2290 loss: 1.5929 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5929 2023/06/05 18:01:12 - mmengine - INFO - Epoch(train) [134][ 960/2569] lr: 4.0000e-03 eta: 3:09:38 time: 0.2736 data_time: 0.0075 memory: 5828 grad_norm: 5.3976 loss: 1.6674 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6674 2023/06/05 18:01:17 - mmengine - INFO - Epoch(train) [134][ 980/2569] lr: 4.0000e-03 eta: 3:09:33 time: 0.2755 data_time: 0.0074 memory: 5828 grad_norm: 5.2045 loss: 1.7016 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7016 2023/06/05 18:01:22 - mmengine - INFO - Epoch(train) [134][1000/2569] lr: 4.0000e-03 eta: 3:09:27 time: 0.2645 data_time: 0.0071 memory: 5828 grad_norm: 5.1168 loss: 1.5757 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5757 2023/06/05 18:01:28 - mmengine - INFO - Epoch(train) [134][1020/2569] lr: 4.0000e-03 eta: 3:09:22 time: 0.2629 data_time: 0.0073 memory: 5828 grad_norm: 5.3346 loss: 1.2988 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2988 2023/06/05 18:01:33 - mmengine - INFO - Epoch(train) [134][1040/2569] lr: 4.0000e-03 eta: 3:09:17 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 5.2173 loss: 1.7425 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7425 2023/06/05 18:01:38 - mmengine - INFO - Epoch(train) [134][1060/2569] lr: 4.0000e-03 eta: 3:09:11 time: 0.2622 data_time: 0.0076 memory: 5828 grad_norm: 5.2755 loss: 1.8257 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8257 2023/06/05 18:01:44 - mmengine - INFO - Epoch(train) [134][1080/2569] lr: 4.0000e-03 eta: 3:09:06 time: 0.2688 data_time: 0.0072 memory: 5828 grad_norm: 5.3218 loss: 1.9119 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9119 2023/06/05 18:01:49 - mmengine - INFO - Epoch(train) [134][1100/2569] lr: 4.0000e-03 eta: 3:09:01 time: 0.2689 data_time: 0.0074 memory: 5828 grad_norm: 5.2569 loss: 1.5552 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5552 2023/06/05 18:01:54 - mmengine - INFO - Epoch(train) [134][1120/2569] lr: 4.0000e-03 eta: 3:08:55 time: 0.2702 data_time: 0.0071 memory: 5828 grad_norm: 5.2730 loss: 1.7511 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7511 2023/06/05 18:02:00 - mmengine - INFO - Epoch(train) [134][1140/2569] lr: 4.0000e-03 eta: 3:08:50 time: 0.2690 data_time: 0.0079 memory: 5828 grad_norm: 5.3757 loss: 1.7257 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7257 2023/06/05 18:02:05 - mmengine - INFO - Epoch(train) [134][1160/2569] lr: 4.0000e-03 eta: 3:08:45 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 5.3211 loss: 1.8590 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8590 2023/06/05 18:02:11 - mmengine - INFO - Epoch(train) [134][1180/2569] lr: 4.0000e-03 eta: 3:08:39 time: 0.2729 data_time: 0.0072 memory: 5828 grad_norm: 5.1786 loss: 1.9091 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9091 2023/06/05 18:02:16 - mmengine - INFO - Epoch(train) [134][1200/2569] lr: 4.0000e-03 eta: 3:08:34 time: 0.2604 data_time: 0.0071 memory: 5828 grad_norm: 5.2559 loss: 1.8971 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8971 2023/06/05 18:02:21 - mmengine - INFO - Epoch(train) [134][1220/2569] lr: 4.0000e-03 eta: 3:08:29 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 5.3010 loss: 1.8676 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8676 2023/06/05 18:02:26 - mmengine - INFO - Epoch(train) [134][1240/2569] lr: 4.0000e-03 eta: 3:08:23 time: 0.2639 data_time: 0.0070 memory: 5828 grad_norm: 5.2065 loss: 1.6468 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6468 2023/06/05 18:02:32 - mmengine - INFO - Epoch(train) [134][1260/2569] lr: 4.0000e-03 eta: 3:08:18 time: 0.2806 data_time: 0.0075 memory: 5828 grad_norm: 5.4523 loss: 1.5938 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5938 2023/06/05 18:02:37 - mmengine - INFO - Epoch(train) [134][1280/2569] lr: 4.0000e-03 eta: 3:08:13 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 5.5447 loss: 1.8764 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8764 2023/06/05 18:02:43 - mmengine - INFO - Epoch(train) [134][1300/2569] lr: 4.0000e-03 eta: 3:08:07 time: 0.2746 data_time: 0.0071 memory: 5828 grad_norm: 5.2962 loss: 1.5186 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5186 2023/06/05 18:02:48 - mmengine - INFO - Epoch(train) [134][1320/2569] lr: 4.0000e-03 eta: 3:08:02 time: 0.2681 data_time: 0.0073 memory: 5828 grad_norm: 5.2661 loss: 1.5261 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5261 2023/06/05 18:02:49 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:02:53 - mmengine - INFO - Epoch(train) [134][1340/2569] lr: 4.0000e-03 eta: 3:07:57 time: 0.2672 data_time: 0.0070 memory: 5828 grad_norm: 5.3450 loss: 1.7698 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7698 2023/06/05 18:02:59 - mmengine - INFO - Epoch(train) [134][1360/2569] lr: 4.0000e-03 eta: 3:07:51 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 5.3805 loss: 1.9277 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9277 2023/06/05 18:03:04 - mmengine - INFO - Epoch(train) [134][1380/2569] lr: 4.0000e-03 eta: 3:07:46 time: 0.2684 data_time: 0.0074 memory: 5828 grad_norm: 5.3061 loss: 1.5438 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5438 2023/06/05 18:03:10 - mmengine - INFO - Epoch(train) [134][1400/2569] lr: 4.0000e-03 eta: 3:07:41 time: 0.2670 data_time: 0.0075 memory: 5828 grad_norm: 5.3323 loss: 1.9351 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9351 2023/06/05 18:03:15 - mmengine - INFO - Epoch(train) [134][1420/2569] lr: 4.0000e-03 eta: 3:07:36 time: 0.2720 data_time: 0.0074 memory: 5828 grad_norm: 5.3755 loss: 1.5906 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5906 2023/06/05 18:03:20 - mmengine - INFO - Epoch(train) [134][1440/2569] lr: 4.0000e-03 eta: 3:07:30 time: 0.2699 data_time: 0.0075 memory: 5828 grad_norm: 5.2866 loss: 2.0455 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0455 2023/06/05 18:03:26 - mmengine - INFO - Epoch(train) [134][1460/2569] lr: 4.0000e-03 eta: 3:07:25 time: 0.2650 data_time: 0.0073 memory: 5828 grad_norm: 5.1821 loss: 1.9198 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9198 2023/06/05 18:03:31 - mmengine - INFO - Epoch(train) [134][1480/2569] lr: 4.0000e-03 eta: 3:07:20 time: 0.2818 data_time: 0.0071 memory: 5828 grad_norm: 5.3394 loss: 1.9199 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9199 2023/06/05 18:03:37 - mmengine - INFO - Epoch(train) [134][1500/2569] lr: 4.0000e-03 eta: 3:07:14 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 5.2354 loss: 1.7215 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7215 2023/06/05 18:03:42 - mmengine - INFO - Epoch(train) [134][1520/2569] lr: 4.0000e-03 eta: 3:07:09 time: 0.2701 data_time: 0.0074 memory: 5828 grad_norm: 5.2652 loss: 1.9217 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9217 2023/06/05 18:03:47 - mmengine - INFO - Epoch(train) [134][1540/2569] lr: 4.0000e-03 eta: 3:07:04 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 5.3029 loss: 1.8843 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8843 2023/06/05 18:03:53 - mmengine - INFO - Epoch(train) [134][1560/2569] lr: 4.0000e-03 eta: 3:06:58 time: 0.2671 data_time: 0.0071 memory: 5828 grad_norm: 5.2158 loss: 1.8132 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8132 2023/06/05 18:03:58 - mmengine - INFO - Epoch(train) [134][1580/2569] lr: 4.0000e-03 eta: 3:06:53 time: 0.2669 data_time: 0.0072 memory: 5828 grad_norm: 5.3596 loss: 1.7285 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7285 2023/06/05 18:04:03 - mmengine - INFO - Epoch(train) [134][1600/2569] lr: 4.0000e-03 eta: 3:06:48 time: 0.2624 data_time: 0.0071 memory: 5828 grad_norm: 5.3021 loss: 1.8677 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8677 2023/06/05 18:04:09 - mmengine - INFO - Epoch(train) [134][1620/2569] lr: 4.0000e-03 eta: 3:06:42 time: 0.2661 data_time: 0.0070 memory: 5828 grad_norm: 5.2944 loss: 2.0320 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0320 2023/06/05 18:04:14 - mmengine - INFO - Epoch(train) [134][1640/2569] lr: 4.0000e-03 eta: 3:06:37 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 5.3198 loss: 1.8240 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8240 2023/06/05 18:04:19 - mmengine - INFO - Epoch(train) [134][1660/2569] lr: 4.0000e-03 eta: 3:06:32 time: 0.2712 data_time: 0.0072 memory: 5828 grad_norm: 5.2609 loss: 1.8718 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 1.8718 2023/06/05 18:04:25 - mmengine - INFO - Epoch(train) [134][1680/2569] lr: 4.0000e-03 eta: 3:06:26 time: 0.2653 data_time: 0.0072 memory: 5828 grad_norm: 5.1904 loss: 1.9015 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9015 2023/06/05 18:04:30 - mmengine - INFO - Epoch(train) [134][1700/2569] lr: 4.0000e-03 eta: 3:06:21 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 5.3870 loss: 1.7216 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7216 2023/06/05 18:04:35 - mmengine - INFO - Epoch(train) [134][1720/2569] lr: 4.0000e-03 eta: 3:06:16 time: 0.2608 data_time: 0.0076 memory: 5828 grad_norm: 5.3124 loss: 1.6850 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6850 2023/06/05 18:04:41 - mmengine - INFO - Epoch(train) [134][1740/2569] lr: 4.0000e-03 eta: 3:06:10 time: 0.2743 data_time: 0.0075 memory: 5828 grad_norm: 5.2101 loss: 1.7120 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7120 2023/06/05 18:04:46 - mmengine - INFO - Epoch(train) [134][1760/2569] lr: 4.0000e-03 eta: 3:06:05 time: 0.2629 data_time: 0.0074 memory: 5828 grad_norm: 5.3416 loss: 1.7637 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7637 2023/06/05 18:04:52 - mmengine - INFO - Epoch(train) [134][1780/2569] lr: 4.0000e-03 eta: 3:06:00 time: 0.2700 data_time: 0.0079 memory: 5828 grad_norm: 5.2895 loss: 1.9180 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9180 2023/06/05 18:04:57 - mmengine - INFO - Epoch(train) [134][1800/2569] lr: 4.0000e-03 eta: 3:05:54 time: 0.2610 data_time: 0.0077 memory: 5828 grad_norm: 5.3396 loss: 1.7394 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7394 2023/06/05 18:05:02 - mmengine - INFO - Epoch(train) [134][1820/2569] lr: 4.0000e-03 eta: 3:05:49 time: 0.2634 data_time: 0.0073 memory: 5828 grad_norm: 5.4560 loss: 1.7035 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7035 2023/06/05 18:05:08 - mmengine - INFO - Epoch(train) [134][1840/2569] lr: 4.0000e-03 eta: 3:05:44 time: 0.2749 data_time: 0.0073 memory: 5828 grad_norm: 5.3501 loss: 1.9447 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9447 2023/06/05 18:05:13 - mmengine - INFO - Epoch(train) [134][1860/2569] lr: 4.0000e-03 eta: 3:05:38 time: 0.2782 data_time: 0.0076 memory: 5828 grad_norm: 5.3534 loss: 1.4977 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4977 2023/06/05 18:05:18 - mmengine - INFO - Epoch(train) [134][1880/2569] lr: 4.0000e-03 eta: 3:05:33 time: 0.2646 data_time: 0.0074 memory: 5828 grad_norm: 5.4235 loss: 1.7035 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7035 2023/06/05 18:05:24 - mmengine - INFO - Epoch(train) [134][1900/2569] lr: 4.0000e-03 eta: 3:05:28 time: 0.2680 data_time: 0.0075 memory: 5828 grad_norm: 5.2720 loss: 1.5105 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5105 2023/06/05 18:05:29 - mmengine - INFO - Epoch(train) [134][1920/2569] lr: 4.0000e-03 eta: 3:05:22 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 5.2928 loss: 2.0730 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0730 2023/06/05 18:05:34 - mmengine - INFO - Epoch(train) [134][1940/2569] lr: 4.0000e-03 eta: 3:05:17 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 5.2380 loss: 1.6625 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6625 2023/06/05 18:05:40 - mmengine - INFO - Epoch(train) [134][1960/2569] lr: 4.0000e-03 eta: 3:05:12 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 5.3419 loss: 1.8335 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8335 2023/06/05 18:05:45 - mmengine - INFO - Epoch(train) [134][1980/2569] lr: 4.0000e-03 eta: 3:05:06 time: 0.2707 data_time: 0.0074 memory: 5828 grad_norm: 5.2621 loss: 1.9062 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9062 2023/06/05 18:05:50 - mmengine - INFO - Epoch(train) [134][2000/2569] lr: 4.0000e-03 eta: 3:05:01 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 5.3271 loss: 1.7190 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7190 2023/06/05 18:05:56 - mmengine - INFO - Epoch(train) [134][2020/2569] lr: 4.0000e-03 eta: 3:04:56 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 5.2282 loss: 2.0601 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0601 2023/06/05 18:06:01 - mmengine - INFO - Epoch(train) [134][2040/2569] lr: 4.0000e-03 eta: 3:04:50 time: 0.2665 data_time: 0.0074 memory: 5828 grad_norm: 5.3627 loss: 1.9445 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9445 2023/06/05 18:06:06 - mmengine - INFO - Epoch(train) [134][2060/2569] lr: 4.0000e-03 eta: 3:04:45 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 5.1605 loss: 1.7482 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7482 2023/06/05 18:06:12 - mmengine - INFO - Epoch(train) [134][2080/2569] lr: 4.0000e-03 eta: 3:04:40 time: 0.2686 data_time: 0.0073 memory: 5828 grad_norm: 5.3802 loss: 1.6048 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6048 2023/06/05 18:06:17 - mmengine - INFO - Epoch(train) [134][2100/2569] lr: 4.0000e-03 eta: 3:04:34 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 5.1673 loss: 1.5322 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5322 2023/06/05 18:06:22 - mmengine - INFO - Epoch(train) [134][2120/2569] lr: 4.0000e-03 eta: 3:04:29 time: 0.2678 data_time: 0.0075 memory: 5828 grad_norm: 5.2785 loss: 1.8731 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8731 2023/06/05 18:06:28 - mmengine - INFO - Epoch(train) [134][2140/2569] lr: 4.0000e-03 eta: 3:04:24 time: 0.2713 data_time: 0.0071 memory: 5828 grad_norm: 5.3266 loss: 1.5469 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5469 2023/06/05 18:06:33 - mmengine - INFO - Epoch(train) [134][2160/2569] lr: 4.0000e-03 eta: 3:04:18 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 5.2935 loss: 1.6659 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6659 2023/06/05 18:06:38 - mmengine - INFO - Epoch(train) [134][2180/2569] lr: 4.0000e-03 eta: 3:04:13 time: 0.2698 data_time: 0.0071 memory: 5828 grad_norm: 5.2669 loss: 1.6947 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6947 2023/06/05 18:06:44 - mmengine - INFO - Epoch(train) [134][2200/2569] lr: 4.0000e-03 eta: 3:04:08 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 5.2945 loss: 2.0188 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.0188 2023/06/05 18:06:49 - mmengine - INFO - Epoch(train) [134][2220/2569] lr: 4.0000e-03 eta: 3:04:02 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 5.1885 loss: 1.4612 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.4612 2023/06/05 18:06:54 - mmengine - INFO - Epoch(train) [134][2240/2569] lr: 4.0000e-03 eta: 3:03:57 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 5.2723 loss: 1.8696 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8696 2023/06/05 18:07:00 - mmengine - INFO - Epoch(train) [134][2260/2569] lr: 4.0000e-03 eta: 3:03:52 time: 0.2787 data_time: 0.0072 memory: 5828 grad_norm: 5.3292 loss: 1.9859 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9859 2023/06/05 18:07:05 - mmengine - INFO - Epoch(train) [134][2280/2569] lr: 4.0000e-03 eta: 3:03:46 time: 0.2612 data_time: 0.0075 memory: 5828 grad_norm: 5.2493 loss: 2.1358 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.1358 2023/06/05 18:07:11 - mmengine - INFO - Epoch(train) [134][2300/2569] lr: 4.0000e-03 eta: 3:03:41 time: 0.2769 data_time: 0.0073 memory: 5828 grad_norm: 5.3149 loss: 1.8195 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8195 2023/06/05 18:07:16 - mmengine - INFO - Epoch(train) [134][2320/2569] lr: 4.0000e-03 eta: 3:03:36 time: 0.2613 data_time: 0.0072 memory: 5828 grad_norm: 5.2302 loss: 1.9980 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9980 2023/06/05 18:07:17 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:07:22 - mmengine - INFO - Epoch(train) [134][2340/2569] lr: 4.0000e-03 eta: 3:03:31 time: 0.2762 data_time: 0.0073 memory: 5828 grad_norm: 5.3548 loss: 2.0436 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.0436 2023/06/05 18:07:27 - mmengine - INFO - Epoch(train) [134][2360/2569] lr: 4.0000e-03 eta: 3:03:25 time: 0.2686 data_time: 0.0072 memory: 5828 grad_norm: 5.3744 loss: 1.5991 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5991 2023/06/05 18:07:32 - mmengine - INFO - Epoch(train) [134][2380/2569] lr: 4.0000e-03 eta: 3:03:20 time: 0.2670 data_time: 0.0072 memory: 5828 grad_norm: 5.2858 loss: 1.7294 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7294 2023/06/05 18:07:38 - mmengine - INFO - Epoch(train) [134][2400/2569] lr: 4.0000e-03 eta: 3:03:15 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 5.3862 loss: 1.7718 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.7718 2023/06/05 18:07:43 - mmengine - INFO - Epoch(train) [134][2420/2569] lr: 4.0000e-03 eta: 3:03:09 time: 0.2657 data_time: 0.0074 memory: 5828 grad_norm: 5.3741 loss: 1.5457 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5457 2023/06/05 18:07:49 - mmengine - INFO - Epoch(train) [134][2440/2569] lr: 4.0000e-03 eta: 3:03:04 time: 0.2844 data_time: 0.0073 memory: 5828 grad_norm: 5.3802 loss: 1.6982 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6982 2023/06/05 18:07:54 - mmengine - INFO - Epoch(train) [134][2460/2569] lr: 4.0000e-03 eta: 3:02:59 time: 0.2652 data_time: 0.0073 memory: 5828 grad_norm: 5.3840 loss: 2.0039 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0039 2023/06/05 18:08:00 - mmengine - INFO - Epoch(train) [134][2480/2569] lr: 4.0000e-03 eta: 3:02:53 time: 0.2750 data_time: 0.0070 memory: 5828 grad_norm: 5.3444 loss: 1.9988 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9988 2023/06/05 18:08:05 - mmengine - INFO - Epoch(train) [134][2500/2569] lr: 4.0000e-03 eta: 3:02:48 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 5.2649 loss: 1.5546 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5546 2023/06/05 18:08:10 - mmengine - INFO - Epoch(train) [134][2520/2569] lr: 4.0000e-03 eta: 3:02:43 time: 0.2677 data_time: 0.0077 memory: 5828 grad_norm: 5.2693 loss: 1.5519 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5519 2023/06/05 18:08:16 - mmengine - INFO - Epoch(train) [134][2540/2569] lr: 4.0000e-03 eta: 3:02:37 time: 0.2784 data_time: 0.0071 memory: 5828 grad_norm: 5.2412 loss: 1.3383 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.3383 2023/06/05 18:08:21 - mmengine - INFO - Epoch(train) [134][2560/2569] lr: 4.0000e-03 eta: 3:02:32 time: 0.2591 data_time: 0.0073 memory: 5828 grad_norm: 5.3246 loss: 1.5119 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5119 2023/06/05 18:08:23 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:08:23 - mmengine - INFO - Epoch(train) [134][2569/2569] lr: 4.0000e-03 eta: 3:02:30 time: 0.2524 data_time: 0.0071 memory: 5828 grad_norm: 5.4075 loss: 1.8273 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8273 2023/06/05 18:08:30 - mmengine - INFO - Epoch(train) [135][ 20/2569] lr: 4.0000e-03 eta: 3:02:24 time: 0.3443 data_time: 0.0510 memory: 5828 grad_norm: 5.3729 loss: 1.7952 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7952 2023/06/05 18:08:36 - mmengine - INFO - Epoch(train) [135][ 40/2569] lr: 4.0000e-03 eta: 3:02:19 time: 0.2742 data_time: 0.0072 memory: 5828 grad_norm: 5.2384 loss: 1.9341 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9341 2023/06/05 18:08:41 - mmengine - INFO - Epoch(train) [135][ 60/2569] lr: 4.0000e-03 eta: 3:02:14 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 5.3167 loss: 1.9645 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9645 2023/06/05 18:08:46 - mmengine - INFO - Epoch(train) [135][ 80/2569] lr: 4.0000e-03 eta: 3:02:09 time: 0.2725 data_time: 0.0072 memory: 5828 grad_norm: 5.4410 loss: 1.6575 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6575 2023/06/05 18:08:52 - mmengine - INFO - Epoch(train) [135][ 100/2569] lr: 4.0000e-03 eta: 3:02:03 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 5.4568 loss: 1.6043 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.6043 2023/06/05 18:08:57 - mmengine - INFO - Epoch(train) [135][ 120/2569] lr: 4.0000e-03 eta: 3:01:58 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 5.2459 loss: 1.9296 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9296 2023/06/05 18:09:02 - mmengine - INFO - Epoch(train) [135][ 140/2569] lr: 4.0000e-03 eta: 3:01:53 time: 0.2654 data_time: 0.0076 memory: 5828 grad_norm: 5.2976 loss: 1.8957 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8957 2023/06/05 18:09:08 - mmengine - INFO - Epoch(train) [135][ 160/2569] lr: 4.0000e-03 eta: 3:01:47 time: 0.2655 data_time: 0.0076 memory: 5828 grad_norm: 5.3120 loss: 1.9033 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9033 2023/06/05 18:09:13 - mmengine - INFO - Epoch(train) [135][ 180/2569] lr: 4.0000e-03 eta: 3:01:42 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 5.2213 loss: 1.6180 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6180 2023/06/05 18:09:18 - mmengine - INFO - Epoch(train) [135][ 200/2569] lr: 4.0000e-03 eta: 3:01:37 time: 0.2611 data_time: 0.0072 memory: 5828 grad_norm: 5.3116 loss: 1.7645 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7645 2023/06/05 18:09:24 - mmengine - INFO - Epoch(train) [135][ 220/2569] lr: 4.0000e-03 eta: 3:01:31 time: 0.2745 data_time: 0.0073 memory: 5828 grad_norm: 5.3459 loss: 1.9546 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9546 2023/06/05 18:09:29 - mmengine - INFO - Epoch(train) [135][ 240/2569] lr: 4.0000e-03 eta: 3:01:26 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 5.3394 loss: 1.6323 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6323 2023/06/05 18:09:35 - mmengine - INFO - Epoch(train) [135][ 260/2569] lr: 4.0000e-03 eta: 3:01:21 time: 0.2741 data_time: 0.0076 memory: 5828 grad_norm: 5.4160 loss: 1.7014 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7014 2023/06/05 18:09:40 - mmengine - INFO - Epoch(train) [135][ 280/2569] lr: 4.0000e-03 eta: 3:01:15 time: 0.2670 data_time: 0.0079 memory: 5828 grad_norm: 5.2012 loss: 1.3933 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3933 2023/06/05 18:09:45 - mmengine - INFO - Epoch(train) [135][ 300/2569] lr: 4.0000e-03 eta: 3:01:10 time: 0.2674 data_time: 0.0078 memory: 5828 grad_norm: 5.3237 loss: 1.4735 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4735 2023/06/05 18:09:51 - mmengine - INFO - Epoch(train) [135][ 320/2569] lr: 4.0000e-03 eta: 3:01:05 time: 0.2666 data_time: 0.0082 memory: 5828 grad_norm: 5.3099 loss: 1.8029 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8029 2023/06/05 18:09:56 - mmengine - INFO - Epoch(train) [135][ 340/2569] lr: 4.0000e-03 eta: 3:00:59 time: 0.2626 data_time: 0.0081 memory: 5828 grad_norm: 5.1631 loss: 1.7109 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7109 2023/06/05 18:10:01 - mmengine - INFO - Epoch(train) [135][ 360/2569] lr: 4.0000e-03 eta: 3:00:54 time: 0.2708 data_time: 0.0078 memory: 5828 grad_norm: 5.2705 loss: 1.6248 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6248 2023/06/05 18:10:07 - mmengine - INFO - Epoch(train) [135][ 380/2569] lr: 4.0000e-03 eta: 3:00:49 time: 0.2650 data_time: 0.0074 memory: 5828 grad_norm: 5.4105 loss: 1.6467 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6467 2023/06/05 18:10:12 - mmengine - INFO - Epoch(train) [135][ 400/2569] lr: 4.0000e-03 eta: 3:00:43 time: 0.2671 data_time: 0.0076 memory: 5828 grad_norm: 5.3021 loss: 1.7720 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7720 2023/06/05 18:10:18 - mmengine - INFO - Epoch(train) [135][ 420/2569] lr: 4.0000e-03 eta: 3:00:38 time: 0.2814 data_time: 0.0072 memory: 5828 grad_norm: 5.3731 loss: 1.8022 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8022 2023/06/05 18:10:23 - mmengine - INFO - Epoch(train) [135][ 440/2569] lr: 4.0000e-03 eta: 3:00:33 time: 0.2778 data_time: 0.0078 memory: 5828 grad_norm: 5.4044 loss: 1.6819 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6819 2023/06/05 18:10:29 - mmengine - INFO - Epoch(train) [135][ 460/2569] lr: 4.0000e-03 eta: 3:00:27 time: 0.2675 data_time: 0.0075 memory: 5828 grad_norm: 5.1820 loss: 1.8715 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8715 2023/06/05 18:10:34 - mmengine - INFO - Epoch(train) [135][ 480/2569] lr: 4.0000e-03 eta: 3:00:22 time: 0.2703 data_time: 0.0076 memory: 5828 grad_norm: 5.3775 loss: 1.9008 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9008 2023/06/05 18:10:39 - mmengine - INFO - Epoch(train) [135][ 500/2569] lr: 4.0000e-03 eta: 3:00:17 time: 0.2680 data_time: 0.0074 memory: 5828 grad_norm: 5.3202 loss: 1.6245 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6245 2023/06/05 18:10:45 - mmengine - INFO - Epoch(train) [135][ 520/2569] lr: 4.0000e-03 eta: 3:00:11 time: 0.2643 data_time: 0.0079 memory: 5828 grad_norm: 5.3245 loss: 1.5616 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5616 2023/06/05 18:10:50 - mmengine - INFO - Epoch(train) [135][ 540/2569] lr: 4.0000e-03 eta: 3:00:06 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 5.2207 loss: 1.7411 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.7411 2023/06/05 18:10:55 - mmengine - INFO - Epoch(train) [135][ 560/2569] lr: 4.0000e-03 eta: 3:00:01 time: 0.2670 data_time: 0.0072 memory: 5828 grad_norm: 5.3688 loss: 1.6428 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6428 2023/06/05 18:11:01 - mmengine - INFO - Epoch(train) [135][ 580/2569] lr: 4.0000e-03 eta: 2:59:55 time: 0.2713 data_time: 0.0073 memory: 5828 grad_norm: 5.4545 loss: 1.5867 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.5867 2023/06/05 18:11:06 - mmengine - INFO - Epoch(train) [135][ 600/2569] lr: 4.0000e-03 eta: 2:59:50 time: 0.2671 data_time: 0.0076 memory: 5828 grad_norm: 5.3831 loss: 1.8812 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8812 2023/06/05 18:11:12 - mmengine - INFO - Epoch(train) [135][ 620/2569] lr: 4.0000e-03 eta: 2:59:45 time: 0.2719 data_time: 0.0071 memory: 5828 grad_norm: 5.3645 loss: 1.9125 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9125 2023/06/05 18:11:17 - mmengine - INFO - Epoch(train) [135][ 640/2569] lr: 4.0000e-03 eta: 2:59:39 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 5.3109 loss: 1.8374 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8374 2023/06/05 18:11:22 - mmengine - INFO - Epoch(train) [135][ 660/2569] lr: 4.0000e-03 eta: 2:59:34 time: 0.2706 data_time: 0.0074 memory: 5828 grad_norm: 5.2533 loss: 1.5710 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5710 2023/06/05 18:11:28 - mmengine - INFO - Epoch(train) [135][ 680/2569] lr: 4.0000e-03 eta: 2:59:29 time: 0.2691 data_time: 0.0074 memory: 5828 grad_norm: 5.2249 loss: 1.7038 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7038 2023/06/05 18:11:33 - mmengine - INFO - Epoch(train) [135][ 700/2569] lr: 4.0000e-03 eta: 2:59:23 time: 0.2685 data_time: 0.0079 memory: 5828 grad_norm: 5.3165 loss: 1.8500 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8500 2023/06/05 18:11:39 - mmengine - INFO - Epoch(train) [135][ 720/2569] lr: 4.0000e-03 eta: 2:59:18 time: 0.2803 data_time: 0.0072 memory: 5828 grad_norm: 5.2727 loss: 1.7491 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7491 2023/06/05 18:11:44 - mmengine - INFO - Epoch(train) [135][ 740/2569] lr: 4.0000e-03 eta: 2:59:13 time: 0.2728 data_time: 0.0077 memory: 5828 grad_norm: 5.2163 loss: 1.5506 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5506 2023/06/05 18:11:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:11:50 - mmengine - INFO - Epoch(train) [135][ 760/2569] lr: 4.0000e-03 eta: 2:59:08 time: 0.2658 data_time: 0.0074 memory: 5828 grad_norm: 5.2891 loss: 1.5707 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5707 2023/06/05 18:11:55 - mmengine - INFO - Epoch(train) [135][ 780/2569] lr: 4.0000e-03 eta: 2:59:02 time: 0.2707 data_time: 0.0073 memory: 5828 grad_norm: 5.4643 loss: 1.8289 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8289 2023/06/05 18:12:00 - mmengine - INFO - Epoch(train) [135][ 800/2569] lr: 4.0000e-03 eta: 2:58:57 time: 0.2711 data_time: 0.0073 memory: 5828 grad_norm: 5.3789 loss: 1.9296 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9296 2023/06/05 18:12:06 - mmengine - INFO - Epoch(train) [135][ 820/2569] lr: 4.0000e-03 eta: 2:58:52 time: 0.2716 data_time: 0.0074 memory: 5828 grad_norm: 5.2252 loss: 1.7913 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7913 2023/06/05 18:12:11 - mmengine - INFO - Epoch(train) [135][ 840/2569] lr: 4.0000e-03 eta: 2:58:46 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 5.3392 loss: 1.5734 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5734 2023/06/05 18:12:16 - mmengine - INFO - Epoch(train) [135][ 860/2569] lr: 4.0000e-03 eta: 2:58:41 time: 0.2678 data_time: 0.0069 memory: 5828 grad_norm: 5.3162 loss: 1.8451 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8451 2023/06/05 18:12:22 - mmengine - INFO - Epoch(train) [135][ 880/2569] lr: 4.0000e-03 eta: 2:58:36 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 5.2531 loss: 1.7745 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7745 2023/06/05 18:12:27 - mmengine - INFO - Epoch(train) [135][ 900/2569] lr: 4.0000e-03 eta: 2:58:30 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 5.2609 loss: 1.5864 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5864 2023/06/05 18:12:33 - mmengine - INFO - Epoch(train) [135][ 920/2569] lr: 4.0000e-03 eta: 2:58:25 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 5.3508 loss: 1.9542 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9542 2023/06/05 18:12:38 - mmengine - INFO - Epoch(train) [135][ 940/2569] lr: 4.0000e-03 eta: 2:58:20 time: 0.2755 data_time: 0.0075 memory: 5828 grad_norm: 5.4491 loss: 1.9294 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9294 2023/06/05 18:12:43 - mmengine - INFO - Epoch(train) [135][ 960/2569] lr: 4.0000e-03 eta: 2:58:14 time: 0.2687 data_time: 0.0080 memory: 5828 grad_norm: 5.3498 loss: 1.5985 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5985 2023/06/05 18:12:49 - mmengine - INFO - Epoch(train) [135][ 980/2569] lr: 4.0000e-03 eta: 2:58:09 time: 0.2801 data_time: 0.0073 memory: 5828 grad_norm: 5.3085 loss: 1.7957 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7957 2023/06/05 18:12:55 - mmengine - INFO - Epoch(train) [135][1000/2569] lr: 4.0000e-03 eta: 2:58:04 time: 0.2726 data_time: 0.0073 memory: 5828 grad_norm: 5.3629 loss: 1.6351 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6351 2023/06/05 18:13:00 - mmengine - INFO - Epoch(train) [135][1020/2569] lr: 4.0000e-03 eta: 2:57:58 time: 0.2801 data_time: 0.0076 memory: 5828 grad_norm: 5.3009 loss: 1.5069 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5069 2023/06/05 18:13:05 - mmengine - INFO - Epoch(train) [135][1040/2569] lr: 4.0000e-03 eta: 2:57:53 time: 0.2628 data_time: 0.0074 memory: 5828 grad_norm: 5.2968 loss: 1.6549 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.6549 2023/06/05 18:13:11 - mmengine - INFO - Epoch(train) [135][1060/2569] lr: 4.0000e-03 eta: 2:57:48 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 5.2798 loss: 1.5981 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5981 2023/06/05 18:13:16 - mmengine - INFO - Epoch(train) [135][1080/2569] lr: 4.0000e-03 eta: 2:57:42 time: 0.2624 data_time: 0.0074 memory: 5828 grad_norm: 5.3214 loss: 1.7816 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7816 2023/06/05 18:13:22 - mmengine - INFO - Epoch(train) [135][1100/2569] lr: 4.0000e-03 eta: 2:57:37 time: 0.2734 data_time: 0.0073 memory: 5828 grad_norm: 5.3099 loss: 1.8008 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8008 2023/06/05 18:13:27 - mmengine - INFO - Epoch(train) [135][1120/2569] lr: 4.0000e-03 eta: 2:57:32 time: 0.2606 data_time: 0.0071 memory: 5828 grad_norm: 5.3722 loss: 2.0299 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0299 2023/06/05 18:13:32 - mmengine - INFO - Epoch(train) [135][1140/2569] lr: 4.0000e-03 eta: 2:57:26 time: 0.2731 data_time: 0.0072 memory: 5828 grad_norm: 5.3225 loss: 1.5594 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5594 2023/06/05 18:13:38 - mmengine - INFO - Epoch(train) [135][1160/2569] lr: 4.0000e-03 eta: 2:57:21 time: 0.2673 data_time: 0.0071 memory: 5828 grad_norm: 5.3153 loss: 1.7853 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7853 2023/06/05 18:13:43 - mmengine - INFO - Epoch(train) [135][1180/2569] lr: 4.0000e-03 eta: 2:57:16 time: 0.2725 data_time: 0.0072 memory: 5828 grad_norm: 5.3421 loss: 2.2142 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.2142 2023/06/05 18:13:48 - mmengine - INFO - Epoch(train) [135][1200/2569] lr: 4.0000e-03 eta: 2:57:10 time: 0.2662 data_time: 0.0081 memory: 5828 grad_norm: 5.3451 loss: 1.9869 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9869 2023/06/05 18:13:54 - mmengine - INFO - Epoch(train) [135][1220/2569] lr: 4.0000e-03 eta: 2:57:05 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 5.3519 loss: 2.1120 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1120 2023/06/05 18:13:59 - mmengine - INFO - Epoch(train) [135][1240/2569] lr: 4.0000e-03 eta: 2:57:00 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 5.2800 loss: 1.7584 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7584 2023/06/05 18:14:04 - mmengine - INFO - Epoch(train) [135][1260/2569] lr: 4.0000e-03 eta: 2:56:54 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 5.3080 loss: 1.7500 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7500 2023/06/05 18:14:10 - mmengine - INFO - Epoch(train) [135][1280/2569] lr: 4.0000e-03 eta: 2:56:49 time: 0.2628 data_time: 0.0074 memory: 5828 grad_norm: 5.4562 loss: 1.9825 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9825 2023/06/05 18:14:15 - mmengine - INFO - Epoch(train) [135][1300/2569] lr: 4.0000e-03 eta: 2:56:44 time: 0.2778 data_time: 0.0074 memory: 5828 grad_norm: 5.3214 loss: 1.5851 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5851 2023/06/05 18:14:21 - mmengine - INFO - Epoch(train) [135][1320/2569] lr: 4.0000e-03 eta: 2:56:39 time: 0.2724 data_time: 0.0075 memory: 5828 grad_norm: 5.3662 loss: 1.8236 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8236 2023/06/05 18:14:26 - mmengine - INFO - Epoch(train) [135][1340/2569] lr: 4.0000e-03 eta: 2:56:33 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 5.2791 loss: 1.8177 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8177 2023/06/05 18:14:31 - mmengine - INFO - Epoch(train) [135][1360/2569] lr: 4.0000e-03 eta: 2:56:28 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 5.2685 loss: 1.8463 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8463 2023/06/05 18:14:37 - mmengine - INFO - Epoch(train) [135][1380/2569] lr: 4.0000e-03 eta: 2:56:23 time: 0.2756 data_time: 0.0072 memory: 5828 grad_norm: 5.3133 loss: 1.7402 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7402 2023/06/05 18:14:42 - mmengine - INFO - Epoch(train) [135][1400/2569] lr: 4.0000e-03 eta: 2:56:17 time: 0.2635 data_time: 0.0072 memory: 5828 grad_norm: 5.2620 loss: 1.8386 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8386 2023/06/05 18:14:48 - mmengine - INFO - Epoch(train) [135][1420/2569] lr: 4.0000e-03 eta: 2:56:12 time: 0.2678 data_time: 0.0070 memory: 5828 grad_norm: 5.1746 loss: 1.8353 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8353 2023/06/05 18:14:53 - mmengine - INFO - Epoch(train) [135][1440/2569] lr: 4.0000e-03 eta: 2:56:07 time: 0.2735 data_time: 0.0073 memory: 5828 grad_norm: 5.3664 loss: 1.8196 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8196 2023/06/05 18:14:58 - mmengine - INFO - Epoch(train) [135][1460/2569] lr: 4.0000e-03 eta: 2:56:01 time: 0.2637 data_time: 0.0074 memory: 5828 grad_norm: 5.4196 loss: 1.9151 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9151 2023/06/05 18:15:04 - mmengine - INFO - Epoch(train) [135][1480/2569] lr: 4.0000e-03 eta: 2:55:56 time: 0.2691 data_time: 0.0075 memory: 5828 grad_norm: 5.4311 loss: 1.7246 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7246 2023/06/05 18:15:09 - mmengine - INFO - Epoch(train) [135][1500/2569] lr: 4.0000e-03 eta: 2:55:51 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 5.2344 loss: 1.7934 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7934 2023/06/05 18:15:14 - mmengine - INFO - Epoch(train) [135][1520/2569] lr: 4.0000e-03 eta: 2:55:45 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 5.2367 loss: 1.8005 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8005 2023/06/05 18:15:20 - mmengine - INFO - Epoch(train) [135][1540/2569] lr: 4.0000e-03 eta: 2:55:40 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 5.3508 loss: 1.4749 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4749 2023/06/05 18:15:25 - mmengine - INFO - Epoch(train) [135][1560/2569] lr: 4.0000e-03 eta: 2:55:35 time: 0.2639 data_time: 0.0072 memory: 5828 grad_norm: 5.4594 loss: 1.5675 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5675 2023/06/05 18:15:30 - mmengine - INFO - Epoch(train) [135][1580/2569] lr: 4.0000e-03 eta: 2:55:29 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 5.3910 loss: 1.8303 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.8303 2023/06/05 18:15:36 - mmengine - INFO - Epoch(train) [135][1600/2569] lr: 4.0000e-03 eta: 2:55:24 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 5.3292 loss: 1.7176 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7176 2023/06/05 18:15:41 - mmengine - INFO - Epoch(train) [135][1620/2569] lr: 4.0000e-03 eta: 2:55:19 time: 0.2668 data_time: 0.0074 memory: 5828 grad_norm: 5.2690 loss: 1.9695 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9695 2023/06/05 18:15:46 - mmengine - INFO - Epoch(train) [135][1640/2569] lr: 4.0000e-03 eta: 2:55:13 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 5.3012 loss: 1.6198 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6198 2023/06/05 18:15:52 - mmengine - INFO - Epoch(train) [135][1660/2569] lr: 4.0000e-03 eta: 2:55:08 time: 0.2721 data_time: 0.0071 memory: 5828 grad_norm: 5.3698 loss: 2.3913 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.3913 2023/06/05 18:15:57 - mmengine - INFO - Epoch(train) [135][1680/2569] lr: 4.0000e-03 eta: 2:55:03 time: 0.2634 data_time: 0.0073 memory: 5828 grad_norm: 5.3398 loss: 1.7064 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.7064 2023/06/05 18:16:02 - mmengine - INFO - Epoch(train) [135][1700/2569] lr: 4.0000e-03 eta: 2:54:57 time: 0.2696 data_time: 0.0073 memory: 5828 grad_norm: 5.3294 loss: 1.6775 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6775 2023/06/05 18:16:08 - mmengine - INFO - Epoch(train) [135][1720/2569] lr: 4.0000e-03 eta: 2:54:52 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 5.4675 loss: 1.8329 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8329 2023/06/05 18:16:13 - mmengine - INFO - Epoch(train) [135][1740/2569] lr: 4.0000e-03 eta: 2:54:47 time: 0.2661 data_time: 0.0073 memory: 5828 grad_norm: 5.4099 loss: 1.9127 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9127 2023/06/05 18:16:17 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:16:18 - mmengine - INFO - Epoch(train) [135][1760/2569] lr: 4.0000e-03 eta: 2:54:41 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 5.3599 loss: 1.6491 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6491 2023/06/05 18:16:24 - mmengine - INFO - Epoch(train) [135][1780/2569] lr: 4.0000e-03 eta: 2:54:36 time: 0.2697 data_time: 0.0071 memory: 5828 grad_norm: 5.4213 loss: 1.5896 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5896 2023/06/05 18:16:29 - mmengine - INFO - Epoch(train) [135][1800/2569] lr: 4.0000e-03 eta: 2:54:31 time: 0.2661 data_time: 0.0072 memory: 5828 grad_norm: 5.3195 loss: 1.7281 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7281 2023/06/05 18:16:34 - mmengine - INFO - Epoch(train) [135][1820/2569] lr: 4.0000e-03 eta: 2:54:25 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 5.2060 loss: 1.8610 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8610 2023/06/05 18:16:40 - mmengine - INFO - Epoch(train) [135][1840/2569] lr: 4.0000e-03 eta: 2:54:20 time: 0.2650 data_time: 0.0073 memory: 5828 grad_norm: 5.2612 loss: 1.8091 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8091 2023/06/05 18:16:45 - mmengine - INFO - Epoch(train) [135][1860/2569] lr: 4.0000e-03 eta: 2:54:15 time: 0.2669 data_time: 0.0072 memory: 5828 grad_norm: 5.2795 loss: 1.7566 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7566 2023/06/05 18:16:50 - mmengine - INFO - Epoch(train) [135][1880/2569] lr: 4.0000e-03 eta: 2:54:09 time: 0.2635 data_time: 0.0071 memory: 5828 grad_norm: 5.3904 loss: 1.5997 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5997 2023/06/05 18:16:56 - mmengine - INFO - Epoch(train) [135][1900/2569] lr: 4.0000e-03 eta: 2:54:04 time: 0.2688 data_time: 0.0075 memory: 5828 grad_norm: 5.3422 loss: 1.7661 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7661 2023/06/05 18:17:01 - mmengine - INFO - Epoch(train) [135][1920/2569] lr: 4.0000e-03 eta: 2:53:59 time: 0.2741 data_time: 0.0079 memory: 5828 grad_norm: 5.3533 loss: 1.5435 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5435 2023/06/05 18:17:07 - mmengine - INFO - Epoch(train) [135][1940/2569] lr: 4.0000e-03 eta: 2:53:53 time: 0.2746 data_time: 0.0075 memory: 5828 grad_norm: 5.3352 loss: 1.7466 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7466 2023/06/05 18:17:12 - mmengine - INFO - Epoch(train) [135][1960/2569] lr: 4.0000e-03 eta: 2:53:48 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 5.4029 loss: 2.0031 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0031 2023/06/05 18:17:17 - mmengine - INFO - Epoch(train) [135][1980/2569] lr: 4.0000e-03 eta: 2:53:43 time: 0.2604 data_time: 0.0081 memory: 5828 grad_norm: 5.3330 loss: 1.9839 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9839 2023/06/05 18:17:23 - mmengine - INFO - Epoch(train) [135][2000/2569] lr: 4.0000e-03 eta: 2:53:37 time: 0.2636 data_time: 0.0077 memory: 5828 grad_norm: 5.4339 loss: 1.9112 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9112 2023/06/05 18:17:28 - mmengine - INFO - Epoch(train) [135][2020/2569] lr: 4.0000e-03 eta: 2:53:32 time: 0.2630 data_time: 0.0074 memory: 5828 grad_norm: 5.3172 loss: 2.0070 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0070 2023/06/05 18:17:33 - mmengine - INFO - Epoch(train) [135][2040/2569] lr: 4.0000e-03 eta: 2:53:27 time: 0.2665 data_time: 0.0076 memory: 5828 grad_norm: 5.3312 loss: 1.9592 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9592 2023/06/05 18:17:38 - mmengine - INFO - Epoch(train) [135][2060/2569] lr: 4.0000e-03 eta: 2:53:21 time: 0.2682 data_time: 0.0074 memory: 5828 grad_norm: 5.2411 loss: 1.7846 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7846 2023/06/05 18:17:44 - mmengine - INFO - Epoch(train) [135][2080/2569] lr: 4.0000e-03 eta: 2:53:16 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 5.3224 loss: 1.6196 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6196 2023/06/05 18:17:49 - mmengine - INFO - Epoch(train) [135][2100/2569] lr: 4.0000e-03 eta: 2:53:11 time: 0.2728 data_time: 0.0070 memory: 5828 grad_norm: 5.3819 loss: 1.5627 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5627 2023/06/05 18:17:55 - mmengine - INFO - Epoch(train) [135][2120/2569] lr: 4.0000e-03 eta: 2:53:05 time: 0.2625 data_time: 0.0076 memory: 5828 grad_norm: 5.2955 loss: 1.7299 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7299 2023/06/05 18:18:00 - mmengine - INFO - Epoch(train) [135][2140/2569] lr: 4.0000e-03 eta: 2:53:00 time: 0.2894 data_time: 0.0077 memory: 5828 grad_norm: 5.3394 loss: 1.8974 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8974 2023/06/05 18:18:06 - mmengine - INFO - Epoch(train) [135][2160/2569] lr: 4.0000e-03 eta: 2:52:55 time: 0.2710 data_time: 0.0074 memory: 5828 grad_norm: 5.3396 loss: 2.1793 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 2.1793 2023/06/05 18:18:11 - mmengine - INFO - Epoch(train) [135][2180/2569] lr: 4.0000e-03 eta: 2:52:50 time: 0.2713 data_time: 0.0083 memory: 5828 grad_norm: 5.4449 loss: 1.7553 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7553 2023/06/05 18:18:17 - mmengine - INFO - Epoch(train) [135][2200/2569] lr: 4.0000e-03 eta: 2:52:44 time: 0.2651 data_time: 0.0072 memory: 5828 grad_norm: 5.3652 loss: 1.8031 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8031 2023/06/05 18:18:22 - mmengine - INFO - Epoch(train) [135][2220/2569] lr: 4.0000e-03 eta: 2:52:39 time: 0.2716 data_time: 0.0073 memory: 5828 grad_norm: 5.4186 loss: 1.4693 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4693 2023/06/05 18:18:27 - mmengine - INFO - Epoch(train) [135][2240/2569] lr: 4.0000e-03 eta: 2:52:34 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 5.2820 loss: 1.6983 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6983 2023/06/05 18:18:33 - mmengine - INFO - Epoch(train) [135][2260/2569] lr: 4.0000e-03 eta: 2:52:28 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 5.4895 loss: 1.5645 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5645 2023/06/05 18:18:38 - mmengine - INFO - Epoch(train) [135][2280/2569] lr: 4.0000e-03 eta: 2:52:23 time: 0.2725 data_time: 0.0073 memory: 5828 grad_norm: 5.3353 loss: 1.8444 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8444 2023/06/05 18:18:43 - mmengine - INFO - Epoch(train) [135][2300/2569] lr: 4.0000e-03 eta: 2:52:18 time: 0.2616 data_time: 0.0075 memory: 5828 grad_norm: 5.2469 loss: 1.7140 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7140 2023/06/05 18:18:49 - mmengine - INFO - Epoch(train) [135][2320/2569] lr: 4.0000e-03 eta: 2:52:12 time: 0.2763 data_time: 0.0074 memory: 5828 grad_norm: 5.2533 loss: 2.0051 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0051 2023/06/05 18:18:54 - mmengine - INFO - Epoch(train) [135][2340/2569] lr: 4.0000e-03 eta: 2:52:07 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 5.3682 loss: 1.7852 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7852 2023/06/05 18:19:00 - mmengine - INFO - Epoch(train) [135][2360/2569] lr: 4.0000e-03 eta: 2:52:02 time: 0.2784 data_time: 0.0074 memory: 5828 grad_norm: 5.4494 loss: 1.6172 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6172 2023/06/05 18:19:05 - mmengine - INFO - Epoch(train) [135][2380/2569] lr: 4.0000e-03 eta: 2:51:56 time: 0.2711 data_time: 0.0074 memory: 5828 grad_norm: 5.3047 loss: 1.8110 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.8110 2023/06/05 18:19:10 - mmengine - INFO - Epoch(train) [135][2400/2569] lr: 4.0000e-03 eta: 2:51:51 time: 0.2666 data_time: 0.0078 memory: 5828 grad_norm: 5.2808 loss: 1.6603 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6603 2023/06/05 18:19:16 - mmengine - INFO - Epoch(train) [135][2420/2569] lr: 4.0000e-03 eta: 2:51:46 time: 0.2601 data_time: 0.0075 memory: 5828 grad_norm: 5.4720 loss: 1.5261 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5261 2023/06/05 18:19:21 - mmengine - INFO - Epoch(train) [135][2440/2569] lr: 4.0000e-03 eta: 2:51:40 time: 0.2674 data_time: 0.0077 memory: 5828 grad_norm: 5.3659 loss: 1.6890 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6890 2023/06/05 18:19:26 - mmengine - INFO - Epoch(train) [135][2460/2569] lr: 4.0000e-03 eta: 2:51:35 time: 0.2665 data_time: 0.0076 memory: 5828 grad_norm: 5.4006 loss: 1.8012 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8012 2023/06/05 18:19:32 - mmengine - INFO - Epoch(train) [135][2480/2569] lr: 4.0000e-03 eta: 2:51:30 time: 0.2649 data_time: 0.0079 memory: 5828 grad_norm: 5.4349 loss: 2.0694 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0694 2023/06/05 18:19:37 - mmengine - INFO - Epoch(train) [135][2500/2569] lr: 4.0000e-03 eta: 2:51:24 time: 0.2736 data_time: 0.0076 memory: 5828 grad_norm: 5.3633 loss: 1.9485 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9485 2023/06/05 18:19:43 - mmengine - INFO - Epoch(train) [135][2520/2569] lr: 4.0000e-03 eta: 2:51:19 time: 0.2734 data_time: 0.0069 memory: 5828 grad_norm: 5.3760 loss: 1.7036 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7036 2023/06/05 18:19:48 - mmengine - INFO - Epoch(train) [135][2540/2569] lr: 4.0000e-03 eta: 2:51:14 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 5.3312 loss: 1.8039 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8039 2023/06/05 18:19:53 - mmengine - INFO - Epoch(train) [135][2560/2569] lr: 4.0000e-03 eta: 2:51:08 time: 0.2703 data_time: 0.0074 memory: 5828 grad_norm: 5.3005 loss: 1.5960 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5960 2023/06/05 18:19:56 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:19:56 - mmengine - INFO - Epoch(train) [135][2569/2569] lr: 4.0000e-03 eta: 2:51:06 time: 0.2592 data_time: 0.0074 memory: 5828 grad_norm: 5.3727 loss: 1.4835 top1_acc: 0.5000 top5_acc: 0.8333 loss_cls: 1.4835 2023/06/05 18:19:59 - mmengine - INFO - Epoch(val) [135][ 20/260] eta: 0:00:40 time: 0.1695 data_time: 0.1106 memory: 1238 2023/06/05 18:20:02 - mmengine - INFO - Epoch(val) [135][ 40/260] eta: 0:00:33 time: 0.1329 data_time: 0.0744 memory: 1238 2023/06/05 18:20:04 - mmengine - INFO - Epoch(val) [135][ 60/260] eta: 0:00:29 time: 0.1351 data_time: 0.0760 memory: 1238 2023/06/05 18:20:07 - mmengine - INFO - Epoch(val) [135][ 80/260] eta: 0:00:25 time: 0.1236 data_time: 0.0649 memory: 1238 2023/06/05 18:20:10 - mmengine - INFO - Epoch(val) [135][100/260] eta: 0:00:22 time: 0.1507 data_time: 0.0919 memory: 1238 2023/06/05 18:20:12 - mmengine - INFO - Epoch(val) [135][120/260] eta: 0:00:19 time: 0.1273 data_time: 0.0684 memory: 1238 2023/06/05 18:20:16 - mmengine - INFO - Epoch(val) [135][140/260] eta: 0:00:17 time: 0.1583 data_time: 0.0994 memory: 1238 2023/06/05 18:20:18 - mmengine - INFO - Epoch(val) [135][160/260] eta: 0:00:13 time: 0.1214 data_time: 0.0630 memory: 1238 2023/06/05 18:20:21 - mmengine - INFO - Epoch(val) [135][180/260] eta: 0:00:11 time: 0.1357 data_time: 0.0774 memory: 1238 2023/06/05 18:20:23 - mmengine - INFO - Epoch(val) [135][200/260] eta: 0:00:08 time: 0.1271 data_time: 0.0683 memory: 1238 2023/06/05 18:20:26 - mmengine - INFO - Epoch(val) [135][220/260] eta: 0:00:05 time: 0.1139 data_time: 0.0552 memory: 1238 2023/06/05 18:20:28 - mmengine - INFO - Epoch(val) [135][240/260] eta: 0:00:02 time: 0.1408 data_time: 0.0816 memory: 1238 2023/06/05 18:20:31 - mmengine - INFO - Epoch(val) [135][260/260] eta: 0:00:00 time: 0.1198 data_time: 0.0626 memory: 1238 2023/06/05 18:20:42 - mmengine - INFO - Epoch(val) [135][260/260] acc/top1: 0.6188 acc/top5: 0.8322 acc/mean1: 0.6125 data_time: 0.0761 time: 0.1348 2023/06/05 18:20:48 - mmengine - INFO - Epoch(train) [136][ 20/2569] lr: 4.0000e-03 eta: 2:51:01 time: 0.3293 data_time: 0.0505 memory: 5828 grad_norm: 5.2697 loss: 1.8619 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8619 2023/06/05 18:20:53 - mmengine - INFO - Epoch(train) [136][ 40/2569] lr: 4.0000e-03 eta: 2:50:55 time: 0.2624 data_time: 0.0071 memory: 5828 grad_norm: 5.4334 loss: 1.7269 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7269 2023/06/05 18:20:59 - mmengine - INFO - Epoch(train) [136][ 60/2569] lr: 4.0000e-03 eta: 2:50:50 time: 0.2697 data_time: 0.0075 memory: 5828 grad_norm: 5.4752 loss: 1.7234 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7234 2023/06/05 18:21:04 - mmengine - INFO - Epoch(train) [136][ 80/2569] lr: 4.0000e-03 eta: 2:50:45 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 5.3956 loss: 1.8743 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8743 2023/06/05 18:21:09 - mmengine - INFO - Epoch(train) [136][ 100/2569] lr: 4.0000e-03 eta: 2:50:39 time: 0.2646 data_time: 0.0074 memory: 5828 grad_norm: 5.3066 loss: 1.7960 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7960 2023/06/05 18:21:15 - mmengine - INFO - Epoch(train) [136][ 120/2569] lr: 4.0000e-03 eta: 2:50:34 time: 0.2669 data_time: 0.0070 memory: 5828 grad_norm: 5.3108 loss: 1.9350 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9350 2023/06/05 18:21:20 - mmengine - INFO - Epoch(train) [136][ 140/2569] lr: 4.0000e-03 eta: 2:50:29 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 5.3188 loss: 1.7026 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7026 2023/06/05 18:21:26 - mmengine - INFO - Epoch(train) [136][ 160/2569] lr: 4.0000e-03 eta: 2:50:23 time: 0.2739 data_time: 0.0078 memory: 5828 grad_norm: 5.3118 loss: 1.6750 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6750 2023/06/05 18:21:31 - mmengine - INFO - Epoch(train) [136][ 180/2569] lr: 4.0000e-03 eta: 2:50:18 time: 0.2671 data_time: 0.0077 memory: 5828 grad_norm: 5.3482 loss: 1.9972 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9972 2023/06/05 18:21:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:21:37 - mmengine - INFO - Epoch(train) [136][ 200/2569] lr: 4.0000e-03 eta: 2:50:13 time: 0.2815 data_time: 0.0072 memory: 5828 grad_norm: 5.3714 loss: 1.6544 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6544 2023/06/05 18:21:42 - mmengine - INFO - Epoch(train) [136][ 220/2569] lr: 4.0000e-03 eta: 2:50:08 time: 0.2674 data_time: 0.0070 memory: 5828 grad_norm: 5.3363 loss: 1.8137 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8137 2023/06/05 18:21:47 - mmengine - INFO - Epoch(train) [136][ 240/2569] lr: 4.0000e-03 eta: 2:50:02 time: 0.2704 data_time: 0.0071 memory: 5828 grad_norm: 5.4341 loss: 1.4525 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.4525 2023/06/05 18:21:53 - mmengine - INFO - Epoch(train) [136][ 260/2569] lr: 4.0000e-03 eta: 2:49:57 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 5.3323 loss: 1.6152 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6152 2023/06/05 18:21:58 - mmengine - INFO - Epoch(train) [136][ 280/2569] lr: 4.0000e-03 eta: 2:49:52 time: 0.2704 data_time: 0.0073 memory: 5828 grad_norm: 5.3732 loss: 1.9325 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9325 2023/06/05 18:22:04 - mmengine - INFO - Epoch(train) [136][ 300/2569] lr: 4.0000e-03 eta: 2:49:46 time: 0.2727 data_time: 0.0075 memory: 5828 grad_norm: 5.2617 loss: 1.5841 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5841 2023/06/05 18:22:09 - mmengine - INFO - Epoch(train) [136][ 320/2569] lr: 4.0000e-03 eta: 2:49:41 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 5.1935 loss: 1.8339 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8339 2023/06/05 18:22:14 - mmengine - INFO - Epoch(train) [136][ 340/2569] lr: 4.0000e-03 eta: 2:49:36 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 5.2563 loss: 1.5019 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5019 2023/06/05 18:22:20 - mmengine - INFO - Epoch(train) [136][ 360/2569] lr: 4.0000e-03 eta: 2:49:30 time: 0.2684 data_time: 0.0074 memory: 5828 grad_norm: 5.3580 loss: 1.7210 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7210 2023/06/05 18:22:25 - mmengine - INFO - Epoch(train) [136][ 380/2569] lr: 4.0000e-03 eta: 2:49:25 time: 0.2738 data_time: 0.0073 memory: 5828 grad_norm: 5.4538 loss: 1.8379 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.8379 2023/06/05 18:22:31 - mmengine - INFO - Epoch(train) [136][ 400/2569] lr: 4.0000e-03 eta: 2:49:20 time: 0.2809 data_time: 0.0072 memory: 5828 grad_norm: 5.3280 loss: 1.5932 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5932 2023/06/05 18:22:36 - mmengine - INFO - Epoch(train) [136][ 420/2569] lr: 4.0000e-03 eta: 2:49:14 time: 0.2666 data_time: 0.0075 memory: 5828 grad_norm: 5.4764 loss: 1.6252 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6252 2023/06/05 18:22:42 - mmengine - INFO - Epoch(train) [136][ 440/2569] lr: 4.0000e-03 eta: 2:49:09 time: 0.2710 data_time: 0.0071 memory: 5828 grad_norm: 5.3902 loss: 1.8782 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8782 2023/06/05 18:22:47 - mmengine - INFO - Epoch(train) [136][ 460/2569] lr: 4.0000e-03 eta: 2:49:04 time: 0.2637 data_time: 0.0075 memory: 5828 grad_norm: 5.3633 loss: 1.5917 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5917 2023/06/05 18:22:52 - mmengine - INFO - Epoch(train) [136][ 480/2569] lr: 4.0000e-03 eta: 2:48:58 time: 0.2712 data_time: 0.0077 memory: 5828 grad_norm: 5.5582 loss: 1.7331 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7331 2023/06/05 18:22:58 - mmengine - INFO - Epoch(train) [136][ 500/2569] lr: 4.0000e-03 eta: 2:48:53 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 5.3888 loss: 1.8841 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8841 2023/06/05 18:23:03 - mmengine - INFO - Epoch(train) [136][ 520/2569] lr: 4.0000e-03 eta: 2:48:48 time: 0.2651 data_time: 0.0072 memory: 5828 grad_norm: 5.2205 loss: 1.7703 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.7703 2023/06/05 18:23:09 - mmengine - INFO - Epoch(train) [136][ 540/2569] lr: 4.0000e-03 eta: 2:48:42 time: 0.2800 data_time: 0.0072 memory: 5828 grad_norm: 5.4297 loss: 1.4412 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.4412 2023/06/05 18:23:14 - mmengine - INFO - Epoch(train) [136][ 560/2569] lr: 4.0000e-03 eta: 2:48:37 time: 0.2671 data_time: 0.0076 memory: 5828 grad_norm: 5.4664 loss: 1.6988 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6988 2023/06/05 18:23:20 - mmengine - INFO - Epoch(train) [136][ 580/2569] lr: 4.0000e-03 eta: 2:48:32 time: 0.2731 data_time: 0.0074 memory: 5828 grad_norm: 5.2325 loss: 1.5500 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5500 2023/06/05 18:23:25 - mmengine - INFO - Epoch(train) [136][ 600/2569] lr: 4.0000e-03 eta: 2:48:26 time: 0.2661 data_time: 0.0069 memory: 5828 grad_norm: 5.3868 loss: 1.7554 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7554 2023/06/05 18:23:30 - mmengine - INFO - Epoch(train) [136][ 620/2569] lr: 4.0000e-03 eta: 2:48:21 time: 0.2739 data_time: 0.0074 memory: 5828 grad_norm: 5.3995 loss: 1.7560 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7560 2023/06/05 18:23:36 - mmengine - INFO - Epoch(train) [136][ 640/2569] lr: 4.0000e-03 eta: 2:48:16 time: 0.2611 data_time: 0.0072 memory: 5828 grad_norm: 5.3788 loss: 1.7168 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.7168 2023/06/05 18:23:41 - mmengine - INFO - Epoch(train) [136][ 660/2569] lr: 4.0000e-03 eta: 2:48:10 time: 0.2740 data_time: 0.0073 memory: 5828 grad_norm: 5.3061 loss: 1.8840 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8840 2023/06/05 18:23:47 - mmengine - INFO - Epoch(train) [136][ 680/2569] lr: 4.0000e-03 eta: 2:48:05 time: 0.2735 data_time: 0.0073 memory: 5828 grad_norm: 5.3715 loss: 1.5527 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5527 2023/06/05 18:23:52 - mmengine - INFO - Epoch(train) [136][ 700/2569] lr: 4.0000e-03 eta: 2:48:00 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 5.5369 loss: 1.6867 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.6867 2023/06/05 18:23:57 - mmengine - INFO - Epoch(train) [136][ 720/2569] lr: 4.0000e-03 eta: 2:47:54 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 5.4006 loss: 1.7184 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7184 2023/06/05 18:24:02 - mmengine - INFO - Epoch(train) [136][ 740/2569] lr: 4.0000e-03 eta: 2:47:49 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 5.3379 loss: 1.7669 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7669 2023/06/05 18:24:08 - mmengine - INFO - Epoch(train) [136][ 760/2569] lr: 4.0000e-03 eta: 2:47:44 time: 0.2645 data_time: 0.0076 memory: 5828 grad_norm: 5.4308 loss: 1.5017 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5017 2023/06/05 18:24:13 - mmengine - INFO - Epoch(train) [136][ 780/2569] lr: 4.0000e-03 eta: 2:47:38 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 5.3557 loss: 1.8727 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8727 2023/06/05 18:24:19 - mmengine - INFO - Epoch(train) [136][ 800/2569] lr: 4.0000e-03 eta: 2:47:33 time: 0.2709 data_time: 0.0075 memory: 5828 grad_norm: 5.4102 loss: 1.7129 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7129 2023/06/05 18:24:24 - mmengine - INFO - Epoch(train) [136][ 820/2569] lr: 4.0000e-03 eta: 2:47:28 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 5.3204 loss: 1.6885 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6885 2023/06/05 18:24:29 - mmengine - INFO - Epoch(train) [136][ 840/2569] lr: 4.0000e-03 eta: 2:47:23 time: 0.2636 data_time: 0.0077 memory: 5828 grad_norm: 5.2440 loss: 1.9433 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9433 2023/06/05 18:24:34 - mmengine - INFO - Epoch(train) [136][ 860/2569] lr: 4.0000e-03 eta: 2:47:17 time: 0.2626 data_time: 0.0079 memory: 5828 grad_norm: 5.2995 loss: 1.7975 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.7975 2023/06/05 18:24:40 - mmengine - INFO - Epoch(train) [136][ 880/2569] lr: 4.0000e-03 eta: 2:47:12 time: 0.2644 data_time: 0.0075 memory: 5828 grad_norm: 5.4236 loss: 1.6493 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6493 2023/06/05 18:24:45 - mmengine - INFO - Epoch(train) [136][ 900/2569] lr: 4.0000e-03 eta: 2:47:07 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 5.3661 loss: 1.8267 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8267 2023/06/05 18:24:50 - mmengine - INFO - Epoch(train) [136][ 920/2569] lr: 4.0000e-03 eta: 2:47:01 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 5.4657 loss: 1.9223 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9223 2023/06/05 18:24:56 - mmengine - INFO - Epoch(train) [136][ 940/2569] lr: 4.0000e-03 eta: 2:46:56 time: 0.2616 data_time: 0.0075 memory: 5828 grad_norm: 5.2926 loss: 1.8054 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8054 2023/06/05 18:25:01 - mmengine - INFO - Epoch(train) [136][ 960/2569] lr: 4.0000e-03 eta: 2:46:51 time: 0.2688 data_time: 0.0075 memory: 5828 grad_norm: 5.3635 loss: 1.7820 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7820 2023/06/05 18:25:07 - mmengine - INFO - Epoch(train) [136][ 980/2569] lr: 4.0000e-03 eta: 2:46:45 time: 0.2834 data_time: 0.0074 memory: 5828 grad_norm: 5.3737 loss: 1.5131 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5131 2023/06/05 18:25:12 - mmengine - INFO - Epoch(train) [136][1000/2569] lr: 4.0000e-03 eta: 2:46:40 time: 0.2684 data_time: 0.0075 memory: 5828 grad_norm: 5.3070 loss: 1.8801 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8801 2023/06/05 18:25:18 - mmengine - INFO - Epoch(train) [136][1020/2569] lr: 4.0000e-03 eta: 2:46:35 time: 0.2728 data_time: 0.0075 memory: 5828 grad_norm: 5.2914 loss: 1.6691 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6691 2023/06/05 18:25:23 - mmengine - INFO - Epoch(train) [136][1040/2569] lr: 4.0000e-03 eta: 2:46:29 time: 0.2638 data_time: 0.0076 memory: 5828 grad_norm: 5.3912 loss: 1.4737 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4737 2023/06/05 18:25:28 - mmengine - INFO - Epoch(train) [136][1060/2569] lr: 4.0000e-03 eta: 2:46:24 time: 0.2782 data_time: 0.0072 memory: 5828 grad_norm: 5.4038 loss: 1.8344 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8344 2023/06/05 18:25:34 - mmengine - INFO - Epoch(train) [136][1080/2569] lr: 4.0000e-03 eta: 2:46:19 time: 0.2628 data_time: 0.0073 memory: 5828 grad_norm: 5.3748 loss: 1.8261 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8261 2023/06/05 18:25:39 - mmengine - INFO - Epoch(train) [136][1100/2569] lr: 4.0000e-03 eta: 2:46:13 time: 0.2701 data_time: 0.0074 memory: 5828 grad_norm: 5.2982 loss: 1.7066 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7066 2023/06/05 18:25:45 - mmengine - INFO - Epoch(train) [136][1120/2569] lr: 4.0000e-03 eta: 2:46:08 time: 0.2686 data_time: 0.0073 memory: 5828 grad_norm: 5.3731 loss: 1.6360 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6360 2023/06/05 18:25:50 - mmengine - INFO - Epoch(train) [136][1140/2569] lr: 4.0000e-03 eta: 2:46:03 time: 0.2721 data_time: 0.0069 memory: 5828 grad_norm: 5.2668 loss: 1.7446 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7446 2023/06/05 18:25:55 - mmengine - INFO - Epoch(train) [136][1160/2569] lr: 4.0000e-03 eta: 2:45:57 time: 0.2748 data_time: 0.0074 memory: 5828 grad_norm: 5.3899 loss: 1.6786 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6786 2023/06/05 18:26:01 - mmengine - INFO - Epoch(train) [136][1180/2569] lr: 4.0000e-03 eta: 2:45:52 time: 0.2813 data_time: 0.0073 memory: 5828 grad_norm: 5.3190 loss: 1.8454 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8454 2023/06/05 18:26:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:26:06 - mmengine - INFO - Epoch(train) [136][1200/2569] lr: 4.0000e-03 eta: 2:45:47 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 5.3368 loss: 1.5858 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5858 2023/06/05 18:26:12 - mmengine - INFO - Epoch(train) [136][1220/2569] lr: 4.0000e-03 eta: 2:45:41 time: 0.2784 data_time: 0.0073 memory: 5828 grad_norm: 5.3431 loss: 1.7744 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7744 2023/06/05 18:26:17 - mmengine - INFO - Epoch(train) [136][1240/2569] lr: 4.0000e-03 eta: 2:45:36 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 5.3704 loss: 1.7372 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7372 2023/06/05 18:26:23 - mmengine - INFO - Epoch(train) [136][1260/2569] lr: 4.0000e-03 eta: 2:45:31 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 5.4032 loss: 1.6711 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6711 2023/06/05 18:26:28 - mmengine - INFO - Epoch(train) [136][1280/2569] lr: 4.0000e-03 eta: 2:45:25 time: 0.2734 data_time: 0.0072 memory: 5828 grad_norm: 5.2965 loss: 1.8722 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8722 2023/06/05 18:26:33 - mmengine - INFO - Epoch(train) [136][1300/2569] lr: 4.0000e-03 eta: 2:45:20 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 5.3916 loss: 1.5029 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5029 2023/06/05 18:26:39 - mmengine - INFO - Epoch(train) [136][1320/2569] lr: 4.0000e-03 eta: 2:45:15 time: 0.2754 data_time: 0.0073 memory: 5828 grad_norm: 5.4805 loss: 1.6417 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6417 2023/06/05 18:26:44 - mmengine - INFO - Epoch(train) [136][1340/2569] lr: 4.0000e-03 eta: 2:45:09 time: 0.2619 data_time: 0.0083 memory: 5828 grad_norm: 5.5161 loss: 1.5864 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5864 2023/06/05 18:26:50 - mmengine - INFO - Epoch(train) [136][1360/2569] lr: 4.0000e-03 eta: 2:45:04 time: 0.2788 data_time: 0.0073 memory: 5828 grad_norm: 5.3043 loss: 2.1740 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1740 2023/06/05 18:26:55 - mmengine - INFO - Epoch(train) [136][1380/2569] lr: 4.0000e-03 eta: 2:44:59 time: 0.2728 data_time: 0.0072 memory: 5828 grad_norm: 5.3868 loss: 1.9019 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9019 2023/06/05 18:27:01 - mmengine - INFO - Epoch(train) [136][1400/2569] lr: 4.0000e-03 eta: 2:44:53 time: 0.2686 data_time: 0.0073 memory: 5828 grad_norm: 5.4441 loss: 1.7084 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7084 2023/06/05 18:27:06 - mmengine - INFO - Epoch(train) [136][1420/2569] lr: 4.0000e-03 eta: 2:44:48 time: 0.2684 data_time: 0.0074 memory: 5828 grad_norm: 5.3583 loss: 1.8373 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8373 2023/06/05 18:27:11 - mmengine - INFO - Epoch(train) [136][1440/2569] lr: 4.0000e-03 eta: 2:44:43 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 5.3975 loss: 1.6378 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6378 2023/06/05 18:27:17 - mmengine - INFO - Epoch(train) [136][1460/2569] lr: 4.0000e-03 eta: 2:44:38 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 5.4527 loss: 2.0592 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0592 2023/06/05 18:27:22 - mmengine - INFO - Epoch(train) [136][1480/2569] lr: 4.0000e-03 eta: 2:44:32 time: 0.2720 data_time: 0.0072 memory: 5828 grad_norm: 5.4027 loss: 1.7436 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7436 2023/06/05 18:27:28 - mmengine - INFO - Epoch(train) [136][1500/2569] lr: 4.0000e-03 eta: 2:44:27 time: 0.2721 data_time: 0.0071 memory: 5828 grad_norm: 5.3225 loss: 1.6707 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6707 2023/06/05 18:27:33 - mmengine - INFO - Epoch(train) [136][1520/2569] lr: 4.0000e-03 eta: 2:44:22 time: 0.2680 data_time: 0.0077 memory: 5828 grad_norm: 5.4284 loss: 1.8448 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8448 2023/06/05 18:27:38 - mmengine - INFO - Epoch(train) [136][1540/2569] lr: 4.0000e-03 eta: 2:44:16 time: 0.2632 data_time: 0.0070 memory: 5828 grad_norm: 5.3977 loss: 1.7350 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7350 2023/06/05 18:27:43 - mmengine - INFO - Epoch(train) [136][1560/2569] lr: 4.0000e-03 eta: 2:44:11 time: 0.2643 data_time: 0.0082 memory: 5828 grad_norm: 5.3962 loss: 2.0196 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0196 2023/06/05 18:27:49 - mmengine - INFO - Epoch(train) [136][1580/2569] lr: 4.0000e-03 eta: 2:44:06 time: 0.2682 data_time: 0.0077 memory: 5828 grad_norm: 5.3340 loss: 1.7375 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.7375 2023/06/05 18:27:54 - mmengine - INFO - Epoch(train) [136][1600/2569] lr: 4.0000e-03 eta: 2:44:00 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 5.3988 loss: 1.8009 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8009 2023/06/05 18:28:00 - mmengine - INFO - Epoch(train) [136][1620/2569] lr: 4.0000e-03 eta: 2:43:55 time: 0.2646 data_time: 0.0077 memory: 5828 grad_norm: 5.4659 loss: 1.8031 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8031 2023/06/05 18:28:05 - mmengine - INFO - Epoch(train) [136][1640/2569] lr: 4.0000e-03 eta: 2:43:50 time: 0.2719 data_time: 0.0071 memory: 5828 grad_norm: 5.3723 loss: 1.8504 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8504 2023/06/05 18:28:11 - mmengine - INFO - Epoch(train) [136][1660/2569] lr: 4.0000e-03 eta: 2:43:44 time: 0.2763 data_time: 0.0072 memory: 5828 grad_norm: 5.3137 loss: 1.9364 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9364 2023/06/05 18:28:16 - mmengine - INFO - Epoch(train) [136][1680/2569] lr: 4.0000e-03 eta: 2:43:39 time: 0.2706 data_time: 0.0070 memory: 5828 grad_norm: 5.3662 loss: 1.4751 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4751 2023/06/05 18:28:21 - mmengine - INFO - Epoch(train) [136][1700/2569] lr: 4.0000e-03 eta: 2:43:34 time: 0.2679 data_time: 0.0077 memory: 5828 grad_norm: 5.4197 loss: 1.5974 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5974 2023/06/05 18:28:27 - mmengine - INFO - Epoch(train) [136][1720/2569] lr: 4.0000e-03 eta: 2:43:28 time: 0.2721 data_time: 0.0074 memory: 5828 grad_norm: 5.3487 loss: 1.7175 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7175 2023/06/05 18:28:32 - mmengine - INFO - Epoch(train) [136][1740/2569] lr: 4.0000e-03 eta: 2:43:23 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 5.3855 loss: 1.7674 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7674 2023/06/05 18:28:37 - mmengine - INFO - Epoch(train) [136][1760/2569] lr: 4.0000e-03 eta: 2:43:18 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 5.3199 loss: 1.7146 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7146 2023/06/05 18:28:43 - mmengine - INFO - Epoch(train) [136][1780/2569] lr: 4.0000e-03 eta: 2:43:12 time: 0.2724 data_time: 0.0074 memory: 5828 grad_norm: 5.4731 loss: 1.8498 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 1.8498 2023/06/05 18:28:48 - mmengine - INFO - Epoch(train) [136][1800/2569] lr: 4.0000e-03 eta: 2:43:07 time: 0.2645 data_time: 0.0073 memory: 5828 grad_norm: 5.4153 loss: 1.6672 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6672 2023/06/05 18:28:53 - mmengine - INFO - Epoch(train) [136][1820/2569] lr: 4.0000e-03 eta: 2:43:02 time: 0.2621 data_time: 0.0069 memory: 5828 grad_norm: 5.3685 loss: 1.6092 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6092 2023/06/05 18:28:59 - mmengine - INFO - Epoch(train) [136][1840/2569] lr: 4.0000e-03 eta: 2:42:56 time: 0.2739 data_time: 0.0071 memory: 5828 grad_norm: 5.2926 loss: 1.6859 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6859 2023/06/05 18:29:04 - mmengine - INFO - Epoch(train) [136][1860/2569] lr: 4.0000e-03 eta: 2:42:51 time: 0.2742 data_time: 0.0072 memory: 5828 grad_norm: 5.3983 loss: 1.7839 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7839 2023/06/05 18:29:10 - mmengine - INFO - Epoch(train) [136][1880/2569] lr: 4.0000e-03 eta: 2:42:46 time: 0.2662 data_time: 0.0079 memory: 5828 grad_norm: 5.3604 loss: 1.5156 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5156 2023/06/05 18:29:15 - mmengine - INFO - Epoch(train) [136][1900/2569] lr: 4.0000e-03 eta: 2:42:40 time: 0.2681 data_time: 0.0074 memory: 5828 grad_norm: 5.3702 loss: 1.8165 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8165 2023/06/05 18:29:21 - mmengine - INFO - Epoch(train) [136][1920/2569] lr: 4.0000e-03 eta: 2:42:35 time: 0.2685 data_time: 0.0077 memory: 5828 grad_norm: 5.3578 loss: 1.4856 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.4856 2023/06/05 18:29:26 - mmengine - INFO - Epoch(train) [136][1940/2569] lr: 4.0000e-03 eta: 2:42:30 time: 0.2709 data_time: 0.0073 memory: 5828 grad_norm: 5.3580 loss: 1.8238 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8238 2023/06/05 18:29:31 - mmengine - INFO - Epoch(train) [136][1960/2569] lr: 4.0000e-03 eta: 2:42:24 time: 0.2631 data_time: 0.0075 memory: 5828 grad_norm: 5.6451 loss: 1.8727 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8727 2023/06/05 18:29:37 - mmengine - INFO - Epoch(train) [136][1980/2569] lr: 4.0000e-03 eta: 2:42:19 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 5.4596 loss: 1.9102 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9102 2023/06/05 18:29:42 - mmengine - INFO - Epoch(train) [136][2000/2569] lr: 4.0000e-03 eta: 2:42:14 time: 0.2638 data_time: 0.0075 memory: 5828 grad_norm: 5.3638 loss: 1.6450 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6450 2023/06/05 18:29:47 - mmengine - INFO - Epoch(train) [136][2020/2569] lr: 4.0000e-03 eta: 2:42:08 time: 0.2724 data_time: 0.0074 memory: 5828 grad_norm: 5.3377 loss: 1.7544 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7544 2023/06/05 18:29:53 - mmengine - INFO - Epoch(train) [136][2040/2569] lr: 4.0000e-03 eta: 2:42:03 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 5.3158 loss: 1.7421 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7421 2023/06/05 18:29:58 - mmengine - INFO - Epoch(train) [136][2060/2569] lr: 4.0000e-03 eta: 2:41:58 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 5.4540 loss: 1.6938 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.6938 2023/06/05 18:30:03 - mmengine - INFO - Epoch(train) [136][2080/2569] lr: 4.0000e-03 eta: 2:41:52 time: 0.2708 data_time: 0.0077 memory: 5828 grad_norm: 5.4804 loss: 1.9106 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9106 2023/06/05 18:30:09 - mmengine - INFO - Epoch(train) [136][2100/2569] lr: 4.0000e-03 eta: 2:41:47 time: 0.2775 data_time: 0.0073 memory: 5828 grad_norm: 5.5089 loss: 1.7741 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7741 2023/06/05 18:30:14 - mmengine - INFO - Epoch(train) [136][2120/2569] lr: 4.0000e-03 eta: 2:41:42 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 5.3806 loss: 1.8768 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8768 2023/06/05 18:30:20 - mmengine - INFO - Epoch(train) [136][2140/2569] lr: 4.0000e-03 eta: 2:41:36 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 5.3092 loss: 1.7929 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7929 2023/06/05 18:30:25 - mmengine - INFO - Epoch(train) [136][2160/2569] lr: 4.0000e-03 eta: 2:41:31 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 5.3523 loss: 1.7898 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7898 2023/06/05 18:30:30 - mmengine - INFO - Epoch(train) [136][2180/2569] lr: 4.0000e-03 eta: 2:41:26 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 5.3375 loss: 1.7868 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7868 2023/06/05 18:30:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:30:36 - mmengine - INFO - Epoch(train) [136][2200/2569] lr: 4.0000e-03 eta: 2:41:21 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 5.3161 loss: 1.8115 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8115 2023/06/05 18:30:41 - mmengine - INFO - Epoch(train) [136][2220/2569] lr: 4.0000e-03 eta: 2:41:15 time: 0.2609 data_time: 0.0073 memory: 5828 grad_norm: 5.3049 loss: 1.7311 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7311 2023/06/05 18:30:46 - mmengine - INFO - Epoch(train) [136][2240/2569] lr: 4.0000e-03 eta: 2:41:10 time: 0.2679 data_time: 0.0072 memory: 5828 grad_norm: 5.4337 loss: 1.6369 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6369 2023/06/05 18:30:52 - mmengine - INFO - Epoch(train) [136][2260/2569] lr: 4.0000e-03 eta: 2:41:05 time: 0.2678 data_time: 0.0076 memory: 5828 grad_norm: 5.3369 loss: 1.5197 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5197 2023/06/05 18:30:57 - mmengine - INFO - Epoch(train) [136][2280/2569] lr: 4.0000e-03 eta: 2:40:59 time: 0.2628 data_time: 0.0070 memory: 5828 grad_norm: 5.3505 loss: 1.6830 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6830 2023/06/05 18:31:02 - mmengine - INFO - Epoch(train) [136][2300/2569] lr: 4.0000e-03 eta: 2:40:54 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 5.3726 loss: 1.8430 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.8430 2023/06/05 18:31:07 - mmengine - INFO - Epoch(train) [136][2320/2569] lr: 4.0000e-03 eta: 2:40:49 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 5.2704 loss: 1.8409 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8409 2023/06/05 18:31:13 - mmengine - INFO - Epoch(train) [136][2340/2569] lr: 4.0000e-03 eta: 2:40:43 time: 0.2740 data_time: 0.0072 memory: 5828 grad_norm: 5.3828 loss: 1.6919 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6919 2023/06/05 18:31:18 - mmengine - INFO - Epoch(train) [136][2360/2569] lr: 4.0000e-03 eta: 2:40:38 time: 0.2687 data_time: 0.0075 memory: 5828 grad_norm: 5.3206 loss: 1.7938 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7938 2023/06/05 18:31:24 - mmengine - INFO - Epoch(train) [136][2380/2569] lr: 4.0000e-03 eta: 2:40:33 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 5.4709 loss: 1.8247 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8247 2023/06/05 18:31:29 - mmengine - INFO - Epoch(train) [136][2400/2569] lr: 4.0000e-03 eta: 2:40:27 time: 0.2644 data_time: 0.0080 memory: 5828 grad_norm: 5.3171 loss: 1.8479 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8479 2023/06/05 18:31:34 - mmengine - INFO - Epoch(train) [136][2420/2569] lr: 4.0000e-03 eta: 2:40:22 time: 0.2623 data_time: 0.0070 memory: 5828 grad_norm: 5.3573 loss: 1.6667 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6667 2023/06/05 18:31:40 - mmengine - INFO - Epoch(train) [136][2440/2569] lr: 4.0000e-03 eta: 2:40:17 time: 0.2848 data_time: 0.0073 memory: 5828 grad_norm: 5.4467 loss: 1.8014 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8014 2023/06/05 18:31:45 - mmengine - INFO - Epoch(train) [136][2460/2569] lr: 4.0000e-03 eta: 2:40:11 time: 0.2699 data_time: 0.0075 memory: 5828 grad_norm: 5.3873 loss: 1.7937 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7937 2023/06/05 18:31:51 - mmengine - INFO - Epoch(train) [136][2480/2569] lr: 4.0000e-03 eta: 2:40:06 time: 0.2697 data_time: 0.0074 memory: 5828 grad_norm: 5.3622 loss: 1.6531 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6531 2023/06/05 18:31:56 - mmengine - INFO - Epoch(train) [136][2500/2569] lr: 4.0000e-03 eta: 2:40:01 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 5.4242 loss: 1.8153 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8153 2023/06/05 18:32:01 - mmengine - INFO - Epoch(train) [136][2520/2569] lr: 4.0000e-03 eta: 2:39:55 time: 0.2658 data_time: 0.0076 memory: 5828 grad_norm: 5.4875 loss: 1.9475 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9475 2023/06/05 18:32:07 - mmengine - INFO - Epoch(train) [136][2540/2569] lr: 4.0000e-03 eta: 2:39:50 time: 0.2714 data_time: 0.0073 memory: 5828 grad_norm: 5.4197 loss: 1.8783 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8783 2023/06/05 18:32:12 - mmengine - INFO - Epoch(train) [136][2560/2569] lr: 4.0000e-03 eta: 2:39:45 time: 0.2588 data_time: 0.0073 memory: 5828 grad_norm: 5.2342 loss: 1.6085 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6085 2023/06/05 18:32:14 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:32:14 - mmengine - INFO - Epoch(train) [136][2569/2569] lr: 4.0000e-03 eta: 2:39:42 time: 0.2526 data_time: 0.0072 memory: 5828 grad_norm: 5.3564 loss: 1.6112 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.6112 2023/06/05 18:32:14 - mmengine - INFO - Saving checkpoint at 136 epochs 2023/06/05 18:32:22 - mmengine - INFO - Epoch(train) [137][ 20/2569] lr: 4.0000e-03 eta: 2:39:37 time: 0.3110 data_time: 0.0495 memory: 5828 grad_norm: 5.4264 loss: 1.8184 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.8184 2023/06/05 18:32:28 - mmengine - INFO - Epoch(train) [137][ 40/2569] lr: 4.0000e-03 eta: 2:39:32 time: 0.2651 data_time: 0.0069 memory: 5828 grad_norm: 5.4615 loss: 1.5995 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.5995 2023/06/05 18:32:33 - mmengine - INFO - Epoch(train) [137][ 60/2569] lr: 4.0000e-03 eta: 2:39:26 time: 0.2760 data_time: 0.0071 memory: 5828 grad_norm: 5.2765 loss: 1.6375 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6375 2023/06/05 18:32:39 - mmengine - INFO - Epoch(train) [137][ 80/2569] lr: 4.0000e-03 eta: 2:39:21 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 5.3972 loss: 1.8454 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8454 2023/06/05 18:32:44 - mmengine - INFO - Epoch(train) [137][ 100/2569] lr: 4.0000e-03 eta: 2:39:16 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 5.3202 loss: 1.5850 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5850 2023/06/05 18:32:49 - mmengine - INFO - Epoch(train) [137][ 120/2569] lr: 4.0000e-03 eta: 2:39:10 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 5.3922 loss: 2.0073 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0073 2023/06/05 18:32:54 - mmengine - INFO - Epoch(train) [137][ 140/2569] lr: 4.0000e-03 eta: 2:39:05 time: 0.2645 data_time: 0.0072 memory: 5828 grad_norm: 5.4237 loss: 1.7580 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7580 2023/06/05 18:33:00 - mmengine - INFO - Epoch(train) [137][ 160/2569] lr: 4.0000e-03 eta: 2:39:00 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 5.5199 loss: 1.9295 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9295 2023/06/05 18:33:05 - mmengine - INFO - Epoch(train) [137][ 180/2569] lr: 4.0000e-03 eta: 2:38:54 time: 0.2710 data_time: 0.0076 memory: 5828 grad_norm: 5.4301 loss: 1.6821 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6821 2023/06/05 18:33:10 - mmengine - INFO - Epoch(train) [137][ 200/2569] lr: 4.0000e-03 eta: 2:38:49 time: 0.2633 data_time: 0.0071 memory: 5828 grad_norm: 5.4286 loss: 1.5806 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5806 2023/06/05 18:33:16 - mmengine - INFO - Epoch(train) [137][ 220/2569] lr: 4.0000e-03 eta: 2:38:44 time: 0.2721 data_time: 0.0076 memory: 5828 grad_norm: 5.4159 loss: 2.2379 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.2379 2023/06/05 18:33:21 - mmengine - INFO - Epoch(train) [137][ 240/2569] lr: 4.0000e-03 eta: 2:38:38 time: 0.2710 data_time: 0.0073 memory: 5828 grad_norm: 5.4112 loss: 1.5097 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5097 2023/06/05 18:33:27 - mmengine - INFO - Epoch(train) [137][ 260/2569] lr: 4.0000e-03 eta: 2:38:33 time: 0.2706 data_time: 0.0076 memory: 5828 grad_norm: 5.4005 loss: 1.6932 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6932 2023/06/05 18:33:32 - mmengine - INFO - Epoch(train) [137][ 280/2569] lr: 4.0000e-03 eta: 2:38:28 time: 0.2635 data_time: 0.0074 memory: 5828 grad_norm: 5.4052 loss: 1.6840 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.6840 2023/06/05 18:33:37 - mmengine - INFO - Epoch(train) [137][ 300/2569] lr: 4.0000e-03 eta: 2:38:22 time: 0.2707 data_time: 0.0071 memory: 5828 grad_norm: 5.4970 loss: 1.9953 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9953 2023/06/05 18:33:43 - mmengine - INFO - Epoch(train) [137][ 320/2569] lr: 4.0000e-03 eta: 2:38:17 time: 0.2652 data_time: 0.0073 memory: 5828 grad_norm: 5.3715 loss: 2.1519 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.1519 2023/06/05 18:33:48 - mmengine - INFO - Epoch(train) [137][ 340/2569] lr: 4.0000e-03 eta: 2:38:12 time: 0.2719 data_time: 0.0072 memory: 5828 grad_norm: 5.3266 loss: 1.8748 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8748 2023/06/05 18:33:54 - mmengine - INFO - Epoch(train) [137][ 360/2569] lr: 4.0000e-03 eta: 2:38:06 time: 0.2681 data_time: 0.0074 memory: 5828 grad_norm: 5.3099 loss: 1.6070 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6070 2023/06/05 18:33:59 - mmengine - INFO - Epoch(train) [137][ 380/2569] lr: 4.0000e-03 eta: 2:38:01 time: 0.2656 data_time: 0.0075 memory: 5828 grad_norm: 5.3801 loss: 1.6502 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6502 2023/06/05 18:34:04 - mmengine - INFO - Epoch(train) [137][ 400/2569] lr: 4.0000e-03 eta: 2:37:56 time: 0.2682 data_time: 0.0074 memory: 5828 grad_norm: 5.2515 loss: 1.6611 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6611 2023/06/05 18:34:10 - mmengine - INFO - Epoch(train) [137][ 420/2569] lr: 4.0000e-03 eta: 2:37:50 time: 0.2655 data_time: 0.0077 memory: 5828 grad_norm: 5.3905 loss: 1.7123 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.7123 2023/06/05 18:34:15 - mmengine - INFO - Epoch(train) [137][ 440/2569] lr: 4.0000e-03 eta: 2:37:45 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 5.5315 loss: 1.5507 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5507 2023/06/05 18:34:20 - mmengine - INFO - Epoch(train) [137][ 460/2569] lr: 4.0000e-03 eta: 2:37:40 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 5.5349 loss: 1.7566 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.7566 2023/06/05 18:34:26 - mmengine - INFO - Epoch(train) [137][ 480/2569] lr: 4.0000e-03 eta: 2:37:34 time: 0.2686 data_time: 0.0076 memory: 5828 grad_norm: 5.4343 loss: 1.5918 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5918 2023/06/05 18:34:31 - mmengine - INFO - Epoch(train) [137][ 500/2569] lr: 4.0000e-03 eta: 2:37:29 time: 0.2799 data_time: 0.0084 memory: 5828 grad_norm: 5.2781 loss: 1.7945 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.7945 2023/06/05 18:34:37 - mmengine - INFO - Epoch(train) [137][ 520/2569] lr: 4.0000e-03 eta: 2:37:24 time: 0.2707 data_time: 0.0084 memory: 5828 grad_norm: 5.4171 loss: 1.4374 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.4374 2023/06/05 18:34:42 - mmengine - INFO - Epoch(train) [137][ 540/2569] lr: 4.0000e-03 eta: 2:37:18 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 5.4391 loss: 1.7619 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.7619 2023/06/05 18:34:47 - mmengine - INFO - Epoch(train) [137][ 560/2569] lr: 4.0000e-03 eta: 2:37:13 time: 0.2662 data_time: 0.0083 memory: 5828 grad_norm: 5.4550 loss: 1.6830 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6830 2023/06/05 18:34:53 - mmengine - INFO - Epoch(train) [137][ 580/2569] lr: 4.0000e-03 eta: 2:37:08 time: 0.2686 data_time: 0.0074 memory: 5828 grad_norm: 5.4191 loss: 1.4211 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4211 2023/06/05 18:34:58 - mmengine - INFO - Epoch(train) [137][ 600/2569] lr: 4.0000e-03 eta: 2:37:02 time: 0.2626 data_time: 0.0073 memory: 5828 grad_norm: 5.4142 loss: 1.7105 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7105 2023/06/05 18:35:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:35:03 - mmengine - INFO - Epoch(train) [137][ 620/2569] lr: 4.0000e-03 eta: 2:36:57 time: 0.2623 data_time: 0.0071 memory: 5828 grad_norm: 5.4619 loss: 1.6149 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6149 2023/06/05 18:35:09 - mmengine - INFO - Epoch(train) [137][ 640/2569] lr: 4.0000e-03 eta: 2:36:52 time: 0.2711 data_time: 0.0070 memory: 5828 grad_norm: 5.4509 loss: 1.9072 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9072 2023/06/05 18:35:14 - mmengine - INFO - Epoch(train) [137][ 660/2569] lr: 4.0000e-03 eta: 2:36:47 time: 0.2663 data_time: 0.0075 memory: 5828 grad_norm: 5.3142 loss: 1.4362 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4362 2023/06/05 18:35:19 - mmengine - INFO - Epoch(train) [137][ 680/2569] lr: 4.0000e-03 eta: 2:36:41 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 5.5611 loss: 1.5396 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5396 2023/06/05 18:35:25 - mmengine - INFO - Epoch(train) [137][ 700/2569] lr: 4.0000e-03 eta: 2:36:36 time: 0.2704 data_time: 0.0073 memory: 5828 grad_norm: 5.3553 loss: 1.6148 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6148 2023/06/05 18:35:30 - mmengine - INFO - Epoch(train) [137][ 720/2569] lr: 4.0000e-03 eta: 2:36:31 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 5.3947 loss: 1.6907 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6907 2023/06/05 18:35:36 - mmengine - INFO - Epoch(train) [137][ 740/2569] lr: 4.0000e-03 eta: 2:36:25 time: 0.2697 data_time: 0.0072 memory: 5828 grad_norm: 5.3598 loss: 1.8150 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8150 2023/06/05 18:35:41 - mmengine - INFO - Epoch(train) [137][ 760/2569] lr: 4.0000e-03 eta: 2:36:20 time: 0.2655 data_time: 0.0073 memory: 5828 grad_norm: 5.3392 loss: 1.6277 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6277 2023/06/05 18:35:46 - mmengine - INFO - Epoch(train) [137][ 780/2569] lr: 4.0000e-03 eta: 2:36:15 time: 0.2642 data_time: 0.0070 memory: 5828 grad_norm: 5.3734 loss: 1.7257 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7257 2023/06/05 18:35:51 - mmengine - INFO - Epoch(train) [137][ 800/2569] lr: 4.0000e-03 eta: 2:36:09 time: 0.2659 data_time: 0.0072 memory: 5828 grad_norm: 5.3726 loss: 1.8629 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8629 2023/06/05 18:35:57 - mmengine - INFO - Epoch(train) [137][ 820/2569] lr: 4.0000e-03 eta: 2:36:04 time: 0.2724 data_time: 0.0075 memory: 5828 grad_norm: 5.4109 loss: 1.6707 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6707 2023/06/05 18:36:02 - mmengine - INFO - Epoch(train) [137][ 840/2569] lr: 4.0000e-03 eta: 2:35:59 time: 0.2691 data_time: 0.0074 memory: 5828 grad_norm: 5.4317 loss: 1.6766 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6766 2023/06/05 18:36:08 - mmengine - INFO - Epoch(train) [137][ 860/2569] lr: 4.0000e-03 eta: 2:35:53 time: 0.2621 data_time: 0.0071 memory: 5828 grad_norm: 5.3989 loss: 1.9654 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9654 2023/06/05 18:36:13 - mmengine - INFO - Epoch(train) [137][ 880/2569] lr: 4.0000e-03 eta: 2:35:48 time: 0.2728 data_time: 0.0074 memory: 5828 grad_norm: 5.4305 loss: 1.8368 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8368 2023/06/05 18:36:18 - mmengine - INFO - Epoch(train) [137][ 900/2569] lr: 4.0000e-03 eta: 2:35:43 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 5.4222 loss: 1.7392 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7392 2023/06/05 18:36:24 - mmengine - INFO - Epoch(train) [137][ 920/2569] lr: 4.0000e-03 eta: 2:35:37 time: 0.2751 data_time: 0.0073 memory: 5828 grad_norm: 5.2850 loss: 1.4100 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4100 2023/06/05 18:36:29 - mmengine - INFO - Epoch(train) [137][ 940/2569] lr: 4.0000e-03 eta: 2:35:32 time: 0.2728 data_time: 0.0072 memory: 5828 grad_norm: 5.4651 loss: 1.6956 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6956 2023/06/05 18:36:35 - mmengine - INFO - Epoch(train) [137][ 960/2569] lr: 4.0000e-03 eta: 2:35:27 time: 0.2679 data_time: 0.0077 memory: 5828 grad_norm: 5.4028 loss: 1.5745 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5745 2023/06/05 18:36:40 - mmengine - INFO - Epoch(train) [137][ 980/2569] lr: 4.0000e-03 eta: 2:35:21 time: 0.2659 data_time: 0.0081 memory: 5828 grad_norm: 5.3448 loss: 1.7656 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7656 2023/06/05 18:36:46 - mmengine - INFO - Epoch(train) [137][1000/2569] lr: 4.0000e-03 eta: 2:35:16 time: 0.2745 data_time: 0.0076 memory: 5828 grad_norm: 5.4084 loss: 1.6794 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6794 2023/06/05 18:36:51 - mmengine - INFO - Epoch(train) [137][1020/2569] lr: 4.0000e-03 eta: 2:35:11 time: 0.2802 data_time: 0.0073 memory: 5828 grad_norm: 5.4801 loss: 1.9405 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9405 2023/06/05 18:36:57 - mmengine - INFO - Epoch(train) [137][1040/2569] lr: 4.0000e-03 eta: 2:35:05 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 5.3657 loss: 1.4773 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4773 2023/06/05 18:37:02 - mmengine - INFO - Epoch(train) [137][1060/2569] lr: 4.0000e-03 eta: 2:35:00 time: 0.2744 data_time: 0.0074 memory: 5828 grad_norm: 5.4862 loss: 1.7371 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7371 2023/06/05 18:37:07 - mmengine - INFO - Epoch(train) [137][1080/2569] lr: 4.0000e-03 eta: 2:34:55 time: 0.2620 data_time: 0.0074 memory: 5828 grad_norm: 5.3050 loss: 1.7810 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7810 2023/06/05 18:37:13 - mmengine - INFO - Epoch(train) [137][1100/2569] lr: 4.0000e-03 eta: 2:34:49 time: 0.2744 data_time: 0.0073 memory: 5828 grad_norm: 5.5049 loss: 2.0012 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0012 2023/06/05 18:37:18 - mmengine - INFO - Epoch(train) [137][1120/2569] lr: 4.0000e-03 eta: 2:34:44 time: 0.2613 data_time: 0.0073 memory: 5828 grad_norm: 5.2896 loss: 1.7664 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7664 2023/06/05 18:37:24 - mmengine - INFO - Epoch(train) [137][1140/2569] lr: 4.0000e-03 eta: 2:34:39 time: 0.2900 data_time: 0.0073 memory: 5828 grad_norm: 5.3558 loss: 1.6062 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6062 2023/06/05 18:37:29 - mmengine - INFO - Epoch(train) [137][1160/2569] lr: 4.0000e-03 eta: 2:34:33 time: 0.2652 data_time: 0.0073 memory: 5828 grad_norm: 5.4166 loss: 1.6422 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6422 2023/06/05 18:37:35 - mmengine - INFO - Epoch(train) [137][1180/2569] lr: 4.0000e-03 eta: 2:34:28 time: 0.2880 data_time: 0.0073 memory: 5828 grad_norm: 5.3879 loss: 1.7762 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7762 2023/06/05 18:37:40 - mmengine - INFO - Epoch(train) [137][1200/2569] lr: 4.0000e-03 eta: 2:34:23 time: 0.2630 data_time: 0.0072 memory: 5828 grad_norm: 5.4895 loss: 1.7560 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7560 2023/06/05 18:37:46 - mmengine - INFO - Epoch(train) [137][1220/2569] lr: 4.0000e-03 eta: 2:34:18 time: 0.2778 data_time: 0.0074 memory: 5828 grad_norm: 5.4645 loss: 1.8451 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8451 2023/06/05 18:37:51 - mmengine - INFO - Epoch(train) [137][1240/2569] lr: 4.0000e-03 eta: 2:34:12 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 5.4751 loss: 1.8233 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8233 2023/06/05 18:37:57 - mmengine - INFO - Epoch(train) [137][1260/2569] lr: 4.0000e-03 eta: 2:34:07 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 5.5629 loss: 2.0297 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0297 2023/06/05 18:38:02 - mmengine - INFO - Epoch(train) [137][1280/2569] lr: 4.0000e-03 eta: 2:34:02 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 5.4165 loss: 1.3470 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3470 2023/06/05 18:38:07 - mmengine - INFO - Epoch(train) [137][1300/2569] lr: 4.0000e-03 eta: 2:33:56 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 5.4733 loss: 1.8534 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.8534 2023/06/05 18:38:13 - mmengine - INFO - Epoch(train) [137][1320/2569] lr: 4.0000e-03 eta: 2:33:51 time: 0.2760 data_time: 0.0077 memory: 5828 grad_norm: 5.3651 loss: 1.7970 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7970 2023/06/05 18:38:18 - mmengine - INFO - Epoch(train) [137][1340/2569] lr: 4.0000e-03 eta: 2:33:46 time: 0.2609 data_time: 0.0072 memory: 5828 grad_norm: 5.3853 loss: 1.6530 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6530 2023/06/05 18:38:23 - mmengine - INFO - Epoch(train) [137][1360/2569] lr: 4.0000e-03 eta: 2:33:40 time: 0.2619 data_time: 0.0071 memory: 5828 grad_norm: 5.4297 loss: 2.0337 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0337 2023/06/05 18:38:28 - mmengine - INFO - Epoch(train) [137][1380/2569] lr: 4.0000e-03 eta: 2:33:35 time: 0.2667 data_time: 0.0070 memory: 5828 grad_norm: 5.4949 loss: 1.7163 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7163 2023/06/05 18:38:34 - mmengine - INFO - Epoch(train) [137][1400/2569] lr: 4.0000e-03 eta: 2:33:30 time: 0.2763 data_time: 0.0074 memory: 5828 grad_norm: 5.3074 loss: 1.7284 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7284 2023/06/05 18:38:39 - mmengine - INFO - Epoch(train) [137][1420/2569] lr: 4.0000e-03 eta: 2:33:24 time: 0.2733 data_time: 0.0074 memory: 5828 grad_norm: 5.4909 loss: 1.9293 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9293 2023/06/05 18:38:45 - mmengine - INFO - Epoch(train) [137][1440/2569] lr: 4.0000e-03 eta: 2:33:19 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 5.4273 loss: 1.6288 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6288 2023/06/05 18:38:50 - mmengine - INFO - Epoch(train) [137][1460/2569] lr: 4.0000e-03 eta: 2:33:14 time: 0.2785 data_time: 0.0072 memory: 5828 grad_norm: 5.4152 loss: 1.9508 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9508 2023/06/05 18:38:56 - mmengine - INFO - Epoch(train) [137][1480/2569] lr: 4.0000e-03 eta: 2:33:08 time: 0.2629 data_time: 0.0074 memory: 5828 grad_norm: 5.3589 loss: 2.0586 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0586 2023/06/05 18:39:01 - mmengine - INFO - Epoch(train) [137][1500/2569] lr: 4.0000e-03 eta: 2:33:03 time: 0.2634 data_time: 0.0070 memory: 5828 grad_norm: 5.2935 loss: 1.9565 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9565 2023/06/05 18:39:06 - mmengine - INFO - Epoch(train) [137][1520/2569] lr: 4.0000e-03 eta: 2:32:58 time: 0.2778 data_time: 0.0072 memory: 5828 grad_norm: 5.3458 loss: 2.0185 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0185 2023/06/05 18:39:12 - mmengine - INFO - Epoch(train) [137][1540/2569] lr: 4.0000e-03 eta: 2:32:52 time: 0.2673 data_time: 0.0072 memory: 5828 grad_norm: 5.3452 loss: 1.6340 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6340 2023/06/05 18:39:17 - mmengine - INFO - Epoch(train) [137][1560/2569] lr: 4.0000e-03 eta: 2:32:47 time: 0.2663 data_time: 0.0073 memory: 5828 grad_norm: 5.3855 loss: 1.8231 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8231 2023/06/05 18:39:23 - mmengine - INFO - Epoch(train) [137][1580/2569] lr: 4.0000e-03 eta: 2:32:42 time: 0.2682 data_time: 0.0074 memory: 5828 grad_norm: 5.3827 loss: 1.9679 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9679 2023/06/05 18:39:28 - mmengine - INFO - Epoch(train) [137][1600/2569] lr: 4.0000e-03 eta: 2:32:36 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 5.4245 loss: 1.9958 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9958 2023/06/05 18:39:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:39:33 - mmengine - INFO - Epoch(train) [137][1620/2569] lr: 4.0000e-03 eta: 2:32:31 time: 0.2733 data_time: 0.0073 memory: 5828 grad_norm: 5.4148 loss: 1.5805 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5805 2023/06/05 18:39:39 - mmengine - INFO - Epoch(train) [137][1640/2569] lr: 4.0000e-03 eta: 2:32:26 time: 0.2650 data_time: 0.0074 memory: 5828 grad_norm: 5.4834 loss: 1.7077 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7077 2023/06/05 18:39:44 - mmengine - INFO - Epoch(train) [137][1660/2569] lr: 4.0000e-03 eta: 2:32:20 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 5.5166 loss: 1.8698 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8698 2023/06/05 18:39:49 - mmengine - INFO - Epoch(train) [137][1680/2569] lr: 4.0000e-03 eta: 2:32:15 time: 0.2628 data_time: 0.0074 memory: 5828 grad_norm: 5.4839 loss: 1.7398 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7398 2023/06/05 18:39:55 - mmengine - INFO - Epoch(train) [137][1700/2569] lr: 4.0000e-03 eta: 2:32:10 time: 0.2773 data_time: 0.0073 memory: 5828 grad_norm: 5.4727 loss: 2.1675 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 2.1675 2023/06/05 18:40:00 - mmengine - INFO - Epoch(train) [137][1720/2569] lr: 4.0000e-03 eta: 2:32:04 time: 0.2662 data_time: 0.0078 memory: 5828 grad_norm: 5.4342 loss: 1.6848 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6848 2023/06/05 18:40:06 - mmengine - INFO - Epoch(train) [137][1740/2569] lr: 4.0000e-03 eta: 2:31:59 time: 0.2741 data_time: 0.0074 memory: 5828 grad_norm: 5.4885 loss: 1.9555 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9555 2023/06/05 18:40:11 - mmengine - INFO - Epoch(train) [137][1760/2569] lr: 4.0000e-03 eta: 2:31:54 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 5.4391 loss: 1.4405 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4405 2023/06/05 18:40:16 - mmengine - INFO - Epoch(train) [137][1780/2569] lr: 4.0000e-03 eta: 2:31:48 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 5.3525 loss: 1.7629 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7629 2023/06/05 18:40:22 - mmengine - INFO - Epoch(train) [137][1800/2569] lr: 4.0000e-03 eta: 2:31:43 time: 0.2674 data_time: 0.0079 memory: 5828 grad_norm: 5.4332 loss: 1.6549 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6549 2023/06/05 18:40:27 - mmengine - INFO - Epoch(train) [137][1820/2569] lr: 4.0000e-03 eta: 2:31:38 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 5.3570 loss: 1.6965 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6965 2023/06/05 18:40:33 - mmengine - INFO - Epoch(train) [137][1840/2569] lr: 4.0000e-03 eta: 2:31:32 time: 0.2796 data_time: 0.0074 memory: 5828 grad_norm: 5.4153 loss: 1.5200 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5200 2023/06/05 18:40:38 - mmengine - INFO - Epoch(train) [137][1860/2569] lr: 4.0000e-03 eta: 2:31:27 time: 0.2761 data_time: 0.0074 memory: 5828 grad_norm: 5.4718 loss: 1.7283 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7283 2023/06/05 18:40:44 - mmengine - INFO - Epoch(train) [137][1880/2569] lr: 4.0000e-03 eta: 2:31:22 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 5.3543 loss: 1.8930 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8930 2023/06/05 18:40:49 - mmengine - INFO - Epoch(train) [137][1900/2569] lr: 4.0000e-03 eta: 2:31:16 time: 0.2665 data_time: 0.0074 memory: 5828 grad_norm: 5.5495 loss: 1.6911 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.6911 2023/06/05 18:40:54 - mmengine - INFO - Epoch(train) [137][1920/2569] lr: 4.0000e-03 eta: 2:31:11 time: 0.2646 data_time: 0.0075 memory: 5828 grad_norm: 5.2640 loss: 1.9640 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9640 2023/06/05 18:41:00 - mmengine - INFO - Epoch(train) [137][1940/2569] lr: 4.0000e-03 eta: 2:31:06 time: 0.2735 data_time: 0.0074 memory: 5828 grad_norm: 5.5140 loss: 1.5158 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5158 2023/06/05 18:41:05 - mmengine - INFO - Epoch(train) [137][1960/2569] lr: 4.0000e-03 eta: 2:31:01 time: 0.2718 data_time: 0.0076 memory: 5828 grad_norm: 5.4367 loss: 1.6610 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.6610 2023/06/05 18:41:11 - mmengine - INFO - Epoch(train) [137][1980/2569] lr: 4.0000e-03 eta: 2:30:55 time: 0.2675 data_time: 0.0075 memory: 5828 grad_norm: 5.4658 loss: 1.6122 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.6122 2023/06/05 18:41:16 - mmengine - INFO - Epoch(train) [137][2000/2569] lr: 4.0000e-03 eta: 2:30:50 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 5.4108 loss: 1.7737 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7737 2023/06/05 18:41:21 - mmengine - INFO - Epoch(train) [137][2020/2569] lr: 4.0000e-03 eta: 2:30:45 time: 0.2618 data_time: 0.0077 memory: 5828 grad_norm: 5.3692 loss: 2.1090 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 2.1090 2023/06/05 18:41:26 - mmengine - INFO - Epoch(train) [137][2040/2569] lr: 4.0000e-03 eta: 2:30:39 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 5.3863 loss: 1.9008 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9008 2023/06/05 18:41:32 - mmengine - INFO - Epoch(train) [137][2060/2569] lr: 4.0000e-03 eta: 2:30:34 time: 0.2681 data_time: 0.0077 memory: 5828 grad_norm: 5.4686 loss: 2.0908 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0908 2023/06/05 18:41:37 - mmengine - INFO - Epoch(train) [137][2080/2569] lr: 4.0000e-03 eta: 2:30:29 time: 0.2718 data_time: 0.0074 memory: 5828 grad_norm: 5.4630 loss: 1.6664 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6664 2023/06/05 18:41:42 - mmengine - INFO - Epoch(train) [137][2100/2569] lr: 4.0000e-03 eta: 2:30:23 time: 0.2614 data_time: 0.0076 memory: 5828 grad_norm: 5.4541 loss: 1.9364 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9364 2023/06/05 18:41:48 - mmengine - INFO - Epoch(train) [137][2120/2569] lr: 4.0000e-03 eta: 2:30:18 time: 0.2651 data_time: 0.0073 memory: 5828 grad_norm: 5.5001 loss: 1.9590 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9590 2023/06/05 18:41:53 - mmengine - INFO - Epoch(train) [137][2140/2569] lr: 4.0000e-03 eta: 2:30:13 time: 0.2650 data_time: 0.0071 memory: 5828 grad_norm: 5.3729 loss: 1.9523 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9523 2023/06/05 18:41:58 - mmengine - INFO - Epoch(train) [137][2160/2569] lr: 4.0000e-03 eta: 2:30:07 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 5.4547 loss: 1.8471 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8471 2023/06/05 18:42:04 - mmengine - INFO - Epoch(train) [137][2180/2569] lr: 4.0000e-03 eta: 2:30:02 time: 0.2692 data_time: 0.0072 memory: 5828 grad_norm: 5.4382 loss: 1.8687 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8687 2023/06/05 18:42:09 - mmengine - INFO - Epoch(train) [137][2200/2569] lr: 4.0000e-03 eta: 2:29:57 time: 0.2719 data_time: 0.0072 memory: 5828 grad_norm: 5.4055 loss: 1.6722 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6722 2023/06/05 18:42:15 - mmengine - INFO - Epoch(train) [137][2220/2569] lr: 4.0000e-03 eta: 2:29:51 time: 0.2722 data_time: 0.0073 memory: 5828 grad_norm: 5.3920 loss: 1.7610 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7610 2023/06/05 18:42:20 - mmengine - INFO - Epoch(train) [137][2240/2569] lr: 4.0000e-03 eta: 2:29:46 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 5.6095 loss: 1.8505 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8505 2023/06/05 18:42:25 - mmengine - INFO - Epoch(train) [137][2260/2569] lr: 4.0000e-03 eta: 2:29:41 time: 0.2708 data_time: 0.0076 memory: 5828 grad_norm: 5.5820 loss: 1.6232 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6232 2023/06/05 18:42:31 - mmengine - INFO - Epoch(train) [137][2280/2569] lr: 4.0000e-03 eta: 2:29:35 time: 0.2630 data_time: 0.0073 memory: 5828 grad_norm: 5.4573 loss: 1.7414 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7414 2023/06/05 18:42:36 - mmengine - INFO - Epoch(train) [137][2300/2569] lr: 4.0000e-03 eta: 2:29:30 time: 0.2692 data_time: 0.0075 memory: 5828 grad_norm: 5.4480 loss: 1.7116 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7116 2023/06/05 18:42:41 - mmengine - INFO - Epoch(train) [137][2320/2569] lr: 4.0000e-03 eta: 2:29:25 time: 0.2620 data_time: 0.0073 memory: 5828 grad_norm: 5.3489 loss: 1.7044 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7044 2023/06/05 18:42:47 - mmengine - INFO - Epoch(train) [137][2340/2569] lr: 4.0000e-03 eta: 2:29:19 time: 0.2730 data_time: 0.0076 memory: 5828 grad_norm: 5.4422 loss: 1.6269 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6269 2023/06/05 18:42:52 - mmengine - INFO - Epoch(train) [137][2360/2569] lr: 4.0000e-03 eta: 2:29:14 time: 0.2615 data_time: 0.0070 memory: 5828 grad_norm: 5.5077 loss: 1.7047 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7047 2023/06/05 18:42:57 - mmengine - INFO - Epoch(train) [137][2380/2569] lr: 4.0000e-03 eta: 2:29:09 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 5.5433 loss: 1.9752 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9752 2023/06/05 18:43:03 - mmengine - INFO - Epoch(train) [137][2400/2569] lr: 4.0000e-03 eta: 2:29:03 time: 0.2671 data_time: 0.0071 memory: 5828 grad_norm: 5.4268 loss: 1.6061 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6061 2023/06/05 18:43:08 - mmengine - INFO - Epoch(train) [137][2420/2569] lr: 4.0000e-03 eta: 2:28:58 time: 0.2683 data_time: 0.0074 memory: 5828 grad_norm: 5.3697 loss: 2.0795 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 2.0795 2023/06/05 18:43:14 - mmengine - INFO - Epoch(train) [137][2440/2569] lr: 4.0000e-03 eta: 2:28:53 time: 0.2697 data_time: 0.0071 memory: 5828 grad_norm: 5.4152 loss: 1.6049 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6049 2023/06/05 18:43:19 - mmengine - INFO - Epoch(train) [137][2460/2569] lr: 4.0000e-03 eta: 2:28:47 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 5.3535 loss: 1.8964 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8964 2023/06/05 18:43:24 - mmengine - INFO - Epoch(train) [137][2480/2569] lr: 4.0000e-03 eta: 2:28:42 time: 0.2636 data_time: 0.0074 memory: 5828 grad_norm: 5.3644 loss: 1.6536 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6536 2023/06/05 18:43:29 - mmengine - INFO - Epoch(train) [137][2500/2569] lr: 4.0000e-03 eta: 2:28:37 time: 0.2666 data_time: 0.0074 memory: 5828 grad_norm: 5.4466 loss: 1.6787 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6787 2023/06/05 18:43:35 - mmengine - INFO - Epoch(train) [137][2520/2569] lr: 4.0000e-03 eta: 2:28:31 time: 0.2620 data_time: 0.0074 memory: 5828 grad_norm: 5.3699 loss: 1.5838 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.5838 2023/06/05 18:43:40 - mmengine - INFO - Epoch(train) [137][2540/2569] lr: 4.0000e-03 eta: 2:28:26 time: 0.2741 data_time: 0.0072 memory: 5828 grad_norm: 5.4557 loss: 1.8742 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8742 2023/06/05 18:43:45 - mmengine - INFO - Epoch(train) [137][2560/2569] lr: 4.0000e-03 eta: 2:28:21 time: 0.2619 data_time: 0.0071 memory: 5828 grad_norm: 5.4493 loss: 1.9071 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9071 2023/06/05 18:43:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:43:48 - mmengine - INFO - Epoch(train) [137][2569/2569] lr: 4.0000e-03 eta: 2:28:18 time: 0.2530 data_time: 0.0073 memory: 5828 grad_norm: 5.5081 loss: 1.9588 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.9588 2023/06/05 18:43:54 - mmengine - INFO - Epoch(train) [138][ 20/2569] lr: 4.0000e-03 eta: 2:28:13 time: 0.3360 data_time: 0.0638 memory: 5828 grad_norm: 5.4475 loss: 1.6493 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6493 2023/06/05 18:44:00 - mmengine - INFO - Epoch(train) [138][ 40/2569] lr: 4.0000e-03 eta: 2:28:08 time: 0.2734 data_time: 0.0081 memory: 5828 grad_norm: 5.3262 loss: 1.5519 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5519 2023/06/05 18:44:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:44:05 - mmengine - INFO - Epoch(train) [138][ 60/2569] lr: 4.0000e-03 eta: 2:28:02 time: 0.2716 data_time: 0.0072 memory: 5828 grad_norm: 5.4177 loss: 1.7251 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7251 2023/06/05 18:44:11 - mmengine - INFO - Epoch(train) [138][ 80/2569] lr: 4.0000e-03 eta: 2:27:57 time: 0.2751 data_time: 0.0077 memory: 5828 grad_norm: 5.4168 loss: 1.8110 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8110 2023/06/05 18:44:16 - mmengine - INFO - Epoch(train) [138][ 100/2569] lr: 4.0000e-03 eta: 2:27:52 time: 0.2648 data_time: 0.0073 memory: 5828 grad_norm: 5.4148 loss: 1.4470 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4470 2023/06/05 18:44:22 - mmengine - INFO - Epoch(train) [138][ 120/2569] lr: 4.0000e-03 eta: 2:27:46 time: 0.2821 data_time: 0.0076 memory: 5828 grad_norm: 5.4810 loss: 1.7475 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7475 2023/06/05 18:44:27 - mmengine - INFO - Epoch(train) [138][ 140/2569] lr: 4.0000e-03 eta: 2:27:41 time: 0.2678 data_time: 0.0073 memory: 5828 grad_norm: 5.4789 loss: 1.5768 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5768 2023/06/05 18:44:33 - mmengine - INFO - Epoch(train) [138][ 160/2569] lr: 4.0000e-03 eta: 2:27:36 time: 0.2776 data_time: 0.0078 memory: 5828 grad_norm: 5.4011 loss: 1.6592 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6592 2023/06/05 18:44:38 - mmengine - INFO - Epoch(train) [138][ 180/2569] lr: 4.0000e-03 eta: 2:27:31 time: 0.2739 data_time: 0.0075 memory: 5828 grad_norm: 5.2767 loss: 1.9164 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 1.9164 2023/06/05 18:44:44 - mmengine - INFO - Epoch(train) [138][ 200/2569] lr: 4.0000e-03 eta: 2:27:25 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 5.4354 loss: 1.9798 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9798 2023/06/05 18:44:49 - mmengine - INFO - Epoch(train) [138][ 220/2569] lr: 4.0000e-03 eta: 2:27:20 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 5.4418 loss: 1.7341 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7341 2023/06/05 18:44:54 - mmengine - INFO - Epoch(train) [138][ 240/2569] lr: 4.0000e-03 eta: 2:27:15 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 5.5013 loss: 1.6631 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6631 2023/06/05 18:45:00 - mmengine - INFO - Epoch(train) [138][ 260/2569] lr: 4.0000e-03 eta: 2:27:09 time: 0.2690 data_time: 0.0073 memory: 5828 grad_norm: 5.5008 loss: 1.6688 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6688 2023/06/05 18:45:05 - mmengine - INFO - Epoch(train) [138][ 280/2569] lr: 4.0000e-03 eta: 2:27:04 time: 0.2676 data_time: 0.0073 memory: 5828 grad_norm: 5.3840 loss: 1.8788 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8788 2023/06/05 18:45:10 - mmengine - INFO - Epoch(train) [138][ 300/2569] lr: 4.0000e-03 eta: 2:26:59 time: 0.2682 data_time: 0.0076 memory: 5828 grad_norm: 5.5554 loss: 1.6884 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6884 2023/06/05 18:45:16 - mmengine - INFO - Epoch(train) [138][ 320/2569] lr: 4.0000e-03 eta: 2:26:53 time: 0.2666 data_time: 0.0076 memory: 5828 grad_norm: 5.5002 loss: 1.7120 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7120 2023/06/05 18:45:21 - mmengine - INFO - Epoch(train) [138][ 340/2569] lr: 4.0000e-03 eta: 2:26:48 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 5.4469 loss: 1.8219 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8219 2023/06/05 18:45:26 - mmengine - INFO - Epoch(train) [138][ 360/2569] lr: 4.0000e-03 eta: 2:26:43 time: 0.2673 data_time: 0.0074 memory: 5828 grad_norm: 5.2977 loss: 1.9359 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9359 2023/06/05 18:45:32 - mmengine - INFO - Epoch(train) [138][ 380/2569] lr: 4.0000e-03 eta: 2:26:37 time: 0.2717 data_time: 0.0071 memory: 5828 grad_norm: 5.5494 loss: 1.5657 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5657 2023/06/05 18:45:37 - mmengine - INFO - Epoch(train) [138][ 400/2569] lr: 4.0000e-03 eta: 2:26:32 time: 0.2627 data_time: 0.0075 memory: 5828 grad_norm: 5.5035 loss: 1.8424 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8424 2023/06/05 18:45:43 - mmengine - INFO - Epoch(train) [138][ 420/2569] lr: 4.0000e-03 eta: 2:26:27 time: 0.2878 data_time: 0.0075 memory: 5828 grad_norm: 5.4738 loss: 1.7259 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7259 2023/06/05 18:45:48 - mmengine - INFO - Epoch(train) [138][ 440/2569] lr: 4.0000e-03 eta: 2:26:21 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 5.3622 loss: 1.8812 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8812 2023/06/05 18:45:54 - mmengine - INFO - Epoch(train) [138][ 460/2569] lr: 4.0000e-03 eta: 2:26:16 time: 0.2701 data_time: 0.0073 memory: 5828 grad_norm: 5.4409 loss: 1.8028 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8028 2023/06/05 18:45:59 - mmengine - INFO - Epoch(train) [138][ 480/2569] lr: 4.0000e-03 eta: 2:26:11 time: 0.2649 data_time: 0.0072 memory: 5828 grad_norm: 5.5653 loss: 1.9095 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9095 2023/06/05 18:46:04 - mmengine - INFO - Epoch(train) [138][ 500/2569] lr: 4.0000e-03 eta: 2:26:05 time: 0.2761 data_time: 0.0071 memory: 5828 grad_norm: 5.5428 loss: 1.6739 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6739 2023/06/05 18:46:10 - mmengine - INFO - Epoch(train) [138][ 520/2569] lr: 4.0000e-03 eta: 2:26:00 time: 0.2734 data_time: 0.0072 memory: 5828 grad_norm: 5.3179 loss: 1.7767 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7767 2023/06/05 18:46:15 - mmengine - INFO - Epoch(train) [138][ 540/2569] lr: 4.0000e-03 eta: 2:25:55 time: 0.2675 data_time: 0.0083 memory: 5828 grad_norm: 5.4665 loss: 2.2102 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.2102 2023/06/05 18:46:21 - mmengine - INFO - Epoch(train) [138][ 560/2569] lr: 4.0000e-03 eta: 2:25:49 time: 0.2713 data_time: 0.0072 memory: 5828 grad_norm: 5.4019 loss: 1.6555 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6555 2023/06/05 18:46:26 - mmengine - INFO - Epoch(train) [138][ 580/2569] lr: 4.0000e-03 eta: 2:25:44 time: 0.2812 data_time: 0.0074 memory: 5828 grad_norm: 5.4151 loss: 1.7058 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7058 2023/06/05 18:46:32 - mmengine - INFO - Epoch(train) [138][ 600/2569] lr: 4.0000e-03 eta: 2:25:39 time: 0.2723 data_time: 0.0074 memory: 5828 grad_norm: 5.4467 loss: 1.7599 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7599 2023/06/05 18:46:37 - mmengine - INFO - Epoch(train) [138][ 620/2569] lr: 4.0000e-03 eta: 2:25:33 time: 0.2657 data_time: 0.0074 memory: 5828 grad_norm: 5.5678 loss: 1.4159 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4159 2023/06/05 18:46:43 - mmengine - INFO - Epoch(train) [138][ 640/2569] lr: 4.0000e-03 eta: 2:25:28 time: 0.2706 data_time: 0.0073 memory: 5828 grad_norm: 5.4045 loss: 1.8080 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8080 2023/06/05 18:46:48 - mmengine - INFO - Epoch(train) [138][ 660/2569] lr: 4.0000e-03 eta: 2:25:23 time: 0.2806 data_time: 0.0071 memory: 5828 grad_norm: 5.5337 loss: 2.0119 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0119 2023/06/05 18:46:54 - mmengine - INFO - Epoch(train) [138][ 680/2569] lr: 4.0000e-03 eta: 2:25:17 time: 0.2724 data_time: 0.0072 memory: 5828 grad_norm: 5.4349 loss: 1.7348 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7348 2023/06/05 18:46:59 - mmengine - INFO - Epoch(train) [138][ 700/2569] lr: 4.0000e-03 eta: 2:25:12 time: 0.2788 data_time: 0.0074 memory: 5828 grad_norm: 5.5583 loss: 1.6916 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6916 2023/06/05 18:47:05 - mmengine - INFO - Epoch(train) [138][ 720/2569] lr: 4.0000e-03 eta: 2:25:07 time: 0.2697 data_time: 0.0077 memory: 5828 grad_norm: 5.4322 loss: 1.6689 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6689 2023/06/05 18:47:10 - mmengine - INFO - Epoch(train) [138][ 740/2569] lr: 4.0000e-03 eta: 2:25:01 time: 0.2661 data_time: 0.0072 memory: 5828 grad_norm: 5.4683 loss: 1.9282 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9282 2023/06/05 18:47:15 - mmengine - INFO - Epoch(train) [138][ 760/2569] lr: 4.0000e-03 eta: 2:24:56 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 5.4172 loss: 1.7430 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7430 2023/06/05 18:47:21 - mmengine - INFO - Epoch(train) [138][ 780/2569] lr: 4.0000e-03 eta: 2:24:51 time: 0.2702 data_time: 0.0079 memory: 5828 grad_norm: 5.4770 loss: 1.8026 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8026 2023/06/05 18:47:26 - mmengine - INFO - Epoch(train) [138][ 800/2569] lr: 4.0000e-03 eta: 2:24:46 time: 0.2682 data_time: 0.0080 memory: 5828 grad_norm: 5.4810 loss: 1.7914 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7914 2023/06/05 18:47:31 - mmengine - INFO - Epoch(train) [138][ 820/2569] lr: 4.0000e-03 eta: 2:24:40 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 5.5496 loss: 1.9427 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9427 2023/06/05 18:47:37 - mmengine - INFO - Epoch(train) [138][ 840/2569] lr: 4.0000e-03 eta: 2:24:35 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 5.4827 loss: 1.4173 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4173 2023/06/05 18:47:42 - mmengine - INFO - Epoch(train) [138][ 860/2569] lr: 4.0000e-03 eta: 2:24:30 time: 0.2679 data_time: 0.0075 memory: 5828 grad_norm: 5.3427 loss: 1.7862 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7862 2023/06/05 18:47:48 - mmengine - INFO - Epoch(train) [138][ 880/2569] lr: 4.0000e-03 eta: 2:24:24 time: 0.2705 data_time: 0.0074 memory: 5828 grad_norm: 5.4649 loss: 1.7767 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7767 2023/06/05 18:47:53 - mmengine - INFO - Epoch(train) [138][ 900/2569] lr: 4.0000e-03 eta: 2:24:19 time: 0.2805 data_time: 0.0073 memory: 5828 grad_norm: 5.4322 loss: 1.8071 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8071 2023/06/05 18:47:58 - mmengine - INFO - Epoch(train) [138][ 920/2569] lr: 4.0000e-03 eta: 2:24:14 time: 0.2661 data_time: 0.0073 memory: 5828 grad_norm: 5.5072 loss: 1.6548 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6548 2023/06/05 18:48:04 - mmengine - INFO - Epoch(train) [138][ 940/2569] lr: 4.0000e-03 eta: 2:24:08 time: 0.2679 data_time: 0.0075 memory: 5828 grad_norm: 5.3380 loss: 1.5354 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5354 2023/06/05 18:48:09 - mmengine - INFO - Epoch(train) [138][ 960/2569] lr: 4.0000e-03 eta: 2:24:03 time: 0.2679 data_time: 0.0076 memory: 5828 grad_norm: 5.4671 loss: 1.7502 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7502 2023/06/05 18:48:15 - mmengine - INFO - Epoch(train) [138][ 980/2569] lr: 4.0000e-03 eta: 2:23:58 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 5.4762 loss: 1.5410 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5410 2023/06/05 18:48:20 - mmengine - INFO - Epoch(train) [138][1000/2569] lr: 4.0000e-03 eta: 2:23:52 time: 0.2828 data_time: 0.0076 memory: 5828 grad_norm: 5.4956 loss: 1.6884 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6884 2023/06/05 18:48:26 - mmengine - INFO - Epoch(train) [138][1020/2569] lr: 4.0000e-03 eta: 2:23:47 time: 0.2697 data_time: 0.0072 memory: 5828 grad_norm: 5.4217 loss: 1.9065 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9065 2023/06/05 18:48:31 - mmengine - INFO - Epoch(train) [138][1040/2569] lr: 4.0000e-03 eta: 2:23:42 time: 0.2733 data_time: 0.0077 memory: 5828 grad_norm: 5.4159 loss: 1.6643 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6643 2023/06/05 18:48:33 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:48:37 - mmengine - INFO - Epoch(train) [138][1060/2569] lr: 4.0000e-03 eta: 2:23:36 time: 0.2683 data_time: 0.0076 memory: 5828 grad_norm: 5.4536 loss: 1.4452 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4452 2023/06/05 18:48:42 - mmengine - INFO - Epoch(train) [138][1080/2569] lr: 4.0000e-03 eta: 2:23:31 time: 0.2642 data_time: 0.0072 memory: 5828 grad_norm: 5.5089 loss: 1.9954 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9954 2023/06/05 18:48:47 - mmengine - INFO - Epoch(train) [138][1100/2569] lr: 4.0000e-03 eta: 2:23:26 time: 0.2704 data_time: 0.0066 memory: 5828 grad_norm: 5.5361 loss: 2.0056 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0056 2023/06/05 18:48:53 - mmengine - INFO - Epoch(train) [138][1120/2569] lr: 4.0000e-03 eta: 2:23:20 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 5.4408 loss: 1.7946 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7946 2023/06/05 18:48:58 - mmengine - INFO - Epoch(train) [138][1140/2569] lr: 4.0000e-03 eta: 2:23:15 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 5.2894 loss: 1.6558 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6558 2023/06/05 18:49:03 - mmengine - INFO - Epoch(train) [138][1160/2569] lr: 4.0000e-03 eta: 2:23:10 time: 0.2692 data_time: 0.0075 memory: 5828 grad_norm: 5.4727 loss: 1.8394 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8394 2023/06/05 18:49:09 - mmengine - INFO - Epoch(train) [138][1180/2569] lr: 4.0000e-03 eta: 2:23:04 time: 0.2678 data_time: 0.0073 memory: 5828 grad_norm: 5.4495 loss: 1.5950 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5950 2023/06/05 18:49:14 - mmengine - INFO - Epoch(train) [138][1200/2569] lr: 4.0000e-03 eta: 2:22:59 time: 0.2781 data_time: 0.0076 memory: 5828 grad_norm: 5.4955 loss: 1.8902 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8902 2023/06/05 18:49:20 - mmengine - INFO - Epoch(train) [138][1220/2569] lr: 4.0000e-03 eta: 2:22:54 time: 0.2696 data_time: 0.0076 memory: 5828 grad_norm: 5.4283 loss: 2.0254 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0254 2023/06/05 18:49:25 - mmengine - INFO - Epoch(train) [138][1240/2569] lr: 4.0000e-03 eta: 2:22:48 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 5.3145 loss: 1.7845 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7845 2023/06/05 18:49:30 - mmengine - INFO - Epoch(train) [138][1260/2569] lr: 4.0000e-03 eta: 2:22:43 time: 0.2665 data_time: 0.0071 memory: 5828 grad_norm: 5.3926 loss: 1.5727 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.5727 2023/06/05 18:49:36 - mmengine - INFO - Epoch(train) [138][1280/2569] lr: 4.0000e-03 eta: 2:22:38 time: 0.2720 data_time: 0.0077 memory: 5828 grad_norm: 5.4390 loss: 1.6372 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6372 2023/06/05 18:49:41 - mmengine - INFO - Epoch(train) [138][1300/2569] lr: 4.0000e-03 eta: 2:22:32 time: 0.2747 data_time: 0.0071 memory: 5828 grad_norm: 5.4976 loss: 1.6231 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6231 2023/06/05 18:49:47 - mmengine - INFO - Epoch(train) [138][1320/2569] lr: 4.0000e-03 eta: 2:22:27 time: 0.2633 data_time: 0.0073 memory: 5828 grad_norm: 5.3630 loss: 1.7424 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7424 2023/06/05 18:49:52 - mmengine - INFO - Epoch(train) [138][1340/2569] lr: 4.0000e-03 eta: 2:22:22 time: 0.2734 data_time: 0.0073 memory: 5828 grad_norm: 5.3827 loss: 1.8878 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8878 2023/06/05 18:49:57 - mmengine - INFO - Epoch(train) [138][1360/2569] lr: 4.0000e-03 eta: 2:22:16 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 5.2442 loss: 1.4473 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4473 2023/06/05 18:50:03 - mmengine - INFO - Epoch(train) [138][1380/2569] lr: 4.0000e-03 eta: 2:22:11 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 5.4697 loss: 1.7302 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7302 2023/06/05 18:50:08 - mmengine - INFO - Epoch(train) [138][1400/2569] lr: 4.0000e-03 eta: 2:22:06 time: 0.2630 data_time: 0.0074 memory: 5828 grad_norm: 5.4492 loss: 1.8922 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8922 2023/06/05 18:50:13 - mmengine - INFO - Epoch(train) [138][1420/2569] lr: 4.0000e-03 eta: 2:22:00 time: 0.2651 data_time: 0.0075 memory: 5828 grad_norm: 5.5487 loss: 1.7016 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7016 2023/06/05 18:50:19 - mmengine - INFO - Epoch(train) [138][1440/2569] lr: 4.0000e-03 eta: 2:21:55 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 5.4058 loss: 1.7331 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7331 2023/06/05 18:50:24 - mmengine - INFO - Epoch(train) [138][1460/2569] lr: 4.0000e-03 eta: 2:21:50 time: 0.2665 data_time: 0.0078 memory: 5828 grad_norm: 5.4948 loss: 1.7030 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7030 2023/06/05 18:50:29 - mmengine - INFO - Epoch(train) [138][1480/2569] lr: 4.0000e-03 eta: 2:21:44 time: 0.2669 data_time: 0.0071 memory: 5828 grad_norm: 5.5953 loss: 1.6344 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6344 2023/06/05 18:50:34 - mmengine - INFO - Epoch(train) [138][1500/2569] lr: 4.0000e-03 eta: 2:21:39 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 5.4296 loss: 1.7042 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7042 2023/06/05 18:50:40 - mmengine - INFO - Epoch(train) [138][1520/2569] lr: 4.0000e-03 eta: 2:21:34 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 5.4180 loss: 1.7544 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7544 2023/06/05 18:50:45 - mmengine - INFO - Epoch(train) [138][1540/2569] lr: 4.0000e-03 eta: 2:21:28 time: 0.2717 data_time: 0.0073 memory: 5828 grad_norm: 5.3823 loss: 1.6262 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.6262 2023/06/05 18:50:51 - mmengine - INFO - Epoch(train) [138][1560/2569] lr: 4.0000e-03 eta: 2:21:23 time: 0.2718 data_time: 0.0070 memory: 5828 grad_norm: 5.5101 loss: 1.8642 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8642 2023/06/05 18:50:56 - mmengine - INFO - Epoch(train) [138][1580/2569] lr: 4.0000e-03 eta: 2:21:18 time: 0.2701 data_time: 0.0072 memory: 5828 grad_norm: 5.5336 loss: 1.8663 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8663 2023/06/05 18:51:01 - mmengine - INFO - Epoch(train) [138][1600/2569] lr: 4.0000e-03 eta: 2:21:12 time: 0.2636 data_time: 0.0076 memory: 5828 grad_norm: 5.5664 loss: 1.8860 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.8860 2023/06/05 18:51:07 - mmengine - INFO - Epoch(train) [138][1620/2569] lr: 4.0000e-03 eta: 2:21:07 time: 0.2693 data_time: 0.0076 memory: 5828 grad_norm: 5.5679 loss: 2.0665 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0665 2023/06/05 18:51:12 - mmengine - INFO - Epoch(train) [138][1640/2569] lr: 4.0000e-03 eta: 2:21:02 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 5.4957 loss: 1.5787 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5787 2023/06/05 18:51:17 - mmengine - INFO - Epoch(train) [138][1660/2569] lr: 4.0000e-03 eta: 2:20:57 time: 0.2745 data_time: 0.0075 memory: 5828 grad_norm: 5.5764 loss: 1.8714 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8714 2023/06/05 18:51:23 - mmengine - INFO - Epoch(train) [138][1680/2569] lr: 4.0000e-03 eta: 2:20:51 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 5.4720 loss: 1.4672 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4672 2023/06/05 18:51:28 - mmengine - INFO - Epoch(train) [138][1700/2569] lr: 4.0000e-03 eta: 2:20:46 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 5.3798 loss: 1.5774 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5774 2023/06/05 18:51:34 - mmengine - INFO - Epoch(train) [138][1720/2569] lr: 4.0000e-03 eta: 2:20:41 time: 0.2674 data_time: 0.0075 memory: 5828 grad_norm: 5.6046 loss: 1.6440 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6440 2023/06/05 18:51:39 - mmengine - INFO - Epoch(train) [138][1740/2569] lr: 4.0000e-03 eta: 2:20:35 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 5.5017 loss: 1.6656 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6656 2023/06/05 18:51:44 - mmengine - INFO - Epoch(train) [138][1760/2569] lr: 4.0000e-03 eta: 2:20:30 time: 0.2738 data_time: 0.0076 memory: 5828 grad_norm: 5.4450 loss: 1.9223 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.9223 2023/06/05 18:51:50 - mmengine - INFO - Epoch(train) [138][1780/2569] lr: 4.0000e-03 eta: 2:20:25 time: 0.2773 data_time: 0.0072 memory: 5828 grad_norm: 5.3912 loss: 1.7430 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7430 2023/06/05 18:51:55 - mmengine - INFO - Epoch(train) [138][1800/2569] lr: 4.0000e-03 eta: 2:20:19 time: 0.2785 data_time: 0.0075 memory: 5828 grad_norm: 5.2514 loss: 1.9444 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9444 2023/06/05 18:52:01 - mmengine - INFO - Epoch(train) [138][1820/2569] lr: 4.0000e-03 eta: 2:20:14 time: 0.2663 data_time: 0.0073 memory: 5828 grad_norm: 5.4972 loss: 1.7048 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7048 2023/06/05 18:52:06 - mmengine - INFO - Epoch(train) [138][1840/2569] lr: 4.0000e-03 eta: 2:20:09 time: 0.2641 data_time: 0.0073 memory: 5828 grad_norm: 5.4629 loss: 2.0994 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0994 2023/06/05 18:52:12 - mmengine - INFO - Epoch(train) [138][1860/2569] lr: 4.0000e-03 eta: 2:20:03 time: 0.2724 data_time: 0.0073 memory: 5828 grad_norm: 5.4304 loss: 1.6733 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6733 2023/06/05 18:52:17 - mmengine - INFO - Epoch(train) [138][1880/2569] lr: 4.0000e-03 eta: 2:19:58 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 5.5117 loss: 1.9964 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9964 2023/06/05 18:52:22 - mmengine - INFO - Epoch(train) [138][1900/2569] lr: 4.0000e-03 eta: 2:19:53 time: 0.2756 data_time: 0.0075 memory: 5828 grad_norm: 5.5266 loss: 1.9276 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9276 2023/06/05 18:52:28 - mmengine - INFO - Epoch(train) [138][1920/2569] lr: 4.0000e-03 eta: 2:19:47 time: 0.2673 data_time: 0.0074 memory: 5828 grad_norm: 5.5475 loss: 1.7428 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7428 2023/06/05 18:52:33 - mmengine - INFO - Epoch(train) [138][1940/2569] lr: 4.0000e-03 eta: 2:19:42 time: 0.2615 data_time: 0.0077 memory: 5828 grad_norm: 5.4456 loss: 1.7365 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7365 2023/06/05 18:52:38 - mmengine - INFO - Epoch(train) [138][1960/2569] lr: 4.0000e-03 eta: 2:19:37 time: 0.2749 data_time: 0.0069 memory: 5828 grad_norm: 5.4867 loss: 1.9714 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9714 2023/06/05 18:52:44 - mmengine - INFO - Epoch(train) [138][1980/2569] lr: 4.0000e-03 eta: 2:19:31 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 5.6324 loss: 1.7033 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.7033 2023/06/05 18:52:49 - mmengine - INFO - Epoch(train) [138][2000/2569] lr: 4.0000e-03 eta: 2:19:26 time: 0.2702 data_time: 0.0077 memory: 5828 grad_norm: 5.4842 loss: 1.9313 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9313 2023/06/05 18:52:54 - mmengine - INFO - Epoch(train) [138][2020/2569] lr: 4.0000e-03 eta: 2:19:21 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 5.5237 loss: 1.4793 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.4793 2023/06/05 18:53:00 - mmengine - INFO - Epoch(train) [138][2040/2569] lr: 4.0000e-03 eta: 2:19:15 time: 0.2680 data_time: 0.0074 memory: 5828 grad_norm: 5.5519 loss: 1.9247 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9247 2023/06/05 18:53:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:53:05 - mmengine - INFO - Epoch(train) [138][2060/2569] lr: 4.0000e-03 eta: 2:19:10 time: 0.2679 data_time: 0.0076 memory: 5828 grad_norm: 5.6116 loss: 1.8135 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8135 2023/06/05 18:53:11 - mmengine - INFO - Epoch(train) [138][2080/2569] lr: 4.0000e-03 eta: 2:19:05 time: 0.2761 data_time: 0.0081 memory: 5828 grad_norm: 5.4328 loss: 1.6712 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6712 2023/06/05 18:53:16 - mmengine - INFO - Epoch(train) [138][2100/2569] lr: 4.0000e-03 eta: 2:18:59 time: 0.2708 data_time: 0.0074 memory: 5828 grad_norm: 5.3858 loss: 1.7525 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7525 2023/06/05 18:53:22 - mmengine - INFO - Epoch(train) [138][2120/2569] lr: 4.0000e-03 eta: 2:18:54 time: 0.2775 data_time: 0.0072 memory: 5828 grad_norm: 5.3417 loss: 1.9331 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9331 2023/06/05 18:53:27 - mmengine - INFO - Epoch(train) [138][2140/2569] lr: 4.0000e-03 eta: 2:18:49 time: 0.2761 data_time: 0.0074 memory: 5828 grad_norm: 5.3873 loss: 1.8147 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8147 2023/06/05 18:53:33 - mmengine - INFO - Epoch(train) [138][2160/2569] lr: 4.0000e-03 eta: 2:18:43 time: 0.2718 data_time: 0.0076 memory: 5828 grad_norm: 5.5085 loss: 1.5802 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5802 2023/06/05 18:53:38 - mmengine - INFO - Epoch(train) [138][2180/2569] lr: 4.0000e-03 eta: 2:18:38 time: 0.2677 data_time: 0.0069 memory: 5828 grad_norm: 5.6257 loss: 1.7765 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7765 2023/06/05 18:53:43 - mmengine - INFO - Epoch(train) [138][2200/2569] lr: 4.0000e-03 eta: 2:18:33 time: 0.2676 data_time: 0.0076 memory: 5828 grad_norm: 5.4894 loss: 1.5930 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5930 2023/06/05 18:53:49 - mmengine - INFO - Epoch(train) [138][2220/2569] lr: 4.0000e-03 eta: 2:18:27 time: 0.2675 data_time: 0.0073 memory: 5828 grad_norm: 5.4991 loss: 2.0734 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.0734 2023/06/05 18:53:54 - mmengine - INFO - Epoch(train) [138][2240/2569] lr: 4.0000e-03 eta: 2:18:22 time: 0.2604 data_time: 0.0072 memory: 5828 grad_norm: 5.4358 loss: 1.7366 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7366 2023/06/05 18:53:59 - mmengine - INFO - Epoch(train) [138][2260/2569] lr: 4.0000e-03 eta: 2:18:17 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 5.3850 loss: 1.5757 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5757 2023/06/05 18:54:05 - mmengine - INFO - Epoch(train) [138][2280/2569] lr: 4.0000e-03 eta: 2:18:11 time: 0.2616 data_time: 0.0076 memory: 5828 grad_norm: 5.6054 loss: 2.1052 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.1052 2023/06/05 18:54:10 - mmengine - INFO - Epoch(train) [138][2300/2569] lr: 4.0000e-03 eta: 2:18:06 time: 0.2669 data_time: 0.0070 memory: 5828 grad_norm: 5.5005 loss: 1.7217 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7217 2023/06/05 18:54:15 - mmengine - INFO - Epoch(train) [138][2320/2569] lr: 4.0000e-03 eta: 2:18:01 time: 0.2742 data_time: 0.0072 memory: 5828 grad_norm: 5.4455 loss: 1.7383 top1_acc: 0.1250 top5_acc: 0.7500 loss_cls: 1.7383 2023/06/05 18:54:21 - mmengine - INFO - Epoch(train) [138][2340/2569] lr: 4.0000e-03 eta: 2:17:55 time: 0.2712 data_time: 0.0073 memory: 5828 grad_norm: 5.3824 loss: 1.9952 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9952 2023/06/05 18:54:26 - mmengine - INFO - Epoch(train) [138][2360/2569] lr: 4.0000e-03 eta: 2:17:50 time: 0.2631 data_time: 0.0075 memory: 5828 grad_norm: 5.4362 loss: 1.7452 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7452 2023/06/05 18:54:31 - mmengine - INFO - Epoch(train) [138][2380/2569] lr: 4.0000e-03 eta: 2:17:45 time: 0.2602 data_time: 0.0075 memory: 5828 grad_norm: 5.5298 loss: 1.9078 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9078 2023/06/05 18:54:37 - mmengine - INFO - Epoch(train) [138][2400/2569] lr: 4.0000e-03 eta: 2:17:39 time: 0.2708 data_time: 0.0073 memory: 5828 grad_norm: 5.3805 loss: 1.8324 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8324 2023/06/05 18:54:42 - mmengine - INFO - Epoch(train) [138][2420/2569] lr: 4.0000e-03 eta: 2:17:34 time: 0.2646 data_time: 0.0077 memory: 5828 grad_norm: 5.5978 loss: 1.7857 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7857 2023/06/05 18:54:48 - mmengine - INFO - Epoch(train) [138][2440/2569] lr: 4.0000e-03 eta: 2:17:29 time: 0.2708 data_time: 0.0074 memory: 5828 grad_norm: 5.3289 loss: 1.7458 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7458 2023/06/05 18:54:53 - mmengine - INFO - Epoch(train) [138][2460/2569] lr: 4.0000e-03 eta: 2:17:23 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 5.4468 loss: 1.5553 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5553 2023/06/05 18:54:58 - mmengine - INFO - Epoch(train) [138][2480/2569] lr: 4.0000e-03 eta: 2:17:18 time: 0.2708 data_time: 0.0073 memory: 5828 grad_norm: 5.5435 loss: 1.8451 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8451 2023/06/05 18:55:04 - mmengine - INFO - Epoch(train) [138][2500/2569] lr: 4.0000e-03 eta: 2:17:13 time: 0.2620 data_time: 0.0079 memory: 5828 grad_norm: 5.4483 loss: 1.5660 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5660 2023/06/05 18:55:09 - mmengine - INFO - Epoch(train) [138][2520/2569] lr: 4.0000e-03 eta: 2:17:07 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 5.4580 loss: 1.6586 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6586 2023/06/05 18:55:14 - mmengine - INFO - Epoch(train) [138][2540/2569] lr: 4.0000e-03 eta: 2:17:02 time: 0.2735 data_time: 0.0074 memory: 5828 grad_norm: 5.4023 loss: 1.9463 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9463 2023/06/05 18:55:20 - mmengine - INFO - Epoch(train) [138][2560/2569] lr: 4.0000e-03 eta: 2:16:57 time: 0.2710 data_time: 0.0075 memory: 5828 grad_norm: 5.5557 loss: 1.4192 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4192 2023/06/05 18:55:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:55:22 - mmengine - INFO - Epoch(train) [138][2569/2569] lr: 4.0000e-03 eta: 2:16:54 time: 0.2587 data_time: 0.0073 memory: 5828 grad_norm: 5.6613 loss: 1.4267 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.4267 2023/06/05 18:55:29 - mmengine - INFO - Epoch(train) [139][ 20/2569] lr: 4.0000e-03 eta: 2:16:49 time: 0.3445 data_time: 0.0430 memory: 5828 grad_norm: 5.5379 loss: 1.7825 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7825 2023/06/05 18:55:35 - mmengine - INFO - Epoch(train) [139][ 40/2569] lr: 4.0000e-03 eta: 2:16:44 time: 0.2760 data_time: 0.0072 memory: 5828 grad_norm: 5.5342 loss: 1.6260 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.6260 2023/06/05 18:55:40 - mmengine - INFO - Epoch(train) [139][ 60/2569] lr: 4.0000e-03 eta: 2:16:39 time: 0.2621 data_time: 0.0076 memory: 5828 grad_norm: 5.4688 loss: 1.7511 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7511 2023/06/05 18:55:45 - mmengine - INFO - Epoch(train) [139][ 80/2569] lr: 4.0000e-03 eta: 2:16:33 time: 0.2729 data_time: 0.0073 memory: 5828 grad_norm: 5.3924 loss: 1.8139 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8139 2023/06/05 18:55:51 - mmengine - INFO - Epoch(train) [139][ 100/2569] lr: 4.0000e-03 eta: 2:16:28 time: 0.2660 data_time: 0.0076 memory: 5828 grad_norm: 5.3933 loss: 1.4722 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4722 2023/06/05 18:55:56 - mmengine - INFO - Epoch(train) [139][ 120/2569] lr: 4.0000e-03 eta: 2:16:23 time: 0.2663 data_time: 0.0074 memory: 5828 grad_norm: 5.3976 loss: 1.8914 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8914 2023/06/05 18:56:01 - mmengine - INFO - Epoch(train) [139][ 140/2569] lr: 4.0000e-03 eta: 2:16:17 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 5.5154 loss: 1.7035 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.7035 2023/06/05 18:56:07 - mmengine - INFO - Epoch(train) [139][ 160/2569] lr: 4.0000e-03 eta: 2:16:12 time: 0.2776 data_time: 0.0076 memory: 5828 grad_norm: 5.4899 loss: 1.5443 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5443 2023/06/05 18:56:12 - mmengine - INFO - Epoch(train) [139][ 180/2569] lr: 4.0000e-03 eta: 2:16:07 time: 0.2841 data_time: 0.0076 memory: 5828 grad_norm: 5.5590 loss: 1.6610 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6610 2023/06/05 18:56:18 - mmengine - INFO - Epoch(train) [139][ 200/2569] lr: 4.0000e-03 eta: 2:16:01 time: 0.2614 data_time: 0.0073 memory: 5828 grad_norm: 5.6091 loss: 1.8443 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8443 2023/06/05 18:56:23 - mmengine - INFO - Epoch(train) [139][ 220/2569] lr: 4.0000e-03 eta: 2:15:56 time: 0.2834 data_time: 0.0073 memory: 5828 grad_norm: 5.4820 loss: 1.6521 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6521 2023/06/05 18:56:29 - mmengine - INFO - Epoch(train) [139][ 240/2569] lr: 4.0000e-03 eta: 2:15:51 time: 0.2667 data_time: 0.0077 memory: 5828 grad_norm: 5.4833 loss: 1.6616 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6616 2023/06/05 18:56:34 - mmengine - INFO - Epoch(train) [139][ 260/2569] lr: 4.0000e-03 eta: 2:15:45 time: 0.2680 data_time: 0.0070 memory: 5828 grad_norm: 5.4155 loss: 1.5865 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5865 2023/06/05 18:56:39 - mmengine - INFO - Epoch(train) [139][ 280/2569] lr: 4.0000e-03 eta: 2:15:40 time: 0.2715 data_time: 0.0074 memory: 5828 grad_norm: 5.5664 loss: 1.5357 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5357 2023/06/05 18:56:45 - mmengine - INFO - Epoch(train) [139][ 300/2569] lr: 4.0000e-03 eta: 2:15:35 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 5.5678 loss: 1.6886 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6886 2023/06/05 18:56:50 - mmengine - INFO - Epoch(train) [139][ 320/2569] lr: 4.0000e-03 eta: 2:15:29 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 5.5060 loss: 1.7128 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7128 2023/06/05 18:56:55 - mmengine - INFO - Epoch(train) [139][ 340/2569] lr: 4.0000e-03 eta: 2:15:24 time: 0.2691 data_time: 0.0072 memory: 5828 grad_norm: 5.6036 loss: 1.6993 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6993 2023/06/05 18:57:01 - mmengine - INFO - Epoch(train) [139][ 360/2569] lr: 4.0000e-03 eta: 2:15:19 time: 0.2722 data_time: 0.0074 memory: 5828 grad_norm: 5.4562 loss: 1.4145 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4145 2023/06/05 18:57:06 - mmengine - INFO - Epoch(train) [139][ 380/2569] lr: 4.0000e-03 eta: 2:15:13 time: 0.2692 data_time: 0.0075 memory: 5828 grad_norm: 5.5335 loss: 1.7676 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7676 2023/06/05 18:57:12 - mmengine - INFO - Epoch(train) [139][ 400/2569] lr: 4.0000e-03 eta: 2:15:08 time: 0.2693 data_time: 0.0074 memory: 5828 grad_norm: 5.3474 loss: 1.7644 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7644 2023/06/05 18:57:17 - mmengine - INFO - Epoch(train) [139][ 420/2569] lr: 4.0000e-03 eta: 2:15:03 time: 0.2671 data_time: 0.0076 memory: 5828 grad_norm: 5.5818 loss: 1.8139 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8139 2023/06/05 18:57:22 - mmengine - INFO - Epoch(train) [139][ 440/2569] lr: 4.0000e-03 eta: 2:14:57 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 5.3955 loss: 1.5671 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5671 2023/06/05 18:57:28 - mmengine - INFO - Epoch(train) [139][ 460/2569] lr: 4.0000e-03 eta: 2:14:52 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 5.5500 loss: 1.4584 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4584 2023/06/05 18:57:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 18:57:33 - mmengine - INFO - Epoch(train) [139][ 480/2569] lr: 4.0000e-03 eta: 2:14:47 time: 0.2696 data_time: 0.0074 memory: 5828 grad_norm: 5.5614 loss: 1.7640 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7640 2023/06/05 18:57:38 - mmengine - INFO - Epoch(train) [139][ 500/2569] lr: 4.0000e-03 eta: 2:14:41 time: 0.2729 data_time: 0.0074 memory: 5828 grad_norm: 5.5139 loss: 1.5901 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5901 2023/06/05 18:57:44 - mmengine - INFO - Epoch(train) [139][ 520/2569] lr: 4.0000e-03 eta: 2:14:36 time: 0.2646 data_time: 0.0072 memory: 5828 grad_norm: 5.6867 loss: 1.9545 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9545 2023/06/05 18:57:49 - mmengine - INFO - Epoch(train) [139][ 540/2569] lr: 4.0000e-03 eta: 2:14:31 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 5.4331 loss: 1.6314 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6314 2023/06/05 18:57:54 - mmengine - INFO - Epoch(train) [139][ 560/2569] lr: 4.0000e-03 eta: 2:14:25 time: 0.2646 data_time: 0.0073 memory: 5828 grad_norm: 5.4021 loss: 1.7447 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7447 2023/06/05 18:58:00 - mmengine - INFO - Epoch(train) [139][ 580/2569] lr: 4.0000e-03 eta: 2:14:20 time: 0.2664 data_time: 0.0074 memory: 5828 grad_norm: 5.6704 loss: 1.7022 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7022 2023/06/05 18:58:05 - mmengine - INFO - Epoch(train) [139][ 600/2569] lr: 4.0000e-03 eta: 2:14:15 time: 0.2680 data_time: 0.0076 memory: 5828 grad_norm: 5.5777 loss: 1.8066 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8066 2023/06/05 18:58:11 - mmengine - INFO - Epoch(train) [139][ 620/2569] lr: 4.0000e-03 eta: 2:14:09 time: 0.2724 data_time: 0.0073 memory: 5828 grad_norm: 5.3902 loss: 1.7531 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7531 2023/06/05 18:58:16 - mmengine - INFO - Epoch(train) [139][ 640/2569] lr: 4.0000e-03 eta: 2:14:04 time: 0.2657 data_time: 0.0073 memory: 5828 grad_norm: 5.5346 loss: 1.8946 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8946 2023/06/05 18:58:21 - mmengine - INFO - Epoch(train) [139][ 660/2569] lr: 4.0000e-03 eta: 2:13:59 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 5.7306 loss: 1.5968 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5968 2023/06/05 18:58:27 - mmengine - INFO - Epoch(train) [139][ 680/2569] lr: 4.0000e-03 eta: 2:13:53 time: 0.2656 data_time: 0.0075 memory: 5828 grad_norm: 5.4461 loss: 1.4736 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4736 2023/06/05 18:58:32 - mmengine - INFO - Epoch(train) [139][ 700/2569] lr: 4.0000e-03 eta: 2:13:48 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 5.5708 loss: 1.7257 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7257 2023/06/05 18:58:37 - mmengine - INFO - Epoch(train) [139][ 720/2569] lr: 4.0000e-03 eta: 2:13:43 time: 0.2690 data_time: 0.0077 memory: 5828 grad_norm: 5.6898 loss: 1.5033 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5033 2023/06/05 18:58:43 - mmengine - INFO - Epoch(train) [139][ 740/2569] lr: 4.0000e-03 eta: 2:13:37 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 5.5124 loss: 1.9490 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9490 2023/06/05 18:58:48 - mmengine - INFO - Epoch(train) [139][ 760/2569] lr: 4.0000e-03 eta: 2:13:32 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 5.5366 loss: 1.6620 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6620 2023/06/05 18:58:53 - mmengine - INFO - Epoch(train) [139][ 780/2569] lr: 4.0000e-03 eta: 2:13:27 time: 0.2666 data_time: 0.0079 memory: 5828 grad_norm: 5.5234 loss: 1.8117 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8117 2023/06/05 18:58:59 - mmengine - INFO - Epoch(train) [139][ 800/2569] lr: 4.0000e-03 eta: 2:13:21 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 5.5788 loss: 1.8063 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8063 2023/06/05 18:59:04 - mmengine - INFO - Epoch(train) [139][ 820/2569] lr: 4.0000e-03 eta: 2:13:16 time: 0.2701 data_time: 0.0071 memory: 5828 grad_norm: 5.5251 loss: 1.7422 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7422 2023/06/05 18:59:09 - mmengine - INFO - Epoch(train) [139][ 840/2569] lr: 4.0000e-03 eta: 2:13:11 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 5.4395 loss: 1.3922 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.3922 2023/06/05 18:59:15 - mmengine - INFO - Epoch(train) [139][ 860/2569] lr: 4.0000e-03 eta: 2:13:06 time: 0.2695 data_time: 0.0078 memory: 5828 grad_norm: 5.5131 loss: 1.6485 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6485 2023/06/05 18:59:20 - mmengine - INFO - Epoch(train) [139][ 880/2569] lr: 4.0000e-03 eta: 2:13:00 time: 0.2801 data_time: 0.0074 memory: 5828 grad_norm: 5.5560 loss: 2.0072 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0072 2023/06/05 18:59:26 - mmengine - INFO - Epoch(train) [139][ 900/2569] lr: 4.0000e-03 eta: 2:12:55 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 5.4940 loss: 1.8835 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8835 2023/06/05 18:59:31 - mmengine - INFO - Epoch(train) [139][ 920/2569] lr: 4.0000e-03 eta: 2:12:50 time: 0.2721 data_time: 0.0074 memory: 5828 grad_norm: 5.5532 loss: 1.4766 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4766 2023/06/05 18:59:37 - mmengine - INFO - Epoch(train) [139][ 940/2569] lr: 4.0000e-03 eta: 2:12:44 time: 0.2779 data_time: 0.0074 memory: 5828 grad_norm: 5.5037 loss: 1.9086 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9086 2023/06/05 18:59:42 - mmengine - INFO - Epoch(train) [139][ 960/2569] lr: 4.0000e-03 eta: 2:12:39 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 5.3535 loss: 1.9705 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.9705 2023/06/05 18:59:48 - mmengine - INFO - Epoch(train) [139][ 980/2569] lr: 4.0000e-03 eta: 2:12:34 time: 0.2688 data_time: 0.0075 memory: 5828 grad_norm: 5.2433 loss: 1.5989 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5989 2023/06/05 18:59:53 - mmengine - INFO - Epoch(train) [139][1000/2569] lr: 4.0000e-03 eta: 2:12:28 time: 0.2784 data_time: 0.0070 memory: 5828 grad_norm: 5.5722 loss: 1.9603 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9603 2023/06/05 18:59:59 - mmengine - INFO - Epoch(train) [139][1020/2569] lr: 4.0000e-03 eta: 2:12:23 time: 0.2752 data_time: 0.0075 memory: 5828 grad_norm: 5.4691 loss: 1.9469 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9469 2023/06/05 19:00:04 - mmengine - INFO - Epoch(train) [139][1040/2569] lr: 4.0000e-03 eta: 2:12:18 time: 0.2710 data_time: 0.0079 memory: 5828 grad_norm: 5.5285 loss: 1.5835 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5835 2023/06/05 19:00:09 - mmengine - INFO - Epoch(train) [139][1060/2569] lr: 4.0000e-03 eta: 2:12:12 time: 0.2640 data_time: 0.0076 memory: 5828 grad_norm: 5.4762 loss: 1.6108 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6108 2023/06/05 19:00:15 - mmengine - INFO - Epoch(train) [139][1080/2569] lr: 4.0000e-03 eta: 2:12:07 time: 0.2696 data_time: 0.0073 memory: 5828 grad_norm: 5.3791 loss: 1.7343 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7343 2023/06/05 19:00:20 - mmengine - INFO - Epoch(train) [139][1100/2569] lr: 4.0000e-03 eta: 2:12:02 time: 0.2634 data_time: 0.0084 memory: 5828 grad_norm: 5.4982 loss: 1.8247 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8247 2023/06/05 19:00:25 - mmengine - INFO - Epoch(train) [139][1120/2569] lr: 4.0000e-03 eta: 2:11:56 time: 0.2643 data_time: 0.0076 memory: 5828 grad_norm: 5.5181 loss: 1.8162 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8162 2023/06/05 19:00:31 - mmengine - INFO - Epoch(train) [139][1140/2569] lr: 4.0000e-03 eta: 2:11:51 time: 0.2708 data_time: 0.0073 memory: 5828 grad_norm: 5.6064 loss: 2.0362 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 2.0362 2023/06/05 19:00:37 - mmengine - INFO - Epoch(train) [139][1160/2569] lr: 4.0000e-03 eta: 2:11:46 time: 0.2867 data_time: 0.0072 memory: 5828 grad_norm: 5.3999 loss: 1.7726 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7726 2023/06/05 19:00:42 - mmengine - INFO - Epoch(train) [139][1180/2569] lr: 4.0000e-03 eta: 2:11:40 time: 0.2694 data_time: 0.0079 memory: 5828 grad_norm: 5.4633 loss: 2.0323 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0323 2023/06/05 19:00:47 - mmengine - INFO - Epoch(train) [139][1200/2569] lr: 4.0000e-03 eta: 2:11:35 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 5.4803 loss: 1.9303 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9303 2023/06/05 19:00:53 - mmengine - INFO - Epoch(train) [139][1220/2569] lr: 4.0000e-03 eta: 2:11:30 time: 0.2697 data_time: 0.0072 memory: 5828 grad_norm: 5.4886 loss: 2.0412 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0412 2023/06/05 19:00:58 - mmengine - INFO - Epoch(train) [139][1240/2569] lr: 4.0000e-03 eta: 2:11:24 time: 0.2638 data_time: 0.0073 memory: 5828 grad_norm: 5.4996 loss: 1.8527 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8527 2023/06/05 19:01:03 - mmengine - INFO - Epoch(train) [139][1260/2569] lr: 4.0000e-03 eta: 2:11:19 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 5.5923 loss: 1.8065 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8065 2023/06/05 19:01:09 - mmengine - INFO - Epoch(train) [139][1280/2569] lr: 4.0000e-03 eta: 2:11:14 time: 0.2696 data_time: 0.0072 memory: 5828 grad_norm: 5.4393 loss: 1.7969 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7969 2023/06/05 19:01:14 - mmengine - INFO - Epoch(train) [139][1300/2569] lr: 4.0000e-03 eta: 2:11:08 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 5.5067 loss: 1.9028 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9028 2023/06/05 19:01:20 - mmengine - INFO - Epoch(train) [139][1320/2569] lr: 4.0000e-03 eta: 2:11:03 time: 0.2757 data_time: 0.0080 memory: 5828 grad_norm: 5.4882 loss: 1.8461 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8461 2023/06/05 19:01:25 - mmengine - INFO - Epoch(train) [139][1340/2569] lr: 4.0000e-03 eta: 2:10:58 time: 0.2620 data_time: 0.0083 memory: 5828 grad_norm: 5.5704 loss: 1.7196 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7196 2023/06/05 19:01:30 - mmengine - INFO - Epoch(train) [139][1360/2569] lr: 4.0000e-03 eta: 2:10:52 time: 0.2701 data_time: 0.0072 memory: 5828 grad_norm: 5.4203 loss: 1.8965 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8965 2023/06/05 19:01:36 - mmengine - INFO - Epoch(train) [139][1380/2569] lr: 4.0000e-03 eta: 2:10:47 time: 0.2621 data_time: 0.0071 memory: 5828 grad_norm: 5.4373 loss: 1.8261 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8261 2023/06/05 19:01:41 - mmengine - INFO - Epoch(train) [139][1400/2569] lr: 4.0000e-03 eta: 2:10:42 time: 0.2680 data_time: 0.0084 memory: 5828 grad_norm: 5.5504 loss: 1.8888 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8888 2023/06/05 19:01:46 - mmengine - INFO - Epoch(train) [139][1420/2569] lr: 4.0000e-03 eta: 2:10:36 time: 0.2637 data_time: 0.0076 memory: 5828 grad_norm: 5.4617 loss: 1.7664 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7664 2023/06/05 19:01:52 - mmengine - INFO - Epoch(train) [139][1440/2569] lr: 4.0000e-03 eta: 2:10:31 time: 0.2676 data_time: 0.0077 memory: 5828 grad_norm: 5.4855 loss: 1.6791 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6791 2023/06/05 19:01:57 - mmengine - INFO - Epoch(train) [139][1460/2569] lr: 4.0000e-03 eta: 2:10:26 time: 0.2660 data_time: 0.0075 memory: 5828 grad_norm: 5.4860 loss: 1.9125 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9125 2023/06/05 19:02:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:02:02 - mmengine - INFO - Epoch(train) [139][1480/2569] lr: 4.0000e-03 eta: 2:10:20 time: 0.2699 data_time: 0.0072 memory: 5828 grad_norm: 5.4988 loss: 1.6657 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6657 2023/06/05 19:02:08 - mmengine - INFO - Epoch(train) [139][1500/2569] lr: 4.0000e-03 eta: 2:10:15 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 5.4865 loss: 1.7790 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7790 2023/06/05 19:02:13 - mmengine - INFO - Epoch(train) [139][1520/2569] lr: 4.0000e-03 eta: 2:10:10 time: 0.2681 data_time: 0.0073 memory: 5828 grad_norm: 5.5763 loss: 1.6330 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6330 2023/06/05 19:02:18 - mmengine - INFO - Epoch(train) [139][1540/2569] lr: 4.0000e-03 eta: 2:10:04 time: 0.2739 data_time: 0.0072 memory: 5828 grad_norm: 5.5325 loss: 2.0545 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0545 2023/06/05 19:02:24 - mmengine - INFO - Epoch(train) [139][1560/2569] lr: 4.0000e-03 eta: 2:09:59 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 5.5264 loss: 1.6534 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6534 2023/06/05 19:02:29 - mmengine - INFO - Epoch(train) [139][1580/2569] lr: 4.0000e-03 eta: 2:09:54 time: 0.2675 data_time: 0.0076 memory: 5828 grad_norm: 5.4737 loss: 1.7277 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7277 2023/06/05 19:02:35 - mmengine - INFO - Epoch(train) [139][1600/2569] lr: 4.0000e-03 eta: 2:09:49 time: 0.2707 data_time: 0.0070 memory: 5828 grad_norm: 5.5052 loss: 2.0695 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0695 2023/06/05 19:02:40 - mmengine - INFO - Epoch(train) [139][1620/2569] lr: 4.0000e-03 eta: 2:09:43 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 5.4636 loss: 1.6903 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6903 2023/06/05 19:02:45 - mmengine - INFO - Epoch(train) [139][1640/2569] lr: 4.0000e-03 eta: 2:09:38 time: 0.2671 data_time: 0.0073 memory: 5828 grad_norm: 5.4665 loss: 1.8994 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8994 2023/06/05 19:02:51 - mmengine - INFO - Epoch(train) [139][1660/2569] lr: 4.0000e-03 eta: 2:09:33 time: 0.2766 data_time: 0.0072 memory: 5828 grad_norm: 5.4310 loss: 1.6718 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6718 2023/06/05 19:02:56 - mmengine - INFO - Epoch(train) [139][1680/2569] lr: 4.0000e-03 eta: 2:09:27 time: 0.2701 data_time: 0.0074 memory: 5828 grad_norm: 5.5372 loss: 1.5937 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5937 2023/06/05 19:03:02 - mmengine - INFO - Epoch(train) [139][1700/2569] lr: 4.0000e-03 eta: 2:09:22 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 5.4894 loss: 1.9067 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9067 2023/06/05 19:03:07 - mmengine - INFO - Epoch(train) [139][1720/2569] lr: 4.0000e-03 eta: 2:09:17 time: 0.2753 data_time: 0.0087 memory: 5828 grad_norm: 5.3785 loss: 1.4982 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.4982 2023/06/05 19:03:13 - mmengine - INFO - Epoch(train) [139][1740/2569] lr: 4.0000e-03 eta: 2:09:11 time: 0.2729 data_time: 0.0073 memory: 5828 grad_norm: 5.6385 loss: 1.7175 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7175 2023/06/05 19:03:18 - mmengine - INFO - Epoch(train) [139][1760/2569] lr: 4.0000e-03 eta: 2:09:06 time: 0.2696 data_time: 0.0076 memory: 5828 grad_norm: 5.4549 loss: 1.6916 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6916 2023/06/05 19:03:23 - mmengine - INFO - Epoch(train) [139][1780/2569] lr: 4.0000e-03 eta: 2:09:01 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 5.5005 loss: 1.9020 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9020 2023/06/05 19:03:29 - mmengine - INFO - Epoch(train) [139][1800/2569] lr: 4.0000e-03 eta: 2:08:55 time: 0.2627 data_time: 0.0071 memory: 5828 grad_norm: 5.6104 loss: 1.9160 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9160 2023/06/05 19:03:34 - mmengine - INFO - Epoch(train) [139][1820/2569] lr: 4.0000e-03 eta: 2:08:50 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 5.5891 loss: 1.6626 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6626 2023/06/05 19:03:39 - mmengine - INFO - Epoch(train) [139][1840/2569] lr: 4.0000e-03 eta: 2:08:45 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 5.3348 loss: 1.6796 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6796 2023/06/05 19:03:44 - mmengine - INFO - Epoch(train) [139][1860/2569] lr: 4.0000e-03 eta: 2:08:39 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 5.5149 loss: 1.9118 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9118 2023/06/05 19:03:50 - mmengine - INFO - Epoch(train) [139][1880/2569] lr: 4.0000e-03 eta: 2:08:34 time: 0.2610 data_time: 0.0075 memory: 5828 grad_norm: 5.4740 loss: 1.9029 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.9029 2023/06/05 19:03:55 - mmengine - INFO - Epoch(train) [139][1900/2569] lr: 4.0000e-03 eta: 2:08:29 time: 0.2662 data_time: 0.0069 memory: 5828 grad_norm: 5.6029 loss: 1.9988 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9988 2023/06/05 19:04:00 - mmengine - INFO - Epoch(train) [139][1920/2569] lr: 4.0000e-03 eta: 2:08:23 time: 0.2694 data_time: 0.0073 memory: 5828 grad_norm: 5.5543 loss: 1.8534 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8534 2023/06/05 19:04:06 - mmengine - INFO - Epoch(train) [139][1940/2569] lr: 4.0000e-03 eta: 2:08:18 time: 0.2682 data_time: 0.0071 memory: 5828 grad_norm: 5.4492 loss: 1.9624 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9624 2023/06/05 19:04:11 - mmengine - INFO - Epoch(train) [139][1960/2569] lr: 4.0000e-03 eta: 2:08:13 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 5.5326 loss: 1.8571 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8571 2023/06/05 19:04:17 - mmengine - INFO - Epoch(train) [139][1980/2569] lr: 4.0000e-03 eta: 2:08:07 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 5.4733 loss: 1.6881 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6881 2023/06/05 19:04:22 - mmengine - INFO - Epoch(train) [139][2000/2569] lr: 4.0000e-03 eta: 2:08:02 time: 0.2734 data_time: 0.0072 memory: 5828 grad_norm: 5.4535 loss: 1.5924 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5924 2023/06/05 19:04:27 - mmengine - INFO - Epoch(train) [139][2020/2569] lr: 4.0000e-03 eta: 2:07:57 time: 0.2689 data_time: 0.0077 memory: 5828 grad_norm: 5.4666 loss: 2.0583 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0583 2023/06/05 19:04:33 - mmengine - INFO - Epoch(train) [139][2040/2569] lr: 4.0000e-03 eta: 2:07:51 time: 0.2682 data_time: 0.0074 memory: 5828 grad_norm: 5.5389 loss: 1.7133 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7133 2023/06/05 19:04:38 - mmengine - INFO - Epoch(train) [139][2060/2569] lr: 4.0000e-03 eta: 2:07:46 time: 0.2698 data_time: 0.0079 memory: 5828 grad_norm: 5.5707 loss: 1.4346 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4346 2023/06/05 19:04:44 - mmengine - INFO - Epoch(train) [139][2080/2569] lr: 4.0000e-03 eta: 2:07:41 time: 0.2665 data_time: 0.0073 memory: 5828 grad_norm: 5.6140 loss: 1.9474 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.9474 2023/06/05 19:04:49 - mmengine - INFO - Epoch(train) [139][2100/2569] lr: 4.0000e-03 eta: 2:07:35 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 5.5266 loss: 1.7199 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7199 2023/06/05 19:04:54 - mmengine - INFO - Epoch(train) [139][2120/2569] lr: 4.0000e-03 eta: 2:07:30 time: 0.2720 data_time: 0.0075 memory: 5828 grad_norm: 5.5045 loss: 1.8340 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8340 2023/06/05 19:05:00 - mmengine - INFO - Epoch(train) [139][2140/2569] lr: 4.0000e-03 eta: 2:07:25 time: 0.2675 data_time: 0.0071 memory: 5828 grad_norm: 5.5740 loss: 1.6159 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6159 2023/06/05 19:05:05 - mmengine - INFO - Epoch(train) [139][2160/2569] lr: 4.0000e-03 eta: 2:07:19 time: 0.2685 data_time: 0.0077 memory: 5828 grad_norm: 5.6396 loss: 1.9835 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9835 2023/06/05 19:05:11 - mmengine - INFO - Epoch(train) [139][2180/2569] lr: 4.0000e-03 eta: 2:07:14 time: 0.2737 data_time: 0.0072 memory: 5828 grad_norm: 5.4150 loss: 1.6111 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6111 2023/06/05 19:05:16 - mmengine - INFO - Epoch(train) [139][2200/2569] lr: 4.0000e-03 eta: 2:07:09 time: 0.2695 data_time: 0.0070 memory: 5828 grad_norm: 5.6906 loss: 1.7891 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7891 2023/06/05 19:05:21 - mmengine - INFO - Epoch(train) [139][2220/2569] lr: 4.0000e-03 eta: 2:07:03 time: 0.2629 data_time: 0.0073 memory: 5828 grad_norm: 5.4586 loss: 1.8349 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8349 2023/06/05 19:05:27 - mmengine - INFO - Epoch(train) [139][2240/2569] lr: 4.0000e-03 eta: 2:06:58 time: 0.2714 data_time: 0.0071 memory: 5828 grad_norm: 5.5236 loss: 1.9258 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9258 2023/06/05 19:05:32 - mmengine - INFO - Epoch(train) [139][2260/2569] lr: 4.0000e-03 eta: 2:06:53 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 5.6135 loss: 1.5496 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5496 2023/06/05 19:05:37 - mmengine - INFO - Epoch(train) [139][2280/2569] lr: 4.0000e-03 eta: 2:06:47 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 5.4906 loss: 1.8128 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8128 2023/06/05 19:05:43 - mmengine - INFO - Epoch(train) [139][2300/2569] lr: 4.0000e-03 eta: 2:06:42 time: 0.2681 data_time: 0.0079 memory: 5828 grad_norm: 5.5653 loss: 1.8772 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8772 2023/06/05 19:05:48 - mmengine - INFO - Epoch(train) [139][2320/2569] lr: 4.0000e-03 eta: 2:06:37 time: 0.2618 data_time: 0.0095 memory: 5828 grad_norm: 5.4992 loss: 1.5361 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5361 2023/06/05 19:05:54 - mmengine - INFO - Epoch(train) [139][2340/2569] lr: 4.0000e-03 eta: 2:06:31 time: 0.2802 data_time: 0.0073 memory: 5828 grad_norm: 5.5014 loss: 2.1729 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1729 2023/06/05 19:05:59 - mmengine - INFO - Epoch(train) [139][2360/2569] lr: 4.0000e-03 eta: 2:06:26 time: 0.2660 data_time: 0.0073 memory: 5828 grad_norm: 5.6130 loss: 2.0140 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0140 2023/06/05 19:06:04 - mmengine - INFO - Epoch(train) [139][2380/2569] lr: 4.0000e-03 eta: 2:06:21 time: 0.2635 data_time: 0.0076 memory: 5828 grad_norm: 5.6421 loss: 1.9352 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.9352 2023/06/05 19:06:09 - mmengine - INFO - Epoch(train) [139][2400/2569] lr: 4.0000e-03 eta: 2:06:15 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 5.5117 loss: 1.7612 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7612 2023/06/05 19:06:15 - mmengine - INFO - Epoch(train) [139][2420/2569] lr: 4.0000e-03 eta: 2:06:10 time: 0.2629 data_time: 0.0076 memory: 5828 grad_norm: 5.5642 loss: 1.9253 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.9253 2023/06/05 19:06:20 - mmengine - INFO - Epoch(train) [139][2440/2569] lr: 4.0000e-03 eta: 2:06:05 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 5.6063 loss: 1.5764 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5764 2023/06/05 19:06:26 - mmengine - INFO - Epoch(train) [139][2460/2569] lr: 4.0000e-03 eta: 2:05:59 time: 0.2725 data_time: 0.0072 memory: 5828 grad_norm: 5.5050 loss: 1.7754 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7754 2023/06/05 19:06:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:06:31 - mmengine - INFO - Epoch(train) [139][2480/2569] lr: 4.0000e-03 eta: 2:05:54 time: 0.2657 data_time: 0.0074 memory: 5828 grad_norm: 5.4626 loss: 1.8608 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8608 2023/06/05 19:06:36 - mmengine - INFO - Epoch(train) [139][2500/2569] lr: 4.0000e-03 eta: 2:05:49 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 5.4575 loss: 2.0779 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 2.0779 2023/06/05 19:06:41 - mmengine - INFO - Epoch(train) [139][2520/2569] lr: 4.0000e-03 eta: 2:05:43 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 5.5223 loss: 2.1853 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.1853 2023/06/05 19:06:47 - mmengine - INFO - Epoch(train) [139][2540/2569] lr: 4.0000e-03 eta: 2:05:38 time: 0.2701 data_time: 0.0073 memory: 5828 grad_norm: 5.5872 loss: 1.9740 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9740 2023/06/05 19:06:52 - mmengine - INFO - Epoch(train) [139][2560/2569] lr: 4.0000e-03 eta: 2:05:33 time: 0.2752 data_time: 0.0077 memory: 5828 grad_norm: 5.5992 loss: 1.7589 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7589 2023/06/05 19:06:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:06:55 - mmengine - INFO - Epoch(train) [139][2569/2569] lr: 4.0000e-03 eta: 2:05:30 time: 0.2633 data_time: 0.0071 memory: 5828 grad_norm: 5.6859 loss: 1.8856 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.8856 2023/06/05 19:07:02 - mmengine - INFO - Epoch(train) [140][ 20/2569] lr: 4.0000e-03 eta: 2:05:25 time: 0.3575 data_time: 0.0561 memory: 5828 grad_norm: 5.6051 loss: 2.0507 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 2.0507 2023/06/05 19:07:07 - mmengine - INFO - Epoch(train) [140][ 40/2569] lr: 4.0000e-03 eta: 2:05:20 time: 0.2695 data_time: 0.0080 memory: 5828 grad_norm: 5.5096 loss: 1.6714 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6714 2023/06/05 19:07:12 - mmengine - INFO - Epoch(train) [140][ 60/2569] lr: 4.0000e-03 eta: 2:05:15 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 5.4869 loss: 1.5395 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5395 2023/06/05 19:07:18 - mmengine - INFO - Epoch(train) [140][ 80/2569] lr: 4.0000e-03 eta: 2:05:09 time: 0.2731 data_time: 0.0074 memory: 5828 grad_norm: 5.5882 loss: 1.7360 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7360 2023/06/05 19:07:23 - mmengine - INFO - Epoch(train) [140][ 100/2569] lr: 4.0000e-03 eta: 2:05:04 time: 0.2689 data_time: 0.0072 memory: 5828 grad_norm: 5.5304 loss: 1.6996 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6996 2023/06/05 19:07:29 - mmengine - INFO - Epoch(train) [140][ 120/2569] lr: 4.0000e-03 eta: 2:04:59 time: 0.2778 data_time: 0.0075 memory: 5828 grad_norm: 5.5119 loss: 1.5265 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5265 2023/06/05 19:07:34 - mmengine - INFO - Epoch(train) [140][ 140/2569] lr: 4.0000e-03 eta: 2:04:53 time: 0.2742 data_time: 0.0074 memory: 5828 grad_norm: 5.5454 loss: 1.7579 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7579 2023/06/05 19:07:40 - mmengine - INFO - Epoch(train) [140][ 160/2569] lr: 4.0000e-03 eta: 2:04:48 time: 0.2636 data_time: 0.0076 memory: 5828 grad_norm: 5.6772 loss: 1.7017 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7017 2023/06/05 19:07:45 - mmengine - INFO - Epoch(train) [140][ 180/2569] lr: 4.0000e-03 eta: 2:04:43 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 5.4684 loss: 1.8246 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8246 2023/06/05 19:07:50 - mmengine - INFO - Epoch(train) [140][ 200/2569] lr: 4.0000e-03 eta: 2:04:37 time: 0.2684 data_time: 0.0075 memory: 5828 grad_norm: 5.5547 loss: 1.9487 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9487 2023/06/05 19:07:56 - mmengine - INFO - Epoch(train) [140][ 220/2569] lr: 4.0000e-03 eta: 2:04:32 time: 0.2734 data_time: 0.0072 memory: 5828 grad_norm: 5.4030 loss: 1.7174 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7174 2023/06/05 19:08:01 - mmengine - INFO - Epoch(train) [140][ 240/2569] lr: 4.0000e-03 eta: 2:04:27 time: 0.2731 data_time: 0.0072 memory: 5828 grad_norm: 5.5518 loss: 1.5681 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5681 2023/06/05 19:08:07 - mmengine - INFO - Epoch(train) [140][ 260/2569] lr: 4.0000e-03 eta: 2:04:21 time: 0.2782 data_time: 0.0079 memory: 5828 grad_norm: 5.5139 loss: 1.5816 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5816 2023/06/05 19:08:12 - mmengine - INFO - Epoch(train) [140][ 280/2569] lr: 4.0000e-03 eta: 2:04:16 time: 0.2734 data_time: 0.0072 memory: 5828 grad_norm: 5.5324 loss: 1.5287 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5287 2023/06/05 19:08:18 - mmengine - INFO - Epoch(train) [140][ 300/2569] lr: 4.0000e-03 eta: 2:04:11 time: 0.2782 data_time: 0.0071 memory: 5828 grad_norm: 5.5199 loss: 1.4037 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4037 2023/06/05 19:08:23 - mmengine - INFO - Epoch(train) [140][ 320/2569] lr: 4.0000e-03 eta: 2:04:05 time: 0.2680 data_time: 0.0077 memory: 5828 grad_norm: 5.6619 loss: 1.6681 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6681 2023/06/05 19:08:29 - mmengine - INFO - Epoch(train) [140][ 340/2569] lr: 4.0000e-03 eta: 2:04:00 time: 0.2727 data_time: 0.0076 memory: 5828 grad_norm: 5.5490 loss: 1.7433 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7433 2023/06/05 19:08:34 - mmengine - INFO - Epoch(train) [140][ 360/2569] lr: 4.0000e-03 eta: 2:03:55 time: 0.2711 data_time: 0.0083 memory: 5828 grad_norm: 5.5531 loss: 1.7357 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7357 2023/06/05 19:08:40 - mmengine - INFO - Epoch(train) [140][ 380/2569] lr: 4.0000e-03 eta: 2:03:49 time: 0.2682 data_time: 0.0076 memory: 5828 grad_norm: 5.5038 loss: 1.5698 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5698 2023/06/05 19:08:45 - mmengine - INFO - Epoch(train) [140][ 400/2569] lr: 4.0000e-03 eta: 2:03:44 time: 0.2637 data_time: 0.0077 memory: 5828 grad_norm: 5.4790 loss: 1.3852 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.3852 2023/06/05 19:08:50 - mmengine - INFO - Epoch(train) [140][ 420/2569] lr: 4.0000e-03 eta: 2:03:39 time: 0.2688 data_time: 0.0078 memory: 5828 grad_norm: 5.4544 loss: 1.9375 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9375 2023/06/05 19:08:55 - mmengine - INFO - Epoch(train) [140][ 440/2569] lr: 4.0000e-03 eta: 2:03:33 time: 0.2630 data_time: 0.0076 memory: 5828 grad_norm: 5.5441 loss: 1.7490 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7490 2023/06/05 19:09:01 - mmengine - INFO - Epoch(train) [140][ 460/2569] lr: 4.0000e-03 eta: 2:03:28 time: 0.2818 data_time: 0.0076 memory: 5828 grad_norm: 5.5632 loss: 1.9205 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9205 2023/06/05 19:09:06 - mmengine - INFO - Epoch(train) [140][ 480/2569] lr: 4.0000e-03 eta: 2:03:23 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 5.5278 loss: 1.7083 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7083 2023/06/05 19:09:12 - mmengine - INFO - Epoch(train) [140][ 500/2569] lr: 4.0000e-03 eta: 2:03:17 time: 0.2761 data_time: 0.0073 memory: 5828 grad_norm: 5.6060 loss: 1.7664 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7664 2023/06/05 19:09:17 - mmengine - INFO - Epoch(train) [140][ 520/2569] lr: 4.0000e-03 eta: 2:03:12 time: 0.2704 data_time: 0.0071 memory: 5828 grad_norm: 5.5706 loss: 2.0017 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 2.0017 2023/06/05 19:09:23 - mmengine - INFO - Epoch(train) [140][ 540/2569] lr: 4.0000e-03 eta: 2:03:07 time: 0.2724 data_time: 0.0073 memory: 5828 grad_norm: 5.4702 loss: 1.8453 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8453 2023/06/05 19:09:28 - mmengine - INFO - Epoch(train) [140][ 560/2569] lr: 4.0000e-03 eta: 2:03:01 time: 0.2720 data_time: 0.0071 memory: 5828 grad_norm: 5.5002 loss: 1.4343 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4343 2023/06/05 19:09:34 - mmengine - INFO - Epoch(train) [140][ 580/2569] lr: 4.0000e-03 eta: 2:02:56 time: 0.2738 data_time: 0.0070 memory: 5828 grad_norm: 5.4619 loss: 1.6753 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6753 2023/06/05 19:09:39 - mmengine - INFO - Epoch(train) [140][ 600/2569] lr: 4.0000e-03 eta: 2:02:51 time: 0.2702 data_time: 0.0073 memory: 5828 grad_norm: 5.6308 loss: 1.6695 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6695 2023/06/05 19:09:45 - mmengine - INFO - Epoch(train) [140][ 620/2569] lr: 4.0000e-03 eta: 2:02:45 time: 0.2685 data_time: 0.0074 memory: 5828 grad_norm: 5.5385 loss: 1.6144 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6144 2023/06/05 19:09:50 - mmengine - INFO - Epoch(train) [140][ 640/2569] lr: 4.0000e-03 eta: 2:02:40 time: 0.2600 data_time: 0.0077 memory: 5828 grad_norm: 5.5553 loss: 1.9051 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9051 2023/06/05 19:09:55 - mmengine - INFO - Epoch(train) [140][ 660/2569] lr: 4.0000e-03 eta: 2:02:35 time: 0.2695 data_time: 0.0074 memory: 5828 grad_norm: 5.6189 loss: 1.6368 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6368 2023/06/05 19:10:00 - mmengine - INFO - Epoch(train) [140][ 680/2569] lr: 4.0000e-03 eta: 2:02:29 time: 0.2620 data_time: 0.0076 memory: 5828 grad_norm: 5.5241 loss: 1.5789 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5789 2023/06/05 19:10:06 - mmengine - INFO - Epoch(train) [140][ 700/2569] lr: 4.0000e-03 eta: 2:02:24 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 5.4408 loss: 1.8707 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8707 2023/06/05 19:10:11 - mmengine - INFO - Epoch(train) [140][ 720/2569] lr: 4.0000e-03 eta: 2:02:19 time: 0.2630 data_time: 0.0077 memory: 5828 grad_norm: 5.5824 loss: 1.4404 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4404 2023/06/05 19:10:16 - mmengine - INFO - Epoch(train) [140][ 740/2569] lr: 4.0000e-03 eta: 2:02:13 time: 0.2643 data_time: 0.0077 memory: 5828 grad_norm: 5.6504 loss: 1.8503 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8503 2023/06/05 19:10:22 - mmengine - INFO - Epoch(train) [140][ 760/2569] lr: 4.0000e-03 eta: 2:02:08 time: 0.2691 data_time: 0.0076 memory: 5828 grad_norm: 5.4794 loss: 1.9021 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9021 2023/06/05 19:10:27 - mmengine - INFO - Epoch(train) [140][ 780/2569] lr: 4.0000e-03 eta: 2:02:03 time: 0.2632 data_time: 0.0076 memory: 5828 grad_norm: 5.7105 loss: 1.8936 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8936 2023/06/05 19:10:33 - mmengine - INFO - Epoch(train) [140][ 800/2569] lr: 4.0000e-03 eta: 2:01:58 time: 0.2847 data_time: 0.0074 memory: 5828 grad_norm: 5.5011 loss: 1.6479 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6479 2023/06/05 19:10:38 - mmengine - INFO - Epoch(train) [140][ 820/2569] lr: 4.0000e-03 eta: 2:01:52 time: 0.2622 data_time: 0.0076 memory: 5828 grad_norm: 5.5068 loss: 1.8958 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8958 2023/06/05 19:10:43 - mmengine - INFO - Epoch(train) [140][ 840/2569] lr: 4.0000e-03 eta: 2:01:47 time: 0.2694 data_time: 0.0073 memory: 5828 grad_norm: 5.4820 loss: 1.8347 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8347 2023/06/05 19:10:49 - mmengine - INFO - Epoch(train) [140][ 860/2569] lr: 4.0000e-03 eta: 2:01:42 time: 0.2693 data_time: 0.0076 memory: 5828 grad_norm: 5.5387 loss: 1.8399 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8399 2023/06/05 19:10:54 - mmengine - INFO - Epoch(train) [140][ 880/2569] lr: 4.0000e-03 eta: 2:01:36 time: 0.2609 data_time: 0.0072 memory: 5828 grad_norm: 5.5324 loss: 1.6498 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6498 2023/06/05 19:11:00 - mmengine - INFO - Epoch(train) [140][ 900/2569] lr: 4.0000e-03 eta: 2:01:31 time: 0.2733 data_time: 0.0074 memory: 5828 grad_norm: 5.4839 loss: 1.6898 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6898 2023/06/05 19:11:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:11:05 - mmengine - INFO - Epoch(train) [140][ 920/2569] lr: 4.0000e-03 eta: 2:01:26 time: 0.2944 data_time: 0.0072 memory: 5828 grad_norm: 5.5743 loss: 1.7744 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7744 2023/06/05 19:11:11 - mmengine - INFO - Epoch(train) [140][ 940/2569] lr: 4.0000e-03 eta: 2:01:20 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 5.5159 loss: 1.9115 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.9115 2023/06/05 19:11:16 - mmengine - INFO - Epoch(train) [140][ 960/2569] lr: 4.0000e-03 eta: 2:01:15 time: 0.2820 data_time: 0.0073 memory: 5828 grad_norm: 5.5218 loss: 1.6811 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6811 2023/06/05 19:11:22 - mmengine - INFO - Epoch(train) [140][ 980/2569] lr: 4.0000e-03 eta: 2:01:10 time: 0.2689 data_time: 0.0081 memory: 5828 grad_norm: 5.4972 loss: 1.9127 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9127 2023/06/05 19:11:27 - mmengine - INFO - Epoch(train) [140][1000/2569] lr: 4.0000e-03 eta: 2:01:04 time: 0.2652 data_time: 0.0074 memory: 5828 grad_norm: 5.5466 loss: 1.8794 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8794 2023/06/05 19:11:33 - mmengine - INFO - Epoch(train) [140][1020/2569] lr: 4.0000e-03 eta: 2:00:59 time: 0.2705 data_time: 0.0072 memory: 5828 grad_norm: 5.5760 loss: 1.8095 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8095 2023/06/05 19:11:38 - mmengine - INFO - Epoch(train) [140][1040/2569] lr: 4.0000e-03 eta: 2:00:54 time: 0.2628 data_time: 0.0074 memory: 5828 grad_norm: 5.4522 loss: 1.4940 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4940 2023/06/05 19:11:43 - mmengine - INFO - Epoch(train) [140][1060/2569] lr: 4.0000e-03 eta: 2:00:48 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 5.5084 loss: 1.9434 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9434 2023/06/05 19:11:49 - mmengine - INFO - Epoch(train) [140][1080/2569] lr: 4.0000e-03 eta: 2:00:43 time: 0.2791 data_time: 0.0074 memory: 5828 grad_norm: 5.4981 loss: 2.1269 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.1269 2023/06/05 19:11:54 - mmengine - INFO - Epoch(train) [140][1100/2569] lr: 4.0000e-03 eta: 2:00:38 time: 0.2672 data_time: 0.0071 memory: 5828 grad_norm: 5.5884 loss: 1.7716 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7716 2023/06/05 19:11:59 - mmengine - INFO - Epoch(train) [140][1120/2569] lr: 4.0000e-03 eta: 2:00:32 time: 0.2676 data_time: 0.0071 memory: 5828 grad_norm: 5.5686 loss: 1.5048 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5048 2023/06/05 19:12:05 - mmengine - INFO - Epoch(train) [140][1140/2569] lr: 4.0000e-03 eta: 2:00:27 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 5.5054 loss: 1.7419 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7419 2023/06/05 19:12:10 - mmengine - INFO - Epoch(train) [140][1160/2569] lr: 4.0000e-03 eta: 2:00:22 time: 0.2617 data_time: 0.0075 memory: 5828 grad_norm: 5.4208 loss: 1.7506 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7506 2023/06/05 19:12:15 - mmengine - INFO - Epoch(train) [140][1180/2569] lr: 4.0000e-03 eta: 2:00:16 time: 0.2629 data_time: 0.0075 memory: 5828 grad_norm: 5.4834 loss: 1.7973 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7973 2023/06/05 19:12:21 - mmengine - INFO - Epoch(train) [140][1200/2569] lr: 4.0000e-03 eta: 2:00:11 time: 0.2692 data_time: 0.0075 memory: 5828 grad_norm: 5.5052 loss: 1.3136 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3136 2023/06/05 19:12:26 - mmengine - INFO - Epoch(train) [140][1220/2569] lr: 4.0000e-03 eta: 2:00:06 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 5.5905 loss: 1.8625 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8625 2023/06/05 19:12:31 - mmengine - INFO - Epoch(train) [140][1240/2569] lr: 4.0000e-03 eta: 2:00:00 time: 0.2742 data_time: 0.0074 memory: 5828 grad_norm: 5.5435 loss: 2.0035 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 2.0035 2023/06/05 19:12:37 - mmengine - INFO - Epoch(train) [140][1260/2569] lr: 4.0000e-03 eta: 1:59:55 time: 0.2727 data_time: 0.0076 memory: 5828 grad_norm: 5.5987 loss: 1.6760 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6760 2023/06/05 19:12:42 - mmengine - INFO - Epoch(train) [140][1280/2569] lr: 4.0000e-03 eta: 1:59:50 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 5.6741 loss: 1.5365 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5365 2023/06/05 19:12:48 - mmengine - INFO - Epoch(train) [140][1300/2569] lr: 4.0000e-03 eta: 1:59:44 time: 0.2709 data_time: 0.0070 memory: 5828 grad_norm: 5.4144 loss: 1.5548 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.5548 2023/06/05 19:12:53 - mmengine - INFO - Epoch(train) [140][1320/2569] lr: 4.0000e-03 eta: 1:59:39 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 5.5621 loss: 1.8216 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8216 2023/06/05 19:12:58 - mmengine - INFO - Epoch(train) [140][1340/2569] lr: 4.0000e-03 eta: 1:59:34 time: 0.2724 data_time: 0.0076 memory: 5828 grad_norm: 5.6345 loss: 1.6169 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6169 2023/06/05 19:13:04 - mmengine - INFO - Epoch(train) [140][1360/2569] lr: 4.0000e-03 eta: 1:59:28 time: 0.2683 data_time: 0.0071 memory: 5828 grad_norm: 5.5336 loss: 2.4645 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.4645 2023/06/05 19:13:09 - mmengine - INFO - Epoch(train) [140][1380/2569] lr: 4.0000e-03 eta: 1:59:23 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 5.4953 loss: 1.9160 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9160 2023/06/05 19:13:14 - mmengine - INFO - Epoch(train) [140][1400/2569] lr: 4.0000e-03 eta: 1:59:18 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 5.5479 loss: 1.9789 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9789 2023/06/05 19:13:20 - mmengine - INFO - Epoch(train) [140][1420/2569] lr: 4.0000e-03 eta: 1:59:12 time: 0.2641 data_time: 0.0070 memory: 5828 grad_norm: 5.4484 loss: 1.8196 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8196 2023/06/05 19:13:25 - mmengine - INFO - Epoch(train) [140][1440/2569] lr: 4.0000e-03 eta: 1:59:07 time: 0.2616 data_time: 0.0076 memory: 5828 grad_norm: 5.5579 loss: 1.8724 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8724 2023/06/05 19:13:31 - mmengine - INFO - Epoch(train) [140][1460/2569] lr: 4.0000e-03 eta: 1:59:02 time: 0.2731 data_time: 0.0069 memory: 5828 grad_norm: 5.6750 loss: 2.1648 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1648 2023/06/05 19:13:36 - mmengine - INFO - Epoch(train) [140][1480/2569] lr: 4.0000e-03 eta: 1:58:56 time: 0.2638 data_time: 0.0075 memory: 5828 grad_norm: 5.5562 loss: 1.6595 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6595 2023/06/05 19:13:41 - mmengine - INFO - Epoch(train) [140][1500/2569] lr: 4.0000e-03 eta: 1:58:51 time: 0.2703 data_time: 0.0070 memory: 5828 grad_norm: 5.6669 loss: 2.0254 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0254 2023/06/05 19:13:47 - mmengine - INFO - Epoch(train) [140][1520/2569] lr: 4.0000e-03 eta: 1:58:46 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 5.5163 loss: 2.0331 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0331 2023/06/05 19:13:52 - mmengine - INFO - Epoch(train) [140][1540/2569] lr: 4.0000e-03 eta: 1:58:40 time: 0.2733 data_time: 0.0071 memory: 5828 grad_norm: 5.6797 loss: 1.7413 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7413 2023/06/05 19:13:58 - mmengine - INFO - Epoch(train) [140][1560/2569] lr: 4.0000e-03 eta: 1:58:35 time: 0.2737 data_time: 0.0073 memory: 5828 grad_norm: 5.6729 loss: 1.5353 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5353 2023/06/05 19:14:03 - mmengine - INFO - Epoch(train) [140][1580/2569] lr: 4.0000e-03 eta: 1:58:30 time: 0.2644 data_time: 0.0076 memory: 5828 grad_norm: 5.4316 loss: 1.7148 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7148 2023/06/05 19:14:08 - mmengine - INFO - Epoch(train) [140][1600/2569] lr: 4.0000e-03 eta: 1:58:24 time: 0.2693 data_time: 0.0080 memory: 5828 grad_norm: 5.5565 loss: 1.6627 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6627 2023/06/05 19:14:14 - mmengine - INFO - Epoch(train) [140][1620/2569] lr: 4.0000e-03 eta: 1:58:19 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 5.4103 loss: 1.7314 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7314 2023/06/05 19:14:19 - mmengine - INFO - Epoch(train) [140][1640/2569] lr: 4.0000e-03 eta: 1:58:14 time: 0.2728 data_time: 0.0072 memory: 5828 grad_norm: 5.3767 loss: 1.7139 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7139 2023/06/05 19:14:24 - mmengine - INFO - Epoch(train) [140][1660/2569] lr: 4.0000e-03 eta: 1:58:08 time: 0.2673 data_time: 0.0077 memory: 5828 grad_norm: 5.6278 loss: 1.6315 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6315 2023/06/05 19:14:30 - mmengine - INFO - Epoch(train) [140][1680/2569] lr: 4.0000e-03 eta: 1:58:03 time: 0.2694 data_time: 0.0070 memory: 5828 grad_norm: 5.6405 loss: 1.8566 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8566 2023/06/05 19:14:35 - mmengine - INFO - Epoch(train) [140][1700/2569] lr: 4.0000e-03 eta: 1:57:58 time: 0.2742 data_time: 0.0072 memory: 5828 grad_norm: 5.5612 loss: 1.6738 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6738 2023/06/05 19:14:41 - mmengine - INFO - Epoch(train) [140][1720/2569] lr: 4.0000e-03 eta: 1:57:52 time: 0.2691 data_time: 0.0073 memory: 5828 grad_norm: 5.5622 loss: 1.7580 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7580 2023/06/05 19:14:46 - mmengine - INFO - Epoch(train) [140][1740/2569] lr: 4.0000e-03 eta: 1:57:47 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 5.6012 loss: 1.7933 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7933 2023/06/05 19:14:51 - mmengine - INFO - Epoch(train) [140][1760/2569] lr: 4.0000e-03 eta: 1:57:42 time: 0.2718 data_time: 0.0075 memory: 5828 grad_norm: 5.5711 loss: 1.7124 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7124 2023/06/05 19:14:57 - mmengine - INFO - Epoch(train) [140][1780/2569] lr: 4.0000e-03 eta: 1:57:37 time: 0.2738 data_time: 0.0074 memory: 5828 grad_norm: 5.5337 loss: 2.1691 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.1691 2023/06/05 19:15:02 - mmengine - INFO - Epoch(train) [140][1800/2569] lr: 4.0000e-03 eta: 1:57:31 time: 0.2780 data_time: 0.0073 memory: 5828 grad_norm: 5.5997 loss: 1.7323 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7323 2023/06/05 19:15:08 - mmengine - INFO - Epoch(train) [140][1820/2569] lr: 4.0000e-03 eta: 1:57:26 time: 0.2702 data_time: 0.0076 memory: 5828 grad_norm: 5.5798 loss: 1.6109 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6109 2023/06/05 19:15:13 - mmengine - INFO - Epoch(train) [140][1840/2569] lr: 4.0000e-03 eta: 1:57:21 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 5.5928 loss: 1.9983 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9983 2023/06/05 19:15:19 - mmengine - INFO - Epoch(train) [140][1860/2569] lr: 4.0000e-03 eta: 1:57:15 time: 0.2712 data_time: 0.0074 memory: 5828 grad_norm: 5.6150 loss: 2.1219 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 2.1219 2023/06/05 19:15:24 - mmengine - INFO - Epoch(train) [140][1880/2569] lr: 4.0000e-03 eta: 1:57:10 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 5.6371 loss: 1.7827 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7827 2023/06/05 19:15:29 - mmengine - INFO - Epoch(train) [140][1900/2569] lr: 4.0000e-03 eta: 1:57:05 time: 0.2619 data_time: 0.0076 memory: 5828 grad_norm: 5.5068 loss: 1.8931 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8931 2023/06/05 19:15:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:15:35 - mmengine - INFO - Epoch(train) [140][1920/2569] lr: 4.0000e-03 eta: 1:56:59 time: 0.2663 data_time: 0.0075 memory: 5828 grad_norm: 5.5485 loss: 1.8286 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8286 2023/06/05 19:15:40 - mmengine - INFO - Epoch(train) [140][1940/2569] lr: 4.0000e-03 eta: 1:56:54 time: 0.2751 data_time: 0.0072 memory: 5828 grad_norm: 5.5892 loss: 1.9136 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9136 2023/06/05 19:15:46 - mmengine - INFO - Epoch(train) [140][1960/2569] lr: 4.0000e-03 eta: 1:56:49 time: 0.2709 data_time: 0.0072 memory: 5828 grad_norm: 5.6539 loss: 1.9895 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9895 2023/06/05 19:15:51 - mmengine - INFO - Epoch(train) [140][1980/2569] lr: 4.0000e-03 eta: 1:56:43 time: 0.2702 data_time: 0.0075 memory: 5828 grad_norm: 5.5607 loss: 1.7674 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7674 2023/06/05 19:15:56 - mmengine - INFO - Epoch(train) [140][2000/2569] lr: 4.0000e-03 eta: 1:56:38 time: 0.2668 data_time: 0.0072 memory: 5828 grad_norm: 5.4977 loss: 1.6952 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6952 2023/06/05 19:16:02 - mmengine - INFO - Epoch(train) [140][2020/2569] lr: 4.0000e-03 eta: 1:56:33 time: 0.2748 data_time: 0.0072 memory: 5828 grad_norm: 5.6819 loss: 1.6247 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6247 2023/06/05 19:16:07 - mmengine - INFO - Epoch(train) [140][2040/2569] lr: 4.0000e-03 eta: 1:56:27 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 5.5756 loss: 1.9753 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9753 2023/06/05 19:16:12 - mmengine - INFO - Epoch(train) [140][2060/2569] lr: 4.0000e-03 eta: 1:56:22 time: 0.2656 data_time: 0.0071 memory: 5828 grad_norm: 5.5809 loss: 1.5264 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5264 2023/06/05 19:16:18 - mmengine - INFO - Epoch(train) [140][2080/2569] lr: 4.0000e-03 eta: 1:56:17 time: 0.2623 data_time: 0.0074 memory: 5828 grad_norm: 5.6164 loss: 1.4771 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4771 2023/06/05 19:16:23 - mmengine - INFO - Epoch(train) [140][2100/2569] lr: 4.0000e-03 eta: 1:56:11 time: 0.2738 data_time: 0.0074 memory: 5828 grad_norm: 5.5671 loss: 1.5904 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5904 2023/06/05 19:16:29 - mmengine - INFO - Epoch(train) [140][2120/2569] lr: 4.0000e-03 eta: 1:56:06 time: 0.2729 data_time: 0.0079 memory: 5828 grad_norm: 5.6539 loss: 1.5180 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5180 2023/06/05 19:16:34 - mmengine - INFO - Epoch(train) [140][2140/2569] lr: 4.0000e-03 eta: 1:56:01 time: 0.2722 data_time: 0.0074 memory: 5828 grad_norm: 5.6144 loss: 1.7464 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7464 2023/06/05 19:16:40 - mmengine - INFO - Epoch(train) [140][2160/2569] lr: 4.0000e-03 eta: 1:55:55 time: 0.2673 data_time: 0.0071 memory: 5828 grad_norm: 5.5464 loss: 2.0563 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 2.0563 2023/06/05 19:16:45 - mmengine - INFO - Epoch(train) [140][2180/2569] lr: 4.0000e-03 eta: 1:55:50 time: 0.2752 data_time: 0.0073 memory: 5828 grad_norm: 5.6612 loss: 1.9564 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9564 2023/06/05 19:16:50 - mmengine - INFO - Epoch(train) [140][2200/2569] lr: 4.0000e-03 eta: 1:55:45 time: 0.2615 data_time: 0.0081 memory: 5828 grad_norm: 5.7148 loss: 1.6015 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6015 2023/06/05 19:16:56 - mmengine - INFO - Epoch(train) [140][2220/2569] lr: 4.0000e-03 eta: 1:55:39 time: 0.2743 data_time: 0.0073 memory: 5828 grad_norm: 5.6764 loss: 1.4803 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4803 2023/06/05 19:17:01 - mmengine - INFO - Epoch(train) [140][2240/2569] lr: 4.0000e-03 eta: 1:55:34 time: 0.2690 data_time: 0.0073 memory: 5828 grad_norm: 5.4486 loss: 1.7820 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7820 2023/06/05 19:17:07 - mmengine - INFO - Epoch(train) [140][2260/2569] lr: 4.0000e-03 eta: 1:55:29 time: 0.2726 data_time: 0.0072 memory: 5828 grad_norm: 5.6140 loss: 1.7142 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7142 2023/06/05 19:17:12 - mmengine - INFO - Epoch(train) [140][2280/2569] lr: 4.0000e-03 eta: 1:55:23 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 5.5906 loss: 1.7011 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7011 2023/06/05 19:17:17 - mmengine - INFO - Epoch(train) [140][2300/2569] lr: 4.0000e-03 eta: 1:55:18 time: 0.2640 data_time: 0.0071 memory: 5828 grad_norm: 5.6202 loss: 1.7027 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7027 2023/06/05 19:17:23 - mmengine - INFO - Epoch(train) [140][2320/2569] lr: 4.0000e-03 eta: 1:55:13 time: 0.2648 data_time: 0.0071 memory: 5828 grad_norm: 5.7024 loss: 2.1594 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.1594 2023/06/05 19:17:28 - mmengine - INFO - Epoch(train) [140][2340/2569] lr: 4.0000e-03 eta: 1:55:07 time: 0.2713 data_time: 0.0072 memory: 5828 grad_norm: 5.5676 loss: 1.5810 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5810 2023/06/05 19:17:33 - mmengine - INFO - Epoch(train) [140][2360/2569] lr: 4.0000e-03 eta: 1:55:02 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 5.5393 loss: 1.7461 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7461 2023/06/05 19:17:39 - mmengine - INFO - Epoch(train) [140][2380/2569] lr: 4.0000e-03 eta: 1:54:57 time: 0.2715 data_time: 0.0072 memory: 5828 grad_norm: 5.5414 loss: 1.7094 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7094 2023/06/05 19:17:44 - mmengine - INFO - Epoch(train) [140][2400/2569] lr: 4.0000e-03 eta: 1:54:51 time: 0.2645 data_time: 0.0071 memory: 5828 grad_norm: 5.5406 loss: 1.9106 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.9106 2023/06/05 19:17:49 - mmengine - INFO - Epoch(train) [140][2420/2569] lr: 4.0000e-03 eta: 1:54:46 time: 0.2750 data_time: 0.0073 memory: 5828 grad_norm: 5.5353 loss: 1.9243 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9243 2023/06/05 19:17:55 - mmengine - INFO - Epoch(train) [140][2440/2569] lr: 4.0000e-03 eta: 1:54:41 time: 0.2725 data_time: 0.0073 memory: 5828 grad_norm: 5.5867 loss: 1.6488 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6488 2023/06/05 19:18:00 - mmengine - INFO - Epoch(train) [140][2460/2569] lr: 4.0000e-03 eta: 1:54:35 time: 0.2731 data_time: 0.0072 memory: 5828 grad_norm: 5.4456 loss: 2.0743 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0743 2023/06/05 19:18:06 - mmengine - INFO - Epoch(train) [140][2480/2569] lr: 4.0000e-03 eta: 1:54:30 time: 0.2680 data_time: 0.0075 memory: 5828 grad_norm: 5.5067 loss: 1.4929 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4929 2023/06/05 19:18:11 - mmengine - INFO - Epoch(train) [140][2500/2569] lr: 4.0000e-03 eta: 1:54:25 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 5.6832 loss: 1.7208 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7208 2023/06/05 19:18:17 - mmengine - INFO - Epoch(train) [140][2520/2569] lr: 4.0000e-03 eta: 1:54:19 time: 0.2694 data_time: 0.0077 memory: 5828 grad_norm: 5.5466 loss: 1.6260 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6260 2023/06/05 19:18:22 - mmengine - INFO - Epoch(train) [140][2540/2569] lr: 4.0000e-03 eta: 1:54:14 time: 0.2776 data_time: 0.0074 memory: 5828 grad_norm: 5.5691 loss: 1.4574 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.4574 2023/06/05 19:18:27 - mmengine - INFO - Epoch(train) [140][2560/2569] lr: 4.0000e-03 eta: 1:54:09 time: 0.2638 data_time: 0.0072 memory: 5828 grad_norm: 5.5022 loss: 1.7268 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 1.7268 2023/06/05 19:18:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:18:30 - mmengine - INFO - Epoch(train) [140][2569/2569] lr: 4.0000e-03 eta: 1:54:06 time: 0.2608 data_time: 0.0072 memory: 5828 grad_norm: 5.5786 loss: 1.7382 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.7382 2023/06/05 19:18:30 - mmengine - INFO - Saving checkpoint at 140 epochs 2023/06/05 19:18:36 - mmengine - INFO - Epoch(val) [140][ 20/260] eta: 0:00:44 time: 0.1842 data_time: 0.1250 memory: 1238 2023/06/05 19:18:39 - mmengine - INFO - Epoch(val) [140][ 40/260] eta: 0:00:35 time: 0.1350 data_time: 0.0763 memory: 1238 2023/06/05 19:18:42 - mmengine - INFO - Epoch(val) [140][ 60/260] eta: 0:00:31 time: 0.1600 data_time: 0.1013 memory: 1238 2023/06/05 19:18:44 - mmengine - INFO - Epoch(val) [140][ 80/260] eta: 0:00:27 time: 0.1218 data_time: 0.0632 memory: 1238 2023/06/05 19:18:48 - mmengine - INFO - Epoch(val) [140][100/260] eta: 0:00:24 time: 0.1567 data_time: 0.0984 memory: 1238 2023/06/05 19:18:50 - mmengine - INFO - Epoch(val) [140][120/260] eta: 0:00:20 time: 0.1239 data_time: 0.0649 memory: 1238 2023/06/05 19:18:53 - mmengine - INFO - Epoch(val) [140][140/260] eta: 0:00:17 time: 0.1434 data_time: 0.0848 memory: 1238 2023/06/05 19:18:55 - mmengine - INFO - Epoch(val) [140][160/260] eta: 0:00:14 time: 0.1225 data_time: 0.0635 memory: 1238 2023/06/05 19:18:58 - mmengine - INFO - Epoch(val) [140][180/260] eta: 0:00:11 time: 0.1586 data_time: 0.1000 memory: 1238 2023/06/05 19:19:01 - mmengine - INFO - Epoch(val) [140][200/260] eta: 0:00:08 time: 0.1431 data_time: 0.0845 memory: 1238 2023/06/05 19:19:04 - mmengine - INFO - Epoch(val) [140][220/260] eta: 0:00:05 time: 0.1563 data_time: 0.0982 memory: 1238 2023/06/05 19:19:07 - mmengine - INFO - Epoch(val) [140][240/260] eta: 0:00:02 time: 0.1126 data_time: 0.0556 memory: 1238 2023/06/05 19:19:09 - mmengine - INFO - Epoch(val) [140][260/260] eta: 0:00:00 time: 0.1054 data_time: 0.0496 memory: 1238 2023/06/05 19:19:16 - mmengine - INFO - Epoch(val) [140][260/260] acc/top1: 0.6185 acc/top5: 0.8327 acc/mean1: 0.6122 data_time: 0.0816 time: 0.1399 2023/06/05 19:19:22 - mmengine - INFO - Epoch(train) [141][ 20/2569] lr: 4.0000e-04 eta: 1:54:01 time: 0.3339 data_time: 0.0519 memory: 5828 grad_norm: 5.4080 loss: 1.8648 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8648 2023/06/05 19:19:28 - mmengine - INFO - Epoch(train) [141][ 40/2569] lr: 4.0000e-04 eta: 1:53:56 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 5.4942 loss: 1.7495 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7495 2023/06/05 19:19:33 - mmengine - INFO - Epoch(train) [141][ 60/2569] lr: 4.0000e-04 eta: 1:53:50 time: 0.2735 data_time: 0.0074 memory: 5828 grad_norm: 5.4157 loss: 1.5725 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5725 2023/06/05 19:19:39 - mmengine - INFO - Epoch(train) [141][ 80/2569] lr: 4.0000e-04 eta: 1:53:45 time: 0.2764 data_time: 0.0071 memory: 5828 grad_norm: 5.3539 loss: 1.7405 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.7405 2023/06/05 19:19:44 - mmengine - INFO - Epoch(train) [141][ 100/2569] lr: 4.0000e-04 eta: 1:53:40 time: 0.2747 data_time: 0.0075 memory: 5828 grad_norm: 5.4538 loss: 2.0627 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0627 2023/06/05 19:19:50 - mmengine - INFO - Epoch(train) [141][ 120/2569] lr: 4.0000e-04 eta: 1:53:35 time: 0.2784 data_time: 0.0074 memory: 5828 grad_norm: 5.5454 loss: 1.7085 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7085 2023/06/05 19:19:55 - mmengine - INFO - Epoch(train) [141][ 140/2569] lr: 4.0000e-04 eta: 1:53:29 time: 0.2687 data_time: 0.0072 memory: 5828 grad_norm: 5.4449 loss: 1.7948 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7948 2023/06/05 19:20:01 - mmengine - INFO - Epoch(train) [141][ 160/2569] lr: 4.0000e-04 eta: 1:53:24 time: 0.2736 data_time: 0.0074 memory: 5828 grad_norm: 5.5077 loss: 1.6614 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6614 2023/06/05 19:20:06 - mmengine - INFO - Epoch(train) [141][ 180/2569] lr: 4.0000e-04 eta: 1:53:19 time: 0.2769 data_time: 0.0072 memory: 5828 grad_norm: 5.3465 loss: 1.7096 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7096 2023/06/05 19:20:12 - mmengine - INFO - Epoch(train) [141][ 200/2569] lr: 4.0000e-04 eta: 1:53:13 time: 0.2778 data_time: 0.0072 memory: 5828 grad_norm: 5.5442 loss: 1.7352 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7352 2023/06/05 19:20:17 - mmengine - INFO - Epoch(train) [141][ 220/2569] lr: 4.0000e-04 eta: 1:53:08 time: 0.2765 data_time: 0.0080 memory: 5828 grad_norm: 5.5182 loss: 1.7055 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7055 2023/06/05 19:20:23 - mmengine - INFO - Epoch(train) [141][ 240/2569] lr: 4.0000e-04 eta: 1:53:03 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 5.4226 loss: 1.5766 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5766 2023/06/05 19:20:28 - mmengine - INFO - Epoch(train) [141][ 260/2569] lr: 4.0000e-04 eta: 1:52:57 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 5.4542 loss: 1.4561 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4561 2023/06/05 19:20:33 - mmengine - INFO - Epoch(train) [141][ 280/2569] lr: 4.0000e-04 eta: 1:52:52 time: 0.2639 data_time: 0.0076 memory: 5828 grad_norm: 5.4033 loss: 1.7104 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7104 2023/06/05 19:20:39 - mmengine - INFO - Epoch(train) [141][ 300/2569] lr: 4.0000e-04 eta: 1:52:47 time: 0.2768 data_time: 0.0073 memory: 5828 grad_norm: 5.5185 loss: 1.7419 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7419 2023/06/05 19:20:44 - mmengine - INFO - Epoch(train) [141][ 320/2569] lr: 4.0000e-04 eta: 1:52:41 time: 0.2802 data_time: 0.0070 memory: 5828 grad_norm: 5.4612 loss: 1.8765 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.8765 2023/06/05 19:20:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:20:50 - mmengine - INFO - Epoch(train) [141][ 340/2569] lr: 4.0000e-04 eta: 1:52:36 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 5.4241 loss: 1.5371 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5371 2023/06/05 19:20:55 - mmengine - INFO - Epoch(train) [141][ 360/2569] lr: 4.0000e-04 eta: 1:52:31 time: 0.2719 data_time: 0.0072 memory: 5828 grad_norm: 5.3574 loss: 1.4751 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4751 2023/06/05 19:21:01 - mmengine - INFO - Epoch(train) [141][ 380/2569] lr: 4.0000e-04 eta: 1:52:25 time: 0.2754 data_time: 0.0076 memory: 5828 grad_norm: 5.5087 loss: 1.4982 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4982 2023/06/05 19:21:06 - mmengine - INFO - Epoch(train) [141][ 400/2569] lr: 4.0000e-04 eta: 1:52:20 time: 0.2748 data_time: 0.0073 memory: 5828 grad_norm: 5.4205 loss: 1.6271 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.6271 2023/06/05 19:21:12 - mmengine - INFO - Epoch(train) [141][ 420/2569] lr: 4.0000e-04 eta: 1:52:15 time: 0.2730 data_time: 0.0071 memory: 5828 grad_norm: 5.4760 loss: 1.5492 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5492 2023/06/05 19:21:17 - mmengine - INFO - Epoch(train) [141][ 440/2569] lr: 4.0000e-04 eta: 1:52:09 time: 0.2807 data_time: 0.0070 memory: 5828 grad_norm: 5.4251 loss: 1.8436 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8436 2023/06/05 19:21:23 - mmengine - INFO - Epoch(train) [141][ 460/2569] lr: 4.0000e-04 eta: 1:52:04 time: 0.2670 data_time: 0.0072 memory: 5828 grad_norm: 5.5420 loss: 1.3735 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.3735 2023/06/05 19:21:28 - mmengine - INFO - Epoch(train) [141][ 480/2569] lr: 4.0000e-04 eta: 1:51:59 time: 0.2615 data_time: 0.0073 memory: 5828 grad_norm: 5.4796 loss: 1.8293 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8293 2023/06/05 19:21:33 - mmengine - INFO - Epoch(train) [141][ 500/2569] lr: 4.0000e-04 eta: 1:51:53 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 5.4237 loss: 1.7875 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7875 2023/06/05 19:21:39 - mmengine - INFO - Epoch(train) [141][ 520/2569] lr: 4.0000e-04 eta: 1:51:48 time: 0.2698 data_time: 0.0074 memory: 5828 grad_norm: 5.5112 loss: 1.9415 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9415 2023/06/05 19:21:44 - mmengine - INFO - Epoch(train) [141][ 540/2569] lr: 4.0000e-04 eta: 1:51:43 time: 0.2657 data_time: 0.0070 memory: 5828 grad_norm: 5.5514 loss: 1.8148 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8148 2023/06/05 19:21:49 - mmengine - INFO - Epoch(train) [141][ 560/2569] lr: 4.0000e-04 eta: 1:51:37 time: 0.2725 data_time: 0.0071 memory: 5828 grad_norm: 5.4815 loss: 1.6772 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6772 2023/06/05 19:21:55 - mmengine - INFO - Epoch(train) [141][ 580/2569] lr: 4.0000e-04 eta: 1:51:32 time: 0.2748 data_time: 0.0072 memory: 5828 grad_norm: 5.4662 loss: 1.8461 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8461 2023/06/05 19:22:00 - mmengine - INFO - Epoch(train) [141][ 600/2569] lr: 4.0000e-04 eta: 1:51:27 time: 0.2713 data_time: 0.0071 memory: 5828 grad_norm: 5.4572 loss: 1.9005 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9005 2023/06/05 19:22:06 - mmengine - INFO - Epoch(train) [141][ 620/2569] lr: 4.0000e-04 eta: 1:51:21 time: 0.2698 data_time: 0.0070 memory: 5828 grad_norm: 5.4844 loss: 1.5915 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5915 2023/06/05 19:22:11 - mmengine - INFO - Epoch(train) [141][ 640/2569] lr: 4.0000e-04 eta: 1:51:16 time: 0.2688 data_time: 0.0071 memory: 5828 grad_norm: 5.5559 loss: 1.8529 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8529 2023/06/05 19:22:17 - mmengine - INFO - Epoch(train) [141][ 660/2569] lr: 4.0000e-04 eta: 1:51:11 time: 0.2749 data_time: 0.0074 memory: 5828 grad_norm: 5.5729 loss: 1.5882 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5882 2023/06/05 19:22:22 - mmengine - INFO - Epoch(train) [141][ 680/2569] lr: 4.0000e-04 eta: 1:51:05 time: 0.2612 data_time: 0.0068 memory: 5828 grad_norm: 5.4396 loss: 1.5214 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5214 2023/06/05 19:22:27 - mmengine - INFO - Epoch(train) [141][ 700/2569] lr: 4.0000e-04 eta: 1:51:00 time: 0.2748 data_time: 0.0072 memory: 5828 grad_norm: 5.5296 loss: 1.7282 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7282 2023/06/05 19:22:33 - mmengine - INFO - Epoch(train) [141][ 720/2569] lr: 4.0000e-04 eta: 1:50:55 time: 0.2616 data_time: 0.0073 memory: 5828 grad_norm: 5.4324 loss: 1.7848 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7848 2023/06/05 19:22:38 - mmengine - INFO - Epoch(train) [141][ 740/2569] lr: 4.0000e-04 eta: 1:50:49 time: 0.2744 data_time: 0.0073 memory: 5828 grad_norm: 5.4577 loss: 1.5829 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5829 2023/06/05 19:22:44 - mmengine - INFO - Epoch(train) [141][ 760/2569] lr: 4.0000e-04 eta: 1:50:44 time: 0.2718 data_time: 0.0075 memory: 5828 grad_norm: 5.4544 loss: 1.6371 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.6371 2023/06/05 19:22:49 - mmengine - INFO - Epoch(train) [141][ 780/2569] lr: 4.0000e-04 eta: 1:50:39 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 5.4870 loss: 1.4988 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4988 2023/06/05 19:22:54 - mmengine - INFO - Epoch(train) [141][ 800/2569] lr: 4.0000e-04 eta: 1:50:33 time: 0.2673 data_time: 0.0076 memory: 5828 grad_norm: 5.4658 loss: 1.4166 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4166 2023/06/05 19:22:59 - mmengine - INFO - Epoch(train) [141][ 820/2569] lr: 4.0000e-04 eta: 1:50:28 time: 0.2667 data_time: 0.0070 memory: 5828 grad_norm: 5.5820 loss: 1.6063 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6063 2023/06/05 19:23:05 - mmengine - INFO - Epoch(train) [141][ 840/2569] lr: 4.0000e-04 eta: 1:50:23 time: 0.2677 data_time: 0.0081 memory: 5828 grad_norm: 5.5758 loss: 1.8610 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8610 2023/06/05 19:23:10 - mmengine - INFO - Epoch(train) [141][ 860/2569] lr: 4.0000e-04 eta: 1:50:17 time: 0.2670 data_time: 0.0071 memory: 5828 grad_norm: 5.5365 loss: 1.6332 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6332 2023/06/05 19:23:16 - mmengine - INFO - Epoch(train) [141][ 880/2569] lr: 4.0000e-04 eta: 1:50:12 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 5.5238 loss: 1.7534 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7534 2023/06/05 19:23:21 - mmengine - INFO - Epoch(train) [141][ 900/2569] lr: 4.0000e-04 eta: 1:50:07 time: 0.2656 data_time: 0.0072 memory: 5828 grad_norm: 5.3875 loss: 1.6114 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6114 2023/06/05 19:23:26 - mmengine - INFO - Epoch(train) [141][ 920/2569] lr: 4.0000e-04 eta: 1:50:01 time: 0.2650 data_time: 0.0073 memory: 5828 grad_norm: 5.5724 loss: 1.4621 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4621 2023/06/05 19:23:32 - mmengine - INFO - Epoch(train) [141][ 940/2569] lr: 4.0000e-04 eta: 1:49:56 time: 0.2679 data_time: 0.0071 memory: 5828 grad_norm: 5.5919 loss: 1.6083 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6083 2023/06/05 19:23:37 - mmengine - INFO - Epoch(train) [141][ 960/2569] lr: 4.0000e-04 eta: 1:49:51 time: 0.2604 data_time: 0.0073 memory: 5828 grad_norm: 5.5607 loss: 1.7236 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7236 2023/06/05 19:23:42 - mmengine - INFO - Epoch(train) [141][ 980/2569] lr: 4.0000e-04 eta: 1:49:46 time: 0.2729 data_time: 0.0074 memory: 5828 grad_norm: 5.4349 loss: 1.8000 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8000 2023/06/05 19:23:48 - mmengine - INFO - Epoch(train) [141][1000/2569] lr: 4.0000e-04 eta: 1:49:40 time: 0.2657 data_time: 0.0071 memory: 5828 grad_norm: 5.4653 loss: 1.4202 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4202 2023/06/05 19:23:53 - mmengine - INFO - Epoch(train) [141][1020/2569] lr: 4.0000e-04 eta: 1:49:35 time: 0.2738 data_time: 0.0075 memory: 5828 grad_norm: 5.5547 loss: 1.5813 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5813 2023/06/05 19:23:58 - mmengine - INFO - Epoch(train) [141][1040/2569] lr: 4.0000e-04 eta: 1:49:30 time: 0.2684 data_time: 0.0071 memory: 5828 grad_norm: 5.4884 loss: 1.6799 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6799 2023/06/05 19:24:04 - mmengine - INFO - Epoch(train) [141][1060/2569] lr: 4.0000e-04 eta: 1:49:24 time: 0.2681 data_time: 0.0070 memory: 5828 grad_norm: 5.5728 loss: 1.8762 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8762 2023/06/05 19:24:09 - mmengine - INFO - Epoch(train) [141][1080/2569] lr: 4.0000e-04 eta: 1:49:19 time: 0.2704 data_time: 0.0072 memory: 5828 grad_norm: 5.5459 loss: 1.8177 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8177 2023/06/05 19:24:15 - mmengine - INFO - Epoch(train) [141][1100/2569] lr: 4.0000e-04 eta: 1:49:14 time: 0.2742 data_time: 0.0072 memory: 5828 grad_norm: 5.5855 loss: 1.6851 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6851 2023/06/05 19:24:20 - mmengine - INFO - Epoch(train) [141][1120/2569] lr: 4.0000e-04 eta: 1:49:08 time: 0.2787 data_time: 0.0073 memory: 5828 grad_norm: 5.6300 loss: 1.7825 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7825 2023/06/05 19:24:26 - mmengine - INFO - Epoch(train) [141][1140/2569] lr: 4.0000e-04 eta: 1:49:03 time: 0.2710 data_time: 0.0071 memory: 5828 grad_norm: 5.5714 loss: 2.1388 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 2.1388 2023/06/05 19:24:31 - mmengine - INFO - Epoch(train) [141][1160/2569] lr: 4.0000e-04 eta: 1:48:58 time: 0.2681 data_time: 0.0076 memory: 5828 grad_norm: 5.5302 loss: 1.5364 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5364 2023/06/05 19:24:37 - mmengine - INFO - Epoch(train) [141][1180/2569] lr: 4.0000e-04 eta: 1:48:52 time: 0.2790 data_time: 0.0072 memory: 5828 grad_norm: 5.4841 loss: 1.7526 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7526 2023/06/05 19:24:42 - mmengine - INFO - Epoch(train) [141][1200/2569] lr: 4.0000e-04 eta: 1:48:47 time: 0.2702 data_time: 0.0071 memory: 5828 grad_norm: 5.5026 loss: 1.7236 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7236 2023/06/05 19:24:48 - mmengine - INFO - Epoch(train) [141][1220/2569] lr: 4.0000e-04 eta: 1:48:42 time: 0.2709 data_time: 0.0073 memory: 5828 grad_norm: 5.5684 loss: 1.5243 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5243 2023/06/05 19:24:53 - mmengine - INFO - Epoch(train) [141][1240/2569] lr: 4.0000e-04 eta: 1:48:36 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 5.7088 loss: 1.7277 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7277 2023/06/05 19:24:59 - mmengine - INFO - Epoch(train) [141][1260/2569] lr: 4.0000e-04 eta: 1:48:31 time: 0.2820 data_time: 0.0074 memory: 5828 grad_norm: 5.4480 loss: 1.6918 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6918 2023/06/05 19:25:04 - mmengine - INFO - Epoch(train) [141][1280/2569] lr: 4.0000e-04 eta: 1:48:26 time: 0.2651 data_time: 0.0070 memory: 5828 grad_norm: 5.4719 loss: 1.8979 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8979 2023/06/05 19:25:10 - mmengine - INFO - Epoch(train) [141][1300/2569] lr: 4.0000e-04 eta: 1:48:20 time: 0.2818 data_time: 0.0071 memory: 5828 grad_norm: 5.5413 loss: 1.5844 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5844 2023/06/05 19:25:15 - mmengine - INFO - Epoch(train) [141][1320/2569] lr: 4.0000e-04 eta: 1:48:15 time: 0.2741 data_time: 0.0072 memory: 5828 grad_norm: 5.5274 loss: 1.5760 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.5760 2023/06/05 19:25:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:25:21 - mmengine - INFO - Epoch(train) [141][1340/2569] lr: 4.0000e-04 eta: 1:48:10 time: 0.2729 data_time: 0.0072 memory: 5828 grad_norm: 5.6679 loss: 1.5946 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5946 2023/06/05 19:25:26 - mmengine - INFO - Epoch(train) [141][1360/2569] lr: 4.0000e-04 eta: 1:48:04 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 5.4790 loss: 1.5415 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5415 2023/06/05 19:25:31 - mmengine - INFO - Epoch(train) [141][1380/2569] lr: 4.0000e-04 eta: 1:47:59 time: 0.2706 data_time: 0.0070 memory: 5828 grad_norm: 5.5323 loss: 1.6497 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6497 2023/06/05 19:25:36 - mmengine - INFO - Epoch(train) [141][1400/2569] lr: 4.0000e-04 eta: 1:47:54 time: 0.2609 data_time: 0.0075 memory: 5828 grad_norm: 5.6220 loss: 1.6287 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6287 2023/06/05 19:25:42 - mmengine - INFO - Epoch(train) [141][1420/2569] lr: 4.0000e-04 eta: 1:47:48 time: 0.2792 data_time: 0.0070 memory: 5828 grad_norm: 5.4720 loss: 1.6558 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6558 2023/06/05 19:25:47 - mmengine - INFO - Epoch(train) [141][1440/2569] lr: 4.0000e-04 eta: 1:47:43 time: 0.2672 data_time: 0.0080 memory: 5828 grad_norm: 5.5221 loss: 1.3754 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3754 2023/06/05 19:25:53 - mmengine - INFO - Epoch(train) [141][1460/2569] lr: 4.0000e-04 eta: 1:47:38 time: 0.2670 data_time: 0.0072 memory: 5828 grad_norm: 5.6459 loss: 1.7614 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7614 2023/06/05 19:25:58 - mmengine - INFO - Epoch(train) [141][1480/2569] lr: 4.0000e-04 eta: 1:47:32 time: 0.2690 data_time: 0.0072 memory: 5828 grad_norm: 5.6801 loss: 1.8714 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8714 2023/06/05 19:26:03 - mmengine - INFO - Epoch(train) [141][1500/2569] lr: 4.0000e-04 eta: 1:47:27 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 5.5826 loss: 1.4229 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4229 2023/06/05 19:26:09 - mmengine - INFO - Epoch(train) [141][1520/2569] lr: 4.0000e-04 eta: 1:47:22 time: 0.2671 data_time: 0.0075 memory: 5828 grad_norm: 5.4399 loss: 1.7273 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7273 2023/06/05 19:26:15 - mmengine - INFO - Epoch(train) [141][1540/2569] lr: 4.0000e-04 eta: 1:47:16 time: 0.2859 data_time: 0.0071 memory: 5828 grad_norm: 5.5657 loss: 1.6918 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6918 2023/06/05 19:26:20 - mmengine - INFO - Epoch(train) [141][1560/2569] lr: 4.0000e-04 eta: 1:47:11 time: 0.2654 data_time: 0.0075 memory: 5828 grad_norm: 5.5075 loss: 1.5677 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.5677 2023/06/05 19:26:25 - mmengine - INFO - Epoch(train) [141][1580/2569] lr: 4.0000e-04 eta: 1:47:06 time: 0.2721 data_time: 0.0073 memory: 5828 grad_norm: 5.6056 loss: 1.9408 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9408 2023/06/05 19:26:31 - mmengine - INFO - Epoch(train) [141][1600/2569] lr: 4.0000e-04 eta: 1:47:00 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 5.5472 loss: 1.5827 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5827 2023/06/05 19:26:36 - mmengine - INFO - Epoch(train) [141][1620/2569] lr: 4.0000e-04 eta: 1:46:55 time: 0.2720 data_time: 0.0080 memory: 5828 grad_norm: 5.5726 loss: 1.7126 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7126 2023/06/05 19:26:41 - mmengine - INFO - Epoch(train) [141][1640/2569] lr: 4.0000e-04 eta: 1:46:50 time: 0.2616 data_time: 0.0077 memory: 5828 grad_norm: 5.6556 loss: 1.9767 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9767 2023/06/05 19:26:47 - mmengine - INFO - Epoch(train) [141][1660/2569] lr: 4.0000e-04 eta: 1:46:44 time: 0.2611 data_time: 0.0074 memory: 5828 grad_norm: 5.5751 loss: 1.8082 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8082 2023/06/05 19:26:52 - mmengine - INFO - Epoch(train) [141][1680/2569] lr: 4.0000e-04 eta: 1:46:39 time: 0.2731 data_time: 0.0073 memory: 5828 grad_norm: 5.5190 loss: 1.6788 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.6788 2023/06/05 19:26:57 - mmengine - INFO - Epoch(train) [141][1700/2569] lr: 4.0000e-04 eta: 1:46:34 time: 0.2720 data_time: 0.0069 memory: 5828 grad_norm: 5.5736 loss: 1.5608 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5608 2023/06/05 19:27:03 - mmengine - INFO - Epoch(train) [141][1720/2569] lr: 4.0000e-04 eta: 1:46:28 time: 0.2599 data_time: 0.0072 memory: 5828 grad_norm: 5.5435 loss: 1.5161 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5161 2023/06/05 19:27:08 - mmengine - INFO - Epoch(train) [141][1740/2569] lr: 4.0000e-04 eta: 1:46:23 time: 0.2626 data_time: 0.0073 memory: 5828 grad_norm: 5.6435 loss: 1.6690 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6690 2023/06/05 19:27:13 - mmengine - INFO - Epoch(train) [141][1760/2569] lr: 4.0000e-04 eta: 1:46:18 time: 0.2680 data_time: 0.0071 memory: 5828 grad_norm: 5.6332 loss: 1.5075 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5075 2023/06/05 19:27:19 - mmengine - INFO - Epoch(train) [141][1780/2569] lr: 4.0000e-04 eta: 1:46:12 time: 0.2750 data_time: 0.0073 memory: 5828 grad_norm: 5.4343 loss: 1.6805 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6805 2023/06/05 19:27:24 - mmengine - INFO - Epoch(train) [141][1800/2569] lr: 4.0000e-04 eta: 1:46:07 time: 0.2773 data_time: 0.0070 memory: 5828 grad_norm: 5.5724 loss: 1.6517 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6517 2023/06/05 19:27:30 - mmengine - INFO - Epoch(train) [141][1820/2569] lr: 4.0000e-04 eta: 1:46:02 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 5.4559 loss: 1.2576 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.2576 2023/06/05 19:27:35 - mmengine - INFO - Epoch(train) [141][1840/2569] lr: 4.0000e-04 eta: 1:45:56 time: 0.2684 data_time: 0.0071 memory: 5828 grad_norm: 5.5439 loss: 1.8586 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8586 2023/06/05 19:27:40 - mmengine - INFO - Epoch(train) [141][1860/2569] lr: 4.0000e-04 eta: 1:45:51 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 5.5421 loss: 1.6515 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6515 2023/06/05 19:27:46 - mmengine - INFO - Epoch(train) [141][1880/2569] lr: 4.0000e-04 eta: 1:45:46 time: 0.2670 data_time: 0.0072 memory: 5828 grad_norm: 5.5803 loss: 1.6860 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6860 2023/06/05 19:27:51 - mmengine - INFO - Epoch(train) [141][1900/2569] lr: 4.0000e-04 eta: 1:45:40 time: 0.2674 data_time: 0.0072 memory: 5828 grad_norm: 5.6576 loss: 1.6043 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6043 2023/06/05 19:27:56 - mmengine - INFO - Epoch(train) [141][1920/2569] lr: 4.0000e-04 eta: 1:45:35 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 5.5862 loss: 1.7613 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7613 2023/06/05 19:28:02 - mmengine - INFO - Epoch(train) [141][1940/2569] lr: 4.0000e-04 eta: 1:45:30 time: 0.2755 data_time: 0.0070 memory: 5828 grad_norm: 5.5476 loss: 1.5410 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5410 2023/06/05 19:28:07 - mmengine - INFO - Epoch(train) [141][1960/2569] lr: 4.0000e-04 eta: 1:45:25 time: 0.2659 data_time: 0.0072 memory: 5828 grad_norm: 5.5533 loss: 1.6366 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.6366 2023/06/05 19:28:13 - mmengine - INFO - Epoch(train) [141][1980/2569] lr: 4.0000e-04 eta: 1:45:19 time: 0.2660 data_time: 0.0072 memory: 5828 grad_norm: 5.4883 loss: 1.4330 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4330 2023/06/05 19:28:18 - mmengine - INFO - Epoch(train) [141][2000/2569] lr: 4.0000e-04 eta: 1:45:14 time: 0.2801 data_time: 0.0070 memory: 5828 grad_norm: 5.5210 loss: 1.7224 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7224 2023/06/05 19:28:24 - mmengine - INFO - Epoch(train) [141][2020/2569] lr: 4.0000e-04 eta: 1:45:09 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 5.6505 loss: 1.7422 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7422 2023/06/05 19:28:29 - mmengine - INFO - Epoch(train) [141][2040/2569] lr: 4.0000e-04 eta: 1:45:03 time: 0.2712 data_time: 0.0071 memory: 5828 grad_norm: 5.5341 loss: 1.6750 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6750 2023/06/05 19:28:34 - mmengine - INFO - Epoch(train) [141][2060/2569] lr: 4.0000e-04 eta: 1:44:58 time: 0.2624 data_time: 0.0084 memory: 5828 grad_norm: 5.5354 loss: 1.6282 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6282 2023/06/05 19:28:40 - mmengine - INFO - Epoch(train) [141][2080/2569] lr: 4.0000e-04 eta: 1:44:53 time: 0.2767 data_time: 0.0075 memory: 5828 grad_norm: 5.6776 loss: 1.3969 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.3969 2023/06/05 19:28:45 - mmengine - INFO - Epoch(train) [141][2100/2569] lr: 4.0000e-04 eta: 1:44:47 time: 0.2732 data_time: 0.0074 memory: 5828 grad_norm: 5.6689 loss: 1.4500 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4500 2023/06/05 19:28:51 - mmengine - INFO - Epoch(train) [141][2120/2569] lr: 4.0000e-04 eta: 1:44:42 time: 0.2735 data_time: 0.0070 memory: 5828 grad_norm: 5.4814 loss: 1.5691 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5691 2023/06/05 19:28:56 - mmengine - INFO - Epoch(train) [141][2140/2569] lr: 4.0000e-04 eta: 1:44:37 time: 0.2632 data_time: 0.0076 memory: 5828 grad_norm: 5.6989 loss: 1.7565 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7565 2023/06/05 19:29:01 - mmengine - INFO - Epoch(train) [141][2160/2569] lr: 4.0000e-04 eta: 1:44:31 time: 0.2678 data_time: 0.0075 memory: 5828 grad_norm: 5.5695 loss: 1.7283 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7283 2023/06/05 19:29:07 - mmengine - INFO - Epoch(train) [141][2180/2569] lr: 4.0000e-04 eta: 1:44:26 time: 0.2607 data_time: 0.0076 memory: 5828 grad_norm: 5.5043 loss: 1.6807 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6807 2023/06/05 19:29:12 - mmengine - INFO - Epoch(train) [141][2200/2569] lr: 4.0000e-04 eta: 1:44:21 time: 0.2684 data_time: 0.0076 memory: 5828 grad_norm: 5.6903 loss: 1.6077 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6077 2023/06/05 19:29:17 - mmengine - INFO - Epoch(train) [141][2220/2569] lr: 4.0000e-04 eta: 1:44:15 time: 0.2615 data_time: 0.0075 memory: 5828 grad_norm: 5.5830 loss: 1.4184 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4184 2023/06/05 19:29:23 - mmengine - INFO - Epoch(train) [141][2240/2569] lr: 4.0000e-04 eta: 1:44:10 time: 0.2751 data_time: 0.0072 memory: 5828 grad_norm: 5.5899 loss: 1.4972 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4972 2023/06/05 19:29:28 - mmengine - INFO - Epoch(train) [141][2260/2569] lr: 4.0000e-04 eta: 1:44:05 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 5.5351 loss: 1.6385 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6385 2023/06/05 19:29:33 - mmengine - INFO - Epoch(train) [141][2280/2569] lr: 4.0000e-04 eta: 1:43:59 time: 0.2668 data_time: 0.0075 memory: 5828 grad_norm: 5.5127 loss: 1.5636 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5636 2023/06/05 19:29:39 - mmengine - INFO - Epoch(train) [141][2300/2569] lr: 4.0000e-04 eta: 1:43:54 time: 0.2662 data_time: 0.0075 memory: 5828 grad_norm: 5.5852 loss: 1.8697 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8697 2023/06/05 19:29:44 - mmengine - INFO - Epoch(train) [141][2320/2569] lr: 4.0000e-04 eta: 1:43:49 time: 0.2726 data_time: 0.0081 memory: 5828 grad_norm: 5.5441 loss: 1.5281 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5281 2023/06/05 19:29:50 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:29:50 - mmengine - INFO - Epoch(train) [141][2340/2569] lr: 4.0000e-04 eta: 1:43:43 time: 0.2727 data_time: 0.0070 memory: 5828 grad_norm: 5.6146 loss: 1.3383 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3383 2023/06/05 19:29:55 - mmengine - INFO - Epoch(train) [141][2360/2569] lr: 4.0000e-04 eta: 1:43:38 time: 0.2679 data_time: 0.0076 memory: 5828 grad_norm: 5.7004 loss: 1.5521 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5521 2023/06/05 19:30:01 - mmengine - INFO - Epoch(train) [141][2380/2569] lr: 4.0000e-04 eta: 1:43:33 time: 0.2743 data_time: 0.0079 memory: 5828 grad_norm: 5.6407 loss: 1.5556 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5556 2023/06/05 19:30:06 - mmengine - INFO - Epoch(train) [141][2400/2569] lr: 4.0000e-04 eta: 1:43:27 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 5.5921 loss: 1.6024 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6024 2023/06/05 19:30:11 - mmengine - INFO - Epoch(train) [141][2420/2569] lr: 4.0000e-04 eta: 1:43:22 time: 0.2702 data_time: 0.0076 memory: 5828 grad_norm: 5.6627 loss: 1.4676 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.4676 2023/06/05 19:30:17 - mmengine - INFO - Epoch(train) [141][2440/2569] lr: 4.0000e-04 eta: 1:43:17 time: 0.2639 data_time: 0.0070 memory: 5828 grad_norm: 5.6707 loss: 1.4274 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4274 2023/06/05 19:30:22 - mmengine - INFO - Epoch(train) [141][2460/2569] lr: 4.0000e-04 eta: 1:43:11 time: 0.2681 data_time: 0.0074 memory: 5828 grad_norm: 5.5952 loss: 1.8919 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8919 2023/06/05 19:30:27 - mmengine - INFO - Epoch(train) [141][2480/2569] lr: 4.0000e-04 eta: 1:43:06 time: 0.2619 data_time: 0.0074 memory: 5828 grad_norm: 5.5475 loss: 1.5925 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5925 2023/06/05 19:30:33 - mmengine - INFO - Epoch(train) [141][2500/2569] lr: 4.0000e-04 eta: 1:43:01 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 5.6377 loss: 1.5494 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.5494 2023/06/05 19:30:38 - mmengine - INFO - Epoch(train) [141][2520/2569] lr: 4.0000e-04 eta: 1:42:55 time: 0.2674 data_time: 0.0071 memory: 5828 grad_norm: 5.6625 loss: 1.7085 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7085 2023/06/05 19:30:43 - mmengine - INFO - Epoch(train) [141][2540/2569] lr: 4.0000e-04 eta: 1:42:50 time: 0.2678 data_time: 0.0075 memory: 5828 grad_norm: 5.6819 loss: 1.5465 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5465 2023/06/05 19:30:49 - mmengine - INFO - Epoch(train) [141][2560/2569] lr: 4.0000e-04 eta: 1:42:45 time: 0.2612 data_time: 0.0073 memory: 5828 grad_norm: 5.6469 loss: 1.4433 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4433 2023/06/05 19:30:51 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:30:51 - mmengine - INFO - Epoch(train) [141][2569/2569] lr: 4.0000e-04 eta: 1:42:42 time: 0.2515 data_time: 0.0073 memory: 5828 grad_norm: 5.6237 loss: 1.6793 top1_acc: 0.1667 top5_acc: 0.8333 loss_cls: 1.6793 2023/06/05 19:30:58 - mmengine - INFO - Epoch(train) [142][ 20/2569] lr: 4.0000e-04 eta: 1:42:37 time: 0.3592 data_time: 0.0562 memory: 5828 grad_norm: 5.5904 loss: 1.5422 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5422 2023/06/05 19:31:03 - mmengine - INFO - Epoch(train) [142][ 40/2569] lr: 4.0000e-04 eta: 1:42:32 time: 0.2686 data_time: 0.0076 memory: 5828 grad_norm: 5.6503 loss: 1.5705 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5705 2023/06/05 19:31:09 - mmengine - INFO - Epoch(train) [142][ 60/2569] lr: 4.0000e-04 eta: 1:42:26 time: 0.2784 data_time: 0.0074 memory: 5828 grad_norm: 5.5116 loss: 1.2379 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2379 2023/06/05 19:31:14 - mmengine - INFO - Epoch(train) [142][ 80/2569] lr: 4.0000e-04 eta: 1:42:21 time: 0.2691 data_time: 0.0083 memory: 5828 grad_norm: 5.6513 loss: 1.7675 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7675 2023/06/05 19:31:20 - mmengine - INFO - Epoch(train) [142][ 100/2569] lr: 4.0000e-04 eta: 1:42:16 time: 0.2667 data_time: 0.0074 memory: 5828 grad_norm: 5.5429 loss: 1.2994 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2994 2023/06/05 19:31:25 - mmengine - INFO - Epoch(train) [142][ 120/2569] lr: 4.0000e-04 eta: 1:42:10 time: 0.2679 data_time: 0.0075 memory: 5828 grad_norm: 5.5519 loss: 1.8608 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8608 2023/06/05 19:31:30 - mmengine - INFO - Epoch(train) [142][ 140/2569] lr: 4.0000e-04 eta: 1:42:05 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 5.5550 loss: 1.6326 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6326 2023/06/05 19:31:36 - mmengine - INFO - Epoch(train) [142][ 160/2569] lr: 4.0000e-04 eta: 1:42:00 time: 0.2632 data_time: 0.0074 memory: 5828 grad_norm: 5.4586 loss: 1.6018 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6018 2023/06/05 19:31:41 - mmengine - INFO - Epoch(train) [142][ 180/2569] lr: 4.0000e-04 eta: 1:41:54 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 5.7060 loss: 1.4862 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4862 2023/06/05 19:31:46 - mmengine - INFO - Epoch(train) [142][ 200/2569] lr: 4.0000e-04 eta: 1:41:49 time: 0.2643 data_time: 0.0074 memory: 5828 grad_norm: 5.6454 loss: 1.3141 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.3141 2023/06/05 19:31:52 - mmengine - INFO - Epoch(train) [142][ 220/2569] lr: 4.0000e-04 eta: 1:41:44 time: 0.2667 data_time: 0.0071 memory: 5828 grad_norm: 5.5427 loss: 1.4229 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.4229 2023/06/05 19:31:57 - mmengine - INFO - Epoch(train) [142][ 240/2569] lr: 4.0000e-04 eta: 1:41:38 time: 0.2636 data_time: 0.0073 memory: 5828 grad_norm: 5.6329 loss: 1.8400 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8400 2023/06/05 19:32:02 - mmengine - INFO - Epoch(train) [142][ 260/2569] lr: 4.0000e-04 eta: 1:41:33 time: 0.2753 data_time: 0.0073 memory: 5828 grad_norm: 5.5910 loss: 1.5546 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5546 2023/06/05 19:32:08 - mmengine - INFO - Epoch(train) [142][ 280/2569] lr: 4.0000e-04 eta: 1:41:28 time: 0.2624 data_time: 0.0078 memory: 5828 grad_norm: 5.6591 loss: 1.4286 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4286 2023/06/05 19:32:13 - mmengine - INFO - Epoch(train) [142][ 300/2569] lr: 4.0000e-04 eta: 1:41:22 time: 0.2754 data_time: 0.0072 memory: 5828 grad_norm: 5.6023 loss: 1.5822 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5822 2023/06/05 19:32:19 - mmengine - INFO - Epoch(train) [142][ 320/2569] lr: 4.0000e-04 eta: 1:41:17 time: 0.2662 data_time: 0.0079 memory: 5828 grad_norm: 5.5478 loss: 1.6448 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6448 2023/06/05 19:32:24 - mmengine - INFO - Epoch(train) [142][ 340/2569] lr: 4.0000e-04 eta: 1:41:12 time: 0.2740 data_time: 0.0076 memory: 5828 grad_norm: 5.6731 loss: 1.5276 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5276 2023/06/05 19:32:29 - mmengine - INFO - Epoch(train) [142][ 360/2569] lr: 4.0000e-04 eta: 1:41:06 time: 0.2651 data_time: 0.0078 memory: 5828 grad_norm: 5.5632 loss: 1.6659 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6659 2023/06/05 19:32:35 - mmengine - INFO - Epoch(train) [142][ 380/2569] lr: 4.0000e-04 eta: 1:41:01 time: 0.2783 data_time: 0.0078 memory: 5828 grad_norm: 5.7343 loss: 1.7254 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7254 2023/06/05 19:32:40 - mmengine - INFO - Epoch(train) [142][ 400/2569] lr: 4.0000e-04 eta: 1:40:56 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 5.5930 loss: 1.3544 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3544 2023/06/05 19:32:46 - mmengine - INFO - Epoch(train) [142][ 420/2569] lr: 4.0000e-04 eta: 1:40:50 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 5.4152 loss: 1.4181 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4181 2023/06/05 19:32:51 - mmengine - INFO - Epoch(train) [142][ 440/2569] lr: 4.0000e-04 eta: 1:40:45 time: 0.2646 data_time: 0.0070 memory: 5828 grad_norm: 5.6130 loss: 1.6852 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6852 2023/06/05 19:32:56 - mmengine - INFO - Epoch(train) [142][ 460/2569] lr: 4.0000e-04 eta: 1:40:40 time: 0.2684 data_time: 0.0070 memory: 5828 grad_norm: 5.5838 loss: 1.3356 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3356 2023/06/05 19:33:02 - mmengine - INFO - Epoch(train) [142][ 480/2569] lr: 4.0000e-04 eta: 1:40:34 time: 0.2684 data_time: 0.0075 memory: 5828 grad_norm: 5.5238 loss: 1.5202 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.5202 2023/06/05 19:33:07 - mmengine - INFO - Epoch(train) [142][ 500/2569] lr: 4.0000e-04 eta: 1:40:29 time: 0.2715 data_time: 0.0072 memory: 5828 grad_norm: 5.6925 loss: 1.6682 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6682 2023/06/05 19:33:12 - mmengine - INFO - Epoch(train) [142][ 520/2569] lr: 4.0000e-04 eta: 1:40:24 time: 0.2626 data_time: 0.0073 memory: 5828 grad_norm: 5.5649 loss: 1.5850 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5850 2023/06/05 19:33:18 - mmengine - INFO - Epoch(train) [142][ 540/2569] lr: 4.0000e-04 eta: 1:40:18 time: 0.2723 data_time: 0.0074 memory: 5828 grad_norm: 5.5425 loss: 1.5479 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5479 2023/06/05 19:33:23 - mmengine - INFO - Epoch(train) [142][ 560/2569] lr: 4.0000e-04 eta: 1:40:13 time: 0.2616 data_time: 0.0071 memory: 5828 grad_norm: 5.6706 loss: 1.7723 top1_acc: 0.1250 top5_acc: 0.3750 loss_cls: 1.7723 2023/06/05 19:33:28 - mmengine - INFO - Epoch(train) [142][ 580/2569] lr: 4.0000e-04 eta: 1:40:08 time: 0.2650 data_time: 0.0074 memory: 5828 grad_norm: 5.4906 loss: 1.4782 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4782 2023/06/05 19:33:34 - mmengine - INFO - Epoch(train) [142][ 600/2569] lr: 4.0000e-04 eta: 1:40:02 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 5.5291 loss: 1.5334 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5334 2023/06/05 19:33:39 - mmengine - INFO - Epoch(train) [142][ 620/2569] lr: 4.0000e-04 eta: 1:39:57 time: 0.2830 data_time: 0.0076 memory: 5828 grad_norm: 5.7547 loss: 1.5679 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5679 2023/06/05 19:33:45 - mmengine - INFO - Epoch(train) [142][ 640/2569] lr: 4.0000e-04 eta: 1:39:52 time: 0.2665 data_time: 0.0081 memory: 5828 grad_norm: 5.6801 loss: 1.5761 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5761 2023/06/05 19:33:50 - mmengine - INFO - Epoch(train) [142][ 660/2569] lr: 4.0000e-04 eta: 1:39:47 time: 0.2774 data_time: 0.0073 memory: 5828 grad_norm: 5.5943 loss: 1.6586 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6586 2023/06/05 19:33:55 - mmengine - INFO - Epoch(train) [142][ 680/2569] lr: 4.0000e-04 eta: 1:39:41 time: 0.2634 data_time: 0.0079 memory: 5828 grad_norm: 5.6051 loss: 1.3834 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.3834 2023/06/05 19:34:01 - mmengine - INFO - Epoch(train) [142][ 700/2569] lr: 4.0000e-04 eta: 1:39:36 time: 0.2605 data_time: 0.0079 memory: 5828 grad_norm: 5.6469 loss: 1.6212 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6212 2023/06/05 19:34:06 - mmengine - INFO - Epoch(train) [142][ 720/2569] lr: 4.0000e-04 eta: 1:39:31 time: 0.2713 data_time: 0.0071 memory: 5828 grad_norm: 5.6321 loss: 1.9992 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9992 2023/06/05 19:34:11 - mmengine - INFO - Epoch(train) [142][ 740/2569] lr: 4.0000e-04 eta: 1:39:25 time: 0.2643 data_time: 0.0073 memory: 5828 grad_norm: 5.5959 loss: 1.6106 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6106 2023/06/05 19:34:17 - mmengine - INFO - Epoch(train) [142][ 760/2569] lr: 4.0000e-04 eta: 1:39:20 time: 0.2705 data_time: 0.0072 memory: 5828 grad_norm: 5.5592 loss: 1.6026 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6026 2023/06/05 19:34:20 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:34:22 - mmengine - INFO - Epoch(train) [142][ 780/2569] lr: 4.0000e-04 eta: 1:39:15 time: 0.2637 data_time: 0.0072 memory: 5828 grad_norm: 5.6553 loss: 1.3422 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3422 2023/06/05 19:34:27 - mmengine - INFO - Epoch(train) [142][ 800/2569] lr: 4.0000e-04 eta: 1:39:09 time: 0.2665 data_time: 0.0072 memory: 5828 grad_norm: 5.6488 loss: 1.6714 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6714 2023/06/05 19:34:33 - mmengine - INFO - Epoch(train) [142][ 820/2569] lr: 4.0000e-04 eta: 1:39:04 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 5.5824 loss: 1.7715 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7715 2023/06/05 19:34:38 - mmengine - INFO - Epoch(train) [142][ 840/2569] lr: 4.0000e-04 eta: 1:38:59 time: 0.2634 data_time: 0.0070 memory: 5828 grad_norm: 5.5195 loss: 1.6222 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6222 2023/06/05 19:34:43 - mmengine - INFO - Epoch(train) [142][ 860/2569] lr: 4.0000e-04 eta: 1:38:53 time: 0.2697 data_time: 0.0077 memory: 5828 grad_norm: 5.7147 loss: 1.4529 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4529 2023/06/05 19:34:49 - mmengine - INFO - Epoch(train) [142][ 880/2569] lr: 4.0000e-04 eta: 1:38:48 time: 0.2626 data_time: 0.0071 memory: 5828 grad_norm: 5.6287 loss: 1.8648 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8648 2023/06/05 19:34:54 - mmengine - INFO - Epoch(train) [142][ 900/2569] lr: 4.0000e-04 eta: 1:38:43 time: 0.2679 data_time: 0.0070 memory: 5828 grad_norm: 5.6670 loss: 1.5919 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5919 2023/06/05 19:35:00 - mmengine - INFO - Epoch(train) [142][ 920/2569] lr: 4.0000e-04 eta: 1:38:37 time: 0.2756 data_time: 0.0071 memory: 5828 grad_norm: 5.6343 loss: 1.6729 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.6729 2023/06/05 19:35:05 - mmengine - INFO - Epoch(train) [142][ 940/2569] lr: 4.0000e-04 eta: 1:38:32 time: 0.2744 data_time: 0.0073 memory: 5828 grad_norm: 5.6274 loss: 1.7565 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.7565 2023/06/05 19:35:11 - mmengine - INFO - Epoch(train) [142][ 960/2569] lr: 4.0000e-04 eta: 1:38:27 time: 0.2791 data_time: 0.0077 memory: 5828 grad_norm: 5.5583 loss: 1.4432 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4432 2023/06/05 19:35:16 - mmengine - INFO - Epoch(train) [142][ 980/2569] lr: 4.0000e-04 eta: 1:38:21 time: 0.2650 data_time: 0.0073 memory: 5828 grad_norm: 5.6357 loss: 1.4486 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4486 2023/06/05 19:35:21 - mmengine - INFO - Epoch(train) [142][1000/2569] lr: 4.0000e-04 eta: 1:38:16 time: 0.2635 data_time: 0.0071 memory: 5828 grad_norm: 5.5692 loss: 1.4823 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4823 2023/06/05 19:35:27 - mmengine - INFO - Epoch(train) [142][1020/2569] lr: 4.0000e-04 eta: 1:38:11 time: 0.2685 data_time: 0.0069 memory: 5828 grad_norm: 5.6417 loss: 1.4814 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4814 2023/06/05 19:35:32 - mmengine - INFO - Epoch(train) [142][1040/2569] lr: 4.0000e-04 eta: 1:38:05 time: 0.2685 data_time: 0.0074 memory: 5828 grad_norm: 5.5861 loss: 1.4456 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4456 2023/06/05 19:35:37 - mmengine - INFO - Epoch(train) [142][1060/2569] lr: 4.0000e-04 eta: 1:38:00 time: 0.2691 data_time: 0.0076 memory: 5828 grad_norm: 5.6532 loss: 1.6768 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6768 2023/06/05 19:35:43 - mmengine - INFO - Epoch(train) [142][1080/2569] lr: 4.0000e-04 eta: 1:37:55 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 5.6326 loss: 1.6640 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6640 2023/06/05 19:35:48 - mmengine - INFO - Epoch(train) [142][1100/2569] lr: 4.0000e-04 eta: 1:37:49 time: 0.2661 data_time: 0.0072 memory: 5828 grad_norm: 5.5776 loss: 1.7443 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7443 2023/06/05 19:35:54 - mmengine - INFO - Epoch(train) [142][1120/2569] lr: 4.0000e-04 eta: 1:37:44 time: 0.2720 data_time: 0.0074 memory: 5828 grad_norm: 5.5877 loss: 1.6954 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6954 2023/06/05 19:35:59 - mmengine - INFO - Epoch(train) [142][1140/2569] lr: 4.0000e-04 eta: 1:37:39 time: 0.2697 data_time: 0.0072 memory: 5828 grad_norm: 5.5271 loss: 1.6714 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6714 2023/06/05 19:36:04 - mmengine - INFO - Epoch(train) [142][1160/2569] lr: 4.0000e-04 eta: 1:37:33 time: 0.2727 data_time: 0.0078 memory: 5828 grad_norm: 5.6822 loss: 1.5254 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5254 2023/06/05 19:36:10 - mmengine - INFO - Epoch(train) [142][1180/2569] lr: 4.0000e-04 eta: 1:37:28 time: 0.2670 data_time: 0.0075 memory: 5828 grad_norm: 5.7289 loss: 1.6153 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6153 2023/06/05 19:36:15 - mmengine - INFO - Epoch(train) [142][1200/2569] lr: 4.0000e-04 eta: 1:37:23 time: 0.2689 data_time: 0.0076 memory: 5828 grad_norm: 5.6230 loss: 1.5165 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5165 2023/06/05 19:36:21 - mmengine - INFO - Epoch(train) [142][1220/2569] lr: 4.0000e-04 eta: 1:37:17 time: 0.2674 data_time: 0.0074 memory: 5828 grad_norm: 5.5846 loss: 1.6345 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6345 2023/06/05 19:36:26 - mmengine - INFO - Epoch(train) [142][1240/2569] lr: 4.0000e-04 eta: 1:37:12 time: 0.2684 data_time: 0.0079 memory: 5828 grad_norm: 5.7447 loss: 1.8680 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8680 2023/06/05 19:36:31 - mmengine - INFO - Epoch(train) [142][1260/2569] lr: 4.0000e-04 eta: 1:37:07 time: 0.2657 data_time: 0.0077 memory: 5828 grad_norm: 5.7393 loss: 1.4389 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4389 2023/06/05 19:36:36 - mmengine - INFO - Epoch(train) [142][1280/2569] lr: 4.0000e-04 eta: 1:37:01 time: 0.2630 data_time: 0.0071 memory: 5828 grad_norm: 5.7018 loss: 1.8079 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8079 2023/06/05 19:36:42 - mmengine - INFO - Epoch(train) [142][1300/2569] lr: 4.0000e-04 eta: 1:36:56 time: 0.2671 data_time: 0.0075 memory: 5828 grad_norm: 5.6502 loss: 1.4907 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4907 2023/06/05 19:36:47 - mmengine - INFO - Epoch(train) [142][1320/2569] lr: 4.0000e-04 eta: 1:36:51 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 5.6793 loss: 1.4939 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4939 2023/06/05 19:36:53 - mmengine - INFO - Epoch(train) [142][1340/2569] lr: 4.0000e-04 eta: 1:36:45 time: 0.2706 data_time: 0.0075 memory: 5828 grad_norm: 5.6497 loss: 1.8276 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8276 2023/06/05 19:36:58 - mmengine - INFO - Epoch(train) [142][1360/2569] lr: 4.0000e-04 eta: 1:36:40 time: 0.2610 data_time: 0.0072 memory: 5828 grad_norm: 5.6635 loss: 1.5912 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5912 2023/06/05 19:37:03 - mmengine - INFO - Epoch(train) [142][1380/2569] lr: 4.0000e-04 eta: 1:36:35 time: 0.2731 data_time: 0.0073 memory: 5828 grad_norm: 5.7856 loss: 1.4393 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4393 2023/06/05 19:37:09 - mmengine - INFO - Epoch(train) [142][1400/2569] lr: 4.0000e-04 eta: 1:36:29 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 5.6680 loss: 1.6815 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6815 2023/06/05 19:37:14 - mmengine - INFO - Epoch(train) [142][1420/2569] lr: 4.0000e-04 eta: 1:36:24 time: 0.2777 data_time: 0.0075 memory: 5828 grad_norm: 5.7457 loss: 1.4571 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4571 2023/06/05 19:37:19 - mmengine - INFO - Epoch(train) [142][1440/2569] lr: 4.0000e-04 eta: 1:36:19 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 5.7304 loss: 1.5138 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5138 2023/06/05 19:37:25 - mmengine - INFO - Epoch(train) [142][1460/2569] lr: 4.0000e-04 eta: 1:36:13 time: 0.2781 data_time: 0.0078 memory: 5828 grad_norm: 5.5831 loss: 1.3230 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3230 2023/06/05 19:37:30 - mmengine - INFO - Epoch(train) [142][1480/2569] lr: 4.0000e-04 eta: 1:36:08 time: 0.2633 data_time: 0.0072 memory: 5828 grad_norm: 5.7424 loss: 1.4331 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.4331 2023/06/05 19:37:35 - mmengine - INFO - Epoch(train) [142][1500/2569] lr: 4.0000e-04 eta: 1:36:03 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 5.7074 loss: 1.4063 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4063 2023/06/05 19:37:41 - mmengine - INFO - Epoch(train) [142][1520/2569] lr: 4.0000e-04 eta: 1:35:57 time: 0.2702 data_time: 0.0075 memory: 5828 grad_norm: 5.5903 loss: 1.5422 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5422 2023/06/05 19:37:46 - mmengine - INFO - Epoch(train) [142][1540/2569] lr: 4.0000e-04 eta: 1:35:52 time: 0.2694 data_time: 0.0072 memory: 5828 grad_norm: 5.6690 loss: 1.6663 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6663 2023/06/05 19:37:52 - mmengine - INFO - Epoch(train) [142][1560/2569] lr: 4.0000e-04 eta: 1:35:47 time: 0.2718 data_time: 0.0074 memory: 5828 grad_norm: 5.6581 loss: 1.7549 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7549 2023/06/05 19:37:57 - mmengine - INFO - Epoch(train) [142][1580/2569] lr: 4.0000e-04 eta: 1:35:41 time: 0.2739 data_time: 0.0072 memory: 5828 grad_norm: 5.6343 loss: 1.9003 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9003 2023/06/05 19:38:02 - mmengine - INFO - Epoch(train) [142][1600/2569] lr: 4.0000e-04 eta: 1:35:36 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 5.7168 loss: 1.5082 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5082 2023/06/05 19:38:08 - mmengine - INFO - Epoch(train) [142][1620/2569] lr: 4.0000e-04 eta: 1:35:31 time: 0.2723 data_time: 0.0076 memory: 5828 grad_norm: 5.5706 loss: 1.6410 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6410 2023/06/05 19:38:13 - mmengine - INFO - Epoch(train) [142][1640/2569] lr: 4.0000e-04 eta: 1:35:25 time: 0.2655 data_time: 0.0073 memory: 5828 grad_norm: 5.6922 loss: 1.7366 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7366 2023/06/05 19:38:19 - mmengine - INFO - Epoch(train) [142][1660/2569] lr: 4.0000e-04 eta: 1:35:20 time: 0.2702 data_time: 0.0076 memory: 5828 grad_norm: 5.6390 loss: 1.4255 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4255 2023/06/05 19:38:24 - mmengine - INFO - Epoch(train) [142][1680/2569] lr: 4.0000e-04 eta: 1:35:15 time: 0.2608 data_time: 0.0076 memory: 5828 grad_norm: 5.6760 loss: 1.5687 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5687 2023/06/05 19:38:29 - mmengine - INFO - Epoch(train) [142][1700/2569] lr: 4.0000e-04 eta: 1:35:09 time: 0.2748 data_time: 0.0072 memory: 5828 grad_norm: 5.5106 loss: 1.3336 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3336 2023/06/05 19:38:35 - mmengine - INFO - Epoch(train) [142][1720/2569] lr: 4.0000e-04 eta: 1:35:04 time: 0.2654 data_time: 0.0073 memory: 5828 grad_norm: 5.6198 loss: 1.8825 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.8825 2023/06/05 19:38:40 - mmengine - INFO - Epoch(train) [142][1740/2569] lr: 4.0000e-04 eta: 1:34:59 time: 0.2637 data_time: 0.0072 memory: 5828 grad_norm: 5.6184 loss: 1.8596 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8596 2023/06/05 19:38:45 - mmengine - INFO - Epoch(train) [142][1760/2569] lr: 4.0000e-04 eta: 1:34:53 time: 0.2662 data_time: 0.0069 memory: 5828 grad_norm: 5.6650 loss: 1.4060 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4060 2023/06/05 19:38:48 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:38:51 - mmengine - INFO - Epoch(train) [142][1780/2569] lr: 4.0000e-04 eta: 1:34:48 time: 0.2653 data_time: 0.0075 memory: 5828 grad_norm: 5.6729 loss: 1.5611 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5611 2023/06/05 19:38:56 - mmengine - INFO - Epoch(train) [142][1800/2569] lr: 4.0000e-04 eta: 1:34:43 time: 0.2740 data_time: 0.0069 memory: 5828 grad_norm: 5.5891 loss: 1.7326 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7326 2023/06/05 19:39:01 - mmengine - INFO - Epoch(train) [142][1820/2569] lr: 4.0000e-04 eta: 1:34:37 time: 0.2615 data_time: 0.0077 memory: 5828 grad_norm: 5.6379 loss: 1.5218 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5218 2023/06/05 19:39:07 - mmengine - INFO - Epoch(train) [142][1840/2569] lr: 4.0000e-04 eta: 1:34:32 time: 0.2624 data_time: 0.0069 memory: 5828 grad_norm: 5.6657 loss: 1.5536 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5536 2023/06/05 19:39:12 - mmengine - INFO - Epoch(train) [142][1860/2569] lr: 4.0000e-04 eta: 1:34:27 time: 0.2671 data_time: 0.0071 memory: 5828 grad_norm: 5.6137 loss: 1.6290 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6290 2023/06/05 19:39:17 - mmengine - INFO - Epoch(train) [142][1880/2569] lr: 4.0000e-04 eta: 1:34:21 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 5.6847 loss: 1.8791 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8791 2023/06/05 19:39:23 - mmengine - INFO - Epoch(train) [142][1900/2569] lr: 4.0000e-04 eta: 1:34:16 time: 0.2682 data_time: 0.0075 memory: 5828 grad_norm: 5.6366 loss: 1.4119 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4119 2023/06/05 19:39:28 - mmengine - INFO - Epoch(train) [142][1920/2569] lr: 4.0000e-04 eta: 1:34:11 time: 0.2661 data_time: 0.0082 memory: 5828 grad_norm: 5.6409 loss: 1.4899 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4899 2023/06/05 19:39:33 - mmengine - INFO - Epoch(train) [142][1940/2569] lr: 4.0000e-04 eta: 1:34:05 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 5.5729 loss: 1.6677 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6677 2023/06/05 19:39:39 - mmengine - INFO - Epoch(train) [142][1960/2569] lr: 4.0000e-04 eta: 1:34:00 time: 0.2734 data_time: 0.0075 memory: 5828 grad_norm: 5.6669 loss: 1.5371 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5371 2023/06/05 19:39:44 - mmengine - INFO - Epoch(train) [142][1980/2569] lr: 4.0000e-04 eta: 1:33:55 time: 0.2689 data_time: 0.0077 memory: 5828 grad_norm: 5.6148 loss: 1.7248 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.7248 2023/06/05 19:39:50 - mmengine - INFO - Epoch(train) [142][2000/2569] lr: 4.0000e-04 eta: 1:33:49 time: 0.2684 data_time: 0.0076 memory: 5828 grad_norm: 5.6294 loss: 1.7846 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.7846 2023/06/05 19:39:55 - mmengine - INFO - Epoch(train) [142][2020/2569] lr: 4.0000e-04 eta: 1:33:44 time: 0.2665 data_time: 0.0079 memory: 5828 grad_norm: 5.5792 loss: 1.6377 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6377 2023/06/05 19:40:00 - mmengine - INFO - Epoch(train) [142][2040/2569] lr: 4.0000e-04 eta: 1:33:39 time: 0.2634 data_time: 0.0077 memory: 5828 grad_norm: 5.6640 loss: 1.4644 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4644 2023/06/05 19:40:06 - mmengine - INFO - Epoch(train) [142][2060/2569] lr: 4.0000e-04 eta: 1:33:33 time: 0.2782 data_time: 0.0082 memory: 5828 grad_norm: 5.6229 loss: 1.5936 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5936 2023/06/05 19:40:11 - mmengine - INFO - Epoch(train) [142][2080/2569] lr: 4.0000e-04 eta: 1:33:28 time: 0.2703 data_time: 0.0073 memory: 5828 grad_norm: 5.6396 loss: 1.4813 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4813 2023/06/05 19:40:17 - mmengine - INFO - Epoch(train) [142][2100/2569] lr: 4.0000e-04 eta: 1:33:23 time: 0.2739 data_time: 0.0075 memory: 5828 grad_norm: 5.6793 loss: 1.7658 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7658 2023/06/05 19:40:22 - mmengine - INFO - Epoch(train) [142][2120/2569] lr: 4.0000e-04 eta: 1:33:17 time: 0.2703 data_time: 0.0077 memory: 5828 grad_norm: 5.7042 loss: 1.5584 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.5584 2023/06/05 19:40:28 - mmengine - INFO - Epoch(train) [142][2140/2569] lr: 4.0000e-04 eta: 1:33:12 time: 0.2674 data_time: 0.0074 memory: 5828 grad_norm: 5.6487 loss: 1.5290 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5290 2023/06/05 19:40:33 - mmengine - INFO - Epoch(train) [142][2160/2569] lr: 4.0000e-04 eta: 1:33:07 time: 0.2634 data_time: 0.0077 memory: 5828 grad_norm: 5.6280 loss: 1.5372 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5372 2023/06/05 19:40:38 - mmengine - INFO - Epoch(train) [142][2180/2569] lr: 4.0000e-04 eta: 1:33:01 time: 0.2654 data_time: 0.0077 memory: 5828 grad_norm: 5.7083 loss: 1.6204 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6204 2023/06/05 19:40:44 - mmengine - INFO - Epoch(train) [142][2200/2569] lr: 4.0000e-04 eta: 1:32:56 time: 0.2700 data_time: 0.0072 memory: 5828 grad_norm: 5.6923 loss: 1.6991 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6991 2023/06/05 19:40:49 - mmengine - INFO - Epoch(train) [142][2220/2569] lr: 4.0000e-04 eta: 1:32:51 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 5.7016 loss: 1.5399 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5399 2023/06/05 19:40:54 - mmengine - INFO - Epoch(train) [142][2240/2569] lr: 4.0000e-04 eta: 1:32:45 time: 0.2749 data_time: 0.0073 memory: 5828 grad_norm: 5.6554 loss: 1.3275 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3275 2023/06/05 19:41:00 - mmengine - INFO - Epoch(train) [142][2260/2569] lr: 4.0000e-04 eta: 1:32:40 time: 0.2634 data_time: 0.0084 memory: 5828 grad_norm: 5.6447 loss: 1.6427 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6427 2023/06/05 19:41:05 - mmengine - INFO - Epoch(train) [142][2280/2569] lr: 4.0000e-04 eta: 1:32:35 time: 0.2777 data_time: 0.0075 memory: 5828 grad_norm: 5.7331 loss: 1.6956 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6956 2023/06/05 19:41:11 - mmengine - INFO - Epoch(train) [142][2300/2569] lr: 4.0000e-04 eta: 1:32:29 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 5.7245 loss: 1.6761 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6761 2023/06/05 19:41:16 - mmengine - INFO - Epoch(train) [142][2320/2569] lr: 4.0000e-04 eta: 1:32:24 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 5.5989 loss: 1.3928 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.3928 2023/06/05 19:41:21 - mmengine - INFO - Epoch(train) [142][2340/2569] lr: 4.0000e-04 eta: 1:32:19 time: 0.2742 data_time: 0.0069 memory: 5828 grad_norm: 5.6548 loss: 1.3464 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3464 2023/06/05 19:41:27 - mmengine - INFO - Epoch(train) [142][2360/2569] lr: 4.0000e-04 eta: 1:32:14 time: 0.2672 data_time: 0.0072 memory: 5828 grad_norm: 5.7317 loss: 1.8694 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8694 2023/06/05 19:41:32 - mmengine - INFO - Epoch(train) [142][2380/2569] lr: 4.0000e-04 eta: 1:32:08 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 5.7652 loss: 1.8009 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8009 2023/06/05 19:41:37 - mmengine - INFO - Epoch(train) [142][2400/2569] lr: 4.0000e-04 eta: 1:32:03 time: 0.2678 data_time: 0.0071 memory: 5828 grad_norm: 5.6053 loss: 1.5132 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5132 2023/06/05 19:41:43 - mmengine - INFO - Epoch(train) [142][2420/2569] lr: 4.0000e-04 eta: 1:31:58 time: 0.2676 data_time: 0.0072 memory: 5828 grad_norm: 5.6289 loss: 1.8556 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8556 2023/06/05 19:41:48 - mmengine - INFO - Epoch(train) [142][2440/2569] lr: 4.0000e-04 eta: 1:31:52 time: 0.2682 data_time: 0.0072 memory: 5828 grad_norm: 5.7841 loss: 1.7198 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7198 2023/06/05 19:41:54 - mmengine - INFO - Epoch(train) [142][2460/2569] lr: 4.0000e-04 eta: 1:31:47 time: 0.2675 data_time: 0.0075 memory: 5828 grad_norm: 5.6717 loss: 1.5264 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5264 2023/06/05 19:41:59 - mmengine - INFO - Epoch(train) [142][2480/2569] lr: 4.0000e-04 eta: 1:31:42 time: 0.2732 data_time: 0.0071 memory: 5828 grad_norm: 5.6429 loss: 1.8333 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8333 2023/06/05 19:42:04 - mmengine - INFO - Epoch(train) [142][2500/2569] lr: 4.0000e-04 eta: 1:31:36 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 5.6014 loss: 1.3920 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.3920 2023/06/05 19:42:10 - mmengine - INFO - Epoch(train) [142][2520/2569] lr: 4.0000e-04 eta: 1:31:31 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 5.6843 loss: 1.7967 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7967 2023/06/05 19:42:15 - mmengine - INFO - Epoch(train) [142][2540/2569] lr: 4.0000e-04 eta: 1:31:26 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 5.6901 loss: 1.8187 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8187 2023/06/05 19:42:20 - mmengine - INFO - Epoch(train) [142][2560/2569] lr: 4.0000e-04 eta: 1:31:20 time: 0.2597 data_time: 0.0072 memory: 5828 grad_norm: 5.6920 loss: 1.7727 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7727 2023/06/05 19:42:22 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:42:22 - mmengine - INFO - Epoch(train) [142][2569/2569] lr: 4.0000e-04 eta: 1:31:18 time: 0.2523 data_time: 0.0069 memory: 5828 grad_norm: 5.7474 loss: 1.6529 top1_acc: 0.6667 top5_acc: 1.0000 loss_cls: 1.6529 2023/06/05 19:42:29 - mmengine - INFO - Epoch(train) [143][ 20/2569] lr: 4.0000e-04 eta: 1:31:13 time: 0.3417 data_time: 0.0535 memory: 5828 grad_norm: 5.6893 loss: 1.5204 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5204 2023/06/05 19:42:35 - mmengine - INFO - Epoch(train) [143][ 40/2569] lr: 4.0000e-04 eta: 1:31:07 time: 0.2733 data_time: 0.0074 memory: 5828 grad_norm: 5.5817 loss: 1.7450 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7450 2023/06/05 19:42:40 - mmengine - INFO - Epoch(train) [143][ 60/2569] lr: 4.0000e-04 eta: 1:31:02 time: 0.2728 data_time: 0.0074 memory: 5828 grad_norm: 5.6360 loss: 1.5049 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.5049 2023/06/05 19:42:45 - mmengine - INFO - Epoch(train) [143][ 80/2569] lr: 4.0000e-04 eta: 1:30:57 time: 0.2622 data_time: 0.0075 memory: 5828 grad_norm: 5.6176 loss: 1.5271 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5271 2023/06/05 19:42:51 - mmengine - INFO - Epoch(train) [143][ 100/2569] lr: 4.0000e-04 eta: 1:30:51 time: 0.2737 data_time: 0.0076 memory: 5828 grad_norm: 5.6711 loss: 1.5750 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5750 2023/06/05 19:42:56 - mmengine - INFO - Epoch(train) [143][ 120/2569] lr: 4.0000e-04 eta: 1:30:46 time: 0.2646 data_time: 0.0076 memory: 5828 grad_norm: 5.6843 loss: 1.5037 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5037 2023/06/05 19:43:02 - mmengine - INFO - Epoch(train) [143][ 140/2569] lr: 4.0000e-04 eta: 1:30:41 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 5.6630 loss: 1.4469 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4469 2023/06/05 19:43:07 - mmengine - INFO - Epoch(train) [143][ 160/2569] lr: 4.0000e-04 eta: 1:30:35 time: 0.2637 data_time: 0.0079 memory: 5828 grad_norm: 5.6851 loss: 1.5329 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5329 2023/06/05 19:43:12 - mmengine - INFO - Epoch(train) [143][ 180/2569] lr: 4.0000e-04 eta: 1:30:30 time: 0.2639 data_time: 0.0079 memory: 5828 grad_norm: 5.6031 loss: 1.9804 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.9804 2023/06/05 19:43:18 - mmengine - INFO - Epoch(train) [143][ 200/2569] lr: 4.0000e-04 eta: 1:30:25 time: 0.2696 data_time: 0.0080 memory: 5828 grad_norm: 5.6802 loss: 1.6776 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6776 2023/06/05 19:43:18 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:43:23 - mmengine - INFO - Epoch(train) [143][ 220/2569] lr: 4.0000e-04 eta: 1:30:19 time: 0.2664 data_time: 0.0076 memory: 5828 grad_norm: 5.5911 loss: 1.5905 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5905 2023/06/05 19:43:28 - mmengine - INFO - Epoch(train) [143][ 240/2569] lr: 4.0000e-04 eta: 1:30:14 time: 0.2769 data_time: 0.0075 memory: 5828 grad_norm: 5.5858 loss: 1.6618 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6618 2023/06/05 19:43:34 - mmengine - INFO - Epoch(train) [143][ 260/2569] lr: 4.0000e-04 eta: 1:30:09 time: 0.2670 data_time: 0.0081 memory: 5828 grad_norm: 5.7594 loss: 1.6466 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6466 2023/06/05 19:43:39 - mmengine - INFO - Epoch(train) [143][ 280/2569] lr: 4.0000e-04 eta: 1:30:03 time: 0.2749 data_time: 0.0074 memory: 5828 grad_norm: 5.7228 loss: 2.0400 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0400 2023/06/05 19:43:45 - mmengine - INFO - Epoch(train) [143][ 300/2569] lr: 4.0000e-04 eta: 1:29:58 time: 0.2662 data_time: 0.0071 memory: 5828 grad_norm: 5.7112 loss: 1.8683 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8683 2023/06/05 19:43:50 - mmengine - INFO - Epoch(train) [143][ 320/2569] lr: 4.0000e-04 eta: 1:29:53 time: 0.2669 data_time: 0.0074 memory: 5828 grad_norm: 5.7691 loss: 1.7134 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7134 2023/06/05 19:43:55 - mmengine - INFO - Epoch(train) [143][ 340/2569] lr: 4.0000e-04 eta: 1:29:47 time: 0.2713 data_time: 0.0073 memory: 5828 grad_norm: 5.6247 loss: 1.6126 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6126 2023/06/05 19:44:01 - mmengine - INFO - Epoch(train) [143][ 360/2569] lr: 4.0000e-04 eta: 1:29:42 time: 0.2718 data_time: 0.0069 memory: 5828 grad_norm: 5.6830 loss: 1.4316 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4316 2023/06/05 19:44:06 - mmengine - INFO - Epoch(train) [143][ 380/2569] lr: 4.0000e-04 eta: 1:29:37 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 5.7285 loss: 1.5534 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5534 2023/06/05 19:44:12 - mmengine - INFO - Epoch(train) [143][ 400/2569] lr: 4.0000e-04 eta: 1:29:31 time: 0.2712 data_time: 0.0074 memory: 5828 grad_norm: 5.6664 loss: 1.5483 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5483 2023/06/05 19:44:17 - mmengine - INFO - Epoch(train) [143][ 420/2569] lr: 4.0000e-04 eta: 1:29:26 time: 0.2734 data_time: 0.0082 memory: 5828 grad_norm: 5.6366 loss: 1.5358 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5358 2023/06/05 19:44:23 - mmengine - INFO - Epoch(train) [143][ 440/2569] lr: 4.0000e-04 eta: 1:29:21 time: 0.2701 data_time: 0.0082 memory: 5828 grad_norm: 5.8006 loss: 1.5640 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5640 2023/06/05 19:44:28 - mmengine - INFO - Epoch(train) [143][ 460/2569] lr: 4.0000e-04 eta: 1:29:15 time: 0.2662 data_time: 0.0076 memory: 5828 grad_norm: 5.7041 loss: 1.6950 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6950 2023/06/05 19:44:33 - mmengine - INFO - Epoch(train) [143][ 480/2569] lr: 4.0000e-04 eta: 1:29:10 time: 0.2717 data_time: 0.0075 memory: 5828 grad_norm: 5.7109 loss: 1.8514 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8514 2023/06/05 19:44:39 - mmengine - INFO - Epoch(train) [143][ 500/2569] lr: 4.0000e-04 eta: 1:29:05 time: 0.2619 data_time: 0.0076 memory: 5828 grad_norm: 5.7352 loss: 1.7972 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7972 2023/06/05 19:44:44 - mmengine - INFO - Epoch(train) [143][ 520/2569] lr: 4.0000e-04 eta: 1:28:59 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 5.7597 loss: 1.9046 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9046 2023/06/05 19:44:49 - mmengine - INFO - Epoch(train) [143][ 540/2569] lr: 4.0000e-04 eta: 1:28:54 time: 0.2637 data_time: 0.0080 memory: 5828 grad_norm: 5.6740 loss: 2.0039 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 2.0039 2023/06/05 19:44:54 - mmengine - INFO - Epoch(train) [143][ 560/2569] lr: 4.0000e-04 eta: 1:28:49 time: 0.2633 data_time: 0.0072 memory: 5828 grad_norm: 5.7112 loss: 1.7377 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7377 2023/06/05 19:45:00 - mmengine - INFO - Epoch(train) [143][ 580/2569] lr: 4.0000e-04 eta: 1:28:43 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 5.7419 loss: 1.3736 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3736 2023/06/05 19:45:05 - mmengine - INFO - Epoch(train) [143][ 600/2569] lr: 4.0000e-04 eta: 1:28:38 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 5.7258 loss: 1.9090 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.9090 2023/06/05 19:45:10 - mmengine - INFO - Epoch(train) [143][ 620/2569] lr: 4.0000e-04 eta: 1:28:33 time: 0.2686 data_time: 0.0075 memory: 5828 grad_norm: 5.6622 loss: 1.6468 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.6468 2023/06/05 19:45:16 - mmengine - INFO - Epoch(train) [143][ 640/2569] lr: 4.0000e-04 eta: 1:28:27 time: 0.2748 data_time: 0.0073 memory: 5828 grad_norm: 5.7262 loss: 1.4365 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4365 2023/06/05 19:45:21 - mmengine - INFO - Epoch(train) [143][ 660/2569] lr: 4.0000e-04 eta: 1:28:22 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 5.7341 loss: 1.6780 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6780 2023/06/05 19:45:27 - mmengine - INFO - Epoch(train) [143][ 680/2569] lr: 4.0000e-04 eta: 1:28:17 time: 0.2670 data_time: 0.0072 memory: 5828 grad_norm: 5.7990 loss: 1.7574 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7574 2023/06/05 19:45:32 - mmengine - INFO - Epoch(train) [143][ 700/2569] lr: 4.0000e-04 eta: 1:28:11 time: 0.2684 data_time: 0.0072 memory: 5828 grad_norm: 5.7633 loss: 1.6061 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6061 2023/06/05 19:45:37 - mmengine - INFO - Epoch(train) [143][ 720/2569] lr: 4.0000e-04 eta: 1:28:06 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 5.6593 loss: 1.6715 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6715 2023/06/05 19:45:43 - mmengine - INFO - Epoch(train) [143][ 740/2569] lr: 4.0000e-04 eta: 1:28:01 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 5.8104 loss: 1.6066 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6066 2023/06/05 19:45:48 - mmengine - INFO - Epoch(train) [143][ 760/2569] lr: 4.0000e-04 eta: 1:27:55 time: 0.2644 data_time: 0.0072 memory: 5828 grad_norm: 5.7150 loss: 1.5387 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5387 2023/06/05 19:45:53 - mmengine - INFO - Epoch(train) [143][ 780/2569] lr: 4.0000e-04 eta: 1:27:50 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 5.7210 loss: 1.5997 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.5997 2023/06/05 19:45:59 - mmengine - INFO - Epoch(train) [143][ 800/2569] lr: 4.0000e-04 eta: 1:27:45 time: 0.2648 data_time: 0.0072 memory: 5828 grad_norm: 5.8769 loss: 1.6032 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6032 2023/06/05 19:46:04 - mmengine - INFO - Epoch(train) [143][ 820/2569] lr: 4.0000e-04 eta: 1:27:39 time: 0.2621 data_time: 0.0072 memory: 5828 grad_norm: 5.7829 loss: 1.7449 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7449 2023/06/05 19:46:09 - mmengine - INFO - Epoch(train) [143][ 840/2569] lr: 4.0000e-04 eta: 1:27:34 time: 0.2668 data_time: 0.0070 memory: 5828 grad_norm: 5.5944 loss: 1.3900 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3900 2023/06/05 19:46:15 - mmengine - INFO - Epoch(train) [143][ 860/2569] lr: 4.0000e-04 eta: 1:27:29 time: 0.2736 data_time: 0.0075 memory: 5828 grad_norm: 5.6550 loss: 1.2908 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2908 2023/06/05 19:46:20 - mmengine - INFO - Epoch(train) [143][ 880/2569] lr: 4.0000e-04 eta: 1:27:23 time: 0.2719 data_time: 0.0072 memory: 5828 grad_norm: 5.7040 loss: 1.4723 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4723 2023/06/05 19:46:25 - mmengine - INFO - Epoch(train) [143][ 900/2569] lr: 4.0000e-04 eta: 1:27:18 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 5.5581 loss: 1.7753 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7753 2023/06/05 19:46:31 - mmengine - INFO - Epoch(train) [143][ 920/2569] lr: 4.0000e-04 eta: 1:27:13 time: 0.2837 data_time: 0.0075 memory: 5828 grad_norm: 5.7226 loss: 1.5995 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5995 2023/06/05 19:46:36 - mmengine - INFO - Epoch(train) [143][ 940/2569] lr: 4.0000e-04 eta: 1:27:07 time: 0.2631 data_time: 0.0077 memory: 5828 grad_norm: 5.7164 loss: 1.5670 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5670 2023/06/05 19:46:42 - mmengine - INFO - Epoch(train) [143][ 960/2569] lr: 4.0000e-04 eta: 1:27:02 time: 0.2660 data_time: 0.0071 memory: 5828 grad_norm: 5.6900 loss: 1.7094 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7094 2023/06/05 19:46:47 - mmengine - INFO - Epoch(train) [143][ 980/2569] lr: 4.0000e-04 eta: 1:26:57 time: 0.2623 data_time: 0.0074 memory: 5828 grad_norm: 5.7722 loss: 1.9622 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9622 2023/06/05 19:46:52 - mmengine - INFO - Epoch(train) [143][1000/2569] lr: 4.0000e-04 eta: 1:26:51 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 5.6545 loss: 1.6587 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6587 2023/06/05 19:46:58 - mmengine - INFO - Epoch(train) [143][1020/2569] lr: 4.0000e-04 eta: 1:26:46 time: 0.2789 data_time: 0.0074 memory: 5828 grad_norm: 5.7507 loss: 1.7021 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7021 2023/06/05 19:47:03 - mmengine - INFO - Epoch(train) [143][1040/2569] lr: 4.0000e-04 eta: 1:26:41 time: 0.2626 data_time: 0.0073 memory: 5828 grad_norm: 5.6538 loss: 1.4975 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4975 2023/06/05 19:47:09 - mmengine - INFO - Epoch(train) [143][1060/2569] lr: 4.0000e-04 eta: 1:26:35 time: 0.2725 data_time: 0.0071 memory: 5828 grad_norm: 5.7267 loss: 1.6775 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6775 2023/06/05 19:47:14 - mmengine - INFO - Epoch(train) [143][1080/2569] lr: 4.0000e-04 eta: 1:26:30 time: 0.2618 data_time: 0.0070 memory: 5828 grad_norm: 5.6255 loss: 1.3803 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3803 2023/06/05 19:47:19 - mmengine - INFO - Epoch(train) [143][1100/2569] lr: 4.0000e-04 eta: 1:26:25 time: 0.2708 data_time: 0.0071 memory: 5828 grad_norm: 5.6366 loss: 1.6663 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6663 2023/06/05 19:47:25 - mmengine - INFO - Epoch(train) [143][1120/2569] lr: 4.0000e-04 eta: 1:26:19 time: 0.2631 data_time: 0.0071 memory: 5828 grad_norm: 5.6585 loss: 1.9402 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9402 2023/06/05 19:47:30 - mmengine - INFO - Epoch(train) [143][1140/2569] lr: 4.0000e-04 eta: 1:26:14 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 5.6758 loss: 1.2981 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2981 2023/06/05 19:47:35 - mmengine - INFO - Epoch(train) [143][1160/2569] lr: 4.0000e-04 eta: 1:26:09 time: 0.2614 data_time: 0.0071 memory: 5828 grad_norm: 5.7206 loss: 1.6960 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6960 2023/06/05 19:47:41 - mmengine - INFO - Epoch(train) [143][1180/2569] lr: 4.0000e-04 eta: 1:26:03 time: 0.2746 data_time: 0.0071 memory: 5828 grad_norm: 5.7541 loss: 1.2522 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.2522 2023/06/05 19:47:46 - mmengine - INFO - Epoch(train) [143][1200/2569] lr: 4.0000e-04 eta: 1:25:58 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 5.6827 loss: 1.5989 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5989 2023/06/05 19:47:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:47:51 - mmengine - INFO - Epoch(train) [143][1220/2569] lr: 4.0000e-04 eta: 1:25:53 time: 0.2723 data_time: 0.0080 memory: 5828 grad_norm: 5.8183 loss: 1.5470 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5470 2023/06/05 19:47:57 - mmengine - INFO - Epoch(train) [143][1240/2569] lr: 4.0000e-04 eta: 1:25:47 time: 0.2603 data_time: 0.0078 memory: 5828 grad_norm: 5.6443 loss: 1.6033 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6033 2023/06/05 19:48:02 - mmengine - INFO - Epoch(train) [143][1260/2569] lr: 4.0000e-04 eta: 1:25:42 time: 0.2766 data_time: 0.0071 memory: 5828 grad_norm: 5.7043 loss: 1.3253 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3253 2023/06/05 19:48:08 - mmengine - INFO - Epoch(train) [143][1280/2569] lr: 4.0000e-04 eta: 1:25:37 time: 0.2719 data_time: 0.0073 memory: 5828 grad_norm: 5.7755 loss: 1.6728 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6728 2023/06/05 19:48:13 - mmengine - INFO - Epoch(train) [143][1300/2569] lr: 4.0000e-04 eta: 1:25:31 time: 0.2674 data_time: 0.0070 memory: 5828 grad_norm: 5.7031 loss: 1.5058 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5058 2023/06/05 19:48:18 - mmengine - INFO - Epoch(train) [143][1320/2569] lr: 4.0000e-04 eta: 1:25:26 time: 0.2723 data_time: 0.0076 memory: 5828 grad_norm: 5.7809 loss: 1.7506 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7506 2023/06/05 19:48:24 - mmengine - INFO - Epoch(train) [143][1340/2569] lr: 4.0000e-04 eta: 1:25:21 time: 0.2802 data_time: 0.0073 memory: 5828 grad_norm: 5.7192 loss: 1.5963 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5963 2023/06/05 19:48:29 - mmengine - INFO - Epoch(train) [143][1360/2569] lr: 4.0000e-04 eta: 1:25:15 time: 0.2623 data_time: 0.0071 memory: 5828 grad_norm: 5.7244 loss: 1.4060 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4060 2023/06/05 19:48:35 - mmengine - INFO - Epoch(train) [143][1380/2569] lr: 4.0000e-04 eta: 1:25:10 time: 0.2693 data_time: 0.0076 memory: 5828 grad_norm: 5.7552 loss: 1.7282 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7282 2023/06/05 19:48:40 - mmengine - INFO - Epoch(train) [143][1400/2569] lr: 4.0000e-04 eta: 1:25:05 time: 0.2675 data_time: 0.0081 memory: 5828 grad_norm: 5.6350 loss: 1.5717 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5717 2023/06/05 19:48:45 - mmengine - INFO - Epoch(train) [143][1420/2569] lr: 4.0000e-04 eta: 1:24:59 time: 0.2730 data_time: 0.0070 memory: 5828 grad_norm: 5.7315 loss: 1.8080 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8080 2023/06/05 19:48:51 - mmengine - INFO - Epoch(train) [143][1440/2569] lr: 4.0000e-04 eta: 1:24:54 time: 0.2665 data_time: 0.0071 memory: 5828 grad_norm: 5.7084 loss: 1.5652 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5652 2023/06/05 19:48:56 - mmengine - INFO - Epoch(train) [143][1460/2569] lr: 4.0000e-04 eta: 1:24:49 time: 0.2801 data_time: 0.0074 memory: 5828 grad_norm: 5.7482 loss: 1.7413 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7413 2023/06/05 19:49:02 - mmengine - INFO - Epoch(train) [143][1480/2569] lr: 4.0000e-04 eta: 1:24:43 time: 0.2676 data_time: 0.0076 memory: 5828 grad_norm: 5.6860 loss: 1.4371 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4371 2023/06/05 19:49:07 - mmengine - INFO - Epoch(train) [143][1500/2569] lr: 4.0000e-04 eta: 1:24:38 time: 0.2673 data_time: 0.0077 memory: 5828 grad_norm: 5.6376 loss: 1.3325 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3325 2023/06/05 19:49:12 - mmengine - INFO - Epoch(train) [143][1520/2569] lr: 4.0000e-04 eta: 1:24:33 time: 0.2614 data_time: 0.0075 memory: 5828 grad_norm: 5.7595 loss: 1.4030 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4030 2023/06/05 19:49:18 - mmengine - INFO - Epoch(train) [143][1540/2569] lr: 4.0000e-04 eta: 1:24:27 time: 0.2681 data_time: 0.0074 memory: 5828 grad_norm: 5.6055 loss: 1.2310 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.2310 2023/06/05 19:49:23 - mmengine - INFO - Epoch(train) [143][1560/2569] lr: 4.0000e-04 eta: 1:24:22 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 5.7687 loss: 1.4934 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4934 2023/06/05 19:49:28 - mmengine - INFO - Epoch(train) [143][1580/2569] lr: 4.0000e-04 eta: 1:24:17 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 5.7572 loss: 1.4646 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.4646 2023/06/05 19:49:34 - mmengine - INFO - Epoch(train) [143][1600/2569] lr: 4.0000e-04 eta: 1:24:12 time: 0.2696 data_time: 0.0070 memory: 5828 grad_norm: 5.7679 loss: 1.9042 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9042 2023/06/05 19:49:39 - mmengine - INFO - Epoch(train) [143][1620/2569] lr: 4.0000e-04 eta: 1:24:06 time: 0.2726 data_time: 0.0072 memory: 5828 grad_norm: 5.7497 loss: 1.8522 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8522 2023/06/05 19:49:45 - mmengine - INFO - Epoch(train) [143][1640/2569] lr: 4.0000e-04 eta: 1:24:01 time: 0.2688 data_time: 0.0073 memory: 5828 grad_norm: 5.7238 loss: 1.7081 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7081 2023/06/05 19:49:50 - mmengine - INFO - Epoch(train) [143][1660/2569] lr: 4.0000e-04 eta: 1:23:56 time: 0.2736 data_time: 0.0071 memory: 5828 grad_norm: 5.6889 loss: 1.7325 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.7325 2023/06/05 19:49:56 - mmengine - INFO - Epoch(train) [143][1680/2569] lr: 4.0000e-04 eta: 1:23:50 time: 0.2754 data_time: 0.0070 memory: 5828 grad_norm: 5.7505 loss: 1.9265 top1_acc: 0.1250 top5_acc: 0.8750 loss_cls: 1.9265 2023/06/05 19:50:01 - mmengine - INFO - Epoch(train) [143][1700/2569] lr: 4.0000e-04 eta: 1:23:45 time: 0.2675 data_time: 0.0070 memory: 5828 grad_norm: 5.7912 loss: 1.8549 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8549 2023/06/05 19:50:06 - mmengine - INFO - Epoch(train) [143][1720/2569] lr: 4.0000e-04 eta: 1:23:40 time: 0.2670 data_time: 0.0072 memory: 5828 grad_norm: 5.7357 loss: 1.6729 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6729 2023/06/05 19:50:12 - mmengine - INFO - Epoch(train) [143][1740/2569] lr: 4.0000e-04 eta: 1:23:34 time: 0.2617 data_time: 0.0071 memory: 5828 grad_norm: 5.8872 loss: 1.6984 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6984 2023/06/05 19:50:17 - mmengine - INFO - Epoch(train) [143][1760/2569] lr: 4.0000e-04 eta: 1:23:29 time: 0.2775 data_time: 0.0072 memory: 5828 grad_norm: 5.8658 loss: 1.5585 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5585 2023/06/05 19:50:23 - mmengine - INFO - Epoch(train) [143][1780/2569] lr: 4.0000e-04 eta: 1:23:24 time: 0.2730 data_time: 0.0074 memory: 5828 grad_norm: 5.7367 loss: 1.3414 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3414 2023/06/05 19:50:28 - mmengine - INFO - Epoch(train) [143][1800/2569] lr: 4.0000e-04 eta: 1:23:18 time: 0.2778 data_time: 0.0070 memory: 5828 grad_norm: 5.8095 loss: 1.5973 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5973 2023/06/05 19:50:33 - mmengine - INFO - Epoch(train) [143][1820/2569] lr: 4.0000e-04 eta: 1:23:13 time: 0.2605 data_time: 0.0074 memory: 5828 grad_norm: 5.7871 loss: 1.8126 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8126 2023/06/05 19:50:39 - mmengine - INFO - Epoch(train) [143][1840/2569] lr: 4.0000e-04 eta: 1:23:08 time: 0.2624 data_time: 0.0074 memory: 5828 grad_norm: 5.7400 loss: 1.5611 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5611 2023/06/05 19:50:44 - mmengine - INFO - Epoch(train) [143][1860/2569] lr: 4.0000e-04 eta: 1:23:02 time: 0.2669 data_time: 0.0071 memory: 5828 grad_norm: 5.8101 loss: 1.7975 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7975 2023/06/05 19:50:49 - mmengine - INFO - Epoch(train) [143][1880/2569] lr: 4.0000e-04 eta: 1:22:57 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 5.6763 loss: 1.5067 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5067 2023/06/05 19:50:55 - mmengine - INFO - Epoch(train) [143][1900/2569] lr: 4.0000e-04 eta: 1:22:52 time: 0.2652 data_time: 0.0071 memory: 5828 grad_norm: 5.7532 loss: 1.8089 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8089 2023/06/05 19:51:00 - mmengine - INFO - Epoch(train) [143][1920/2569] lr: 4.0000e-04 eta: 1:22:46 time: 0.2631 data_time: 0.0075 memory: 5828 grad_norm: 5.6409 loss: 1.6274 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6274 2023/06/05 19:51:05 - mmengine - INFO - Epoch(train) [143][1940/2569] lr: 4.0000e-04 eta: 1:22:41 time: 0.2672 data_time: 0.0075 memory: 5828 grad_norm: 5.7282 loss: 1.4503 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4503 2023/06/05 19:51:11 - mmengine - INFO - Epoch(train) [143][1960/2569] lr: 4.0000e-04 eta: 1:22:36 time: 0.2692 data_time: 0.0072 memory: 5828 grad_norm: 5.7228 loss: 1.6097 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6097 2023/06/05 19:51:16 - mmengine - INFO - Epoch(train) [143][1980/2569] lr: 4.0000e-04 eta: 1:22:30 time: 0.2623 data_time: 0.0075 memory: 5828 grad_norm: 5.8090 loss: 1.7577 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7577 2023/06/05 19:51:21 - mmengine - INFO - Epoch(train) [143][2000/2569] lr: 4.0000e-04 eta: 1:22:25 time: 0.2665 data_time: 0.0070 memory: 5828 grad_norm: 5.7299 loss: 1.5344 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5344 2023/06/05 19:51:27 - mmengine - INFO - Epoch(train) [143][2020/2569] lr: 4.0000e-04 eta: 1:22:20 time: 0.2696 data_time: 0.0075 memory: 5828 grad_norm: 5.7326 loss: 1.7032 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7032 2023/06/05 19:51:32 - mmengine - INFO - Epoch(train) [143][2040/2569] lr: 4.0000e-04 eta: 1:22:14 time: 0.2706 data_time: 0.0071 memory: 5828 grad_norm: 5.7274 loss: 1.5864 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5864 2023/06/05 19:51:38 - mmengine - INFO - Epoch(train) [143][2060/2569] lr: 4.0000e-04 eta: 1:22:09 time: 0.2800 data_time: 0.0074 memory: 5828 grad_norm: 5.9055 loss: 1.7197 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7197 2023/06/05 19:51:43 - mmengine - INFO - Epoch(train) [143][2080/2569] lr: 4.0000e-04 eta: 1:22:04 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 5.7033 loss: 1.7410 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7410 2023/06/05 19:51:48 - mmengine - INFO - Epoch(train) [143][2100/2569] lr: 4.0000e-04 eta: 1:21:58 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 5.6677 loss: 1.4194 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4194 2023/06/05 19:51:54 - mmengine - INFO - Epoch(train) [143][2120/2569] lr: 4.0000e-04 eta: 1:21:53 time: 0.2696 data_time: 0.0070 memory: 5828 grad_norm: 5.8042 loss: 1.4800 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.4800 2023/06/05 19:51:59 - mmengine - INFO - Epoch(train) [143][2140/2569] lr: 4.0000e-04 eta: 1:21:48 time: 0.2679 data_time: 0.0071 memory: 5828 grad_norm: 5.7081 loss: 1.5439 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5439 2023/06/05 19:52:05 - mmengine - INFO - Epoch(train) [143][2160/2569] lr: 4.0000e-04 eta: 1:21:42 time: 0.2726 data_time: 0.0072 memory: 5828 grad_norm: 5.6482 loss: 1.2811 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2811 2023/06/05 19:52:10 - mmengine - INFO - Epoch(train) [143][2180/2569] lr: 4.0000e-04 eta: 1:21:37 time: 0.2624 data_time: 0.0072 memory: 5828 grad_norm: 5.8085 loss: 1.6122 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6122 2023/06/05 19:52:15 - mmengine - INFO - Epoch(train) [143][2200/2569] lr: 4.0000e-04 eta: 1:21:32 time: 0.2736 data_time: 0.0074 memory: 5828 grad_norm: 5.7330 loss: 1.5593 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5593 2023/06/05 19:52:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:52:21 - mmengine - INFO - Epoch(train) [143][2220/2569] lr: 4.0000e-04 eta: 1:21:26 time: 0.2695 data_time: 0.0071 memory: 5828 grad_norm: 5.7105 loss: 1.6831 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6831 2023/06/05 19:52:26 - mmengine - INFO - Epoch(train) [143][2240/2569] lr: 4.0000e-04 eta: 1:21:21 time: 0.2648 data_time: 0.0075 memory: 5828 grad_norm: 5.8619 loss: 1.6146 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.6146 2023/06/05 19:52:31 - mmengine - INFO - Epoch(train) [143][2260/2569] lr: 4.0000e-04 eta: 1:21:16 time: 0.2641 data_time: 0.0069 memory: 5828 grad_norm: 5.7490 loss: 1.5609 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5609 2023/06/05 19:52:37 - mmengine - INFO - Epoch(train) [143][2280/2569] lr: 4.0000e-04 eta: 1:21:10 time: 0.2726 data_time: 0.0070 memory: 5828 grad_norm: 5.7060 loss: 1.3875 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.3875 2023/06/05 19:52:42 - mmengine - INFO - Epoch(train) [143][2300/2569] lr: 4.0000e-04 eta: 1:21:05 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 5.6980 loss: 1.6878 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6878 2023/06/05 19:52:47 - mmengine - INFO - Epoch(train) [143][2320/2569] lr: 4.0000e-04 eta: 1:21:00 time: 0.2638 data_time: 0.0070 memory: 5828 grad_norm: 5.6975 loss: 1.4782 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4782 2023/06/05 19:52:53 - mmengine - INFO - Epoch(train) [143][2340/2569] lr: 4.0000e-04 eta: 1:20:54 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 5.7767 loss: 1.6240 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6240 2023/06/05 19:52:58 - mmengine - INFO - Epoch(train) [143][2360/2569] lr: 4.0000e-04 eta: 1:20:49 time: 0.2702 data_time: 0.0072 memory: 5828 grad_norm: 5.7699 loss: 1.3452 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3452 2023/06/05 19:53:03 - mmengine - INFO - Epoch(train) [143][2380/2569] lr: 4.0000e-04 eta: 1:20:44 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 5.7699 loss: 1.7462 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7462 2023/06/05 19:53:09 - mmengine - INFO - Epoch(train) [143][2400/2569] lr: 4.0000e-04 eta: 1:20:38 time: 0.2735 data_time: 0.0074 memory: 5828 grad_norm: 5.7188 loss: 1.6322 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6322 2023/06/05 19:53:14 - mmengine - INFO - Epoch(train) [143][2420/2569] lr: 4.0000e-04 eta: 1:20:33 time: 0.2740 data_time: 0.0074 memory: 5828 grad_norm: 5.8665 loss: 1.6262 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6262 2023/06/05 19:53:20 - mmengine - INFO - Epoch(train) [143][2440/2569] lr: 4.0000e-04 eta: 1:20:28 time: 0.2665 data_time: 0.0072 memory: 5828 grad_norm: 5.7604 loss: 1.6902 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6902 2023/06/05 19:53:25 - mmengine - INFO - Epoch(train) [143][2460/2569] lr: 4.0000e-04 eta: 1:20:22 time: 0.2651 data_time: 0.0072 memory: 5828 grad_norm: 5.7005 loss: 1.6763 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6763 2023/06/05 19:53:30 - mmengine - INFO - Epoch(train) [143][2480/2569] lr: 4.0000e-04 eta: 1:20:17 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 5.7984 loss: 1.5832 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5832 2023/06/05 19:53:36 - mmengine - INFO - Epoch(train) [143][2500/2569] lr: 4.0000e-04 eta: 1:20:12 time: 0.2701 data_time: 0.0074 memory: 5828 grad_norm: 5.6437 loss: 1.6935 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6935 2023/06/05 19:53:42 - mmengine - INFO - Epoch(train) [143][2520/2569] lr: 4.0000e-04 eta: 1:20:06 time: 0.2843 data_time: 0.0073 memory: 5828 grad_norm: 5.6848 loss: 1.7307 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7307 2023/06/05 19:53:47 - mmengine - INFO - Epoch(train) [143][2540/2569] lr: 4.0000e-04 eta: 1:20:01 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 5.7497 loss: 1.5170 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5170 2023/06/05 19:53:52 - mmengine - INFO - Epoch(train) [143][2560/2569] lr: 4.0000e-04 eta: 1:19:56 time: 0.2741 data_time: 0.0072 memory: 5828 grad_norm: 5.6940 loss: 1.6256 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.6256 2023/06/05 19:53:55 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:53:55 - mmengine - INFO - Epoch(train) [143][2569/2569] lr: 4.0000e-04 eta: 1:19:53 time: 0.2600 data_time: 0.0070 memory: 5828 grad_norm: 5.7188 loss: 1.6302 top1_acc: 0.3333 top5_acc: 0.8333 loss_cls: 1.6302 2023/06/05 19:54:02 - mmengine - INFO - Epoch(train) [144][ 20/2569] lr: 4.0000e-04 eta: 1:19:48 time: 0.3427 data_time: 0.0542 memory: 5828 grad_norm: 5.7207 loss: 1.6404 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6404 2023/06/05 19:54:07 - mmengine - INFO - Epoch(train) [144][ 40/2569] lr: 4.0000e-04 eta: 1:19:43 time: 0.2776 data_time: 0.0071 memory: 5828 grad_norm: 5.6859 loss: 1.5013 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5013 2023/06/05 19:54:12 - mmengine - INFO - Epoch(train) [144][ 60/2569] lr: 4.0000e-04 eta: 1:19:37 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 5.6900 loss: 1.3309 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3309 2023/06/05 19:54:18 - mmengine - INFO - Epoch(train) [144][ 80/2569] lr: 4.0000e-04 eta: 1:19:32 time: 0.2644 data_time: 0.0074 memory: 5828 grad_norm: 5.6438 loss: 1.9482 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9482 2023/06/05 19:54:23 - mmengine - INFO - Epoch(train) [144][ 100/2569] lr: 4.0000e-04 eta: 1:19:27 time: 0.2736 data_time: 0.0074 memory: 5828 grad_norm: 5.8389 loss: 1.3834 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3834 2023/06/05 19:54:29 - mmengine - INFO - Epoch(train) [144][ 120/2569] lr: 4.0000e-04 eta: 1:19:21 time: 0.2676 data_time: 0.0069 memory: 5828 grad_norm: 5.7727 loss: 1.5862 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5862 2023/06/05 19:54:34 - mmengine - INFO - Epoch(train) [144][ 140/2569] lr: 4.0000e-04 eta: 1:19:16 time: 0.2642 data_time: 0.0073 memory: 5828 grad_norm: 5.6607 loss: 1.5868 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5868 2023/06/05 19:54:39 - mmengine - INFO - Epoch(train) [144][ 160/2569] lr: 4.0000e-04 eta: 1:19:11 time: 0.2668 data_time: 0.0081 memory: 5828 grad_norm: 5.8709 loss: 1.5650 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5650 2023/06/05 19:54:45 - mmengine - INFO - Epoch(train) [144][ 180/2569] lr: 4.0000e-04 eta: 1:19:05 time: 0.2729 data_time: 0.0074 memory: 5828 grad_norm: 5.6426 loss: 1.3402 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.3402 2023/06/05 19:54:50 - mmengine - INFO - Epoch(train) [144][ 200/2569] lr: 4.0000e-04 eta: 1:19:00 time: 0.2656 data_time: 0.0076 memory: 5828 grad_norm: 5.7496 loss: 1.5122 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5122 2023/06/05 19:54:55 - mmengine - INFO - Epoch(train) [144][ 220/2569] lr: 4.0000e-04 eta: 1:18:55 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 5.7106 loss: 1.4096 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4096 2023/06/05 19:55:01 - mmengine - INFO - Epoch(train) [144][ 240/2569] lr: 4.0000e-04 eta: 1:18:49 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 5.7456 loss: 1.7374 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7374 2023/06/05 19:55:06 - mmengine - INFO - Epoch(train) [144][ 260/2569] lr: 4.0000e-04 eta: 1:18:44 time: 0.2741 data_time: 0.0072 memory: 5828 grad_norm: 5.6034 loss: 1.5708 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5708 2023/06/05 19:55:11 - mmengine - INFO - Epoch(train) [144][ 280/2569] lr: 4.0000e-04 eta: 1:18:39 time: 0.2642 data_time: 0.0075 memory: 5828 grad_norm: 5.6777 loss: 1.8163 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8163 2023/06/05 19:55:17 - mmengine - INFO - Epoch(train) [144][ 300/2569] lr: 4.0000e-04 eta: 1:18:33 time: 0.2715 data_time: 0.0075 memory: 5828 grad_norm: 5.6761 loss: 1.8375 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8375 2023/06/05 19:55:22 - mmengine - INFO - Epoch(train) [144][ 320/2569] lr: 4.0000e-04 eta: 1:18:28 time: 0.2620 data_time: 0.0074 memory: 5828 grad_norm: 5.7172 loss: 1.6182 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6182 2023/06/05 19:55:27 - mmengine - INFO - Epoch(train) [144][ 340/2569] lr: 4.0000e-04 eta: 1:18:23 time: 0.2620 data_time: 0.0070 memory: 5828 grad_norm: 5.8054 loss: 1.4766 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4766 2023/06/05 19:55:33 - mmengine - INFO - Epoch(train) [144][ 360/2569] lr: 4.0000e-04 eta: 1:18:17 time: 0.2705 data_time: 0.0072 memory: 5828 grad_norm: 5.6606 loss: 1.8021 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.8021 2023/06/05 19:55:38 - mmengine - INFO - Epoch(train) [144][ 380/2569] lr: 4.0000e-04 eta: 1:18:12 time: 0.2624 data_time: 0.0070 memory: 5828 grad_norm: 5.7144 loss: 1.9071 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.9071 2023/06/05 19:55:44 - mmengine - INFO - Epoch(train) [144][ 400/2569] lr: 4.0000e-04 eta: 1:18:07 time: 0.2778 data_time: 0.0070 memory: 5828 grad_norm: 5.8279 loss: 1.4422 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4422 2023/06/05 19:55:49 - mmengine - INFO - Epoch(train) [144][ 420/2569] lr: 4.0000e-04 eta: 1:18:01 time: 0.2637 data_time: 0.0075 memory: 5828 grad_norm: 5.8006 loss: 1.7791 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7791 2023/06/05 19:55:55 - mmengine - INFO - Epoch(train) [144][ 440/2569] lr: 4.0000e-04 eta: 1:17:56 time: 0.2767 data_time: 0.0071 memory: 5828 grad_norm: 5.9181 loss: 1.7318 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7318 2023/06/05 19:56:00 - mmengine - INFO - Epoch(train) [144][ 460/2569] lr: 4.0000e-04 eta: 1:17:51 time: 0.2683 data_time: 0.0071 memory: 5828 grad_norm: 5.7902 loss: 1.8346 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.8346 2023/06/05 19:56:05 - mmengine - INFO - Epoch(train) [144][ 480/2569] lr: 4.0000e-04 eta: 1:17:45 time: 0.2674 data_time: 0.0075 memory: 5828 grad_norm: 5.7065 loss: 1.5583 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5583 2023/06/05 19:56:11 - mmengine - INFO - Epoch(train) [144][ 500/2569] lr: 4.0000e-04 eta: 1:17:40 time: 0.2684 data_time: 0.0071 memory: 5828 grad_norm: 5.7635 loss: 1.5556 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5556 2023/06/05 19:56:16 - mmengine - INFO - Epoch(train) [144][ 520/2569] lr: 4.0000e-04 eta: 1:17:35 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 5.7849 loss: 1.6288 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6288 2023/06/05 19:56:21 - mmengine - INFO - Epoch(train) [144][ 540/2569] lr: 4.0000e-04 eta: 1:17:29 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 5.7283 loss: 1.6351 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6351 2023/06/05 19:56:27 - mmengine - INFO - Epoch(train) [144][ 560/2569] lr: 4.0000e-04 eta: 1:17:24 time: 0.2696 data_time: 0.0071 memory: 5828 grad_norm: 5.7567 loss: 1.7872 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7872 2023/06/05 19:56:32 - mmengine - INFO - Epoch(train) [144][ 580/2569] lr: 4.0000e-04 eta: 1:17:19 time: 0.2734 data_time: 0.0070 memory: 5828 grad_norm: 5.8276 loss: 1.5896 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5896 2023/06/05 19:56:38 - mmengine - INFO - Epoch(train) [144][ 600/2569] lr: 4.0000e-04 eta: 1:17:13 time: 0.2686 data_time: 0.0073 memory: 5828 grad_norm: 5.7511 loss: 1.5028 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5028 2023/06/05 19:56:43 - mmengine - INFO - Epoch(train) [144][ 620/2569] lr: 4.0000e-04 eta: 1:17:08 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 5.7368 loss: 1.8584 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8584 2023/06/05 19:56:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 19:56:48 - mmengine - INFO - Epoch(train) [144][ 640/2569] lr: 4.0000e-04 eta: 1:17:03 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 5.8363 loss: 1.5768 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5768 2023/06/05 19:56:54 - mmengine - INFO - Epoch(train) [144][ 660/2569] lr: 4.0000e-04 eta: 1:16:57 time: 0.2701 data_time: 0.0073 memory: 5828 grad_norm: 5.7515 loss: 1.7295 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7295 2023/06/05 19:56:59 - mmengine - INFO - Epoch(train) [144][ 680/2569] lr: 4.0000e-04 eta: 1:16:52 time: 0.2687 data_time: 0.0075 memory: 5828 grad_norm: 5.8200 loss: 1.7639 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7639 2023/06/05 19:57:04 - mmengine - INFO - Epoch(train) [144][ 700/2569] lr: 4.0000e-04 eta: 1:16:47 time: 0.2612 data_time: 0.0069 memory: 5828 grad_norm: 5.6219 loss: 1.3364 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3364 2023/06/05 19:57:10 - mmengine - INFO - Epoch(train) [144][ 720/2569] lr: 4.0000e-04 eta: 1:16:41 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 5.6920 loss: 1.4279 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4279 2023/06/05 19:57:15 - mmengine - INFO - Epoch(train) [144][ 740/2569] lr: 4.0000e-04 eta: 1:16:36 time: 0.2682 data_time: 0.0071 memory: 5828 grad_norm: 5.6989 loss: 1.2932 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.2932 2023/06/05 19:57:20 - mmengine - INFO - Epoch(train) [144][ 760/2569] lr: 4.0000e-04 eta: 1:16:31 time: 0.2644 data_time: 0.0073 memory: 5828 grad_norm: 5.7520 loss: 1.4031 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4031 2023/06/05 19:57:26 - mmengine - INFO - Epoch(train) [144][ 780/2569] lr: 4.0000e-04 eta: 1:16:25 time: 0.2690 data_time: 0.0072 memory: 5828 grad_norm: 5.8459 loss: 1.5042 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5042 2023/06/05 19:57:31 - mmengine - INFO - Epoch(train) [144][ 800/2569] lr: 4.0000e-04 eta: 1:16:20 time: 0.2635 data_time: 0.0074 memory: 5828 grad_norm: 5.7773 loss: 1.4745 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4745 2023/06/05 19:57:36 - mmengine - INFO - Epoch(train) [144][ 820/2569] lr: 4.0000e-04 eta: 1:16:15 time: 0.2685 data_time: 0.0077 memory: 5828 grad_norm: 5.7815 loss: 1.3553 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.3553 2023/06/05 19:57:42 - mmengine - INFO - Epoch(train) [144][ 840/2569] lr: 4.0000e-04 eta: 1:16:10 time: 0.2782 data_time: 0.0071 memory: 5828 grad_norm: 5.6574 loss: 1.6161 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6161 2023/06/05 19:57:47 - mmengine - INFO - Epoch(train) [144][ 860/2569] lr: 4.0000e-04 eta: 1:16:04 time: 0.2669 data_time: 0.0072 memory: 5828 grad_norm: 5.8742 loss: 1.5249 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5249 2023/06/05 19:57:53 - mmengine - INFO - Epoch(train) [144][ 880/2569] lr: 4.0000e-04 eta: 1:15:59 time: 0.2688 data_time: 0.0072 memory: 5828 grad_norm: 5.7161 loss: 1.8499 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8499 2023/06/05 19:57:58 - mmengine - INFO - Epoch(train) [144][ 900/2569] lr: 4.0000e-04 eta: 1:15:54 time: 0.2812 data_time: 0.0074 memory: 5828 grad_norm: 5.7253 loss: 1.5843 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5843 2023/06/05 19:58:04 - mmengine - INFO - Epoch(train) [144][ 920/2569] lr: 4.0000e-04 eta: 1:15:48 time: 0.2714 data_time: 0.0072 memory: 5828 grad_norm: 5.7260 loss: 1.6075 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.6075 2023/06/05 19:58:09 - mmengine - INFO - Epoch(train) [144][ 940/2569] lr: 4.0000e-04 eta: 1:15:43 time: 0.2726 data_time: 0.0074 memory: 5828 grad_norm: 5.7196 loss: 1.4948 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4948 2023/06/05 19:58:15 - mmengine - INFO - Epoch(train) [144][ 960/2569] lr: 4.0000e-04 eta: 1:15:38 time: 0.2826 data_time: 0.0071 memory: 5828 grad_norm: 5.7576 loss: 1.3279 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.3279 2023/06/05 19:58:20 - mmengine - INFO - Epoch(train) [144][ 980/2569] lr: 4.0000e-04 eta: 1:15:32 time: 0.2614 data_time: 0.0072 memory: 5828 grad_norm: 5.7035 loss: 1.5265 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5265 2023/06/05 19:58:25 - mmengine - INFO - Epoch(train) [144][1000/2569] lr: 4.0000e-04 eta: 1:15:27 time: 0.2671 data_time: 0.0070 memory: 5828 grad_norm: 5.7827 loss: 1.5200 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5200 2023/06/05 19:58:31 - mmengine - INFO - Epoch(train) [144][1020/2569] lr: 4.0000e-04 eta: 1:15:22 time: 0.2698 data_time: 0.0075 memory: 5828 grad_norm: 5.7681 loss: 1.6366 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6366 2023/06/05 19:58:36 - mmengine - INFO - Epoch(train) [144][1040/2569] lr: 4.0000e-04 eta: 1:15:16 time: 0.2740 data_time: 0.0073 memory: 5828 grad_norm: 5.9172 loss: 1.5895 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.5895 2023/06/05 19:58:42 - mmengine - INFO - Epoch(train) [144][1060/2569] lr: 4.0000e-04 eta: 1:15:11 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 5.8153 loss: 1.4344 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.4344 2023/06/05 19:58:47 - mmengine - INFO - Epoch(train) [144][1080/2569] lr: 4.0000e-04 eta: 1:15:06 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 5.8193 loss: 1.7616 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7616 2023/06/05 19:58:52 - mmengine - INFO - Epoch(train) [144][1100/2569] lr: 4.0000e-04 eta: 1:15:00 time: 0.2699 data_time: 0.0070 memory: 5828 grad_norm: 5.7821 loss: 1.5810 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5810 2023/06/05 19:58:58 - mmengine - INFO - Epoch(train) [144][1120/2569] lr: 4.0000e-04 eta: 1:14:55 time: 0.2658 data_time: 0.0082 memory: 5828 grad_norm: 5.6630 loss: 1.6044 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6044 2023/06/05 19:59:03 - mmengine - INFO - Epoch(train) [144][1140/2569] lr: 4.0000e-04 eta: 1:14:50 time: 0.2683 data_time: 0.0074 memory: 5828 grad_norm: 5.7263 loss: 1.4261 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4261 2023/06/05 19:59:08 - mmengine - INFO - Epoch(train) [144][1160/2569] lr: 4.0000e-04 eta: 1:14:44 time: 0.2615 data_time: 0.0073 memory: 5828 grad_norm: 5.7532 loss: 2.0054 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 2.0054 2023/06/05 19:59:14 - mmengine - INFO - Epoch(train) [144][1180/2569] lr: 4.0000e-04 eta: 1:14:39 time: 0.2722 data_time: 0.0070 memory: 5828 grad_norm: 5.7241 loss: 1.7319 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7319 2023/06/05 19:59:19 - mmengine - INFO - Epoch(train) [144][1200/2569] lr: 4.0000e-04 eta: 1:14:34 time: 0.2681 data_time: 0.0070 memory: 5828 grad_norm: 5.7658 loss: 1.6868 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.6868 2023/06/05 19:59:25 - mmengine - INFO - Epoch(train) [144][1220/2569] lr: 4.0000e-04 eta: 1:14:28 time: 0.2707 data_time: 0.0072 memory: 5828 grad_norm: 5.7554 loss: 1.5050 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5050 2023/06/05 19:59:30 - mmengine - INFO - Epoch(train) [144][1240/2569] lr: 4.0000e-04 eta: 1:14:23 time: 0.2629 data_time: 0.0071 memory: 5828 grad_norm: 5.8897 loss: 1.7106 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7106 2023/06/05 19:59:36 - mmengine - INFO - Epoch(train) [144][1260/2569] lr: 4.0000e-04 eta: 1:14:18 time: 0.2813 data_time: 0.0072 memory: 5828 grad_norm: 5.7255 loss: 1.5079 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5079 2023/06/05 19:59:41 - mmengine - INFO - Epoch(train) [144][1280/2569] lr: 4.0000e-04 eta: 1:14:12 time: 0.2663 data_time: 0.0079 memory: 5828 grad_norm: 5.7594 loss: 1.5397 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5397 2023/06/05 19:59:46 - mmengine - INFO - Epoch(train) [144][1300/2569] lr: 4.0000e-04 eta: 1:14:07 time: 0.2706 data_time: 0.0069 memory: 5828 grad_norm: 5.8371 loss: 1.7506 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7506 2023/06/05 19:59:52 - mmengine - INFO - Epoch(train) [144][1320/2569] lr: 4.0000e-04 eta: 1:14:02 time: 0.2745 data_time: 0.0073 memory: 5828 grad_norm: 5.8270 loss: 1.7511 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7511 2023/06/05 19:59:57 - mmengine - INFO - Epoch(train) [144][1340/2569] lr: 4.0000e-04 eta: 1:13:56 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 5.7621 loss: 1.6571 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6571 2023/06/05 20:00:03 - mmengine - INFO - Epoch(train) [144][1360/2569] lr: 4.0000e-04 eta: 1:13:51 time: 0.2719 data_time: 0.0072 memory: 5828 grad_norm: 5.7592 loss: 1.4695 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4695 2023/06/05 20:00:08 - mmengine - INFO - Epoch(train) [144][1380/2569] lr: 4.0000e-04 eta: 1:13:46 time: 0.2627 data_time: 0.0072 memory: 5828 grad_norm: 5.7467 loss: 1.3962 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.3962 2023/06/05 20:00:13 - mmengine - INFO - Epoch(train) [144][1400/2569] lr: 4.0000e-04 eta: 1:13:40 time: 0.2670 data_time: 0.0074 memory: 5828 grad_norm: 5.7574 loss: 1.5332 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5332 2023/06/05 20:00:18 - mmengine - INFO - Epoch(train) [144][1420/2569] lr: 4.0000e-04 eta: 1:13:35 time: 0.2619 data_time: 0.0073 memory: 5828 grad_norm: 5.7981 loss: 1.7253 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7253 2023/06/05 20:00:24 - mmengine - INFO - Epoch(train) [144][1440/2569] lr: 4.0000e-04 eta: 1:13:30 time: 0.2645 data_time: 0.0074 memory: 5828 grad_norm: 5.9042 loss: 1.7394 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7394 2023/06/05 20:00:29 - mmengine - INFO - Epoch(train) [144][1460/2569] lr: 4.0000e-04 eta: 1:13:24 time: 0.2611 data_time: 0.0076 memory: 5828 grad_norm: 5.7191 loss: 1.6174 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6174 2023/06/05 20:00:34 - mmengine - INFO - Epoch(train) [144][1480/2569] lr: 4.0000e-04 eta: 1:13:19 time: 0.2699 data_time: 0.0075 memory: 5828 grad_norm: 5.8266 loss: 1.5258 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5258 2023/06/05 20:00:40 - mmengine - INFO - Epoch(train) [144][1500/2569] lr: 4.0000e-04 eta: 1:13:14 time: 0.2787 data_time: 0.0073 memory: 5828 grad_norm: 5.8444 loss: 1.4155 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4155 2023/06/05 20:00:45 - mmengine - INFO - Epoch(train) [144][1520/2569] lr: 4.0000e-04 eta: 1:13:08 time: 0.2614 data_time: 0.0074 memory: 5828 grad_norm: 5.7387 loss: 1.5833 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5833 2023/06/05 20:00:50 - mmengine - INFO - Epoch(train) [144][1540/2569] lr: 4.0000e-04 eta: 1:13:03 time: 0.2613 data_time: 0.0072 memory: 5828 grad_norm: 5.8115 loss: 1.5500 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5500 2023/06/05 20:00:56 - mmengine - INFO - Epoch(train) [144][1560/2569] lr: 4.0000e-04 eta: 1:12:58 time: 0.2717 data_time: 0.0071 memory: 5828 grad_norm: 5.8296 loss: 1.6292 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6292 2023/06/05 20:01:01 - mmengine - INFO - Epoch(train) [144][1580/2569] lr: 4.0000e-04 eta: 1:12:52 time: 0.2651 data_time: 0.0074 memory: 5828 grad_norm: 5.8213 loss: 1.6014 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6014 2023/06/05 20:01:07 - mmengine - INFO - Epoch(train) [144][1600/2569] lr: 4.0000e-04 eta: 1:12:47 time: 0.2769 data_time: 0.0071 memory: 5828 grad_norm: 5.7301 loss: 1.7149 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7149 2023/06/05 20:01:12 - mmengine - INFO - Epoch(train) [144][1620/2569] lr: 4.0000e-04 eta: 1:12:42 time: 0.2794 data_time: 0.0069 memory: 5828 grad_norm: 5.6897 loss: 1.4111 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4111 2023/06/05 20:01:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:01:18 - mmengine - INFO - Epoch(train) [144][1640/2569] lr: 4.0000e-04 eta: 1:12:36 time: 0.2743 data_time: 0.0072 memory: 5828 grad_norm: 5.7982 loss: 1.7089 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7089 2023/06/05 20:01:23 - mmengine - INFO - Epoch(train) [144][1660/2569] lr: 4.0000e-04 eta: 1:12:31 time: 0.2664 data_time: 0.0071 memory: 5828 grad_norm: 5.7929 loss: 1.5647 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5647 2023/06/05 20:01:29 - mmengine - INFO - Epoch(train) [144][1680/2569] lr: 4.0000e-04 eta: 1:12:26 time: 0.2733 data_time: 0.0073 memory: 5828 grad_norm: 5.8272 loss: 1.4938 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4938 2023/06/05 20:01:34 - mmengine - INFO - Epoch(train) [144][1700/2569] lr: 4.0000e-04 eta: 1:12:20 time: 0.2660 data_time: 0.0071 memory: 5828 grad_norm: 5.8294 loss: 1.6842 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6842 2023/06/05 20:01:40 - mmengine - INFO - Epoch(train) [144][1720/2569] lr: 4.0000e-04 eta: 1:12:15 time: 0.2742 data_time: 0.0071 memory: 5828 grad_norm: 5.7297 loss: 1.8045 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8045 2023/06/05 20:01:45 - mmengine - INFO - Epoch(train) [144][1740/2569] lr: 4.0000e-04 eta: 1:12:10 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 5.7525 loss: 1.1074 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.1074 2023/06/05 20:01:50 - mmengine - INFO - Epoch(train) [144][1760/2569] lr: 4.0000e-04 eta: 1:12:04 time: 0.2722 data_time: 0.0072 memory: 5828 grad_norm: 5.7672 loss: 1.6519 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6519 2023/06/05 20:01:56 - mmengine - INFO - Epoch(train) [144][1780/2569] lr: 4.0000e-04 eta: 1:11:59 time: 0.2689 data_time: 0.0074 memory: 5828 grad_norm: 5.7674 loss: 1.8250 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8250 2023/06/05 20:02:01 - mmengine - INFO - Epoch(train) [144][1800/2569] lr: 4.0000e-04 eta: 1:11:54 time: 0.2654 data_time: 0.0072 memory: 5828 grad_norm: 5.7626 loss: 1.8771 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8771 2023/06/05 20:02:06 - mmengine - INFO - Epoch(train) [144][1820/2569] lr: 4.0000e-04 eta: 1:11:48 time: 0.2658 data_time: 0.0071 memory: 5828 grad_norm: 5.6730 loss: 1.6327 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6327 2023/06/05 20:02:12 - mmengine - INFO - Epoch(train) [144][1840/2569] lr: 4.0000e-04 eta: 1:11:43 time: 0.2694 data_time: 0.0075 memory: 5828 grad_norm: 5.7557 loss: 1.5018 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5018 2023/06/05 20:02:17 - mmengine - INFO - Epoch(train) [144][1860/2569] lr: 4.0000e-04 eta: 1:11:38 time: 0.2637 data_time: 0.0072 memory: 5828 grad_norm: 5.8452 loss: 1.4127 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4127 2023/06/05 20:02:22 - mmengine - INFO - Epoch(train) [144][1880/2569] lr: 4.0000e-04 eta: 1:11:32 time: 0.2629 data_time: 0.0074 memory: 5828 grad_norm: 5.7758 loss: 1.6525 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6525 2023/06/05 20:02:28 - mmengine - INFO - Epoch(train) [144][1900/2569] lr: 4.0000e-04 eta: 1:11:27 time: 0.2690 data_time: 0.0071 memory: 5828 grad_norm: 5.7454 loss: 1.5519 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5519 2023/06/05 20:02:33 - mmengine - INFO - Epoch(train) [144][1920/2569] lr: 4.0000e-04 eta: 1:11:22 time: 0.2772 data_time: 0.0072 memory: 5828 grad_norm: 5.8176 loss: 1.6093 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6093 2023/06/05 20:02:39 - mmengine - INFO - Epoch(train) [144][1940/2569] lr: 4.0000e-04 eta: 1:11:16 time: 0.2687 data_time: 0.0074 memory: 5828 grad_norm: 5.8236 loss: 1.7369 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7369 2023/06/05 20:02:44 - mmengine - INFO - Epoch(train) [144][1960/2569] lr: 4.0000e-04 eta: 1:11:11 time: 0.2718 data_time: 0.0073 memory: 5828 grad_norm: 5.7685 loss: 1.6002 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6002 2023/06/05 20:02:49 - mmengine - INFO - Epoch(train) [144][1980/2569] lr: 4.0000e-04 eta: 1:11:06 time: 0.2647 data_time: 0.0075 memory: 5828 grad_norm: 5.6832 loss: 1.4198 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4198 2023/06/05 20:02:55 - mmengine - INFO - Epoch(train) [144][2000/2569] lr: 4.0000e-04 eta: 1:11:00 time: 0.2620 data_time: 0.0072 memory: 5828 grad_norm: 5.7581 loss: 1.6754 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6754 2023/06/05 20:03:00 - mmengine - INFO - Epoch(train) [144][2020/2569] lr: 4.0000e-04 eta: 1:10:55 time: 0.2639 data_time: 0.0073 memory: 5828 grad_norm: 5.7746 loss: 1.5954 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5954 2023/06/05 20:03:05 - mmengine - INFO - Epoch(train) [144][2040/2569] lr: 4.0000e-04 eta: 1:10:50 time: 0.2705 data_time: 0.0070 memory: 5828 grad_norm: 5.9525 loss: 1.4751 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4751 2023/06/05 20:03:11 - mmengine - INFO - Epoch(train) [144][2060/2569] lr: 4.0000e-04 eta: 1:10:44 time: 0.2739 data_time: 0.0080 memory: 5828 grad_norm: 5.8752 loss: 1.6185 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6185 2023/06/05 20:03:16 - mmengine - INFO - Epoch(train) [144][2080/2569] lr: 4.0000e-04 eta: 1:10:39 time: 0.2663 data_time: 0.0075 memory: 5828 grad_norm: 5.9334 loss: 1.3516 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3516 2023/06/05 20:03:22 - mmengine - INFO - Epoch(train) [144][2100/2569] lr: 4.0000e-04 eta: 1:10:34 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 5.7734 loss: 1.5327 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5327 2023/06/05 20:03:27 - mmengine - INFO - Epoch(train) [144][2120/2569] lr: 4.0000e-04 eta: 1:10:28 time: 0.2681 data_time: 0.0070 memory: 5828 grad_norm: 5.7933 loss: 1.8270 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8270 2023/06/05 20:03:32 - mmengine - INFO - Epoch(train) [144][2140/2569] lr: 4.0000e-04 eta: 1:10:23 time: 0.2684 data_time: 0.0071 memory: 5828 grad_norm: 5.8934 loss: 1.7828 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7828 2023/06/05 20:03:38 - mmengine - INFO - Epoch(train) [144][2160/2569] lr: 4.0000e-04 eta: 1:10:18 time: 0.2648 data_time: 0.0073 memory: 5828 grad_norm: 5.7700 loss: 1.5248 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5248 2023/06/05 20:03:43 - mmengine - INFO - Epoch(train) [144][2180/2569] lr: 4.0000e-04 eta: 1:10:12 time: 0.2697 data_time: 0.0074 memory: 5828 grad_norm: 5.6741 loss: 1.7401 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7401 2023/06/05 20:03:48 - mmengine - INFO - Epoch(train) [144][2200/2569] lr: 4.0000e-04 eta: 1:10:07 time: 0.2667 data_time: 0.0070 memory: 5828 grad_norm: 5.8239 loss: 1.3631 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.3631 2023/06/05 20:03:54 - mmengine - INFO - Epoch(train) [144][2220/2569] lr: 4.0000e-04 eta: 1:10:02 time: 0.2657 data_time: 0.0073 memory: 5828 grad_norm: 5.7784 loss: 1.7374 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7374 2023/06/05 20:03:59 - mmengine - INFO - Epoch(train) [144][2240/2569] lr: 4.0000e-04 eta: 1:09:56 time: 0.2681 data_time: 0.0076 memory: 5828 grad_norm: 5.6810 loss: 1.6165 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6165 2023/06/05 20:04:04 - mmengine - INFO - Epoch(train) [144][2260/2569] lr: 4.0000e-04 eta: 1:09:51 time: 0.2694 data_time: 0.0072 memory: 5828 grad_norm: 5.6711 loss: 1.3182 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.3182 2023/06/05 20:04:10 - mmengine - INFO - Epoch(train) [144][2280/2569] lr: 4.0000e-04 eta: 1:09:46 time: 0.2635 data_time: 0.0074 memory: 5828 grad_norm: 5.7913 loss: 1.5095 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5095 2023/06/05 20:04:15 - mmengine - INFO - Epoch(train) [144][2300/2569] lr: 4.0000e-04 eta: 1:09:40 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 5.6824 loss: 1.3152 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.3152 2023/06/05 20:04:20 - mmengine - INFO - Epoch(train) [144][2320/2569] lr: 4.0000e-04 eta: 1:09:35 time: 0.2651 data_time: 0.0078 memory: 5828 grad_norm: 5.7789 loss: 1.6701 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6701 2023/06/05 20:04:26 - mmengine - INFO - Epoch(train) [144][2340/2569] lr: 4.0000e-04 eta: 1:09:30 time: 0.2696 data_time: 0.0079 memory: 5828 grad_norm: 5.6685 loss: 1.5849 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5849 2023/06/05 20:04:31 - mmengine - INFO - Epoch(train) [144][2360/2569] lr: 4.0000e-04 eta: 1:09:24 time: 0.2631 data_time: 0.0071 memory: 5828 grad_norm: 5.7589 loss: 1.6232 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6232 2023/06/05 20:04:36 - mmengine - INFO - Epoch(train) [144][2380/2569] lr: 4.0000e-04 eta: 1:09:19 time: 0.2707 data_time: 0.0073 memory: 5828 grad_norm: 5.6511 loss: 1.6518 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6518 2023/06/05 20:04:42 - mmengine - INFO - Epoch(train) [144][2400/2569] lr: 4.0000e-04 eta: 1:09:14 time: 0.2617 data_time: 0.0075 memory: 5828 grad_norm: 5.9178 loss: 1.4971 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4971 2023/06/05 20:04:47 - mmengine - INFO - Epoch(train) [144][2420/2569] lr: 4.0000e-04 eta: 1:09:08 time: 0.2675 data_time: 0.0076 memory: 5828 grad_norm: 5.7963 loss: 1.9541 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9541 2023/06/05 20:04:52 - mmengine - INFO - Epoch(train) [144][2440/2569] lr: 4.0000e-04 eta: 1:09:03 time: 0.2670 data_time: 0.0074 memory: 5828 grad_norm: 5.8548 loss: 1.8808 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8808 2023/06/05 20:04:58 - mmengine - INFO - Epoch(train) [144][2460/2569] lr: 4.0000e-04 eta: 1:08:58 time: 0.2686 data_time: 0.0077 memory: 5828 grad_norm: 5.8731 loss: 1.9778 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9778 2023/06/05 20:05:03 - mmengine - INFO - Epoch(train) [144][2480/2569] lr: 4.0000e-04 eta: 1:08:52 time: 0.2644 data_time: 0.0071 memory: 5828 grad_norm: 5.7855 loss: 1.6698 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6698 2023/06/05 20:05:09 - mmengine - INFO - Epoch(train) [144][2500/2569] lr: 4.0000e-04 eta: 1:08:47 time: 0.2707 data_time: 0.0080 memory: 5828 grad_norm: 5.8011 loss: 1.8251 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8251 2023/06/05 20:05:14 - mmengine - INFO - Epoch(train) [144][2520/2569] lr: 4.0000e-04 eta: 1:08:42 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 5.8684 loss: 1.4937 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4937 2023/06/05 20:05:19 - mmengine - INFO - Epoch(train) [144][2540/2569] lr: 4.0000e-04 eta: 1:08:36 time: 0.2740 data_time: 0.0073 memory: 5828 grad_norm: 5.6757 loss: 1.5939 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5939 2023/06/05 20:05:25 - mmengine - INFO - Epoch(train) [144][2560/2569] lr: 4.0000e-04 eta: 1:08:31 time: 0.2618 data_time: 0.0077 memory: 5828 grad_norm: 5.7475 loss: 1.7575 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7575 2023/06/05 20:05:27 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:05:27 - mmengine - INFO - Epoch(train) [144][2569/2569] lr: 4.0000e-04 eta: 1:08:29 time: 0.2566 data_time: 0.0075 memory: 5828 grad_norm: 5.8005 loss: 1.6012 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.6012 2023/06/05 20:05:27 - mmengine - INFO - Saving checkpoint at 144 epochs 2023/06/05 20:05:35 - mmengine - INFO - Epoch(train) [145][ 20/2569] lr: 4.0000e-04 eta: 1:08:23 time: 0.3113 data_time: 0.0505 memory: 5828 grad_norm: 5.9115 loss: 1.6037 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6037 2023/06/05 20:05:40 - mmengine - INFO - Epoch(train) [145][ 40/2569] lr: 4.0000e-04 eta: 1:08:18 time: 0.2742 data_time: 0.0072 memory: 5828 grad_norm: 5.8281 loss: 1.5696 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5696 2023/06/05 20:05:46 - mmengine - INFO - Epoch(train) [145][ 60/2569] lr: 4.0000e-04 eta: 1:08:13 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 5.7460 loss: 1.4129 top1_acc: 0.2500 top5_acc: 0.5000 loss_cls: 1.4129 2023/06/05 20:05:47 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:05:51 - mmengine - INFO - Epoch(train) [145][ 80/2569] lr: 4.0000e-04 eta: 1:08:07 time: 0.2660 data_time: 0.0074 memory: 5828 grad_norm: 5.8037 loss: 1.4817 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4817 2023/06/05 20:05:57 - mmengine - INFO - Epoch(train) [145][ 100/2569] lr: 4.0000e-04 eta: 1:08:02 time: 0.2696 data_time: 0.0071 memory: 5828 grad_norm: 5.8530 loss: 1.6405 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6405 2023/06/05 20:06:02 - mmengine - INFO - Epoch(train) [145][ 120/2569] lr: 4.0000e-04 eta: 1:07:57 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 5.8906 loss: 1.7876 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7876 2023/06/05 20:06:07 - mmengine - INFO - Epoch(train) [145][ 140/2569] lr: 4.0000e-04 eta: 1:07:51 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 5.7971 loss: 1.8272 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8272 2023/06/05 20:06:13 - mmengine - INFO - Epoch(train) [145][ 160/2569] lr: 4.0000e-04 eta: 1:07:46 time: 0.2744 data_time: 0.0072 memory: 5828 grad_norm: 5.7236 loss: 1.3399 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3399 2023/06/05 20:06:18 - mmengine - INFO - Epoch(train) [145][ 180/2569] lr: 4.0000e-04 eta: 1:07:41 time: 0.2647 data_time: 0.0073 memory: 5828 grad_norm: 5.8430 loss: 1.7895 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7895 2023/06/05 20:06:23 - mmengine - INFO - Epoch(train) [145][ 200/2569] lr: 4.0000e-04 eta: 1:07:35 time: 0.2698 data_time: 0.0072 memory: 5828 grad_norm: 5.6576 loss: 1.3491 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3491 2023/06/05 20:06:29 - mmengine - INFO - Epoch(train) [145][ 220/2569] lr: 4.0000e-04 eta: 1:07:30 time: 0.2687 data_time: 0.0073 memory: 5828 grad_norm: 5.7857 loss: 1.4459 top1_acc: 0.3750 top5_acc: 1.0000 loss_cls: 1.4459 2023/06/05 20:06:34 - mmengine - INFO - Epoch(train) [145][ 240/2569] lr: 4.0000e-04 eta: 1:07:25 time: 0.2713 data_time: 0.0073 memory: 5828 grad_norm: 5.8042 loss: 1.7060 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7060 2023/06/05 20:06:40 - mmengine - INFO - Epoch(train) [145][ 260/2569] lr: 4.0000e-04 eta: 1:07:19 time: 0.2754 data_time: 0.0073 memory: 5828 grad_norm: 5.6565 loss: 1.3965 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3965 2023/06/05 20:06:45 - mmengine - INFO - Epoch(train) [145][ 280/2569] lr: 4.0000e-04 eta: 1:07:14 time: 0.2720 data_time: 0.0073 memory: 5828 grad_norm: 5.7510 loss: 1.2743 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2743 2023/06/05 20:06:51 - mmengine - INFO - Epoch(train) [145][ 300/2569] lr: 4.0000e-04 eta: 1:07:09 time: 0.2776 data_time: 0.0073 memory: 5828 grad_norm: 5.7125 loss: 1.6524 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6524 2023/06/05 20:06:56 - mmengine - INFO - Epoch(train) [145][ 320/2569] lr: 4.0000e-04 eta: 1:07:03 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 5.7975 loss: 1.5146 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5146 2023/06/05 20:07:01 - mmengine - INFO - Epoch(train) [145][ 340/2569] lr: 4.0000e-04 eta: 1:06:58 time: 0.2734 data_time: 0.0072 memory: 5828 grad_norm: 5.7976 loss: 1.5609 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5609 2023/06/05 20:07:07 - mmengine - INFO - Epoch(train) [145][ 360/2569] lr: 4.0000e-04 eta: 1:06:53 time: 0.2655 data_time: 0.0078 memory: 5828 grad_norm: 5.7986 loss: 1.6566 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6566 2023/06/05 20:07:12 - mmengine - INFO - Epoch(train) [145][ 380/2569] lr: 4.0000e-04 eta: 1:06:47 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 5.8246 loss: 1.4876 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4876 2023/06/05 20:07:18 - mmengine - INFO - Epoch(train) [145][ 400/2569] lr: 4.0000e-04 eta: 1:06:42 time: 0.2739 data_time: 0.0076 memory: 5828 grad_norm: 5.7769 loss: 1.4778 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4778 2023/06/05 20:07:23 - mmengine - INFO - Epoch(train) [145][ 420/2569] lr: 4.0000e-04 eta: 1:06:37 time: 0.2756 data_time: 0.0073 memory: 5828 grad_norm: 5.7693 loss: 1.9160 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9160 2023/06/05 20:07:29 - mmengine - INFO - Epoch(train) [145][ 440/2569] lr: 4.0000e-04 eta: 1:06:31 time: 0.2692 data_time: 0.0071 memory: 5828 grad_norm: 5.8716 loss: 1.4998 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4998 2023/06/05 20:07:34 - mmengine - INFO - Epoch(train) [145][ 460/2569] lr: 4.0000e-04 eta: 1:06:26 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 5.8603 loss: 1.9091 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.9091 2023/06/05 20:07:39 - mmengine - INFO - Epoch(train) [145][ 480/2569] lr: 4.0000e-04 eta: 1:06:21 time: 0.2660 data_time: 0.0077 memory: 5828 grad_norm: 5.8225 loss: 1.5749 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5749 2023/06/05 20:07:45 - mmengine - INFO - Epoch(train) [145][ 500/2569] lr: 4.0000e-04 eta: 1:06:15 time: 0.2661 data_time: 0.0075 memory: 5828 grad_norm: 5.8852 loss: 1.5220 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5220 2023/06/05 20:07:50 - mmengine - INFO - Epoch(train) [145][ 520/2569] lr: 4.0000e-04 eta: 1:06:10 time: 0.2677 data_time: 0.0075 memory: 5828 grad_norm: 5.7578 loss: 1.4870 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4870 2023/06/05 20:07:55 - mmengine - INFO - Epoch(train) [145][ 540/2569] lr: 4.0000e-04 eta: 1:06:05 time: 0.2738 data_time: 0.0075 memory: 5828 grad_norm: 5.8637 loss: 1.8439 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8439 2023/06/05 20:08:01 - mmengine - INFO - Epoch(train) [145][ 560/2569] lr: 4.0000e-04 eta: 1:06:00 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 6.0368 loss: 1.6476 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6476 2023/06/05 20:08:06 - mmengine - INFO - Epoch(train) [145][ 580/2569] lr: 4.0000e-04 eta: 1:05:54 time: 0.2705 data_time: 0.0075 memory: 5828 grad_norm: 5.8483 loss: 1.8480 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8480 2023/06/05 20:08:11 - mmengine - INFO - Epoch(train) [145][ 600/2569] lr: 4.0000e-04 eta: 1:05:49 time: 0.2633 data_time: 0.0076 memory: 5828 grad_norm: 5.8789 loss: 1.6674 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6674 2023/06/05 20:08:17 - mmengine - INFO - Epoch(train) [145][ 620/2569] lr: 4.0000e-04 eta: 1:05:44 time: 0.2700 data_time: 0.0074 memory: 5828 grad_norm: 5.8368 loss: 1.9159 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.9159 2023/06/05 20:08:22 - mmengine - INFO - Epoch(train) [145][ 640/2569] lr: 4.0000e-04 eta: 1:05:38 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 5.8055 loss: 1.3492 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3492 2023/06/05 20:08:28 - mmengine - INFO - Epoch(train) [145][ 660/2569] lr: 4.0000e-04 eta: 1:05:33 time: 0.2679 data_time: 0.0073 memory: 5828 grad_norm: 5.6962 loss: 1.5066 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5066 2023/06/05 20:08:33 - mmengine - INFO - Epoch(train) [145][ 680/2569] lr: 4.0000e-04 eta: 1:05:28 time: 0.2625 data_time: 0.0079 memory: 5828 grad_norm: 5.8631 loss: 1.5794 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5794 2023/06/05 20:08:38 - mmengine - INFO - Epoch(train) [145][ 700/2569] lr: 4.0000e-04 eta: 1:05:22 time: 0.2775 data_time: 0.0073 memory: 5828 grad_norm: 5.8725 loss: 1.7011 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7011 2023/06/05 20:08:44 - mmengine - INFO - Epoch(train) [145][ 720/2569] lr: 4.0000e-04 eta: 1:05:17 time: 0.2700 data_time: 0.0074 memory: 5828 grad_norm: 5.9048 loss: 1.6189 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6189 2023/06/05 20:08:49 - mmengine - INFO - Epoch(train) [145][ 740/2569] lr: 4.0000e-04 eta: 1:05:12 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 5.8615 loss: 1.6432 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6432 2023/06/05 20:08:54 - mmengine - INFO - Epoch(train) [145][ 760/2569] lr: 4.0000e-04 eta: 1:05:06 time: 0.2618 data_time: 0.0075 memory: 5828 grad_norm: 5.7055 loss: 1.5253 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5253 2023/06/05 20:09:00 - mmengine - INFO - Epoch(train) [145][ 780/2569] lr: 4.0000e-04 eta: 1:05:01 time: 0.2757 data_time: 0.0076 memory: 5828 grad_norm: 5.7374 loss: 1.5766 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5766 2023/06/05 20:09:05 - mmengine - INFO - Epoch(train) [145][ 800/2569] lr: 4.0000e-04 eta: 1:04:56 time: 0.2645 data_time: 0.0078 memory: 5828 grad_norm: 5.7468 loss: 1.3875 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.3875 2023/06/05 20:09:11 - mmengine - INFO - Epoch(train) [145][ 820/2569] lr: 4.0000e-04 eta: 1:04:50 time: 0.2741 data_time: 0.0087 memory: 5828 grad_norm: 5.8342 loss: 1.8089 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8089 2023/06/05 20:09:16 - mmengine - INFO - Epoch(train) [145][ 840/2569] lr: 4.0000e-04 eta: 1:04:45 time: 0.2676 data_time: 0.0073 memory: 5828 grad_norm: 5.7315 loss: 1.4953 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4953 2023/06/05 20:09:21 - mmengine - INFO - Epoch(train) [145][ 860/2569] lr: 4.0000e-04 eta: 1:04:40 time: 0.2620 data_time: 0.0076 memory: 5828 grad_norm: 5.7984 loss: 1.5309 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5309 2023/06/05 20:09:27 - mmengine - INFO - Epoch(train) [145][ 880/2569] lr: 4.0000e-04 eta: 1:04:34 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 5.7257 loss: 1.6167 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6167 2023/06/05 20:09:32 - mmengine - INFO - Epoch(train) [145][ 900/2569] lr: 4.0000e-04 eta: 1:04:29 time: 0.2696 data_time: 0.0078 memory: 5828 grad_norm: 5.8687 loss: 1.5834 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5834 2023/06/05 20:09:37 - mmengine - INFO - Epoch(train) [145][ 920/2569] lr: 4.0000e-04 eta: 1:04:24 time: 0.2638 data_time: 0.0076 memory: 5828 grad_norm: 5.8933 loss: 1.5717 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5717 2023/06/05 20:09:43 - mmengine - INFO - Epoch(train) [145][ 940/2569] lr: 4.0000e-04 eta: 1:04:18 time: 0.2698 data_time: 0.0071 memory: 5828 grad_norm: 5.7477 loss: 1.7387 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7387 2023/06/05 20:09:48 - mmengine - INFO - Epoch(train) [145][ 960/2569] lr: 4.0000e-04 eta: 1:04:13 time: 0.2736 data_time: 0.0073 memory: 5828 grad_norm: 5.8634 loss: 1.5277 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5277 2023/06/05 20:09:54 - mmengine - INFO - Epoch(train) [145][ 980/2569] lr: 4.0000e-04 eta: 1:04:08 time: 0.2737 data_time: 0.0073 memory: 5828 grad_norm: 5.8458 loss: 1.4337 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4337 2023/06/05 20:09:59 - mmengine - INFO - Epoch(train) [145][1000/2569] lr: 4.0000e-04 eta: 1:04:02 time: 0.2698 data_time: 0.0074 memory: 5828 grad_norm: 5.6144 loss: 1.4464 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4464 2023/06/05 20:10:04 - mmengine - INFO - Epoch(train) [145][1020/2569] lr: 4.0000e-04 eta: 1:03:57 time: 0.2663 data_time: 0.0075 memory: 5828 grad_norm: 5.7686 loss: 1.8626 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8626 2023/06/05 20:10:10 - mmengine - INFO - Epoch(train) [145][1040/2569] lr: 4.0000e-04 eta: 1:03:52 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 5.8346 loss: 1.2948 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2948 2023/06/05 20:10:15 - mmengine - INFO - Epoch(train) [145][1060/2569] lr: 4.0000e-04 eta: 1:03:46 time: 0.2654 data_time: 0.0073 memory: 5828 grad_norm: 5.9111 loss: 1.4018 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4018 2023/06/05 20:10:16 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:10:20 - mmengine - INFO - Epoch(train) [145][1080/2569] lr: 4.0000e-04 eta: 1:03:41 time: 0.2640 data_time: 0.0073 memory: 5828 grad_norm: 5.7134 loss: 1.5513 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5513 2023/06/05 20:10:26 - mmengine - INFO - Epoch(train) [145][1100/2569] lr: 4.0000e-04 eta: 1:03:36 time: 0.2723 data_time: 0.0074 memory: 5828 grad_norm: 5.6365 loss: 1.6282 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6282 2023/06/05 20:10:31 - mmengine - INFO - Epoch(train) [145][1120/2569] lr: 4.0000e-04 eta: 1:03:30 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 5.7633 loss: 1.5742 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5742 2023/06/05 20:10:37 - mmengine - INFO - Epoch(train) [145][1140/2569] lr: 4.0000e-04 eta: 1:03:25 time: 0.2799 data_time: 0.0074 memory: 5828 grad_norm: 5.8814 loss: 1.4112 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4112 2023/06/05 20:10:42 - mmengine - INFO - Epoch(train) [145][1160/2569] lr: 4.0000e-04 eta: 1:03:20 time: 0.2738 data_time: 0.0073 memory: 5828 grad_norm: 5.8639 loss: 1.7130 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7130 2023/06/05 20:10:48 - mmengine - INFO - Epoch(train) [145][1180/2569] lr: 4.0000e-04 eta: 1:03:14 time: 0.2740 data_time: 0.0073 memory: 5828 grad_norm: 5.9271 loss: 1.4562 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4562 2023/06/05 20:10:53 - mmengine - INFO - Epoch(train) [145][1200/2569] lr: 4.0000e-04 eta: 1:03:09 time: 0.2737 data_time: 0.0073 memory: 5828 grad_norm: 5.8314 loss: 1.5252 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5252 2023/06/05 20:10:59 - mmengine - INFO - Epoch(train) [145][1220/2569] lr: 4.0000e-04 eta: 1:03:04 time: 0.2719 data_time: 0.0071 memory: 5828 grad_norm: 5.8773 loss: 1.6437 top1_acc: 0.3750 top5_acc: 0.3750 loss_cls: 1.6437 2023/06/05 20:11:04 - mmengine - INFO - Epoch(train) [145][1240/2569] lr: 4.0000e-04 eta: 1:02:58 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 5.7308 loss: 1.7754 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7754 2023/06/05 20:11:09 - mmengine - INFO - Epoch(train) [145][1260/2569] lr: 4.0000e-04 eta: 1:02:53 time: 0.2693 data_time: 0.0071 memory: 5828 grad_norm: 5.8320 loss: 1.6982 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6982 2023/06/05 20:11:15 - mmengine - INFO - Epoch(train) [145][1280/2569] lr: 4.0000e-04 eta: 1:02:48 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 5.8629 loss: 1.9621 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.9621 2023/06/05 20:11:20 - mmengine - INFO - Epoch(train) [145][1300/2569] lr: 4.0000e-04 eta: 1:02:42 time: 0.2681 data_time: 0.0073 memory: 5828 grad_norm: 5.7595 loss: 1.5840 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5840 2023/06/05 20:11:25 - mmengine - INFO - Epoch(train) [145][1320/2569] lr: 4.0000e-04 eta: 1:02:37 time: 0.2677 data_time: 0.0075 memory: 5828 grad_norm: 5.8222 loss: 1.6117 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6117 2023/06/05 20:11:31 - mmengine - INFO - Epoch(train) [145][1340/2569] lr: 4.0000e-04 eta: 1:02:32 time: 0.2663 data_time: 0.0076 memory: 5828 grad_norm: 5.8475 loss: 1.6043 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6043 2023/06/05 20:11:36 - mmengine - INFO - Epoch(train) [145][1360/2569] lr: 4.0000e-04 eta: 1:02:26 time: 0.2792 data_time: 0.0075 memory: 5828 grad_norm: 5.8240 loss: 1.7092 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7092 2023/06/05 20:11:42 - mmengine - INFO - Epoch(train) [145][1380/2569] lr: 4.0000e-04 eta: 1:02:21 time: 0.2789 data_time: 0.0070 memory: 5828 grad_norm: 5.8972 loss: 1.6141 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6141 2023/06/05 20:11:47 - mmengine - INFO - Epoch(train) [145][1400/2569] lr: 4.0000e-04 eta: 1:02:16 time: 0.2730 data_time: 0.0073 memory: 5828 grad_norm: 5.6946 loss: 1.6174 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.6174 2023/06/05 20:11:53 - mmengine - INFO - Epoch(train) [145][1420/2569] lr: 4.0000e-04 eta: 1:02:10 time: 0.2735 data_time: 0.0074 memory: 5828 grad_norm: 5.7733 loss: 1.6124 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6124 2023/06/05 20:11:58 - mmengine - INFO - Epoch(train) [145][1440/2569] lr: 4.0000e-04 eta: 1:02:05 time: 0.2695 data_time: 0.0072 memory: 5828 grad_norm: 5.9256 loss: 1.4887 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4887 2023/06/05 20:12:04 - mmengine - INFO - Epoch(train) [145][1460/2569] lr: 4.0000e-04 eta: 1:02:00 time: 0.2761 data_time: 0.0077 memory: 5828 grad_norm: 5.7196 loss: 1.8561 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8561 2023/06/05 20:12:09 - mmengine - INFO - Epoch(train) [145][1480/2569] lr: 4.0000e-04 eta: 1:01:54 time: 0.2678 data_time: 0.0071 memory: 5828 grad_norm: 5.7102 loss: 1.7153 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7153 2023/06/05 20:12:14 - mmengine - INFO - Epoch(train) [145][1500/2569] lr: 4.0000e-04 eta: 1:01:49 time: 0.2634 data_time: 0.0073 memory: 5828 grad_norm: 5.8547 loss: 1.5480 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5480 2023/06/05 20:12:20 - mmengine - INFO - Epoch(train) [145][1520/2569] lr: 4.0000e-04 eta: 1:01:44 time: 0.2698 data_time: 0.0072 memory: 5828 grad_norm: 5.8018 loss: 1.5704 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5704 2023/06/05 20:12:25 - mmengine - INFO - Epoch(train) [145][1540/2569] lr: 4.0000e-04 eta: 1:01:38 time: 0.2626 data_time: 0.0072 memory: 5828 grad_norm: 5.7716 loss: 1.8376 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8376 2023/06/05 20:12:30 - mmengine - INFO - Epoch(train) [145][1560/2569] lr: 4.0000e-04 eta: 1:01:33 time: 0.2717 data_time: 0.0071 memory: 5828 grad_norm: 5.8972 loss: 1.5516 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5516 2023/06/05 20:12:36 - mmengine - INFO - Epoch(train) [145][1580/2569] lr: 4.0000e-04 eta: 1:01:28 time: 0.2713 data_time: 0.0072 memory: 5828 grad_norm: 5.8550 loss: 1.5409 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5409 2023/06/05 20:12:41 - mmengine - INFO - Epoch(train) [145][1600/2569] lr: 4.0000e-04 eta: 1:01:22 time: 0.2636 data_time: 0.0078 memory: 5828 grad_norm: 5.7996 loss: 1.3933 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3933 2023/06/05 20:12:47 - mmengine - INFO - Epoch(train) [145][1620/2569] lr: 4.0000e-04 eta: 1:01:17 time: 0.2745 data_time: 0.0073 memory: 5828 grad_norm: 5.7992 loss: 1.6564 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6564 2023/06/05 20:12:52 - mmengine - INFO - Epoch(train) [145][1640/2569] lr: 4.0000e-04 eta: 1:01:12 time: 0.2735 data_time: 0.0073 memory: 5828 grad_norm: 5.8555 loss: 1.7671 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7671 2023/06/05 20:12:58 - mmengine - INFO - Epoch(train) [145][1660/2569] lr: 4.0000e-04 eta: 1:01:06 time: 0.2719 data_time: 0.0073 memory: 5828 grad_norm: 5.8586 loss: 1.5243 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5243 2023/06/05 20:13:03 - mmengine - INFO - Epoch(train) [145][1680/2569] lr: 4.0000e-04 eta: 1:01:01 time: 0.2628 data_time: 0.0076 memory: 5828 grad_norm: 5.8419 loss: 1.4691 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4691 2023/06/05 20:13:08 - mmengine - INFO - Epoch(train) [145][1700/2569] lr: 4.0000e-04 eta: 1:00:56 time: 0.2728 data_time: 0.0075 memory: 5828 grad_norm: 5.7895 loss: 1.7974 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7974 2023/06/05 20:13:14 - mmengine - INFO - Epoch(train) [145][1720/2569] lr: 4.0000e-04 eta: 1:00:50 time: 0.2711 data_time: 0.0074 memory: 5828 grad_norm: 5.8271 loss: 1.5975 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5975 2023/06/05 20:13:19 - mmengine - INFO - Epoch(train) [145][1740/2569] lr: 4.0000e-04 eta: 1:00:45 time: 0.2645 data_time: 0.0078 memory: 5828 grad_norm: 5.7064 loss: 1.5098 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5098 2023/06/05 20:13:25 - mmengine - INFO - Epoch(train) [145][1760/2569] lr: 4.0000e-04 eta: 1:00:40 time: 0.2793 data_time: 0.0075 memory: 5828 grad_norm: 5.7566 loss: 1.5754 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5754 2023/06/05 20:13:30 - mmengine - INFO - Epoch(train) [145][1780/2569] lr: 4.0000e-04 eta: 1:00:34 time: 0.2613 data_time: 0.0070 memory: 5828 grad_norm: 5.7851 loss: 1.6124 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6124 2023/06/05 20:13:35 - mmengine - INFO - Epoch(train) [145][1800/2569] lr: 4.0000e-04 eta: 1:00:29 time: 0.2623 data_time: 0.0072 memory: 5828 grad_norm: 5.8826 loss: 1.4328 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4328 2023/06/05 20:13:41 - mmengine - INFO - Epoch(train) [145][1820/2569] lr: 4.0000e-04 eta: 1:00:24 time: 0.2685 data_time: 0.0076 memory: 5828 grad_norm: 5.7768 loss: 1.5682 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5682 2023/06/05 20:13:46 - mmengine - INFO - Epoch(train) [145][1840/2569] lr: 4.0000e-04 eta: 1:00:18 time: 0.2662 data_time: 0.0073 memory: 5828 grad_norm: 5.8550 loss: 1.7619 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7619 2023/06/05 20:13:51 - mmengine - INFO - Epoch(train) [145][1860/2569] lr: 4.0000e-04 eta: 1:00:13 time: 0.2704 data_time: 0.0073 memory: 5828 grad_norm: 5.6484 loss: 1.3489 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3489 2023/06/05 20:13:57 - mmengine - INFO - Epoch(train) [145][1880/2569] lr: 4.0000e-04 eta: 1:00:08 time: 0.2757 data_time: 0.0071 memory: 5828 grad_norm: 5.7126 loss: 1.6886 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6886 2023/06/05 20:14:02 - mmengine - INFO - Epoch(train) [145][1900/2569] lr: 4.0000e-04 eta: 1:00:02 time: 0.2721 data_time: 0.0075 memory: 5828 grad_norm: 5.8277 loss: 1.5245 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5245 2023/06/05 20:14:08 - mmengine - INFO - Epoch(train) [145][1920/2569] lr: 4.0000e-04 eta: 0:59:57 time: 0.2621 data_time: 0.0072 memory: 5828 grad_norm: 5.8515 loss: 1.6916 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6916 2023/06/05 20:14:13 - mmengine - INFO - Epoch(train) [145][1940/2569] lr: 4.0000e-04 eta: 0:59:52 time: 0.2697 data_time: 0.0073 memory: 5828 grad_norm: 5.8044 loss: 1.6201 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.6201 2023/06/05 20:14:18 - mmengine - INFO - Epoch(train) [145][1960/2569] lr: 4.0000e-04 eta: 0:59:46 time: 0.2711 data_time: 0.0075 memory: 5828 grad_norm: 5.7433 loss: 1.5196 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5196 2023/06/05 20:14:24 - mmengine - INFO - Epoch(train) [145][1980/2569] lr: 4.0000e-04 eta: 0:59:41 time: 0.2621 data_time: 0.0075 memory: 5828 grad_norm: 5.7542 loss: 1.4825 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4825 2023/06/05 20:14:29 - mmengine - INFO - Epoch(train) [145][2000/2569] lr: 4.0000e-04 eta: 0:59:36 time: 0.2690 data_time: 0.0072 memory: 5828 grad_norm: 5.7544 loss: 1.7867 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7867 2023/06/05 20:14:34 - mmengine - INFO - Epoch(train) [145][2020/2569] lr: 4.0000e-04 eta: 0:59:30 time: 0.2626 data_time: 0.0074 memory: 5828 grad_norm: 5.8471 loss: 1.2576 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2576 2023/06/05 20:14:40 - mmengine - INFO - Epoch(train) [145][2040/2569] lr: 4.0000e-04 eta: 0:59:25 time: 0.2723 data_time: 0.0072 memory: 5828 grad_norm: 5.7334 loss: 1.6673 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6673 2023/06/05 20:14:45 - mmengine - INFO - Epoch(train) [145][2060/2569] lr: 4.0000e-04 eta: 0:59:20 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 5.7859 loss: 1.3722 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.3722 2023/06/05 20:14:46 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:14:51 - mmengine - INFO - Epoch(train) [145][2080/2569] lr: 4.0000e-04 eta: 0:59:14 time: 0.2723 data_time: 0.0073 memory: 5828 grad_norm: 5.7884 loss: 1.5846 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5846 2023/06/05 20:14:56 - mmengine - INFO - Epoch(train) [145][2100/2569] lr: 4.0000e-04 eta: 0:59:09 time: 0.2714 data_time: 0.0072 memory: 5828 grad_norm: 5.8166 loss: 1.5972 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5972 2023/06/05 20:15:01 - mmengine - INFO - Epoch(train) [145][2120/2569] lr: 4.0000e-04 eta: 0:59:04 time: 0.2656 data_time: 0.0076 memory: 5828 grad_norm: 5.9031 loss: 1.4656 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4656 2023/06/05 20:15:07 - mmengine - INFO - Epoch(train) [145][2140/2569] lr: 4.0000e-04 eta: 0:58:58 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 5.7845 loss: 1.4944 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4944 2023/06/05 20:15:12 - mmengine - INFO - Epoch(train) [145][2160/2569] lr: 4.0000e-04 eta: 0:58:53 time: 0.2674 data_time: 0.0075 memory: 5828 grad_norm: 5.8193 loss: 1.8455 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.8455 2023/06/05 20:15:17 - mmengine - INFO - Epoch(train) [145][2180/2569] lr: 4.0000e-04 eta: 0:58:48 time: 0.2621 data_time: 0.0072 memory: 5828 grad_norm: 5.8129 loss: 1.7200 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7200 2023/06/05 20:15:23 - mmengine - INFO - Epoch(train) [145][2200/2569] lr: 4.0000e-04 eta: 0:58:42 time: 0.2733 data_time: 0.0074 memory: 5828 grad_norm: 5.8088 loss: 1.4433 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4433 2023/06/05 20:15:28 - mmengine - INFO - Epoch(train) [145][2220/2569] lr: 4.0000e-04 eta: 0:58:37 time: 0.2784 data_time: 0.0073 memory: 5828 grad_norm: 5.8200 loss: 1.4268 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4268 2023/06/05 20:15:34 - mmengine - INFO - Epoch(train) [145][2240/2569] lr: 4.0000e-04 eta: 0:58:32 time: 0.2677 data_time: 0.0071 memory: 5828 grad_norm: 5.8521 loss: 1.6840 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6840 2023/06/05 20:15:39 - mmengine - INFO - Epoch(train) [145][2260/2569] lr: 4.0000e-04 eta: 0:58:26 time: 0.2676 data_time: 0.0073 memory: 5828 grad_norm: 5.7630 loss: 1.7677 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7677 2023/06/05 20:15:45 - mmengine - INFO - Epoch(train) [145][2280/2569] lr: 4.0000e-04 eta: 0:58:21 time: 0.2694 data_time: 0.0071 memory: 5828 grad_norm: 5.8182 loss: 1.5065 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5065 2023/06/05 20:15:50 - mmengine - INFO - Epoch(train) [145][2300/2569] lr: 4.0000e-04 eta: 0:58:16 time: 0.2615 data_time: 0.0074 memory: 5828 grad_norm: 5.8220 loss: 1.7671 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7671 2023/06/05 20:15:55 - mmengine - INFO - Epoch(train) [145][2320/2569] lr: 4.0000e-04 eta: 0:58:10 time: 0.2794 data_time: 0.0074 memory: 5828 grad_norm: 5.6350 loss: 1.3708 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3708 2023/06/05 20:16:01 - mmengine - INFO - Epoch(train) [145][2340/2569] lr: 4.0000e-04 eta: 0:58:05 time: 0.2753 data_time: 0.0072 memory: 5828 grad_norm: 5.6522 loss: 1.4776 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4776 2023/06/05 20:16:06 - mmengine - INFO - Epoch(train) [145][2360/2569] lr: 4.0000e-04 eta: 0:58:00 time: 0.2709 data_time: 0.0074 memory: 5828 grad_norm: 5.7023 loss: 1.4063 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4063 2023/06/05 20:16:12 - mmengine - INFO - Epoch(train) [145][2380/2569] lr: 4.0000e-04 eta: 0:57:54 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 5.8077 loss: 1.3971 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3971 2023/06/05 20:16:17 - mmengine - INFO - Epoch(train) [145][2400/2569] lr: 4.0000e-04 eta: 0:57:49 time: 0.2726 data_time: 0.0075 memory: 5828 grad_norm: 5.8503 loss: 1.8677 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8677 2023/06/05 20:16:22 - mmengine - INFO - Epoch(train) [145][2420/2569] lr: 4.0000e-04 eta: 0:57:44 time: 0.2675 data_time: 0.0074 memory: 5828 grad_norm: 5.8465 loss: 1.7954 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7954 2023/06/05 20:16:28 - mmengine - INFO - Epoch(train) [145][2440/2569] lr: 4.0000e-04 eta: 0:57:38 time: 0.2611 data_time: 0.0071 memory: 5828 grad_norm: 5.8066 loss: 1.9534 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.9534 2023/06/05 20:16:33 - mmengine - INFO - Epoch(train) [145][2460/2569] lr: 4.0000e-04 eta: 0:57:33 time: 0.2618 data_time: 0.0074 memory: 5828 grad_norm: 5.8111 loss: 1.3905 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3905 2023/06/05 20:16:38 - mmengine - INFO - Epoch(train) [145][2480/2569] lr: 4.0000e-04 eta: 0:57:28 time: 0.2623 data_time: 0.0073 memory: 5828 grad_norm: 5.9141 loss: 1.4907 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4907 2023/06/05 20:16:43 - mmengine - INFO - Epoch(train) [145][2500/2569] lr: 4.0000e-04 eta: 0:57:22 time: 0.2635 data_time: 0.0081 memory: 5828 grad_norm: 5.8163 loss: 1.3459 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.3459 2023/06/05 20:16:49 - mmengine - INFO - Epoch(train) [145][2520/2569] lr: 4.0000e-04 eta: 0:57:17 time: 0.2670 data_time: 0.0075 memory: 5828 grad_norm: 5.8628 loss: 1.5163 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5163 2023/06/05 20:16:54 - mmengine - INFO - Epoch(train) [145][2540/2569] lr: 4.0000e-04 eta: 0:57:12 time: 0.2729 data_time: 0.0074 memory: 5828 grad_norm: 5.7648 loss: 1.5410 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5410 2023/06/05 20:17:00 - mmengine - INFO - Epoch(train) [145][2560/2569] lr: 4.0000e-04 eta: 0:57:06 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 5.8912 loss: 1.5731 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5731 2023/06/05 20:17:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:17:02 - mmengine - INFO - Epoch(train) [145][2569/2569] lr: 4.0000e-04 eta: 0:57:04 time: 0.2548 data_time: 0.0072 memory: 5828 grad_norm: 5.9874 loss: 1.4148 top1_acc: 0.8333 top5_acc: 1.0000 loss_cls: 1.4148 2023/06/05 20:17:06 - mmengine - INFO - Epoch(val) [145][ 20/260] eta: 0:00:44 time: 0.1861 data_time: 0.1271 memory: 1238 2023/06/05 20:17:08 - mmengine - INFO - Epoch(val) [145][ 40/260] eta: 0:00:35 time: 0.1385 data_time: 0.0799 memory: 1238 2023/06/05 20:17:11 - mmengine - INFO - Epoch(val) [145][ 60/260] eta: 0:00:31 time: 0.1430 data_time: 0.0843 memory: 1238 2023/06/05 20:17:14 - mmengine - INFO - Epoch(val) [145][ 80/260] eta: 0:00:26 time: 0.1316 data_time: 0.0729 memory: 1238 2023/06/05 20:17:17 - mmengine - INFO - Epoch(val) [145][100/260] eta: 0:00:24 time: 0.1572 data_time: 0.0983 memory: 1238 2023/06/05 20:17:20 - mmengine - INFO - Epoch(val) [145][120/260] eta: 0:00:20 time: 0.1387 data_time: 0.0802 memory: 1238 2023/06/05 20:17:22 - mmengine - INFO - Epoch(val) [145][140/260] eta: 0:00:17 time: 0.1225 data_time: 0.0635 memory: 1238 2023/06/05 20:17:25 - mmengine - INFO - Epoch(val) [145][160/260] eta: 0:00:14 time: 0.1331 data_time: 0.0739 memory: 1238 2023/06/05 20:17:28 - mmengine - INFO - Epoch(val) [145][180/260] eta: 0:00:11 time: 0.1397 data_time: 0.0809 memory: 1238 2023/06/05 20:17:30 - mmengine - INFO - Epoch(val) [145][200/260] eta: 0:00:08 time: 0.1282 data_time: 0.0689 memory: 1238 2023/06/05 20:17:33 - mmengine - INFO - Epoch(val) [145][220/260] eta: 0:00:05 time: 0.1552 data_time: 0.0969 memory: 1238 2023/06/05 20:17:36 - mmengine - INFO - Epoch(val) [145][240/260] eta: 0:00:02 time: 0.1296 data_time: 0.0715 memory: 1238 2023/06/05 20:17:39 - mmengine - INFO - Epoch(val) [145][260/260] eta: 0:00:00 time: 0.1363 data_time: 0.0797 memory: 1238 2023/06/05 20:17:47 - mmengine - INFO - Epoch(val) [145][260/260] acc/top1: 0.6424 acc/top5: 0.8455 acc/mean1: 0.6357 data_time: 0.0826 time: 0.1411 2023/06/05 20:17:47 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_125.pth is removed 2023/06/05 20:17:48 - mmengine - INFO - The best checkpoint with 0.6424 acc/top1 at 145 epoch is saved to best_acc_top1_epoch_145.pth. 2023/06/05 20:17:54 - mmengine - INFO - Epoch(train) [146][ 20/2569] lr: 4.0000e-04 eta: 0:56:59 time: 0.3011 data_time: 0.0460 memory: 5828 grad_norm: 5.8958 loss: 1.5749 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5749 2023/06/05 20:18:00 - mmengine - INFO - Epoch(train) [146][ 40/2569] lr: 4.0000e-04 eta: 0:56:53 time: 0.2643 data_time: 0.0070 memory: 5828 grad_norm: 5.9061 loss: 1.6371 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6371 2023/06/05 20:18:05 - mmengine - INFO - Epoch(train) [146][ 60/2569] lr: 4.0000e-04 eta: 0:56:48 time: 0.2688 data_time: 0.0071 memory: 5828 grad_norm: 5.8986 loss: 1.4935 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4935 2023/06/05 20:18:10 - mmengine - INFO - Epoch(train) [146][ 80/2569] lr: 4.0000e-04 eta: 0:56:43 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 5.8751 loss: 1.5341 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5341 2023/06/05 20:18:16 - mmengine - INFO - Epoch(train) [146][ 100/2569] lr: 4.0000e-04 eta: 0:56:37 time: 0.2699 data_time: 0.0074 memory: 5828 grad_norm: 5.7766 loss: 1.5644 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5644 2023/06/05 20:18:21 - mmengine - INFO - Epoch(train) [146][ 120/2569] lr: 4.0000e-04 eta: 0:56:32 time: 0.2651 data_time: 0.0076 memory: 5828 grad_norm: 5.7653 loss: 1.4653 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4653 2023/06/05 20:18:26 - mmengine - INFO - Epoch(train) [146][ 140/2569] lr: 4.0000e-04 eta: 0:56:27 time: 0.2627 data_time: 0.0077 memory: 5828 grad_norm: 5.8361 loss: 1.5925 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5925 2023/06/05 20:18:32 - mmengine - INFO - Epoch(train) [146][ 160/2569] lr: 4.0000e-04 eta: 0:56:21 time: 0.2636 data_time: 0.0076 memory: 5828 grad_norm: 5.8272 loss: 1.7619 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7619 2023/06/05 20:18:37 - mmengine - INFO - Epoch(train) [146][ 180/2569] lr: 4.0000e-04 eta: 0:56:16 time: 0.2630 data_time: 0.0072 memory: 5828 grad_norm: 5.7824 loss: 1.5566 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5566 2023/06/05 20:18:42 - mmengine - INFO - Epoch(train) [146][ 200/2569] lr: 4.0000e-04 eta: 0:56:11 time: 0.2702 data_time: 0.0072 memory: 5828 grad_norm: 5.8743 loss: 1.2138 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2138 2023/06/05 20:18:48 - mmengine - INFO - Epoch(train) [146][ 220/2569] lr: 4.0000e-04 eta: 0:56:05 time: 0.2655 data_time: 0.0071 memory: 5828 grad_norm: 5.9209 loss: 1.7375 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7375 2023/06/05 20:18:53 - mmengine - INFO - Epoch(train) [146][ 240/2569] lr: 4.0000e-04 eta: 0:56:00 time: 0.2617 data_time: 0.0072 memory: 5828 grad_norm: 5.8677 loss: 1.6260 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6260 2023/06/05 20:18:58 - mmengine - INFO - Epoch(train) [146][ 260/2569] lr: 4.0000e-04 eta: 0:55:55 time: 0.2702 data_time: 0.0071 memory: 5828 grad_norm: 5.7825 loss: 1.7528 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7528 2023/06/05 20:19:04 - mmengine - INFO - Epoch(train) [146][ 280/2569] lr: 4.0000e-04 eta: 0:55:49 time: 0.2685 data_time: 0.0074 memory: 5828 grad_norm: 5.9483 loss: 1.5578 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5578 2023/06/05 20:19:09 - mmengine - INFO - Epoch(train) [146][ 300/2569] lr: 4.0000e-04 eta: 0:55:44 time: 0.2667 data_time: 0.0070 memory: 5828 grad_norm: 5.9393 loss: 1.4226 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4226 2023/06/05 20:19:14 - mmengine - INFO - Epoch(train) [146][ 320/2569] lr: 4.0000e-04 eta: 0:55:39 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 5.7715 loss: 1.6131 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6131 2023/06/05 20:19:20 - mmengine - INFO - Epoch(train) [146][ 340/2569] lr: 4.0000e-04 eta: 0:55:33 time: 0.2680 data_time: 0.0077 memory: 5828 grad_norm: 5.8466 loss: 1.6739 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6739 2023/06/05 20:19:25 - mmengine - INFO - Epoch(train) [146][ 360/2569] lr: 4.0000e-04 eta: 0:55:28 time: 0.2650 data_time: 0.0072 memory: 5828 grad_norm: 5.7845 loss: 1.3477 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.3477 2023/06/05 20:19:31 - mmengine - INFO - Epoch(train) [146][ 380/2569] lr: 4.0000e-04 eta: 0:55:23 time: 0.2701 data_time: 0.0070 memory: 5828 grad_norm: 5.7540 loss: 1.4976 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4976 2023/06/05 20:19:36 - mmengine - INFO - Epoch(train) [146][ 400/2569] lr: 4.0000e-04 eta: 0:55:17 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 5.8080 loss: 1.2335 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2335 2023/06/05 20:19:41 - mmengine - INFO - Epoch(train) [146][ 420/2569] lr: 4.0000e-04 eta: 0:55:12 time: 0.2735 data_time: 0.0070 memory: 5828 grad_norm: 5.8384 loss: 1.5046 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5046 2023/06/05 20:19:47 - mmengine - INFO - Epoch(train) [146][ 440/2569] lr: 4.0000e-04 eta: 0:55:07 time: 0.2635 data_time: 0.0072 memory: 5828 grad_norm: 5.8101 loss: 1.4414 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4414 2023/06/05 20:19:52 - mmengine - INFO - Epoch(train) [146][ 460/2569] lr: 4.0000e-04 eta: 0:55:01 time: 0.2751 data_time: 0.0074 memory: 5828 grad_norm: 5.7754 loss: 1.3802 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3802 2023/06/05 20:19:58 - mmengine - INFO - Epoch(train) [146][ 480/2569] lr: 4.0000e-04 eta: 0:54:56 time: 0.2747 data_time: 0.0071 memory: 5828 grad_norm: 5.8910 loss: 1.7105 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7105 2023/06/05 20:20:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:20:03 - mmengine - INFO - Epoch(train) [146][ 500/2569] lr: 4.0000e-04 eta: 0:54:51 time: 0.2794 data_time: 0.0069 memory: 5828 grad_norm: 5.8605 loss: 1.3947 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.3947 2023/06/05 20:20:08 - mmengine - INFO - Epoch(train) [146][ 520/2569] lr: 4.0000e-04 eta: 0:54:45 time: 0.2634 data_time: 0.0073 memory: 5828 grad_norm: 5.9347 loss: 1.7725 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7725 2023/06/05 20:20:14 - mmengine - INFO - Epoch(train) [146][ 540/2569] lr: 4.0000e-04 eta: 0:54:40 time: 0.2700 data_time: 0.0074 memory: 5828 grad_norm: 5.7804 loss: 1.5150 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5150 2023/06/05 20:20:19 - mmengine - INFO - Epoch(train) [146][ 560/2569] lr: 4.0000e-04 eta: 0:54:35 time: 0.2672 data_time: 0.0079 memory: 5828 grad_norm: 5.8075 loss: 1.3520 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3520 2023/06/05 20:20:25 - mmengine - INFO - Epoch(train) [146][ 580/2569] lr: 4.0000e-04 eta: 0:54:29 time: 0.2675 data_time: 0.0072 memory: 5828 grad_norm: 5.8301 loss: 1.3936 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.3936 2023/06/05 20:20:30 - mmengine - INFO - Epoch(train) [146][ 600/2569] lr: 4.0000e-04 eta: 0:54:24 time: 0.2731 data_time: 0.0072 memory: 5828 grad_norm: 5.9142 loss: 1.6031 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6031 2023/06/05 20:20:35 - mmengine - INFO - Epoch(train) [146][ 620/2569] lr: 4.0000e-04 eta: 0:54:19 time: 0.2678 data_time: 0.0078 memory: 5828 grad_norm: 5.8230 loss: 1.4875 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.4875 2023/06/05 20:20:41 - mmengine - INFO - Epoch(train) [146][ 640/2569] lr: 4.0000e-04 eta: 0:54:13 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 6.0021 loss: 1.7322 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7322 2023/06/05 20:20:46 - mmengine - INFO - Epoch(train) [146][ 660/2569] lr: 4.0000e-04 eta: 0:54:08 time: 0.2699 data_time: 0.0073 memory: 5828 grad_norm: 5.7754 loss: 1.3993 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3993 2023/06/05 20:20:51 - mmengine - INFO - Epoch(train) [146][ 680/2569] lr: 4.0000e-04 eta: 0:54:03 time: 0.2626 data_time: 0.0071 memory: 5828 grad_norm: 5.8017 loss: 1.4605 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4605 2023/06/05 20:20:57 - mmengine - INFO - Epoch(train) [146][ 700/2569] lr: 4.0000e-04 eta: 0:53:57 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 5.9172 loss: 1.8254 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8254 2023/06/05 20:21:02 - mmengine - INFO - Epoch(train) [146][ 720/2569] lr: 4.0000e-04 eta: 0:53:52 time: 0.2754 data_time: 0.0074 memory: 5828 grad_norm: 5.9169 loss: 1.6717 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6717 2023/06/05 20:21:08 - mmengine - INFO - Epoch(train) [146][ 740/2569] lr: 4.0000e-04 eta: 0:53:47 time: 0.2739 data_time: 0.0072 memory: 5828 grad_norm: 5.7818 loss: 1.3352 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3352 2023/06/05 20:21:13 - mmengine - INFO - Epoch(train) [146][ 760/2569] lr: 4.0000e-04 eta: 0:53:42 time: 0.2747 data_time: 0.0072 memory: 5828 grad_norm: 5.9403 loss: 1.5899 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5899 2023/06/05 20:21:19 - mmengine - INFO - Epoch(train) [146][ 780/2569] lr: 4.0000e-04 eta: 0:53:36 time: 0.2725 data_time: 0.0070 memory: 5828 grad_norm: 5.7962 loss: 1.7909 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7909 2023/06/05 20:21:24 - mmengine - INFO - Epoch(train) [146][ 800/2569] lr: 4.0000e-04 eta: 0:53:31 time: 0.2632 data_time: 0.0071 memory: 5828 grad_norm: 5.8353 loss: 1.7765 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7765 2023/06/05 20:21:30 - mmengine - INFO - Epoch(train) [146][ 820/2569] lr: 4.0000e-04 eta: 0:53:26 time: 0.2734 data_time: 0.0073 memory: 5828 grad_norm: 5.8666 loss: 1.6947 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6947 2023/06/05 20:21:35 - mmengine - INFO - Epoch(train) [146][ 840/2569] lr: 4.0000e-04 eta: 0:53:20 time: 0.2629 data_time: 0.0074 memory: 5828 grad_norm: 5.7813 loss: 1.7383 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7383 2023/06/05 20:21:40 - mmengine - INFO - Epoch(train) [146][ 860/2569] lr: 4.0000e-04 eta: 0:53:15 time: 0.2761 data_time: 0.0074 memory: 5828 grad_norm: 5.8763 loss: 1.7181 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7181 2023/06/05 20:21:46 - mmengine - INFO - Epoch(train) [146][ 880/2569] lr: 4.0000e-04 eta: 0:53:10 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 5.8798 loss: 1.7252 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7252 2023/06/05 20:21:51 - mmengine - INFO - Epoch(train) [146][ 900/2569] lr: 4.0000e-04 eta: 0:53:04 time: 0.2652 data_time: 0.0072 memory: 5828 grad_norm: 5.8203 loss: 1.5028 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5028 2023/06/05 20:21:57 - mmengine - INFO - Epoch(train) [146][ 920/2569] lr: 4.0000e-04 eta: 0:52:59 time: 0.2750 data_time: 0.0072 memory: 5828 grad_norm: 5.8568 loss: 1.6885 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6885 2023/06/05 20:22:02 - mmengine - INFO - Epoch(train) [146][ 940/2569] lr: 4.0000e-04 eta: 0:52:54 time: 0.2795 data_time: 0.0073 memory: 5828 grad_norm: 5.9376 loss: 1.5004 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5004 2023/06/05 20:22:08 - mmengine - INFO - Epoch(train) [146][ 960/2569] lr: 4.0000e-04 eta: 0:52:48 time: 0.2768 data_time: 0.0075 memory: 5828 grad_norm: 5.7918 loss: 1.7929 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7929 2023/06/05 20:22:13 - mmengine - INFO - Epoch(train) [146][ 980/2569] lr: 4.0000e-04 eta: 0:52:43 time: 0.2760 data_time: 0.0072 memory: 5828 grad_norm: 5.8553 loss: 1.3387 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.3387 2023/06/05 20:22:19 - mmengine - INFO - Epoch(train) [146][1000/2569] lr: 4.0000e-04 eta: 0:52:38 time: 0.2750 data_time: 0.0074 memory: 5828 grad_norm: 5.9504 loss: 1.5546 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5546 2023/06/05 20:22:24 - mmengine - INFO - Epoch(train) [146][1020/2569] lr: 4.0000e-04 eta: 0:52:32 time: 0.2721 data_time: 0.0073 memory: 5828 grad_norm: 5.8496 loss: 1.4398 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.4398 2023/06/05 20:22:29 - mmengine - INFO - Epoch(train) [146][1040/2569] lr: 4.0000e-04 eta: 0:52:27 time: 0.2655 data_time: 0.0074 memory: 5828 grad_norm: 5.8313 loss: 1.4406 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.4406 2023/06/05 20:22:35 - mmengine - INFO - Epoch(train) [146][1060/2569] lr: 4.0000e-04 eta: 0:52:22 time: 0.2812 data_time: 0.0075 memory: 5828 grad_norm: 5.8471 loss: 1.6397 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.6397 2023/06/05 20:22:40 - mmengine - INFO - Epoch(train) [146][1080/2569] lr: 4.0000e-04 eta: 0:52:16 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 5.7999 loss: 1.7545 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.7545 2023/06/05 20:22:46 - mmengine - INFO - Epoch(train) [146][1100/2569] lr: 4.0000e-04 eta: 0:52:11 time: 0.2705 data_time: 0.0072 memory: 5828 grad_norm: 5.8772 loss: 1.3817 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3817 2023/06/05 20:22:51 - mmengine - INFO - Epoch(train) [146][1120/2569] lr: 4.0000e-04 eta: 0:52:06 time: 0.2698 data_time: 0.0074 memory: 5828 grad_norm: 5.8388 loss: 1.7096 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7096 2023/06/05 20:22:57 - mmengine - INFO - Epoch(train) [146][1140/2569] lr: 4.0000e-04 eta: 0:52:00 time: 0.2655 data_time: 0.0073 memory: 5828 grad_norm: 5.8949 loss: 1.8551 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8551 2023/06/05 20:23:02 - mmengine - INFO - Epoch(train) [146][1160/2569] lr: 4.0000e-04 eta: 0:51:55 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 5.8746 loss: 1.7936 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7936 2023/06/05 20:23:07 - mmengine - INFO - Epoch(train) [146][1180/2569] lr: 4.0000e-04 eta: 0:51:50 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 5.6778 loss: 1.5264 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5264 2023/06/05 20:23:13 - mmengine - INFO - Epoch(train) [146][1200/2569] lr: 4.0000e-04 eta: 0:51:44 time: 0.2779 data_time: 0.0074 memory: 5828 grad_norm: 5.8496 loss: 1.5007 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5007 2023/06/05 20:23:18 - mmengine - INFO - Epoch(train) [146][1220/2569] lr: 4.0000e-04 eta: 0:51:39 time: 0.2653 data_time: 0.0072 memory: 5828 grad_norm: 5.9141 loss: 1.5812 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.5812 2023/06/05 20:23:24 - mmengine - INFO - Epoch(train) [146][1240/2569] lr: 4.0000e-04 eta: 0:51:34 time: 0.2722 data_time: 0.0072 memory: 5828 grad_norm: 5.8286 loss: 1.5866 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5866 2023/06/05 20:23:29 - mmengine - INFO - Epoch(train) [146][1260/2569] lr: 4.0000e-04 eta: 0:51:28 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 5.7376 loss: 1.3444 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.3444 2023/06/05 20:23:34 - mmengine - INFO - Epoch(train) [146][1280/2569] lr: 4.0000e-04 eta: 0:51:23 time: 0.2707 data_time: 0.0073 memory: 5828 grad_norm: 5.8140 loss: 1.3536 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.3536 2023/06/05 20:23:40 - mmengine - INFO - Epoch(train) [146][1300/2569] lr: 4.0000e-04 eta: 0:51:18 time: 0.2737 data_time: 0.0071 memory: 5828 grad_norm: 5.9298 loss: 1.6132 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6132 2023/06/05 20:23:45 - mmengine - INFO - Epoch(train) [146][1320/2569] lr: 4.0000e-04 eta: 0:51:12 time: 0.2718 data_time: 0.0072 memory: 5828 grad_norm: 5.8400 loss: 1.4931 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4931 2023/06/05 20:23:51 - mmengine - INFO - Epoch(train) [146][1340/2569] lr: 4.0000e-04 eta: 0:51:07 time: 0.2664 data_time: 0.0072 memory: 5828 grad_norm: 5.8976 loss: 1.8087 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8087 2023/06/05 20:23:56 - mmengine - INFO - Epoch(train) [146][1360/2569] lr: 4.0000e-04 eta: 0:51:02 time: 0.2716 data_time: 0.0077 memory: 5828 grad_norm: 5.8728 loss: 1.5341 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5341 2023/06/05 20:24:01 - mmengine - INFO - Epoch(train) [146][1380/2569] lr: 4.0000e-04 eta: 0:50:56 time: 0.2622 data_time: 0.0071 memory: 5828 grad_norm: 5.8326 loss: 1.6669 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6669 2023/06/05 20:24:07 - mmengine - INFO - Epoch(train) [146][1400/2569] lr: 4.0000e-04 eta: 0:50:51 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 5.8169 loss: 1.4504 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4504 2023/06/05 20:24:12 - mmengine - INFO - Epoch(train) [146][1420/2569] lr: 4.0000e-04 eta: 0:50:46 time: 0.2653 data_time: 0.0076 memory: 5828 grad_norm: 5.8825 loss: 1.6507 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6507 2023/06/05 20:24:18 - mmengine - INFO - Epoch(train) [146][1440/2569] lr: 4.0000e-04 eta: 0:50:40 time: 0.2802 data_time: 0.0073 memory: 5828 grad_norm: 5.8099 loss: 1.4626 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4626 2023/06/05 20:24:23 - mmengine - INFO - Epoch(train) [146][1460/2569] lr: 4.0000e-04 eta: 0:50:35 time: 0.2708 data_time: 0.0075 memory: 5828 grad_norm: 5.8317 loss: 2.0012 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 2.0012 2023/06/05 20:24:28 - mmengine - INFO - Epoch(train) [146][1480/2569] lr: 4.0000e-04 eta: 0:50:30 time: 0.2641 data_time: 0.0071 memory: 5828 grad_norm: 5.8937 loss: 1.5879 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5879 2023/06/05 20:24:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:24:34 - mmengine - INFO - Epoch(train) [146][1500/2569] lr: 4.0000e-04 eta: 0:50:24 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 5.9046 loss: 1.5986 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5986 2023/06/05 20:24:39 - mmengine - INFO - Epoch(train) [146][1520/2569] lr: 4.0000e-04 eta: 0:50:19 time: 0.2633 data_time: 0.0072 memory: 5828 grad_norm: 5.9906 loss: 1.4444 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4444 2023/06/05 20:24:44 - mmengine - INFO - Epoch(train) [146][1540/2569] lr: 4.0000e-04 eta: 0:50:14 time: 0.2690 data_time: 0.0070 memory: 5828 grad_norm: 6.0722 loss: 1.7980 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7980 2023/06/05 20:24:50 - mmengine - INFO - Epoch(train) [146][1560/2569] lr: 4.0000e-04 eta: 0:50:08 time: 0.2673 data_time: 0.0074 memory: 5828 grad_norm: 5.8654 loss: 1.7372 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7372 2023/06/05 20:24:55 - mmengine - INFO - Epoch(train) [146][1580/2569] lr: 4.0000e-04 eta: 0:50:03 time: 0.2764 data_time: 0.0072 memory: 5828 grad_norm: 5.8983 loss: 1.3231 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3231 2023/06/05 20:25:01 - mmengine - INFO - Epoch(train) [146][1600/2569] lr: 4.0000e-04 eta: 0:49:58 time: 0.2675 data_time: 0.0071 memory: 5828 grad_norm: 5.8655 loss: 1.4638 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4638 2023/06/05 20:25:06 - mmengine - INFO - Epoch(train) [146][1620/2569] lr: 4.0000e-04 eta: 0:49:52 time: 0.2647 data_time: 0.0074 memory: 5828 grad_norm: 5.8515 loss: 1.5902 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5902 2023/06/05 20:25:11 - mmengine - INFO - Epoch(train) [146][1640/2569] lr: 4.0000e-04 eta: 0:49:47 time: 0.2640 data_time: 0.0077 memory: 5828 grad_norm: 5.9687 loss: 1.6787 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6787 2023/06/05 20:25:16 - mmengine - INFO - Epoch(train) [146][1660/2569] lr: 4.0000e-04 eta: 0:49:42 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 5.8211 loss: 1.7390 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7390 2023/06/05 20:25:22 - mmengine - INFO - Epoch(train) [146][1680/2569] lr: 4.0000e-04 eta: 0:49:36 time: 0.2732 data_time: 0.0073 memory: 5828 grad_norm: 5.8770 loss: 1.4061 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.4061 2023/06/05 20:25:27 - mmengine - INFO - Epoch(train) [146][1700/2569] lr: 4.0000e-04 eta: 0:49:31 time: 0.2694 data_time: 0.0077 memory: 5828 grad_norm: 5.9084 loss: 1.6224 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6224 2023/06/05 20:25:33 - mmengine - INFO - Epoch(train) [146][1720/2569] lr: 4.0000e-04 eta: 0:49:26 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 5.9559 loss: 1.5232 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5232 2023/06/05 20:25:38 - mmengine - INFO - Epoch(train) [146][1740/2569] lr: 4.0000e-04 eta: 0:49:20 time: 0.2655 data_time: 0.0077 memory: 5828 grad_norm: 5.8682 loss: 1.6451 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6451 2023/06/05 20:25:43 - mmengine - INFO - Epoch(train) [146][1760/2569] lr: 4.0000e-04 eta: 0:49:15 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 5.8337 loss: 1.4508 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4508 2023/06/05 20:25:49 - mmengine - INFO - Epoch(train) [146][1780/2569] lr: 4.0000e-04 eta: 0:49:10 time: 0.2623 data_time: 0.0069 memory: 5828 grad_norm: 5.8076 loss: 1.5208 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5208 2023/06/05 20:25:54 - mmengine - INFO - Epoch(train) [146][1800/2569] lr: 4.0000e-04 eta: 0:49:04 time: 0.2677 data_time: 0.0072 memory: 5828 grad_norm: 5.9266 loss: 1.7900 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7900 2023/06/05 20:25:59 - mmengine - INFO - Epoch(train) [146][1820/2569] lr: 4.0000e-04 eta: 0:48:59 time: 0.2732 data_time: 0.0072 memory: 5828 grad_norm: 5.8139 loss: 1.4867 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.4867 2023/06/05 20:26:05 - mmengine - INFO - Epoch(train) [146][1840/2569] lr: 4.0000e-04 eta: 0:48:54 time: 0.2751 data_time: 0.0074 memory: 5828 grad_norm: 5.8659 loss: 1.6317 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6317 2023/06/05 20:26:10 - mmengine - INFO - Epoch(train) [146][1860/2569] lr: 4.0000e-04 eta: 0:48:48 time: 0.2687 data_time: 0.0074 memory: 5828 grad_norm: 5.9212 loss: 1.6723 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6723 2023/06/05 20:26:16 - mmengine - INFO - Epoch(train) [146][1880/2569] lr: 4.0000e-04 eta: 0:48:43 time: 0.2651 data_time: 0.0075 memory: 5828 grad_norm: 5.7154 loss: 1.3371 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.3371 2023/06/05 20:26:21 - mmengine - INFO - Epoch(train) [146][1900/2569] lr: 4.0000e-04 eta: 0:48:38 time: 0.2706 data_time: 0.0072 memory: 5828 grad_norm: 5.7961 loss: 1.5800 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5800 2023/06/05 20:26:26 - mmengine - INFO - Epoch(train) [146][1920/2569] lr: 4.0000e-04 eta: 0:48:32 time: 0.2663 data_time: 0.0073 memory: 5828 grad_norm: 5.8503 loss: 1.7707 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7707 2023/06/05 20:26:32 - mmengine - INFO - Epoch(train) [146][1940/2569] lr: 4.0000e-04 eta: 0:48:27 time: 0.2679 data_time: 0.0071 memory: 5828 grad_norm: 5.7334 loss: 1.9025 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.9025 2023/06/05 20:26:37 - mmengine - INFO - Epoch(train) [146][1960/2569] lr: 4.0000e-04 eta: 0:48:22 time: 0.2656 data_time: 0.0072 memory: 5828 grad_norm: 5.7816 loss: 1.5075 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5075 2023/06/05 20:26:43 - mmengine - INFO - Epoch(train) [146][1980/2569] lr: 4.0000e-04 eta: 0:48:16 time: 0.2711 data_time: 0.0073 memory: 5828 grad_norm: 5.9266 loss: 1.4050 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4050 2023/06/05 20:26:48 - mmengine - INFO - Epoch(train) [146][2000/2569] lr: 4.0000e-04 eta: 0:48:11 time: 0.2727 data_time: 0.0073 memory: 5828 grad_norm: 5.9467 loss: 1.1771 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.1771 2023/06/05 20:26:54 - mmengine - INFO - Epoch(train) [146][2020/2569] lr: 4.0000e-04 eta: 0:48:06 time: 0.2736 data_time: 0.0072 memory: 5828 grad_norm: 5.8420 loss: 1.5190 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5190 2023/06/05 20:26:59 - mmengine - INFO - Epoch(train) [146][2040/2569] lr: 4.0000e-04 eta: 0:48:00 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 5.7608 loss: 1.6748 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6748 2023/06/05 20:27:04 - mmengine - INFO - Epoch(train) [146][2060/2569] lr: 4.0000e-04 eta: 0:47:55 time: 0.2690 data_time: 0.0076 memory: 5828 grad_norm: 5.9062 loss: 1.3893 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3893 2023/06/05 20:27:09 - mmengine - INFO - Epoch(train) [146][2080/2569] lr: 4.0000e-04 eta: 0:47:50 time: 0.2628 data_time: 0.0073 memory: 5828 grad_norm: 5.6801 loss: 1.2543 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2543 2023/06/05 20:27:15 - mmengine - INFO - Epoch(train) [146][2100/2569] lr: 4.0000e-04 eta: 0:47:44 time: 0.2647 data_time: 0.0078 memory: 5828 grad_norm: 5.8361 loss: 1.4418 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4418 2023/06/05 20:27:20 - mmengine - INFO - Epoch(train) [146][2120/2569] lr: 4.0000e-04 eta: 0:47:39 time: 0.2762 data_time: 0.0073 memory: 5828 grad_norm: 5.7493 loss: 1.7345 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7345 2023/06/05 20:27:26 - mmengine - INFO - Epoch(train) [146][2140/2569] lr: 4.0000e-04 eta: 0:47:34 time: 0.2626 data_time: 0.0072 memory: 5828 grad_norm: 5.8011 loss: 1.7287 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7287 2023/06/05 20:27:31 - mmengine - INFO - Epoch(train) [146][2160/2569] lr: 4.0000e-04 eta: 0:47:28 time: 0.2660 data_time: 0.0074 memory: 5828 grad_norm: 5.8882 loss: 1.8669 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8669 2023/06/05 20:27:36 - mmengine - INFO - Epoch(train) [146][2180/2569] lr: 4.0000e-04 eta: 0:47:23 time: 0.2684 data_time: 0.0076 memory: 5828 grad_norm: 5.8833 loss: 1.9332 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.9332 2023/06/05 20:27:42 - mmengine - INFO - Epoch(train) [146][2200/2569] lr: 4.0000e-04 eta: 0:47:18 time: 0.2727 data_time: 0.0073 memory: 5828 grad_norm: 5.8920 loss: 1.6043 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6043 2023/06/05 20:27:47 - mmengine - INFO - Epoch(train) [146][2220/2569] lr: 4.0000e-04 eta: 0:47:12 time: 0.2736 data_time: 0.0074 memory: 5828 grad_norm: 5.7747 loss: 1.4828 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4828 2023/06/05 20:27:53 - mmengine - INFO - Epoch(train) [146][2240/2569] lr: 4.0000e-04 eta: 0:47:07 time: 0.2737 data_time: 0.0074 memory: 5828 grad_norm: 5.7242 loss: 1.4438 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4438 2023/06/05 20:27:58 - mmengine - INFO - Epoch(train) [146][2260/2569] lr: 4.0000e-04 eta: 0:47:02 time: 0.2699 data_time: 0.0071 memory: 5828 grad_norm: 5.8681 loss: 1.7366 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7366 2023/06/05 20:28:04 - mmengine - INFO - Epoch(train) [146][2280/2569] lr: 4.0000e-04 eta: 0:46:56 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 5.8849 loss: 1.0516 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0516 2023/06/05 20:28:09 - mmengine - INFO - Epoch(train) [146][2300/2569] lr: 4.0000e-04 eta: 0:46:51 time: 0.2696 data_time: 0.0073 memory: 5828 grad_norm: 5.9583 loss: 1.8797 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8797 2023/06/05 20:28:14 - mmengine - INFO - Epoch(train) [146][2320/2569] lr: 4.0000e-04 eta: 0:46:46 time: 0.2693 data_time: 0.0081 memory: 5828 grad_norm: 5.8683 loss: 1.8079 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8079 2023/06/05 20:28:20 - mmengine - INFO - Epoch(train) [146][2340/2569] lr: 4.0000e-04 eta: 0:46:40 time: 0.2667 data_time: 0.0076 memory: 5828 grad_norm: 5.9410 loss: 1.5591 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5591 2023/06/05 20:28:25 - mmengine - INFO - Epoch(train) [146][2360/2569] lr: 4.0000e-04 eta: 0:46:35 time: 0.2655 data_time: 0.0079 memory: 5828 grad_norm: 5.8920 loss: 1.3834 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3834 2023/06/05 20:28:31 - mmengine - INFO - Epoch(train) [146][2380/2569] lr: 4.0000e-04 eta: 0:46:30 time: 0.2813 data_time: 0.0079 memory: 5828 grad_norm: 5.8746 loss: 1.7762 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7762 2023/06/05 20:28:36 - mmengine - INFO - Epoch(train) [146][2400/2569] lr: 4.0000e-04 eta: 0:46:24 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 5.9374 loss: 2.0277 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0277 2023/06/05 20:28:42 - mmengine - INFO - Epoch(train) [146][2420/2569] lr: 4.0000e-04 eta: 0:46:19 time: 0.2757 data_time: 0.0076 memory: 5828 grad_norm: 5.9145 loss: 1.5845 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5845 2023/06/05 20:28:47 - mmengine - INFO - Epoch(train) [146][2440/2569] lr: 4.0000e-04 eta: 0:46:14 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 5.8440 loss: 1.6709 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6709 2023/06/05 20:28:52 - mmengine - INFO - Epoch(train) [146][2460/2569] lr: 4.0000e-04 eta: 0:46:08 time: 0.2628 data_time: 0.0070 memory: 5828 grad_norm: 5.9013 loss: 1.5190 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5190 2023/06/05 20:28:58 - mmengine - INFO - Epoch(train) [146][2480/2569] lr: 4.0000e-04 eta: 0:46:03 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 5.9071 loss: 1.6223 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6223 2023/06/05 20:29:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:29:03 - mmengine - INFO - Epoch(train) [146][2500/2569] lr: 4.0000e-04 eta: 0:45:58 time: 0.2693 data_time: 0.0074 memory: 5828 grad_norm: 5.8753 loss: 1.6425 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6425 2023/06/05 20:29:08 - mmengine - INFO - Epoch(train) [146][2520/2569] lr: 4.0000e-04 eta: 0:45:52 time: 0.2722 data_time: 0.0073 memory: 5828 grad_norm: 5.8912 loss: 1.7073 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7073 2023/06/05 20:29:14 - mmengine - INFO - Epoch(train) [146][2540/2569] lr: 4.0000e-04 eta: 0:45:47 time: 0.2638 data_time: 0.0074 memory: 5828 grad_norm: 5.8340 loss: 1.5140 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5140 2023/06/05 20:29:19 - mmengine - INFO - Epoch(train) [146][2560/2569] lr: 4.0000e-04 eta: 0:45:42 time: 0.2648 data_time: 0.0074 memory: 5828 grad_norm: 5.7037 loss: 1.6426 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6426 2023/06/05 20:29:21 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:29:21 - mmengine - INFO - Epoch(train) [146][2569/2569] lr: 4.0000e-04 eta: 0:45:39 time: 0.2530 data_time: 0.0074 memory: 5828 grad_norm: 5.8116 loss: 1.6228 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.6228 2023/06/05 20:29:28 - mmengine - INFO - Epoch(train) [147][ 20/2569] lr: 4.0000e-04 eta: 0:45:34 time: 0.3332 data_time: 0.0610 memory: 5828 grad_norm: 5.8668 loss: 1.5491 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5491 2023/06/05 20:29:33 - mmengine - INFO - Epoch(train) [147][ 40/2569] lr: 4.0000e-04 eta: 0:45:29 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 5.7820 loss: 1.4489 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4489 2023/06/05 20:29:39 - mmengine - INFO - Epoch(train) [147][ 60/2569] lr: 4.0000e-04 eta: 0:45:23 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 5.8857 loss: 1.4043 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4043 2023/06/05 20:29:44 - mmengine - INFO - Epoch(train) [147][ 80/2569] lr: 4.0000e-04 eta: 0:45:18 time: 0.2646 data_time: 0.0078 memory: 5828 grad_norm: 5.7952 loss: 1.8184 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8184 2023/06/05 20:29:49 - mmengine - INFO - Epoch(train) [147][ 100/2569] lr: 4.0000e-04 eta: 0:45:13 time: 0.2704 data_time: 0.0072 memory: 5828 grad_norm: 5.9715 loss: 1.4715 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.4715 2023/06/05 20:29:55 - mmengine - INFO - Epoch(train) [147][ 120/2569] lr: 4.0000e-04 eta: 0:45:07 time: 0.2707 data_time: 0.0076 memory: 5828 grad_norm: 5.8245 loss: 1.5248 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.5248 2023/06/05 20:30:00 - mmengine - INFO - Epoch(train) [147][ 140/2569] lr: 4.0000e-04 eta: 0:45:02 time: 0.2635 data_time: 0.0074 memory: 5828 grad_norm: 5.8761 loss: 1.5603 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5603 2023/06/05 20:30:06 - mmengine - INFO - Epoch(train) [147][ 160/2569] lr: 4.0000e-04 eta: 0:44:57 time: 0.2745 data_time: 0.0081 memory: 5828 grad_norm: 5.9007 loss: 1.4027 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4027 2023/06/05 20:30:11 - mmengine - INFO - Epoch(train) [147][ 180/2569] lr: 4.0000e-04 eta: 0:44:51 time: 0.2634 data_time: 0.0074 memory: 5828 grad_norm: 5.7605 loss: 1.4289 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4289 2023/06/05 20:30:16 - mmengine - INFO - Epoch(train) [147][ 200/2569] lr: 4.0000e-04 eta: 0:44:46 time: 0.2758 data_time: 0.0075 memory: 5828 grad_norm: 5.9582 loss: 1.5872 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5872 2023/06/05 20:30:22 - mmengine - INFO - Epoch(train) [147][ 220/2569] lr: 4.0000e-04 eta: 0:44:41 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 5.9653 loss: 1.6984 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6984 2023/06/05 20:30:27 - mmengine - INFO - Epoch(train) [147][ 240/2569] lr: 4.0000e-04 eta: 0:44:35 time: 0.2710 data_time: 0.0072 memory: 5828 grad_norm: 5.8690 loss: 1.3030 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3030 2023/06/05 20:30:33 - mmengine - INFO - Epoch(train) [147][ 260/2569] lr: 4.0000e-04 eta: 0:44:30 time: 0.2689 data_time: 0.0074 memory: 5828 grad_norm: 5.8153 loss: 1.6162 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6162 2023/06/05 20:30:38 - mmengine - INFO - Epoch(train) [147][ 280/2569] lr: 4.0000e-04 eta: 0:44:25 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 5.8874 loss: 1.3214 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.3214 2023/06/05 20:30:43 - mmengine - INFO - Epoch(train) [147][ 300/2569] lr: 4.0000e-04 eta: 0:44:19 time: 0.2608 data_time: 0.0073 memory: 5828 grad_norm: 5.8137 loss: 1.3850 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3850 2023/06/05 20:30:49 - mmengine - INFO - Epoch(train) [147][ 320/2569] lr: 4.0000e-04 eta: 0:44:14 time: 0.2747 data_time: 0.0076 memory: 5828 grad_norm: 5.8410 loss: 1.5784 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5784 2023/06/05 20:30:54 - mmengine - INFO - Epoch(train) [147][ 340/2569] lr: 4.0000e-04 eta: 0:44:09 time: 0.2644 data_time: 0.0077 memory: 5828 grad_norm: 5.6891 loss: 1.2113 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2113 2023/06/05 20:30:59 - mmengine - INFO - Epoch(train) [147][ 360/2569] lr: 4.0000e-04 eta: 0:44:03 time: 0.2697 data_time: 0.0071 memory: 5828 grad_norm: 5.7872 loss: 1.5162 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5162 2023/06/05 20:31:05 - mmengine - INFO - Epoch(train) [147][ 380/2569] lr: 4.0000e-04 eta: 0:43:58 time: 0.2700 data_time: 0.0073 memory: 5828 grad_norm: 5.7038 loss: 1.5815 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5815 2023/06/05 20:31:10 - mmengine - INFO - Epoch(train) [147][ 400/2569] lr: 4.0000e-04 eta: 0:43:53 time: 0.2672 data_time: 0.0072 memory: 5828 grad_norm: 5.6735 loss: 1.7798 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7798 2023/06/05 20:31:15 - mmengine - INFO - Epoch(train) [147][ 420/2569] lr: 4.0000e-04 eta: 0:43:47 time: 0.2640 data_time: 0.0074 memory: 5828 grad_norm: 5.8944 loss: 1.5832 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5832 2023/06/05 20:31:21 - mmengine - INFO - Epoch(train) [147][ 440/2569] lr: 4.0000e-04 eta: 0:43:42 time: 0.2615 data_time: 0.0074 memory: 5828 grad_norm: 5.8857 loss: 1.5909 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5909 2023/06/05 20:31:26 - mmengine - INFO - Epoch(train) [147][ 460/2569] lr: 4.0000e-04 eta: 0:43:37 time: 0.2682 data_time: 0.0075 memory: 5828 grad_norm: 5.8794 loss: 1.3892 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3892 2023/06/05 20:31:31 - mmengine - INFO - Epoch(train) [147][ 480/2569] lr: 4.0000e-04 eta: 0:43:31 time: 0.2730 data_time: 0.0072 memory: 5828 grad_norm: 5.8599 loss: 1.5148 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5148 2023/06/05 20:31:37 - mmengine - INFO - Epoch(train) [147][ 500/2569] lr: 4.0000e-04 eta: 0:43:26 time: 0.2656 data_time: 0.0073 memory: 5828 grad_norm: 5.9739 loss: 1.3849 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.3849 2023/06/05 20:31:42 - mmengine - INFO - Epoch(train) [147][ 520/2569] lr: 4.0000e-04 eta: 0:43:21 time: 0.2696 data_time: 0.0075 memory: 5828 grad_norm: 5.8376 loss: 1.8088 top1_acc: 0.2500 top5_acc: 0.3750 loss_cls: 1.8088 2023/06/05 20:31:47 - mmengine - INFO - Epoch(train) [147][ 540/2569] lr: 4.0000e-04 eta: 0:43:15 time: 0.2636 data_time: 0.0075 memory: 5828 grad_norm: 5.8789 loss: 1.3657 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3657 2023/06/05 20:31:53 - mmengine - INFO - Epoch(train) [147][ 560/2569] lr: 4.0000e-04 eta: 0:43:10 time: 0.2627 data_time: 0.0074 memory: 5828 grad_norm: 5.8684 loss: 1.7609 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7609 2023/06/05 20:31:58 - mmengine - INFO - Epoch(train) [147][ 580/2569] lr: 4.0000e-04 eta: 0:43:05 time: 0.2685 data_time: 0.0071 memory: 5828 grad_norm: 5.8778 loss: 1.5711 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5711 2023/06/05 20:32:03 - mmengine - INFO - Epoch(train) [147][ 600/2569] lr: 4.0000e-04 eta: 0:42:59 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 5.8880 loss: 1.5898 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5898 2023/06/05 20:32:09 - mmengine - INFO - Epoch(train) [147][ 620/2569] lr: 4.0000e-04 eta: 0:42:54 time: 0.2623 data_time: 0.0074 memory: 5828 grad_norm: 5.8598 loss: 1.6437 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6437 2023/06/05 20:32:14 - mmengine - INFO - Epoch(train) [147][ 640/2569] lr: 4.0000e-04 eta: 0:42:49 time: 0.2717 data_time: 0.0077 memory: 5828 grad_norm: 5.7925 loss: 1.5547 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5547 2023/06/05 20:32:19 - mmengine - INFO - Epoch(train) [147][ 660/2569] lr: 4.0000e-04 eta: 0:42:43 time: 0.2674 data_time: 0.0076 memory: 5828 grad_norm: 6.1186 loss: 1.2337 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.2337 2023/06/05 20:32:25 - mmengine - INFO - Epoch(train) [147][ 680/2569] lr: 4.0000e-04 eta: 0:42:38 time: 0.2708 data_time: 0.0070 memory: 5828 grad_norm: 5.8275 loss: 1.6295 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6295 2023/06/05 20:32:30 - mmengine - INFO - Epoch(train) [147][ 700/2569] lr: 4.0000e-04 eta: 0:42:33 time: 0.2729 data_time: 0.0076 memory: 5828 grad_norm: 5.6787 loss: 1.4530 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4530 2023/06/05 20:32:36 - mmengine - INFO - Epoch(train) [147][ 720/2569] lr: 4.0000e-04 eta: 0:42:27 time: 0.2683 data_time: 0.0077 memory: 5828 grad_norm: 5.8933 loss: 1.7428 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7428 2023/06/05 20:32:41 - mmengine - INFO - Epoch(train) [147][ 740/2569] lr: 4.0000e-04 eta: 0:42:22 time: 0.2675 data_time: 0.0079 memory: 5828 grad_norm: 5.7993 loss: 1.4294 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4294 2023/06/05 20:32:46 - mmengine - INFO - Epoch(train) [147][ 760/2569] lr: 4.0000e-04 eta: 0:42:17 time: 0.2711 data_time: 0.0072 memory: 5828 grad_norm: 6.0084 loss: 1.8037 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.8037 2023/06/05 20:32:52 - mmengine - INFO - Epoch(train) [147][ 780/2569] lr: 4.0000e-04 eta: 0:42:11 time: 0.2789 data_time: 0.0075 memory: 5828 grad_norm: 5.9271 loss: 1.6451 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6451 2023/06/05 20:32:57 - mmengine - INFO - Epoch(train) [147][ 800/2569] lr: 4.0000e-04 eta: 0:42:06 time: 0.2634 data_time: 0.0075 memory: 5828 grad_norm: 5.7565 loss: 1.4263 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4263 2023/06/05 20:33:03 - mmengine - INFO - Epoch(train) [147][ 820/2569] lr: 4.0000e-04 eta: 0:42:01 time: 0.2664 data_time: 0.0073 memory: 5828 grad_norm: 5.9760 loss: 1.3866 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3866 2023/06/05 20:33:08 - mmengine - INFO - Epoch(train) [147][ 840/2569] lr: 4.0000e-04 eta: 0:41:55 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 5.8143 loss: 1.6579 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6579 2023/06/05 20:33:13 - mmengine - INFO - Epoch(train) [147][ 860/2569] lr: 4.0000e-04 eta: 0:41:50 time: 0.2732 data_time: 0.0072 memory: 5828 grad_norm: 6.0919 loss: 1.9238 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.9238 2023/06/05 20:33:19 - mmengine - INFO - Epoch(train) [147][ 880/2569] lr: 4.0000e-04 eta: 0:41:45 time: 0.2696 data_time: 0.0073 memory: 5828 grad_norm: 5.9227 loss: 1.3505 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.3505 2023/06/05 20:33:24 - mmengine - INFO - Epoch(train) [147][ 900/2569] lr: 4.0000e-04 eta: 0:41:39 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 5.8542 loss: 1.6893 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6893 2023/06/05 20:33:29 - mmengine - INFO - Epoch(train) [147][ 920/2569] lr: 4.0000e-04 eta: 0:41:34 time: 0.2624 data_time: 0.0074 memory: 5828 grad_norm: 5.8857 loss: 1.8314 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8314 2023/06/05 20:33:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:33:35 - mmengine - INFO - Epoch(train) [147][ 940/2569] lr: 4.0000e-04 eta: 0:41:29 time: 0.2787 data_time: 0.0078 memory: 5828 grad_norm: 5.9121 loss: 1.7539 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7539 2023/06/05 20:33:40 - mmengine - INFO - Epoch(train) [147][ 960/2569] lr: 4.0000e-04 eta: 0:41:23 time: 0.2682 data_time: 0.0075 memory: 5828 grad_norm: 5.9033 loss: 1.6889 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6889 2023/06/05 20:33:46 - mmengine - INFO - Epoch(train) [147][ 980/2569] lr: 4.0000e-04 eta: 0:41:18 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 5.6638 loss: 1.5182 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5182 2023/06/05 20:33:51 - mmengine - INFO - Epoch(train) [147][1000/2569] lr: 4.0000e-04 eta: 0:41:13 time: 0.2707 data_time: 0.0075 memory: 5828 grad_norm: 5.8668 loss: 1.5412 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.5412 2023/06/05 20:33:56 - mmengine - INFO - Epoch(train) [147][1020/2569] lr: 4.0000e-04 eta: 0:41:07 time: 0.2617 data_time: 0.0075 memory: 5828 grad_norm: 5.8949 loss: 1.4464 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4464 2023/06/05 20:34:02 - mmengine - INFO - Epoch(train) [147][1040/2569] lr: 4.0000e-04 eta: 0:41:02 time: 0.2709 data_time: 0.0074 memory: 5828 grad_norm: 5.8829 loss: 1.6737 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6737 2023/06/05 20:34:07 - mmengine - INFO - Epoch(train) [147][1060/2569] lr: 4.0000e-04 eta: 0:40:57 time: 0.2616 data_time: 0.0075 memory: 5828 grad_norm: 5.9480 loss: 1.6646 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6646 2023/06/05 20:34:13 - mmengine - INFO - Epoch(train) [147][1080/2569] lr: 4.0000e-04 eta: 0:40:51 time: 0.2769 data_time: 0.0073 memory: 5828 grad_norm: 5.9541 loss: 1.6909 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6909 2023/06/05 20:34:18 - mmengine - INFO - Epoch(train) [147][1100/2569] lr: 4.0000e-04 eta: 0:40:46 time: 0.2622 data_time: 0.0074 memory: 5828 grad_norm: 5.8504 loss: 1.4610 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4610 2023/06/05 20:34:23 - mmengine - INFO - Epoch(train) [147][1120/2569] lr: 4.0000e-04 eta: 0:40:41 time: 0.2801 data_time: 0.0071 memory: 5828 grad_norm: 5.9013 loss: 1.3259 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.3259 2023/06/05 20:34:29 - mmengine - INFO - Epoch(train) [147][1140/2569] lr: 4.0000e-04 eta: 0:40:35 time: 0.2688 data_time: 0.0071 memory: 5828 grad_norm: 5.8450 loss: 1.6194 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6194 2023/06/05 20:34:34 - mmengine - INFO - Epoch(train) [147][1160/2569] lr: 4.0000e-04 eta: 0:40:30 time: 0.2785 data_time: 0.0073 memory: 5828 grad_norm: 5.9288 loss: 1.5118 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5118 2023/06/05 20:34:40 - mmengine - INFO - Epoch(train) [147][1180/2569] lr: 4.0000e-04 eta: 0:40:25 time: 0.2669 data_time: 0.0072 memory: 5828 grad_norm: 5.8492 loss: 1.6448 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6448 2023/06/05 20:34:45 - mmengine - INFO - Epoch(train) [147][1200/2569] lr: 4.0000e-04 eta: 0:40:19 time: 0.2674 data_time: 0.0087 memory: 5828 grad_norm: 5.8240 loss: 1.4737 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4737 2023/06/05 20:34:50 - mmengine - INFO - Epoch(train) [147][1220/2569] lr: 4.0000e-04 eta: 0:40:14 time: 0.2665 data_time: 0.0073 memory: 5828 grad_norm: 5.8467 loss: 1.5970 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5970 2023/06/05 20:34:56 - mmengine - INFO - Epoch(train) [147][1240/2569] lr: 4.0000e-04 eta: 0:40:09 time: 0.2729 data_time: 0.0078 memory: 5828 grad_norm: 5.8345 loss: 1.4499 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4499 2023/06/05 20:35:01 - mmengine - INFO - Epoch(train) [147][1260/2569] lr: 4.0000e-04 eta: 0:40:03 time: 0.2732 data_time: 0.0076 memory: 5828 grad_norm: 5.8266 loss: 1.8287 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8287 2023/06/05 20:35:07 - mmengine - INFO - Epoch(train) [147][1280/2569] lr: 4.0000e-04 eta: 0:39:58 time: 0.2709 data_time: 0.0076 memory: 5828 grad_norm: 5.9086 loss: 1.3902 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.3902 2023/06/05 20:35:12 - mmengine - INFO - Epoch(train) [147][1300/2569] lr: 4.0000e-04 eta: 0:39:53 time: 0.2641 data_time: 0.0086 memory: 5828 grad_norm: 5.8830 loss: 1.3789 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3789 2023/06/05 20:35:18 - mmengine - INFO - Epoch(train) [147][1320/2569] lr: 4.0000e-04 eta: 0:39:47 time: 0.2711 data_time: 0.0072 memory: 5828 grad_norm: 5.9856 loss: 1.6185 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6185 2023/06/05 20:35:23 - mmengine - INFO - Epoch(train) [147][1340/2569] lr: 4.0000e-04 eta: 0:39:42 time: 0.2618 data_time: 0.0070 memory: 5828 grad_norm: 5.8549 loss: 1.3111 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.3111 2023/06/05 20:35:28 - mmengine - INFO - Epoch(train) [147][1360/2569] lr: 4.0000e-04 eta: 0:39:37 time: 0.2707 data_time: 0.0078 memory: 5828 grad_norm: 5.9973 loss: 1.6632 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6632 2023/06/05 20:35:34 - mmengine - INFO - Epoch(train) [147][1380/2569] lr: 4.0000e-04 eta: 0:39:31 time: 0.2642 data_time: 0.0071 memory: 5828 grad_norm: 5.8651 loss: 1.4518 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4518 2023/06/05 20:35:39 - mmengine - INFO - Epoch(train) [147][1400/2569] lr: 4.0000e-04 eta: 0:39:26 time: 0.2718 data_time: 0.0073 memory: 5828 grad_norm: 5.8230 loss: 1.3474 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.3474 2023/06/05 20:35:44 - mmengine - INFO - Epoch(train) [147][1420/2569] lr: 4.0000e-04 eta: 0:39:21 time: 0.2617 data_time: 0.0074 memory: 5828 grad_norm: 5.9111 loss: 1.8037 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8037 2023/06/05 20:35:50 - mmengine - INFO - Epoch(train) [147][1440/2569] lr: 4.0000e-04 eta: 0:39:15 time: 0.2699 data_time: 0.0072 memory: 5828 grad_norm: 6.0046 loss: 1.5519 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5519 2023/06/05 20:35:55 - mmengine - INFO - Epoch(train) [147][1460/2569] lr: 4.0000e-04 eta: 0:39:10 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 5.8904 loss: 1.7535 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7535 2023/06/05 20:36:01 - mmengine - INFO - Epoch(train) [147][1480/2569] lr: 4.0000e-04 eta: 0:39:05 time: 0.2785 data_time: 0.0073 memory: 5828 grad_norm: 5.8548 loss: 1.4778 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4778 2023/06/05 20:36:06 - mmengine - INFO - Epoch(train) [147][1500/2569] lr: 4.0000e-04 eta: 0:38:59 time: 0.2738 data_time: 0.0074 memory: 5828 grad_norm: 5.9297 loss: 1.5696 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.5696 2023/06/05 20:36:12 - mmengine - INFO - Epoch(train) [147][1520/2569] lr: 4.0000e-04 eta: 0:38:54 time: 0.2750 data_time: 0.0075 memory: 5828 grad_norm: 5.8686 loss: 1.5623 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5623 2023/06/05 20:36:17 - mmengine - INFO - Epoch(train) [147][1540/2569] lr: 4.0000e-04 eta: 0:38:49 time: 0.2726 data_time: 0.0070 memory: 5828 grad_norm: 5.8911 loss: 1.6298 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6298 2023/06/05 20:36:22 - mmengine - INFO - Epoch(train) [147][1560/2569] lr: 4.0000e-04 eta: 0:38:43 time: 0.2728 data_time: 0.0076 memory: 5828 grad_norm: 5.9887 loss: 1.7481 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7481 2023/06/05 20:36:28 - mmengine - INFO - Epoch(train) [147][1580/2569] lr: 4.0000e-04 eta: 0:38:38 time: 0.2699 data_time: 0.0075 memory: 5828 grad_norm: 5.9779 loss: 1.6722 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.6722 2023/06/05 20:36:33 - mmengine - INFO - Epoch(train) [147][1600/2569] lr: 4.0000e-04 eta: 0:38:33 time: 0.2644 data_time: 0.0092 memory: 5828 grad_norm: 6.0032 loss: 1.6225 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6225 2023/06/05 20:36:39 - mmengine - INFO - Epoch(train) [147][1620/2569] lr: 4.0000e-04 eta: 0:38:27 time: 0.2700 data_time: 0.0078 memory: 5828 grad_norm: 5.9087 loss: 1.5121 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5121 2023/06/05 20:36:44 - mmengine - INFO - Epoch(train) [147][1640/2569] lr: 4.0000e-04 eta: 0:38:22 time: 0.2652 data_time: 0.0074 memory: 5828 grad_norm: 6.0280 loss: 1.5403 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.5403 2023/06/05 20:36:49 - mmengine - INFO - Epoch(train) [147][1660/2569] lr: 4.0000e-04 eta: 0:38:17 time: 0.2624 data_time: 0.0076 memory: 5828 grad_norm: 5.8872 loss: 1.3736 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.3736 2023/06/05 20:36:54 - mmengine - INFO - Epoch(train) [147][1680/2569] lr: 4.0000e-04 eta: 0:38:11 time: 0.2658 data_time: 0.0073 memory: 5828 grad_norm: 6.0016 loss: 1.6705 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6705 2023/06/05 20:37:00 - mmengine - INFO - Epoch(train) [147][1700/2569] lr: 4.0000e-04 eta: 0:38:06 time: 0.2666 data_time: 0.0081 memory: 5828 grad_norm: 5.8764 loss: 1.5731 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5731 2023/06/05 20:37:05 - mmengine - INFO - Epoch(train) [147][1720/2569] lr: 4.0000e-04 eta: 0:38:01 time: 0.2688 data_time: 0.0071 memory: 5828 grad_norm: 5.9050 loss: 1.7777 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7777 2023/06/05 20:37:11 - mmengine - INFO - Epoch(train) [147][1740/2569] lr: 4.0000e-04 eta: 0:37:55 time: 0.2683 data_time: 0.0077 memory: 5828 grad_norm: 5.8651 loss: 1.7607 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7607 2023/06/05 20:37:16 - mmengine - INFO - Epoch(train) [147][1760/2569] lr: 4.0000e-04 eta: 0:37:50 time: 0.2676 data_time: 0.0074 memory: 5828 grad_norm: 5.9517 loss: 1.6684 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6684 2023/06/05 20:37:21 - mmengine - INFO - Epoch(train) [147][1780/2569] lr: 4.0000e-04 eta: 0:37:45 time: 0.2695 data_time: 0.0077 memory: 5828 grad_norm: 5.8365 loss: 1.4511 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4511 2023/06/05 20:37:27 - mmengine - INFO - Epoch(train) [147][1800/2569] lr: 4.0000e-04 eta: 0:37:39 time: 0.2692 data_time: 0.0071 memory: 5828 grad_norm: 5.9049 loss: 1.8227 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8227 2023/06/05 20:37:32 - mmengine - INFO - Epoch(train) [147][1820/2569] lr: 4.0000e-04 eta: 0:37:34 time: 0.2653 data_time: 0.0073 memory: 5828 grad_norm: 5.7835 loss: 1.5872 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.5872 2023/06/05 20:37:37 - mmengine - INFO - Epoch(train) [147][1840/2569] lr: 4.0000e-04 eta: 0:37:29 time: 0.2668 data_time: 0.0080 memory: 5828 grad_norm: 5.7953 loss: 1.8086 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.8086 2023/06/05 20:37:43 - mmengine - INFO - Epoch(train) [147][1860/2569] lr: 4.0000e-04 eta: 0:37:23 time: 0.2631 data_time: 0.0075 memory: 5828 grad_norm: 5.9055 loss: 1.6159 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6159 2023/06/05 20:37:48 - mmengine - INFO - Epoch(train) [147][1880/2569] lr: 4.0000e-04 eta: 0:37:18 time: 0.2696 data_time: 0.0076 memory: 5828 grad_norm: 5.7560 loss: 1.2985 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.2985 2023/06/05 20:37:53 - mmengine - INFO - Epoch(train) [147][1900/2569] lr: 4.0000e-04 eta: 0:37:13 time: 0.2670 data_time: 0.0073 memory: 5828 grad_norm: 5.8793 loss: 1.5686 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5686 2023/06/05 20:37:59 - mmengine - INFO - Epoch(train) [147][1920/2569] lr: 4.0000e-04 eta: 0:37:08 time: 0.2678 data_time: 0.0075 memory: 5828 grad_norm: 5.9512 loss: 1.7327 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7327 2023/06/05 20:38:00 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:38:04 - mmengine - INFO - Epoch(train) [147][1940/2569] lr: 4.0000e-04 eta: 0:37:02 time: 0.2662 data_time: 0.0074 memory: 5828 grad_norm: 5.9403 loss: 1.4752 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4752 2023/06/05 20:38:10 - mmengine - INFO - Epoch(train) [147][1960/2569] lr: 4.0000e-04 eta: 0:36:57 time: 0.2710 data_time: 0.0078 memory: 5828 grad_norm: 5.8497 loss: 1.4497 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4497 2023/06/05 20:38:15 - mmengine - INFO - Epoch(train) [147][1980/2569] lr: 4.0000e-04 eta: 0:36:52 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 5.9822 loss: 1.6799 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6799 2023/06/05 20:38:20 - mmengine - INFO - Epoch(train) [147][2000/2569] lr: 4.0000e-04 eta: 0:36:46 time: 0.2657 data_time: 0.0076 memory: 5828 grad_norm: 6.0498 loss: 1.7382 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7382 2023/06/05 20:38:26 - mmengine - INFO - Epoch(train) [147][2020/2569] lr: 4.0000e-04 eta: 0:36:41 time: 0.2703 data_time: 0.0073 memory: 5828 grad_norm: 5.8206 loss: 1.5062 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5062 2023/06/05 20:38:31 - mmengine - INFO - Epoch(train) [147][2040/2569] lr: 4.0000e-04 eta: 0:36:36 time: 0.2736 data_time: 0.0074 memory: 5828 grad_norm: 5.8712 loss: 1.5317 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5317 2023/06/05 20:38:37 - mmengine - INFO - Epoch(train) [147][2060/2569] lr: 4.0000e-04 eta: 0:36:30 time: 0.2741 data_time: 0.0073 memory: 5828 grad_norm: 5.8849 loss: 1.5678 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5678 2023/06/05 20:38:42 - mmengine - INFO - Epoch(train) [147][2080/2569] lr: 4.0000e-04 eta: 0:36:25 time: 0.2693 data_time: 0.0083 memory: 5828 grad_norm: 5.8759 loss: 1.7425 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7425 2023/06/05 20:38:48 - mmengine - INFO - Epoch(train) [147][2100/2569] lr: 4.0000e-04 eta: 0:36:20 time: 0.2710 data_time: 0.0079 memory: 5828 grad_norm: 6.0206 loss: 1.3672 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3672 2023/06/05 20:38:53 - mmengine - INFO - Epoch(train) [147][2120/2569] lr: 4.0000e-04 eta: 0:36:14 time: 0.2672 data_time: 0.0071 memory: 5828 grad_norm: 5.9502 loss: 1.3215 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3215 2023/06/05 20:38:58 - mmengine - INFO - Epoch(train) [147][2140/2569] lr: 4.0000e-04 eta: 0:36:09 time: 0.2748 data_time: 0.0083 memory: 5828 grad_norm: 5.8994 loss: 1.5616 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5616 2023/06/05 20:39:04 - mmengine - INFO - Epoch(train) [147][2160/2569] lr: 4.0000e-04 eta: 0:36:04 time: 0.2619 data_time: 0.0072 memory: 5828 grad_norm: 6.0077 loss: 1.6602 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6602 2023/06/05 20:39:09 - mmengine - INFO - Epoch(train) [147][2180/2569] lr: 4.0000e-04 eta: 0:35:58 time: 0.2717 data_time: 0.0068 memory: 5828 grad_norm: 6.1433 loss: 1.7523 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7523 2023/06/05 20:39:14 - mmengine - INFO - Epoch(train) [147][2200/2569] lr: 4.0000e-04 eta: 0:35:53 time: 0.2647 data_time: 0.0072 memory: 5828 grad_norm: 5.9472 loss: 1.7793 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7793 2023/06/05 20:39:20 - mmengine - INFO - Epoch(train) [147][2220/2569] lr: 4.0000e-04 eta: 0:35:48 time: 0.2638 data_time: 0.0075 memory: 5828 grad_norm: 5.8511 loss: 1.5000 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5000 2023/06/05 20:39:25 - mmengine - INFO - Epoch(train) [147][2240/2569] lr: 4.0000e-04 eta: 0:35:42 time: 0.2686 data_time: 0.0073 memory: 5828 grad_norm: 5.9580 loss: 1.4867 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.4867 2023/06/05 20:39:30 - mmengine - INFO - Epoch(train) [147][2260/2569] lr: 4.0000e-04 eta: 0:35:37 time: 0.2672 data_time: 0.0080 memory: 5828 grad_norm: 6.0531 loss: 1.4815 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4815 2023/06/05 20:39:36 - mmengine - INFO - Epoch(train) [147][2280/2569] lr: 4.0000e-04 eta: 0:35:32 time: 0.2675 data_time: 0.0072 memory: 5828 grad_norm: 5.7809 loss: 1.5088 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5088 2023/06/05 20:39:41 - mmengine - INFO - Epoch(train) [147][2300/2569] lr: 4.0000e-04 eta: 0:35:26 time: 0.2797 data_time: 0.0079 memory: 5828 grad_norm: 5.7146 loss: 1.3033 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3033 2023/06/05 20:39:47 - mmengine - INFO - Epoch(train) [147][2320/2569] lr: 4.0000e-04 eta: 0:35:21 time: 0.2631 data_time: 0.0074 memory: 5828 grad_norm: 5.9274 loss: 1.7466 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7466 2023/06/05 20:39:52 - mmengine - INFO - Epoch(train) [147][2340/2569] lr: 4.0000e-04 eta: 0:35:16 time: 0.2685 data_time: 0.0074 memory: 5828 grad_norm: 5.9320 loss: 1.6577 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6577 2023/06/05 20:39:57 - mmengine - INFO - Epoch(train) [147][2360/2569] lr: 4.0000e-04 eta: 0:35:10 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 5.8470 loss: 1.2822 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2822 2023/06/05 20:40:03 - mmengine - INFO - Epoch(train) [147][2380/2569] lr: 4.0000e-04 eta: 0:35:05 time: 0.2748 data_time: 0.0071 memory: 5828 grad_norm: 5.8672 loss: 1.4957 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4957 2023/06/05 20:40:08 - mmengine - INFO - Epoch(train) [147][2400/2569] lr: 4.0000e-04 eta: 0:35:00 time: 0.2680 data_time: 0.0073 memory: 5828 grad_norm: 6.0367 loss: 1.5197 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5197 2023/06/05 20:40:14 - mmengine - INFO - Epoch(train) [147][2420/2569] lr: 4.0000e-04 eta: 0:34:54 time: 0.2796 data_time: 0.0077 memory: 5828 grad_norm: 5.9641 loss: 1.5468 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5468 2023/06/05 20:40:19 - mmengine - INFO - Epoch(train) [147][2440/2569] lr: 4.0000e-04 eta: 0:34:49 time: 0.2717 data_time: 0.0071 memory: 5828 grad_norm: 5.9310 loss: 1.6241 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6241 2023/06/05 20:40:25 - mmengine - INFO - Epoch(train) [147][2460/2569] lr: 4.0000e-04 eta: 0:34:44 time: 0.2690 data_time: 0.0072 memory: 5828 grad_norm: 6.0682 loss: 1.6010 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6010 2023/06/05 20:40:30 - mmengine - INFO - Epoch(train) [147][2480/2569] lr: 4.0000e-04 eta: 0:34:38 time: 0.2725 data_time: 0.0070 memory: 5828 grad_norm: 5.9632 loss: 1.7318 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7318 2023/06/05 20:40:36 - mmengine - INFO - Epoch(train) [147][2500/2569] lr: 4.0000e-04 eta: 0:34:33 time: 0.2694 data_time: 0.0076 memory: 5828 grad_norm: 5.9151 loss: 1.6828 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6828 2023/06/05 20:40:41 - mmengine - INFO - Epoch(train) [147][2520/2569] lr: 4.0000e-04 eta: 0:34:28 time: 0.2713 data_time: 0.0072 memory: 5828 grad_norm: 5.8503 loss: 1.7112 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7112 2023/06/05 20:40:46 - mmengine - INFO - Epoch(train) [147][2540/2569] lr: 4.0000e-04 eta: 0:34:22 time: 0.2687 data_time: 0.0076 memory: 5828 grad_norm: 6.0424 loss: 1.7287 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7287 2023/06/05 20:40:52 - mmengine - INFO - Epoch(train) [147][2560/2569] lr: 4.0000e-04 eta: 0:34:17 time: 0.2798 data_time: 0.0076 memory: 5828 grad_norm: 6.0477 loss: 1.4763 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4763 2023/06/05 20:40:54 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:40:54 - mmengine - INFO - Epoch(train) [147][2569/2569] lr: 4.0000e-04 eta: 0:34:14 time: 0.2596 data_time: 0.0074 memory: 5828 grad_norm: 5.9851 loss: 1.6762 top1_acc: 0.8333 top5_acc: 0.8333 loss_cls: 1.6762 2023/06/05 20:41:01 - mmengine - INFO - Epoch(train) [148][ 20/2569] lr: 4.0000e-04 eta: 0:34:09 time: 0.3369 data_time: 0.0400 memory: 5828 grad_norm: 6.0300 loss: 1.6797 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6797 2023/06/05 20:41:06 - mmengine - INFO - Epoch(train) [148][ 40/2569] lr: 4.0000e-04 eta: 0:34:04 time: 0.2647 data_time: 0.0070 memory: 5828 grad_norm: 5.7811 loss: 1.7016 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7016 2023/06/05 20:41:12 - mmengine - INFO - Epoch(train) [148][ 60/2569] lr: 4.0000e-04 eta: 0:33:59 time: 0.2713 data_time: 0.0074 memory: 5828 grad_norm: 6.0576 loss: 1.7534 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7534 2023/06/05 20:41:17 - mmengine - INFO - Epoch(train) [148][ 80/2569] lr: 4.0000e-04 eta: 0:33:53 time: 0.2650 data_time: 0.0073 memory: 5828 grad_norm: 6.0711 loss: 1.6780 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6780 2023/06/05 20:41:22 - mmengine - INFO - Epoch(train) [148][ 100/2569] lr: 4.0000e-04 eta: 0:33:48 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 5.8849 loss: 1.4821 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4821 2023/06/05 20:41:28 - mmengine - INFO - Epoch(train) [148][ 120/2569] lr: 4.0000e-04 eta: 0:33:43 time: 0.2636 data_time: 0.0076 memory: 5828 grad_norm: 5.9473 loss: 1.4838 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4838 2023/06/05 20:41:33 - mmengine - INFO - Epoch(train) [148][ 140/2569] lr: 4.0000e-04 eta: 0:33:37 time: 0.2676 data_time: 0.0075 memory: 5828 grad_norm: 6.0049 loss: 1.6387 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6387 2023/06/05 20:41:38 - mmengine - INFO - Epoch(train) [148][ 160/2569] lr: 4.0000e-04 eta: 0:33:32 time: 0.2673 data_time: 0.0073 memory: 5828 grad_norm: 5.9518 loss: 1.6584 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6584 2023/06/05 20:41:44 - mmengine - INFO - Epoch(train) [148][ 180/2569] lr: 4.0000e-04 eta: 0:33:27 time: 0.2629 data_time: 0.0073 memory: 5828 grad_norm: 5.8021 loss: 1.4345 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4345 2023/06/05 20:41:49 - mmengine - INFO - Epoch(train) [148][ 200/2569] lr: 4.0000e-04 eta: 0:33:21 time: 0.2687 data_time: 0.0071 memory: 5828 grad_norm: 5.7511 loss: 1.5490 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5490 2023/06/05 20:41:55 - mmengine - INFO - Epoch(train) [148][ 220/2569] lr: 4.0000e-04 eta: 0:33:16 time: 0.2725 data_time: 0.0073 memory: 5828 grad_norm: 5.9959 loss: 1.7307 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7307 2023/06/05 20:42:00 - mmengine - INFO - Epoch(train) [148][ 240/2569] lr: 4.0000e-04 eta: 0:33:11 time: 0.2704 data_time: 0.0075 memory: 5828 grad_norm: 5.9590 loss: 1.8441 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8441 2023/06/05 20:42:05 - mmengine - INFO - Epoch(train) [148][ 260/2569] lr: 4.0000e-04 eta: 0:33:05 time: 0.2733 data_time: 0.0071 memory: 5828 grad_norm: 5.9509 loss: 1.3154 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.3154 2023/06/05 20:42:11 - mmengine - INFO - Epoch(train) [148][ 280/2569] lr: 4.0000e-04 eta: 0:33:00 time: 0.2621 data_time: 0.0072 memory: 5828 grad_norm: 5.8239 loss: 1.4635 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4635 2023/06/05 20:42:16 - mmengine - INFO - Epoch(train) [148][ 300/2569] lr: 4.0000e-04 eta: 0:32:55 time: 0.2661 data_time: 0.0074 memory: 5828 grad_norm: 5.9084 loss: 1.3418 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3418 2023/06/05 20:42:21 - mmengine - INFO - Epoch(train) [148][ 320/2569] lr: 4.0000e-04 eta: 0:32:49 time: 0.2622 data_time: 0.0074 memory: 5828 grad_norm: 5.9213 loss: 1.5794 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5794 2023/06/05 20:42:27 - mmengine - INFO - Epoch(train) [148][ 340/2569] lr: 4.0000e-04 eta: 0:32:44 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 6.4114 loss: 1.3338 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.3338 2023/06/05 20:42:31 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:42:32 - mmengine - INFO - Epoch(train) [148][ 360/2569] lr: 4.0000e-04 eta: 0:32:39 time: 0.2689 data_time: 0.0073 memory: 5828 grad_norm: 5.9016 loss: 1.6116 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6116 2023/06/05 20:42:37 - mmengine - INFO - Epoch(train) [148][ 380/2569] lr: 4.0000e-04 eta: 0:32:33 time: 0.2622 data_time: 0.0073 memory: 5828 grad_norm: 5.7993 loss: 1.2784 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.2784 2023/06/05 20:42:43 - mmengine - INFO - Epoch(train) [148][ 400/2569] lr: 4.0000e-04 eta: 0:32:28 time: 0.2699 data_time: 0.0071 memory: 5828 grad_norm: 5.8838 loss: 1.7286 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7286 2023/06/05 20:42:48 - mmengine - INFO - Epoch(train) [148][ 420/2569] lr: 4.0000e-04 eta: 0:32:23 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 5.9832 loss: 1.5555 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5555 2023/06/05 20:42:53 - mmengine - INFO - Epoch(train) [148][ 440/2569] lr: 4.0000e-04 eta: 0:32:17 time: 0.2716 data_time: 0.0072 memory: 5828 grad_norm: 5.8123 loss: 1.5421 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5421 2023/06/05 20:42:59 - mmengine - INFO - Epoch(train) [148][ 460/2569] lr: 4.0000e-04 eta: 0:32:12 time: 0.2652 data_time: 0.0075 memory: 5828 grad_norm: 5.8837 loss: 1.6414 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6414 2023/06/05 20:43:04 - mmengine - INFO - Epoch(train) [148][ 480/2569] lr: 4.0000e-04 eta: 0:32:07 time: 0.2691 data_time: 0.0072 memory: 5828 grad_norm: 5.7716 loss: 1.4261 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4261 2023/06/05 20:43:10 - mmengine - INFO - Epoch(train) [148][ 500/2569] lr: 4.0000e-04 eta: 0:32:01 time: 0.2709 data_time: 0.0075 memory: 5828 grad_norm: 5.8838 loss: 1.6162 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6162 2023/06/05 20:43:15 - mmengine - INFO - Epoch(train) [148][ 520/2569] lr: 4.0000e-04 eta: 0:31:56 time: 0.2729 data_time: 0.0075 memory: 5828 grad_norm: 5.9341 loss: 1.5682 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5682 2023/06/05 20:43:21 - mmengine - INFO - Epoch(train) [148][ 540/2569] lr: 4.0000e-04 eta: 0:31:51 time: 0.2766 data_time: 0.0076 memory: 5828 grad_norm: 5.8056 loss: 1.4932 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4932 2023/06/05 20:43:26 - mmengine - INFO - Epoch(train) [148][ 560/2569] lr: 4.0000e-04 eta: 0:31:45 time: 0.2795 data_time: 0.0072 memory: 5828 grad_norm: 5.8298 loss: 1.7451 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7451 2023/06/05 20:43:32 - mmengine - INFO - Epoch(train) [148][ 580/2569] lr: 4.0000e-04 eta: 0:31:40 time: 0.2746 data_time: 0.0084 memory: 5828 grad_norm: 6.0978 loss: 1.6881 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6881 2023/06/05 20:43:37 - mmengine - INFO - Epoch(train) [148][ 600/2569] lr: 4.0000e-04 eta: 0:31:35 time: 0.2725 data_time: 0.0071 memory: 5828 grad_norm: 5.9083 loss: 1.3744 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.3744 2023/06/05 20:43:42 - mmengine - INFO - Epoch(train) [148][ 620/2569] lr: 4.0000e-04 eta: 0:31:29 time: 0.2683 data_time: 0.0072 memory: 5828 grad_norm: 5.7914 loss: 1.5791 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5791 2023/06/05 20:43:48 - mmengine - INFO - Epoch(train) [148][ 640/2569] lr: 4.0000e-04 eta: 0:31:24 time: 0.2743 data_time: 0.0076 memory: 5828 grad_norm: 5.9886 loss: 2.0598 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 2.0598 2023/06/05 20:43:53 - mmengine - INFO - Epoch(train) [148][ 660/2569] lr: 4.0000e-04 eta: 0:31:19 time: 0.2725 data_time: 0.0073 memory: 5828 grad_norm: 5.9501 loss: 1.5086 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5086 2023/06/05 20:43:59 - mmengine - INFO - Epoch(train) [148][ 680/2569] lr: 4.0000e-04 eta: 0:31:13 time: 0.2711 data_time: 0.0077 memory: 5828 grad_norm: 5.9855 loss: 1.7238 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7238 2023/06/05 20:44:04 - mmengine - INFO - Epoch(train) [148][ 700/2569] lr: 4.0000e-04 eta: 0:31:08 time: 0.2692 data_time: 0.0073 memory: 5828 grad_norm: 5.8804 loss: 1.3484 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3484 2023/06/05 20:44:10 - mmengine - INFO - Epoch(train) [148][ 720/2569] lr: 4.0000e-04 eta: 0:31:03 time: 0.2655 data_time: 0.0071 memory: 5828 grad_norm: 6.0770 loss: 1.5613 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5613 2023/06/05 20:44:15 - mmengine - INFO - Epoch(train) [148][ 740/2569] lr: 4.0000e-04 eta: 0:30:57 time: 0.2674 data_time: 0.0075 memory: 5828 grad_norm: 5.9493 loss: 1.6010 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6010 2023/06/05 20:44:20 - mmengine - INFO - Epoch(train) [148][ 760/2569] lr: 4.0000e-04 eta: 0:30:52 time: 0.2680 data_time: 0.0074 memory: 5828 grad_norm: 5.9735 loss: 1.7841 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7841 2023/06/05 20:44:26 - mmengine - INFO - Epoch(train) [148][ 780/2569] lr: 4.0000e-04 eta: 0:30:47 time: 0.2693 data_time: 0.0074 memory: 5828 grad_norm: 5.8555 loss: 1.7992 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7992 2023/06/05 20:44:31 - mmengine - INFO - Epoch(train) [148][ 800/2569] lr: 4.0000e-04 eta: 0:30:41 time: 0.2739 data_time: 0.0072 memory: 5828 grad_norm: 5.8010 loss: 1.3685 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3685 2023/06/05 20:44:37 - mmengine - INFO - Epoch(train) [148][ 820/2569] lr: 4.0000e-04 eta: 0:30:36 time: 0.2667 data_time: 0.0072 memory: 5828 grad_norm: 5.8780 loss: 1.5945 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5945 2023/06/05 20:44:42 - mmengine - INFO - Epoch(train) [148][ 840/2569] lr: 4.0000e-04 eta: 0:30:31 time: 0.2653 data_time: 0.0070 memory: 5828 grad_norm: 6.0220 loss: 1.8560 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8560 2023/06/05 20:44:47 - mmengine - INFO - Epoch(train) [148][ 860/2569] lr: 4.0000e-04 eta: 0:30:25 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 5.8694 loss: 1.6245 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6245 2023/06/05 20:44:53 - mmengine - INFO - Epoch(train) [148][ 880/2569] lr: 4.0000e-04 eta: 0:30:20 time: 0.2805 data_time: 0.0072 memory: 5828 grad_norm: 5.9199 loss: 1.8026 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8026 2023/06/05 20:44:58 - mmengine - INFO - Epoch(train) [148][ 900/2569] lr: 4.0000e-04 eta: 0:30:15 time: 0.2683 data_time: 0.0073 memory: 5828 grad_norm: 5.9691 loss: 1.5110 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5110 2023/06/05 20:45:04 - mmengine - INFO - Epoch(train) [148][ 920/2569] lr: 4.0000e-04 eta: 0:30:09 time: 0.2719 data_time: 0.0075 memory: 5828 grad_norm: 5.7436 loss: 1.2313 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.2313 2023/06/05 20:45:09 - mmengine - INFO - Epoch(train) [148][ 940/2569] lr: 4.0000e-04 eta: 0:30:04 time: 0.2698 data_time: 0.0075 memory: 5828 grad_norm: 5.9221 loss: 1.4713 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4713 2023/06/05 20:45:14 - mmengine - INFO - Epoch(train) [148][ 960/2569] lr: 4.0000e-04 eta: 0:29:59 time: 0.2643 data_time: 0.0072 memory: 5828 grad_norm: 5.9280 loss: 1.8290 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8290 2023/06/05 20:45:20 - mmengine - INFO - Epoch(train) [148][ 980/2569] lr: 4.0000e-04 eta: 0:29:53 time: 0.2618 data_time: 0.0072 memory: 5828 grad_norm: 5.8632 loss: 1.7933 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7933 2023/06/05 20:45:25 - mmengine - INFO - Epoch(train) [148][1000/2569] lr: 4.0000e-04 eta: 0:29:48 time: 0.2623 data_time: 0.0071 memory: 5828 grad_norm: 5.8879 loss: 1.5826 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5826 2023/06/05 20:45:30 - mmengine - INFO - Epoch(train) [148][1020/2569] lr: 4.0000e-04 eta: 0:29:43 time: 0.2729 data_time: 0.0076 memory: 5828 grad_norm: 5.8590 loss: 1.7570 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7570 2023/06/05 20:45:36 - mmengine - INFO - Epoch(train) [148][1040/2569] lr: 4.0000e-04 eta: 0:29:37 time: 0.2692 data_time: 0.0075 memory: 5828 grad_norm: 5.9756 loss: 1.6882 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6882 2023/06/05 20:45:41 - mmengine - INFO - Epoch(train) [148][1060/2569] lr: 4.0000e-04 eta: 0:29:32 time: 0.2733 data_time: 0.0075 memory: 5828 grad_norm: 5.9459 loss: 1.5510 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5510 2023/06/05 20:45:47 - mmengine - INFO - Epoch(train) [148][1080/2569] lr: 4.0000e-04 eta: 0:29:27 time: 0.2711 data_time: 0.0073 memory: 5828 grad_norm: 6.0434 loss: 1.6798 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6798 2023/06/05 20:45:52 - mmengine - INFO - Epoch(train) [148][1100/2569] lr: 4.0000e-04 eta: 0:29:21 time: 0.2799 data_time: 0.0072 memory: 5828 grad_norm: 5.8206 loss: 1.5315 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5315 2023/06/05 20:45:58 - mmengine - INFO - Epoch(train) [148][1120/2569] lr: 4.0000e-04 eta: 0:29:16 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 5.9808 loss: 1.6016 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6016 2023/06/05 20:46:03 - mmengine - INFO - Epoch(train) [148][1140/2569] lr: 4.0000e-04 eta: 0:29:11 time: 0.2739 data_time: 0.0071 memory: 5828 grad_norm: 5.8562 loss: 1.5936 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5936 2023/06/05 20:46:09 - mmengine - INFO - Epoch(train) [148][1160/2569] lr: 4.0000e-04 eta: 0:29:05 time: 0.2724 data_time: 0.0074 memory: 5828 grad_norm: 5.9172 loss: 1.8399 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8399 2023/06/05 20:46:14 - mmengine - INFO - Epoch(train) [148][1180/2569] lr: 4.0000e-04 eta: 0:29:00 time: 0.2717 data_time: 0.0076 memory: 5828 grad_norm: 5.9647 loss: 1.9769 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.9769 2023/06/05 20:46:19 - mmengine - INFO - Epoch(train) [148][1200/2569] lr: 4.0000e-04 eta: 0:28:55 time: 0.2721 data_time: 0.0073 memory: 5828 grad_norm: 5.8635 loss: 1.5752 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5752 2023/06/05 20:46:25 - mmengine - INFO - Epoch(train) [148][1220/2569] lr: 4.0000e-04 eta: 0:28:49 time: 0.2695 data_time: 0.0075 memory: 5828 grad_norm: 5.9671 loss: 1.3563 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.3563 2023/06/05 20:46:30 - mmengine - INFO - Epoch(train) [148][1240/2569] lr: 4.0000e-04 eta: 0:28:44 time: 0.2762 data_time: 0.0079 memory: 5828 grad_norm: 5.9151 loss: 1.5910 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5910 2023/06/05 20:46:36 - mmengine - INFO - Epoch(train) [148][1260/2569] lr: 4.0000e-04 eta: 0:28:39 time: 0.2735 data_time: 0.0071 memory: 5828 grad_norm: 5.7711 loss: 1.6336 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6336 2023/06/05 20:46:41 - mmengine - INFO - Epoch(train) [148][1280/2569] lr: 4.0000e-04 eta: 0:28:33 time: 0.2639 data_time: 0.0074 memory: 5828 grad_norm: 5.7551 loss: 1.4309 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4309 2023/06/05 20:46:47 - mmengine - INFO - Epoch(train) [148][1300/2569] lr: 4.0000e-04 eta: 0:28:28 time: 0.2741 data_time: 0.0073 memory: 5828 grad_norm: 5.9987 loss: 1.8176 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8176 2023/06/05 20:46:52 - mmengine - INFO - Epoch(train) [148][1320/2569] lr: 4.0000e-04 eta: 0:28:23 time: 0.2686 data_time: 0.0075 memory: 5828 grad_norm: 5.8763 loss: 1.5262 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5262 2023/06/05 20:46:57 - mmengine - INFO - Epoch(train) [148][1340/2569] lr: 4.0000e-04 eta: 0:28:17 time: 0.2626 data_time: 0.0073 memory: 5828 grad_norm: 5.8968 loss: 1.6742 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6742 2023/06/05 20:47:02 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:47:03 - mmengine - INFO - Epoch(train) [148][1360/2569] lr: 4.0000e-04 eta: 0:28:12 time: 0.2819 data_time: 0.0077 memory: 5828 grad_norm: 5.8160 loss: 1.5129 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.5129 2023/06/05 20:47:08 - mmengine - INFO - Epoch(train) [148][1380/2569] lr: 4.0000e-04 eta: 0:28:07 time: 0.2731 data_time: 0.0077 memory: 5828 grad_norm: 5.9155 loss: 1.4032 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4032 2023/06/05 20:47:14 - mmengine - INFO - Epoch(train) [148][1400/2569] lr: 4.0000e-04 eta: 0:28:01 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 5.9288 loss: 1.8182 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8182 2023/06/05 20:47:19 - mmengine - INFO - Epoch(train) [148][1420/2569] lr: 4.0000e-04 eta: 0:27:56 time: 0.2826 data_time: 0.0071 memory: 5828 grad_norm: 5.9578 loss: 1.6901 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6901 2023/06/05 20:47:25 - mmengine - INFO - Epoch(train) [148][1440/2569] lr: 4.0000e-04 eta: 0:27:51 time: 0.2668 data_time: 0.0071 memory: 5828 grad_norm: 5.9692 loss: 1.7654 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7654 2023/06/05 20:47:30 - mmengine - INFO - Epoch(train) [148][1460/2569] lr: 4.0000e-04 eta: 0:27:45 time: 0.2622 data_time: 0.0072 memory: 5828 grad_norm: 6.0185 loss: 1.6752 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6752 2023/06/05 20:47:36 - mmengine - INFO - Epoch(train) [148][1480/2569] lr: 4.0000e-04 eta: 0:27:40 time: 0.2773 data_time: 0.0073 memory: 5828 grad_norm: 5.9741 loss: 1.2997 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.2997 2023/06/05 20:47:41 - mmengine - INFO - Epoch(train) [148][1500/2569] lr: 4.0000e-04 eta: 0:27:35 time: 0.2678 data_time: 0.0077 memory: 5828 grad_norm: 5.9325 loss: 1.4544 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.4544 2023/06/05 20:47:46 - mmengine - INFO - Epoch(train) [148][1520/2569] lr: 4.0000e-04 eta: 0:27:29 time: 0.2637 data_time: 0.0073 memory: 5828 grad_norm: 5.9363 loss: 1.5906 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5906 2023/06/05 20:47:52 - mmengine - INFO - Epoch(train) [148][1540/2569] lr: 4.0000e-04 eta: 0:27:24 time: 0.2746 data_time: 0.0077 memory: 5828 grad_norm: 5.8935 loss: 1.3671 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.3671 2023/06/05 20:47:57 - mmengine - INFO - Epoch(train) [148][1560/2569] lr: 4.0000e-04 eta: 0:27:19 time: 0.2686 data_time: 0.0070 memory: 5828 grad_norm: 5.9386 loss: 1.3808 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.3808 2023/06/05 20:48:03 - mmengine - INFO - Epoch(train) [148][1580/2569] lr: 4.0000e-04 eta: 0:27:13 time: 0.2669 data_time: 0.0075 memory: 5828 grad_norm: 5.8766 loss: 1.7788 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7788 2023/06/05 20:48:08 - mmengine - INFO - Epoch(train) [148][1600/2569] lr: 4.0000e-04 eta: 0:27:08 time: 0.2677 data_time: 0.0080 memory: 5828 grad_norm: 5.9034 loss: 1.5424 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5424 2023/06/05 20:48:13 - mmengine - INFO - Epoch(train) [148][1620/2569] lr: 4.0000e-04 eta: 0:27:03 time: 0.2714 data_time: 0.0087 memory: 5828 grad_norm: 5.8631 loss: 1.5814 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5814 2023/06/05 20:48:19 - mmengine - INFO - Epoch(train) [148][1640/2569] lr: 4.0000e-04 eta: 0:26:57 time: 0.2628 data_time: 0.0073 memory: 5828 grad_norm: 5.8332 loss: 1.5011 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5011 2023/06/05 20:48:24 - mmengine - INFO - Epoch(train) [148][1660/2569] lr: 4.0000e-04 eta: 0:26:52 time: 0.2654 data_time: 0.0074 memory: 5828 grad_norm: 6.0069 loss: 1.5758 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5758 2023/06/05 20:48:29 - mmengine - INFO - Epoch(train) [148][1680/2569] lr: 4.0000e-04 eta: 0:26:47 time: 0.2738 data_time: 0.0075 memory: 5828 grad_norm: 5.9226 loss: 1.7667 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.7667 2023/06/05 20:48:35 - mmengine - INFO - Epoch(train) [148][1700/2569] lr: 4.0000e-04 eta: 0:26:41 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 5.9154 loss: 1.5096 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5096 2023/06/05 20:48:40 - mmengine - INFO - Epoch(train) [148][1720/2569] lr: 4.0000e-04 eta: 0:26:36 time: 0.2723 data_time: 0.0074 memory: 5828 grad_norm: 5.9869 loss: 1.4687 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4687 2023/06/05 20:48:46 - mmengine - INFO - Epoch(train) [148][1740/2569] lr: 4.0000e-04 eta: 0:26:31 time: 0.2660 data_time: 0.0072 memory: 5828 grad_norm: 5.8510 loss: 1.5233 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5233 2023/06/05 20:48:51 - mmengine - INFO - Epoch(train) [148][1760/2569] lr: 4.0000e-04 eta: 0:26:25 time: 0.2750 data_time: 0.0078 memory: 5828 grad_norm: 5.9887 loss: 1.4804 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.4804 2023/06/05 20:48:56 - mmengine - INFO - Epoch(train) [148][1780/2569] lr: 4.0000e-04 eta: 0:26:20 time: 0.2619 data_time: 0.0072 memory: 5828 grad_norm: 5.9512 loss: 1.5072 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5072 2023/06/05 20:49:02 - mmengine - INFO - Epoch(train) [148][1800/2569] lr: 4.0000e-04 eta: 0:26:15 time: 0.2738 data_time: 0.0073 memory: 5828 grad_norm: 6.0025 loss: 1.5580 top1_acc: 0.2500 top5_acc: 0.8750 loss_cls: 1.5580 2023/06/05 20:49:07 - mmengine - INFO - Epoch(train) [148][1820/2569] lr: 4.0000e-04 eta: 0:26:09 time: 0.2751 data_time: 0.0073 memory: 5828 grad_norm: 6.0402 loss: 1.6900 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6900 2023/06/05 20:49:13 - mmengine - INFO - Epoch(train) [148][1840/2569] lr: 4.0000e-04 eta: 0:26:04 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 5.8794 loss: 1.5669 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.5669 2023/06/05 20:49:18 - mmengine - INFO - Epoch(train) [148][1860/2569] lr: 4.0000e-04 eta: 0:25:59 time: 0.2668 data_time: 0.0073 memory: 5828 grad_norm: 5.9673 loss: 1.6218 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6218 2023/06/05 20:49:23 - mmengine - INFO - Epoch(train) [148][1880/2569] lr: 4.0000e-04 eta: 0:25:53 time: 0.2660 data_time: 0.0070 memory: 5828 grad_norm: 5.9089 loss: 1.6829 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6829 2023/06/05 20:49:29 - mmengine - INFO - Epoch(train) [148][1900/2569] lr: 4.0000e-04 eta: 0:25:48 time: 0.2691 data_time: 0.0071 memory: 5828 grad_norm: 5.9531 loss: 1.4328 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4328 2023/06/05 20:49:34 - mmengine - INFO - Epoch(train) [148][1920/2569] lr: 4.0000e-04 eta: 0:25:43 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 5.8621 loss: 1.5111 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5111 2023/06/05 20:49:39 - mmengine - INFO - Epoch(train) [148][1940/2569] lr: 4.0000e-04 eta: 0:25:37 time: 0.2626 data_time: 0.0072 memory: 5828 grad_norm: 5.8988 loss: 1.4439 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4439 2023/06/05 20:49:45 - mmengine - INFO - Epoch(train) [148][1960/2569] lr: 4.0000e-04 eta: 0:25:32 time: 0.2685 data_time: 0.0075 memory: 5828 grad_norm: 6.0042 loss: 1.4516 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4516 2023/06/05 20:49:50 - mmengine - INFO - Epoch(train) [148][1980/2569] lr: 4.0000e-04 eta: 0:25:27 time: 0.2710 data_time: 0.0074 memory: 5828 grad_norm: 5.8784 loss: 1.3740 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.3740 2023/06/05 20:49:55 - mmengine - INFO - Epoch(train) [148][2000/2569] lr: 4.0000e-04 eta: 0:25:21 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 6.0244 loss: 1.6125 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6125 2023/06/05 20:50:01 - mmengine - INFO - Epoch(train) [148][2020/2569] lr: 4.0000e-04 eta: 0:25:16 time: 0.2667 data_time: 0.0073 memory: 5828 grad_norm: 5.9724 loss: 1.4091 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4091 2023/06/05 20:50:06 - mmengine - INFO - Epoch(train) [148][2040/2569] lr: 4.0000e-04 eta: 0:25:11 time: 0.2701 data_time: 0.0077 memory: 5828 grad_norm: 6.0383 loss: 1.7825 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7825 2023/06/05 20:50:12 - mmengine - INFO - Epoch(train) [148][2060/2569] lr: 4.0000e-04 eta: 0:25:05 time: 0.2633 data_time: 0.0073 memory: 5828 grad_norm: 6.0520 loss: 1.5137 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5137 2023/06/05 20:50:17 - mmengine - INFO - Epoch(train) [148][2080/2569] lr: 4.0000e-04 eta: 0:25:00 time: 0.2796 data_time: 0.0072 memory: 5828 grad_norm: 5.9685 loss: 1.6804 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6804 2023/06/05 20:50:23 - mmengine - INFO - Epoch(train) [148][2100/2569] lr: 4.0000e-04 eta: 0:24:55 time: 0.2690 data_time: 0.0072 memory: 5828 grad_norm: 5.8236 loss: 1.4799 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4799 2023/06/05 20:50:28 - mmengine - INFO - Epoch(train) [148][2120/2569] lr: 4.0000e-04 eta: 0:24:49 time: 0.2799 data_time: 0.0074 memory: 5828 grad_norm: 5.8616 loss: 1.6837 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6837 2023/06/05 20:50:34 - mmengine - INFO - Epoch(train) [148][2140/2569] lr: 4.0000e-04 eta: 0:24:44 time: 0.2822 data_time: 0.0077 memory: 5828 grad_norm: 5.9321 loss: 1.6519 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6519 2023/06/05 20:50:39 - mmengine - INFO - Epoch(train) [148][2160/2569] lr: 4.0000e-04 eta: 0:24:39 time: 0.2629 data_time: 0.0072 memory: 5828 grad_norm: 5.9183 loss: 1.3010 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3010 2023/06/05 20:50:45 - mmengine - INFO - Epoch(train) [148][2180/2569] lr: 4.0000e-04 eta: 0:24:33 time: 0.2864 data_time: 0.0073 memory: 5828 grad_norm: 5.9214 loss: 1.4444 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4444 2023/06/05 20:50:50 - mmengine - INFO - Epoch(train) [148][2200/2569] lr: 4.0000e-04 eta: 0:24:28 time: 0.2633 data_time: 0.0074 memory: 5828 grad_norm: 6.0978 loss: 1.8442 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.8442 2023/06/05 20:50:56 - mmengine - INFO - Epoch(train) [148][2220/2569] lr: 4.0000e-04 eta: 0:24:23 time: 0.2746 data_time: 0.0074 memory: 5828 grad_norm: 5.9416 loss: 1.2719 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.2719 2023/06/05 20:51:01 - mmengine - INFO - Epoch(train) [148][2240/2569] lr: 4.0000e-04 eta: 0:24:17 time: 0.2626 data_time: 0.0071 memory: 5828 grad_norm: 5.9656 loss: 1.7285 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7285 2023/06/05 20:51:06 - mmengine - INFO - Epoch(train) [148][2260/2569] lr: 4.0000e-04 eta: 0:24:12 time: 0.2721 data_time: 0.0072 memory: 5828 grad_norm: 6.0405 loss: 1.4696 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4696 2023/06/05 20:51:12 - mmengine - INFO - Epoch(train) [148][2280/2569] lr: 4.0000e-04 eta: 0:24:07 time: 0.2616 data_time: 0.0075 memory: 5828 grad_norm: 5.9433 loss: 1.4239 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4239 2023/06/05 20:51:17 - mmengine - INFO - Epoch(train) [148][2300/2569] lr: 4.0000e-04 eta: 0:24:01 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 6.0696 loss: 1.7793 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7793 2023/06/05 20:51:22 - mmengine - INFO - Epoch(train) [148][2320/2569] lr: 4.0000e-04 eta: 0:23:56 time: 0.2732 data_time: 0.0073 memory: 5828 grad_norm: 5.9565 loss: 1.6915 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6915 2023/06/05 20:51:28 - mmengine - INFO - Epoch(train) [148][2340/2569] lr: 4.0000e-04 eta: 0:23:51 time: 0.2777 data_time: 0.0069 memory: 5828 grad_norm: 5.9617 loss: 1.4181 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4181 2023/06/05 20:51:32 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:51:33 - mmengine - INFO - Epoch(train) [148][2360/2569] lr: 4.0000e-04 eta: 0:23:45 time: 0.2661 data_time: 0.0073 memory: 5828 grad_norm: 5.9043 loss: 1.5707 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5707 2023/06/05 20:51:39 - mmengine - INFO - Epoch(train) [148][2380/2569] lr: 4.0000e-04 eta: 0:23:40 time: 0.2753 data_time: 0.0070 memory: 5828 grad_norm: 6.0407 loss: 1.3672 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.3672 2023/06/05 20:51:44 - mmengine - INFO - Epoch(train) [148][2400/2569] lr: 4.0000e-04 eta: 0:23:35 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 5.9359 loss: 1.4118 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4118 2023/06/05 20:51:50 - mmengine - INFO - Epoch(train) [148][2420/2569] lr: 4.0000e-04 eta: 0:23:29 time: 0.2803 data_time: 0.0074 memory: 5828 grad_norm: 5.9085 loss: 1.4100 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4100 2023/06/05 20:51:55 - mmengine - INFO - Epoch(train) [148][2440/2569] lr: 4.0000e-04 eta: 0:23:24 time: 0.2748 data_time: 0.0076 memory: 5828 grad_norm: 5.9040 loss: 1.6280 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6280 2023/06/05 20:52:00 - mmengine - INFO - Epoch(train) [148][2460/2569] lr: 4.0000e-04 eta: 0:23:19 time: 0.2649 data_time: 0.0074 memory: 5828 grad_norm: 5.9037 loss: 1.7219 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7219 2023/06/05 20:52:06 - mmengine - INFO - Epoch(train) [148][2480/2569] lr: 4.0000e-04 eta: 0:23:13 time: 0.2689 data_time: 0.0081 memory: 5828 grad_norm: 6.0516 loss: 1.8753 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8753 2023/06/05 20:52:11 - mmengine - INFO - Epoch(train) [148][2500/2569] lr: 4.0000e-04 eta: 0:23:08 time: 0.2645 data_time: 0.0076 memory: 5828 grad_norm: 5.8804 loss: 1.6853 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6853 2023/06/05 20:52:17 - mmengine - INFO - Epoch(train) [148][2520/2569] lr: 4.0000e-04 eta: 0:23:03 time: 0.2742 data_time: 0.0075 memory: 5828 grad_norm: 5.9876 loss: 1.6397 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6397 2023/06/05 20:52:22 - mmengine - INFO - Epoch(train) [148][2540/2569] lr: 4.0000e-04 eta: 0:22:57 time: 0.2737 data_time: 0.0073 memory: 5828 grad_norm: 5.9619 loss: 1.4709 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4709 2023/06/05 20:52:27 - mmengine - INFO - Epoch(train) [148][2560/2569] lr: 4.0000e-04 eta: 0:22:52 time: 0.2614 data_time: 0.0076 memory: 5828 grad_norm: 6.0177 loss: 1.4536 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4536 2023/06/05 20:52:30 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:52:30 - mmengine - INFO - Epoch(train) [148][2569/2569] lr: 4.0000e-04 eta: 0:22:50 time: 0.2611 data_time: 0.0072 memory: 5828 grad_norm: 6.0472 loss: 1.4622 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.4622 2023/06/05 20:52:30 - mmengine - INFO - Saving checkpoint at 148 epochs 2023/06/05 20:53:13 - mmengine - INFO - Epoch(train) [149][ 20/2569] lr: 4.0000e-04 eta: 0:22:44 time: 0.2945 data_time: 0.0415 memory: 5828 grad_norm: 6.0139 loss: 1.8654 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.8654 2023/06/05 20:53:19 - mmengine - INFO - Epoch(train) [149][ 40/2569] lr: 4.0000e-04 eta: 0:22:39 time: 0.2680 data_time: 0.0078 memory: 5828 grad_norm: 5.9968 loss: 1.4361 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4361 2023/06/05 20:53:24 - mmengine - INFO - Epoch(train) [149][ 60/2569] lr: 4.0000e-04 eta: 0:22:34 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 5.9772 loss: 1.3806 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3806 2023/06/05 20:53:29 - mmengine - INFO - Epoch(train) [149][ 80/2569] lr: 4.0000e-04 eta: 0:22:28 time: 0.2674 data_time: 0.0075 memory: 5828 grad_norm: 5.8143 loss: 1.5373 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5373 2023/06/05 20:53:35 - mmengine - INFO - Epoch(train) [149][ 100/2569] lr: 4.0000e-04 eta: 0:22:23 time: 0.2732 data_time: 0.0076 memory: 5828 grad_norm: 5.9783 loss: 1.8036 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8036 2023/06/05 20:53:40 - mmengine - INFO - Epoch(train) [149][ 120/2569] lr: 4.0000e-04 eta: 0:22:18 time: 0.2619 data_time: 0.0077 memory: 5828 grad_norm: 5.9768 loss: 1.8307 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.8307 2023/06/05 20:53:46 - mmengine - INFO - Epoch(train) [149][ 140/2569] lr: 4.0000e-04 eta: 0:22:12 time: 0.2766 data_time: 0.0077 memory: 5828 grad_norm: 6.0340 loss: 1.3155 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3155 2023/06/05 20:53:51 - mmengine - INFO - Epoch(train) [149][ 160/2569] lr: 4.0000e-04 eta: 0:22:07 time: 0.2685 data_time: 0.0072 memory: 5828 grad_norm: 5.9193 loss: 1.5437 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5437 2023/06/05 20:53:56 - mmengine - INFO - Epoch(train) [149][ 180/2569] lr: 4.0000e-04 eta: 0:22:02 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 6.0809 loss: 1.3515 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3515 2023/06/05 20:54:02 - mmengine - INFO - Epoch(train) [149][ 200/2569] lr: 4.0000e-04 eta: 0:21:56 time: 0.2694 data_time: 0.0072 memory: 5828 grad_norm: 5.9335 loss: 1.2659 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.2659 2023/06/05 20:54:07 - mmengine - INFO - Epoch(train) [149][ 220/2569] lr: 4.0000e-04 eta: 0:21:51 time: 0.2682 data_time: 0.0071 memory: 5828 grad_norm: 5.9177 loss: 1.5797 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5797 2023/06/05 20:54:13 - mmengine - INFO - Epoch(train) [149][ 240/2569] lr: 4.0000e-04 eta: 0:21:46 time: 0.2746 data_time: 0.0072 memory: 5828 grad_norm: 5.9572 loss: 1.5486 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5486 2023/06/05 20:54:18 - mmengine - INFO - Epoch(train) [149][ 260/2569] lr: 4.0000e-04 eta: 0:21:40 time: 0.2635 data_time: 0.0073 memory: 5828 grad_norm: 5.9689 loss: 1.3440 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3440 2023/06/05 20:54:23 - mmengine - INFO - Epoch(train) [149][ 280/2569] lr: 4.0000e-04 eta: 0:21:35 time: 0.2702 data_time: 0.0071 memory: 5828 grad_norm: 5.9305 loss: 1.6200 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6200 2023/06/05 20:54:29 - mmengine - INFO - Epoch(train) [149][ 300/2569] lr: 4.0000e-04 eta: 0:21:30 time: 0.2663 data_time: 0.0073 memory: 5828 grad_norm: 5.8841 loss: 1.7246 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7246 2023/06/05 20:54:34 - mmengine - INFO - Epoch(train) [149][ 320/2569] lr: 4.0000e-04 eta: 0:21:24 time: 0.2763 data_time: 0.0073 memory: 5828 grad_norm: 5.9674 loss: 1.2050 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.2050 2023/06/05 20:54:39 - mmengine - INFO - Epoch(train) [149][ 340/2569] lr: 4.0000e-04 eta: 0:21:19 time: 0.2698 data_time: 0.0077 memory: 5828 grad_norm: 5.9740 loss: 1.5921 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5921 2023/06/05 20:54:45 - mmengine - INFO - Epoch(train) [149][ 360/2569] lr: 4.0000e-04 eta: 0:21:14 time: 0.2641 data_time: 0.0074 memory: 5828 grad_norm: 6.0179 loss: 2.0403 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 2.0403 2023/06/05 20:54:51 - mmengine - INFO - Epoch(train) [149][ 380/2569] lr: 4.0000e-04 eta: 0:21:08 time: 0.2852 data_time: 0.0072 memory: 5828 grad_norm: 5.9567 loss: 1.5782 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.5782 2023/06/05 20:54:56 - mmengine - INFO - Epoch(train) [149][ 400/2569] lr: 4.0000e-04 eta: 0:21:03 time: 0.2681 data_time: 0.0072 memory: 5828 grad_norm: 5.8750 loss: 1.3564 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3564 2023/06/05 20:55:01 - mmengine - INFO - Epoch(train) [149][ 420/2569] lr: 4.0000e-04 eta: 0:20:58 time: 0.2786 data_time: 0.0073 memory: 5828 grad_norm: 5.9693 loss: 1.4906 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4906 2023/06/05 20:55:07 - mmengine - INFO - Epoch(train) [149][ 440/2569] lr: 4.0000e-04 eta: 0:20:52 time: 0.2682 data_time: 0.0075 memory: 5828 grad_norm: 5.8870 loss: 1.5775 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.5775 2023/06/05 20:55:12 - mmengine - INFO - Epoch(train) [149][ 460/2569] lr: 4.0000e-04 eta: 0:20:47 time: 0.2747 data_time: 0.0073 memory: 5828 grad_norm: 5.9569 loss: 1.8376 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.8376 2023/06/05 20:55:18 - mmengine - INFO - Epoch(train) [149][ 480/2569] lr: 4.0000e-04 eta: 0:20:42 time: 0.2737 data_time: 0.0077 memory: 5828 grad_norm: 5.9051 loss: 1.3136 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.3136 2023/06/05 20:55:23 - mmengine - INFO - Epoch(train) [149][ 500/2569] lr: 4.0000e-04 eta: 0:20:36 time: 0.2727 data_time: 0.0074 memory: 5828 grad_norm: 5.8744 loss: 1.3329 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.3329 2023/06/05 20:55:29 - mmengine - INFO - Epoch(train) [149][ 520/2569] lr: 4.0000e-04 eta: 0:20:31 time: 0.2809 data_time: 0.0075 memory: 5828 grad_norm: 5.9739 loss: 1.8489 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8489 2023/06/05 20:55:34 - mmengine - INFO - Epoch(train) [149][ 540/2569] lr: 4.0000e-04 eta: 0:20:26 time: 0.2669 data_time: 0.0073 memory: 5828 grad_norm: 5.8786 loss: 1.5757 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5757 2023/06/05 20:55:40 - mmengine - INFO - Epoch(train) [149][ 560/2569] lr: 4.0000e-04 eta: 0:20:20 time: 0.2677 data_time: 0.0075 memory: 5828 grad_norm: 5.9378 loss: 1.5233 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5233 2023/06/05 20:55:45 - mmengine - INFO - Epoch(train) [149][ 580/2569] lr: 4.0000e-04 eta: 0:20:15 time: 0.2688 data_time: 0.0075 memory: 5828 grad_norm: 5.8670 loss: 1.4322 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4322 2023/06/05 20:55:50 - mmengine - INFO - Epoch(train) [149][ 600/2569] lr: 4.0000e-04 eta: 0:20:10 time: 0.2671 data_time: 0.0074 memory: 5828 grad_norm: 6.0628 loss: 1.4573 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4573 2023/06/05 20:55:56 - mmengine - INFO - Epoch(train) [149][ 620/2569] lr: 4.0000e-04 eta: 0:20:04 time: 0.2747 data_time: 0.0076 memory: 5828 grad_norm: 5.9558 loss: 1.4497 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4497 2023/06/05 20:56:01 - mmengine - INFO - Epoch(train) [149][ 640/2569] lr: 4.0000e-04 eta: 0:19:59 time: 0.2650 data_time: 0.0075 memory: 5828 grad_norm: 5.9508 loss: 1.9595 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9595 2023/06/05 20:56:07 - mmengine - INFO - Epoch(train) [149][ 660/2569] lr: 4.0000e-04 eta: 0:19:54 time: 0.2794 data_time: 0.0077 memory: 5828 grad_norm: 5.9972 loss: 1.8519 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8519 2023/06/05 20:56:12 - mmengine - INFO - Epoch(train) [149][ 680/2569] lr: 4.0000e-04 eta: 0:19:48 time: 0.2719 data_time: 0.0075 memory: 5828 grad_norm: 6.1246 loss: 1.7483 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7483 2023/06/05 20:56:18 - mmengine - INFO - Epoch(train) [149][ 700/2569] lr: 4.0000e-04 eta: 0:19:43 time: 0.2757 data_time: 0.0076 memory: 5828 grad_norm: 6.0173 loss: 1.6250 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6250 2023/06/05 20:56:23 - mmengine - INFO - Epoch(train) [149][ 720/2569] lr: 4.0000e-04 eta: 0:19:38 time: 0.2696 data_time: 0.0074 memory: 5828 grad_norm: 5.9597 loss: 1.7708 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7708 2023/06/05 20:56:29 - mmengine - INFO - Epoch(train) [149][ 740/2569] lr: 4.0000e-04 eta: 0:19:32 time: 0.2742 data_time: 0.0075 memory: 5828 grad_norm: 6.0622 loss: 1.5812 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5812 2023/06/05 20:56:34 - mmengine - INFO - Epoch(train) [149][ 760/2569] lr: 4.0000e-04 eta: 0:19:27 time: 0.2675 data_time: 0.0077 memory: 5828 grad_norm: 6.0076 loss: 1.5019 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5019 2023/06/05 20:56:39 - mmengine - INFO - Epoch(train) [149][ 780/2569] lr: 4.0000e-04 eta: 0:19:22 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 5.9577 loss: 1.8402 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8402 2023/06/05 20:56:42 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 20:56:45 - mmengine - INFO - Epoch(train) [149][ 800/2569] lr: 4.0000e-04 eta: 0:19:16 time: 0.2698 data_time: 0.0078 memory: 5828 grad_norm: 5.9945 loss: 1.3078 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3078 2023/06/05 20:56:50 - mmengine - INFO - Epoch(train) [149][ 820/2569] lr: 4.0000e-04 eta: 0:19:11 time: 0.2796 data_time: 0.0072 memory: 5828 grad_norm: 5.9924 loss: 1.4480 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4480 2023/06/05 20:56:56 - mmengine - INFO - Epoch(train) [149][ 840/2569] lr: 4.0000e-04 eta: 0:19:06 time: 0.2699 data_time: 0.0074 memory: 5828 grad_norm: 5.9644 loss: 1.0428 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.0428 2023/06/05 20:57:02 - mmengine - INFO - Epoch(train) [149][ 860/2569] lr: 4.0000e-04 eta: 0:19:00 time: 0.2859 data_time: 0.0074 memory: 5828 grad_norm: 6.0325 loss: 1.5424 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5424 2023/06/05 20:57:07 - mmengine - INFO - Epoch(train) [149][ 880/2569] lr: 4.0000e-04 eta: 0:18:55 time: 0.2656 data_time: 0.0075 memory: 5828 grad_norm: 5.8927 loss: 1.4914 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4914 2023/06/05 20:57:12 - mmengine - INFO - Epoch(train) [149][ 900/2569] lr: 4.0000e-04 eta: 0:18:50 time: 0.2805 data_time: 0.0072 memory: 5828 grad_norm: 5.9624 loss: 1.3299 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3299 2023/06/05 20:57:18 - mmengine - INFO - Epoch(train) [149][ 920/2569] lr: 4.0000e-04 eta: 0:18:44 time: 0.2795 data_time: 0.0074 memory: 5828 grad_norm: 5.8768 loss: 1.7183 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7183 2023/06/05 20:57:23 - mmengine - INFO - Epoch(train) [149][ 940/2569] lr: 4.0000e-04 eta: 0:18:39 time: 0.2613 data_time: 0.0074 memory: 5828 grad_norm: 5.8779 loss: 1.8489 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8489 2023/06/05 20:57:29 - mmengine - INFO - Epoch(train) [149][ 960/2569] lr: 4.0000e-04 eta: 0:18:34 time: 0.2736 data_time: 0.0077 memory: 5828 grad_norm: 5.9710 loss: 1.9640 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.9640 2023/06/05 20:57:34 - mmengine - INFO - Epoch(train) [149][ 980/2569] lr: 4.0000e-04 eta: 0:18:28 time: 0.2744 data_time: 0.0074 memory: 5828 grad_norm: 5.9378 loss: 1.9004 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9004 2023/06/05 20:57:40 - mmengine - INFO - Epoch(train) [149][1000/2569] lr: 4.0000e-04 eta: 0:18:23 time: 0.2726 data_time: 0.0077 memory: 5828 grad_norm: 6.0190 loss: 1.5191 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5191 2023/06/05 20:57:45 - mmengine - INFO - Epoch(train) [149][1020/2569] lr: 4.0000e-04 eta: 0:18:18 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 5.9092 loss: 1.7216 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7216 2023/06/05 20:57:50 - mmengine - INFO - Epoch(train) [149][1040/2569] lr: 4.0000e-04 eta: 0:18:12 time: 0.2742 data_time: 0.0072 memory: 5828 grad_norm: 5.9767 loss: 1.6769 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6769 2023/06/05 20:57:56 - mmengine - INFO - Epoch(train) [149][1060/2569] lr: 4.0000e-04 eta: 0:18:07 time: 0.2678 data_time: 0.0072 memory: 5828 grad_norm: 6.0368 loss: 1.6138 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6138 2023/06/05 20:58:01 - mmengine - INFO - Epoch(train) [149][1080/2569] lr: 4.0000e-04 eta: 0:18:02 time: 0.2681 data_time: 0.0075 memory: 5828 grad_norm: 5.9252 loss: 1.5867 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5867 2023/06/05 20:58:07 - mmengine - INFO - Epoch(train) [149][1100/2569] lr: 4.0000e-04 eta: 0:17:56 time: 0.2672 data_time: 0.0072 memory: 5828 grad_norm: 6.0218 loss: 1.5888 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5888 2023/06/05 20:58:12 - mmengine - INFO - Epoch(train) [149][1120/2569] lr: 4.0000e-04 eta: 0:17:51 time: 0.2684 data_time: 0.0078 memory: 5828 grad_norm: 5.8937 loss: 1.4703 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.4703 2023/06/05 20:58:17 - mmengine - INFO - Epoch(train) [149][1140/2569] lr: 4.0000e-04 eta: 0:17:46 time: 0.2637 data_time: 0.0074 memory: 5828 grad_norm: 6.0225 loss: 1.4963 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4963 2023/06/05 20:58:23 - mmengine - INFO - Epoch(train) [149][1160/2569] lr: 4.0000e-04 eta: 0:17:40 time: 0.2678 data_time: 0.0074 memory: 5828 grad_norm: 5.9725 loss: 1.5508 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5508 2023/06/05 20:58:28 - mmengine - INFO - Epoch(train) [149][1180/2569] lr: 4.0000e-04 eta: 0:17:35 time: 0.2705 data_time: 0.0080 memory: 5828 grad_norm: 5.9132 loss: 1.8273 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.8273 2023/06/05 20:58:33 - mmengine - INFO - Epoch(train) [149][1200/2569] lr: 4.0000e-04 eta: 0:17:30 time: 0.2646 data_time: 0.0074 memory: 5828 grad_norm: 5.9260 loss: 1.4104 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4104 2023/06/05 20:58:39 - mmengine - INFO - Epoch(train) [149][1220/2569] lr: 4.0000e-04 eta: 0:17:24 time: 0.2681 data_time: 0.0076 memory: 5828 grad_norm: 5.9913 loss: 1.5126 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5126 2023/06/05 20:58:44 - mmengine - INFO - Epoch(train) [149][1240/2569] lr: 4.0000e-04 eta: 0:17:19 time: 0.2690 data_time: 0.0076 memory: 5828 grad_norm: 5.8256 loss: 1.7322 top1_acc: 0.1250 top5_acc: 0.6250 loss_cls: 1.7322 2023/06/05 20:58:49 - mmengine - INFO - Epoch(train) [149][1260/2569] lr: 4.0000e-04 eta: 0:17:14 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 5.8316 loss: 1.5076 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5076 2023/06/05 20:58:55 - mmengine - INFO - Epoch(train) [149][1280/2569] lr: 4.0000e-04 eta: 0:17:08 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 5.8166 loss: 1.5919 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5919 2023/06/05 20:59:00 - mmengine - INFO - Epoch(train) [149][1300/2569] lr: 4.0000e-04 eta: 0:17:03 time: 0.2633 data_time: 0.0071 memory: 5828 grad_norm: 6.0053 loss: 1.7833 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7833 2023/06/05 20:59:06 - mmengine - INFO - Epoch(train) [149][1320/2569] lr: 4.0000e-04 eta: 0:16:58 time: 0.2684 data_time: 0.0073 memory: 5828 grad_norm: 5.9281 loss: 1.6656 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6656 2023/06/05 20:59:11 - mmengine - INFO - Epoch(train) [149][1340/2569] lr: 4.0000e-04 eta: 0:16:52 time: 0.2658 data_time: 0.0072 memory: 5828 grad_norm: 5.9468 loss: 1.4489 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.4489 2023/06/05 20:59:16 - mmengine - INFO - Epoch(train) [149][1360/2569] lr: 4.0000e-04 eta: 0:16:47 time: 0.2684 data_time: 0.0070 memory: 5828 grad_norm: 5.9846 loss: 1.2782 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.2782 2023/06/05 20:59:21 - mmengine - INFO - Epoch(train) [149][1380/2569] lr: 4.0000e-04 eta: 0:16:42 time: 0.2624 data_time: 0.0075 memory: 5828 grad_norm: 5.9147 loss: 1.5663 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5663 2023/06/05 20:59:27 - mmengine - INFO - Epoch(train) [149][1400/2569] lr: 4.0000e-04 eta: 0:16:36 time: 0.2671 data_time: 0.0072 memory: 5828 grad_norm: 5.8830 loss: 1.7163 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.7163 2023/06/05 20:59:32 - mmengine - INFO - Epoch(train) [149][1420/2569] lr: 4.0000e-04 eta: 0:16:31 time: 0.2705 data_time: 0.0076 memory: 5828 grad_norm: 5.9163 loss: 1.4542 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4542 2023/06/05 20:59:38 - mmengine - INFO - Epoch(train) [149][1440/2569] lr: 4.0000e-04 eta: 0:16:26 time: 0.2724 data_time: 0.0073 memory: 5828 grad_norm: 5.9476 loss: 1.1972 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.1972 2023/06/05 20:59:43 - mmengine - INFO - Epoch(train) [149][1460/2569] lr: 4.0000e-04 eta: 0:16:20 time: 0.2875 data_time: 0.0074 memory: 5828 grad_norm: 5.9228 loss: 1.6369 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6369 2023/06/05 20:59:49 - mmengine - INFO - Epoch(train) [149][1480/2569] lr: 4.0000e-04 eta: 0:16:15 time: 0.2688 data_time: 0.0074 memory: 5828 grad_norm: 5.7969 loss: 1.6907 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6907 2023/06/05 20:59:54 - mmengine - INFO - Epoch(train) [149][1500/2569] lr: 4.0000e-04 eta: 0:16:10 time: 0.2679 data_time: 0.0074 memory: 5828 grad_norm: 6.0058 loss: 1.6962 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6962 2023/06/05 21:00:00 - mmengine - INFO - Epoch(train) [149][1520/2569] lr: 4.0000e-04 eta: 0:16:04 time: 0.2690 data_time: 0.0073 memory: 5828 grad_norm: 6.0681 loss: 1.4577 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.4577 2023/06/05 21:00:05 - mmengine - INFO - Epoch(train) [149][1540/2569] lr: 4.0000e-04 eta: 0:15:59 time: 0.2692 data_time: 0.0075 memory: 5828 grad_norm: 5.8906 loss: 1.2579 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.2579 2023/06/05 21:00:10 - mmengine - INFO - Epoch(train) [149][1560/2569] lr: 4.0000e-04 eta: 0:15:54 time: 0.2656 data_time: 0.0074 memory: 5828 grad_norm: 5.9684 loss: 1.4922 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4922 2023/06/05 21:00:16 - mmengine - INFO - Epoch(train) [149][1580/2569] lr: 4.0000e-04 eta: 0:15:48 time: 0.2639 data_time: 0.0075 memory: 5828 grad_norm: 6.0198 loss: 1.3643 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3643 2023/06/05 21:00:21 - mmengine - INFO - Epoch(train) [149][1600/2569] lr: 4.0000e-04 eta: 0:15:43 time: 0.2672 data_time: 0.0073 memory: 5828 grad_norm: 6.0240 loss: 1.7872 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7872 2023/06/05 21:00:26 - mmengine - INFO - Epoch(train) [149][1620/2569] lr: 4.0000e-04 eta: 0:15:38 time: 0.2694 data_time: 0.0073 memory: 5828 grad_norm: 5.9793 loss: 1.7288 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.7288 2023/06/05 21:00:32 - mmengine - INFO - Epoch(train) [149][1640/2569] lr: 4.0000e-04 eta: 0:15:32 time: 0.2676 data_time: 0.0075 memory: 5828 grad_norm: 5.9510 loss: 1.6841 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6841 2023/06/05 21:00:37 - mmengine - INFO - Epoch(train) [149][1660/2569] lr: 4.0000e-04 eta: 0:15:27 time: 0.2728 data_time: 0.0075 memory: 5828 grad_norm: 5.9868 loss: 1.4590 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4590 2023/06/05 21:00:43 - mmengine - INFO - Epoch(train) [149][1680/2569] lr: 4.0000e-04 eta: 0:15:22 time: 0.2787 data_time: 0.0075 memory: 5828 grad_norm: 6.0024 loss: 1.5786 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5786 2023/06/05 21:00:48 - mmengine - INFO - Epoch(train) [149][1700/2569] lr: 4.0000e-04 eta: 0:15:16 time: 0.2681 data_time: 0.0071 memory: 5828 grad_norm: 5.9354 loss: 1.5471 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.5471 2023/06/05 21:00:54 - mmengine - INFO - Epoch(train) [149][1720/2569] lr: 4.0000e-04 eta: 0:15:11 time: 0.2732 data_time: 0.0073 memory: 5828 grad_norm: 5.9150 loss: 1.4951 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4951 2023/06/05 21:00:59 - mmengine - INFO - Epoch(train) [149][1740/2569] lr: 4.0000e-04 eta: 0:15:06 time: 0.2790 data_time: 0.0074 memory: 5828 grad_norm: 5.8738 loss: 1.2686 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.2686 2023/06/05 21:01:05 - mmengine - INFO - Epoch(train) [149][1760/2569] lr: 4.0000e-04 eta: 0:15:00 time: 0.2690 data_time: 0.0074 memory: 5828 grad_norm: 5.8999 loss: 1.5746 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5746 2023/06/05 21:01:10 - mmengine - INFO - Epoch(train) [149][1780/2569] lr: 4.0000e-04 eta: 0:14:55 time: 0.2617 data_time: 0.0073 memory: 5828 grad_norm: 5.8727 loss: 1.9750 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.9750 2023/06/05 21:01:12 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 21:01:15 - mmengine - INFO - Epoch(train) [149][1800/2569] lr: 4.0000e-04 eta: 0:14:50 time: 0.2738 data_time: 0.0075 memory: 5828 grad_norm: 5.8876 loss: 1.6959 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6959 2023/06/05 21:01:21 - mmengine - INFO - Epoch(train) [149][1820/2569] lr: 4.0000e-04 eta: 0:14:44 time: 0.2674 data_time: 0.0077 memory: 5828 grad_norm: 5.8103 loss: 1.5239 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.5239 2023/06/05 21:01:26 - mmengine - INFO - Epoch(train) [149][1840/2569] lr: 4.0000e-04 eta: 0:14:39 time: 0.2715 data_time: 0.0082 memory: 5828 grad_norm: 5.9121 loss: 1.3377 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.3377 2023/06/05 21:01:32 - mmengine - INFO - Epoch(train) [149][1860/2569] lr: 4.0000e-04 eta: 0:14:34 time: 0.2694 data_time: 0.0073 memory: 5828 grad_norm: 5.9901 loss: 1.3434 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3434 2023/06/05 21:01:37 - mmengine - INFO - Epoch(train) [149][1880/2569] lr: 4.0000e-04 eta: 0:14:28 time: 0.2815 data_time: 0.0072 memory: 5828 grad_norm: 5.8693 loss: 1.4585 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4585 2023/06/05 21:01:43 - mmengine - INFO - Epoch(train) [149][1900/2569] lr: 4.0000e-04 eta: 0:14:23 time: 0.2618 data_time: 0.0073 memory: 5828 grad_norm: 5.9790 loss: 1.4994 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4994 2023/06/05 21:01:48 - mmengine - INFO - Epoch(train) [149][1920/2569] lr: 4.0000e-04 eta: 0:14:18 time: 0.2619 data_time: 0.0072 memory: 5828 grad_norm: 6.0231 loss: 1.6051 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.6051 2023/06/05 21:01:53 - mmengine - INFO - Epoch(train) [149][1940/2569] lr: 4.0000e-04 eta: 0:14:12 time: 0.2762 data_time: 0.0074 memory: 5828 grad_norm: 5.8911 loss: 1.6743 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.6743 2023/06/05 21:01:59 - mmengine - INFO - Epoch(train) [149][1960/2569] lr: 4.0000e-04 eta: 0:14:07 time: 0.2632 data_time: 0.0073 memory: 5828 grad_norm: 5.9104 loss: 1.6737 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6737 2023/06/05 21:02:04 - mmengine - INFO - Epoch(train) [149][1980/2569] lr: 4.0000e-04 eta: 0:14:02 time: 0.2712 data_time: 0.0076 memory: 5828 grad_norm: 5.8802 loss: 1.2514 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2514 2023/06/05 21:02:09 - mmengine - INFO - Epoch(train) [149][2000/2569] lr: 4.0000e-04 eta: 0:13:56 time: 0.2636 data_time: 0.0076 memory: 5828 grad_norm: 5.8383 loss: 1.4720 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.4720 2023/06/05 21:02:15 - mmengine - INFO - Epoch(train) [149][2020/2569] lr: 4.0000e-04 eta: 0:13:51 time: 0.2771 data_time: 0.0076 memory: 5828 grad_norm: 6.0654 loss: 1.6434 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6434 2023/06/05 21:02:20 - mmengine - INFO - Epoch(train) [149][2040/2569] lr: 4.0000e-04 eta: 0:13:46 time: 0.2655 data_time: 0.0074 memory: 5828 grad_norm: 6.0236 loss: 1.5990 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.5990 2023/06/05 21:02:26 - mmengine - INFO - Epoch(train) [149][2060/2569] lr: 4.0000e-04 eta: 0:13:40 time: 0.2762 data_time: 0.0071 memory: 5828 grad_norm: 6.0169 loss: 1.5556 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5556 2023/06/05 21:02:31 - mmengine - INFO - Epoch(train) [149][2080/2569] lr: 4.0000e-04 eta: 0:13:35 time: 0.2700 data_time: 0.0075 memory: 5828 grad_norm: 5.9215 loss: 1.5338 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5338 2023/06/05 21:02:37 - mmengine - INFO - Epoch(train) [149][2100/2569] lr: 4.0000e-04 eta: 0:13:30 time: 0.2726 data_time: 0.0077 memory: 5828 grad_norm: 6.0472 loss: 1.5264 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5264 2023/06/05 21:02:42 - mmengine - INFO - Epoch(train) [149][2120/2569] lr: 4.0000e-04 eta: 0:13:24 time: 0.2751 data_time: 0.0077 memory: 5828 grad_norm: 5.9083 loss: 1.6479 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6479 2023/06/05 21:02:48 - mmengine - INFO - Epoch(train) [149][2140/2569] lr: 4.0000e-04 eta: 0:13:19 time: 0.2720 data_time: 0.0084 memory: 5828 grad_norm: 5.9143 loss: 1.4315 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4315 2023/06/05 21:02:53 - mmengine - INFO - Epoch(train) [149][2160/2569] lr: 4.0000e-04 eta: 0:13:14 time: 0.2629 data_time: 0.0077 memory: 5828 grad_norm: 6.0821 loss: 1.3712 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3712 2023/06/05 21:02:58 - mmengine - INFO - Epoch(train) [149][2180/2569] lr: 4.0000e-04 eta: 0:13:08 time: 0.2732 data_time: 0.0076 memory: 5828 grad_norm: 5.8781 loss: 1.4817 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4817 2023/06/05 21:03:04 - mmengine - INFO - Epoch(train) [149][2200/2569] lr: 4.0000e-04 eta: 0:13:03 time: 0.2632 data_time: 0.0070 memory: 5828 grad_norm: 6.0048 loss: 1.6282 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6282 2023/06/05 21:03:09 - mmengine - INFO - Epoch(train) [149][2220/2569] lr: 4.0000e-04 eta: 0:12:58 time: 0.2706 data_time: 0.0072 memory: 5828 grad_norm: 6.0893 loss: 1.5475 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5475 2023/06/05 21:03:14 - mmengine - INFO - Epoch(train) [149][2240/2569] lr: 4.0000e-04 eta: 0:12:52 time: 0.2722 data_time: 0.0071 memory: 5828 grad_norm: 6.0831 loss: 2.0307 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 2.0307 2023/06/05 21:03:20 - mmengine - INFO - Epoch(train) [149][2260/2569] lr: 4.0000e-04 eta: 0:12:47 time: 0.2631 data_time: 0.0071 memory: 5828 grad_norm: 5.8923 loss: 1.7234 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7234 2023/06/05 21:03:25 - mmengine - INFO - Epoch(train) [149][2280/2569] lr: 4.0000e-04 eta: 0:12:42 time: 0.2666 data_time: 0.0074 memory: 5828 grad_norm: 5.9872 loss: 1.7961 top1_acc: 0.2500 top5_acc: 0.6250 loss_cls: 1.7961 2023/06/05 21:03:31 - mmengine - INFO - Epoch(train) [149][2300/2569] lr: 4.0000e-04 eta: 0:12:36 time: 0.2730 data_time: 0.0072 memory: 5828 grad_norm: 5.9588 loss: 1.3829 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.3829 2023/06/05 21:03:36 - mmengine - INFO - Epoch(train) [149][2320/2569] lr: 4.0000e-04 eta: 0:12:31 time: 0.2659 data_time: 0.0071 memory: 5828 grad_norm: 5.8921 loss: 1.3166 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3166 2023/06/05 21:03:41 - mmengine - INFO - Epoch(train) [149][2340/2569] lr: 4.0000e-04 eta: 0:12:26 time: 0.2631 data_time: 0.0073 memory: 5828 grad_norm: 6.0215 loss: 1.4012 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4012 2023/06/05 21:03:47 - mmengine - INFO - Epoch(train) [149][2360/2569] lr: 4.0000e-04 eta: 0:12:20 time: 0.2801 data_time: 0.0072 memory: 5828 grad_norm: 5.9820 loss: 1.6734 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6734 2023/06/05 21:03:52 - mmengine - INFO - Epoch(train) [149][2380/2569] lr: 4.0000e-04 eta: 0:12:15 time: 0.2642 data_time: 0.0071 memory: 5828 grad_norm: 5.9099 loss: 1.6265 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6265 2023/06/05 21:03:58 - mmengine - INFO - Epoch(train) [149][2400/2569] lr: 4.0000e-04 eta: 0:12:10 time: 0.2727 data_time: 0.0074 memory: 5828 grad_norm: 5.9901 loss: 1.6588 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6588 2023/06/05 21:04:03 - mmengine - INFO - Epoch(train) [149][2420/2569] lr: 4.0000e-04 eta: 0:12:04 time: 0.2613 data_time: 0.0075 memory: 5828 grad_norm: 5.9430 loss: 1.6320 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6320 2023/06/05 21:04:08 - mmengine - INFO - Epoch(train) [149][2440/2569] lr: 4.0000e-04 eta: 0:11:59 time: 0.2694 data_time: 0.0078 memory: 5828 grad_norm: 5.8941 loss: 1.8503 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8503 2023/06/05 21:04:14 - mmengine - INFO - Epoch(train) [149][2460/2569] lr: 4.0000e-04 eta: 0:11:54 time: 0.2651 data_time: 0.0075 memory: 5828 grad_norm: 5.9341 loss: 1.7271 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7271 2023/06/05 21:04:19 - mmengine - INFO - Epoch(train) [149][2480/2569] lr: 4.0000e-04 eta: 0:11:48 time: 0.2706 data_time: 0.0076 memory: 5828 grad_norm: 5.8921 loss: 1.2797 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2797 2023/06/05 21:04:24 - mmengine - INFO - Epoch(train) [149][2500/2569] lr: 4.0000e-04 eta: 0:11:43 time: 0.2760 data_time: 0.0076 memory: 5828 grad_norm: 6.0698 loss: 1.7380 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7380 2023/06/05 21:04:30 - mmengine - INFO - Epoch(train) [149][2520/2569] lr: 4.0000e-04 eta: 0:11:38 time: 0.2659 data_time: 0.0073 memory: 5828 grad_norm: 5.9182 loss: 1.6474 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.6474 2023/06/05 21:04:35 - mmengine - INFO - Epoch(train) [149][2540/2569] lr: 4.0000e-04 eta: 0:11:32 time: 0.2702 data_time: 0.0074 memory: 5828 grad_norm: 5.9361 loss: 1.6431 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6431 2023/06/05 21:04:41 - mmengine - INFO - Epoch(train) [149][2560/2569] lr: 4.0000e-04 eta: 0:11:27 time: 0.2690 data_time: 0.0077 memory: 5828 grad_norm: 5.8385 loss: 1.5332 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5332 2023/06/05 21:04:43 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 21:04:43 - mmengine - INFO - Epoch(train) [149][2569/2569] lr: 4.0000e-04 eta: 0:11:25 time: 0.2675 data_time: 0.0075 memory: 5828 grad_norm: 5.8518 loss: 1.4475 top1_acc: 0.6667 top5_acc: 0.6667 loss_cls: 1.4475 2023/06/05 21:04:50 - mmengine - INFO - Epoch(train) [150][ 20/2569] lr: 4.0000e-04 eta: 0:11:19 time: 0.3435 data_time: 0.0606 memory: 5828 grad_norm: 5.8912 loss: 1.6167 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6167 2023/06/05 21:04:55 - mmengine - INFO - Epoch(train) [150][ 40/2569] lr: 4.0000e-04 eta: 0:11:14 time: 0.2714 data_time: 0.0075 memory: 5828 grad_norm: 5.9994 loss: 1.5954 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5954 2023/06/05 21:05:01 - mmengine - INFO - Epoch(train) [150][ 60/2569] lr: 4.0000e-04 eta: 0:11:09 time: 0.2636 data_time: 0.0076 memory: 5828 grad_norm: 5.8734 loss: 1.5795 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5795 2023/06/05 21:05:06 - mmengine - INFO - Epoch(train) [150][ 80/2569] lr: 4.0000e-04 eta: 0:11:03 time: 0.2684 data_time: 0.0076 memory: 5828 grad_norm: 6.0931 loss: 1.4129 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4129 2023/06/05 21:05:11 - mmengine - INFO - Epoch(train) [150][ 100/2569] lr: 4.0000e-04 eta: 0:10:58 time: 0.2735 data_time: 0.0076 memory: 5828 grad_norm: 6.0005 loss: 1.4774 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4774 2023/06/05 21:05:17 - mmengine - INFO - Epoch(train) [150][ 120/2569] lr: 4.0000e-04 eta: 0:10:53 time: 0.2805 data_time: 0.0072 memory: 5828 grad_norm: 6.0080 loss: 1.4388 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4388 2023/06/05 21:05:22 - mmengine - INFO - Epoch(train) [150][ 140/2569] lr: 4.0000e-04 eta: 0:10:47 time: 0.2625 data_time: 0.0074 memory: 5828 grad_norm: 5.8604 loss: 1.5216 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.5216 2023/06/05 21:05:28 - mmengine - INFO - Epoch(train) [150][ 160/2569] lr: 4.0000e-04 eta: 0:10:42 time: 0.2783 data_time: 0.0083 memory: 5828 grad_norm: 5.9700 loss: 1.5717 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5717 2023/06/05 21:05:33 - mmengine - INFO - Epoch(train) [150][ 180/2569] lr: 4.0000e-04 eta: 0:10:37 time: 0.2621 data_time: 0.0074 memory: 5828 grad_norm: 6.0240 loss: 1.6615 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.6615 2023/06/05 21:05:39 - mmengine - INFO - Epoch(train) [150][ 200/2569] lr: 4.0000e-04 eta: 0:10:31 time: 0.2667 data_time: 0.0075 memory: 5828 grad_norm: 5.9215 loss: 1.6972 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6972 2023/06/05 21:05:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 21:05:44 - mmengine - INFO - Epoch(train) [150][ 220/2569] lr: 4.0000e-04 eta: 0:10:26 time: 0.2695 data_time: 0.0075 memory: 5828 grad_norm: 5.9090 loss: 1.7533 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7533 2023/06/05 21:05:49 - mmengine - INFO - Epoch(train) [150][ 240/2569] lr: 4.0000e-04 eta: 0:10:21 time: 0.2635 data_time: 0.0074 memory: 5828 grad_norm: 6.0308 loss: 1.6566 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6566 2023/06/05 21:05:55 - mmengine - INFO - Epoch(train) [150][ 260/2569] lr: 4.0000e-04 eta: 0:10:15 time: 0.2806 data_time: 0.0073 memory: 5828 grad_norm: 6.0638 loss: 1.7271 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7271 2023/06/05 21:06:00 - mmengine - INFO - Epoch(train) [150][ 280/2569] lr: 4.0000e-04 eta: 0:10:10 time: 0.2624 data_time: 0.0073 memory: 5828 grad_norm: 5.9457 loss: 1.4029 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4029 2023/06/05 21:06:06 - mmengine - INFO - Epoch(train) [150][ 300/2569] lr: 4.0000e-04 eta: 0:10:05 time: 0.2776 data_time: 0.0072 memory: 5828 grad_norm: 5.8704 loss: 1.5858 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5858 2023/06/05 21:06:11 - mmengine - INFO - Epoch(train) [150][ 320/2569] lr: 4.0000e-04 eta: 0:09:59 time: 0.2636 data_time: 0.0069 memory: 5828 grad_norm: 5.8792 loss: 1.4858 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.4858 2023/06/05 21:06:16 - mmengine - INFO - Epoch(train) [150][ 340/2569] lr: 4.0000e-04 eta: 0:09:54 time: 0.2679 data_time: 0.0076 memory: 5828 grad_norm: 5.9975 loss: 1.3977 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3977 2023/06/05 21:06:22 - mmengine - INFO - Epoch(train) [150][ 360/2569] lr: 4.0000e-04 eta: 0:09:49 time: 0.2734 data_time: 0.0072 memory: 5828 grad_norm: 5.9302 loss: 1.6000 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6000 2023/06/05 21:06:27 - mmengine - INFO - Epoch(train) [150][ 380/2569] lr: 4.0000e-04 eta: 0:09:43 time: 0.2735 data_time: 0.0075 memory: 5828 grad_norm: 5.8215 loss: 1.3351 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3351 2023/06/05 21:06:33 - mmengine - INFO - Epoch(train) [150][ 400/2569] lr: 4.0000e-04 eta: 0:09:38 time: 0.2777 data_time: 0.0072 memory: 5828 grad_norm: 5.9710 loss: 1.4781 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4781 2023/06/05 21:06:38 - mmengine - INFO - Epoch(train) [150][ 420/2569] lr: 4.0000e-04 eta: 0:09:33 time: 0.2618 data_time: 0.0089 memory: 5828 grad_norm: 5.9679 loss: 1.6898 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6898 2023/06/05 21:06:44 - mmengine - INFO - Epoch(train) [150][ 440/2569] lr: 4.0000e-04 eta: 0:09:27 time: 0.2797 data_time: 0.0073 memory: 5828 grad_norm: 5.9834 loss: 1.5601 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.5601 2023/06/05 21:06:49 - mmengine - INFO - Epoch(train) [150][ 460/2569] lr: 4.0000e-04 eta: 0:09:22 time: 0.2724 data_time: 0.0076 memory: 5828 grad_norm: 5.9810 loss: 1.7163 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7163 2023/06/05 21:06:55 - mmengine - INFO - Epoch(train) [150][ 480/2569] lr: 4.0000e-04 eta: 0:09:17 time: 0.2696 data_time: 0.0074 memory: 5828 grad_norm: 5.8365 loss: 1.6217 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6217 2023/06/05 21:07:00 - mmengine - INFO - Epoch(train) [150][ 500/2569] lr: 4.0000e-04 eta: 0:09:11 time: 0.2676 data_time: 0.0074 memory: 5828 grad_norm: 5.9834 loss: 1.6261 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6261 2023/06/05 21:07:05 - mmengine - INFO - Epoch(train) [150][ 520/2569] lr: 4.0000e-04 eta: 0:09:06 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 6.0020 loss: 1.7112 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.7112 2023/06/05 21:07:11 - mmengine - INFO - Epoch(train) [150][ 540/2569] lr: 4.0000e-04 eta: 0:09:01 time: 0.2673 data_time: 0.0072 memory: 5828 grad_norm: 5.9435 loss: 1.6679 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6679 2023/06/05 21:07:16 - mmengine - INFO - Epoch(train) [150][ 560/2569] lr: 4.0000e-04 eta: 0:08:55 time: 0.2641 data_time: 0.0072 memory: 5828 grad_norm: 5.9387 loss: 1.4284 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4284 2023/06/05 21:07:21 - mmengine - INFO - Epoch(train) [150][ 580/2569] lr: 4.0000e-04 eta: 0:08:50 time: 0.2707 data_time: 0.0073 memory: 5828 grad_norm: 6.0863 loss: 1.6151 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6151 2023/06/05 21:07:27 - mmengine - INFO - Epoch(train) [150][ 600/2569] lr: 4.0000e-04 eta: 0:08:45 time: 0.2625 data_time: 0.0071 memory: 5828 grad_norm: 5.9837 loss: 1.7265 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.7265 2023/06/05 21:07:32 - mmengine - INFO - Epoch(train) [150][ 620/2569] lr: 4.0000e-04 eta: 0:08:39 time: 0.2678 data_time: 0.0072 memory: 5828 grad_norm: 6.0709 loss: 1.4779 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.4779 2023/06/05 21:07:37 - mmengine - INFO - Epoch(train) [150][ 640/2569] lr: 4.0000e-04 eta: 0:08:34 time: 0.2625 data_time: 0.0073 memory: 5828 grad_norm: 6.0105 loss: 1.8578 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.8578 2023/06/05 21:07:43 - mmengine - INFO - Epoch(train) [150][ 660/2569] lr: 4.0000e-04 eta: 0:08:29 time: 0.2755 data_time: 0.0074 memory: 5828 grad_norm: 5.8841 loss: 1.4056 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.4056 2023/06/05 21:07:48 - mmengine - INFO - Epoch(train) [150][ 680/2569] lr: 4.0000e-04 eta: 0:08:23 time: 0.2600 data_time: 0.0073 memory: 5828 grad_norm: 6.0155 loss: 1.3183 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.3183 2023/06/05 21:07:53 - mmengine - INFO - Epoch(train) [150][ 700/2569] lr: 4.0000e-04 eta: 0:08:18 time: 0.2673 data_time: 0.0076 memory: 5828 grad_norm: 5.9908 loss: 1.4170 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.4170 2023/06/05 21:07:59 - mmengine - INFO - Epoch(train) [150][ 720/2569] lr: 4.0000e-04 eta: 0:08:13 time: 0.2672 data_time: 0.0074 memory: 5828 grad_norm: 6.0861 loss: 2.0190 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 2.0190 2023/06/05 21:08:04 - mmengine - INFO - Epoch(train) [150][ 740/2569] lr: 4.0000e-04 eta: 0:08:07 time: 0.2760 data_time: 0.0076 memory: 5828 grad_norm: 5.9999 loss: 1.5213 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.5213 2023/06/05 21:08:10 - mmengine - INFO - Epoch(train) [150][ 760/2569] lr: 4.0000e-04 eta: 0:08:02 time: 0.2680 data_time: 0.0078 memory: 5828 grad_norm: 5.9084 loss: 1.8512 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.8512 2023/06/05 21:08:15 - mmengine - INFO - Epoch(train) [150][ 780/2569] lr: 4.0000e-04 eta: 0:07:57 time: 0.2756 data_time: 0.0073 memory: 5828 grad_norm: 5.8922 loss: 1.4310 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4310 2023/06/05 21:08:20 - mmengine - INFO - Epoch(train) [150][ 800/2569] lr: 4.0000e-04 eta: 0:07:51 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 6.0996 loss: 1.7763 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.7763 2023/06/05 21:08:26 - mmengine - INFO - Epoch(train) [150][ 820/2569] lr: 4.0000e-04 eta: 0:07:46 time: 0.2682 data_time: 0.0075 memory: 5828 grad_norm: 5.9379 loss: 1.3624 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3624 2023/06/05 21:08:31 - mmengine - INFO - Epoch(train) [150][ 840/2569] lr: 4.0000e-04 eta: 0:07:41 time: 0.2643 data_time: 0.0077 memory: 5828 grad_norm: 5.9670 loss: 1.5710 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5710 2023/06/05 21:08:36 - mmengine - INFO - Epoch(train) [150][ 860/2569] lr: 4.0000e-04 eta: 0:07:35 time: 0.2665 data_time: 0.0075 memory: 5828 grad_norm: 5.9734 loss: 1.8811 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.8811 2023/06/05 21:08:42 - mmengine - INFO - Epoch(train) [150][ 880/2569] lr: 4.0000e-04 eta: 0:07:30 time: 0.2643 data_time: 0.0080 memory: 5828 grad_norm: 5.9415 loss: 1.5512 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5512 2023/06/05 21:08:47 - mmengine - INFO - Epoch(train) [150][ 900/2569] lr: 4.0000e-04 eta: 0:07:25 time: 0.2685 data_time: 0.0073 memory: 5828 grad_norm: 6.0391 loss: 1.9862 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.9862 2023/06/05 21:08:53 - mmengine - INFO - Epoch(train) [150][ 920/2569] lr: 4.0000e-04 eta: 0:07:19 time: 0.2745 data_time: 0.0074 memory: 5828 grad_norm: 5.9128 loss: 1.5928 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.5928 2023/06/05 21:08:58 - mmengine - INFO - Epoch(train) [150][ 940/2569] lr: 4.0000e-04 eta: 0:07:14 time: 0.2676 data_time: 0.0074 memory: 5828 grad_norm: 5.9254 loss: 1.4947 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4947 2023/06/05 21:09:03 - mmengine - INFO - Epoch(train) [150][ 960/2569] lr: 4.0000e-04 eta: 0:07:09 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 6.0178 loss: 1.6720 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6720 2023/06/05 21:09:09 - mmengine - INFO - Epoch(train) [150][ 980/2569] lr: 4.0000e-04 eta: 0:07:03 time: 0.2726 data_time: 0.0076 memory: 5828 grad_norm: 6.0241 loss: 1.7651 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.7651 2023/06/05 21:09:14 - mmengine - INFO - Epoch(train) [150][1000/2569] lr: 4.0000e-04 eta: 0:06:58 time: 0.2640 data_time: 0.0072 memory: 5828 grad_norm: 5.9435 loss: 1.8693 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.8693 2023/06/05 21:09:19 - mmengine - INFO - Epoch(train) [150][1020/2569] lr: 4.0000e-04 eta: 0:06:53 time: 0.2704 data_time: 0.0073 memory: 5828 grad_norm: 5.9525 loss: 1.6379 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6379 2023/06/05 21:09:25 - mmengine - INFO - Epoch(train) [150][1040/2569] lr: 4.0000e-04 eta: 0:06:47 time: 0.2693 data_time: 0.0072 memory: 5828 grad_norm: 5.9855 loss: 1.6907 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6907 2023/06/05 21:09:30 - mmengine - INFO - Epoch(train) [150][1060/2569] lr: 4.0000e-04 eta: 0:06:42 time: 0.2743 data_time: 0.0070 memory: 5828 grad_norm: 5.9073 loss: 1.6343 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6343 2023/06/05 21:09:36 - mmengine - INFO - Epoch(train) [150][1080/2569] lr: 4.0000e-04 eta: 0:06:37 time: 0.2720 data_time: 0.0072 memory: 5828 grad_norm: 5.9537 loss: 1.8290 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.8290 2023/06/05 21:09:42 - mmengine - INFO - Epoch(train) [150][1100/2569] lr: 4.0000e-04 eta: 0:06:31 time: 0.2832 data_time: 0.0274 memory: 5828 grad_norm: 6.0041 loss: 1.3355 top1_acc: 0.5000 top5_acc: 1.0000 loss_cls: 1.3355 2023/06/05 21:09:47 - mmengine - INFO - Epoch(train) [150][1120/2569] lr: 4.0000e-04 eta: 0:06:26 time: 0.2759 data_time: 0.0080 memory: 5828 grad_norm: 5.8537 loss: 1.4511 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.4511 2023/06/05 21:09:53 - mmengine - INFO - Epoch(train) [150][1140/2569] lr: 4.0000e-04 eta: 0:06:21 time: 0.2776 data_time: 0.0190 memory: 5828 grad_norm: 5.9909 loss: 1.5722 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.5722 2023/06/05 21:09:58 - mmengine - INFO - Epoch(train) [150][1160/2569] lr: 4.0000e-04 eta: 0:06:15 time: 0.2750 data_time: 0.0175 memory: 5828 grad_norm: 5.8928 loss: 1.5134 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5134 2023/06/05 21:10:04 - mmengine - INFO - Epoch(train) [150][1180/2569] lr: 4.0000e-04 eta: 0:06:10 time: 0.2764 data_time: 0.0222 memory: 5828 grad_norm: 5.9277 loss: 1.8104 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.8104 2023/06/05 21:10:09 - mmengine - INFO - Epoch(train) [150][1200/2569] lr: 4.0000e-04 eta: 0:06:05 time: 0.2734 data_time: 0.0120 memory: 5828 grad_norm: 6.1504 loss: 1.7826 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7826 2023/06/05 21:10:15 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 21:10:15 - mmengine - INFO - Epoch(train) [150][1220/2569] lr: 4.0000e-04 eta: 0:05:59 time: 0.2842 data_time: 0.0176 memory: 5828 grad_norm: 5.9911 loss: 1.3748 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.3748 2023/06/05 21:10:20 - mmengine - INFO - Epoch(train) [150][1240/2569] lr: 4.0000e-04 eta: 0:05:54 time: 0.2681 data_time: 0.0070 memory: 5828 grad_norm: 6.0090 loss: 1.5031 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5031 2023/06/05 21:10:25 - mmengine - INFO - Epoch(train) [150][1260/2569] lr: 4.0000e-04 eta: 0:05:49 time: 0.2621 data_time: 0.0073 memory: 5828 grad_norm: 5.9883 loss: 1.7660 top1_acc: 0.6250 top5_acc: 1.0000 loss_cls: 1.7660 2023/06/05 21:10:31 - mmengine - INFO - Epoch(train) [150][1280/2569] lr: 4.0000e-04 eta: 0:05:43 time: 0.2686 data_time: 0.0071 memory: 5828 grad_norm: 5.8681 loss: 1.6171 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6171 2023/06/05 21:10:36 - mmengine - INFO - Epoch(train) [150][1300/2569] lr: 4.0000e-04 eta: 0:05:38 time: 0.2694 data_time: 0.0072 memory: 5828 grad_norm: 5.9463 loss: 1.4691 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.4691 2023/06/05 21:10:42 - mmengine - INFO - Epoch(train) [150][1320/2569] lr: 4.0000e-04 eta: 0:05:33 time: 0.2705 data_time: 0.0073 memory: 5828 grad_norm: 5.8598 loss: 1.7262 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.7262 2023/06/05 21:10:47 - mmengine - INFO - Epoch(train) [150][1340/2569] lr: 4.0000e-04 eta: 0:05:27 time: 0.2642 data_time: 0.0072 memory: 5828 grad_norm: 6.0550 loss: 1.4756 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4756 2023/06/05 21:10:52 - mmengine - INFO - Epoch(train) [150][1360/2569] lr: 4.0000e-04 eta: 0:05:22 time: 0.2682 data_time: 0.0073 memory: 5828 grad_norm: 5.9454 loss: 1.6048 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6048 2023/06/05 21:10:58 - mmengine - INFO - Epoch(train) [150][1380/2569] lr: 4.0000e-04 eta: 0:05:17 time: 0.2634 data_time: 0.0072 memory: 5828 grad_norm: 5.9500 loss: 1.7158 top1_acc: 0.3750 top5_acc: 0.6250 loss_cls: 1.7158 2023/06/05 21:11:03 - mmengine - INFO - Epoch(train) [150][1400/2569] lr: 4.0000e-04 eta: 0:05:11 time: 0.2681 data_time: 0.0074 memory: 5828 grad_norm: 5.9800 loss: 1.6015 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.6015 2023/06/05 21:11:09 - mmengine - INFO - Epoch(train) [150][1420/2569] lr: 4.0000e-04 eta: 0:05:06 time: 0.2735 data_time: 0.0072 memory: 5828 grad_norm: 6.0481 loss: 1.4491 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4491 2023/06/05 21:11:14 - mmengine - INFO - Epoch(train) [150][1440/2569] lr: 4.0000e-04 eta: 0:05:01 time: 0.2769 data_time: 0.0075 memory: 5828 grad_norm: 5.9839 loss: 1.6287 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6287 2023/06/05 21:11:19 - mmengine - INFO - Epoch(train) [150][1460/2569] lr: 4.0000e-04 eta: 0:04:55 time: 0.2676 data_time: 0.0076 memory: 5828 grad_norm: 5.9916 loss: 1.7188 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.7188 2023/06/05 21:11:25 - mmengine - INFO - Epoch(train) [150][1480/2569] lr: 4.0000e-04 eta: 0:04:50 time: 0.2632 data_time: 0.0075 memory: 5828 grad_norm: 6.0599 loss: 1.7842 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.7842 2023/06/05 21:11:30 - mmengine - INFO - Epoch(train) [150][1500/2569] lr: 4.0000e-04 eta: 0:04:45 time: 0.2626 data_time: 0.0071 memory: 5828 grad_norm: 6.0629 loss: 1.6556 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.6556 2023/06/05 21:11:35 - mmengine - INFO - Epoch(train) [150][1520/2569] lr: 4.0000e-04 eta: 0:04:39 time: 0.2628 data_time: 0.0075 memory: 5828 grad_norm: 6.0921 loss: 1.2870 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.2870 2023/06/05 21:11:41 - mmengine - INFO - Epoch(train) [150][1540/2569] lr: 4.0000e-04 eta: 0:04:34 time: 0.2638 data_time: 0.0076 memory: 5828 grad_norm: 5.8917 loss: 1.7758 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.7758 2023/06/05 21:11:46 - mmengine - INFO - Epoch(train) [150][1560/2569] lr: 4.0000e-04 eta: 0:04:29 time: 0.2757 data_time: 0.0071 memory: 5828 grad_norm: 5.9860 loss: 1.5171 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.5171 2023/06/05 21:11:51 - mmengine - INFO - Epoch(train) [150][1580/2569] lr: 4.0000e-04 eta: 0:04:23 time: 0.2699 data_time: 0.0076 memory: 5828 grad_norm: 6.0290 loss: 1.7778 top1_acc: 0.5000 top5_acc: 0.5000 loss_cls: 1.7778 2023/06/05 21:11:57 - mmengine - INFO - Epoch(train) [150][1600/2569] lr: 4.0000e-04 eta: 0:04:18 time: 0.2685 data_time: 0.0076 memory: 5828 grad_norm: 5.9701 loss: 1.4702 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4702 2023/06/05 21:12:02 - mmengine - INFO - Epoch(train) [150][1620/2569] lr: 4.0000e-04 eta: 0:04:13 time: 0.2719 data_time: 0.0072 memory: 5828 grad_norm: 5.9890 loss: 1.3957 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.3957 2023/06/05 21:12:08 - mmengine - INFO - Epoch(train) [150][1640/2569] lr: 4.0000e-04 eta: 0:04:07 time: 0.2635 data_time: 0.0072 memory: 5828 grad_norm: 6.0074 loss: 1.4371 top1_acc: 0.3750 top5_acc: 0.8750 loss_cls: 1.4371 2023/06/05 21:12:13 - mmengine - INFO - Epoch(train) [150][1660/2569] lr: 4.0000e-04 eta: 0:04:02 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 6.0820 loss: 1.5586 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.5586 2023/06/05 21:12:18 - mmengine - INFO - Epoch(train) [150][1680/2569] lr: 4.0000e-04 eta: 0:03:57 time: 0.2728 data_time: 0.0075 memory: 5828 grad_norm: 5.9100 loss: 1.7937 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.7937 2023/06/05 21:12:24 - mmengine - INFO - Epoch(train) [150][1700/2569] lr: 4.0000e-04 eta: 0:03:51 time: 0.2622 data_time: 0.0081 memory: 5828 grad_norm: 5.9499 loss: 1.6803 top1_acc: 0.5000 top5_acc: 0.7500 loss_cls: 1.6803 2023/06/05 21:12:30 - mmengine - INFO - Epoch(train) [150][1720/2569] lr: 4.0000e-04 eta: 0:03:46 time: 0.2926 data_time: 0.0080 memory: 5828 grad_norm: 5.8929 loss: 1.4078 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4078 2023/06/05 21:12:35 - mmengine - INFO - Epoch(train) [150][1740/2569] lr: 4.0000e-04 eta: 0:03:41 time: 0.2734 data_time: 0.0076 memory: 5828 grad_norm: 6.0398 loss: 1.4209 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4209 2023/06/05 21:12:40 - mmengine - INFO - Epoch(train) [150][1760/2569] lr: 4.0000e-04 eta: 0:03:35 time: 0.2659 data_time: 0.0074 memory: 5828 grad_norm: 5.9924 loss: 1.3254 top1_acc: 1.0000 top5_acc: 1.0000 loss_cls: 1.3254 2023/06/05 21:12:46 - mmengine - INFO - Epoch(train) [150][1780/2569] lr: 4.0000e-04 eta: 0:03:30 time: 0.2630 data_time: 0.0078 memory: 5828 grad_norm: 5.9071 loss: 1.6221 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6221 2023/06/05 21:12:51 - mmengine - INFO - Epoch(train) [150][1800/2569] lr: 4.0000e-04 eta: 0:03:25 time: 0.2629 data_time: 0.0083 memory: 5828 grad_norm: 6.0139 loss: 1.5626 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.5626 2023/06/05 21:12:56 - mmengine - INFO - Epoch(train) [150][1820/2569] lr: 4.0000e-04 eta: 0:03:19 time: 0.2728 data_time: 0.0073 memory: 5828 grad_norm: 6.0629 loss: 1.5693 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.5693 2023/06/05 21:13:02 - mmengine - INFO - Epoch(train) [150][1840/2569] lr: 4.0000e-04 eta: 0:03:14 time: 0.2710 data_time: 0.0076 memory: 5828 grad_norm: 5.9980 loss: 1.4112 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4112 2023/06/05 21:13:07 - mmengine - INFO - Epoch(train) [150][1860/2569] lr: 4.0000e-04 eta: 0:03:09 time: 0.2780 data_time: 0.0074 memory: 5828 grad_norm: 5.9433 loss: 1.6295 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.6295 2023/06/05 21:13:13 - mmengine - INFO - Epoch(train) [150][1880/2569] lr: 4.0000e-04 eta: 0:03:03 time: 0.2646 data_time: 0.0072 memory: 5828 grad_norm: 6.0000 loss: 1.8469 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.8469 2023/06/05 21:13:18 - mmengine - INFO - Epoch(train) [150][1900/2569] lr: 4.0000e-04 eta: 0:02:58 time: 0.2711 data_time: 0.0076 memory: 5828 grad_norm: 6.0893 loss: 1.6580 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6580 2023/06/05 21:13:24 - mmengine - INFO - Epoch(train) [150][1920/2569] lr: 4.0000e-04 eta: 0:02:53 time: 0.2723 data_time: 0.0073 memory: 5828 grad_norm: 5.9950 loss: 1.5023 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.5023 2023/06/05 21:13:29 - mmengine - INFO - Epoch(train) [150][1940/2569] lr: 4.0000e-04 eta: 0:02:47 time: 0.2641 data_time: 0.0071 memory: 5828 grad_norm: 5.9571 loss: 1.6922 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.6922 2023/06/05 21:13:34 - mmengine - INFO - Epoch(train) [150][1960/2569] lr: 4.0000e-04 eta: 0:02:42 time: 0.2781 data_time: 0.0075 memory: 5828 grad_norm: 5.8924 loss: 1.6617 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.6617 2023/06/05 21:13:40 - mmengine - INFO - Epoch(train) [150][1980/2569] lr: 4.0000e-04 eta: 0:02:37 time: 0.2619 data_time: 0.0075 memory: 5828 grad_norm: 5.9402 loss: 1.6587 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.6587 2023/06/05 21:13:45 - mmengine - INFO - Epoch(train) [150][2000/2569] lr: 4.0000e-04 eta: 0:02:31 time: 0.2711 data_time: 0.0074 memory: 5828 grad_norm: 5.9806 loss: 1.3801 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3801 2023/06/05 21:13:50 - mmengine - INFO - Epoch(train) [150][2020/2569] lr: 4.0000e-04 eta: 0:02:26 time: 0.2632 data_time: 0.0072 memory: 5828 grad_norm: 6.0664 loss: 1.4679 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.4679 2023/06/05 21:13:56 - mmengine - INFO - Epoch(train) [150][2040/2569] lr: 4.0000e-04 eta: 0:02:21 time: 0.2737 data_time: 0.0073 memory: 5828 grad_norm: 6.0631 loss: 1.3711 top1_acc: 0.6250 top5_acc: 0.6250 loss_cls: 1.3711 2023/06/05 21:14:01 - mmengine - INFO - Epoch(train) [150][2060/2569] lr: 4.0000e-04 eta: 0:02:15 time: 0.2718 data_time: 0.0073 memory: 5828 grad_norm: 5.9987 loss: 1.6342 top1_acc: 0.5000 top5_acc: 0.6250 loss_cls: 1.6342 2023/06/05 21:14:07 - mmengine - INFO - Epoch(train) [150][2080/2569] lr: 4.0000e-04 eta: 0:02:10 time: 0.2762 data_time: 0.0074 memory: 5828 grad_norm: 5.9618 loss: 1.7463 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.7463 2023/06/05 21:14:12 - mmengine - INFO - Epoch(train) [150][2100/2569] lr: 4.0000e-04 eta: 0:02:05 time: 0.2683 data_time: 0.0075 memory: 5828 grad_norm: 5.8435 loss: 1.4727 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4727 2023/06/05 21:14:18 - mmengine - INFO - Epoch(train) [150][2120/2569] lr: 4.0000e-04 eta: 0:01:59 time: 0.2722 data_time: 0.0079 memory: 5828 grad_norm: 5.9978 loss: 1.4594 top1_acc: 0.2500 top5_acc: 0.7500 loss_cls: 1.4594 2023/06/05 21:14:23 - mmengine - INFO - Epoch(train) [150][2140/2569] lr: 4.0000e-04 eta: 0:01:54 time: 0.2677 data_time: 0.0074 memory: 5828 grad_norm: 5.8827 loss: 1.5284 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.5284 2023/06/05 21:14:28 - mmengine - INFO - Epoch(train) [150][2160/2569] lr: 4.0000e-04 eta: 0:01:49 time: 0.2625 data_time: 0.0077 memory: 5828 grad_norm: 6.0164 loss: 1.4435 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.4435 2023/06/05 21:14:34 - mmengine - INFO - Epoch(train) [150][2180/2569] lr: 4.0000e-04 eta: 0:01:43 time: 0.2653 data_time: 0.0074 memory: 5828 grad_norm: 5.9499 loss: 1.7627 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.7627 2023/06/05 21:14:39 - mmengine - INFO - Epoch(train) [150][2200/2569] lr: 4.0000e-04 eta: 0:01:38 time: 0.2612 data_time: 0.0074 memory: 5828 grad_norm: 6.0933 loss: 1.6192 top1_acc: 0.1250 top5_acc: 0.5000 loss_cls: 1.6192 2023/06/05 21:14:44 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 21:14:44 - mmengine - INFO - Epoch(train) [150][2220/2569] lr: 4.0000e-04 eta: 0:01:33 time: 0.2779 data_time: 0.0076 memory: 5828 grad_norm: 6.0505 loss: 1.6730 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.6730 2023/06/05 21:14:50 - mmengine - INFO - Epoch(train) [150][2240/2569] lr: 4.0000e-04 eta: 0:01:27 time: 0.2630 data_time: 0.0075 memory: 5828 grad_norm: 5.9552 loss: 1.8444 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.8444 2023/06/05 21:14:55 - mmengine - INFO - Epoch(train) [150][2260/2569] lr: 4.0000e-04 eta: 0:01:22 time: 0.2727 data_time: 0.0073 memory: 5828 grad_norm: 5.9753 loss: 1.4027 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.4027 2023/06/05 21:15:00 - mmengine - INFO - Epoch(train) [150][2280/2569] lr: 4.0000e-04 eta: 0:01:17 time: 0.2628 data_time: 0.0072 memory: 5828 grad_norm: 6.1020 loss: 1.4605 top1_acc: 0.3750 top5_acc: 0.7500 loss_cls: 1.4605 2023/06/05 21:15:06 - mmengine - INFO - Epoch(train) [150][2300/2569] lr: 4.0000e-04 eta: 0:01:11 time: 0.2698 data_time: 0.0073 memory: 5828 grad_norm: 6.0912 loss: 1.2974 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.2974 2023/06/05 21:15:11 - mmengine - INFO - Epoch(train) [150][2320/2569] lr: 4.0000e-04 eta: 0:01:06 time: 0.2659 data_time: 0.0075 memory: 5828 grad_norm: 5.9792 loss: 1.2530 top1_acc: 0.7500 top5_acc: 0.7500 loss_cls: 1.2530 2023/06/05 21:15:17 - mmengine - INFO - Epoch(train) [150][2340/2569] lr: 4.0000e-04 eta: 0:01:01 time: 0.2641 data_time: 0.0075 memory: 5828 grad_norm: 6.0024 loss: 1.4191 top1_acc: 0.8750 top5_acc: 0.8750 loss_cls: 1.4191 2023/06/05 21:15:22 - mmengine - INFO - Epoch(train) [150][2360/2569] lr: 4.0000e-04 eta: 0:00:55 time: 0.2842 data_time: 0.0076 memory: 5828 grad_norm: 5.8731 loss: 1.3769 top1_acc: 0.6250 top5_acc: 0.7500 loss_cls: 1.3769 2023/06/05 21:15:28 - mmengine - INFO - Epoch(train) [150][2380/2569] lr: 4.0000e-04 eta: 0:00:50 time: 0.2666 data_time: 0.0073 memory: 5828 grad_norm: 6.0624 loss: 1.6039 top1_acc: 0.7500 top5_acc: 1.0000 loss_cls: 1.6039 2023/06/05 21:15:33 - mmengine - INFO - Epoch(train) [150][2400/2569] lr: 4.0000e-04 eta: 0:00:45 time: 0.2853 data_time: 0.0073 memory: 5828 grad_norm: 6.0433 loss: 1.3833 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.3833 2023/06/05 21:15:39 - mmengine - INFO - Epoch(train) [150][2420/2569] lr: 4.0000e-04 eta: 0:00:39 time: 0.2694 data_time: 0.0078 memory: 5828 grad_norm: 5.8697 loss: 1.4868 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.4868 2023/06/05 21:15:44 - mmengine - INFO - Epoch(train) [150][2440/2569] lr: 4.0000e-04 eta: 0:00:34 time: 0.2691 data_time: 0.0074 memory: 5828 grad_norm: 5.9280 loss: 1.3186 top1_acc: 0.7500 top5_acc: 0.8750 loss_cls: 1.3186 2023/06/05 21:15:49 - mmengine - INFO - Epoch(train) [150][2460/2569] lr: 4.0000e-04 eta: 0:00:29 time: 0.2676 data_time: 0.0076 memory: 5828 grad_norm: 6.0672 loss: 1.6328 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6328 2023/06/05 21:15:55 - mmengine - INFO - Epoch(train) [150][2480/2569] lr: 4.0000e-04 eta: 0:00:23 time: 0.2622 data_time: 0.0077 memory: 5828 grad_norm: 5.9631 loss: 1.6509 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.6509 2023/06/05 21:16:00 - mmengine - INFO - Epoch(train) [150][2500/2569] lr: 4.0000e-04 eta: 0:00:18 time: 0.2746 data_time: 0.0075 memory: 5828 grad_norm: 5.9747 loss: 1.5984 top1_acc: 0.3750 top5_acc: 0.5000 loss_cls: 1.5984 2023/06/05 21:16:06 - mmengine - INFO - Epoch(train) [150][2520/2569] lr: 4.0000e-04 eta: 0:00:13 time: 0.2667 data_time: 0.0075 memory: 5828 grad_norm: 6.0761 loss: 1.4093 top1_acc: 0.8750 top5_acc: 1.0000 loss_cls: 1.4093 2023/06/05 21:16:11 - mmengine - INFO - Epoch(train) [150][2540/2569] lr: 4.0000e-04 eta: 0:00:07 time: 0.2696 data_time: 0.0077 memory: 5828 grad_norm: 6.0840 loss: 1.4848 top1_acc: 0.5000 top5_acc: 0.8750 loss_cls: 1.4848 2023/06/05 21:16:16 - mmengine - INFO - Epoch(train) [150][2560/2569] lr: 4.0000e-04 eta: 0:00:02 time: 0.2669 data_time: 0.0078 memory: 5828 grad_norm: 5.9133 loss: 1.6000 top1_acc: 0.6250 top5_acc: 0.8750 loss_cls: 1.6000 2023/06/05 21:16:19 - mmengine - INFO - Exp name: slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb_20230604_161654 2023/06/05 21:16:19 - mmengine - INFO - Epoch(train) [150][2569/2569] lr: 4.0000e-04 eta: 0:00:00 time: 0.2612 data_time: 0.0074 memory: 5828 grad_norm: 6.0644 loss: 1.4483 top1_acc: 0.6667 top5_acc: 0.8333 loss_cls: 1.4483 2023/06/05 21:16:19 - mmengine - INFO - Saving checkpoint at 150 epochs 2023/06/05 21:16:25 - mmengine - INFO - Epoch(val) [150][ 20/260] eta: 0:00:42 time: 0.1790 data_time: 0.1198 memory: 1238 2023/06/05 21:16:28 - mmengine - INFO - Epoch(val) [150][ 40/260] eta: 0:00:35 time: 0.1449 data_time: 0.0861 memory: 1238 2023/06/05 21:16:31 - mmengine - INFO - Epoch(val) [150][ 60/260] eta: 0:00:31 time: 0.1513 data_time: 0.0922 memory: 1238 2023/06/05 21:16:33 - mmengine - INFO - Epoch(val) [150][ 80/260] eta: 0:00:27 time: 0.1287 data_time: 0.0698 memory: 1238 2023/06/05 21:16:36 - mmengine - INFO - Epoch(val) [150][100/260] eta: 0:00:24 time: 0.1490 data_time: 0.0904 memory: 1238 2023/06/05 21:16:39 - mmengine - INFO - Epoch(val) [150][120/260] eta: 0:00:20 time: 0.1333 data_time: 0.0746 memory: 1238 2023/06/05 21:16:42 - mmengine - INFO - Epoch(val) [150][140/260] eta: 0:00:17 time: 0.1321 data_time: 0.0736 memory: 1238 2023/06/05 21:16:45 - mmengine - INFO - Epoch(val) [150][160/260] eta: 0:00:14 time: 0.1490 data_time: 0.0905 memory: 1238 2023/06/05 21:16:48 - mmengine - INFO - Epoch(val) [150][180/260] eta: 0:00:11 time: 0.1501 data_time: 0.0917 memory: 1238 2023/06/05 21:16:50 - mmengine - INFO - Epoch(val) [150][200/260] eta: 0:00:08 time: 0.1218 data_time: 0.0631 memory: 1238 2023/06/05 21:16:53 - mmengine - INFO - Epoch(val) [150][220/260] eta: 0:00:05 time: 0.1486 data_time: 0.0901 memory: 1238 2023/06/05 21:16:55 - mmengine - INFO - Epoch(val) [150][240/260] eta: 0:00:02 time: 0.1135 data_time: 0.0562 memory: 1238 2023/06/05 21:16:57 - mmengine - INFO - Epoch(val) [150][260/260] eta: 0:00:00 time: 0.1066 data_time: 0.0507 memory: 1238 2023/06/05 21:17:04 - mmengine - INFO - Epoch(val) [150][260/260] acc/top1: 0.6435 acc/top5: 0.8458 acc/mean1: 0.6369 data_time: 0.0804 time: 0.1387 2023/06/05 21:17:05 - mmengine - INFO - The previous best checkpoint /mnt/data/mmact/lilin/Repos/mmaction2/work_dirs/slowonly_imagenet-pretrained-r50_16xb16-8x8x1-steplr-150e_kinetics710-rgb/best_acc_top1_epoch_145.pth is removed 2023/06/05 21:17:06 - mmengine - INFO - The best checkpoint with 0.6435 acc/top1 at 150 epoch is saved to best_acc_top1_epoch_150.pth.